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1. A method for application interfacing a native physics engine, comprising: embedding access to the native physics engine within a WebCore of a browser engine by providing JavaScript bindings within the WebCore for supporting a plurality of application classes from the browser engine to the native physics engine and to a JavaScript engine; triggering, by the JavaScript engine, a function that calls into a corresponding JavaScript binding function of the WebCore through a table, the corresponding JavaScript binding function calling a wrapper layer function in the JavaScript binding that calls a native function from the native physics engine; and providing, by the WebCore of the browser engine, transparent access from at least one web application to the native physics engine through the JavaScript bindings. | 1. A method for application interfacing a native physics engine, comprising: embedding access to the native physics engine within a WebCore of a browser engine by providing JavaScript bindings within the WebCore for supporting a plurality of application classes from the browser engine to the native physics engine and to a JavaScript engine; triggering, by the JavaScript engine, a function that calls into a corresponding JavaScript binding function of the WebCore through a table, the corresponding JavaScript binding function calling a wrapper layer function in the JavaScript binding that calls a native function from the native physics engine; and providing, by the WebCore of the browser engine, transparent access from at least one web application to the native physics engine through the JavaScript bindings. 3. The method of claim 1 , wherein the JavaScript bindings are generated using an interface definition language (IDL) generator that supports constructor-type static read-only attributes. | 0.569723 |
11. A computer-implemented method for managing data model evaluation, the computer-implemented method comprising: receiving a domain-specific language database query expression of a domain-specific language of a data model, the domain-specific language database query expression to be evaluated by an application, the application having been written in a first programming language, wherein the database query expression comprises a formula; providing predefined code in a general-purpose imperative programming language mapped to model expressions in the domain-specific language; dynamically generating new code in the general-purpose imperative programming language by translating the domain-specific language database query expression into the general-purpose imperative programming language based on one or more portions of the predefined code, the new code being compilable; compiling the generated new code, using an optimizing compiler, into a compilation of the general-purpose imperative programming language; making the compilation of the general-purpose imperative programming language available to the application written in the first programming language such that the application evaluates the domain-specific language database query expression by using the compilation of the general-purpose imperative programming language; and executing the compilation of the general-purpose imperative programming language by a processor. | 11. A computer-implemented method for managing data model evaluation, the computer-implemented method comprising: receiving a domain-specific language database query expression of a domain-specific language of a data model, the domain-specific language database query expression to be evaluated by an application, the application having been written in a first programming language, wherein the database query expression comprises a formula; providing predefined code in a general-purpose imperative programming language mapped to model expressions in the domain-specific language; dynamically generating new code in the general-purpose imperative programming language by translating the domain-specific language database query expression into the general-purpose imperative programming language based on one or more portions of the predefined code, the new code being compilable; compiling the generated new code, using an optimizing compiler, into a compilation of the general-purpose imperative programming language; making the compilation of the general-purpose imperative programming language available to the application written in the first programming language such that the application evaluates the domain-specific language database query expression by using the compilation of the general-purpose imperative programming language; and executing the compilation of the general-purpose imperative programming language by a processor. 22. The method of claim 11 , wherein the first programming language is compilable into bytecode and the general-purpose imperative programming language is compilable into machine code. | 0.675926 |
1. A consultative system containing an advice and having a projection device, for helping a user to improve one's interactive ability by analyzing a particular person's behaviors in a simulation environment, said particular person being selected from a group including said user, a person different from said user, and a virtual person, said system comprising: building a plurality of virtual events for said advice, said plurality of virtual events involving interactions among two or more persons; projecting said plurality of virtual events by said projection device; capturing a response from said particular person; analyzing said response according to said advice to produce a report; and providing said report to said user, whereby said system guides said user to observe and examine said particular person's behaviors in a simulation scenario so that said user can learn effectively from both one's own behaviors and other person's behaviors and is able to apply said advice more naturally in a real life. | 1. A consultative system containing an advice and having a projection device, for helping a user to improve one's interactive ability by analyzing a particular person's behaviors in a simulation environment, said particular person being selected from a group including said user, a person different from said user, and a virtual person, said system comprising: building a plurality of virtual events for said advice, said plurality of virtual events involving interactions among two or more persons; projecting said plurality of virtual events by said projection device; capturing a response from said particular person; analyzing said response according to said advice to produce a report; and providing said report to said user, whereby said system guides said user to observe and examine said particular person's behaviors in a simulation scenario so that said user can learn effectively from both one's own behaviors and other person's behaviors and is able to apply said advice more naturally in a real life. 2. The system in claim 1 , said plurality of virtual events involving a plurality of activities produced by a plurality of virtual human objects, said advice associating an example in a form selected from a group including text descriptions, image descriptions, and a recorded plurality of virtual events, said system further comprising means for controlling projecting speed and means for controlling projecting direction; in case said example is in form of text descriptions, wherein said building a plurality of virtual events for said advice comprises means for helping said user visualize said example, means for building a virtual human object, means for instantiating a virtual human object, means for devising a virtual event schedule according to said text descriptions, and means for constructing said plurality of virtual events; in case said example is in form of image descriptions, wherein said building a plurality of virtual events for said advice comprises means for modifying image descriptions, means for emphasizing important issues, means for removing trivial portions, means for inserting assistant actions, means for building a virtual human object, and means for instantiating a virtual human object; in case said example is in form of a recorded plurality of virtual events, wherein said building a plurality of virtual events for said advice comprises means for modifying a particular virtual human object, means for modifying a particular virtual event, and means for providing comments for a particular virtual event. | 0.783109 |
13. A non-transitory computer-readable medium having instructions stored thereon, which, when executed by at least one processor, causes the processor to perform operations comprising: on a first device, receiving information from a plurality of second devices located within a communication range of the first device, the information comprising a plurality of identifiers, each identifier associated with one of the second devices; creating a digital file on the first device using a digital recording device comprised within the first device, wherein the digital file comprises at least one of audio content, image content or video content; providing, on the first device and after creating the digital file, a plurality of user interface items for display in association with at least a portion of the digital file, each user interface item having a label and corresponding to one of the second devices, each label corresponding to an identifier of the respective second device and including an identifier of a user of the second device; receiving a selection of one of the user interface items; and associating the label of the selected user interface item with the digital file, including storing the label as metadata of the digital file or storing the digital file in a file directory named using the label. | 13. A non-transitory computer-readable medium having instructions stored thereon, which, when executed by at least one processor, causes the processor to perform operations comprising: on a first device, receiving information from a plurality of second devices located within a communication range of the first device, the information comprising a plurality of identifiers, each identifier associated with one of the second devices; creating a digital file on the first device using a digital recording device comprised within the first device, wherein the digital file comprises at least one of audio content, image content or video content; providing, on the first device and after creating the digital file, a plurality of user interface items for display in association with at least a portion of the digital file, each user interface item having a label and corresponding to one of the second devices, each label corresponding to an identifier of the respective second device and including an identifier of a user of the second device; receiving a selection of one of the user interface items; and associating the label of the selected user interface item with the digital file, including storing the label as metadata of the digital file or storing the digital file in a file directory named using the label. 24. The computer-readable medium of claim 13 , the operations further comprising sharing a device list among a selected group of users, the sharing including sending the device list to the devices whose identifiers are contained in the device list. | 0.575488 |
7. The handheld electronic device of claim 6 , wherein the plurality of objects further comprise a plurality of frequency objects, at least some of the frequency objects each having a frequency value, at least some of the language objects each having a frequency object associated therewith, and wherein the operations further comprise outputting the at least one of: at least some of the first linguistic results, and at least some of the second linguistic results in order of decreasing frequency value. | 7. The handheld electronic device of claim 6 , wherein the plurality of objects further comprise a plurality of frequency objects, at least some of the frequency objects each having a frequency value, at least some of the language objects each having a frequency object associated therewith, and wherein the operations further comprise outputting the at least one of: at least some of the first linguistic results, and at least some of the second linguistic results in order of decreasing frequency value. 8. The handheld electronic device of claim 7 , wherein the operations further comprise comparing a first frequency value of at least one of the first linguistic results with a second frequency value of at least one of the second linguistic results. | 0.906601 |
11. An article of manufacture comprising a non-transitory computer readable storage medium for storing computer readable program code which, when executed, causes a computer to: determine a vicinity from which speech input to a speech recognition system originates, wherein the determination of the vicinity comprises an estimation of a sound direction of a source of the speech input based on a signal processing method; obtain non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein the obtaining of the non-acoustic data comprises program code that causes the computer to capture visual data of the vicinity of the speech input; indenify a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein the identification of the subject speaker comprises program code that causes the computer to: segment one or more faces from the captured visual data; detect mouth motion on the one or more faces, wherein the detection of the mouth motion comprises an application of temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and select a face corresponding to the subject speaker from the one or more faces in response to a determination that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extract one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyze the one or more non-acoustic attributes, and assign at least one demographic to the subject speaker based on the analysis; select at least one model for use by the speech recognition system based on the demographic assigned to the subject speaker; adjust the speech recognition system using the at least one selected model; and process the speech input using the adjusted speech recognition system. | 11. An article of manufacture comprising a non-transitory computer readable storage medium for storing computer readable program code which, when executed, causes a computer to: determine a vicinity from which speech input to a speech recognition system originates, wherein the determination of the vicinity comprises an estimation of a sound direction of a source of the speech input based on a signal processing method; obtain non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein the obtaining of the non-acoustic data comprises program code that causes the computer to capture visual data of the vicinity of the speech input; indenify a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein the identification of the subject speaker comprises program code that causes the computer to: segment one or more faces from the captured visual data; detect mouth motion on the one or more faces, wherein the detection of the mouth motion comprises an application of temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and select a face corresponding to the subject speaker from the one or more faces in response to a determination that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extract one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyze the one or more non-acoustic attributes, and assign at least one demographic to the subject speaker based on the analysis; select at least one model for use by the speech recognition system based on the demographic assigned to the subject speaker; adjust the speech recognition system using the at least one selected model; and process the speech input using the adjusted speech recognition system. 16. The article of claim 11 , wherein the at least one model comprises at least one of an acoustic model and a language model. | 0.558101 |
13. A storage medium for storing a structured document processing program which causes a computer to execute a structured document processing method, said method comprising the steps of: inputting a first structured document including a first element, and first designation information for designating a location in the first structured document at which the first element is included, a second structured document including a second element, and second designation information for designating a location in the second structured document at which no element is included into which the first element is to be inserted; selecting the first element in the first structured document in accordance with the first designation information designating the location in the first structured document at which the first element is included; and inserting the first element selected in the selecting step into the second structured document at the location designated by the second designation information for designating the location into which the first element is to be inserted. | 13. A storage medium for storing a structured document processing program which causes a computer to execute a structured document processing method, said method comprising the steps of: inputting a first structured document including a first element, and first designation information for designating a location in the first structured document at which the first element is included, a second structured document including a second element, and second designation information for designating a location in the second structured document at which no element is included into which the first element is to be inserted; selecting the first element in the first structured document in accordance with the first designation information designating the location in the first structured document at which the first element is included; and inserting the first element selected in the selecting step into the second structured document at the location designated by the second designation information for designating the location into which the first element is to be inserted. 18. The medium according to claim 13 , wherein the selecting step includes a step of selecting the first element in the first structured document in accordance with a plurality of element names included in the first designation information and an order of element names. | 0.589991 |
6. A computer program product comprising: a computer readable storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer, perform a method for advanced searching of a service registry for a service description that most closely matches a service name provided by a user, said method comprising: said processor receiving the service name, wherein the SOA service registry system comprises the service registry, a name parser, a dictionary, and a name composer, and wherein the service registry comprises at least one service description searchable by a respectively associated service name; said processor determining that the service name does not have the service description that is an exact match to the received service name in the service registry; said processor generating a ranked alternative service name list by use of the name parser, the dictionary, and the name composer, wherein the ranked alternative service name list comprises at least one alternative service name and a respective rank of each alternative service name of said at least one alternative service name, wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining that the service description matches the highest ranked alternative service name in the alternative service name list by searching the service registry with said at least one alternative service name in a descending order of the respective ranks of said at least one alternative service name; and said processor communicating the service description matching the highest ranked alternative service name to the user. | 6. A computer program product comprising: a computer readable storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer, perform a method for advanced searching of a service registry for a service description that most closely matches a service name provided by a user, said method comprising: said processor receiving the service name, wherein the SOA service registry system comprises the service registry, a name parser, a dictionary, and a name composer, and wherein the service registry comprises at least one service description searchable by a respectively associated service name; said processor determining that the service name does not have the service description that is an exact match to the received service name in the service registry; said processor generating a ranked alternative service name list by use of the name parser, the dictionary, and the name composer, wherein the ranked alternative service name list comprises at least one alternative service name and a respective rank of each alternative service name of said at least one alternative service name, wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining that the service description matches the highest ranked alternative service name in the alternative service name list by searching the service registry with said at least one alternative service name in a descending order of the respective ranks of said at least one alternative service name; and said processor communicating the service description matching the highest ranked alternative service name to the user. 7. The computer program product of claim 6 , said generating comprising: creating a constituent word list comprising at least one constituent word that is a respective dictionary word appearing in the service name as a result of parsing the service name into a set of dictionary words by the name parser; associating a respective weight to each constituent word of said at least one constituent word, wherein said respective weight associated with said each constituent word is predefined by the SOA service registry system; producing a respective synonym list for said each constituent word as a result of running the dictionary, the respective synonym list comprising at least one synonym of said each constituent word as located in the dictionary; associating a respective weight to each synonym in the respective synonym list for said each constituent word, wherein said respective weight associated with said each synonym is predefined by the SOA service registry system; composing at least one alternative service name by combining said at least one constituent word from the constituent word list and said at least one synonym from the respective synonym list pursuant to a sequence in the service name by use of the name composer; calculating a respective rank for said at least one alternative service name by adding the respective weights of all words employed in each alternative service name from said composing; rendering the ranked alternative service name list by associating the respective rank with said each alternative service name. | 0.521343 |
1. A computerized adaptive method for improving a users audible discrimination, the method comprising: a) displaying a plurality of graphical images, the graphical images associated with acoustic events that are modified by stretching in the time domain; b) associating in pairs the plurality of graphical images with particular modified acoustic events such that two different graphical images are associated with a particular modified acoustic event; c) upon selection of any of the plurality of graphical images, presenting its associated modified acoustic event; and d) requiring the user to discriminate between the modified acoustic events by sequentially selecting the two different graphical images from among the plurality of graphical images, that are associated with the particular modified acoustic event. | 1. A computerized adaptive method for improving a users audible discrimination, the method comprising: a) displaying a plurality of graphical images, the graphical images associated with acoustic events that are modified by stretching in the time domain; b) associating in pairs the plurality of graphical images with particular modified acoustic events such that two different graphical images are associated with a particular modified acoustic event; c) upon selection of any of the plurality of graphical images, presenting its associated modified acoustic event; and d) requiring the user to discriminate between the modified acoustic events by sequentially selecting the two different graphical images from among the plurality of graphical images, that are associated with the particular modified acoustic event. 4. The computerized adaptive method as recited in claim 1 wherein the modified acoustic events are short duration acoustic events that are stretched in the time domain only, while maintaining frequencies associated with unstretched acoustic events. | 0.530715 |
1. A computer implemented method for automatically determining a role of a user within an organization based on classification of applications and content, the method comprising the steps, executed by at least one processor, of: identifying applications and files installed on a user's computer; filtering out identified applications and identified files that are not indicative of the role of the user within the organization; functionally classifying non-filtered out identified applications and files according to associated roles within the organization, based on predetermined functional classification information; functionally classifying at least one specific identified type of file installed on the user's computer as being indicative of a specific role of the user within the organization; determining the role of the user within the organization based on at least the functional classification of the non-filtered out identified applications and files; and utilizing the functional classification of the at least one file based on the specific identified file type in the determining of the role of the user within the organization. | 1. A computer implemented method for automatically determining a role of a user within an organization based on classification of applications and content, the method comprising the steps, executed by at least one processor, of: identifying applications and files installed on a user's computer; filtering out identified applications and identified files that are not indicative of the role of the user within the organization; functionally classifying non-filtered out identified applications and files according to associated roles within the organization, based on predetermined functional classification information; functionally classifying at least one specific identified type of file installed on the user's computer as being indicative of a specific role of the user within the organization; determining the role of the user within the organization based on at least the functional classification of the non-filtered out identified applications and files; and utilizing the functional classification of the at least one file based on the specific identified file type in the determining of the role of the user within the organization. 4. The method of claim 1 further comprising: analyzing content of at least one file installed on the user's computer; functionally classifying the at least one file as being indicative of a specific role of the user within the organization, based on the analyzed content; and utilizing the functional classification of the at least one file based on the analyzed content in the determining of the role of the user within the organization. | 0.634419 |
1. A method of analyzing dialogs, the method comprising: receiving, via a processor, call-logs associated with a plurality of dialogs between a dialog system and users and external information about at least one user; extracting a first portion of turn-by-turn details of dialogs from the call-logs comprising at least a time stamp associated with a turn in the plurality of dialogs; inferring a second portion of the turn-by-turn details unavailable in the call-logs based on the first portion of the turn-by-turn details using a call-flow specification as a guide, the second portion of the turn-by-turn details comprising an interleaved sequence of at least two attributes that characterize a system state and a user response; and generating, from the first portion of the turn-by-turn details, the external information about the user, and the second portion of the turn-by-turn details, an empirical call-flow representation of the dialog. | 1. A method of analyzing dialogs, the method comprising: receiving, via a processor, call-logs associated with a plurality of dialogs between a dialog system and users and external information about at least one user; extracting a first portion of turn-by-turn details of dialogs from the call-logs comprising at least a time stamp associated with a turn in the plurality of dialogs; inferring a second portion of the turn-by-turn details unavailable in the call-logs based on the first portion of the turn-by-turn details using a call-flow specification as a guide, the second portion of the turn-by-turn details comprising an interleaved sequence of at least two attributes that characterize a system state and a user response; and generating, from the first portion of the turn-by-turn details, the external information about the user, and the second portion of the turn-by-turn details, an empirical call-flow representation of the dialog. 8. The method of claim 1 , wherein the plurality of dialogs is between a human and an automated dialog system. | 0.644805 |
5. A barcoded quality indicator according to claim 1 and wherein said quality indicator also comprises a release layer which is adhered to an adhesive back surface of said quality indicator. | 5. A barcoded quality indicator according to claim 1 and wherein said quality indicator also comprises a release layer which is adhered to an adhesive back surface of said quality indicator. 7. A barcoded quality indicator according to claim 5 and wherein said release layer comprises a release tab operable for enabling release of said release layer from said adhesive back surface. | 0.931706 |
1. A computer program product for locating information on a topic within a peer-to-peer network, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to receive, on a first peer computer within the peer-to-peer network, a request to locate a topic; program instructions to determine a second peer computer within the peer-to-peer network to query for the topic; program instructions to query an index of the second peer computer for the topic; responsive to determining the topic exists in the index of the second peer computer, program instructions to receive identification information of participants of an instant messaging conversation corresponding to the topic; program instructions to determine the received identification information originated from a currently unavailable peer computer, wherein the currently unavailable peer computer previously pushed an index with the identification information to the second peer computer; and program instructions to store, on the first peer computer, the identification information of the participants and indexing the stored identification information by the topic. | 1. A computer program product for locating information on a topic within a peer-to-peer network, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to receive, on a first peer computer within the peer-to-peer network, a request to locate a topic; program instructions to determine a second peer computer within the peer-to-peer network to query for the topic; program instructions to query an index of the second peer computer for the topic; responsive to determining the topic exists in the index of the second peer computer, program instructions to receive identification information of participants of an instant messaging conversation corresponding to the topic; program instructions to determine the received identification information originated from a currently unavailable peer computer, wherein the currently unavailable peer computer previously pushed an index with the identification information to the second peer computer; and program instructions to store, on the first peer computer, the identification information of the participants and indexing the stored identification information by the topic. 2. The computer program product of claim 1 , further comprising, stored on the one or more non-transitory computer-readable storage media: program instructions to receive, at the first peer computer, a query from a third peer computer within the peer-to-peer network for a separate topic; program instructions to identify an instant messaging conversation stored on the first peer computer that corresponds to the separate topic; and program instructions to send identification information of participants of the instant messaging conversation that corresponds to the separate topic to the third peer computer. | 0.5235 |
1. A method comprising: receiving at a computing device one or more identifiers and one or more data request types; generating and performing a first data query from at least one source identified by said one or more identifiers and having a data type associated with a first data request type of said one or more data request types; retrieving at least one first result from the at least one source in response to said first data query; generating and performing a second data query derived from said one or more identifiers and from a second data request type of said one or more data request types, wherein said second data request type is of a type different from said first data request type; and, retrieving at least one second result from the at least one source in response to said second data query, wherein said second data query is automatically generated based on said first data query to select said at least one second result having content associated with, but not identified by, said first data query. | 1. A method comprising: receiving at a computing device one or more identifiers and one or more data request types; generating and performing a first data query from at least one source identified by said one or more identifiers and having a data type associated with a first data request type of said one or more data request types; retrieving at least one first result from the at least one source in response to said first data query; generating and performing a second data query derived from said one or more identifiers and from a second data request type of said one or more data request types, wherein said second data request type is of a type different from said first data request type; and, retrieving at least one second result from the at least one source in response to said second data query, wherein said second data query is automatically generated based on said first data query to select said at least one second result having content associated with, but not identified by, said first data query. 18. The method, as set forth in claim 1 , further comprising parsing said one or more identifiers and said one or more data request types from at least one input source, said at least one input source being received from a user interface device from a browser. | 0.844651 |
31. A character processing method applicable to an apparatus which stores parameters to generate a plurality of modified font patterns for all character patterns of a single font, said method comprising the steps of: designating a desired one or more of a plurality of items of modification information for each graphic pattern in order to generate a plurality of graphic patterns, the parameters being based on the designated one or more items of modification information; generating a request for display; displaying a plurality of graphic patterns corresponding to a plurality of modified font patterns each corresponding to the same character of the single font on the basis of the parameters stored in the apparatus in response to said request generating step, wherein the one character pattern of the single font is predetermined; selecting one of the plurality of graphic patterns that correspond to the plurality of modified font patterns for the one character pattern displayed in said displaying step; and controlling said display step such that the one graphic pattern corresponding to the modified font pattern selected in said selecting step is displayed in said displaying step distinguishably from other graphic patterns corresponding to the other modified font patterns. | 31. A character processing method applicable to an apparatus which stores parameters to generate a plurality of modified font patterns for all character patterns of a single font, said method comprising the steps of: designating a desired one or more of a plurality of items of modification information for each graphic pattern in order to generate a plurality of graphic patterns, the parameters being based on the designated one or more items of modification information; generating a request for display; displaying a plurality of graphic patterns corresponding to a plurality of modified font patterns each corresponding to the same character of the single font on the basis of the parameters stored in the apparatus in response to said request generating step, wherein the one character pattern of the single font is predetermined; selecting one of the plurality of graphic patterns that correspond to the plurality of modified font patterns for the one character pattern displayed in said displaying step; and controlling said display step such that the one graphic pattern corresponding to the modified font pattern selected in said selecting step is displayed in said displaying step distinguishably from other graphic patterns corresponding to the other modified font patterns. 32. A character processing method according to claim 31, wherein arbitrary type parameters are registered in said apparatus by a user. | 0.606799 |
1. A computer-implemented method for linking documents that refer to other documents through implicit linkages, the method comprising: identifying a first document, the first document comprising an authoritative comment regarding a second document; establishing an explicit linkage between the first document and the second document based upon the authoritative comment; identifying one or more third documents based upon the existence of a citation relationship between the second document and each of the one or more third documents detecting an implicit relationship between the first document and the one or more third documents by using common information between the second document and the one or more third documents; generating an impact value for each of the one or more third documents by comparing the implicit relationship with the first document to the explicit relationship with the second document, the impact value being an indicator of the implicit relationship between the first document and each of the one or more third documents; linking the first document to the one or more third documents based upon the impact value; and presenting the one or more third documents in response to a query for the first document. | 1. A computer-implemented method for linking documents that refer to other documents through implicit linkages, the method comprising: identifying a first document, the first document comprising an authoritative comment regarding a second document; establishing an explicit linkage between the first document and the second document based upon the authoritative comment; identifying one or more third documents based upon the existence of a citation relationship between the second document and each of the one or more third documents detecting an implicit relationship between the first document and the one or more third documents by using common information between the second document and the one or more third documents; generating an impact value for each of the one or more third documents by comparing the implicit relationship with the first document to the explicit relationship with the second document, the impact value being an indicator of the implicit relationship between the first document and each of the one or more third documents; linking the first document to the one or more third documents based upon the impact value; and presenting the one or more third documents in response to a query for the first document. 5. The computer-implemented method of claim 1 , wherein the impact value relates to a visual effect for displaying a reference between the first document and the one or more third documents. | 0.647601 |
1. A method of optimizing content selection infrastructure, comprising: retrieving, by an entity engine executing on one or more processors of a data processing system, a search query report that includes 1) a plurality of queries corresponding to selected content items of a content campaign, and 2) a performance metric for each of the plurality of queries determined based on a performance of the selected content items of the content campaign; determining, by the entity engine using a database, an entity for each query of the plurality of queries, the entity having a unique identifier indicating a classification based on a domain, a type and a property that establishes a relationship to at least one other entity stored in the database; generating, by a cluster engine executing on the data processing system, using a clustering technique applied to the unique identifier indicating the classification of the entity for each query of the plurality of queries, a first subset of the plurality of queries and a second subset of the plurality of queries, wherein the plurality of queries are separated into the first subset and the second subset based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; generating, by the cluster engine based on the performance metric for each of the plurality of queries, a first performance metric for the first subset and a second performance metric for the second subset, the first performance metric different from the second performance metric; providing, for display via an interface, the first performance metric and the second performance metric; receiving, by the data processing system, based on the first performance metric, a selection of a semantic criterion associated with the first subset generated based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; and updating, by the data processing system, the content campaign to include the semantic criterion. | 1. A method of optimizing content selection infrastructure, comprising: retrieving, by an entity engine executing on one or more processors of a data processing system, a search query report that includes 1) a plurality of queries corresponding to selected content items of a content campaign, and 2) a performance metric for each of the plurality of queries determined based on a performance of the selected content items of the content campaign; determining, by the entity engine using a database, an entity for each query of the plurality of queries, the entity having a unique identifier indicating a classification based on a domain, a type and a property that establishes a relationship to at least one other entity stored in the database; generating, by a cluster engine executing on the data processing system, using a clustering technique applied to the unique identifier indicating the classification of the entity for each query of the plurality of queries, a first subset of the plurality of queries and a second subset of the plurality of queries, wherein the plurality of queries are separated into the first subset and the second subset based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; generating, by the cluster engine based on the performance metric for each of the plurality of queries, a first performance metric for the first subset and a second performance metric for the second subset, the first performance metric different from the second performance metric; providing, for display via an interface, the first performance metric and the second performance metric; receiving, by the data processing system, based on the first performance metric, a selection of a semantic criterion associated with the first subset generated based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; and updating, by the data processing system, the content campaign to include the semantic criterion. 3. The method of claim 1 , wherein at least one of the selected content items was displayed via a computing device that input a query of the plurality of queries. | 0.828782 |
13. The erector of claim 9 further comprising first and second substantially rigid compensators, each compensator having an axis, the first compensator being coupled at one end to one of the arcuate arms and the second compensator being coupled at one end to the other arcuate arm, the other ends of the compensators having substantially semi-circular bends essentially normal to the axes of the compensators forming thereby a planar split ring; and a hollow resilient thimble-shaped probe having an open end, the probe mounted on the split ring, the probe having a plurality of resilient projections at the outer surface of the probe. | 13. The erector of claim 9 further comprising first and second substantially rigid compensators, each compensator having an axis, the first compensator being coupled at one end to one of the arcuate arms and the second compensator being coupled at one end to the other arcuate arm, the other ends of the compensators having substantially semi-circular bends essentially normal to the axes of the compensators forming thereby a planar split ring; and a hollow resilient thimble-shaped probe having an open end, the probe mounted on the split ring, the probe having a plurality of resilient projections at the outer surface of the probe. 14. The erector of claim 13 wherein the probe is mounted at its open end on the split ring, the probe further comprising plug means adapted for providing a water-tight seal at the open end of the probe. | 0.777267 |
11. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive a portion of content comprising a table data structure and text associated with the table data structure; identify at least one of key terms or semantic relationships in the table data structure and the associated text; identify, by the data processing system, insight data points in the table data structure based on the identification of at least one of key terms or semantic relationships in the table data structure and the associated text, wherein the insight data points are data points in the table data structure meeting an insight condition set forth in a predefined insight data point rule; generate, by the data processing system, an insight data structure specifying a field in the table data structure with which the insight data point is associated, an insight condition met by the insight data point, a location in the table data structure corresponding to the insight data point, and a value corresponding to the insight data point; populate fields of an insight statement template with information obtained from the key terms and semantic relationships, based on the insight data structure, to generate an insight statement data structure; and output the insight statement data structure, wherein the insight statement data structure is a natural language statement describing an aspect of the table data structure, wherein the computer readable program further causes the computing device to identify an insight data point in the table data structure at least by: performing a matching operation that matches key terms and semantic relationships in the associated text with key terms and semantic relationships in the table data structure to identify matching portions of the table data structure, wherein the identification of the insight data point and generation of the insight data structure is performed for the matching portions of the table data structure. | 11. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive a portion of content comprising a table data structure and text associated with the table data structure; identify at least one of key terms or semantic relationships in the table data structure and the associated text; identify, by the data processing system, insight data points in the table data structure based on the identification of at least one of key terms or semantic relationships in the table data structure and the associated text, wherein the insight data points are data points in the table data structure meeting an insight condition set forth in a predefined insight data point rule; generate, by the data processing system, an insight data structure specifying a field in the table data structure with which the insight data point is associated, an insight condition met by the insight data point, a location in the table data structure corresponding to the insight data point, and a value corresponding to the insight data point; populate fields of an insight statement template with information obtained from the key terms and semantic relationships, based on the insight data structure, to generate an insight statement data structure; and output the insight statement data structure, wherein the insight statement data structure is a natural language statement describing an aspect of the table data structure, wherein the computer readable program further causes the computing device to identify an insight data point in the table data structure at least by: performing a matching operation that matches key terms and semantic relationships in the associated text with key terms and semantic relationships in the table data structure to identify matching portions of the table data structure, wherein the identification of the insight data point and generation of the insight data structure is performed for the matching portions of the table data structure. 15. The computer program product of claim 11 , wherein the text is one of a table summary text associated with the table data structure or a predetermined amount of text in close proximity to the table data structure in the content. | 0.573616 |
43. A user-interest note derived by using a computer processor to transform a user selected passage of a text into a packed meaning structure which is at least one of: a logical formula in the predicate calculus, a minimal recursion semantic structure, a head-driven phrase structure, and an f-structure; and wherein the user interest note and is based on one or more input indicators of user interest and includes: a condensation transformation expressed as rewrite rules and functions which reduce the selected passage by merging, deleting, and changing elements of the selected passage; a reduced passage text note by removing information from the passage based on the condensation transformation, the user interest, and user interest information; and meaning distortion constraints beyond which the reduced passage text condensation is identified as being distorted after the condensation transformation is applied to the passage, wherein the meaning structure for a passage is created through the use of a stochastic disambiguation model and/or predictive model which assigns higher probabilities to better examples from a training set and assigns lower probabilities to less desirable or less appropriate examples. | 43. A user-interest note derived by using a computer processor to transform a user selected passage of a text into a packed meaning structure which is at least one of: a logical formula in the predicate calculus, a minimal recursion semantic structure, a head-driven phrase structure, and an f-structure; and wherein the user interest note and is based on one or more input indicators of user interest and includes: a condensation transformation expressed as rewrite rules and functions which reduce the selected passage by merging, deleting, and changing elements of the selected passage; a reduced passage text note by removing information from the passage based on the condensation transformation, the user interest, and user interest information; and meaning distortion constraints beyond which the reduced passage text condensation is identified as being distorted after the condensation transformation is applied to the passage, wherein the meaning structure for a passage is created through the use of a stochastic disambiguation model and/or predictive model which assigns higher probabilities to better examples from a training set and assigns lower probabilities to less desirable or less appropriate examples. 48. The note of claim 43 , wherein the passage portion is displayed in at least one of: a window; a dialog box; a pop-up-box and a status area. | 0.58754 |
1. A method for dynamically adjusting speech recognition processing to reduce latency, the method comprising: receiving an audio signal, the audio signal corresponding to an utterance; performing first speech recognition processing on a first portion of the audio signal, the first speech recognition processing involving a first plurality of hypotheses, each of the first plurality having a respective score within a first hypothesis score range; determining a processing value for each frame of the first portion, wherein the processing value corresponds to an amount of processing performed by one or more processors; determining a total number of frames in the first portion; determining, using the processing value, an estimated amount of time to process the first portion; determining that the estimated amount of time is above a time threshold; determining an adjusted hypothesis score range to increase a speed of speech recognition processing in response to the estimated amount of time being above the time threshold; and performing second speech recognition processing on a second portion of the audio signal using, the second speech recognition processing involving a second plurality of hypotheses, each of the first plurality having a respective score within the adjusted hypothesis score range, the second plurality including fewer hypotheses than the first plurality. | 1. A method for dynamically adjusting speech recognition processing to reduce latency, the method comprising: receiving an audio signal, the audio signal corresponding to an utterance; performing first speech recognition processing on a first portion of the audio signal, the first speech recognition processing involving a first plurality of hypotheses, each of the first plurality having a respective score within a first hypothesis score range; determining a processing value for each frame of the first portion, wherein the processing value corresponds to an amount of processing performed by one or more processors; determining a total number of frames in the first portion; determining, using the processing value, an estimated amount of time to process the first portion; determining that the estimated amount of time is above a time threshold; determining an adjusted hypothesis score range to increase a speed of speech recognition processing in response to the estimated amount of time being above the time threshold; and performing second speech recognition processing on a second portion of the audio signal using, the second speech recognition processing involving a second plurality of hypotheses, each of the first plurality having a respective score within the adjusted hypothesis score range, the second plurality including fewer hypotheses than the first plurality. 2. The method of claim 1 , wherein the processing value corresponds to at least one of: a number of active nodes of a speech decoding graph being considered; a number of Gaussian mixture-components scored; a number of nodes of the speech decoding graph traversed; an audio quality metric value of the audio signal; a number of arcs added to a decoding graph; or a number of processor instructions executed. | 0.698026 |
10. A system comprising: a processor configured to perform speech analysis; and a computer-readable storage medium having instructions stored which, when executed by the processor, case the processor to perform operations comprising: receiving speech from a user as part of a dialog between the user and a dialog system; identifying an identity of the user using characteristics of the speech, to yield a user identification; generating a personalized natural language generation model based on a stylistic analysis and the user identification, wherein the stylistic analysis is performed on a literary narrative, and wherein the stylistic analysis identifies connections between a personality independent quotation lattice, personality independent attributes, personality dependent attributes, and speakers within the literary narrative; and applying the personalized natural language generation model while performing, as part of the dialog, one of automatic speech recognition and natural language generation. | 10. A system comprising: a processor configured to perform speech analysis; and a computer-readable storage medium having instructions stored which, when executed by the processor, case the processor to perform operations comprising: receiving speech from a user as part of a dialog between the user and a dialog system; identifying an identity of the user using characteristics of the speech, to yield a user identification; generating a personalized natural language generation model based on a stylistic analysis and the user identification, wherein the stylistic analysis is performed on a literary narrative, and wherein the stylistic analysis identifies connections between a personality independent quotation lattice, personality independent attributes, personality dependent attributes, and speakers within the literary narrative; and applying the personalized natural language generation model while performing, as part of the dialog, one of automatic speech recognition and natural language generation. 13. The system of claim 10 , wherein the stylistic analysis further comprises identifying a semantic difference between quotations associated with distinct demographics of the speakers. | 0.862237 |
2. The method of claim 1, wherein the identifying step comprises: generating an automaton based on the desired information; generating the composite automaton by combining a schema of the database with the automaton; and analyzing the composite automaton to identify broken paths. | 2. The method of claim 1, wherein the identifying step comprises: generating an automaton based on the desired information; generating the composite automaton by combining a schema of the database with the automaton; and analyzing the composite automaton to identify broken paths. 3. The method of claim 2, further comprising selecting portions of the automaton that does not correspond to the broken paths of the composite automaton. | 0.773035 |
11. A platen for an automated teller machine comprising: a generally planar substrate including an upper portion and lower portion, the lower portion sloping at an angle relative to the upper portion, the lower portion having a lower edge having a central edge section extending generally laterally along the lower edge and having at least one end edge section tapering from the central edge toward the upper portion, where the substrate defines a generally longitudinally extending channel between the upper portion and the lower portion, and where the platen further included a retaining arm extending from the substrate to retain a module disposed with the channel. | 11. A platen for an automated teller machine comprising: a generally planar substrate including an upper portion and lower portion, the lower portion sloping at an angle relative to the upper portion, the lower portion having a lower edge having a central edge section extending generally laterally along the lower edge and having at least one end edge section tapering from the central edge toward the upper portion, where the substrate defines a generally longitudinally extending channel between the upper portion and the lower portion, and where the platen further included a retaining arm extending from the substrate to retain a module disposed with the channel. 13. The platen of claim 11 wherein the at least one end edge section includes a flange extending from the at least one end edge section toward a rear face of the platen. | 0.61772 |
8. The method of claim 7 , further comprising generating an adjusted recipe to accomplish the target product output based at least in part on the set of relationships. | 8. The method of claim 7 , further comprising generating an adjusted recipe to accomplish the target product output based at least in part on the set of relationships. 9. The method of claim 8 , further comprising evaluating whether the target product output is fulfilled in response to determining that generation of the adjusted recipe is successful. | 0.898253 |
1. A computer implemented method for matching voice based keywords to keyword indexed search items, the computer implemented method comprising: responsive to receiving a spoken search request from a caller, identifying keywords within the spoken search request; creating a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match; locating keyword indexed search items having at least one of the keywords as an index and an original matching score; weighting the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores; sorting the keyword indexed search items based on the weighted matching scores; and creating a list of the sorted keyword indexed search items. | 1. A computer implemented method for matching voice based keywords to keyword indexed search items, the computer implemented method comprising: responsive to receiving a spoken search request from a caller, identifying keywords within the spoken search request; creating a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match; locating keyword indexed search items having at least one of the keywords as an index and an original matching score; weighting the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores; sorting the keyword indexed search items based on the weighted matching scores; and creating a list of the sorted keyword indexed search items. 7. The computer implemented method of claim 1 , wherein the locating, weighting, sorting, and creating steps are performed by a search engine. | 0.726087 |
17. A method for automated document research, aggregation, and compilation, in a client-server environment, the method comprising: (a) generating, with a server computer, a search interface displayable to a client communicably coupled to the server; (b) searching and sorting, with the server computer in response to instructions received via the search interface, selections of interest within a plurality of source documents; (c) generating, with the server computer, a custom report interface displayable to the client; (d) extracting and aggregating, with the server computer in response to user selection instructions received via the custom report interface, the selections of interest into a customized report configured to simultaneously display a plurality of the selections of interest; (e) enabling, with the server computer in response to user selection instructions, documents in a portable document format to be searched, sorted, extracted and aggregated into the customized report; (f) enabling, with the server computer in response to user selection instructions, documents in a presentation format to be searched, sorted, extracted and aggregated into the customized report; (g) enabling, with the server computer in response to user selection instructions, documents in a spread sheet format to be searched, sorted, extracted and aggregated into the customized report; and (h) storing and indexing, with the server computer, a plurality of source documents in a plurality of native formats including text, portable document, presentation, and spread sheet, while maintaining the original native formats of the stored and indexed source documents, and storing each of the plurality of source documents in a plurality of sub-document portions populated to one or more tables; and (i) generating, with the server computer, a tool interface displayable to the client, the tool interface being configured to link user comments to any of the sub-document portions in response to instructions received from the client; wherein said extracting and aggregating (d) includes extracting and aggregating the sub-document portions of the selections of interest, along with any of the linked user comments, into the customized report while maintaining the original native formats of the selections of interest. | 17. A method for automated document research, aggregation, and compilation, in a client-server environment, the method comprising: (a) generating, with a server computer, a search interface displayable to a client communicably coupled to the server; (b) searching and sorting, with the server computer in response to instructions received via the search interface, selections of interest within a plurality of source documents; (c) generating, with the server computer, a custom report interface displayable to the client; (d) extracting and aggregating, with the server computer in response to user selection instructions received via the custom report interface, the selections of interest into a customized report configured to simultaneously display a plurality of the selections of interest; (e) enabling, with the server computer in response to user selection instructions, documents in a portable document format to be searched, sorted, extracted and aggregated into the customized report; (f) enabling, with the server computer in response to user selection instructions, documents in a presentation format to be searched, sorted, extracted and aggregated into the customized report; (g) enabling, with the server computer in response to user selection instructions, documents in a spread sheet format to be searched, sorted, extracted and aggregated into the customized report; and (h) storing and indexing, with the server computer, a plurality of source documents in a plurality of native formats including text, portable document, presentation, and spread sheet, while maintaining the original native formats of the stored and indexed source documents, and storing each of the plurality of source documents in a plurality of sub-document portions populated to one or more tables; and (i) generating, with the server computer, a tool interface displayable to the client, the tool interface being configured to link user comments to any of the sub-document portions in response to instructions received from the client; wherein said extracting and aggregating (d) includes extracting and aggregating the sub-document portions of the selections of interest, along with any of the linked user comments, into the customized report while maintaining the original native formats of the selections of interest. 19. The method of claim 17 , comprising (h) tracking, with the server computer, versions of the custom report, and outputting, in response to instructions received from the client, a desired version of the custom report. | 0.524882 |
1. A printing device comprising: a user interface configured to display information to users and receive user input from the users; a shared memory; a locked print module configured to: examine PDF print data received by the printing device to determine whether an electronic document contained in the PDF print data is a policy-enabled document, if the electronic document contained in the PDF print data is a policy-enabled document, then cause the PDF print data to be stored at the printing device instead of being processed for printing, and in response to both a successful verification of a user and a request to print the electronic document via the user interface at the printing device, designating the PDF print data as available for processing; a policy client module configured to: retrieve, from the shared memory, a request for security data for the PDF print data, based upon the request, retrieve, from a policy server, the security data for the PDF print data, and store, in the shared memory, the security data for the PDF print data; and a PDF-to-postscript conversion module configured to: retrieve the PDF print data stored at the printing device, generate, based upon the PDF print data, the request for security data for the PDF print data, store the request for the security data for the PDF print data in the shared memory, retrieve, from the shared memory, the security data for the PDF print data, decrypt the PDF print data to generate decrypted PDF print data, and convert the decrypted PDF print data into postscript print data for printing. | 1. A printing device comprising: a user interface configured to display information to users and receive user input from the users; a shared memory; a locked print module configured to: examine PDF print data received by the printing device to determine whether an electronic document contained in the PDF print data is a policy-enabled document, if the electronic document contained in the PDF print data is a policy-enabled document, then cause the PDF print data to be stored at the printing device instead of being processed for printing, and in response to both a successful verification of a user and a request to print the electronic document via the user interface at the printing device, designating the PDF print data as available for processing; a policy client module configured to: retrieve, from the shared memory, a request for security data for the PDF print data, based upon the request, retrieve, from a policy server, the security data for the PDF print data, and store, in the shared memory, the security data for the PDF print data; and a PDF-to-postscript conversion module configured to: retrieve the PDF print data stored at the printing device, generate, based upon the PDF print data, the request for security data for the PDF print data, store the request for the security data for the PDF print data in the shared memory, retrieve, from the shared memory, the security data for the PDF print data, decrypt the PDF print data to generate decrypted PDF print data, and convert the decrypted PDF print data into postscript print data for printing. 7. The printing device as recited in claim 1 , wherein the locked print module is further configured to cause a list of print jobs associated with the user to be displayed on the user interface and select one or more of the print jobs for printing. | 0.620286 |
14. A computerized method for transforming an input text string, the input text string being an ordered set of characters, the method comprising: storing a plurality of tokens in a dictionary data store, wherein each token is associated with a score, and wherein each token is a string of one or more characters; generating a chart parse of the input text string, wherein: the chart parse includes a plurality of entries; each entry includes (i) an indication of a start character of the entry within the input text string and (ii) an indication of an end character of the entry within the input text strings, and generating the chart parse includes, for each position within the input text string, (i) identifying a string of at least one consecutive character in the input text string that begins at that position and matches one of the plurality of tokens and (ii) unless the identified string is a single character matching the start character for another entry in the chart parse, creating an entry corresponding to the identified string; determining a selected partition of the input text string based on the entries of the chart parse, wherein: the selected partition includes an array of tokens such that a concatenation of the array of tokens matches the ordered set of characters of the input text string, each of the array of tokens is selected from the chart parse, a score of the selected partition is based on a sum of, for each token of the array of tokens, the score specified by the dictionary data store, and the selected partition is a minimum score partition; in response to a set of tokens, selecting records from a data store storing application records to form a consideration set of records; assigning a score to each record of the consideration set of records; and responding to the user device with a subset of the consideration set of records, wherein the subset is selected based on the assigned scores, and wherein the subset identifies application states of applications that are relevant to a search query from the user device, wherein the input text string is based on the search query from the user device. | 14. A computerized method for transforming an input text string, the input text string being an ordered set of characters, the method comprising: storing a plurality of tokens in a dictionary data store, wherein each token is associated with a score, and wherein each token is a string of one or more characters; generating a chart parse of the input text string, wherein: the chart parse includes a plurality of entries; each entry includes (i) an indication of a start character of the entry within the input text string and (ii) an indication of an end character of the entry within the input text strings, and generating the chart parse includes, for each position within the input text string, (i) identifying a string of at least one consecutive character in the input text string that begins at that position and matches one of the plurality of tokens and (ii) unless the identified string is a single character matching the start character for another entry in the chart parse, creating an entry corresponding to the identified string; determining a selected partition of the input text string based on the entries of the chart parse, wherein: the selected partition includes an array of tokens such that a concatenation of the array of tokens matches the ordered set of characters of the input text string, each of the array of tokens is selected from the chart parse, a score of the selected partition is based on a sum of, for each token of the array of tokens, the score specified by the dictionary data store, and the selected partition is a minimum score partition; in response to a set of tokens, selecting records from a data store storing application records to form a consideration set of records; assigning a score to each record of the consideration set of records; and responding to the user device with a subset of the consideration set of records, wherein the subset is selected based on the assigned scores, and wherein the subset identifies application states of applications that are relevant to a search query from the user device, wherein the input text string is based on the search query from the user device. 23. The method of claim 14 wherein, for each token in the dictionary data store, the associated score is based on frequency of occurrence of the token. | 0.578377 |
4. The computer based system of claim 3 , wherein the mapping specification contains a data definition language statement with an option specifying the XPath expression. | 4. The computer based system of claim 3 , wherein the mapping specification contains a data definition language statement with an option specifying the XPath expression. 5. The computer based system of claim 4 , wherein the query is a Structured Query Language (SQL) query. | 0.914194 |
1. An information processing apparatus comprising: an algorithm configuring section that configures an amount-of-feature extraction algorithm that determines whether an input signal has a particular characteristic by using a genetic search technique, the algorithm comprising: feature extraction expressions that specify: a type of the input signal, the type indicating a type of data representing the input signal; and operations to be performed on the input signal; and an information estimation expression including a linear combination of the feature extraction expressions, wherein the information estimation expression uses first-order values output from the feature extraction expressions to estimate information indicating features of the input signal; a tradeoff analyzing section that generates pareto optimal solutions by selecting information estimation expressions having maximum values of evaluation indices; an optimum algorithm determining section that selects, from the pareto optimal solutions, an optimum algorithm that matches a requested condition of the evaluation indices; and a storage for storing the algorithm. | 1. An information processing apparatus comprising: an algorithm configuring section that configures an amount-of-feature extraction algorithm that determines whether an input signal has a particular characteristic by using a genetic search technique, the algorithm comprising: feature extraction expressions that specify: a type of the input signal, the type indicating a type of data representing the input signal; and operations to be performed on the input signal; and an information estimation expression including a linear combination of the feature extraction expressions, wherein the information estimation expression uses first-order values output from the feature extraction expressions to estimate information indicating features of the input signal; a tradeoff analyzing section that generates pareto optimal solutions by selecting information estimation expressions having maximum values of evaluation indices; an optimum algorithm determining section that selects, from the pareto optimal solutions, an optimum algorithm that matches a requested condition of the evaluation indices; and a storage for storing the algorithm. 7. The information processing apparatus according to claim 1 , further comprising an evaluation-value calculating section that determines evaluation values of the feature extraction expressions in the information estimation expression, wherein the algorithm configuring section updates the feature extraction expressions in the information estimation expression, on a basis of the determined evaluation values of the feature extraction expressions. | 0.5 |
3. The method of claim 1 , wherein determining, based on the detected one or more accesses, by the one or more computer processors, whether the first data structure is a highly dynamic part of the document object model further comprises: responsive to detecting one or more accesses to the first data structure of the document object model, collecting, by the one or more processors, statistics of the one or more accesses to the first data structure of the document object model; applying, by the one or more computer processors, an optimization policy to the collected statistics, wherein the optimization policy comprises at least one rule to define a data structure as a highly dynamic part; and determining, by the one or more computer processors, the collected statistics meet requirements of the at least one rule of the optimization policy. | 3. The method of claim 1 , wherein determining, based on the detected one or more accesses, by the one or more computer processors, whether the first data structure is a highly dynamic part of the document object model further comprises: responsive to detecting one or more accesses to the first data structure of the document object model, collecting, by the one or more processors, statistics of the one or more accesses to the first data structure of the document object model; applying, by the one or more computer processors, an optimization policy to the collected statistics, wherein the optimization policy comprises at least one rule to define a data structure as a highly dynamic part; and determining, by the one or more computer processors, the collected statistics meet requirements of the at least one rule of the optimization policy. 4. The method of claim 3 , wherein statistics of the one or more accesses to the first data structure of the document object model comprises at least one of access type, access quantity, access paths, and access costs. | 0.930344 |
10. A method comprising: receiving a logical description that references an XML datatype, wherein a database system supports multiple database representations for the XML datatype; receiving one or more Data Manipulation Language (DML) queries that reference the XML datatype; evaluating the one or more DML queries, wherein evaluating one or more DML queries comprises: determining a plurality of database representations that the database system supports for the XML datatype; re-writing the one or more DML queries based on the plurality of database representations; performing a cost analysis of the re-written DML queries; based on the logical description and said evaluating said one or more DML queries, determining a database representation for the XML datatype; wherein said database representation includes one or more base structures that are used to store data for the XML datatype; wherein the methodis performed by one or more computing devices. | 10. A method comprising: receiving a logical description that references an XML datatype, wherein a database system supports multiple database representations for the XML datatype; receiving one or more Data Manipulation Language (DML) queries that reference the XML datatype; evaluating the one or more DML queries, wherein evaluating one or more DML queries comprises: determining a plurality of database representations that the database system supports for the XML datatype; re-writing the one or more DML queries based on the plurality of database representations; performing a cost analysis of the re-written DML queries; based on the logical description and said evaluating said one or more DML queries, determining a database representation for the XML datatype; wherein said database representation includes one or more base structures that are used to store data for the XML datatype; wherein the methodis performed by one or more computing devices. 17. The method of claim 10 , wherein determining the database representation for the XML datatype is further based on a schema for the datatype. | 0.599743 |
1. A computer system for processing Business Intelligence (BI) reports, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the computer program is executable by the processor to perform operations, the operations comprising: using a database, coupled to the computer system, to generate information for consumption by a BI tool by: creating a description of data in one or more data tables, stored in the database, that identifies each column in each of the one or more data tables, wherein each column has multiple values; using the description of the data in the one or more data tables to create a new table, stored in the database, that includes a row for each value of the multiple values for each column in each of the one or more data tables and new columns for statistics about the data in the one or more data tables; generating BI meta information based on the description of the data in the one or more data tables and based on a schema and data of the new table that describes the columns for the statistics; generating a BI report specification that describes how a first BI report is to be rendered based on the schema and the data of the new table by describing a layout of data in the columns in each of the one or more data tables and in the columns for the statistics; deploying the BI meta information and the BI report specification to a BI server for use in generating the first BI report using the BI tool at the BI server; in response to a request for the first BI report, generating the first BI report dynamically with the BI tool at the BI server that dynamically invokes a stored procedure, stored in the database, with one or more parameters and that uses the BI meta information and the BI report specification to provide the statistics about the data in the one or more data tables; and displaying one or more graphs for the first BI report in a second screen; in response to another request for the first BI report after data in the one or more data tables has changed, using the new table to generate new BI meta information and a new BI report specification for use in generating a new BI report dynamically; and displaying one or more graphs for the new BI report in a second screen; in response to a request for a second BI report, using the new table to generate new BI meta information and another new BI report specification for use in generating a second BI report dynamically; and displaying one or more different graphs for the second BI report in a third screen. | 1. A computer system for processing Business Intelligence (BI) reports, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the computer program is executable by the processor to perform operations, the operations comprising: using a database, coupled to the computer system, to generate information for consumption by a BI tool by: creating a description of data in one or more data tables, stored in the database, that identifies each column in each of the one or more data tables, wherein each column has multiple values; using the description of the data in the one or more data tables to create a new table, stored in the database, that includes a row for each value of the multiple values for each column in each of the one or more data tables and new columns for statistics about the data in the one or more data tables; generating BI meta information based on the description of the data in the one or more data tables and based on a schema and data of the new table that describes the columns for the statistics; generating a BI report specification that describes how a first BI report is to be rendered based on the schema and the data of the new table by describing a layout of data in the columns in each of the one or more data tables and in the columns for the statistics; deploying the BI meta information and the BI report specification to a BI server for use in generating the first BI report using the BI tool at the BI server; in response to a request for the first BI report, generating the first BI report dynamically with the BI tool at the BI server that dynamically invokes a stored procedure, stored in the database, with one or more parameters and that uses the BI meta information and the BI report specification to provide the statistics about the data in the one or more data tables; and displaying one or more graphs for the first BI report in a second screen; in response to another request for the first BI report after data in the one or more data tables has changed, using the new table to generate new BI meta information and a new BI report specification for use in generating a new BI report dynamically; and displaying one or more graphs for the new BI report in a second screen; in response to a request for a second BI report, using the new table to generate new BI meta information and another new BI report specification for use in generating a second BI report dynamically; and displaying one or more different graphs for the second BI report in a third screen. 2. The computer system of claim 1 , wherein the operations further comprise: preparing the data in the one or more data tables for data mining. | 0.801508 |
1. A method for analyzing a linguistic input comprising, at a computing device: receiving the linguistic input, the linguistic input comprising at least one word; accessing prestored language data for a language corresponding to the linguistic input; converting the linguistic input into a text possibility based on the received language data; determining a meaning of the text possibility based on the prestored language data, including: selecting a subset of the text possibility, and generating at least one new language construction and/or lexeme based on the subset of the text possibility; generating at least one semantic structure corresponding to the determined meaning; and determining an action to perform based on the generated at least one semantic structure. | 1. A method for analyzing a linguistic input comprising, at a computing device: receiving the linguistic input, the linguistic input comprising at least one word; accessing prestored language data for a language corresponding to the linguistic input; converting the linguistic input into a text possibility based on the received language data; determining a meaning of the text possibility based on the prestored language data, including: selecting a subset of the text possibility, and generating at least one new language construction and/or lexeme based on the subset of the text possibility; generating at least one semantic structure corresponding to the determined meaning; and determining an action to perform based on the generated at least one semantic structure. 5. The method of claim 1 , further comprising: receiving a user input; and converting the user input into the linguistic input, wherein the linguistic input is converted into the text possibility based on at least one of handwriting recognition, speech recognition, optical character recognition, and a gesture based user interface. | 0.638668 |
1. A method comprising: identifying, by one or more computers, an image in a first storage system; determining, by the one or more computers, whether a second storage system includes an entry for the image identifying a region of interest in the image; when the second storage system does not include an entry for the image, identifying, by the one or more computers, a region of interest for the image; performing, by the one or more computers, one or more transforms on the identified region of interest in order to identify one or more aspects of the identified region of interest. | 1. A method comprising: identifying, by one or more computers, an image in a first storage system; determining, by the one or more computers, whether a second storage system includes an entry for the image identifying a region of interest in the image; when the second storage system does not include an entry for the image, identifying, by the one or more computers, a region of interest for the image; performing, by the one or more computers, one or more transforms on the identified region of interest in order to identify one or more aspects of the identified region of interest. 7. The method of claim 1 , wherein identifying the identified region of interest includes: segmenting the image into a plurality of regions of interest, each region of interest of the plurality of regions of interest containing content associated with one or more actual features of a physical object; and extracting at least one physical descriptor from the content for the identified region of interest as a feature vector, each physical descriptor corresponding to one or more actual features of a given physical object in the identified region of interest, wherein the feature vector describes the one or more aspects. | 0.5 |
11. A texture unit of claim 10 wherein said cache is included in a read modify write path associated with said texture unit. | 11. A texture unit of claim 10 wherein said cache is included in a read modify write path associated with said texture unit. 13. A texture unit of claim 11 wherein said atomic OR is performed when evicting textel information out of memory. | 0.911725 |
24. The computer-readable storage medium of claim 23 wherein a relationship is based on a time associated with a scene. | 24. The computer-readable storage medium of claim 23 wherein a relationship is based on a time associated with a scene. 25. The computer-readable storage medium of claim 24 wherein the classification is whether a scene is a commercial. | 0.957418 |
16. A system comprising: a processor and a non-transitory computer-readable medium storing executable computer instructions configured to, when executed by the processor, cause the system to perform steps comprising: accessing a string of characters; producing an intermediate string of characters by replacing a first portion of the string of characters with a first token mapped to a value of the first portion of the string of characters by a first token table; and producing a tokenized string of characters by replacing a second portion of the intermediate string of characters with a second token mapped to a value of the second portion of the intermediate string of characters by a second token table, wherein the second portion of the intermediate string of characters includes at least one character replaced by the first token. | 16. A system comprising: a processor and a non-transitory computer-readable medium storing executable computer instructions configured to, when executed by the processor, cause the system to perform steps comprising: accessing a string of characters; producing an intermediate string of characters by replacing a first portion of the string of characters with a first token mapped to a value of the first portion of the string of characters by a first token table; and producing a tokenized string of characters by replacing a second portion of the intermediate string of characters with a second token mapped to a value of the second portion of the intermediate string of characters by a second token table, wherein the second portion of the intermediate string of characters includes at least one character replaced by the first token. 17. The system of claim 16 , the instructions further configured to perform steps comprising one or more of: modifying the first portion of the string of characters before replacing the first portion, and modifying the second portion of the string of characters before replacing the second portion. | 0.541264 |
5. The system of claim 4 , wherein determining whether the query sequence ends in a word boundary comprises: selecting a subsequent character the subsequent character being a character that is next in sequence to a character that is last in the subsequence of the query sequence; determining that the query sequence ends in a word boundary if the subsequent character is indicative of a word boundary; and determining that the query sequence ends in a non-word boundary if the subsequent character is indicative of a non-word boundary. | 5. The system of claim 4 , wherein determining whether the query sequence ends in a word boundary comprises: selecting a subsequent character the subsequent character being a character that is next in sequence to a character that is last in the subsequence of the query sequence; determining that the query sequence ends in a word boundary if the subsequent character is indicative of a word boundary; and determining that the query sequence ends in a non-word boundary if the subsequent character is indicative of a non-word boundary. 6. The system of claim 5 , wherein: the subsequent character is indicative of a word boundary when the subsequent character is a space character; and the subsequent character is indicative of a non-word boundary when the subsequent character is a letter character. | 0.875975 |
1. A method for providing spectral speech descriptions to be used for synthesis of a speech utterance comprising the steps of receiving at least one spectral envelope input representation corresponding to the speech utterance, where the at least one spectral envelope input representation includes at least one of at least one formant and at least one spectral trough in the form of at least one of a local peak and a local valley in the spectral envelope input representation, extracting from the at least one spectral envelope input representation a rapidly varying input component, where the rapidly varying input component is generated, at least in part, by removing from the at least one spectral envelope input representation a slowly varying input component in the form of a non-constant coarse shape of the at least one spectral envelope input representation and by keeping the fine details of the at least one spectral envelope input representation, where the details contain at least one of a peak or a valley, creating a rapidly varying final component, where the rapidly varying final component is derived from the rapidly varying input component by manipulating at least one of at least one peak and at least one valley, combining the rapidly varying final component with one of the slowly varying input component and the spectral envelope input representation to form a spectral envelope final representation, and providing a spectral speech description output vector to be used for synthesis of a speech utterance, where at least a part of the spectral speech description output vector is derived from the spectral envelope final representation. | 1. A method for providing spectral speech descriptions to be used for synthesis of a speech utterance comprising the steps of receiving at least one spectral envelope input representation corresponding to the speech utterance, where the at least one spectral envelope input representation includes at least one of at least one formant and at least one spectral trough in the form of at least one of a local peak and a local valley in the spectral envelope input representation, extracting from the at least one spectral envelope input representation a rapidly varying input component, where the rapidly varying input component is generated, at least in part, by removing from the at least one spectral envelope input representation a slowly varying input component in the form of a non-constant coarse shape of the at least one spectral envelope input representation and by keeping the fine details of the at least one spectral envelope input representation, where the details contain at least one of a peak or a valley, creating a rapidly varying final component, where the rapidly varying final component is derived from the rapidly varying input component by manipulating at least one of at least one peak and at least one valley, combining the rapidly varying final component with one of the slowly varying input component and the spectral envelope input representation to form a spectral envelope final representation, and providing a spectral speech description output vector to be used for synthesis of a speech utterance, where at least a part of the spectral speech description output vector is derived from the spectral envelope final representation. 7. Method as claimed in claim 1 , where the step of creating a rapidly varying final component includes modifying the rapidly varying input component with a transformation that attenuates the excursion of at least one of a first local minimum and a first local maximum of the rapidly varying input component and preserves the excursion of at least one of a second local maximum and a second local minimum of the rapidly varying component. | 0.532527 |
9. A method as in claim 1 additionally comprising: performing a statistics scan of a subject sequence prior to the step of carrying out the comparison. | 9. A method as in claim 1 additionally comprising: performing a statistics scan of a subject sequence prior to the step of carrying out the comparison. 10. A method as in claim 9 wherein results of the statistics scan are stored as part of the controls table. | 0.933946 |
6. The method of claim 4 , wherein the determining the best candidate solution comprises comparing the spelling errors with all words in a dictionary using the variable cost distance and selecting one or more words having a minimum variable cost distance. | 6. The method of claim 4 , wherein the determining the best candidate solution comprises comparing the spelling errors with all words in a dictionary using the variable cost distance and selecting one or more words having a minimum variable cost distance. 11. The method of claim 6 , further comprising clustering the words in the dictionary to reduce a number of comparisons. | 0.925214 |
17. The computer-readable medium of claim 3 , wherein identifying one or more attributes comprises identifying one or more attributes from a structured data source. | 17. The computer-readable medium of claim 3 , wherein identifying one or more attributes comprises identifying one or more attributes from a structured data source. 27. The computer-readable medium of claim 17 , wherein the structured data source is a social graph. | 0.972002 |
1. A method for compiling a unique sample code for specific web content, comprising: defining at least one sample code template comprising multiple sample code segments to be used for building a sample code for specific web content, said sample code segments at least comprising: a sample owner identifying code segment, and a sample identifying code segment; specifying the content of the sample code segments to be used for building said sample code, wherein the sample owner identifying code segment is specified by an Internet address of an owner of the specific web content; stringing the specified sample code segments to form the sample code; defining a digital path to a digital location via which access can be gained to the specific web content and which is mutually distinctive from the sample code; creating a cross-reference between the sample code generated during the stringing of the specified sample code segments and the digital path defined during the defining of the digital path; and providing the sample code with a time stamp indicating a time dependency of the specific web content. | 1. A method for compiling a unique sample code for specific web content, comprising: defining at least one sample code template comprising multiple sample code segments to be used for building a sample code for specific web content, said sample code segments at least comprising: a sample owner identifying code segment, and a sample identifying code segment; specifying the content of the sample code segments to be used for building said sample code, wherein the sample owner identifying code segment is specified by an Internet address of an owner of the specific web content; stringing the specified sample code segments to form the sample code; defining a digital path to a digital location via which access can be gained to the specific web content and which is mutually distinctive from the sample code; creating a cross-reference between the sample code generated during the stringing of the specified sample code segments and the digital path defined during the defining of the digital path; and providing the sample code with a time stamp indicating a time dependency of the specific web content. 5. The method according to claim 1 , wherein the method comprises converting the sample code into a machine-readable format. | 0.630113 |
39. The knowledge system as claimed in claim 36, wherein said knowledge base includes rules having factors in premises and concluding values for expressions, and said means for probing includes: means for probing the subject system for a value of an expression pertaining to said condition upon which the operation of the knowledge base interpreter is interrupted. means for probing the subject system for factors supporting the value of said expression pertaining to said condition, and means for probing the subject system for the values of factors supporting the values of said expression pertaining to said condition. | 39. The knowledge system as claimed in claim 36, wherein said knowledge base includes rules having factors in premises and concluding values for expressions, and said means for probing includes: means for probing the subject system for a value of an expression pertaining to said condition upon which the operation of the knowledge base interpreter is interrupted. means for probing the subject system for factors supporting the value of said expression pertaining to said condition, and means for probing the subject system for the values of factors supporting the values of said expression pertaining to said condition. 40. The knowledge system as claimed in claim 39, wherein said subset of conditions is indicated by a selected subset of said expressions, and said conditions occur when values are found for the expressions included in said subset of expressions. | 0.850433 |
5. The engine of claim 1 , wherein the medical data comprises biometric data of the patient. | 5. The engine of claim 1 , wherein the medical data comprises biometric data of the patient. 7. The engine of claim 5 , wherein the biometric data includes at least one of the following: a change in a biometric, a pressure point, a perspiration, a body fluid metric, a respiration, a blood pressure, and a perfusion. | 0.909783 |
13. The method of claim 1 further comprising creating a new event that is triggered by the occurrence of the tracked event. | 13. The method of claim 1 further comprising creating a new event that is triggered by the occurrence of the tracked event. 14. The method of claim 13 wherein generating the instructions stored in a computer readable medium comprises generating code for the new event to implement tracking and sending information about occurrences of the tracked event to the collection service. | 0.891892 |
16. The computer storage medium of claim 15 , the operations further comprising: updating a cluster index with information from the summarized cluster. | 16. The computer storage medium of claim 15 , the operations further comprising: updating a cluster index with information from the summarized cluster. 17. The computer storage medium of claim 16 , wherein identifying one or more candidate clusters of observations responsive to the generated query comprises: identifying one or more candidate clusters of observations responsive to the generated query using the cluster index. | 0.913311 |
26. The electronic device of claim 15 , wherein the processing of the respective touch includes processing the respective touch with two or more of the gesture recognizers, including the discrete gesture recognizer and the continuous gesture recognizer. | 26. The electronic device of claim 15 , wherein the processing of the respective touch includes processing the respective touch with two or more of the gesture recognizers, including the discrete gesture recognizer and the continuous gesture recognizer. 27. The electronic device of claim 26 , wherein: the continuous gesture recognizer is configured to, in response to detecting a change in location of a respective touch, enter a gesture changed state in accordance with a determination that the change in location of the respective touch corresponds to the gesture definition corresponding to the continuous gesture recognizer; and the discrete gesture recognizer is configured to, in response to detecting the change in location of the respective touch, enter a gesture recognized state, that is distinct from the gesture changed state, in accordance with a determination that the change in location of the respective touch corresponds to the gesture definition corresponding to the discrete gesture recognizer. | 0.824732 |
10. A first electronic device, comprising: an input unit; a display unit; memory; one or more processors; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions: to listen to a conversation on the first electronic device; to determine whether the conversation satisfies a recommendation criterion; to determine whether at least one suggestion information exists in a database if the conversation satisfies the recommendation criterion, wherein the database comprises a local database associated with a plurality of applications installed in the memory; to display on the first electronic device at least one suggestion option related to the at least one suggestion information on the display unit if the at least one suggestion information exists in the database; to receive a selection signal of a target option selected from the at least one suggestion option; to transmit a query signal by the first electronic device, wherein the query signal is associated with the selected target option; and to monitor a feedback, wherein the feedback is associated with the query signal; wherein if the feedback is positive, to store the information related to the selected target option in at least one corresponding application installed on the first electronic device. | 10. A first electronic device, comprising: an input unit; a display unit; memory; one or more processors; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions: to listen to a conversation on the first electronic device; to determine whether the conversation satisfies a recommendation criterion; to determine whether at least one suggestion information exists in a database if the conversation satisfies the recommendation criterion, wherein the database comprises a local database associated with a plurality of applications installed in the memory; to display on the first electronic device at least one suggestion option related to the at least one suggestion information on the display unit if the at least one suggestion information exists in the database; to receive a selection signal of a target option selected from the at least one suggestion option; to transmit a query signal by the first electronic device, wherein the query signal is associated with the selected target option; and to monitor a feedback, wherein the feedback is associated with the query signal; wherein if the feedback is positive, to store the information related to the selected target option in at least one corresponding application installed on the first electronic device. 11. The first electronic device of claim 10 , wherein the conversion is between the first device and a second device, wherein the database further comprises a local database installed in the second electronic device, and wherein the instruction determines whether at least one suggestion information exists in a database if the conversion satisfies the recommendation criterion comprises: to send a search request. | 0.592762 |
11. The method of claim 1 , wherein the lexicon is implemented, by the computing device, as a trie data structure. | 11. The method of claim 1 , wherein the lexicon is implemented, by the computing device, as a trie data structure. 12. The method of claim 11 , wherein determining the set of candidate strings further comprises: determining, by the computing device, a first word-level token originating at an entry node of the trie; and advancing, by the computing device, the first word-level token to a child node of the trie based at least in part on the characters associated with the first sequence of one or more keys. | 0.931881 |
24. A method for configuring a web crawl, the method comprising the steps of: specifying a starter seed uniform resource locator (URL) and a user-specified web crawl configuration to a configurable web crawler which crawls a web to inspect text of page resources accessible on the web, each page resource identified by a unique URL, the user-specified web crawl configuration comprising user-specified crawling rules specifying crawling behavior, the crawling rules specifying crawling behavior for at least one each of a general crawl behavior, one or more page-specific crawl behavior to be applied during a crawl to one or more identified pages, and one or more element-specific crawl behavior to be applied during a crawl to one or more identified page elements, wherein the received crawling rules define the crawling behavior in terms of whether to record the resource text, whether to follow hyperlinks of the resource, whether to record text description in metadata associated with the page, whether to record keywords identified in the metadata associated with the page, whether to override a page title element, whether to exclude one or more identified resource pages, whether to exclude one or more identified domains; wherein the configurable web crawler is configured to maintain a queue of unprocessed URLs of resources, insert the specified starter seed URL into the queue of unprocessed URLs of resources, retrieve from the queue a next unprocessed URL, retrieve the user-specified web crawl configuration which specifies the crawling rules, and if allowed by the specified general crawl behavior and page-specific crawl behavior of the retrieved crawling rules, fetch the page resource addressed by the retrieved URL and process the fetched page resource on an element-by-element basis by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules, and wherein the default crawl behavior comprises extracting URLs of outbound links and adding the extracted URLs to the queue, storing text to a resource repository for further analysis, the one or more processing units repeating the processing on available unprocessed URLs in the queue. | 24. A method for configuring a web crawl, the method comprising the steps of: specifying a starter seed uniform resource locator (URL) and a user-specified web crawl configuration to a configurable web crawler which crawls a web to inspect text of page resources accessible on the web, each page resource identified by a unique URL, the user-specified web crawl configuration comprising user-specified crawling rules specifying crawling behavior, the crawling rules specifying crawling behavior for at least one each of a general crawl behavior, one or more page-specific crawl behavior to be applied during a crawl to one or more identified pages, and one or more element-specific crawl behavior to be applied during a crawl to one or more identified page elements, wherein the received crawling rules define the crawling behavior in terms of whether to record the resource text, whether to follow hyperlinks of the resource, whether to record text description in metadata associated with the page, whether to record keywords identified in the metadata associated with the page, whether to override a page title element, whether to exclude one or more identified resource pages, whether to exclude one or more identified domains; wherein the configurable web crawler is configured to maintain a queue of unprocessed URLs of resources, insert the specified starter seed URL into the queue of unprocessed URLs of resources, retrieve from the queue a next unprocessed URL, retrieve the user-specified web crawl configuration which specifies the crawling rules, and if allowed by the specified general crawl behavior and page-specific crawl behavior of the retrieved crawling rules, fetch the page resource addressed by the retrieved URL and process the fetched page resource on an element-by-element basis by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules, and wherein the default crawl behavior comprises extracting URLs of outbound links and adding the extracted URLs to the queue, storing text to a resource repository for further analysis, the one or more processing units repeating the processing on available unprocessed URLs in the queue. 25. The method of claim 24 , comprising specifying a crawl depth indicating to the web crawler a maximum number of URL links deep from the starter seed URL to crawl, and wherein the default crawl behavior comprises extracting URLs of outbound links and adding the extracted URLs to the queue so long as the specified crawl depth has not been reached. | 0.636427 |
71. A machine-implemented method comprising: displaying a graphical user interface (GUI) object; and displaying at least one user-manipulable control element within the GUI object, the user-manipulable control element manipulable to specify a parameter used in determining whether to automatically submit received search input as a query to a search engine, wherein the query is automatically submitted to the search engine if the search input satisfies a temporal trigger, wherein the temporal trigger is based upon a connection speed to the search engine; and wherein the parameter includes at least one of temporal and substantive triggers, and delays. | 71. A machine-implemented method comprising: displaying a graphical user interface (GUI) object; and displaying at least one user-manipulable control element within the GUI object, the user-manipulable control element manipulable to specify a parameter used in determining whether to automatically submit received search input as a query to a search engine, wherein the query is automatically submitted to the search engine if the search input satisfies a temporal trigger, wherein the temporal trigger is based upon a connection speed to the search engine; and wherein the parameter includes at least one of temporal and substantive triggers, and delays. 72. The method of claim 71 , further comprising: receiving input through the user-manipulable control element, the input specifying the parameter. | 0.805281 |
78. A method of selecting advertisements in a computer including a data storage, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer to a behavior vector; comparing the behavior vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector, and selecting at least one electronic advertisement to communicate to the user computing device. | 78. A method of selecting advertisements in a computer including a data storage, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer to a behavior vector; comparing the behavior vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector, and selecting at least one electronic advertisement to communicate to the user computing device. 84. The method as defined in claim 78, wherein the converting includes identifying the behavior vector based upon a page identifier. | 0.793365 |
1. A computer-implemented method for estimating an interest a reader has in a requested document, useful in association with a list of textual terms with advertising value, the method comprising: building a trained model comprising using linear regression to identify a scoring function based on textual terms and associated documents, wherein the scoring function is of the form:
o ( k,p )=α+Σβ i log f i ( k )+Σγ i log g i ( k,p ) wherein β i and γ i are comparative relevance attributes and α is a relevancy factor; wherein k is a term factor and p is a web document identifier, eliminating extraneous material from the requested document; comparing a plurality of textual terms of the requested document to the list of textual terms with the advertising value, wherein the advertising value is based upon a bid value associated with one or more textual terms of the list of textual terms by one or more advertisers and the textual terms also including non-contextual features; computing a significance level based on the trained model for each of the plurality of textual terms of the requested document found on the list of textual terms with advertising value according to the advertising value of each of the plurality of terms of the requested document and computing the significant level based on the non-contextual feature of the positions of the textual terms in the requested document; ranking each of the plurality of textual terms of the requested document found on the list of textual terms with advertising value according to the significance level of each of the plurality of textual terms of the requested document that are found on the list of textual terms with advertising value; selecting one or more of the plurality of ranked textual terms as keywords to search for one or more relevant advertisements; and displaying the one or more relevant advertisements along with the requested document. | 1. A computer-implemented method for estimating an interest a reader has in a requested document, useful in association with a list of textual terms with advertising value, the method comprising: building a trained model comprising using linear regression to identify a scoring function based on textual terms and associated documents, wherein the scoring function is of the form:
o ( k,p )=α+Σβ i log f i ( k )+Σγ i log g i ( k,p ) wherein β i and γ i are comparative relevance attributes and α is a relevancy factor; wherein k is a term factor and p is a web document identifier, eliminating extraneous material from the requested document; comparing a plurality of textual terms of the requested document to the list of textual terms with the advertising value, wherein the advertising value is based upon a bid value associated with one or more textual terms of the list of textual terms by one or more advertisers and the textual terms also including non-contextual features; computing a significance level based on the trained model for each of the plurality of textual terms of the requested document found on the list of textual terms with advertising value according to the advertising value of each of the plurality of terms of the requested document and computing the significant level based on the non-contextual feature of the positions of the textual terms in the requested document; ranking each of the plurality of textual terms of the requested document found on the list of textual terms with advertising value according to the significance level of each of the plurality of textual terms of the requested document that are found on the list of textual terms with advertising value; selecting one or more of the plurality of ranked textual terms as keywords to search for one or more relevant advertisements; and displaying the one or more relevant advertisements along with the requested document. 6. The method of claim 1 wherein the plurality of textual terms of the requested document include numbers. | 0.838369 |
5. A method of protecting sensitive data in a multiple domain environment, said method comprising the computer-implemented steps of: establishing a first data vault located at a first domain, and a replica of said first data vault at each of a plurality of second domains; establishing a plurality of second data vaults, each located at one of said plurality of second domains, and establishing a replica of each said plurality of second data vaults at said first domain; receiving at said first domain a sensitive data string for tokenization from a client process; searching said first data vault to determine if a first token corresponding to said sensitive data string exists therein and, if found, returning said first token to said client process and, if not found: searching each said replica of each of said plurality of second data vaults to determine if a second token corresponding to said sensitive data string exists therein and, if found, returning said second token to said client process and, if not found: generating a new token according to a token generation algorithm wherein said new token is independent of at least a portion of the data in said sensitive data string, and wherein said token generation algorithm is configured to embed within said new token a domain designator corresponding to said first domain; storing said new token in said first data vault; returning said new token to said client process; and updating said replica of said first data vault at each of said plurality of second domains. | 5. A method of protecting sensitive data in a multiple domain environment, said method comprising the computer-implemented steps of: establishing a first data vault located at a first domain, and a replica of said first data vault at each of a plurality of second domains; establishing a plurality of second data vaults, each located at one of said plurality of second domains, and establishing a replica of each said plurality of second data vaults at said first domain; receiving at said first domain a sensitive data string for tokenization from a client process; searching said first data vault to determine if a first token corresponding to said sensitive data string exists therein and, if found, returning said first token to said client process and, if not found: searching each said replica of each of said plurality of second data vaults to determine if a second token corresponding to said sensitive data string exists therein and, if found, returning said second token to said client process and, if not found: generating a new token according to a token generation algorithm wherein said new token is independent of at least a portion of the data in said sensitive data string, and wherein said token generation algorithm is configured to embed within said new token a domain designator corresponding to said first domain; storing said new token in said first data vault; returning said new token to said client process; and updating said replica of said first data vault at each of said plurality of second domains. 7. The method of claim 5 , wherein said domain designator comprises a single digit selected from the ten numerals, zero through nine. | 0.691646 |
9. A computer-implemented method that provides a customized user experience for a computing system, the method comprising: receiving a markup language file comprising one or more markup tags that generates a user interface comprising one or more user interface objects and one or more markup tags for accessing a function exposed by a computer program through an application programming interface (API); rendering the markup language file to provide the user interface; determining whether the markup language file has at least one markup language tag stored therein that references a function to be exposed by a computer program through the API; and in response to determining that the markup language file has the at least one markup language tag stored therein that references the function exposed through the API, calling the API to execute the function provided by the computer program by way of the user interface. | 9. A computer-implemented method that provides a customized user experience for a computing system, the method comprising: receiving a markup language file comprising one or more markup tags that generates a user interface comprising one or more user interface objects and one or more markup tags for accessing a function exposed by a computer program through an application programming interface (API); rendering the markup language file to provide the user interface; determining whether the markup language file has at least one markup language tag stored therein that references a function to be exposed by a computer program through the API; and in response to determining that the markup language file has the at least one markup language tag stored therein that references the function exposed through the API, calling the API to execute the function provided by the computer program by way of the user interface. 14. The computer-implemented method of claim 9 , wherein the API comprises an application- specific API. | 0.648247 |
1. A computer program product for implementing a method for controlling a computing system, the computer program product comprising physical computer storage media containing computer-executable instructions for implementing a method for customizing a binary content file stored at the computing system without recompiling source code associated with the binary content file so as to modify the behavior of the binary content file when the binary content file is executed at a destination computing system, and wherein the method comprises: at a computing system performing an act of translating an object file compiled from source code into one or more compiled binary content files; an act of receiving at a computing system for storage one or more compiled binary content files that each includes one or more variables that are assigned current values; an act of preparing at a computing system one or more non-binary script files that each include one or more references to updated values for one or more of the variables in one or more of the compiled binary content files; inputting for storage at the computing system at which the one or more compiled binary content files are stored the prepared script files, and then performing at a variable initialization module of the computing system an act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files; and at the computing system where the one or more compiles binary content files are stored, using the variable initialization module to update the one or more compiled binary content files with the change to current values of the one or more variables obtained from the one or more script files without having to recompile the updated binary content files. | 1. A computer program product for implementing a method for controlling a computing system, the computer program product comprising physical computer storage media containing computer-executable instructions for implementing a method for customizing a binary content file stored at the computing system without recompiling source code associated with the binary content file so as to modify the behavior of the binary content file when the binary content file is executed at a destination computing system, and wherein the method comprises: at a computing system performing an act of translating an object file compiled from source code into one or more compiled binary content files; an act of receiving at a computing system for storage one or more compiled binary content files that each includes one or more variables that are assigned current values; an act of preparing at a computing system one or more non-binary script files that each include one or more references to updated values for one or more of the variables in one or more of the compiled binary content files; inputting for storage at the computing system at which the one or more compiled binary content files are stored the prepared script files, and then performing at a variable initialization module of the computing system an act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files; and at the computing system where the one or more compiles binary content files are stored, using the variable initialization module to update the one or more compiled binary content files with the change to current values of the one or more variables obtained from the one or more script files without having to recompile the updated binary content files. 5. The computer program product as recited in claim 1 , wherein the act of preparing at a computing system one or more non-binary script files that each include one or more references to updated values for one or more of the variables in one or more of the compiled binary content files comprises the following: an act of preparing at least one of the script file to include one or more conditional statements for selecting appropriate references to updated values for one or more variables. | 0.576592 |
19. A non-transitory computer readable storage device storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: obtaining search results that are responsive to a received query received from a user; retrieving a set of topics associated with the user from a topics repository, the set of topics being provided from a topics service that associates one or more topics with users of one or more computer-implemented services, and each topic in the set of topics being associated with a topic score; determining a subset of topics from the set of topics associated with the user, the subset of topics comprising topics having respective topic scores that exceed a threshold score; determining that one or more topics are associated with the query, and in response: determining that social annotations are to be displayed in a search results page based on one or more topics being included in an intersection of i) the one or more topics associated with the query and ii) one or more topics in the subset of topics associated with the user having topic scores that exceed the threshold score, and in response to determining that social annotations are to be displayed: providing an electronic document comprising instructions that, when executed by a computing device, cause the computing device to display an enhanced search results page, wherein the enhanced search results page comprises the obtained search results and one or more social annotations, at least one social annotation comprising a graphical representation of social networking data that is associated with a respective search result and the user; and transmitting the electronic document to a computing device associated with the user. | 19. A non-transitory computer readable storage device storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: obtaining search results that are responsive to a received query received from a user; retrieving a set of topics associated with the user from a topics repository, the set of topics being provided from a topics service that associates one or more topics with users of one or more computer-implemented services, and each topic in the set of topics being associated with a topic score; determining a subset of topics from the set of topics associated with the user, the subset of topics comprising topics having respective topic scores that exceed a threshold score; determining that one or more topics are associated with the query, and in response: determining that social annotations are to be displayed in a search results page based on one or more topics being included in an intersection of i) the one or more topics associated with the query and ii) one or more topics in the subset of topics associated with the user having topic scores that exceed the threshold score, and in response to determining that social annotations are to be displayed: providing an electronic document comprising instructions that, when executed by a computing device, cause the computing device to display an enhanced search results page, wherein the enhanced search results page comprises the obtained search results and one or more social annotations, at least one social annotation comprising a graphical representation of social networking data that is associated with a respective search result and the user; and transmitting the electronic document to a computing device associated with the user. 20. The non-transitory computer readable storage device of claim 19 , wherein determining that social annotations are to be displayed comprises determining that the at least one topic is associated with the user. | 0.553703 |
6. The method of claim 1 , wherein traversing the runtime plan tree further comprises, upon determining that the first compiled object corresponding to the first string key is in the compiled object cache: retrieving the first compiled object from the compiled object cache in accordance with the first string key; and setting a function pointer to the first compiled object. | 6. The method of claim 1 , wherein traversing the runtime plan tree further comprises, upon determining that the first compiled object corresponding to the first string key is in the compiled object cache: retrieving the first compiled object from the compiled object cache in accordance with the first string key; and setting a function pointer to the first compiled object. 7. The method of claim 6 , wherein traversing the runtime plan tree further comprises, upon determining that the first compiled object is in the compiled object cache: remapping symbols for the first compiled object; and relocating an address of symbols for the first compiled object. | 0.873483 |
18. A system to determine a routing destination based upon speech, the system comprising: an acoustic engine configured to accept a speech input and to output a text based on at least a portion of the speech; a semantic engine coupled to the acoustic engine and operable to identify one or more actions and one or more objects based at least in part on the text; a probability system operable to assign a corresponding confidence level to each of the one or more actions and the one or more objects identified; an action-object pairing system to: identify a dominant entry from the one or more identified actions and the one or more identified objects; and select a complement to the dominant entry from the one or more identified actions and the one or more identified objects, wherein the selection is based at least in part on the dominant entry; and form an action-object pair that includes the dominant entry and the complement to the dominant entry; and an action-object routing table operable to provide a routing destination based at least partially on the action-object pair. | 18. A system to determine a routing destination based upon speech, the system comprising: an acoustic engine configured to accept a speech input and to output a text based on at least a portion of the speech; a semantic engine coupled to the acoustic engine and operable to identify one or more actions and one or more objects based at least in part on the text; a probability system operable to assign a corresponding confidence level to each of the one or more actions and the one or more objects identified; an action-object pairing system to: identify a dominant entry from the one or more identified actions and the one or more identified objects; and select a complement to the dominant entry from the one or more identified actions and the one or more identified objects, wherein the selection is based at least in part on the dominant entry; and form an action-object pair that includes the dominant entry and the complement to the dominant entry; and an action-object routing table operable to provide a routing destination based at least partially on the action-object pair. 22. The system of claim 18 , wherein the complement to the dominant entry is selected based at least in part on a likelihood of consistency with the dominant entry. | 0.613333 |
9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a computing device, audio data that corresponds to an utterance; determining that the utterance likely includes a particular, predefined hotword; in response to determining that the utterance likely includes the particular, predefined hotword, determining score that reflects a loudness of the audio data; determining a duration of a delay period, wherein the duration of the delay period is inversely proportional to the loudness of the audio data; activating a mode in which the computing device temporarily listens, for the duration of the delay period, for a predetermined audio signal that indicates that another computing device is commencing speech recognition processing on the audio data; after the duration of the delay period has elapsed without hearing the predetermined audio signal from another computing device, deactivating the mode and transmitting the predetermined audio signal that indicates that the computing device is commencing speech recognition processing on the audio data; and after transmitting the predetermined audio signal, processing at least a portion of the audio data using an automated speech recognizer on the computing device. | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a computing device, audio data that corresponds to an utterance; determining that the utterance likely includes a particular, predefined hotword; in response to determining that the utterance likely includes the particular, predefined hotword, determining score that reflects a loudness of the audio data; determining a duration of a delay period, wherein the duration of the delay period is inversely proportional to the loudness of the audio data; activating a mode in which the computing device temporarily listens, for the duration of the delay period, for a predetermined audio signal that indicates that another computing device is commencing speech recognition processing on the audio data; after the duration of the delay period has elapsed without hearing the predetermined audio signal from another computing device, deactivating the mode and transmitting the predetermined audio signal that indicates that the computing device is commencing speech recognition processing on the audio data; and after transmitting the predetermined audio signal, processing at least a portion of the audio data using an automated speech recognizer on the computing device. 12. The system of claim 9 , wherein the predetermined audio signal comprises an ultrasonic signal. | 0.909756 |
1. A method in a computing system having a processor, the method comprising: receiving a request for a web page, the request including a locale identifier value, the locale identifier value referencing a geographic location associated with a referral website and a language associated with a webpage of the referral website containing a link used to generate the request; with the processor, retrieving a version of marketing information identified by processing the locale identifier value included in the request for the web page; with the processor, generating the requested web page to include information representative of the retrieved version of the marketing information; and transmitting the generated web page. | 1. A method in a computing system having a processor, the method comprising: receiving a request for a web page, the request including a locale identifier value, the locale identifier value referencing a geographic location associated with a referral website and a language associated with a webpage of the referral website containing a link used to generate the request; with the processor, retrieving a version of marketing information identified by processing the locale identifier value included in the request for the web page; with the processor, generating the requested web page to include information representative of the retrieved version of the marketing information; and transmitting the generated web page. 13. The method of claim 1 , wherein the generated web page includes a link for Internet telephony communication with a customer service representative. | 0.644433 |
22. A non-transitory computer-readable storage medium comprising instructions for causing one or more processor to: receive a spoken utterance; generate a first phoneme-independent representation based on the spoken utterance; decompose the first phoneme-independent representation into at least one content-independent characteristic unit; compare the at least one content-independent characteristic unit to at least one-content-independent recognition distribution value associated with a registered user of a device, the at least one content-independent recognition distribution value previously generated by: generate a second phoneme-independent representation based on speech from the registered user; and decompose the second phoneme-independent representation into a content-independent recognition unit, the at least one content-independent recognition distribution value based on the content-independent recognition unit; and determine that the spoken utterance is spoken by the registered user if the at least one content-independent characteristic unit is within a threshold limit of the at least one content-independent recognition distribution value. | 22. A non-transitory computer-readable storage medium comprising instructions for causing one or more processor to: receive a spoken utterance; generate a first phoneme-independent representation based on the spoken utterance; decompose the first phoneme-independent representation into at least one content-independent characteristic unit; compare the at least one content-independent characteristic unit to at least one-content-independent recognition distribution value associated with a registered user of a device, the at least one content-independent recognition distribution value previously generated by: generate a second phoneme-independent representation based on speech from the registered user; and decompose the second phoneme-independent representation into a content-independent recognition unit, the at least one content-independent recognition distribution value based on the content-independent recognition unit; and determine that the spoken utterance is spoken by the registered user if the at least one content-independent characteristic unit is within a threshold limit of the at least one content-independent recognition distribution value. 26. The computer-readable storage medium of claim 22 , wherein decomposing the first phoneme-independent representation further comprises: applying a singular value decomposition to the first phoneme-independent representation. | 0.644582 |
9. A computer implemented system least partially implemented in hardware, comprising: an Xpath parser configured to perform a first Xpath evaluation on a stream of Extensible Markup Language (XML) messages using a processor, the first Xpath evaluation based on a group of Xpath queries associated with a first user transaction, the Xpath parser configured to receive a plurality of requests to modify the Xpath query group and combining the plurality of requests into a single atomic modification; and a modifying module configured to modify an Xpath query group, in a persistent manner, without affecting the ongoing Xpath evaluation on the XML messages, wherein the modifying module is further configured to generate a second data structure as a copy of a portion of a first data structure, the first data structure comprising a hash table with branches, the branches derived from the group of Xpath queries prior to modification and only copying branches of the first data structure being modified, the modifying module configured to alter at least one branch of the second data structure in accordance with the modification request, wherein the single atomic modification modifies the second data structure to perform a subsequent Xpath evaluation corresponding to a subsequent modification request of the plurality of requests without generating an additional data structure, the modifying module configured to perform a second Xpath evaluation, associated with a second user transaction, using the second data structure in substantially real time with the first Xpath evaluation such that the first and second user transactions are overlapping, and deleting the first data structure upon completion of the first user transaction and using the second data structure for additional user transactions until modified. | 9. A computer implemented system least partially implemented in hardware, comprising: an Xpath parser configured to perform a first Xpath evaluation on a stream of Extensible Markup Language (XML) messages using a processor, the first Xpath evaluation based on a group of Xpath queries associated with a first user transaction, the Xpath parser configured to receive a plurality of requests to modify the Xpath query group and combining the plurality of requests into a single atomic modification; and a modifying module configured to modify an Xpath query group, in a persistent manner, without affecting the ongoing Xpath evaluation on the XML messages, wherein the modifying module is further configured to generate a second data structure as a copy of a portion of a first data structure, the first data structure comprising a hash table with branches, the branches derived from the group of Xpath queries prior to modification and only copying branches of the first data structure being modified, the modifying module configured to alter at least one branch of the second data structure in accordance with the modification request, wherein the single atomic modification modifies the second data structure to perform a subsequent Xpath evaluation corresponding to a subsequent modification request of the plurality of requests without generating an additional data structure, the modifying module configured to perform a second Xpath evaluation, associated with a second user transaction, using the second data structure in substantially real time with the first Xpath evaluation such that the first and second user transactions are overlapping, and deleting the first data structure upon completion of the first user transaction and using the second data structure for additional user transactions until modified. 13. The computer implemented system of claim 9 , wherein the modification request comprises a request for: deleting an existing Xpath query from the Xpath query group. | 0.602378 |
15. The computer program product of claim 4 , further comprising program code for: when one or more of the group-by columns of the definition query of the MQT are expanded using functional dependency relationships, creating the first set of columns that includes the group-by columns of the MQT definition query expanded; when one or more of the group-by columns of the incoming query are identified, defining the second set of columns by utilizing the one or more of the group-by columns of the incoming query; when one or more matching columns between the first set and the second set are identified, creating a matched group using the one or more matching columns; when one or more of the group-by columns of the first set that do not belong to the matched group are identified, creating a first unmatched group that comprises the one or more of the group-by columns of the first set that do not belong to the matched group; and when one or more of the group-by columns of the second set that do not belong to the matched group are identified, creating a second unmatched group that comprises the one or more of the group-by columns of the second set that do not belong to the matched group. | 15. The computer program product of claim 4 , further comprising program code for: when one or more of the group-by columns of the definition query of the MQT are expanded using functional dependency relationships, creating the first set of columns that includes the group-by columns of the MQT definition query expanded; when one or more of the group-by columns of the incoming query are identified, defining the second set of columns by utilizing the one or more of the group-by columns of the incoming query; when one or more matching columns between the first set and the second set are identified, creating a matched group using the one or more matching columns; when one or more of the group-by columns of the first set that do not belong to the matched group are identified, creating a first unmatched group that comprises the one or more of the group-by columns of the first set that do not belong to the matched group; and when one or more of the group-by columns of the second set that do not belong to the matched group are identified, creating a second unmatched group that comprises the one or more of the group-by columns of the second set that do not belong to the matched group. 18. The computer program product of claim 15 , further comprising program code for: when the matched group exists and the non-empty first unmatched group and the second unmatched group are identified: (1) determining whether the matched group functionally determines the non-empty first unmatched group and the second unmatched group; and (2) identifying the MQT as a candidate match when (a) the matched group exists and is identified, (b) the matched group functionally determines the non-empty first and second unmatched group(s), and (c) one or more of the qualifying conditions are satisfied; when the matched group does not exist or the matched group exists but does not functionally determine the non-empty first and second unmatched group(s): (1) determining whether the incoming query is based on measures which are exclusively additive; and (2) identifying the MQT as a candidate match when (a) the incoming query is based on measures which are exclusively additive, (b) the number of columns in the first set functionally determines the number of columns in the second set, and (c) one or more of the qualifying conditions are satisfied. | 0.707037 |
1. A volatile memory, non-volatile memory, optical disk, or hard drive storing computer-executable instructions which, when executed by a computer, cause the computer to perform acts comprising: representing historical user behaviors of a user using a set of features, the set of features including click features and query features; training a classifier using training data comprising values for the features to identify a plurality of historical search contexts, wherein the plurality of historical search contexts include: a first historical search context having first values for the features, wherein the first values include: first click feature values for the click features, the first click feature values representing multiple first clicks entered by the user on multiple different first uniform resource locators (URLs) as part of the first historical search context, and first query feature values for the query features, the first query feature values representing multiple different first queries entered by the user as part of the first historical search context, a second historical search context having second values for the features, wherein the second values include: second click feature values for the click features, the second click feature values representing multiple second clicks entered by the user on multiple different second URLs as part of the second historical search context, and second query feature values for the query features, the second query feature values representing multiple different second queries entered by the user as part of the second historical search context; representing current user behavior during a current user session using third values for the features, wherein the third values include current click feature values for the click features and current query feature values for the query features, the current click feature values representing multiple current clicks entered by the user on multiple different current URLs during a current session and the current query feature values representing multiple different current queries entered by the user during the current session; during the current user session, determining that the current user behavior is relatively more similar to the first historical search context than the second historical search context, wherein the determining comprises: using the first click feature values, the second click feature values, and the current click feature values to analyze similarity of the multiple different current URLs clicked by the user during the current session to the multiple different first URLs clicked by the user as part of the first historical search context and the multiple different second URLs clicked by the user as part of the second historical search context, and using the first query feature values, the second query feature values, and the current query feature values to analyze similarity of the multiple current queries entered by the user during the current session to the multiple different first queries entered by the user as part of the first historical search context and the multiple different second queries entered by the user as part of the second historical search context; and surfacing the first historical search context as part of the current session for the user. | 1. A volatile memory, non-volatile memory, optical disk, or hard drive storing computer-executable instructions which, when executed by a computer, cause the computer to perform acts comprising: representing historical user behaviors of a user using a set of features, the set of features including click features and query features; training a classifier using training data comprising values for the features to identify a plurality of historical search contexts, wherein the plurality of historical search contexts include: a first historical search context having first values for the features, wherein the first values include: first click feature values for the click features, the first click feature values representing multiple first clicks entered by the user on multiple different first uniform resource locators (URLs) as part of the first historical search context, and first query feature values for the query features, the first query feature values representing multiple different first queries entered by the user as part of the first historical search context, a second historical search context having second values for the features, wherein the second values include: second click feature values for the click features, the second click feature values representing multiple second clicks entered by the user on multiple different second URLs as part of the second historical search context, and second query feature values for the query features, the second query feature values representing multiple different second queries entered by the user as part of the second historical search context; representing current user behavior during a current user session using third values for the features, wherein the third values include current click feature values for the click features and current query feature values for the query features, the current click feature values representing multiple current clicks entered by the user on multiple different current URLs during a current session and the current query feature values representing multiple different current queries entered by the user during the current session; during the current user session, determining that the current user behavior is relatively more similar to the first historical search context than the second historical search context, wherein the determining comprises: using the first click feature values, the second click feature values, and the current click feature values to analyze similarity of the multiple different current URLs clicked by the user during the current session to the multiple different first URLs clicked by the user as part of the first historical search context and the multiple different second URLs clicked by the user as part of the second historical search context, and using the first query feature values, the second query feature values, and the current query feature values to analyze similarity of the multiple current queries entered by the user during the current session to the multiple different first queries entered by the user as part of the first historical search context and the multiple different second queries entered by the user as part of the second historical search context; and surfacing the first historical search context as part of the current session for the user. 4. The physical storage media of claim 1 , the acts further comprising: creating a click graph representing the multiple first clicks and the multiple second clicks, the click graph having a first terminal state representing a first web page labeled as a first category and a second terminal state representing a second web page labeled as a second category; performing a first random walk over the click graph for an individual first click to reach the first terminal state; responsive to reaching the first terminal state via the first random walk, tagging the individual first click with the first category as an individual first click feature value; performing a second random walk over the click graph for an individual second click to reach the second terminal state; responsive to reaching the second terminal state via the second random walk, tagging the individual second click with the second category as an individual second click feature value. | 0.500492 |
1. A machine-readable medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for generating human-centric driving directions, the process comprising: generating a route in response to a user request for travel directions, the request specifying at least a target destination; identifying distinctive waypoints along the route, wherein the waypoints are physical structures along the route and are in addition to road names and road topology and each waypoint is associated with a distinctiveness score, wherein the distinctiveness score of each waypoint is based at least in part on a visual prominence of the respective waypoint and based at least in part on an advertising fee per use for incorporating the respective waypoint in travel directions; and incorporating one or more of the waypoints into travel directions responsive to the associated distinctiveness score. | 1. A machine-readable medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for generating human-centric driving directions, the process comprising: generating a route in response to a user request for travel directions, the request specifying at least a target destination; identifying distinctive waypoints along the route, wherein the waypoints are physical structures along the route and are in addition to road names and road topology and each waypoint is associated with a distinctiveness score, wherein the distinctiveness score of each waypoint is based at least in part on a visual prominence of the respective waypoint and based at least in part on an advertising fee per use for incorporating the respective waypoint in travel directions; and incorporating one or more of the waypoints into travel directions responsive to the associated distinctiveness score. 7. The machine-readable medium of claim 1 wherein incorporating one or more of the waypoints into travel directions includes generating textual directions that use natural language to communicate the travel directions. | 0.548344 |
16. The system of claim 15 further comprising: an online binder module that works in cooperation with the processor to store the converted data files as pages of the online binder and associate the pages with a particular online binder. | 16. The system of claim 15 further comprising: an online binder module that works in cooperation with the processor to store the converted data files as pages of the online binder and associate the pages with a particular online binder. 18. The system of claim 16 , wherein the online binder module is further configured to store: (a) a first data related to each of the pages associated with the online binder, the first data including at least one of (i) a name of a specified page of the pages, (ii) a file type of a data file to which the specified page corresponds, (iii) a size of the specified page, or (iv) a hash value of the specified page, and (b) a second data related to annotations associated with one or more of the pages of the online binder. | 0.85143 |
55. The method of claim 54 , wherein the remote computing equipment comprises a computer running a media player application, and wherein transmitting the portion of the voice command and the portion of the contextual information comprises: transmitting the stored information about the given media file and the portion of the voice command to the media player application on the computer. | 55. The method of claim 54 , wherein the remote computing equipment comprises a computer running a media player application, and wherein transmitting the portion of the voice command and the portion of the contextual information comprises: transmitting the stored information about the given media file and the portion of the voice command to the media player application on the computer. 56. The method of claim 55 , wherein the information about the given media file is selected from the group consisting of: a track name; a track title; an artist name; an album name; and an album genre. | 0.822644 |
1. A method for performing script operations in a mobile device, comprising: (a) requesting a first web-based object; (b) transmitting a list of scripting languages that are compatible with said mobile device; (c) receiving said first web-based object and a first script related to said first web-based object; (d) storing said first web-based object and said first script; (e) executing said first script, when said first script is in a scripting language included in said transmitted list, thereby causing a page specific global object to be defined, wherein said page specific global object controls how web-based objects are presented on a first web-page displayed on said mobile device; (f) storing said page specific global object; (g) updating, when said first web-page is displayed, one or more properties of said stored page specific global object in accordance with said first script, wherein said properties determine how web-based objects are presented on said first web-page; (h) retrieving said stored page specific global object for use by a second script related to said first web-page; and (i) controlling access to said properties of said stored page specific global object from a third script related to a second web-page. | 1. A method for performing script operations in a mobile device, comprising: (a) requesting a first web-based object; (b) transmitting a list of scripting languages that are compatible with said mobile device; (c) receiving said first web-based object and a first script related to said first web-based object; (d) storing said first web-based object and said first script; (e) executing said first script, when said first script is in a scripting language included in said transmitted list, thereby causing a page specific global object to be defined, wherein said page specific global object controls how web-based objects are presented on a first web-page displayed on said mobile device; (f) storing said page specific global object; (g) updating, when said first web-page is displayed, one or more properties of said stored page specific global object in accordance with said first script, wherein said properties determine how web-based objects are presented on said first web-page; (h) retrieving said stored page specific global object for use by a second script related to said first web-page; and (i) controlling access to said properties of said stored page specific global object from a third script related to a second web-page. 5. The method of claim 1 , wherein a language of said first script is JavaScript, ECMAScript, Java, Perl, Tcl, Visual BASIC, or VBScript. | 0.92952 |
9. A method comprising: receiving, at a client device, through a first connection, notification data that indicates that particular data is available; in response to receiving the notification data, determining, at the client device, based on the notification data, that the particular data is available; in response to determining that the particular data is available, sending, from the client device, through a second connection that is different than the first connection, request data that indicates a request for the particular data; after sending the request data, receiving, at the client device, through the second connection, the particular data that is in a particular markup language; in response to receiving the particular data, processing the particular data to render a window on a display of the client device; wherein the method is performed by one or more computing devices. | 9. A method comprising: receiving, at a client device, through a first connection, notification data that indicates that particular data is available; in response to receiving the notification data, determining, at the client device, based on the notification data, that the particular data is available; in response to determining that the particular data is available, sending, from the client device, through a second connection that is different than the first connection, request data that indicates a request for the particular data; after sending the request data, receiving, at the client device, through the second connection, the particular data that is in a particular markup language; in response to receiving the particular data, processing the particular data to render a window on a display of the client device; wherein the method is performed by one or more computing devices. 11. The method of claim 9 , wherein the particular markup language is HTML or XML. | 0.673451 |
17. A computer-implemented system comprising: one or more devices to: obtain a document relating to a search term, the document comprising structural elements; identify occurrences of the search term in the document with regard to the structural elements; group occurrences of the search term into clusters based on a physical proximity of the occurrences of the search term, a first cluster, of the clusters, that lies within a particular structural element, of the structural elements, being favored over a second cluster, of the clusters, that lies within multiple structural elements of the structural elements; identify a structural element, of the structural elements, encompassing each of the clusters; and provide, for presentation, information relating to the identified structural element. | 17. A computer-implemented system comprising: one or more devices to: obtain a document relating to a search term, the document comprising structural elements; identify occurrences of the search term in the document with regard to the structural elements; group occurrences of the search term into clusters based on a physical proximity of the occurrences of the search term, a first cluster, of the clusters, that lies within a particular structural element, of the structural elements, being favored over a second cluster, of the clusters, that lies within multiple structural elements of the structural elements; identify a structural element, of the structural elements, encompassing each of the clusters; and provide, for presentation, information relating to the identified structural element. 19. The computer-implemented system of claim 17 , where the one or more devices are further to: determine a smallest structural element, of the structural elements, encompassing each of the clusters. | 0.797366 |
12. A computer-implemented method of converting text to speech, the method comprising: generate a response text and a response intent based on user input; receiving response text and an intent representative of intended meaning of the response text that can be conveyed by non-lexical cues; determining, on the one or more computing devices, an insertion point of a non-lexical cue, in the response text, based on the intent; inserting by the one or more computing devices a non-lexical cue at the insertion point within the response text to generate augmented text; and providing the augmented text to a speech synthesizer to synthesize speech from the augmented text using speech units associated with the response text and the inserted response intent. | 12. A computer-implemented method of converting text to speech, the method comprising: generate a response text and a response intent based on user input; receiving response text and an intent representative of intended meaning of the response text that can be conveyed by non-lexical cues; determining, on the one or more computing devices, an insertion point of a non-lexical cue, in the response text, based on the intent; inserting by the one or more computing devices a non-lexical cue at the insertion point within the response text to generate augmented text; and providing the augmented text to a speech synthesizer to synthesize speech from the augmented text using speech units associated with the response text and the inserted response intent. 16. The method of claim 12 , wherein inserting the non-lexical cue at the insertion point comprises changing a portion of the response text. | 0.65966 |
43. A computing system including: one or more data storage systems; means for receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and means for processing the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged. | 43. A computing system including: one or more data storage systems; means for receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and means for processing the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged. 52. The computing system of claim 43 , wherein generating the procedural specification includes generating a dataflow graph from the third collection, the dataflow graph including components configured to perform operations corresponding to relational expressions in respective nodes of the third collection, and links representing flows of the records between output and input ports of components. | 0.546296 |
15. An apparatus configured to index data, the apparatus comprising: one or more processors; and logic encoded in one or more tangible media for execution by the one or more processors and when executed operable to: receive input from a user defining a classification and an analytic for the classification; determine a definition of relevance parameters that characterize the classification; populate a cortex of unstructured data in a tangible computer readable database, the cortex of unstructured data being populated based on the classification; determine relevant data from unstructured data based on the definition of relevance parameters, the relevant data being data that is determined to be relevant to the classification defined by the user; analyze the relevant data from unstructured data based on the relevance parameters to determine attributes in the relevant data; generate an index of the attributes from the relevant data based on the analyzing of the relevant data; store the index in the cortex; and receive a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index useable by an analytics tool to provide results for the query using the analytics measure applied to the unstructured data in the relevant data indexed in the classification. | 15. An apparatus configured to index data, the apparatus comprising: one or more processors; and logic encoded in one or more tangible media for execution by the one or more processors and when executed operable to: receive input from a user defining a classification and an analytic for the classification; determine a definition of relevance parameters that characterize the classification; populate a cortex of unstructured data in a tangible computer readable database, the cortex of unstructured data being populated based on the classification; determine relevant data from unstructured data based on the definition of relevance parameters, the relevant data being data that is determined to be relevant to the classification defined by the user; analyze the relevant data from unstructured data based on the relevance parameters to determine attributes in the relevant data; generate an index of the attributes from the relevant data based on the analyzing of the relevant data; store the index in the cortex; and receive a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index useable by an analytics tool to provide results for the query using the analytics measure applied to the unstructured data in the relevant data indexed in the classification. 20. The apparatus of claim 15 , wherein the relevant data can also include structured data. | 0.581278 |
26. The software framework of claim 25 , wherein the software framework is configured to allow addition of at least one new method selected from the group consisting of: a new producer method; a new converter method; and a new distributor method. | 26. The software framework of claim 25 , wherein the software framework is configured to allow addition of at least one new method selected from the group consisting of: a new producer method; a new converter method; and a new distributor method. 28. The software framework of claim 26 , wherein the new converter method is added and wherein the addition of the new converter method involves declaring a new output format. | 0.938945 |
10. A computer readable memory device encoded with a computer program for assisting a user in creating software code, the computer program comprising computer executable instructions for: receiving user input editing software code through a code editor, the software code being associated with a programming language having a plurality of software constructs, wherein at least one software construct includes one or more invocation points each for receiving user-provided information; receiving user input invoking a code assistant associated with the code editor, the code assistant comprising a plurality of panels that correspond to the plurality of software constructs, one or more of the plurality of panels containing a set of user-selectable options associated with the one or more invocation points of the software constructs to assist the user in editing the software constructs; receiving selected options for the software constructs from the one or more panels and enabling creation of one or more sub-constructs within the software constructs, the one or more of the plurality of panels containing a set of user-selectable options associated with the sub-constructs to assist the user in editing the sub-constructs; and synchronizing the code assistant and code editor in response to each selection of the user-selectable option for an invocation point within the code assistant and each edit of an invocation point of the software constructs entered within the code editor to enable selective switching between the code editor and code assistant during modification of a given software construct to retrieve information for at least one invocation point for the given software construct from the code editor and a user-selectable option for at least one other invocation point of the given software construct from the code assistant. | 10. A computer readable memory device encoded with a computer program for assisting a user in creating software code, the computer program comprising computer executable instructions for: receiving user input editing software code through a code editor, the software code being associated with a programming language having a plurality of software constructs, wherein at least one software construct includes one or more invocation points each for receiving user-provided information; receiving user input invoking a code assistant associated with the code editor, the code assistant comprising a plurality of panels that correspond to the plurality of software constructs, one or more of the plurality of panels containing a set of user-selectable options associated with the one or more invocation points of the software constructs to assist the user in editing the software constructs; receiving selected options for the software constructs from the one or more panels and enabling creation of one or more sub-constructs within the software constructs, the one or more of the plurality of panels containing a set of user-selectable options associated with the sub-constructs to assist the user in editing the sub-constructs; and synchronizing the code assistant and code editor in response to each selection of the user-selectable option for an invocation point within the code assistant and each edit of an invocation point of the software constructs entered within the code editor to enable selective switching between the code editor and code assistant during modification of a given software construct to retrieve information for at least one invocation point for the given software construct from the code editor and a user-selectable option for at least one other invocation point of the given software construct from the code assistant. 13. The computer readable memory device of claim 10 , wherein the computer program further comprises computer executable instructions for immediately reflecting a result of a user selection of an option within a panel of the code assistant within the software code being edited through the code editor. | 0.5 |
15. A portable, real time voice translation system for use by use by a child of preschool or elementary school age, comprising: a translation system for use on a single unit, portable device having a processor and a memory, the translation system for use by use by a child of preschool or elementary school age and having a content state selector on the front of the device that includes simplified pictorial representations of a plurality of translatable content for easy selection by use by the child of preschool or elementary school age; a computer program that is operable for executing the following functions: accessing a multilanguage database embodied in a non-transitory computer readable storage medium including a plurality of phrase templates associated with a respective plurality of phrases; selecting a source language from a plurality of source languages and a destination language from a plurality of destination languages; inputting a source phrase; transmitting the source phrase to (i) a speech recognition module embodied in a non-transitory computer readable storage medium for converting the spoken source phrase into a recognized source phrase; (ii) a translation engine embodied in a non-transitory computer readable storage medium for translating the recognized source phrase in the selected source language into a destination phrase in a destination language selected from multiple languages, wherein the plurality of phrases in the multilanguage database include the destination phrase; and, (iii) a template look-up engine embodied in a non-transitory computer readable storage medium for finding the phrase template associated with the destination phrase from among the multiple languages; and, outputting the spoken translation in the selected destination language, the outputting pace being adjustable from a real-time translation to a slow and more easily assimilated translation pace for ease of use by the child of preschool or elementary school age, the real-time pace being no slower than 0.010 seconds; and, a graphical user interface on the front of the device that includes a text display of the source phrase and the destination phrase; wherein, the translation system having a total time between the input of the source phrase and output of the destination phrase that is no slower than the 0.010 seconds. | 15. A portable, real time voice translation system for use by use by a child of preschool or elementary school age, comprising: a translation system for use on a single unit, portable device having a processor and a memory, the translation system for use by use by a child of preschool or elementary school age and having a content state selector on the front of the device that includes simplified pictorial representations of a plurality of translatable content for easy selection by use by the child of preschool or elementary school age; a computer program that is operable for executing the following functions: accessing a multilanguage database embodied in a non-transitory computer readable storage medium including a plurality of phrase templates associated with a respective plurality of phrases; selecting a source language from a plurality of source languages and a destination language from a plurality of destination languages; inputting a source phrase; transmitting the source phrase to (i) a speech recognition module embodied in a non-transitory computer readable storage medium for converting the spoken source phrase into a recognized source phrase; (ii) a translation engine embodied in a non-transitory computer readable storage medium for translating the recognized source phrase in the selected source language into a destination phrase in a destination language selected from multiple languages, wherein the plurality of phrases in the multilanguage database include the destination phrase; and, (iii) a template look-up engine embodied in a non-transitory computer readable storage medium for finding the phrase template associated with the destination phrase from among the multiple languages; and, outputting the spoken translation in the selected destination language, the outputting pace being adjustable from a real-time translation to a slow and more easily assimilated translation pace for ease of use by the child of preschool or elementary school age, the real-time pace being no slower than 0.010 seconds; and, a graphical user interface on the front of the device that includes a text display of the source phrase and the destination phrase; wherein, the translation system having a total time between the input of the source phrase and output of the destination phrase that is no slower than the 0.010 seconds. 18. The system of claim 15 , wherein the executing includes sequentially translating a series of input source phrases to provide a real-time translation in the form of a series of spoken destination phrases in the language selected from multiple languages, wherein the time between the input and output of the source phrase in the speech recognition module is no slower than about 2 milliseconds, in the voice coding module is no slower than 3 milliseconds, in the translation engine is no slower than about 2 milliseconds, and in the parameterization module is no slower than about 3 milliseconds, such that the total time between the input of the source phrase and output of the destination phrase is no slower than 0.010 second. | 0.534574 |
39. The machine-implemented process of claim 38 and further comprising: based on the automated determination of commonality as between the first and second users, causing a generating of a desirability of joinder score indicating how desirable it is to automatically suggest to both of the first and second users that they join into a common online forum participation session and/or into a common real life (ReL) or virtual life event. | 39. The machine-implemented process of claim 38 and further comprising: based on the automated determination of commonality as between the first and second users, causing a generating of a desirability of joinder score indicating how desirable it is to automatically suggest to both of the first and second users that they join into a common online forum participation session and/or into a common real life (ReL) or virtual life event. 40. The machine-implemented process of claim 39 wherein the common real life (ReL) event, if suggested, is at least one of: a group discount transactional event; a promotional offering event; a customized promotional offering event; an eating experience; a drinking experience; a business meeting; a sports event; a conference; a shared multi-media experience; and a resources using event in which physical resources of a shared physical location are to be used. | 0.969283 |
16. A method of detecting fake antivirus software, said method comprising: collecting keywords that are comprehensible words by monitoring system behavior of a plurality of executing fake antivirus software samples and storing said keywords in a keyword database; identifying an executing process in a computer, said process being legitimate antivirus software; retrieving a rule from a rule database, said rule using two or more of said keywords to identify fake software; retrieving said keywords from said keyword database, each of said keywords being indicative of fake antivirus software; applying said rule to said executing process and determining that keywords of said rule match data in said process executing in a memory of said computer by scanning said process in said memory; determining, after said step of applying, that said process is not legitimate antivirus software when a digital certificate of said process is nonexistent or is invalid, when an identification of said process does not exist in a white list of valid processes, or when a company name associated with said process does not exist in a white list of valid company names; and displaying, on said computer, an indication that said process is fake antivirus software based on said applying and said determining. | 16. A method of detecting fake antivirus software, said method comprising: collecting keywords that are comprehensible words by monitoring system behavior of a plurality of executing fake antivirus software samples and storing said keywords in a keyword database; identifying an executing process in a computer, said process being legitimate antivirus software; retrieving a rule from a rule database, said rule using two or more of said keywords to identify fake software; retrieving said keywords from said keyword database, each of said keywords being indicative of fake antivirus software; applying said rule to said executing process and determining that keywords of said rule match data in said process executing in a memory of said computer by scanning said process in said memory; determining, after said step of applying, that said process is not legitimate antivirus software when a digital certificate of said process is nonexistent or is invalid, when an identification of said process does not exist in a white list of valid processes, or when a company name associated with said process does not exist in a white list of valid company names; and displaying, on said computer, an indication that said process is fake antivirus software based on said applying and said determining. 22. A method as recited in claim 16 further comprising: using statistical analysis to determine the most common keywords to be stored in said keyword database. | 0.523229 |
9. A method, comprising: determining, by a computer, a first token of a plurality of tokens in an unstructured input document, the first token having a visual style; producing, by the computer, a first probability distribution of the first token across a plurality of classes, each class of the plurality of classes being related to a corresponding content of one or more of the plurality of tokens; modifying, by the computer, the first probability distribution to produce a second probability distribution of the first token across the plurality of classes, the second probability distribution being based on one or more classes of the plurality of classes, the one or more classes being likely to contain a plurality of surrounding tokens appearing near the first token in context of the input document; producing, by the computer, a third probability distribution of the first token across the plurality of classes, the third probability distribution being based on the visual style of the first token and the second probability distribution; determining, by the computer based at least on the third probability distribution, a classification of the first token into one of the plurality of classes; and forming, by the computer, a structured document from the first token and the classification. | 9. A method, comprising: determining, by a computer, a first token of a plurality of tokens in an unstructured input document, the first token having a visual style; producing, by the computer, a first probability distribution of the first token across a plurality of classes, each class of the plurality of classes being related to a corresponding content of one or more of the plurality of tokens; modifying, by the computer, the first probability distribution to produce a second probability distribution of the first token across the plurality of classes, the second probability distribution being based on one or more classes of the plurality of classes, the one or more classes being likely to contain a plurality of surrounding tokens appearing near the first token in context of the input document; producing, by the computer, a third probability distribution of the first token across the plurality of classes, the third probability distribution being based on the visual style of the first token and the second probability distribution; determining, by the computer based at least on the third probability distribution, a classification of the first token into one of the plurality of classes; and forming, by the computer, a structured document from the first token and the classification. 13. The method of claim 9 , wherein the input document is an HTML page, and the computer does not produce any of the first probability distribution, the second probability distribution, or the third probability distribution for the first token based on a relationship between HTML tags. | 0.876718 |
18. A system, comprising: one or more processors; and a non-transitory machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the processors to perform operations comprising: determining excess queries over multiple time periods for two or more given geographic features, where each geographic feature defines a location; comparing the two or more geographic features for similarity based at least in part on the determined excess queries associated with each geographic feature; for a given target geographic feature, determining one or more similar geographic features based on the comparing; and relating electronically the target geographic feature and the one or more similar geographic features as a set of similar geographic features, wherein determining the excess queries over the multiple time periods for the two or more given geographic features includes: generating a geo-query count that represents a total number of times that the search query was received over a specified period; obtaining a corresponding expected query count for the at least one of the search queries by accessing a search query log that includes data specifying search queries corresponding to a particular geographic feature; comparing the geo-query count to the corresponding expected query count for the at least one of the search queries, the corresponding expected query count being a baseline number of times that the query is expected to be received; and in response to determining that the geo-query count of the at least one of the search queries exceeds the corresponding expected query count by at least a threshold amount, classifying the at least one of the search queries as an excess query for the particular geographic feature. | 18. A system, comprising: one or more processors; and a non-transitory machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the processors to perform operations comprising: determining excess queries over multiple time periods for two or more given geographic features, where each geographic feature defines a location; comparing the two or more geographic features for similarity based at least in part on the determined excess queries associated with each geographic feature; for a given target geographic feature, determining one or more similar geographic features based on the comparing; and relating electronically the target geographic feature and the one or more similar geographic features as a set of similar geographic features, wherein determining the excess queries over the multiple time periods for the two or more given geographic features includes: generating a geo-query count that represents a total number of times that the search query was received over a specified period; obtaining a corresponding expected query count for the at least one of the search queries by accessing a search query log that includes data specifying search queries corresponding to a particular geographic feature; comparing the geo-query count to the corresponding expected query count for the at least one of the search queries, the corresponding expected query count being a baseline number of times that the query is expected to be received; and in response to determining that the geo-query count of the at least one of the search queries exceeds the corresponding expected query count by at least a threshold amount, classifying the at least one of the search queries as an excess query for the particular geographic feature. 19. The system of claim 18 where the operations for comparing the two or more geographic features for similarity include determining a number of excess queries in common between two geographic features. | 0.587395 |
18. A method according to claim 14 , further comprising generating or modifying a search result of the search engine based on probabilities computed by the statistical machine translation model, the search result corresponding to a user-inputted query form. | 18. A method according to claim 14 , further comprising generating or modifying a search result of the search engine based on probabilities computed by the statistical machine translation model, the search result corresponding to a user-inputted query form. 19. A method according to claim 18 , further comprising using the probabilities to rank or eliminate search result. | 0.975063 |
12. A system, comprising: a processor configured to: receive, from a non-transitory computer readable media, a block of text that includes at least one topic; identify the at least one topic associated with the block of text, the identification comprising a comparison of each portion of a plurality of portions of the block of text to a topic listing of a plurality of topics; identify one or more categories for each of the identified topics, the identification of one or more categories comprising a comparison of each of the identified topics to a hierarchical category graph that includes a mapping of topics to categories; determine unique categories across the one or more categories for each of the topics, the unique categories selected from the identified one or more categories, wherein each unique category is an identified category associated with at least one portion of the plurality of portions of the block of text, the unique categories acting as a unique identifier of the block of text; associate each unique category with M levels of parent categories of each unique category and N levels of child categories of the unique category; determine category graph data for the block of text including each unique category, the category graph data identifying the M levels of parent categories for each unique category, and the N levels of child categories for each unique category; determine a connected category count for a unique category based on the category graph data, the connected category count indicating a number of unique categories connected to the parent categories in the M levels and connected to child categories in the N levels as identified in the category graph data; and determine one or more filtered categories from the unique categories based on the connected category count for the unique category and one or more other connected category counts for one or more other unique categories. | 12. A system, comprising: a processor configured to: receive, from a non-transitory computer readable media, a block of text that includes at least one topic; identify the at least one topic associated with the block of text, the identification comprising a comparison of each portion of a plurality of portions of the block of text to a topic listing of a plurality of topics; identify one or more categories for each of the identified topics, the identification of one or more categories comprising a comparison of each of the identified topics to a hierarchical category graph that includes a mapping of topics to categories; determine unique categories across the one or more categories for each of the topics, the unique categories selected from the identified one or more categories, wherein each unique category is an identified category associated with at least one portion of the plurality of portions of the block of text, the unique categories acting as a unique identifier of the block of text; associate each unique category with M levels of parent categories of each unique category and N levels of child categories of the unique category; determine category graph data for the block of text including each unique category, the category graph data identifying the M levels of parent categories for each unique category, and the N levels of child categories for each unique category; determine a connected category count for a unique category based on the category graph data, the connected category count indicating a number of unique categories connected to the parent categories in the M levels and connected to child categories in the N levels as identified in the category graph data; and determine one or more filtered categories from the unique categories based on the connected category count for the unique category and one or more other connected category counts for one or more other unique categories. 21. The system of claim 12 , wherein M and N are both 1. | 0.673356 |
4. The method of claim 1 , further comprising, generating a logical field having an access method mapping the logical field to one of the selected additional fields of one of the query entity definitions. | 4. The method of claim 1 , further comprising, generating a logical field having an access method mapping the logical field to one of the selected additional fields of one of the query entity definitions. 5. The method of claim 4 , wherein the access method is one of a simple, filtered and composed access method type. | 0.958889 |
16. A system for backing up data computed using an application in a cloud computing environment, comprising: a processor; a module to modify the application to register a servlet, and publish the application to the cloud computing environment, and during execution of the application, the module being further to use the servlet for detecting annotated entities created in the code of the application by parsing user codes, finding out properties and property types of the annotated entities, generating a plurality of structured query language (SQL) statements to query out data to be backed up in accordance with the annotated entities, and publishing the backed up data. | 16. A system for backing up data computed using an application in a cloud computing environment, comprising: a processor; a module to modify the application to register a servlet, and publish the application to the cloud computing environment, and during execution of the application, the module being further to use the servlet for detecting annotated entities created in the code of the application by parsing user codes, finding out properties and property types of the annotated entities, generating a plurality of structured query language (SQL) statements to query out data to be backed up in accordance with the annotated entities, and publishing the backed up data. 21. The system according to claim 16 , wherein the module is further to add a library to the application. | 0.632642 |
19. A method of generating annotated training data to train a natural language understanding (NLU) system having one or more models, comprising: generating a proposed annotation with the NLU system for each of one or more units of unannotated training data; displaying the proposed annotations for user verification or correction to obtain a user-confirmed annotation, comprising: displaying a plurality of alternative proposed annotations to data portions associated with a child node in response to that child node being deleted; wherein the user is enabled to select one of the alternative proposed annotations from among the plurality of alternative proposed annotations, and the user-selected alternative proposed annotation is incorporated into the annotated training data; training the NLU system with the user-confirmed annotation; and displaying an indication of a volume of training data used to train a plurality of different portions of the one or more models of the natural language understanding system, wherein displaying an indication of a volume of training data comprises: displaying a representation of the one or more models; and visually contrasting portions of the one or more models that have been trained with a threshold volume of training data. | 19. A method of generating annotated training data to train a natural language understanding (NLU) system having one or more models, comprising: generating a proposed annotation with the NLU system for each of one or more units of unannotated training data; displaying the proposed annotations for user verification or correction to obtain a user-confirmed annotation, comprising: displaying a plurality of alternative proposed annotations to data portions associated with a child node in response to that child node being deleted; wherein the user is enabled to select one of the alternative proposed annotations from among the plurality of alternative proposed annotations, and the user-selected alternative proposed annotation is incorporated into the annotated training data; training the NLU system with the user-confirmed annotation; and displaying an indication of a volume of training data used to train a plurality of different portions of the one or more models of the natural language understanding system, wherein displaying an indication of a volume of training data comprises: displaying a representation of the one or more models; and visually contrasting portions of the one or more models that have been trained with a threshold volume of training data. 20. The method of claim 19 wherein the threshold volume of training data is dynamic, based on one or more performance criteria for the one or more models. | 0.759468 |
1. A method for entering new characters or editing pre-existing characters in a plurality of data entry fields on a display screen including a handwriting capture widget in a fixed location and separate from a plurality of text entry widgets corresponding to the data entry fields using a user interface, comprising the steps of: assigning one text entry widget from a sequentially ordered list of text entry widgets as a current text entry widget; displaying in the handwriting capture widget any characters in the current text entry widget; receiving in the handwriting capture widget at least one character for entry into the current text entry widget; after receipt of the at least one character in the current text entry widget is complete and when the current text entry widget is not a last text entry widget in the sequentially ordered list of text entry widgets, automatically selecting as the current text entry widget a next text entry widget from the sequentially ordered list of text entry widgets; and repeating said displaying step, said receiving step, and said selecting step. | 1. A method for entering new characters or editing pre-existing characters in a plurality of data entry fields on a display screen including a handwriting capture widget in a fixed location and separate from a plurality of text entry widgets corresponding to the data entry fields using a user interface, comprising the steps of: assigning one text entry widget from a sequentially ordered list of text entry widgets as a current text entry widget; displaying in the handwriting capture widget any characters in the current text entry widget; receiving in the handwriting capture widget at least one character for entry into the current text entry widget; after receipt of the at least one character in the current text entry widget is complete and when the current text entry widget is not a last text entry widget in the sequentially ordered list of text entry widgets, automatically selecting as the current text entry widget a next text entry widget from the sequentially ordered list of text entry widgets; and repeating said displaying step, said receiving step, and said selecting step. 2. A method in accordance with claim 1, wherein said receiving step comprises receiving at least one handwritten new character in the handwriting capture widget. | 0.502234 |
12. The method of claim 1 , further comprising selecting, by the at least one processor, the subset by processing the plurality of interaction transcriptions to identify a triggering theme and then creating the subset around the identified triggering theme. | 12. The method of claim 1 , further comprising selecting, by the at least one processor, the subset by processing the plurality of interaction transcriptions to identify a triggering theme and then creating the subset around the identified triggering theme. 14. The method of claim 12 , wherein the subset is created as a particular number of back and forth interactions between an agent and a customer. | 0.921656 |
12. A method of presenting speech information comprising producing a sequence of signals representative of speech phonemes; transforming the signals into a sequence of first and second grid patterns of points, the first pattern being a code which identifies the phoneme sound and the second pattern being another code which identifies a mouth form that produces the phoneme sound; and presenting the first and second patterns by activating presenters arranged in a multiple point grid matrix in accordance with said patterns of points. | 12. A method of presenting speech information comprising producing a sequence of signals representative of speech phonemes; transforming the signals into a sequence of first and second grid patterns of points, the first pattern being a code which identifies the phoneme sound and the second pattern being another code which identifies a mouth form that produces the phoneme sound; and presenting the first and second patterns by activating presenters arranged in a multiple point grid matrix in accordance with said patterns of points. 13. The method of claim 12, wherein said transforming comprises analyzing the speech in real time to identify successive phonemes, and forming a corresponding sequence of said first and second patterns, and wherein said presenting comprises presenting the patterns substantially contemporaneously with the speech. | 0.572674 |
12. A system for processing a hierarchically structured document, comprising: means for creating a first dictionary having a first set of information including key-value pairs; means for creating a first reference to the first dictionary, said first reference to the first dictionary being associated with a structure portion of a predetermined hierarchical level of the document; means for creating, for said predetermined hierarchical level of the document when a content portion of said predetermined hierarchical level is processed, a second reference to the first dictionary; means for processing a structure portion of a subsequent hierarchical level, wherein said subsequent hierarchical level is lower in the hierarchical structure of the document than the predetermined hierarchical level; means for determining if processing of content for said predetermined hierarchical level is in process; means for copying the second reference to a third reference associated with structure of the subsequent hierarchical level, when said processing of content for said predetermined hierarchical level is determined to be in process; means for copying the first reference to the third reference associated with the structure of the subsequent hierarchical level, when said processing of content for said predetermined hierarchical level is determined not to be in process; means for creating, for said subsequent hierarchical level of the document when a content portion of said subsequent hierarchical level is processed, a second dictionary referenced by a fourth reference; means for processing said content portion of said subsequent hierarchical level using said second dictionary; and means for continuing processing of said content portion of said predetermined hierarchical level after processing of said content portion of said subsequent hierarchical level is complete, using said second reference to said first dictionary, when said processing of content for said predetermined hierarchical level is determined to be in process. | 12. A system for processing a hierarchically structured document, comprising: means for creating a first dictionary having a first set of information including key-value pairs; means for creating a first reference to the first dictionary, said first reference to the first dictionary being associated with a structure portion of a predetermined hierarchical level of the document; means for creating, for said predetermined hierarchical level of the document when a content portion of said predetermined hierarchical level is processed, a second reference to the first dictionary; means for processing a structure portion of a subsequent hierarchical level, wherein said subsequent hierarchical level is lower in the hierarchical structure of the document than the predetermined hierarchical level; means for determining if processing of content for said predetermined hierarchical level is in process; means for copying the second reference to a third reference associated with structure of the subsequent hierarchical level, when said processing of content for said predetermined hierarchical level is determined to be in process; means for copying the first reference to the third reference associated with the structure of the subsequent hierarchical level, when said processing of content for said predetermined hierarchical level is determined not to be in process; means for creating, for said subsequent hierarchical level of the document when a content portion of said subsequent hierarchical level is processed, a second dictionary referenced by a fourth reference; means for processing said content portion of said subsequent hierarchical level using said second dictionary; and means for continuing processing of said content portion of said predetermined hierarchical level after processing of said content portion of said subsequent hierarchical level is complete, using said second reference to said first dictionary, when said processing of content for said predetermined hierarchical level is determined to be in process. 15. A system according to claim 12, further comprising: means for copying the fourth reference to the third reference, after processing of said content portion of said subsequent hierarchical level is complete. | 0.530401 |
1. A method of encoding an image comprising: analyzing, by a computer having one or more processors, colors and spatial features of pixels of the image to identify a text region of the image that is separate from a picture region of the image; generating, by the computer, for a portion of the text region, a mask dividing the portion into background pixels and a plurality of text pixels, wherein the background pixels are identified as pixels with a constant color, the plurality of text pixels are identified as pixels contrasting the constant color, and the plurality of text pixels comprise a plurality of colors; analyzing chrominance values of the plurality of colors to determine a text chrominance; generating, for each text pixel of the plurality of text pixels, a text pixel value to generate a plurality of text pixel values, wherein each text pixel value is based on a luminance of a text pixel for which it was generated; and transmitting an encoding of the portion comprising an encoding of each of the constant color, the mask, the text chrominance and the plurality of text pixel values. | 1. A method of encoding an image comprising: analyzing, by a computer having one or more processors, colors and spatial features of pixels of the image to identify a text region of the image that is separate from a picture region of the image; generating, by the computer, for a portion of the text region, a mask dividing the portion into background pixels and a plurality of text pixels, wherein the background pixels are identified as pixels with a constant color, the plurality of text pixels are identified as pixels contrasting the constant color, and the plurality of text pixels comprise a plurality of colors; analyzing chrominance values of the plurality of colors to determine a text chrominance; generating, for each text pixel of the plurality of text pixels, a text pixel value to generate a plurality of text pixel values, wherein each text pixel value is based on a luminance of a text pixel for which it was generated; and transmitting an encoding of the portion comprising an encoding of each of the constant color, the mask, the text chrominance and the plurality of text pixel values. 10. The method of claim 1 , further comprising generating a subsequent encoding of the image comprising an indication of repeating, from the encoding of the portion, a use of at least one of the constant color, the mask or the text chrominance. | 0.581117 |
1. A method in a computer system for identifying authors that have a relationship, the method comprising: providing documents, each document having one or more authors; clustering of authors to identify author clusters of authors from the provided documents based on co-author relationships between the authors wherein authors have a co-author relationship when the authors co-author a document, wherein the clustering includes: generating a publication vector for each author, a publication vector identifying documents authored by the author; and wherein the clustering is based on distance between the publication vectors; for each author cluster, identifying document clusters of documents from the documents that the authors of the author cluster authored; and upon receiving a request to provide information on a selected author, selecting an author cluster that includes the selected author; displaying an indication of authors that are in the selected author cluster; and displaying an indication of the document clusters identified for the selected author cluster. | 1. A method in a computer system for identifying authors that have a relationship, the method comprising: providing documents, each document having one or more authors; clustering of authors to identify author clusters of authors from the provided documents based on co-author relationships between the authors wherein authors have a co-author relationship when the authors co-author a document, wherein the clustering includes: generating a publication vector for each author, a publication vector identifying documents authored by the author; and wherein the clustering is based on distance between the publication vectors; for each author cluster, identifying document clusters of documents from the documents that the authors of the author cluster authored; and upon receiving a request to provide information on a selected author, selecting an author cluster that includes the selected author; displaying an indication of authors that are in the selected author cluster; and displaying an indication of the document clusters identified for the selected author cluster. 6. The method of claim 1 including identifying descriptions of a topic of the documents of a document cluster. | 0.573471 |
2. The method of claim 1 , further comprising: retrieving, by one or more processors, compiled source code, wherein the compiled source code is compiled such that when user visible strings are extracted from a bundle and sent to text attributes of controls, a key and a name of the bundle are also written to the controls, providing a mapping between the bundle location of the string and the key used to extract the user visible strings. | 2. The method of claim 1 , further comprising: retrieving, by one or more processors, compiled source code, wherein the compiled source code is compiled such that when user visible strings are extracted from a bundle and sent to text attributes of controls, a key and a name of the bundle are also written to the controls, providing a mapping between the bundle location of the string and the key used to extract the user visible strings. 3. The method of claim 2 , wherein alternative strings from the second language bundle are embedded in the compiled source code. | 0.904734 |
1. A method comprising: receiving, from a first entity, a request to generate a model, wherein the request comprises input data and a seed model; receiving a cost function associated with generation of the model, the cost function indicating an accuracy and one of speed and memory usage, wherein the cost function is formulated as:
Accscore( ASR ( Xi ))= f ( Xi )→word accuracy and speed where the following definitions apply:
f min( Xi )=−1*(word accuracy−β*speed),
speed=(CPU time)/(audio time), β=a weighting factor to speed that provides a tradeoff between accuracy and speed, Xi=a set of parameters that affect accuracy and speed, such as beam width, LM scale, MAP multiplier, maximum active arcs, duration scale; processing, at a second entity, the input data based on the seed model and based on parameters that modify one of the accuracy and the one of the speed and the memory usage of the cost function, to yield an updated model; and outputting the updated model. | 1. A method comprising: receiving, from a first entity, a request to generate a model, wherein the request comprises input data and a seed model; receiving a cost function associated with generation of the model, the cost function indicating an accuracy and one of speed and memory usage, wherein the cost function is formulated as:
Accscore( ASR ( Xi ))= f ( Xi )→word accuracy and speed where the following definitions apply:
f min( Xi )=−1*(word accuracy−β*speed),
speed=(CPU time)/(audio time), β=a weighting factor to speed that provides a tradeoff between accuracy and speed, Xi=a set of parameters that affect accuracy and speed, such as beam width, LM scale, MAP multiplier, maximum active arcs, duration scale; processing, at a second entity, the input data based on the seed model and based on parameters that modify one of the accuracy and the one of the speed and the memory usage of the cost function, to yield an updated model; and outputting the updated model. 4. The method of claim 1 , wherein processing the input data further comprises one of building the updated model, tuning the updated model, and certifying the updated model. | 0.73716 |
10. The information processing apparatus according to claim 9 , wherein: said score calculation unit further includes, as the group of functions for performing said recursive calculation, a second-type function of associating a substructure between a second node of interest and a parent node in said query pattern with a second range in said sentence, recursively calling, for each attempt position separating descendants of a parent-side end child node and a sibling node of said second node of interest, said first-type function in an opposite direction for a range on the side opposite to said parent with the attempt position of said second range as a boundary and recursively calling said first-type function in the forward direction for a parent-side range to output a partial score for all the attempt positions; and said first-type function recursively calls said forward-direction first-type function as well as recursively calling said second-type function in a forward direction for the parent-side range with the attempt position of said first range as a boundary. | 10. The information processing apparatus according to claim 9 , wherein: said score calculation unit further includes, as the group of functions for performing said recursive calculation, a second-type function of associating a substructure between a second node of interest and a parent node in said query pattern with a second range in said sentence, recursively calling, for each attempt position separating descendants of a parent-side end child node and a sibling node of said second node of interest, said first-type function in an opposite direction for a range on the side opposite to said parent with the attempt position of said second range as a boundary and recursively calling said first-type function in the forward direction for a parent-side range to output a partial score for all the attempt positions; and said first-type function recursively calls said forward-direction first-type function as well as recursively calling said second-type function in a forward direction for the parent-side range with the attempt position of said first range as a boundary. 11. The information processing apparatus according to claim 10 , wherein: said first-type function gives an end child node on the side opposite to said parent of said first node of interest when calling said forward-direction first-type function and gives said first node of interest when calling said forward-direction second-type function; and said second-type function gives said parent-side end child node of said second node of interest when calling said opposite-direction first-type function and gives said sibling node of said second node of interest when calling said forward-direction first-type function. | 0.619926 |
7. A method of delivering a document from a server to a remote electronic device, comprising: building a graph structure representing a map of said document, said graph structure having a plurality of nodes, said nodes including one or more hyperlink nodes each having a corresponding hyperlink and one or more bookmark nodes each having a corresponding bookmark, wherein the hyperlink of each of said one or more hyperlink nodes has as its destination the bookmark of one of said one or more bookmark nodes; traversing and paginating said graph structure into successive pages based on a page size limit, wherein each of said nodes is included in one of said successive pages and wherein each of said successive pages has a corresponding page index value; and for each of said nodes that is one of said hyperlink nodes, storing in association with the one of said hyperlink nodes during said traversing and paginating a bookmark page index value, said bookmark page index value being the page index value of the one of said successive pages that includes the one of said bookmark nodes having the bookmark that is the destination of the hyperlink of the one of said hyperlink nodes; transmitting a particular one of said successive pages from said server to said remote electronic device, said particular one of said successive pages containing the hyperlink of one or more of said hyperlink nodes; receiving an information request from said remote electronic device indicating that the hyperlink of a particular one of said one or more of said hyperlink nodes has been activated; identifying the bookmark page index value that is stored in association with the particular one of said one or more of said hyperlink nodes; and transmitting a second one of said successive pages to said remote electronic device, wherein the second one of said successive pages corresponds to the identified bookmark page index value. | 7. A method of delivering a document from a server to a remote electronic device, comprising: building a graph structure representing a map of said document, said graph structure having a plurality of nodes, said nodes including one or more hyperlink nodes each having a corresponding hyperlink and one or more bookmark nodes each having a corresponding bookmark, wherein the hyperlink of each of said one or more hyperlink nodes has as its destination the bookmark of one of said one or more bookmark nodes; traversing and paginating said graph structure into successive pages based on a page size limit, wherein each of said nodes is included in one of said successive pages and wherein each of said successive pages has a corresponding page index value; and for each of said nodes that is one of said hyperlink nodes, storing in association with the one of said hyperlink nodes during said traversing and paginating a bookmark page index value, said bookmark page index value being the page index value of the one of said successive pages that includes the one of said bookmark nodes having the bookmark that is the destination of the hyperlink of the one of said hyperlink nodes; transmitting a particular one of said successive pages from said server to said remote electronic device, said particular one of said successive pages containing the hyperlink of one or more of said hyperlink nodes; receiving an information request from said remote electronic device indicating that the hyperlink of a particular one of said one or more of said hyperlink nodes has been activated; identifying the bookmark page index value that is stored in association with the particular one of said one or more of said hyperlink nodes; and transmitting a second one of said successive pages to said remote electronic device, wherein the second one of said successive pages corresponds to the identified bookmark page index value. 10. The method according to claim 7 , wherein said storing step comprises adding as an attribute to the one of said hyperlink nodes the page index value of the one of said successive pages that includes the one of said bookmark nodes having the bookmark that is the destination of the hyperlink of the one of said hyperlink nodes. | 0.5 |
2. Apparatus for formatting text with justified margins comprising: first means responsive to said text for storing suffixes whch are characters to be prevented from appearing at the ends of lines of justified text, second means for building a formatted line of characters in accordance with said text, and third means for comparing the last character of said formatted line with the stored characters that are to be prevented from being at the end of a line and for placing that character at the beginning of the next line if it is one of the stored characters. | 2. Apparatus for formatting text with justified margins comprising: first means responsive to said text for storing suffixes whch are characters to be prevented from appearing at the ends of lines of justified text, second means for building a formatted line of characters in accordance with said text, and third means for comparing the last character of said formatted line with the stored characters that are to be prevented from being at the end of a line and for placing that character at the beginning of the next line if it is one of the stored characters. 4. The apparatus as set forth in claim 2 wherein the suffixes and prefixes are identical by a command buried in the text to be formatted. | 0.834813 |
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