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8,489,438 | 1 | 9 | 1. A method for providing voice reviews for an entity comprising: receiving, by a review framework separate from the entity, a call from a first user reviewing the entity; identifying an entity identifier for the entity; recording, during the call, a voice review comprising comments from the first user about the entity, wherein the voice review comprises an audio component and a video component; storing the voice review and the entity identifier in a review map within the review framework, wherein the voice review is included in the voice reviews that are stored in the review map; processing, by a computer processor executing the review framework, the voice review to obtain a language rating defining an audience appropriate maturity level of the comments in the voice review; receiving, from a second user in a vehicle, a search request comprising attributes associated with the voice reviews, wherein the attributes comprise a limitation on a type of language; comparing, by the computer processor, the voice review and the attributes to generate a match, wherein the comparing comprises matching the limitation on the type of language to the language rating of the voice review; including the voice review in an evaluation list based on the match; sending, based on a selection from the evaluation list by the second user, the voice review to the second user to evaluate the entity, wherein sending the voice review comprises: displaying the entity and the evaluation list on a map of a global positioning system (GPS) in the vehicle; receiving, from the second user and using the GPS, the selection of the voice review from the evaluation list in response to displaying the evaluation list; and playing back, using the GPS, the voice review to the second user; receiving, from the second user, by the computer processor, a voice review rating defining a reliability factor of the comments in the voice review and a reliability factor of the first user to the second user in evaluating the entity, wherein the voice review rating is based at least on the second user listening to the voice review; storing the voice review rating and the language rating with the voice review, wherein the voice review rating and the language rating are used by a third user to determine whether to listen to the voice review. | 1. A method for providing voice reviews for an entity comprising: receiving, by a review framework separate from the entity, a call from a first user reviewing the entity; identifying an entity identifier for the entity; recording, during the call, a voice review comprising comments from the first user about the entity, wherein the voice review comprises an audio component and a video component; storing the voice review and the entity identifier in a review map within the review framework, wherein the voice review is included in the voice reviews that are stored in the review map; processing, by a computer processor executing the review framework, the voice review to obtain a language rating defining an audience appropriate maturity level of the comments in the voice review; receiving, from a second user in a vehicle, a search request comprising attributes associated with the voice reviews, wherein the attributes comprise a limitation on a type of language; comparing, by the computer processor, the voice review and the attributes to generate a match, wherein the comparing comprises matching the limitation on the type of language to the language rating of the voice review; including the voice review in an evaluation list based on the match; sending, based on a selection from the evaluation list by the second user, the voice review to the second user to evaluate the entity, wherein sending the voice review comprises: displaying the entity and the evaluation list on a map of a global positioning system (GPS) in the vehicle; receiving, from the second user and using the GPS, the selection of the voice review from the evaluation list in response to displaying the evaluation list; and playing back, using the GPS, the voice review to the second user; receiving, from the second user, by the computer processor, a voice review rating defining a reliability factor of the comments in the voice review and a reliability factor of the first user to the second user in evaluating the entity, wherein the voice review rating is based at least on the second user listening to the voice review; storing the voice review rating and the language rating with the voice review, wherein the voice review rating and the language rating are used by a third user to determine whether to listen to the voice review. 9. The method of claim 1 , further comprising: saving the voice review in at least one selected from a group consisting of the GPS and a space associated with the second user in the review framework; and sending, based on instructions from the second user, the voice review to a third user to share the voice review. | 0.769006 |
9,311,528 | 5 | 6 | 5. The method of claim 1 wherein the interactive feedback mechanism comprises an animated hand together with one or more motion indications. | 5. The method of claim 1 wherein the interactive feedback mechanism comprises an animated hand together with one or more motion indications. 6. The method of claim 5 wherein the animated hand comprises one or more items selected from the group consisting of: a line drawing, a three-dimensional rendering, and a translucent shadow of a hand. | 0.5671 |
4,078,319 | 8 | 10 | 8. A method as defined in claim 1 which further includes providing an external source of rhythmically repeated, sensible sensations, and instructing the reader to coordinate the timing of his eye movements with the tempo of said rhythmic sensations. | 8. A method as defined in claim 1 which further includes providing an external source of rhythmically repeated, sensible sensations, and instructing the reader to coordinate the timing of his eye movements with the tempo of said rhythmic sensations. 10. A method as defined in claim 8 wherein said source comprises a metronome adapted to emit a visible signal. | 0.5 |
8,352,457 | 8 | 12 | 8. A non-transitory computer accessible memory medium storing program instructions for dynamically generating an XQuery for an XML database that stores a plurality of non-XML text documents, each non-XML document having a corresponding shadow XML document in a collection of shadow XML documents in the XML database, wherein the collection contains the corresponding shadow XML documents on which the XQuery is to be executed, wherein each shadow XML document comprises metadata extracted from the corresponding non-XML text document and wherein the XML database is configured for executing an XQuery on the shadow XML documents and for retrieving corresponding non-XML text documents, wherein the program instructions are executable to: provide a FLWOR expression comprising a plurality of units of XQuery code, the plurality of units being predefined based on the non-XML text documents and comprising at least one predefined text retrieval function, wherein the FLWOR expression comprises a for clause predefined based on the shadow XML documents in the collection of shadow XML documents corresponding to the non-XML text documents, wherein the for clause indicates the collection of shadow XML documents and a doctype; and combine the one or more units according to dynamic input from a user to generate the XQuery, the dynamic input from the user defining a where clause including at least one dynamically defined condition for the XQuery. | 8. A non-transitory computer accessible memory medium storing program instructions for dynamically generating an XQuery for an XML database that stores a plurality of non-XML text documents, each non-XML document having a corresponding shadow XML document in a collection of shadow XML documents in the XML database, wherein the collection contains the corresponding shadow XML documents on which the XQuery is to be executed, wherein each shadow XML document comprises metadata extracted from the corresponding non-XML text document and wherein the XML database is configured for executing an XQuery on the shadow XML documents and for retrieving corresponding non-XML text documents, wherein the program instructions are executable to: provide a FLWOR expression comprising a plurality of units of XQuery code, the plurality of units being predefined based on the non-XML text documents and comprising at least one predefined text retrieval function, wherein the FLWOR expression comprises a for clause predefined based on the shadow XML documents in the collection of shadow XML documents corresponding to the non-XML text documents, wherein the for clause indicates the collection of shadow XML documents and a doctype; and combine the one or more units according to dynamic input from a user to generate the XQuery, the dynamic input from the user defining a where clause including at least one dynamically defined condition for the XQuery. 12. The non-transitory computer accessible memory medium of claim 8 , wherein the non-XML text documents comprise one or more of Microsoft Office documents or Adobe PDF documents. | 0.688153 |
10,127,222 | 1 | 9 | 1. A method, comprising: receiving, by a processing system of a first communication device including a processor, input data comprising a group of words inputted via a user interface of the first communication device; performing, by the processing system, auto-correction of a target word included in the group of words to generate a corrected text message; receiving, by the processing system, via the user interface a request to transmit the corrected text message to a second communication device; responsive to the receiving the request, presenting, by the processing system, a correction alert at the first communication device, the correction alert comprising an audio signal to indicate that the target word has been auto-corrected, wherein the correction alert is selected from provisioning information accessible to the processing system, wherein the provisioning information is accessed to select the audio signal, wherein the selected audio signal is indexed to an intended recipient of the corrected text message, a subject matter of the corrected text message, or a type of the target word; and responsive to the presenting the correction alert, presenting, by the first communication device, an option for modifying the target word prior to initiating a transmission of the corrected text message. | 1. A method, comprising: receiving, by a processing system of a first communication device including a processor, input data comprising a group of words inputted via a user interface of the first communication device; performing, by the processing system, auto-correction of a target word included in the group of words to generate a corrected text message; receiving, by the processing system, via the user interface a request to transmit the corrected text message to a second communication device; responsive to the receiving the request, presenting, by the processing system, a correction alert at the first communication device, the correction alert comprising an audio signal to indicate that the target word has been auto-corrected, wherein the correction alert is selected from provisioning information accessible to the processing system, wherein the provisioning information is accessed to select the audio signal, wherein the selected audio signal is indexed to an intended recipient of the corrected text message, a subject matter of the corrected text message, or a type of the target word; and responsive to the presenting the correction alert, presenting, by the first communication device, an option for modifying the target word prior to initiating a transmission of the corrected text message. 9. The method of claim 1 , further comprising providing, by the processing system, a recipient alert with the transmission of the corrected text message to the second communication device, wherein the recipient alert enables the second communication device to obtain an unmodified version of the target word. | 0.677149 |
8,239,184 | 11 | 12 | 11. A method of teaching language or numeric skills in multiple spoken languages using the fast and engaging, real-time voice translation system of claim 1 , comprising setting the operational states of the system, wherein the setting includes setting the source language and the destination language, and optionally includes setting a vocabulary database, an output pace, automatic mode, interactive mode, or microphone on/off; providing the source phrase to the translation engine; and outputting the spoken translation to teach language or numeric skills in the language selected from the multiple languages by the user. | 11. A method of teaching language or numeric skills in multiple spoken languages using the fast and engaging, real-time voice translation system of claim 1 , comprising setting the operational states of the system, wherein the setting includes setting the source language and the destination language, and optionally includes setting a vocabulary database, an output pace, automatic mode, interactive mode, or microphone on/off; providing the source phrase to the translation engine; and outputting the spoken translation to teach language or numeric skills in the language selected from the multiple languages by the user. 12. The method of claim 11 , wherein the setting comprises setting a state selector to a category associated with a plurality of source phrases, wherein the source phrases are stored in the memory of the system, and one of the source phrases is translated into a destination phrase, wherein both the plurality of source phrases and the destination phrase are in languages selected from multiple languages. | 0.728916 |
9,576,578 | 14 | 19 | 14. A computer-implemented method comprising: obtaining, by an automated speech recognizer, audio data encoding an utterance; obtaining, by the automated speech recognizer, one or more initial candidate transcriptions for the utterance based on the audio data; transmitting, by the automated speech recognizer, the one or more initial candidate transcriptions for the utterance; in response to transmitting the one or more initial candidate transcriptions for the utterance, receiving, by the automated speech recognizer, one or more additional candidate transcriptions that each include an alternate term that (i) does not occur in the candidate transcriptions that are output by the automated speech recognizer, and (ii) are indicated as phonetically similar to one or more terms that do occur in the initial candidate transcriptions that are output by the automated speech recognizer; after receiving the one or more additional candidate transcriptions, generating, by the automated speech recognizer, a score for each of the initial candidate transcriptions and the additional candidate transcriptions based on the audio data; selecting, by the automated speech recognizer, a particular candidate transcription, from among the initial candidate transcriptions and the additional candidate transcriptions, based at least on the score; and providing, by the automated speech recognizer, the particular candidate transcription for output. | 14. A computer-implemented method comprising: obtaining, by an automated speech recognizer, audio data encoding an utterance; obtaining, by the automated speech recognizer, one or more initial candidate transcriptions for the utterance based on the audio data; transmitting, by the automated speech recognizer, the one or more initial candidate transcriptions for the utterance; in response to transmitting the one or more initial candidate transcriptions for the utterance, receiving, by the automated speech recognizer, one or more additional candidate transcriptions that each include an alternate term that (i) does not occur in the candidate transcriptions that are output by the automated speech recognizer, and (ii) are indicated as phonetically similar to one or more terms that do occur in the initial candidate transcriptions that are output by the automated speech recognizer; after receiving the one or more additional candidate transcriptions, generating, by the automated speech recognizer, a score for each of the initial candidate transcriptions and the additional candidate transcriptions based on the audio data; selecting, by the automated speech recognizer, a particular candidate transcription, from among the initial candidate transcriptions and the additional candidate transcriptions, based at least on the score; and providing, by the automated speech recognizer, the particular candidate transcription for output. 19. The method of claim 14 , wherein selecting the particular candidate transcription from among the initial candidate transcriptions and the additional candidate transcriptions, comprises: comparing the score for each of the initial candidate transcriptions and the additional candidate transcriptions; determining, based at least on comparing the score for each of the initial candidate transcriptions and the additional candidate transcriptions, that a score for a particular candidate transcription indicates a higher likelihood than the score for each of the initial candidate transcriptions that the particular candidate transcription represents an accurate transcription of the audio date; and selecting the particular transcription for output. | 0.5 |
7,761,858 | 16 | 30 | 16. A system for compiling a natural language software application based on a set of programming constructs utilized to model semantics of a natural language, the system comprising: a computer readable storage medium to store instructions comprising: a programming language comprising a set of programming constructs for facilitating programming of natural language software applications, the set of programming constructs including a plurality of types that correspond to declarative linguistic elements of a linguistic object model, each type of the plurality of types being independent of a particular spoken language, the plurality of types comprising: an entity type derived from an entity base class having data members, properties, and methods, the entity type adapted to model noun phrases and adjective phrases; a frame type derived from a frame base class and adapted to model semantic events including verbs and nouns; a restriction type derived from a restriction base class and adapted to model oblique arguments, modifiers, and other semantic elements, the restriction type to define semantic relationships between entities and constraints on objects derived from the plurality of types, the restriction type adapted to normalize relationship semantics across syntactic representations; a denoter representing a privileged data member to map entity objects instantiated from the entity type to natural language words; and a framework including a plurality of clauses associated with each of the plurality of types, the plurality of clauses including a begin clause, a success clause, and a fail clause to resolve the existence of each of the plurality of types at runtime; and a compiler adapted to take source code containing instances of the set of programming constructs and the framework and to generate computer readable machine code and declarative schema; and a processor having access to the computer readable storage medium, the processor adapted to receive a set of instructions including selected constructs from the set of programming constructs and the framework, the processor adapted to execute the compiler to compile the set of instructions into a natural language software application. | 16. A system for compiling a natural language software application based on a set of programming constructs utilized to model semantics of a natural language, the system comprising: a computer readable storage medium to store instructions comprising: a programming language comprising a set of programming constructs for facilitating programming of natural language software applications, the set of programming constructs including a plurality of types that correspond to declarative linguistic elements of a linguistic object model, each type of the plurality of types being independent of a particular spoken language, the plurality of types comprising: an entity type derived from an entity base class having data members, properties, and methods, the entity type adapted to model noun phrases and adjective phrases; a frame type derived from a frame base class and adapted to model semantic events including verbs and nouns; a restriction type derived from a restriction base class and adapted to model oblique arguments, modifiers, and other semantic elements, the restriction type to define semantic relationships between entities and constraints on objects derived from the plurality of types, the restriction type adapted to normalize relationship semantics across syntactic representations; a denoter representing a privileged data member to map entity objects instantiated from the entity type to natural language words; and a framework including a plurality of clauses associated with each of the plurality of types, the plurality of clauses including a begin clause, a success clause, and a fail clause to resolve the existence of each of the plurality of types at runtime; and a compiler adapted to take source code containing instances of the set of programming constructs and the framework and to generate computer readable machine code and declarative schema; and a processor having access to the computer readable storage medium, the processor adapted to receive a set of instructions including selected constructs from the set of programming constructs and the framework, the processor adapted to execute the compiler to compile the set of instructions into a natural language software application. 30. The system of claim 16 wherein the computer readable machine code comprises: a set of resolvable types for selecting between linguistically possible types, each resolvable type being processed according to resolution semantics to determine if an instance of the resolvable type exists. | 0.599723 |
10,127,022 | 50 | 53 | 50. A method of developing a dataflow program comprising: using a graphical user interface to specify a graphical representation of a dataflow program, the program comprising producer types, transducer types, and extractor types, wherein through the graphical user interface, a user can select and move the producer types, transducer types, and extractor types, represented using blocks, into various positions on a computer screen; using the graphical user interface, allowing the user to interconnect via interconnection links the blocks representing the producer types, transducer types, and extractor types; allowing the user to specify internals of each of the blocks through the graphical user interface, wherein for a transducer type block, the user can specify an operation; automatically generating computer source code that corresponds to the dataflow program the user specified using the graphical user interface; allowing the user to view and edit the computer source code automatically generated in a textual interface; and allowing the user to specify generating of a computer package of code executable on a target hardware platform that is an implementation of the dataflow program specified by the user using the graphical user interface. | 50. A method of developing a dataflow program comprising: using a graphical user interface to specify a graphical representation of a dataflow program, the program comprising producer types, transducer types, and extractor types, wherein through the graphical user interface, a user can select and move the producer types, transducer types, and extractor types, represented using blocks, into various positions on a computer screen; using the graphical user interface, allowing the user to interconnect via interconnection links the blocks representing the producer types, transducer types, and extractor types; allowing the user to specify internals of each of the blocks through the graphical user interface, wherein for a transducer type block, the user can specify an operation; automatically generating computer source code that corresponds to the dataflow program the user specified using the graphical user interface; allowing the user to view and edit the computer source code automatically generated in a textual interface; and allowing the user to specify generating of a computer package of code executable on a target hardware platform that is an implementation of the dataflow program specified by the user using the graphical user interface. 53. The method of claim 50 comprising: providing the user with performance semantic-level debugging capabilities. | 0.845205 |
8,620,667 | 1 | 3 | 1. A computer-implemented method of supporting speech-activated user commands, the method comprising: activating a speech-activated command and control application; launching speech support based at least in part upon the activation of the speech-activated command and control application; performing a plurality of queries against a search engine interface, comprising a web service, to obtain a collection of human language terms from a remote source through the web service, the human language terms pertaining to a system resource, the plurality of queries being directed locally and through the web service to a plurality of different sources, one of the plurality of different sources including a central database having application capability and characteristic information, a second one of the plurality of different sources including a descriptive information file that includes application description and explanation information, a third one of the plurality of different sources including directly obtaining information from a plurality of individual applications, wherein at least one term in the collection does not describe the identity of the system resource, wherein the plurality of queries include specifications of what should be included in the collection of human language terms, wherein the collection of human language terms includes query results received in response to the plurality of queries, and wherein content of the collection of human language terms is automatically determined, by a computer processor that is a functional component of a computer, to be consistent with said specifications; incorporating the collection of human language terms into a grammar, wherein the grammar includes action words including run, launch, load and start, wherein the grammar defines a collection of terms that have a logical connection to the system resource, wherein the grammar also defines other terms that have logical connections to other system resources, wherein the other terms that have the logical connections to the other system resources include names of the other system resources, the names being derived based on analysis of one or more user accessible file systems; receiving a spoken user command; identifying a particular word included in the spoken command; determining that the particular word included in the spoken command is included in the grammar as part of the collection of terms that have a logical connection to the system resource, and wherein the particular word included in the spoken command is one of the collection of human language terms received in response to the query; transmitting an indication of the particular word to the speech-activated command and control application; utilizing the speech-activated command and control application to execute one of a plurality of functions related to the system resource, wherein executing the one of the plurality of functions comprises executing the one function at least partially in response to the determination that the particular word included in the spoken command is included in the grammar as part of the collection of terms that have a logical connection to the system resource; receiving a notification that a new system resource has been added; and reconstructing the grammar to account for the new system resource. | 1. A computer-implemented method of supporting speech-activated user commands, the method comprising: activating a speech-activated command and control application; launching speech support based at least in part upon the activation of the speech-activated command and control application; performing a plurality of queries against a search engine interface, comprising a web service, to obtain a collection of human language terms from a remote source through the web service, the human language terms pertaining to a system resource, the plurality of queries being directed locally and through the web service to a plurality of different sources, one of the plurality of different sources including a central database having application capability and characteristic information, a second one of the plurality of different sources including a descriptive information file that includes application description and explanation information, a third one of the plurality of different sources including directly obtaining information from a plurality of individual applications, wherein at least one term in the collection does not describe the identity of the system resource, wherein the plurality of queries include specifications of what should be included in the collection of human language terms, wherein the collection of human language terms includes query results received in response to the plurality of queries, and wherein content of the collection of human language terms is automatically determined, by a computer processor that is a functional component of a computer, to be consistent with said specifications; incorporating the collection of human language terms into a grammar, wherein the grammar includes action words including run, launch, load and start, wherein the grammar defines a collection of terms that have a logical connection to the system resource, wherein the grammar also defines other terms that have logical connections to other system resources, wherein the other terms that have the logical connections to the other system resources include names of the other system resources, the names being derived based on analysis of one or more user accessible file systems; receiving a spoken user command; identifying a particular word included in the spoken command; determining that the particular word included in the spoken command is included in the grammar as part of the collection of terms that have a logical connection to the system resource, and wherein the particular word included in the spoken command is one of the collection of human language terms received in response to the query; transmitting an indication of the particular word to the speech-activated command and control application; utilizing the speech-activated command and control application to execute one of a plurality of functions related to the system resource, wherein executing the one of the plurality of functions comprises executing the one function at least partially in response to the determination that the particular word included in the spoken command is included in the grammar as part of the collection of terms that have a logical connection to the system resource; receiving a notification that a new system resource has been added; and reconstructing the grammar to account for the new system resource. 3. The method of claim 1 , wherein: the system resource is a software application; obtaining the collection of terms further comprises obtaining a collection of terms that include attributes of the software application; the collection of terms includes words that describe functions, from the perspective of a user of the software application, that the software application is configured to perform; and the attributes of the software application include a capability of the software application. | 0.576792 |
9,519,731 | 1 | 3 | 1. A computer implemented method for determining a heating, ventilation, and air conditioning (HVAC) model for a building, comprising: receiving, by a processor, a description of the building from a user, wherein the description of the building includes physical connections between components of an HVAC system of the building; receiving, by the processor, an HVAC meta-model, wherein the HVAC meta-model is independent of the building; determining, by the processor, a predictive HVAC model for the building based on the description of the building and the HVAC meta-model; and using, by the processor, the predictive HVAC model for the building to control the HVAC system of the building based on predicted operating conditions of the components of the HVAC system, wherein the predicted operating conditions include a predicted water temperature and a predicted water velocity of a boiler of the HVAC system. | 1. A computer implemented method for determining a heating, ventilation, and air conditioning (HVAC) model for a building, comprising: receiving, by a processor, a description of the building from a user, wherein the description of the building includes physical connections between components of an HVAC system of the building; receiving, by the processor, an HVAC meta-model, wherein the HVAC meta-model is independent of the building; determining, by the processor, a predictive HVAC model for the building based on the description of the building and the HVAC meta-model; and using, by the processor, the predictive HVAC model for the building to control the HVAC system of the building based on predicted operating conditions of the components of the HVAC system, wherein the predicted operating conditions include a predicted water temperature and a predicted water velocity of a boiler of the HVAC system. 3. The method of claim 1 , wherein the HVAC meta-model includes a number of rules for determining an HVAC model. | 0.525424 |
8,635,218 | 7 | 12 | 7. A method for transforming a first document into a second document, the second document configured for use at an electronic device, the method comprising: receiving user interface information about the electronic device; selecting content rules for modifying content in the first document according to the user interface information; selecting presentation rules for presenting the content from the first document according to the user interface information; and combining the content rules and presentation rules to form transformation instructions for transforming the first document into the second document; and wherein the user interface information includes at least one of screen size and keypad type. | 7. A method for transforming a first document into a second document, the second document configured for use at an electronic device, the method comprising: receiving user interface information about the electronic device; selecting content rules for modifying content in the first document according to the user interface information; selecting presentation rules for presenting the content from the first document according to the user interface information; and combining the content rules and presentation rules to form transformation instructions for transforming the first document into the second document; and wherein the user interface information includes at least one of screen size and keypad type. 12. The method of claim 7 , further comprising transforming the first markup document into the second document using the transformation instructions. | 0.682979 |
4,724,523 | 69 | 74 | 69. A method according to claim 66 in which said third coding step comprises storing a signal representative of at least one addressable other elemental expression of a paradigm of which said corresponding stored entry is an element. | 69. A method according to claim 66 in which said third coding step comprises storing a signal representative of at least one addressable other elemental expression of a paradigm of which said corresponding stored entry is an element. 74. A method according to claim 69 in which said inflecting step comprises responding to said input expression being of verbal grammatical class and of present participle inflectional class for (i) generating a signal representative of an expression having a doubled stem-final consonant and a suffix "ing", for selected related expressions, and (ii) generating a signal representative of an expression having a suffix "ing", for other said selected related expressions. | 0.807377 |
8,306,806 | 9 | 15 | 9. A method, comprising: retrieving one or more bilingual web pages from at least one website using a search engine that is executed on a computing device, each bilingual web page including a plurality of terms that comprise a search term and one or more additional terms in a first language; forming a plurality of candidate translation pairs by selecting one or more candidate translations for each of the plurality of terms, and creating each candidate translation pair by pairing one of the one or more candidate translations and a corresponding term of the plurality of terms; extracting one or more translation layout patterns from the plurality of candidate translation pairs; computing one or more features based on at least one of the terms using the computing device, the one or more features including a context similarity feature that compares a similarity between a context of a term in the first language and a context of a corresponding candidate translation in a second language; deriving a term translation in the second language for the search term in the first language based on a hidden conditional random field (HCRF) model stored on the computing device that includes the one or more candidate translations, the one or more translation layout patterns, and the one or more features, the HCRF model including a hidden variable that represents the one or more translation layout patterns; and storing the term translation in a lexicon repository. | 9. A method, comprising: retrieving one or more bilingual web pages from at least one website using a search engine that is executed on a computing device, each bilingual web page including a plurality of terms that comprise a search term and one or more additional terms in a first language; forming a plurality of candidate translation pairs by selecting one or more candidate translations for each of the plurality of terms, and creating each candidate translation pair by pairing one of the one or more candidate translations and a corresponding term of the plurality of terms; extracting one or more translation layout patterns from the plurality of candidate translation pairs; computing one or more features based on at least one of the terms using the computing device, the one or more features including a context similarity feature that compares a similarity between a context of a term in the first language and a context of a corresponding candidate translation in a second language; deriving a term translation in the second language for the search term in the first language based on a hidden conditional random field (HCRF) model stored on the computing device that includes the one or more candidate translations, the one or more translation layout patterns, and the one or more features, the HCRF model including a hidden variable that represents the one or more translation layout patterns; and storing the term translation in a lexicon repository. 15. The method of claim 9 , wherein the retrieving includes retrieving the one or more bilingual web pages using a query based on the search term and one or more trigger words. | 0.806593 |
9,230,356 | 26 | 27 | 26. The system of claim 25 , wherein the second modification is associated with a graphical element of the document. | 26. The system of claim 25 , wherein the second modification is associated with a graphical element of the document. 27. The system of claim 26 , wherein the instructions further cause: animating the graphical element on the display of the first device. | 0.5 |
10,146,751 | 4 | 5 | 4. The computer-implemented method of claim 1 , wherein the second term is identified as referring to or representing the second attribute, the method further comprising: assigning a term weight value to the first term based on the second attribute, wherein the function of the term weight value includes at least being a term importance value for document summarization, tagging and search result ranking. | 4. The computer-implemented method of claim 1 , wherein the second term is identified as referring to or representing the second attribute, the method further comprising: assigning a term weight value to the first term based on the second attribute, wherein the function of the term weight value includes at least being a term importance value for document summarization, tagging and search result ranking. 5. The computer-implemented method of claim 4 , further comprising: determining a weighting co-efficient value for the second attribute, wherein the term weight value assigned to the first term is determined based on the weighting co-efficient value. | 0.5 |
7,610,315 | 11 | 16 | 11. A system comprising: a user interface device; a document control component comprising a hierarchical knowledge structure including document control policies, including at least one document control policy inherited by a parent node in accordance with an algebraic maximum of rules associated with child nodes of the parent node; and one or more computers operable to interact with the user interface device and the document control component to determine a genre classification for a document, compare the genre classification with the hierarchical knowledge structure to identify a relevant node among multiple nodes, including the parent node, and recommend at least one document control policy to govern access to the document based on the identified relevant node in the hierarchical knowledge structure, the relevant node identified by successively comparing multiple terms in the genre classification with the hierarchical knowledge structure based on hierarchical positions of the terms until either a matching node in the hierarchical knowledge structure is found or the term in the highest hierarchical position of the multiple terms is reached and no matching node is found in which case a document control policy corresponding to a root node is used, and when the hierarchical knowledge structure of the document control component differs from a hierarchical knowledge structure used for determining the genre classification, the one or more computers being operable to identify a correlation between the different knowledge structures. | 11. A system comprising: a user interface device; a document control component comprising a hierarchical knowledge structure including document control policies, including at least one document control policy inherited by a parent node in accordance with an algebraic maximum of rules associated with child nodes of the parent node; and one or more computers operable to interact with the user interface device and the document control component to determine a genre classification for a document, compare the genre classification with the hierarchical knowledge structure to identify a relevant node among multiple nodes, including the parent node, and recommend at least one document control policy to govern access to the document based on the identified relevant node in the hierarchical knowledge structure, the relevant node identified by successively comparing multiple terms in the genre classification with the hierarchical knowledge structure based on hierarchical positions of the terms until either a matching node in the hierarchical knowledge structure is found or the term in the highest hierarchical position of the multiple terms is reached and no matching node is found in which case a document control policy corresponding to a root node is used, and when the hierarchical knowledge structure of the document control component differs from a hierarchical knowledge structure used for determining the genre classification, the one or more computers being operable to identify a correlation between the different knowledge structures. 16. The system of claim 11 , the one or more computers further operable to derive a document control policy for a parent node in the hierarchical knowledge structure, in the document control component, based on a combination of multiple document control policies associated with child nodes of the parent node in the hierarchical knowledge structure of the document control component; and to associate the derived document control policy with the parent node in the hierarchical knowledge structure of the document control component. | 0.669355 |
9,098,551 | 1 | 4 | 1. A computer-implemented method for ranking content entities by their associated web pages and search queries, the method comprising: at a computer system having memory and one or more processors: performing an automated textual analysis on one or more predefined websites to identify a plurality of reference web pages, further including determining content information and one or more corresponding search queries for each reference web page, wherein a reference web page is a web page whose content information provides an accurate description of a particular content entity; for a respective content entity: identifying a subset of the reference web pages associated with the respective content entity and the corresponding search queries based on the content information of the reference web pages and query terms of the corresponding search queries; and inferring a popularity ranking for the respective content entity based on one or more server and/or search logs of user interactions with the identified subset of reference web pages and the corresponding search queries; and in response to a user search request related to one or more content entities, selecting at least a subset of the content entities for display to an end user in accordance with their respective popularity rankings. | 1. A computer-implemented method for ranking content entities by their associated web pages and search queries, the method comprising: at a computer system having memory and one or more processors: performing an automated textual analysis on one or more predefined websites to identify a plurality of reference web pages, further including determining content information and one or more corresponding search queries for each reference web page, wherein a reference web page is a web page whose content information provides an accurate description of a particular content entity; for a respective content entity: identifying a subset of the reference web pages associated with the respective content entity and the corresponding search queries based on the content information of the reference web pages and query terms of the corresponding search queries; and inferring a popularity ranking for the respective content entity based on one or more server and/or search logs of user interactions with the identified subset of reference web pages and the corresponding search queries; and in response to a user search request related to one or more content entities, selecting at least a subset of the content entities for display to an end user in accordance with their respective popularity rankings. 4. The method of claim 1 , wherein the content information of a respective reference web page includes one or more of title, release time, running time, director, writer, plot, producer, starring, cinematographer, editing by, music by, studio, country of release, language, budget, box office, and genre of a respective content entity that is a subject of the reference web page. | 0.712443 |
7,721,203 | 10 | 11 | 10. The computer-readable storage medium of claim 9 , further comprising: receiving a fourth character of the sequence of input characters; and when the first character, the second character, and the fourth character do not form the at least one valid sequence of characters according to the rules associated with forming the complex character, displaying the complex character formed by the first character and the second character. | 10. The computer-readable storage medium of claim 9 , further comprising: receiving a fourth character of the sequence of input characters; and when the first character, the second character, and the fourth character do not form the at least one valid sequence of characters according to the rules associated with forming the complex character, displaying the complex character formed by the first character and the second character. 11. The computer-readable storage medium of claim 10 , further comprising: when the first character, the second character, and the fourth character do not form the at least one valid sequence of characters according to the rules associated with forming the complex character, discarding the fourth character. | 0.674419 |
8,131,647 | 1 | 17 | 1. A computer-implemented method for providing an annotation of a digital work, comprising: under control of instructions that are executed by one or more computing devices: receiving multiple annotations from different authors for particular content in a digital work; storing the annotations in association with the digital work; providing a list of abbreviated versions of the annotations to a user desiring to access one or more of the annotations, wherein the list presents the annotations in an order determined by reference to a criterion; receiving an authorization credential from a user desiring to access one or more of the annotations; and if the authorization credential is valid, providing a full version of one or more of the annotations of the digital work to the user in context with regard to the digital work. | 1. A computer-implemented method for providing an annotation of a digital work, comprising: under control of instructions that are executed by one or more computing devices: receiving multiple annotations from different authors for particular content in a digital work; storing the annotations in association with the digital work; providing a list of abbreviated versions of the annotations to a user desiring to access one or more of the annotations, wherein the list presents the annotations in an order determined by reference to a criterion; receiving an authorization credential from a user desiring to access one or more of the annotations; and if the authorization credential is valid, providing a full version of one or more of the annotations of the digital work to the user in context with regard to the digital work. 17. The method of claim 1 , wherein an annotation, when combined with the digital work to which it pertains, becomes accessible upon accessing the digital work. | 0.662447 |
7,929,769 | 2 | 7 | 2. The computer-readable medium excluding signals, the computer-readable medium of claim 1 having computer-executable instructions to perform: (d) identifying a direction of the writing line; and (e) utilizing the direction of the writing line for classifying the script type of the writing line. | 2. The computer-readable medium excluding signals, the computer-readable medium of claim 1 having computer-executable instructions to perform: (d) identifying a direction of the writing line; and (e) utilizing the direction of the writing line for classifying the script type of the writing line. 7. The computer-readable medium excluding signals, the computer-readable medium of claim 2 , wherein the script type is selected from the group consisting of a Han script and a Roman script, having computer-executable instructions to perform: (f) classifying the script type as the Han script when the direction of the writing line corresponds to a vertical direction. | 0.5 |
7,743,047 | 1 | 3 | 1. A computer-implemented method for modifying a user's search experience, the method comprising: assigning a first set of symbols that represent a first set of actions initiated by the user during creation of a first search trail; assigning a second set of symbols that represent a second set of actions initiated by the user during creation of a second search trail; determining a measure of interaction variance classification that represents an extent to which there are differences between that first and second sets of symbols, wherein determining the measure of interaction variance comprises determining the measure based at least in part on hyperlink navigations initiated by the user and indicated by the first and second sets of symbols; assigning a search behavior classification to the user based at least in part on the measure of interaction variance; and customizing, based at least in part on the assigned search behavior classification, the user's experience with a search process. | 1. A computer-implemented method for modifying a user's search experience, the method comprising: assigning a first set of symbols that represent a first set of actions initiated by the user during creation of a first search trail; assigning a second set of symbols that represent a second set of actions initiated by the user during creation of a second search trail; determining a measure of interaction variance classification that represents an extent to which there are differences between that first and second sets of symbols, wherein determining the measure of interaction variance comprises determining the measure based at least in part on hyperlink navigations initiated by the user and indicated by the first and second sets of symbols; assigning a search behavior classification to the user based at least in part on the measure of interaction variance; and customizing, based at least in part on the assigned search behavior classification, the user's experience with a search process. 3. The method of claim 1 , wherein the assigned search behavior classification is indicative of a data navigation strategy utilized to arrive at a desired item of information at the end of a data searching process. | 0.586873 |
7,870,486 | 1 | 4 | 1. A system for simultaneously commencing output of disparately encoded electronic documents comprising: a document processing device including a processor and associated data storage; means adapted for receiving, into the document processing device, selection data representative of a plurality of different user-selected electronic documents, each of the plurality of documents being encoded in a unique one of a plurality of disparate formats; association means adapted for associating each of the plurality of disparate formats with at least one software module; means adapted for retrieving the plurality of user-selected electronic documents in accordance with received selection data; means adapted for communicating each of the plurality of user-selected electronic documents to one of a plurality of corresponding software modules in accordance with an output of the association means; means adapted for acquiring common document output characteristics associated with each of the plurality of user-selected electronic documents; means adapted for communicating configuration data corresponding to acquired document output characteristics to each of a plurality of unique software modules in a format compatible thereto; and document processor means adapted for commencing a selected document processing operation on each of a series of the user-selected electronic documents by calling a sequence of the software modules, with each module corresponding to one of the series of user-selected electronic documents such that each module is operative in accordance with the common document output characteristics. | 1. A system for simultaneously commencing output of disparately encoded electronic documents comprising: a document processing device including a processor and associated data storage; means adapted for receiving, into the document processing device, selection data representative of a plurality of different user-selected electronic documents, each of the plurality of documents being encoded in a unique one of a plurality of disparate formats; association means adapted for associating each of the plurality of disparate formats with at least one software module; means adapted for retrieving the plurality of user-selected electronic documents in accordance with received selection data; means adapted for communicating each of the plurality of user-selected electronic documents to one of a plurality of corresponding software modules in accordance with an output of the association means; means adapted for acquiring common document output characteristics associated with each of the plurality of user-selected electronic documents; means adapted for communicating configuration data corresponding to acquired document output characteristics to each of a plurality of unique software modules in a format compatible thereto; and document processor means adapted for commencing a selected document processing operation on each of a series of the user-selected electronic documents by calling a sequence of the software modules, with each module corresponding to one of the series of user-selected electronic documents such that each module is operative in accordance with the common document output characteristics. 4. The system for simultaneously commencing output of disparately encoded electronic documents of claim 1 wherein the document processor means includes means adapted for commencing each document processing operation in a selected order. | 0.614379 |
8,156,134 | 10 | 13 | 10. A method, comprising: providing a plurality of first type query translator modules including information indicating a first data store type to which the first query translator modules apply; providing a plurality of second query translator modules including information indicating a second data store type to which the first query translator modules apply; receiving a query to query a target data store, wherein the first and second query translator modules for the first and second data store types include database specific operations to implement query optimization for the first and second data store types to which the first and second query translator modules respectively apply and include first and second resolve modules, respectively; determining whether the target data store is of the first data store type or the second data store type; generating a parse tree of nodes; grouping the nodes according to query parts to produce a query graph; forwarding the query graph to the first or second resolve module from the determined first or second query translator modules to validate that the query attributes are valid attributes in the target data store; and in response to validating the query parts, performing: using the first query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the first data store type; and using the second query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the second data store type. | 10. A method, comprising: providing a plurality of first type query translator modules including information indicating a first data store type to which the first query translator modules apply; providing a plurality of second query translator modules including information indicating a second data store type to which the first query translator modules apply; receiving a query to query a target data store, wherein the first and second query translator modules for the first and second data store types include database specific operations to implement query optimization for the first and second data store types to which the first and second query translator modules respectively apply and include first and second resolve modules, respectively; determining whether the target data store is of the first data store type or the second data store type; generating a parse tree of nodes; grouping the nodes according to query parts to produce a query graph; forwarding the query graph to the first or second resolve module from the determined first or second query translator modules to validate that the query attributes are valid attributes in the target data store; and in response to validating the query parts, performing: using the first query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the first data store type; and using the second query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the second data store type. 13. The method of claim 10 , wherein the first data store comprises an application specific data store and the second data store comprises an object oriented or relational database. | 0.726586 |
9,288,175 | 6 | 10 | 6. A system for extending a conversation across applications, the system comprising a conversation engine and a context engine, wherein: the conversation engine is configured to receive conversation calls from a plurality of applications; the context engine is configured to identify a conversation in a conversation repository having a context that is relevant to a first application object of a first application of the plurality of applications in response to the conversation engine receiving a conversation call from a second application of the plurality of applications; and the conversation engine is configured to cause a user interface to display the identified conversation. | 6. A system for extending a conversation across applications, the system comprising a conversation engine and a context engine, wherein: the conversation engine is configured to receive conversation calls from a plurality of applications; the context engine is configured to identify a conversation in a conversation repository having a context that is relevant to a first application object of a first application of the plurality of applications in response to the conversation engine receiving a conversation call from a second application of the plurality of applications; and the conversation engine is configured to cause a user interface to display the identified conversation. 10. The system of claim 6 , wherein: the conversation repository stores a plurality of conversations each associated with an application object of one of a plurality of applications; the conversation engine is configured to receive an object identifier for the first application in the conversation call from the second application; and the context engine is configured to identify the conversation by querying the conversation repository using the application object identifier for the first application object received by the conversation engine. | 0.5 |
7,519,902 | 6 | 9 | 6. The method as defined in claim 1 , wherein the retrieving the dynamic data document further comprises performing the following sub-steps of: initializing a first list with seed values; checking if there are any URLs to be processed and in response that any URL exists to be processed then performing the following sub-steps of: determining if a URL is in a second list; and in response that a URL is not in the second list then performing the following sub-steps of: inserting the URL into the first list; scheduling the URL for crawling; crawling the URL when scheduled to do so; removing the URL from the first list after the scheduled crawling; entering the URL into the second list; and repeating the checking step until there are no more URLs to be processed; where if the determining step determines that the URL is in the second list then repeating the checking step until there are no more URLs to be processed. | 6. The method as defined in claim 1 , wherein the retrieving the dynamic data document further comprises performing the following sub-steps of: initializing a first list with seed values; checking if there are any URLs to be processed and in response that any URL exists to be processed then performing the following sub-steps of: determining if a URL is in a second list; and in response that a URL is not in the second list then performing the following sub-steps of: inserting the URL into the first list; scheduling the URL for crawling; crawling the URL when scheduled to do so; removing the URL from the first list after the scheduled crawling; entering the URL into the second list; and repeating the checking step until there are no more URLs to be processed; where if the determining step determines that the URL is in the second list then repeating the checking step until there are no more URLs to be processed. 9. The method as defined in claim 6 , wherein the sub-step of crawling further comprises the sub-steps of: issuing an HTTP command to a web server named in the URL; receiving contents of an HTML page as a result of the issued HTTP command; and passing on the contents of the HTML page to a Page Rendering subroutine. | 0.5 |
8,285,721 | 10 | 11 | 10. A system comprising: an item database; a hardware-implemented analysis module communicatively coupled to the item database, the analysis module being configured to: access a seller-generated item description received from a seller of an item, the item description being descriptive of the item; infer an attribute and an attribute value based on the item description; and include the attribute and the attribute value in an item record for the item, the item record being stored in an item database; and a hardware-implemented mapping module communicatively coupled to the item database, the mapping module being configured to: present a product record stored in a product database to the seller as a proposed record to be mapped to the item record; receive an acceptance of the proposed record from the seller; increment an acceptance count corresponding to the product record; and map the item record to the product record by including a reference to the product record in the item record based on the attribute and on the attribute value. | 10. A system comprising: an item database; a hardware-implemented analysis module communicatively coupled to the item database, the analysis module being configured to: access a seller-generated item description received from a seller of an item, the item description being descriptive of the item; infer an attribute and an attribute value based on the item description; and include the attribute and the attribute value in an item record for the item, the item record being stored in an item database; and a hardware-implemented mapping module communicatively coupled to the item database, the mapping module being configured to: present a product record stored in a product database to the seller as a proposed record to be mapped to the item record; receive an acceptance of the proposed record from the seller; increment an acceptance count corresponding to the product record; and map the item record to the product record by including a reference to the product record in the item record based on the attribute and on the attribute value. 11. The system of claim 10 , further comprising: a search module communicatively coupled to the item database, the search module to: receive search criteria from a user, the search criteria including the attribute value; identify a plurality of item records satisfying search criteria; present the plurality of item records to the user as specimens of the product record. | 0.574541 |
9,626,352 | 7 | 8 | 7. A computer program product stored in a computer readable storage medium, comprising computer program code that, when executed by an information handling system, causes the information handling system to perform actions comprising: analyzing a plurality of posts included in one or more threads of a threaded discussion, wherein the analyzing further comprises: identifying a term in a parent post of the threaded discussion; detecting that an anaphor in a child post of the threaded discussion references the identified term; and resolving the anaphor found in the child post with the identified term; storing the parent post with the identified term and the child post with the resolved anaphor in the memory; and ingesting the parent post with the identified term and the child post with the resolved anaphor into a corpus utilized by a question answering (QA) system. | 7. A computer program product stored in a computer readable storage medium, comprising computer program code that, when executed by an information handling system, causes the information handling system to perform actions comprising: analyzing a plurality of posts included in one or more threads of a threaded discussion, wherein the analyzing further comprises: identifying a term in a parent post of the threaded discussion; detecting that an anaphor in a child post of the threaded discussion references the identified term; and resolving the anaphor found in the child post with the identified term; storing the parent post with the identified term and the child post with the resolved anaphor in the memory; and ingesting the parent post with the identified term and the child post with the resolved anaphor into a corpus utilized by a question answering (QA) system. 8. The computer program product of claim 7 wherein the actions further comprise: identifying one or more referential types corresponding to one or more words included in the parent post; identifying one or more matching anaphora types corresponding to the identified referential types in one or more child posts, wherein the child posts include the child post; detecting the anaphors in the one or more child posts that relate to one or more of the words included in the parent post based upon matching the referential types to the anaphora types; resolving each of the anaphors detected in the child posts with the corresponding words found in the parent post; and associating each of the child posts that include one or more anaphors relating to corresponding words in the parent post to the parent post, wherein the association is accessible by the QA system. | 0.5 |
7,877,376 | 12 | 14 | 12. A computer-readable volatile or non-volatile medium storing one or more sequences of instructions that comprise instructions for rewriting queries, which instructions when executed by one or more processors cause the one or more processors to perform steps comprising: storing a plurality of materialized views, wherein a definition of each materialized view of the plurality of materialized views includes a set of aggregate expressions, and wherein storing said each materialized view comprises: identifying first one or more disjuncts in the set of aggregate expressions; wherein each of the set of aggregate expressions is an expression that specifies, in the definition of said each materialized view, computation of aggregated data; wherein each of the first one or more disjuncts is an expression block, included within one or more of the set of aggregate expressions, that identifies at least one column and at least one algebraic operator; and generating, based on the first one or more disjuncts, a set of disjunct trees that represent the set of aggregate expressions; storing the set of disjunct trees in computer data storage; receiving a query that requests particular aggregated data, wherein the query comprises an aggregate expression that specifies how the particular aggregated data is to be computed; identifying second one or more disjuncts in the aggregate expression; generating, based on the second one or more disjuncts, a disjunct tree that represents the aggregate expression; based on the disjunct tree and on the set of disjunct trees associated with said each materialized view of the plurality of materialized views, determining a particular materialized view from the plurality of materialized views that stores the particular aggregated data specified by the aggregate expression; and rewriting the query into an equivalent query that references the particular materialized view, wherein the equivalent query when executed would retrieve the particular aggregated data from the particular materialized view. | 12. A computer-readable volatile or non-volatile medium storing one or more sequences of instructions that comprise instructions for rewriting queries, which instructions when executed by one or more processors cause the one or more processors to perform steps comprising: storing a plurality of materialized views, wherein a definition of each materialized view of the plurality of materialized views includes a set of aggregate expressions, and wherein storing said each materialized view comprises: identifying first one or more disjuncts in the set of aggregate expressions; wherein each of the set of aggregate expressions is an expression that specifies, in the definition of said each materialized view, computation of aggregated data; wherein each of the first one or more disjuncts is an expression block, included within one or more of the set of aggregate expressions, that identifies at least one column and at least one algebraic operator; and generating, based on the first one or more disjuncts, a set of disjunct trees that represent the set of aggregate expressions; storing the set of disjunct trees in computer data storage; receiving a query that requests particular aggregated data, wherein the query comprises an aggregate expression that specifies how the particular aggregated data is to be computed; identifying second one or more disjuncts in the aggregate expression; generating, based on the second one or more disjuncts, a disjunct tree that represents the aggregate expression; based on the disjunct tree and on the set of disjunct trees associated with said each materialized view of the plurality of materialized views, determining a particular materialized view from the plurality of materialized views that stores the particular aggregated data specified by the aggregate expression; and rewriting the query into an equivalent query that references the particular materialized view, wherein the equivalent query when executed would retrieve the particular aggregated data from the particular materialized view. 14. The computer-readable volatile or non-volatile medium of claim 12 , wherein the instructions that cause generating the set of disjunct trees comprise instructions which, when executed by the one or more processors, cause generating each disjunct tree of the set of disjunct trees, wherein said each disjunct tree is associated with one aggregate expression from the set of aggregate expressions, and wherein generating said each disjunct tree comprises: determining one or more operators in said one aggregate expression; storing the one or more operators in one or more non-leaf nodes of said each disjunct tree; and for each disjunct, of the first one or more disjuncts, that is included in said one aggregate expression: storing said each disjunct in a leaf node of said each disjunct tree; determining a multiplicative coefficient that is associated with said each disjunct in said one aggregate expression; and storing the multiplicative coefficient in the leaf node of said each disjunct tree separately from said each disjunct. | 0.702749 |
9,056,256 | 1 | 8 | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. 8. The method of claim 1 wherein: capturing actions taken by the user includes determining topics reflected in books purchased online by the user; and automatically determining a play personality of the user is based, at least in part, on the topics reflected in items purchased online by the user. | 0.565598 |
8,271,436 | 13 | 14 | 13. A system comprising: a near-line server coupled to one or more servers; and a shadowing system coupled to the near-line server and configured to: receive delta data that describes at least one of an incremental and differential change to original data of one or more servers; dynamically and continuously generate and maintain an updated version of a copy of the original data at the near-line server, wherein the generating and maintaining comprise the one or more servers writing ahead information to at least one log file in response to changes in state of the original data, the information including the delta data, the one or more servers shipping the at least one log file to the near-line server, and the near-line server receiving and applying the write-ahead logs in maintaining the updated version; and retro-fit log shipping capability for application data and other structured and unstructured data based in part on the use of an override operation of an application state to allow log files to be applied as they are received, the override operation used in part to prevent a component of the near-line server from entering the application state in which no further log files can be applied; and control the applying using modified information of the component of the near-line server. | 13. A system comprising: a near-line server coupled to one or more servers; and a shadowing system coupled to the near-line server and configured to: receive delta data that describes at least one of an incremental and differential change to original data of one or more servers; dynamically and continuously generate and maintain an updated version of a copy of the original data at the near-line server, wherein the generating and maintaining comprise the one or more servers writing ahead information to at least one log file in response to changes in state of the original data, the information including the delta data, the one or more servers shipping the at least one log file to the near-line server, and the near-line server receiving and applying the write-ahead logs in maintaining the updated version; and retro-fit log shipping capability for application data and other structured and unstructured data based in part on the use of an override operation of an application state to allow log files to be applied as they are received, the override operation used in part to prevent a component of the near-line server from entering the application state in which no further log files can be applied; and control the applying using modified information of the component of the near-line server. 14. The system of claim 13 , wherein the component includes structural metadata of the copy. | 0.896629 |
9,069,847 | 30 | 31 | 30. The article of claim 19 wherein the initially and subsequently processings individually comprise identifying the features present in respective ones of the initial documents and the subsequent documents. | 30. The article of claim 19 wherein the initially and subsequently processings individually comprise identifying the features present in respective ones of the initial documents and the subsequent documents. 31. The article of claim 30 wherein the initial documents are not processed again to identify the features present in the initial documents after the initially processing. | 0.5 |
9,286,356 | 1 | 6 | 1. A method performed by one or more processing devices, comprising: determining, based on usage of a social network by a user, a maturity score for the user, where the maturity score represents a measure of user development of the user within the social network; for a particular type of content associated with a resource, retrieving, from a set of utility score instructions, a utility score instruction for the particular type of content; wherein the utility score instruction defines, for the particular type of content in the social network, a relationship between a utility score and the maturity score; wherein the utility score represents a measure of utility of the particular type of content to the user as defined by the measure of user development in the social network; and wherein the utility score is determined independent of user input; wherein defined relationships across the set of utility score instructions promote a first pre-defined type of content among less mature users of the social network relative to other maturities of other users of the social network and promote a second pre-defined type of content among more mature users of the social network relative to the other maturities of the other users of the social network; and determining, based on the set of utility score instructions and the maturity score, utility scores for resources that are accessible to the user. | 1. A method performed by one or more processing devices, comprising: determining, based on usage of a social network by a user, a maturity score for the user, where the maturity score represents a measure of user development of the user within the social network; for a particular type of content associated with a resource, retrieving, from a set of utility score instructions, a utility score instruction for the particular type of content; wherein the utility score instruction defines, for the particular type of content in the social network, a relationship between a utility score and the maturity score; wherein the utility score represents a measure of utility of the particular type of content to the user as defined by the measure of user development in the social network; and wherein the utility score is determined independent of user input; wherein defined relationships across the set of utility score instructions promote a first pre-defined type of content among less mature users of the social network relative to other maturities of other users of the social network and promote a second pre-defined type of content among more mature users of the social network relative to the other maturities of the other users of the social network; and determining, based on the set of utility score instructions and the maturity score, utility scores for resources that are accessible to the user. 6. The method of claim 1 , wherein the user comprises a first user, the maturity score comprises a first maturity score, the utility scores comprise first utility scores, and wherein the method further comprises: determining a second maturity score for a second user; determining, based on the second maturity score, second utility scores for the resources; and ranking the resources based on the second utility scores; wherein the ranking of the resources based on the second utility scores vary from a ranking of the resources based on the first utility scores. | 0.5 |
9,063,960 | 5 | 6 | 5. The computer-implemented method of claim 1 , further comprising: retrieving new data from a plurality of data stores; normalizing the new data; populating the relational multi-dimensional analytic database with the new data. | 5. The computer-implemented method of claim 1 , further comprising: retrieving new data from a plurality of data stores; normalizing the new data; populating the relational multi-dimensional analytic database with the new data. 6. The computer-implemented method of claim 5 , wherein normalizing the new data comprises analyzing the new data by correlating data entries within the new data. | 0.731788 |
8,032,532 | 9 | 14 | 9. A computer system comprising: a central processing unit (CPU); a memory coupled to said CPU; a computer-readable, tangible storage device coupled to said CPU, said storage device containing instructions that are carried out by said CPU via said memory to implement a method of querying multifaceted information, said method comprising: constructing an inverted index having a plurality of unique indexed tokens associated with a plurality of posting lists in a one-to-one correspondence, each posting list including one or more documents of a plurality of documents, wherein an indexed token of said plurality of unique indexed tokens is one of a facet token included as an annotation in a document of said plurality of documents and a path prefix of said facet token, wherein said annotation indicates a path within a tree structure representing a facet that includes said document, said tree structure including a plurality of nodes representing a category and one or more sub-categories that categorize said document; receiving a query that includes a plurality of constraints on said plurality of documents, said plurality of constraints being associated with multiple indexed tokens of said plurality of unique indexed tokens and multiple posting lists corresponding to said multiple indexed tokens; and executing said query by identifying said multiple posting lists via a utilization of said plurality of constraints and said inverted index, and intersecting said multiple posting lists to obtain a result of said query. | 9. A computer system comprising: a central processing unit (CPU); a memory coupled to said CPU; a computer-readable, tangible storage device coupled to said CPU, said storage device containing instructions that are carried out by said CPU via said memory to implement a method of querying multifaceted information, said method comprising: constructing an inverted index having a plurality of unique indexed tokens associated with a plurality of posting lists in a one-to-one correspondence, each posting list including one or more documents of a plurality of documents, wherein an indexed token of said plurality of unique indexed tokens is one of a facet token included as an annotation in a document of said plurality of documents and a path prefix of said facet token, wherein said annotation indicates a path within a tree structure representing a facet that includes said document, said tree structure including a plurality of nodes representing a category and one or more sub-categories that categorize said document; receiving a query that includes a plurality of constraints on said plurality of documents, said plurality of constraints being associated with multiple indexed tokens of said plurality of unique indexed tokens and multiple posting lists corresponding to said multiple indexed tokens; and executing said query by identifying said multiple posting lists via a utilization of said plurality of constraints and said inverted index, and intersecting said multiple posting lists to obtain a result of said query. 14. The system of claim 9 , further comprising: receiving, by said IR system, an arithmetic expression included in said query, said arithmetic expression associated with at least one numeric field included in one or more documents of said plurality of documents; and computing an evaluation of said arithmetic expression, said computing performed per sub-category of a category indicated by a constraint of said plurality of constraints. | 0.794256 |
7,747,552 | 12 | 13 | 12. The method of claim 7 where establishing one or more leaf nodes comprises: establishing one or more leaf nodes for sand-grain composition; and establishing one or more leaf nodes for sand texture. | 12. The method of claim 7 where establishing one or more leaf nodes comprises: establishing one or more leaf nodes for sand-grain composition; and establishing one or more leaf nodes for sand texture. 13. The method of claim 12 where establishing one or more leaf nodes for sand texture comprises: establishing a leaf node for grain size; establishing a leaf node for degree of sorting; and establishing a leaf node for deposited matrix abundance. | 0.671123 |
9,711,043 | 1 | 6 | 1. An infrared signal generator comprising: an interface for receiving an encoded infrared command from a controller; a decoder for decoding the encoded infrared command; and protocol generation circuitry for generating a bitstream based on the decoded infrared command; wherein the bitstream comprises one or more data words that comprise data to be transmitted and one or more protocol words that describe symbols of an infrared protocol; and components for generating a drive signal using the protocol words and the data words. | 1. An infrared signal generator comprising: an interface for receiving an encoded infrared command from a controller; a decoder for decoding the encoded infrared command; and protocol generation circuitry for generating a bitstream based on the decoded infrared command; wherein the bitstream comprises one or more data words that comprise data to be transmitted and one or more protocol words that describe symbols of an infrared protocol; and components for generating a drive signal using the protocol words and the data words. 6. The infrared signal generator of claim 1 , wherein the data word comprises a length field that denotes the number of valid bits in a data payload. | 0.61399 |
8,086,624 | 13 | 14 | 13. A system for determining proximity to ad topics, comprising: one or more computers configured to perform operations comprising: preliminarily selecting an advertisement based on a set of search keywords associated with a search query, determining a set of ad keywords associated with the advertisement; mapping the ad keywords to at least one keyword cluster, where each keyword cluster is related to a topic of the advertisement; computing a first conditional probability that the ad keywords occur in the at least one keyword cluster; computing a second conditional probability that the search keywords occur in the at least one keyword cluster; and determining a topical proximity between the search query and the advertisement from a comparison of the first conditional probability and the second conditional probability. | 13. A system for determining proximity to ad topics, comprising: one or more computers configured to perform operations comprising: preliminarily selecting an advertisement based on a set of search keywords associated with a search query, determining a set of ad keywords associated with the advertisement; mapping the ad keywords to at least one keyword cluster, where each keyword cluster is related to a topic of the advertisement; computing a first conditional probability that the ad keywords occur in the at least one keyword cluster; computing a second conditional probability that the search keywords occur in the at least one keyword cluster; and determining a topical proximity between the search query and the advertisement from a comparison of the first conditional probability and the second conditional probability. 14. The system of claim 13 , further configured to perform operations comprising: determining a plurality of first average conditional logarithmic odds for the ad keywords with respect to the at least one keyword cluster for the first conditional probability; determining a plurality of second average conditional logarithmic odds for the search keywords with respect to the at least one keyword cluster for the second conditional probability; and comparing the first conditional probability and the second conditional probability by taking the difference between the two probabilities. | 0.5 |
8,533,643 | 2 | 3 | 2. The method of claim 1 , wherein each of the super-CCR template graphs defines at least one of a plurality of CCRs or a plurality of super-CCRs that are interconnected, the method further comprising: the processor generating a graph for each candidate combination; and the processor determining which of the candidate combinations actually match the formatted super-CCR template graph. | 2. The method of claim 1 , wherein each of the super-CCR template graphs defines at least one of a plurality of CCRs or a plurality of super-CCRs that are interconnected, the method further comprising: the processor generating a graph for each candidate combination; and the processor determining which of the candidate combinations actually match the formatted super-CCR template graph. 3. The method of claim 2 further comprising: the processor storing in a database the graphs of the candidate combinations that are determined to actually match the formatted super-CCR template graph. | 0.5 |
9,502,024 | 1 | 3 | 1. A method for use with an automatic speech recognition (ASR) system, the ASR system comprising at least one model having a plurality of representations of phones, the method comprising acts of: receiving an audio signal comprising a first user input; analyzing the audio signal to identify at least one first phone as having a selected recognition performance characteristic, wherein the act of analyzing comprises comparing one or more sounds in the audio signal with a representation of the at least one first phone in the at least one model; subsequent to receiving and analyzing the audio signal comprising the first user input, selecting a user prompt to be presented to a user of a speech-responsive application to elicit a second user input, wherein the speech-responsive application is programmed to perform at least one action based on the second user input, and wherein the user prompt is selected based on a determination of whether the user is expected to speak, in response to the user prompt, the at least one first phone which is identified as having the selected recognition performance characteristic; causing the user prompt to be presented to the user of the speech-responsive application, wherein: the at least one first phone is associated with a first confidence score, the first confidence score being lower than a selected confidence threshold, and the user prompt is selected to invite the user to speak an input phrase that combines a first word with one or more second words, wherein the first word comprises the at least one first phone associated with the first confidence score that is lower than the selected confidence threshold, and the one or more second words comprise at least one second phone that is associated with a second confidence score, the second confidence score being higher than the selected confidence threshold; and performing, by the speech-responsive application, the at least one action based on the second user input. | 1. A method for use with an automatic speech recognition (ASR) system, the ASR system comprising at least one model having a plurality of representations of phones, the method comprising acts of: receiving an audio signal comprising a first user input; analyzing the audio signal to identify at least one first phone as having a selected recognition performance characteristic, wherein the act of analyzing comprises comparing one or more sounds in the audio signal with a representation of the at least one first phone in the at least one model; subsequent to receiving and analyzing the audio signal comprising the first user input, selecting a user prompt to be presented to a user of a speech-responsive application to elicit a second user input, wherein the speech-responsive application is programmed to perform at least one action based on the second user input, and wherein the user prompt is selected based on a determination of whether the user is expected to speak, in response to the user prompt, the at least one first phone which is identified as having the selected recognition performance characteristic; causing the user prompt to be presented to the user of the speech-responsive application, wherein: the at least one first phone is associated with a first confidence score, the first confidence score being lower than a selected confidence threshold, and the user prompt is selected to invite the user to speak an input phrase that combines a first word with one or more second words, wherein the first word comprises the at least one first phone associated with the first confidence score that is lower than the selected confidence threshold, and the one or more second words comprise at least one second phone that is associated with a second confidence score, the second confidence score being higher than the selected confidence threshold; and performing, by the speech-responsive application, the at least one action based on the second user input. 3. The method of claim 1 , wherein the user prompt prompts the user to speak one of a plurality of input phrases, and wherein the act of selecting the user prompt comprises selecting at least one input phrase of the plurality of input phrases based on a presence or absence of the identified at least one first phone in the at least one input phrase. | 0.5 |
8,549,314 | 1 | 9 | 1. A computer-implemented method comprising: receiving a plurality of characters input to a computer device by a user, wherein the plurality of characters input by the user include a user password, variable characters, a plurality of terminator characters, and wherein the plurality of characters input by the user further include a plurality of safeguard characters; identifying locations of the plurality of terminator characters, each one of the terminator characters separated from one another by a portion of the variable characters; and extracting the user password from the plurality of characters which included the user password, variable character, the plurality of terminator characters, and the plurality of safeguard characters, wherein the safeguard is number that presents the minimum number of variable characters the user enter after each character in the actual user password and followed by variable characters and terminator characters; input by the user based on a one-to-one correspondence of each character of the user password with each one of the terminator characters and the locations of each one of the terminator characters. | 1. A computer-implemented method comprising: receiving a plurality of characters input to a computer device by a user, wherein the plurality of characters input by the user include a user password, variable characters, a plurality of terminator characters, and wherein the plurality of characters input by the user further include a plurality of safeguard characters; identifying locations of the plurality of terminator characters, each one of the terminator characters separated from one another by a portion of the variable characters; and extracting the user password from the plurality of characters which included the user password, variable character, the plurality of terminator characters, and the plurality of safeguard characters, wherein the safeguard is number that presents the minimum number of variable characters the user enter after each character in the actual user password and followed by variable characters and terminator characters; input by the user based on a one-to-one correspondence of each character of the user password with each one of the terminator characters and the locations of each one of the terminator characters. 9. A computer-implemented method as recited in claim 1 further comprising communicating the plurality of characters input by the user to a server for storage of the plurality of characters. | 0.73 |
7,835,999 | 1 | 2 | 1. At a computer system including a multi-touch input display surface, a method for training the computer system to recognize input gesture data entered at the multi-touch input display surface as a corresponding specified input pattern, the method comprising: an act of accessing input gesture data for at least one example of a specified input pattern, the input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including for at least the one example of the specified input pattern: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of encoding the input gesture data into an input vector of real values, each real value corresponding to a sample taken from the first or second axis, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value; an act of saving an indication that the real values contained in the input vector represent an example of the specified input pattern; an act of accessing a fully connected neural network, the neural network including input nodes, hidden nodes, and output nodes, the input nodes being fully connected to the hidden nodes and the hidden nodes being fully connected to the output nodes; an act of creating a training set to supply to the neural network to train the neural network to recognize the specified input pattern, the training set including at least the input vector and a corresponding output vector, the corresponding output vector indicating the desired output of the neural network that is to correspond to the specified input pattern; and an act of using a back propagation algorithm to train the neural network to recognize the specified pattern of input by training the neural network to generate output node values approximating the corresponding output vector in response to receiving the input vector. | 1. At a computer system including a multi-touch input display surface, a method for training the computer system to recognize input gesture data entered at the multi-touch input display surface as a corresponding specified input pattern, the method comprising: an act of accessing input gesture data for at least one example of a specified input pattern, the input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including for at least the one example of the specified input pattern: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of encoding the input gesture data into an input vector of real values, each real value corresponding to a sample taken from the first or second axis, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value; an act of saving an indication that the real values contained in the input vector represent an example of the specified input pattern; an act of accessing a fully connected neural network, the neural network including input nodes, hidden nodes, and output nodes, the input nodes being fully connected to the hidden nodes and the hidden nodes being fully connected to the output nodes; an act of creating a training set to supply to the neural network to train the neural network to recognize the specified input pattern, the training set including at least the input vector and a corresponding output vector, the corresponding output vector indicating the desired output of the neural network that is to correspond to the specified input pattern; and an act of using a back propagation algorithm to train the neural network to recognize the specified pattern of input by training the neural network to generate output node values approximating the corresponding output vector in response to receiving the input vector. 2. The method as recited in claim 1 , wherein the act of accessing input gesture data for at least one example of a specified input pattern comprises an act of access input gesture data for a plurality of examples of the specified input pattern. | 0.668022 |
8,396,820 | 17 | 18 | 17. The method of claim 16 wherein the retrieved related sentiment adjectives are returned in an order. | 17. The method of claim 16 wherein the retrieved related sentiment adjectives are returned in an order. 18. The method of claim 17 wherein the order is based upon a connection type stored for the indicated adjective in relation to each related sentiment adjective word-sense. | 0.611364 |
9,792,617 | 15 | 19 | 15. A computer implemented method performed for conducting a plurality of survey sessions arranged for different events, comprising: A) launching the plurality of survey sessions respectively; B) presenting a single survey question for each of the plurality of survey sessions; C) the method arranged such that the single survey question is arranged to have the same wording and no more than three words; D) concluding a corresponding survey session automatically after receiving a user response to the single question; and E) transmitting survey results to a survey facility via an electronic device or a communication network. | 15. A computer implemented method performed for conducting a plurality of survey sessions arranged for different events, comprising: A) launching the plurality of survey sessions respectively; B) presenting a single survey question for each of the plurality of survey sessions; C) the method arranged such that the single survey question is arranged to have the same wording and no more than three words; D) concluding a corresponding survey session automatically after receiving a user response to the single question; and E) transmitting survey results to a survey facility via an electronic device or a communication network. 19. The method according to claim 15 , further including providing a working space for a user to enter own words. | 0.702632 |
8,078,450 | 13 | 14 | 13. A method of analyzing a sentence in a source language, comprising: performing a lexical analysis of the sentence in the source language; performing a lexical-morphological analysis on each element of the sentence and building a lexical-morphological structure for the whole sentence; performing a rough syntactic analysis on the lexical-morphological structure comprising: generating all possible constituents for each element of the lexical-morphological structure; generalizing the constituents to form a set of generalized constituents; and generating a graph of the generalized constituents to describe all possible syntactic structures of the whole sentence, comprising: for each generalized constituent having a lexical meaning and grammatical value which corresponds to a connection in the lexical-morphological structure: initializing a surface model for the generalized constituent; attempting to attach other constituents in surface slots of the syntforms of the surface model right and left neighboring constituents; and establishing non-tree links on the graph of the generalized constituents; performing a precise syntactic analysis on the graph of the generalized constituents, wherein the precise syntactic analysis includes: rating the graph of the precise constituents based on a plurality of rating scores independently obtained and calculated, including a rating score for one or more lexical meanings for each element of the sentence, a rating score for one or more syntactic constructions for each element of the sentence, a rating score for a degree of correspondence of the precise constituents to their semantic descriptions, and a rating score for the linear order of the constituents; using the rating scores to generate hypotheses about the overall syntactic structure of the sentence; and selecting one or more best hypotheses about the overall syntactic structure of the sentence with the highest rating score from the hypotheses generated; generating a graph of precise constituents, the graph of precise constituents being an intermediate re resentation between the graph of the generalized constituents and one or more syntactic trees; generating one or more syntactic trees from the graph of the precise constituents; selecting a syntactic structure for the sentence from the one or more syntactic trees; performing a semantic analysis on the selected syntactic structure of the sentence; and generating a language-independent semantic structure for the sentence of the language based at least in part on the semantic analysis of the selected syntactic structure. | 13. A method of analyzing a sentence in a source language, comprising: performing a lexical analysis of the sentence in the source language; performing a lexical-morphological analysis on each element of the sentence and building a lexical-morphological structure for the whole sentence; performing a rough syntactic analysis on the lexical-morphological structure comprising: generating all possible constituents for each element of the lexical-morphological structure; generalizing the constituents to form a set of generalized constituents; and generating a graph of the generalized constituents to describe all possible syntactic structures of the whole sentence, comprising: for each generalized constituent having a lexical meaning and grammatical value which corresponds to a connection in the lexical-morphological structure: initializing a surface model for the generalized constituent; attempting to attach other constituents in surface slots of the syntforms of the surface model right and left neighboring constituents; and establishing non-tree links on the graph of the generalized constituents; performing a precise syntactic analysis on the graph of the generalized constituents, wherein the precise syntactic analysis includes: rating the graph of the precise constituents based on a plurality of rating scores independently obtained and calculated, including a rating score for one or more lexical meanings for each element of the sentence, a rating score for one or more syntactic constructions for each element of the sentence, a rating score for a degree of correspondence of the precise constituents to their semantic descriptions, and a rating score for the linear order of the constituents; using the rating scores to generate hypotheses about the overall syntactic structure of the sentence; and selecting one or more best hypotheses about the overall syntactic structure of the sentence with the highest rating score from the hypotheses generated; generating a graph of precise constituents, the graph of precise constituents being an intermediate re resentation between the graph of the generalized constituents and one or more syntactic trees; generating one or more syntactic trees from the graph of the precise constituents; selecting a syntactic structure for the sentence from the one or more syntactic trees; performing a semantic analysis on the selected syntactic structure of the sentence; and generating a language-independent semantic structure for the sentence of the language based at least in part on the semantic analysis of the selected syntactic structure. 14. The method of claim 13 , wherein filtering of the constituents is performed prior to and after building the graph of the generalized constituents. | 0.741379 |
7,614,003 | 13 | 19 | 13. A system comprising: an input device; a display device; a computer platform including an operating system and a virtual machine, the virtual machine configured to create a virtualized environment between the computer platform and a software application programmed to operate on the virtual machine; and the virtual machine operable to generate a user interface for the software application, using the input device and the display device, by rendering and dynamically updating interactive HTML content through a vector graphics rendering engine, wherein the virtual machine comprises an HTML rendering engine, separate from the vector graphics rendering engine, configured to render the interactive HTML content to primitives of the vector graphics rendering engine, and the virtual machine comprises the vector graphics rendering engine configured to render the primitives to provide the user interface. | 13. A system comprising: an input device; a display device; a computer platform including an operating system and a virtual machine, the virtual machine configured to create a virtualized environment between the computer platform and a software application programmed to operate on the virtual machine; and the virtual machine operable to generate a user interface for the software application, using the input device and the display device, by rendering and dynamically updating interactive HTML content through a vector graphics rendering engine, wherein the virtual machine comprises an HTML rendering engine, separate from the vector graphics rendering engine, configured to render the interactive HTML content to primitives of the vector graphics rendering engine, and the virtual machine comprises the vector graphics rendering engine configured to render the primitives to provide the user interface. 19. The system of claim 13 , wherein the computer platform, the input device and the display device comprise one personal computer. | 0.819061 |
10,062,300 | 1 | 40 | 1. A modular learning device comprising of: a base board having a frame with plurality of sides, a complementary joining construction on sides of the base board, a front plane, a rear plane, a network of tracks having a spinal track, several dormant tracks, several solution tracks, several parking tracks, the dormant tracks and the parking tracks and the solution tracks are connected to the spinal track, a recess, wherein some parking tracks are also solution tracks; a plurality of sliding blocks having a tread, a stopper and a shaft, the shaft having a first end and a second end; and a plurality of wisdom cards having an identifier section, a margin having up to same number of sides as the base board, a plurality of zones in the margin, a middle area and corresponding solutions in the zones randomly, a solution code for problems or situations, each wisdom card containing different problems or situations on a plurality of subjects, an indicator for each problem or situation, wherein the indicator is a hint or a prompt to arrive at correct provided solution; different base boards unifiable by the complementary joining construction on the sides of the base board, the plurality of wisdom cards mounted, either one at a time, or in combination, one in each recess of the base board, the plurality of sliding blocks mounted on the base board with the head on the front plane of the base board and the stopper on the rear plane of the base board, the plurality of sliding blocks can move freely in the network of tracks and cannot get dislodged unless the stopper is separated or manoeuvred using a minimum force. | 1. A modular learning device comprising of: a base board having a frame with plurality of sides, a complementary joining construction on sides of the base board, a front plane, a rear plane, a network of tracks having a spinal track, several dormant tracks, several solution tracks, several parking tracks, the dormant tracks and the parking tracks and the solution tracks are connected to the spinal track, a recess, wherein some parking tracks are also solution tracks; a plurality of sliding blocks having a tread, a stopper and a shaft, the shaft having a first end and a second end; and a plurality of wisdom cards having an identifier section, a margin having up to same number of sides as the base board, a plurality of zones in the margin, a middle area and corresponding solutions in the zones randomly, a solution code for problems or situations, each wisdom card containing different problems or situations on a plurality of subjects, an indicator for each problem or situation, wherein the indicator is a hint or a prompt to arrive at correct provided solution; different base boards unifiable by the complementary joining construction on the sides of the base board, the plurality of wisdom cards mounted, either one at a time, or in combination, one in each recess of the base board, the plurality of sliding blocks mounted on the base board with the head on the front plane of the base board and the stopper on the rear plane of the base board, the plurality of sliding blocks can move freely in the network of tracks and cannot get dislodged unless the stopper is separated or manoeuvred using a minimum force. 40. The modular learning device as claimed in claim 1 , wherein the plurality of subjects are in the wisdom card. | 0.833824 |
10,007,707 | 1 | 10 | 1. A computer server system coupleable to a network for personalization of network search results and search result rankings, the server system comprising: a network input and output interface for network data transmission and reception, the network input and output interface adapted to receive at least one query from a respondent or co-respondent via the network; to transmit a plurality of return queries to the respondent or co-respondent via the network; to receive a plurality of responses to the return queries from the respondent or co-respondent via the network; and to transmit personalized network search results and search result rankings to the respondent or co-respondent via the network; at least one data storage device storing a plurality of return queries; and one or more processors coupled to the at least one data storage device and network input and output interface, the one or more processors adapted to access the at least one data storage device and using the at least one query, to select the plurality of return queries for transmission; to generate a digital filter from each plurality of responses to the return queries to form a plurality of digital filters; to search the at least one data storage device for corresponding pluralities of responses to the return queries from one or more co-respondents or respondents, respectively; to comparatively pair-wise score the plurality of responses to the return queries against the corresponding pluralities of responses to the return queries by using the plurality of digital filters to provide a two-stage filtering of the search results through both a respondent digital filter of a selected respondent and a co-respondent digital filter of a selected co-respondent, of the plurality of digital filters, to form a plurality of pair-wise alignment scores for a plurality of respondent and co-respondent combinations; to sort and rank the plurality of respondent and co-respondent combinations according to the plurality of pair-wise alignment scores; and to output a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings. | 1. A computer server system coupleable to a network for personalization of network search results and search result rankings, the server system comprising: a network input and output interface for network data transmission and reception, the network input and output interface adapted to receive at least one query from a respondent or co-respondent via the network; to transmit a plurality of return queries to the respondent or co-respondent via the network; to receive a plurality of responses to the return queries from the respondent or co-respondent via the network; and to transmit personalized network search results and search result rankings to the respondent or co-respondent via the network; at least one data storage device storing a plurality of return queries; and one or more processors coupled to the at least one data storage device and network input and output interface, the one or more processors adapted to access the at least one data storage device and using the at least one query, to select the plurality of return queries for transmission; to generate a digital filter from each plurality of responses to the return queries to form a plurality of digital filters; to search the at least one data storage device for corresponding pluralities of responses to the return queries from one or more co-respondents or respondents, respectively; to comparatively pair-wise score the plurality of responses to the return queries against the corresponding pluralities of responses to the return queries by using the plurality of digital filters to provide a two-stage filtering of the search results through both a respondent digital filter of a selected respondent and a co-respondent digital filter of a selected co-respondent, of the plurality of digital filters, to form a plurality of pair-wise alignment scores for a plurality of respondent and co-respondent combinations; to sort and rank the plurality of respondent and co-respondent combinations according to the plurality of pair-wise alignment scores; and to output a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings. 10. The computer server system of claim 1 , wherein the one or more processors are further adapted to store the plurality of pair-wise alignment scores for the plurality of respondent and co-respondent combinations in the at least one data storage device, and to store the listing of the sorted and ranked respondents or co-respondents in the at least one data storage device. | 0.661871 |
10,165,149 | 1 | 4 | 1. A system comprising a scanning device, wherein the scanning device comprises: an input device; a display device; a data store in communication with the electronic device; and a computer-readable storage medium comprising one or more programming instructions that, when executed, cause the scanning device to: receive a physical document that is to be converted into an electronic document, perform optical character recognition on at least a portion of the physical document to identify one or more terms that are present in the physical document, store the identified terms in the data store associated with the scanning device, receive, from the input device, input from a user, wherein the input comprises one or more first characters and corresponds to a title of the electronic document, identify one or more terms from the data store that correspond to the one or more first characters by querying the data store using the received input, and cause the identified terms to be displayed to the user via a display device of the scanning device as suggested document names for the electronic document. | 1. A system comprising a scanning device, wherein the scanning device comprises: an input device; a display device; a data store in communication with the electronic device; and a computer-readable storage medium comprising one or more programming instructions that, when executed, cause the scanning device to: receive a physical document that is to be converted into an electronic document, perform optical character recognition on at least a portion of the physical document to identify one or more terms that are present in the physical document, store the identified terms in the data store associated with the scanning device, receive, from the input device, input from a user, wherein the input comprises one or more first characters and corresponds to a title of the electronic document, identify one or more terms from the data store that correspond to the one or more first characters by querying the data store using the received input, and cause the identified terms to be displayed to the user via a display device of the scanning device as suggested document names for the electronic document. 4. The system of claim 1 , wherein the one or more programming instructions that, when executed, cause the electronic device to receive, from the input device, input from a user, comprise one or more programming instructions that, when executed, cause the scanning device to determine that the input is being provided in a field associated with a name of the scanning document. | 0.705928 |
4,831,654 | 12 | 13 | 12. In the dictionary manipulation apparatus of claim 3 and wherein: the dictionary manipulation commands include dictionary scanning commands including an entry selection command; and the dictionary manipulation command execution means responds to the entry selection command by selecting one of the dictionary entries and to the play command by providing the phonemic representation contained in the selected entry to the phonemic representation to speech conversion means. | 12. In the dictionary manipulation apparatus of claim 3 and wherein: the dictionary manipulation commands include dictionary scanning commands including an entry selection command; and the dictionary manipulation command execution means responds to the entry selection command by selecting one of the dictionary entries and to the play command by providing the phonemic representation contained in the selected entry to the phonemic representation to speech conversion means. 13. In the dictionary manipulation apparatus of claim 12 and wherein: the dictionary manipulation commands further include an edit entry command and a plurality of phonemic representation editing commands; and the dictionary manipulation command execution means responds to the edit entry command by making the phonemic representation editing commands available at the input means and to the phonemic representation editing commands by editing the phonemic representation from the selected dictionary entry and employing the play command to provide the edited phonemic representation to the phonemic representation to speech conversion means. | 0.5 |
9,501,569 | 6 | 7 | 6. A system comprising: one or more processors; a memory, accessible by the one or more processors; a keyword module stored in the memory and executable on the one or more processors to receive a set of keywords; a concepts module stored in the memory and executable on the one or more processors to determine a set of concepts for the keywords, wherein the concepts module: determines the set of concepts for the keywords with a general purpose knowledgebase such that one or more of the set of concepts are associated with a score to indicate a probability that a term from the general purpose knowledgebase is a concept of the keyword; a context module stored in the memory and executable on the one or more processors to obtain context information for the keywords, wherein the context module: accesses a search engine; collects snippets from search results obtained from the search engine; ranks a predetermined number of snippet words based at least in part on frequency of occurrence; and stores the predetermined number of highest ranked snippet words as the context information; and a taxonomy module stored in the memory and executable on the one or more processors to determine a weight for a term based at least in part on the set of concepts and the context information and perform hierarchical clustering based at least in part on the weight, the set of concepts and the context information. | 6. A system comprising: one or more processors; a memory, accessible by the one or more processors; a keyword module stored in the memory and executable on the one or more processors to receive a set of keywords; a concepts module stored in the memory and executable on the one or more processors to determine a set of concepts for the keywords, wherein the concepts module: determines the set of concepts for the keywords with a general purpose knowledgebase such that one or more of the set of concepts are associated with a score to indicate a probability that a term from the general purpose knowledgebase is a concept of the keyword; a context module stored in the memory and executable on the one or more processors to obtain context information for the keywords, wherein the context module: accesses a search engine; collects snippets from search results obtained from the search engine; ranks a predetermined number of snippet words based at least in part on frequency of occurrence; and stores the predetermined number of highest ranked snippet words as the context information; and a taxonomy module stored in the memory and executable on the one or more processors to determine a weight for a term based at least in part on the set of concepts and the context information and perform hierarchical clustering based at least in part on the weight, the set of concepts and the context information. 7. The system of claim 6 , wherein the set of concepts is based at least in part on terms returned by the general purpose knowledgebase. | 0.534247 |
8,903,174 | 25 | 27 | 25. The computer program product of claim 24 wherein the proportion of the display element's pixel width is a function of at least the display element's number of characters and an empirically determined recognition position ratio. | 25. The computer program product of claim 24 wherein the proportion of the display element's pixel width is a function of at least the display element's number of characters and an empirically determined recognition position ratio. 27. The computer program product of claim 25 wherein the empirically determined recognition ratio is an average position ratio of respective optimal recognition position characters for respective display elements from a length of three characters to a length of at least thirteen characters. | 0.5 |
8,156,520 | 8 | 9 | 8. A receiving device comprising: a communication interface that receives a first audio/video stream including at least one segment of a show and at least one interstitial of the show, and that further receives supplemental data associated with the first audio/video stream, the supplemental data including closed captioning data associated with the first audio/video stream; a storage unit that stores the first audio/video stream and the supplemental data; control logic that: receives autonomous location information separately from the first audio/video stream, the autonomous location information that references the closed captioning data, the autonomous location information including a plurality of data segments, each comprising a displayable text string included within the closed captioning data as originally transmitted by a content provider; processes the closed captioning data recorded to locate a first video location corresponding with the presentation of a first of the plurality of data segments located in the closed captioning data recorded; determines that the first of the plurality of data segments is not located within the closed captioning data recorded; processes the closed captioning data recorded again to locate a second video location corresponding with the presentation of a second of the plurality of data segments in the closed captioning data recorded; identifies the boundaries of the at least one segment of the show based on the second video location and the autonomous location information; identifies substitute content based on the second video location and the autonomous location information to present in association with the at least one segment of the show; and an audio/video interface that outputs a second audio/video stream for presentation on a display device, the second audio/video stream including the at least one segment of the show and the substitute content. | 8. A receiving device comprising: a communication interface that receives a first audio/video stream including at least one segment of a show and at least one interstitial of the show, and that further receives supplemental data associated with the first audio/video stream, the supplemental data including closed captioning data associated with the first audio/video stream; a storage unit that stores the first audio/video stream and the supplemental data; control logic that: receives autonomous location information separately from the first audio/video stream, the autonomous location information that references the closed captioning data, the autonomous location information including a plurality of data segments, each comprising a displayable text string included within the closed captioning data as originally transmitted by a content provider; processes the closed captioning data recorded to locate a first video location corresponding with the presentation of a first of the plurality of data segments located in the closed captioning data recorded; determines that the first of the plurality of data segments is not located within the closed captioning data recorded; processes the closed captioning data recorded again to locate a second video location corresponding with the presentation of a second of the plurality of data segments in the closed captioning data recorded; identifies the boundaries of the at least one segment of the show based on the second video location and the autonomous location information; identifies substitute content based on the second video location and the autonomous location information to present in association with the at least one segment of the show; and an audio/video interface that outputs a second audio/video stream for presentation on a display device, the second audio/video stream including the at least one segment of the show and the substitute content. 9. The receiving device of claim 8 , wherein the control logic sorts the closed captioning data according to a presentation order of the closed captioning data and stores the sorted closed captioning data in a data file separate from the first audio/video stream. | 0.794852 |
8,972,389 | 10 | 13 | 10. A system comprising: a processing unit to support navigation of a hierarchical path within ontological data; a functional unit in communication with the processing unit, the functional unit having tools to support an interface representing the ontological data, the tools comprising: an ontology manager to derive context for a selected item from items associated with the selected item and to extract at least one ontology defining a set of representational elements categorized according to a relevant quality associated with a first selected item, wherein the at least one ontology includes an element contextually associated with the selected item, wherein the element is an image; a representation manager in communication with the ontology manager, the representation manager to support selection of at least one representational item from the at least one extracted ontology; a navigation manager in communication with the representation manager, the navigation manager to support navigation on at least one hierarchical path within the ontology in one of at least two directions, the directions selected from the group consisting of: an element broader in scope than the at least one representational item; and an element narrower in scope than the at least one representational item; and the navigation manger to replace the at least one selected representational element with a different representational element corresponding to the direction of navigation on the hierarchical path; and a presentation manager in communication with the representation manager, the presentation manager to present the at least one representational element selected by the representation manager; the presentation manager to align two or more ontology streams associated with the selected first item upon presentation, wherein the alignment includes the presentation manager to present the representative element from each ontology stream adjacent to the selected item; and the presentation manager to present the extracted ontology streams simultaneously, including the presentation manager to maintain two of the ontology streams upon navigation on one of the hierarchical paths within one of the at least two ontology streams. | 10. A system comprising: a processing unit to support navigation of a hierarchical path within ontological data; a functional unit in communication with the processing unit, the functional unit having tools to support an interface representing the ontological data, the tools comprising: an ontology manager to derive context for a selected item from items associated with the selected item and to extract at least one ontology defining a set of representational elements categorized according to a relevant quality associated with a first selected item, wherein the at least one ontology includes an element contextually associated with the selected item, wherein the element is an image; a representation manager in communication with the ontology manager, the representation manager to support selection of at least one representational item from the at least one extracted ontology; a navigation manager in communication with the representation manager, the navigation manager to support navigation on at least one hierarchical path within the ontology in one of at least two directions, the directions selected from the group consisting of: an element broader in scope than the at least one representational item; and an element narrower in scope than the at least one representational item; and the navigation manger to replace the at least one selected representational element with a different representational element corresponding to the direction of navigation on the hierarchical path; and a presentation manager in communication with the representation manager, the presentation manager to present the at least one representational element selected by the representation manager; the presentation manager to align two or more ontology streams associated with the selected first item upon presentation, wherein the alignment includes the presentation manager to present the representative element from each ontology stream adjacent to the selected item; and the presentation manager to present the extracted ontology streams simultaneously, including the presentation manager to maintain two of the ontology streams upon navigation on one of the hierarchical paths within one of the at least two ontology streams. 13. The system of claim 10 , further comprising the selected item associated with multiple ontology streams, and a rank manager in communication with the ontology manager, the rank manager to rank an extracted ontology stream and the presentation manager to present at least two of the ontology streams responsive to the ranking. | 0.5 |
6,052,657 | 1 | 16 | 1. A method for segmenting a stream of text into segments using a plurality of language models, the stream of text including a sequence of blocks of text, the method comprising: scoring the blocks of text against the language models to generate language model scores for the blocks of text, the language model score for a block of text against a language model indicating a correlation between the block of text and the language model; generating language model sequence scores for different sequences of language models to which a sequence of blocks of text may correspond, a language model sequence score being a function of the scores of a sequence of blocks of text against a sequence of language models; selecting a sequence of language models that satisfies a predetermined condition; and identifying segment boundaries in the stream of text that correspond to language model transitions in the selected sequence of language models. | 1. A method for segmenting a stream of text into segments using a plurality of language models, the stream of text including a sequence of blocks of text, the method comprising: scoring the blocks of text against the language models to generate language model scores for the blocks of text, the language model score for a block of text against a language model indicating a correlation between the block of text and the language model; generating language model sequence scores for different sequences of language models to which a sequence of blocks of text may correspond, a language model sequence score being a function of the scores of a sequence of blocks of text against a sequence of language models; selecting a sequence of language models that satisfies a predetermined condition; and identifying segment boundaries in the stream of text that correspond to language model transitions in the selected sequence of language models. 16. The method of claim 1, wherein the language models comprise bigram language models. | 0.873913 |
8,145,618 | 21 | 23 | 21. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a search criteria; identifying one or more documents responsive to the search criteria; determining a text match score for each document based on degree of match between the responsive document and the search criteria; determining a document-categories score for each of a plurality of categories based on a degree of match between each document and each of the categories; determining a search criteria-categories score for each of the one or more categories based on a degree of match between the search criteria and each of the one or more categories, wherein the search criteria-categories score for a particular category indicates the degree of match between the search criteria and the category; determining a category match score for each document by combining the document-categories score of each of the one or more categories and the respective search criteria-categories score; determining an overall score for each document based on the text match score of each document and the respective category match score; and determining, based on the overall score for each document, a ranked order for the one or more documents. | 21. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a search criteria; identifying one or more documents responsive to the search criteria; determining a text match score for each document based on degree of match between the responsive document and the search criteria; determining a document-categories score for each of a plurality of categories based on a degree of match between each document and each of the categories; determining a search criteria-categories score for each of the one or more categories based on a degree of match between the search criteria and each of the one or more categories, wherein the search criteria-categories score for a particular category indicates the degree of match between the search criteria and the category; determining a category match score for each document by combining the document-categories score of each of the one or more categories and the respective search criteria-categories score; determining an overall score for each document based on the text match score of each document and the respective category match score; and determining, based on the overall score for each document, a ranked order for the one or more documents. 23. The computer storage medium of claim 21 , wherein the search criteria includes a concept, the concept comprising one or more terms, and wherein the text match score indicates a quality of match between the terms and each document, and wherein the search criteria-categories score indicates a quality of match between the terms and each of the one or more categories. | 0.530457 |
9,244,979 | 30 | 31 | 30. The one or more non-transitory storage media of claim 27 , wherein determining that the first set of predicates is correlated with the second set of predicates includes determining, based on the first set of predicates, that a variable reference in the second set of predicates is constrained to certain values. | 30. The one or more non-transitory storage media of claim 27 , wherein determining that the first set of predicates is correlated with the second set of predicates includes determining, based on the first set of predicates, that a variable reference in the second set of predicates is constrained to certain values. 31. The one or more non-transitory storage media of claim 30 , wherein determining that the variable reference in the second set of predicates is constrained to certain values comprises determining that the variable reference in the second set of predicates is constrained to elements under a particular path indicated in the query. | 0.5 |
9,779,063 | 7 | 8 | 7. A computer-implemented method according to claim 1 , further comprising presenting a document drafting interface to a user comprising an indicator of one or more of the allowable node data object types. | 7. A computer-implemented method according to claim 1 , further comprising presenting a document drafting interface to a user comprising an indicator of one or more of the allowable node data object types. 8. A computer-implemented method according to claim 7 , wherein the document drafting interface prevents entry of a node data object having a type that is not allowed, based on the document schema. | 0.537559 |
9,256,582 | 1 | 4 | 1. A computer program product for converting a presentation file to Darwin Information Typing Architecture (DITA), the computer program product comprising: one or more computer-readable tangible storage devices and program instructions stored on the one or more computer-readable tangible storage devices, the program instructions comprising: prior to receiving a command to convert one or more presentation slides to a DITA document, program instructions to receive a command to group graphical elements located on a presentation slide; responsive to receiving the command to group graphical elements located on the presentation slide, program instructions to assign metadata tags to the grouped graphical elements, the metadata tags comprising at least in part a file name for the group of graphical elements and an indication that the group is to be exported to a single image file; program instructions to receive a command to convert one or more presentation slides to a DITA document, wherein the one or more presentation slides to be converted have been tagged with metadata corresponding to topic type and grouped graphical element file names; program instructions responsive to receiving the command to convert one or more presentation slides to a DITA document, to compile information from the presentation slide, the information selected from the group consisting of the metadata tags, text in the presentation slide, text in a notes section of the presentation slide, and grouped graphical element file names from a first presentation slide of the one or more presentation slides into a string parsed with DITA markup; program instructions to access the metadata tags for a second presentation slide and determining whether the second presentation slide is a new topic; program instructions to determine that the second presentation slide is a new topic; and program instructions responsive to determining that the second presentation slide is a new topic, to convert the string parsed with DITA markup to a DITA topic defined by the metadata in the presentation slide. | 1. A computer program product for converting a presentation file to Darwin Information Typing Architecture (DITA), the computer program product comprising: one or more computer-readable tangible storage devices and program instructions stored on the one or more computer-readable tangible storage devices, the program instructions comprising: prior to receiving a command to convert one or more presentation slides to a DITA document, program instructions to receive a command to group graphical elements located on a presentation slide; responsive to receiving the command to group graphical elements located on the presentation slide, program instructions to assign metadata tags to the grouped graphical elements, the metadata tags comprising at least in part a file name for the group of graphical elements and an indication that the group is to be exported to a single image file; program instructions to receive a command to convert one or more presentation slides to a DITA document, wherein the one or more presentation slides to be converted have been tagged with metadata corresponding to topic type and grouped graphical element file names; program instructions responsive to receiving the command to convert one or more presentation slides to a DITA document, to compile information from the presentation slide, the information selected from the group consisting of the metadata tags, text in the presentation slide, text in a notes section of the presentation slide, and grouped graphical element file names from a first presentation slide of the one or more presentation slides into a string parsed with DITA markup; program instructions to access the metadata tags for a second presentation slide and determining whether the second presentation slide is a new topic; program instructions to determine that the second presentation slide is a new topic; and program instructions responsive to determining that the second presentation slide is a new topic, to convert the string parsed with DITA markup to a DITA topic defined by the metadata in the presentation slide. 4. The computer program product of claim 1 , wherein the program instructions to determine that the second presentation slide is a new topic is based on accessing the topic type, topic title, and topic file name located in the metadata of the second presentation slide. | 0.814738 |
8,346,879 | 13 | 22 | 13. An electronic out-of-office message analysis system comprising: a mailer module comprising instructions stored in memory for receiving an electronic out-of-office message generated by a user in a natural language, the electronic out-of-office message including a time window of absence and an alternate named contact; a temporal expression module comprising instructions stored in memory for identifying and normalizing a temporal expression from text content of the user's out-of-office message to generate a normalized representation of the time window of absence; a named entity recognition module comprising instructions stored in memory for identifying the alternate named contact from the text content of the user's out-of-office message by recognizing named entities in the user's out-of-office message and cross-referencing the recognized named entities with a named entity directory for identifying an alternate named contact corresponding to one of the recognized named entities; a representation module comprising instructions stored in memory for generating a structured representation of the user's out-of-office message which includes a reference to the user, a reference to the identified alternate named contact, and the normalized representation of the time window; an out-of-office module comprising instructions stored in memory for storing the structured representation of the out-of-office message in a database and notifying the user that a conflict exists between the user's out-of-office message and an out-of-office message of the identified alternate named contact, by comparing the normalized representation of the time window included in the structured representation of the user's out-of-office message with a normalized representation of a time window included in a structured representation of the identified alternate named contact's out-of-office message; and a processor which executes the instructions. | 13. An electronic out-of-office message analysis system comprising: a mailer module comprising instructions stored in memory for receiving an electronic out-of-office message generated by a user in a natural language, the electronic out-of-office message including a time window of absence and an alternate named contact; a temporal expression module comprising instructions stored in memory for identifying and normalizing a temporal expression from text content of the user's out-of-office message to generate a normalized representation of the time window of absence; a named entity recognition module comprising instructions stored in memory for identifying the alternate named contact from the text content of the user's out-of-office message by recognizing named entities in the user's out-of-office message and cross-referencing the recognized named entities with a named entity directory for identifying an alternate named contact corresponding to one of the recognized named entities; a representation module comprising instructions stored in memory for generating a structured representation of the user's out-of-office message which includes a reference to the user, a reference to the identified alternate named contact, and the normalized representation of the time window; an out-of-office module comprising instructions stored in memory for storing the structured representation of the out-of-office message in a database and notifying the user that a conflict exists between the user's out-of-office message and an out-of-office message of the identified alternate named contact, by comparing the normalized representation of the time window included in the structured representation of the user's out-of-office message with a normalized representation of a time window included in a structured representation of the identified alternate named contact's out-of-office message; and a processor which executes the instructions. 22. The electronic out-of-office message analysis system of claim 13 , further comprising a plurality of client computers, each configured for generating out-of-office messages, the electronic out-of-office message analysis system being resident on at least one of the client computers and a server computer in communication therewith via a network and wherein the database is linked to the at least one of the client computers and the server computer via the network. | 0.5 |
9,773,045 | 14 | 20 | 14. A system for providing search results, the system comprising: a memory; a processor; and a component that is stored in said memory, that executes on said processor, that receives a query from a user, that determines that said query is one to be asked to a person in addition to, or instead of, a search engine, that obtains objective results corresponding to the query from a corpus of information, that identifies one or more people in a social graph whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query, that creates person results that comprise a portion of said one or more people, that creates, for each of said one or more people, an explanation of each person's relevance to said query, and that provides, to said user, a set of results that comprise said objective results and said person results. | 14. A system for providing search results, the system comprising: a memory; a processor; and a component that is stored in said memory, that executes on said processor, that receives a query from a user, that determines that said query is one to be asked to a person in addition to, or instead of, a search engine, that obtains objective results corresponding to the query from a corpus of information, that identifies one or more people in a social graph whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query, that creates person results that comprise a portion of said one or more people, that creates, for each of said one or more people, an explanation of each person's relevance to said query, and that provides, to said user, a set of results that comprise said objective results and said person results. 20. The system of claim 14 , wherein said component determines that said query is answerable, in part, with subjective information based on whether specific words appear in said query. | 0.793722 |
8,897,500 | 1 | 2 | 1. A method comprising: receiving a request from a speaker to confirm a user identity; retrieving a user profile associated with the user identity; generating, based on the user profile and a level of security desired, a text challenge, wherein generating the text challenge is based on eliciting distinctive behavior of the speaker when compared to behavior of other users, the behavior of other users and the highly distinctive behavior of the speaker being stored in a database of dynamic image features; prompting the speaker to utter the text challenge; recording an audio recording and a video recording of the speaker as the speaker utters the text challenge; and performing speaker verification using the audio recording, the video recording, and the user profile. | 1. A method comprising: receiving a request from a speaker to confirm a user identity; retrieving a user profile associated with the user identity; generating, based on the user profile and a level of security desired, a text challenge, wherein generating the text challenge is based on eliciting distinctive behavior of the speaker when compared to behavior of other users, the behavior of other users and the highly distinctive behavior of the speaker being stored in a database of dynamic image features; prompting the speaker to utter the text challenge; recording an audio recording and a video recording of the speaker as the speaker utters the text challenge; and performing speaker verification using the audio recording, the video recording, and the user profile. 2. The method of claim 1 , wherein the recording of the audio recording and the video recording yields a dynamic image feature. | 0.5 |
7,836,070 | 8 | 9 | 8. A computer-implemented method comprising: receiving a query at a processor; determining, based on the received query, one or more objects and one or more aspects of the objects; registering the one or more objects and the one or more aspects of the objects with one or more event handlers to monitor at least one of the objects and the aspects; evaluating the received query, when at least one of the event handlers indicates a change to at least one of the objects and the aspects; providing a result of the received query based on the evaluation; and registering other event handlers, when at least one of the event handlers indicates the change. | 8. A computer-implemented method comprising: receiving a query at a processor; determining, based on the received query, one or more objects and one or more aspects of the objects; registering the one or more objects and the one or more aspects of the objects with one or more event handlers to monitor at least one of the objects and the aspects; evaluating the received query, when at least one of the event handlers indicates a change to at least one of the objects and the aspects; providing a result of the received query based on the evaluation; and registering other event handlers, when at least one of the event handlers indicates the change. 9. The computer-implemented method of claim 8 wherein receiving further comprises: receiving the query as a message and implementing the query using SQL (Structured Query Language) or XQuery. | 0.738356 |
7,917,455 | 1 | 2 | 1. A computing device for rapidly evaluating logical expressions, the computing device comprising: a memory space for storing code; a processor, coupled to the memory space, executing the code to cause the computing device to repeatedly perform operations of: determining a set of primitives defining some or all of a current state of a model of a virtual or real world; accessing a set of logical expressions including the primitives, each of the logical expressions being either a true or false statement about the current state of the model, wherein a union of the logical expressions is expressed in one or more directed acyclic graphs; and computing which of the logical expressions are true statements about the current state of the model by traversing the one or more directed acyclic graphs once exactly in one path from a root node to a leaf node in the one or more directed acyclic graphs. | 1. A computing device for rapidly evaluating logical expressions, the computing device comprising: a memory space for storing code; a processor, coupled to the memory space, executing the code to cause the computing device to repeatedly perform operations of: determining a set of primitives defining some or all of a current state of a model of a virtual or real world; accessing a set of logical expressions including the primitives, each of the logical expressions being either a true or false statement about the current state of the model, wherein a union of the logical expressions is expressed in one or more directed acyclic graphs; and computing which of the logical expressions are true statements about the current state of the model by traversing the one or more directed acyclic graphs once exactly in one path from a root node to a leaf node in the one or more directed acyclic graphs. 2. The computing device as recited in claim 1 , wherein the one or more directed acyclic graphs include at least one node associated with one of the primitives used in at least one of the logical expressions, a value of the one of the primitives being evaluated to reflect the current state of the model when the node is visited in traversing the one or more directed acyclic graphs. | 0.5 |
8,418,165 | 5 | 7 | 5. At a computer hardware system, the computer hardware system including one or more designers and a visualizer, the one or more designers and the visualizer for visually formulating application package designs that customize the appearance and layout of corresponding application packages, the computer system also including a package generator for generating application packages from application package designs, generated application packages being in a format expected by product deployment software, a method of generating an application package for deploying an application across a plurality of server computers, the method comprising: customizing an application package design, including: presenting the structure of an application package through an arrangement of user-interface elements in a view of the visualizer, the user-interface elements corresponding to application package element references, the application package element references referencing application package elements; receiving user input within the visualizer view; in response to the user input: visually altering one or more user-interface elements in the arrangement of user-interface elements; and altering the structure of the application package by the one or more designers altering application package element references corresponding the visually altered one or more user-interface elements; and generating a customized application package from the customized application design, creation of the application package including: creating an application package element manifest by traversing the altered structure of application package in accordance with the application package element references to identify application package elements that are to be included in the customized application package; transforming the application package element manifest into one or more manifest files in a format that is compatible with a packaging schema for the product deployment software by mapping between types and properties in an object model and elements and attributes in the packaging schema; previewing the customized application package on disk by creating, from the one or more manifest files, a directory hierarchy comprising the identified application package elements and placing the identified application package elements in locations relative to the directory hierarchy on at least one server computer of the plurality of server computers; and using the directory hierarchy to bundle the identified application package elements into one file for deploying the collaborative server application across the plurality of server computers, the one file in a format expected by the product deployment software. | 5. At a computer hardware system, the computer hardware system including one or more designers and a visualizer, the one or more designers and the visualizer for visually formulating application package designs that customize the appearance and layout of corresponding application packages, the computer system also including a package generator for generating application packages from application package designs, generated application packages being in a format expected by product deployment software, a method of generating an application package for deploying an application across a plurality of server computers, the method comprising: customizing an application package design, including: presenting the structure of an application package through an arrangement of user-interface elements in a view of the visualizer, the user-interface elements corresponding to application package element references, the application package element references referencing application package elements; receiving user input within the visualizer view; in response to the user input: visually altering one or more user-interface elements in the arrangement of user-interface elements; and altering the structure of the application package by the one or more designers altering application package element references corresponding the visually altered one or more user-interface elements; and generating a customized application package from the customized application design, creation of the application package including: creating an application package element manifest by traversing the altered structure of application package in accordance with the application package element references to identify application package elements that are to be included in the customized application package; transforming the application package element manifest into one or more manifest files in a format that is compatible with a packaging schema for the product deployment software by mapping between types and properties in an object model and elements and attributes in the packaging schema; previewing the customized application package on disk by creating, from the one or more manifest files, a directory hierarchy comprising the identified application package elements and placing the identified application package elements in locations relative to the directory hierarchy on at least one server computer of the plurality of server computers; and using the directory hierarchy to bundle the identified application package elements into one file for deploying the collaborative server application across the plurality of server computers, the one file in a format expected by the product deployment software. 7. The method of claim 5 , wherein customizing the application package includes customizing a feature using a feature designer, wherein the feature designer receives user input and based on the user input performs at least one of: configures project items within the feature, combines combinations of project items into the feature, sets properties on the feature, visualizes defined project items in a project, adds a project item to the feature, or removes a project item from the feature. | 0.513861 |
7,730,455 | 21 | 22 | 21. An article of manufacture having one or more recordable media storing instructions thereon which, when executed by a system, cause the system to perform a method comprising: evaluating resource usage of computer program code; and annotating the computer program, by inserting one or more operations into the computer program code that will cause one or more operations to be performed when the program code is executed for resource use safety, based on a result of evaluating the resource usage of the computer program code. | 21. An article of manufacture having one or more recordable media storing instructions thereon which, when executed by a system, cause the system to perform a method comprising: evaluating resource usage of computer program code; and annotating the computer program, by inserting one or more operations into the computer program code that will cause one or more operations to be performed when the program code is executed for resource use safety, based on a result of evaluating the resource usage of the computer program code. 22. The article of manufacture defined in claim 21 wherein inserting one or more operations comprises inserting one or more operations into the computer program code to remove one or more resource consumption constraints. | 0.794227 |
4,040,191 | 1 | 3 | 1. An educational game comprising a substantially planar support surface defining a substantially centrally located aperture, shaft means adapted to communicate with said aperture, said support surface adapted to rotate its own axis about said shaft means, platform means integral with said shaft means and disposed at one distal end thereof, a plurality of slotted channels disposed substantially equidistant from each other on a surface of said support surface, sleeve means open at at least one end thereof and disposed on said platform means, a hollow walled housing open at at least one end thereof and adapted to receive and concentrically engage said sleeve means, and a plurality of clip means containing printed matter thereon dispersed in said sleeve means, each of said clip means for selective clipped affixment to said platform means. | 1. An educational game comprising a substantially planar support surface defining a substantially centrally located aperture, shaft means adapted to communicate with said aperture, said support surface adapted to rotate its own axis about said shaft means, platform means integral with said shaft means and disposed at one distal end thereof, a plurality of slotted channels disposed substantially equidistant from each other on a surface of said support surface, sleeve means open at at least one end thereof and disposed on said platform means, a hollow walled housing open at at least one end thereof and adapted to receive and concentrically engage said sleeve means, and a plurality of clip means containing printed matter thereon dispersed in said sleeve means, each of said clip means for selective clipped affixment to said platform means. 3. The game as defined in claim 1 wherein the internal diameter of said sleeve is smaller than the external diameter of said housing. | 0.550676 |
8,615,478 | 11 | 12 | 11. The article of claim 10 further storing instructions that, if executed, enable the processor-based system to develop a forest supervised classifier. | 11. The article of claim 10 further storing instructions that, if executed, enable the processor-based system to develop a forest supervised classifier. 12. The article of claim 11 further storing instructions that, if executed, enable the processor-based system to sum the affinity between said first and second points in each tree of the forest and take the average as the result. | 0.5 |
9,270,736 | 9 | 10 | 9. The server according to claim 7 , wherein the Q-context includes a predefined set of objects, properties, and values that define the Q-context assertions, the queries, and the rules relevant to each of the instrumented semantic objects represented by an OBJECT-PROPERTY-VALUE assertion. | 9. The server according to claim 7 , wherein the Q-context includes a predefined set of objects, properties, and values that define the Q-context assertions, the queries, and the rules relevant to each of the instrumented semantic objects represented by an OBJECT-PROPERTY-VALUE assertion. 10. The server according to claim 9 , wherein OBJECT refers to a reference to an instrumented semantic object, PROPERTY is the reference to a property of the instrumented semantic object in a given namespace, and VALUE is one of a reference, a scalar value, or an aggregate value. | 0.591837 |
8,285,859 | 5 | 6 | 5. A method of claim 3 , further comprising: receiving a request from an external semantic information broker to join the respective one of the information spaces; authenticating the external semantic information broker in response to the request; determining a stability factor for the external semantic information broker based on the authentication; comparing the stability factor for the external semantic information broker against the stability factors of the one or more master semantic information brokers of the respective information space; and adding the external semantic information broker to the respective information space as a new master semantic information broker based on the comparison. | 5. A method of claim 3 , further comprising: receiving a request from an external semantic information broker to join the respective one of the information spaces; authenticating the external semantic information broker in response to the request; determining a stability factor for the external semantic information broker based on the authentication; comparing the stability factor for the external semantic information broker against the stability factors of the one or more master semantic information brokers of the respective information space; and adding the external semantic information broker to the respective information space as a new master semantic information broker based on the comparison. 6. A method of claim 5 , wherein the external semantic information broker assumes a role of the master semantic information broker if no response to the request is provided within a predetermined period of time. | 0.5 |
8,630,919 | 8 | 10 | 8. The apparatus of claim 7 , wherein the at least one assertion template includes a grammatical pattern and a field name representing the data field. | 8. The apparatus of claim 7 , wherein the at least one assertion template includes a grammatical pattern and a field name representing the data field. 10. The apparatus of claim 8 wherein the at least one assertion template includes a connotation indicator and wherein the assertion is published into a narrative based on the connotation. | 0.569124 |
5,526,463 | 8 | 14 | 8. A system according to claim 7 wherein said data reduction means is adapted whereby w=b+(s-1)c. | 8. A system according to claim 7 wherein said data reduction means is adapted whereby w=b+(s-1)c. 14. A system according to claim 8 wherein w=12, k=8, s=3, b=4, c=4, and a.sub.i =1/b. | 0.532967 |
7,865,465 | 1 | 9 | 1. A model edit control system for controlling editing of a data model, the model edit control system comprising: a computer; and a computer readable medium storing instructions, wherein the instructions, when executed by the computer, cause the computer to implement; a model repository manager, wherein the model repository manager is configured to copy a stored model stored in a repository to multiple users for executing actions on multiple model copies in parallel; an action log manager, wherein the action log manager is configured to create a model action log for tracking actions executed on the stored model and to create a current action log for each model copy to record actions executed on the model copy; and a model merger manager, wherein the model merger manager is configured to merge the model copies into the stored model in the repository by playing actions in the current action log against the stored model, wherein the model merger manager comprises: an action player, wherein the action player is configured to play the executed actions in the model copies against the stored model in the repository based on the current action log of each model copy; and a conflict handler, wherein the conflict handler is configured to handle conflict between the stored model in the repository and the model copies based on the action log of each model copy, wherein the conflict handler comprises: a conflict information handler, wherein the conflict information handler is configured to provide information of at least one conflict identified responsive to playing the executed actions to the user of the model copy; and an option handler, wherein the option handler is configured to present options of resolving the at least one conflict and receiving a selected option. | 1. A model edit control system for controlling editing of a data model, the model edit control system comprising: a computer; and a computer readable medium storing instructions, wherein the instructions, when executed by the computer, cause the computer to implement; a model repository manager, wherein the model repository manager is configured to copy a stored model stored in a repository to multiple users for executing actions on multiple model copies in parallel; an action log manager, wherein the action log manager is configured to create a model action log for tracking actions executed on the stored model and to create a current action log for each model copy to record actions executed on the model copy; and a model merger manager, wherein the model merger manager is configured to merge the model copies into the stored model in the repository by playing actions in the current action log against the stored model, wherein the model merger manager comprises: an action player, wherein the action player is configured to play the executed actions in the model copies against the stored model in the repository based on the current action log of each model copy; and a conflict handler, wherein the conflict handler is configured to handle conflict between the stored model in the repository and the model copies based on the action log of each model copy, wherein the conflict handler comprises: a conflict information handler, wherein the conflict information handler is configured to provide information of at least one conflict identified responsive to playing the executed actions to the user of the model copy; and an option handler, wherein the option handler is configured to present options of resolving the at least one conflict and receiving a selected option. 9. The model edit control system as claimed in claim 1 , wherein the action log manager comprises: a log file creator, wherein the log file creator is configured to create a model log file for the stored model and a current copy log file when a model copy is created; a model log file handler, wherein the model log file hander is configured to track and record, in the model log file, actions executed on the stored model; and a current copy log file handler, wherein the current copy log file hander is configured to track and record, in the current log file, actions executed on its corresponding model copy. | 0.5 |
8,407,259 | 14 | 15 | 14. The non-transitory computer readable medium according to claim 13 wherein said generating comprises combining said first, second, third, and fourth values. | 14. The non-transitory computer readable medium according to claim 13 wherein said generating comprises combining said first, second, third, and fourth values. 15. The non-transitory computer readable medium according to claim 14 , wherein said combining comprises concatenating said first, second, third, and fourth values. | 0.5 |
8,885,797 | 15 | 19 | 15. A network device comprising: a memory to store one or more instructions; and a processor to execute the one or more instructions to: receive, via a first network connection, a key and information identifying a security level, of a plurality of security levels, from a different network device, the security level and the key being associated with a call transferred to the network device, by the different network device, via a second network connection that is different than the first network connection, the call being transferred using an access telephone number selected, from a plurality of access numbers, based on the security level, the security level being determined by the other network device prior to the security level being received by the network device, the security level and the key being received to perform speaker verification of a user associated with the call, associate the security level with the transferred call based on the key, perform, at a level corresponding to the security level and using a user profile that is associated with the user, the speaker verification of the user to generate a result, transfer, based on performing the speaker verification and via the second network connection, the call back to the different network device, and transmit, via the first network connection, the result and the key to the different network device, the different network device performing a transaction associated with the call based on the result. | 15. A network device comprising: a memory to store one or more instructions; and a processor to execute the one or more instructions to: receive, via a first network connection, a key and information identifying a security level, of a plurality of security levels, from a different network device, the security level and the key being associated with a call transferred to the network device, by the different network device, via a second network connection that is different than the first network connection, the call being transferred using an access telephone number selected, from a plurality of access numbers, based on the security level, the security level being determined by the other network device prior to the security level being received by the network device, the security level and the key being received to perform speaker verification of a user associated with the call, associate the security level with the transferred call based on the key, perform, at a level corresponding to the security level and using a user profile that is associated with the user, the speaker verification of the user to generate a result, transfer, based on performing the speaker verification and via the second network connection, the call back to the different network device, and transmit, via the first network connection, the result and the key to the different network device, the different network device performing a transaction associated with the call based on the result. 19. The network device of claim 15 , where the key and the information identifying the security level are received via a packet switched network and the second network comprises a Public Switched Telephone Network (PSTN). | 0.780318 |
5,586,319 | 2 | 3 | 2. The method of claim 1 wherein said plurality of user commands includes an addInstance command that adds an instance of a specified cell to the netlist. | 2. The method of claim 1 wherein said plurality of user commands includes an addInstance command that adds an instance of a specified cell to the netlist. 3. The method of claim 2 wherein the addInstance command has as parameters an instance name and a cell name. | 0.644737 |
9,153,231 | 5 | 10 | 5. A computing device, comprising: at least one processor; a memory device including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive an audio signal; to perform speech recognition processing on the audio signal using a neural network to obtain speech recognition results; and to update the neural network during runtime based at least in part on the speech recognition results. | 5. A computing device, comprising: at least one processor; a memory device including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive an audio signal; to perform speech recognition processing on the audio signal using a neural network to obtain speech recognition results; and to update the neural network during runtime based at least in part on the speech recognition results. 10. The computing device of claim 5 , wherein the at least one processor is further configured: to compute a feature vector from the audio signal; to determine a hidden Markov model state associated with the feature vector from the first result; and wherein the at least one processor configured to update the neural network comprises the at least one processor configured to use the feature vector as an input to the neural network and the hidden Markov model state as an output to the neural network. | 0.605346 |
9,972,034 | 1 | 3 | 1. A system comprising one or more processors and a non-transitory storage medium comprising program logic for execution by the one or more processors, the program logic comprising: a native advertisement placement engine that: performs an analysis comprising: obtaining a Document Object Model of an HTML document; identifying Document Object Model elements, of the Document Object Model, associated with native advertisement placement candidate containers; identifying, in the Document Object Model, HTML tag sequences that include at least L tags, where L is a specified number, repeat at least R times, where R is a specified number, and all correspond to a single element of the Document Object Model; constructing a suffix tree of a string of tags comprising all tags in the Document Object Model; and performing a traversal of the suffix tree, beginning with a root node, and computes, for each node that is non-root and non-leaf, a number of leaf nodes of the each node; based at least in part on the analysis associated with the Document Object Model, and utilizing at least some of the identified elements, determines, within the Document Object Model, one or more native advertisement placement candidate containers; displaying, on a display, advertisements on the determined one or more native advertisement placement candidate containers. | 1. A system comprising one or more processors and a non-transitory storage medium comprising program logic for execution by the one or more processors, the program logic comprising: a native advertisement placement engine that: performs an analysis comprising: obtaining a Document Object Model of an HTML document; identifying Document Object Model elements, of the Document Object Model, associated with native advertisement placement candidate containers; identifying, in the Document Object Model, HTML tag sequences that include at least L tags, where L is a specified number, repeat at least R times, where R is a specified number, and all correspond to a single element of the Document Object Model; constructing a suffix tree of a string of tags comprising all tags in the Document Object Model; and performing a traversal of the suffix tree, beginning with a root node, and computes, for each node that is non-root and non-leaf, a number of leaf nodes of the each node; based at least in part on the analysis associated with the Document Object Model, and utilizing at least some of the identified elements, determines, within the Document Object Model, one or more native advertisement placement candidate containers; displaying, on a display, advertisements on the determined one or more native advertisement placement candidate containers. 3. The system of claim 1 , wherein suffix trees are utilized in identifying the HTML tag sequences. | 0.882143 |
9,568,993 | 1 | 15 | 1. A method for automated avatar mood effects in a virtual world, comprising: detecting occurrence of a mood changing condition relatable to a user's avatar; determining an avatar mood effect from the plurality of predefined avatar mood effects to be applied to the user's avatar in the virtual world based on the detected mood changing condition; automatically applying the avatar mood effect to the user's avatar in the virtual world in response to detecting occurrence of the mood changing condition and determining an applicable avatar mood effect based on the detected mood changing condition; and presenting the automatically applied avatar mood effect in association with the user's avatar in the virtual world, wherein presenting the automatically applied avatar mood effect comprises presenting a predefined script spoken by the user's avatar in at least one of a visual form and an audible form and presenting different colored clothing worn by the user's avatar depending on the avatar mood effect applied, bright colored clothing worn by the user's avatar expressing a happy mood and dark, black or gray colored clothing worn by the user's avatar expressing a sad mood. | 1. A method for automated avatar mood effects in a virtual world, comprising: detecting occurrence of a mood changing condition relatable to a user's avatar; determining an avatar mood effect from the plurality of predefined avatar mood effects to be applied to the user's avatar in the virtual world based on the detected mood changing condition; automatically applying the avatar mood effect to the user's avatar in the virtual world in response to detecting occurrence of the mood changing condition and determining an applicable avatar mood effect based on the detected mood changing condition; and presenting the automatically applied avatar mood effect in association with the user's avatar in the virtual world, wherein presenting the automatically applied avatar mood effect comprises presenting a predefined script spoken by the user's avatar in at least one of a visual form and an audible form and presenting different colored clothing worn by the user's avatar depending on the avatar mood effect applied, bright colored clothing worn by the user's avatar expressing a happy mood and dark, black or gray colored clothing worn by the user's avatar expressing a sad mood. 15. The method of claim 1 , further comprising allowing mining of mood effect changes and any actions taken by the user's avatar while in a particular mood effect. | 0.854464 |
9,002,395 | 1 | 6 | 1. A messaging system that communicates with a plurality of location aware personal communications devices each carried by a person, the messaging system comprising: a database comprising a plurality of zone specifications and a plurality of device records; a device registration module wherein the location aware personal communications devices each communicate wirelessly and automatically supply device identification information and location information to the device registration module and wherein the device identification information is stored in the device records to thereby automatically register the location aware personal communications devices with the messaging system; a message reception module wherein the messaging system accepts an input text video or audio message from a publisher into their location aware personal device, the publisher setting the publication zone, wherein the input message comprises a payload and publication zone data specifying at least one publication zone and wherein every publication zone is a geographic area; a message targeting module that selects a plurality of recipient devices from the device records, wherein the recipient devices are located inside of the at least one publication zone; and a message publication module that sends a published message comprising the payload to the recipient devices to thereby pass the payload to a plurality of human recipients wherein each human recipient is carrying at least one of the recipient devices, wherein the database comprises permission specifications wherein the publisher is restricted to directing messages only to at least one permitted zone, wherein the publication zone is not geographically the same as the permitted zone, the at least one publication zone that was set by the publisher intersects the at least one permitted zone, and wherein one of the location aware personal communications devices located inside the permitted zone that is unable to wirelessly connect to the messaging system connects to the messaging system by way of another one of the location aware personal communications devices located within the publication zone based on the another one of the location aware personal communications devices enabling the connection and wirelessly routing the published message to the one of the location aware personal communications devices located inside the permitted zone. | 1. A messaging system that communicates with a plurality of location aware personal communications devices each carried by a person, the messaging system comprising: a database comprising a plurality of zone specifications and a plurality of device records; a device registration module wherein the location aware personal communications devices each communicate wirelessly and automatically supply device identification information and location information to the device registration module and wherein the device identification information is stored in the device records to thereby automatically register the location aware personal communications devices with the messaging system; a message reception module wherein the messaging system accepts an input text video or audio message from a publisher into their location aware personal device, the publisher setting the publication zone, wherein the input message comprises a payload and publication zone data specifying at least one publication zone and wherein every publication zone is a geographic area; a message targeting module that selects a plurality of recipient devices from the device records, wherein the recipient devices are located inside of the at least one publication zone; and a message publication module that sends a published message comprising the payload to the recipient devices to thereby pass the payload to a plurality of human recipients wherein each human recipient is carrying at least one of the recipient devices, wherein the database comprises permission specifications wherein the publisher is restricted to directing messages only to at least one permitted zone, wherein the publication zone is not geographically the same as the permitted zone, the at least one publication zone that was set by the publisher intersects the at least one permitted zone, and wherein one of the location aware personal communications devices located inside the permitted zone that is unable to wirelessly connect to the messaging system connects to the messaging system by way of another one of the location aware personal communications devices located within the publication zone based on the another one of the location aware personal communications devices enabling the connection and wirelessly routing the published message to the one of the location aware personal communications devices located inside the permitted zone. 6. The messaging system of claim 1 wherein the other one of the location aware personal communications devices is located outside the publication zone. | 0.948429 |
8,005,294 | 2 | 3 | 2. The method of claim 1 , wherein the feature information includes moment features, geometrical and positional information based features, pixel distribution features, topological features, stroke connectedness features, and reference line features. | 2. The method of claim 1 , wherein the feature information includes moment features, geometrical and positional information based features, pixel distribution features, topological features, stroke connectedness features, and reference line features. 3. The method of claim 2 , wherein the imaged word is an Arabic word and the feature information further includes aspect ratio features, location and number of disconnected dots, and chain code features. | 0.5 |
9,646,611 | 4 | 6 | 4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. | 4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. 6. The computing system of claim 4 wherein the linguistic processing system comprises: a first linguistic processing system disposed on the computing system and including a speech recognition system and a natural language understanding system, the speech recognition system configured to generate a textual representation of the utterance and the natural language understanding system identifying the intent and arguments in a first linguistic processing result, and to further disambiguate otherwise ambiguous arguments based on the current context. | 0.5 |
8,234,174 | 31 | 36 | 31. The method of claim 27 , further comprising: a. configuring the at least one host server with interactive advertisement builder for generating advertisements, an interactive website builder for generating linked webpages, or combinations thereof; and b. enabling the remote company user to manage the advertisement builder and generate advertisements thereby, to manage the interactive website builder and generate linked remote company webpages thereby, or combinations thereof. | 31. The method of claim 27 , further comprising: a. configuring the at least one host server with interactive advertisement builder for generating advertisements, an interactive website builder for generating linked webpages, or combinations thereof; and b. enabling the remote company user to manage the advertisement builder and generate advertisements thereby, to manage the interactive website builder and generate linked remote company webpages thereby, or combinations thereof. 36. The method of claim 31 , further comprising: a. configuring the at least one host server to monitor website referrals to keep track of which websites refer clients to hosted web pages. | 0.698718 |
7,680,890 | 1 | 3 | 1. A computer-implemented method comprising: receiving a first classification value associated with an e-mail message that is an output of a first classification tool and a second classification value associated with said e-mail message that is an output of a second classification tool, said first classification value and said second classification value indicative of whether said e-mail message is spam; and generating a single, aggregated classification value for said e-mail message by combining said first classification value and said second classification value using a fuzzy logic-based voting mechanism, wherein said first classification value and said second classification value represent probabilities P 1 and P 2 , respectively, and said single, aggregated classification value represents a combined probability P combined , and wherein said fuzzy logic-based voting mechanism includes a voting formula comprising:
P combined =( P 1 ×P 2 )/(( P 1 ×P 2 )+(1− P 1 )(1− P 2 )). | 1. A computer-implemented method comprising: receiving a first classification value associated with an e-mail message that is an output of a first classification tool and a second classification value associated with said e-mail message that is an output of a second classification tool, said first classification value and said second classification value indicative of whether said e-mail message is spam; and generating a single, aggregated classification value for said e-mail message by combining said first classification value and said second classification value using a fuzzy logic-based voting mechanism, wherein said first classification value and said second classification value represent probabilities P 1 and P 2 , respectively, and said single, aggregated classification value represents a combined probability P combined , and wherein said fuzzy logic-based voting mechanism includes a voting formula comprising:
P combined =( P 1 ×P 2 )/(( P 1 ×P 2 )+(1− P 1 )(1− P 2 )). 3. The method of claim 1 , wherein said first classification value has an associated first confidence factor and said second classification value has an associated second confidence factor, and wherein said combining said first classification value and said second classification value produces a confidence factor associated with said single, aggregated classification value that is greater than said first confidence factor and said second confidence factor. | 0.591474 |
9,170,989 | 5 | 6 | 5. The computerized method of claim 4 , wherein the action of the first web site server receiving data indicating an actuation of the user interaction function further comprises receiving a comment sourced by the entity and, the first web site server including the comment when sending the data. | 5. The computerized method of claim 4 , wherein the action of the first web site server receiving data indicating an actuation of the user interaction function further comprises receiving a comment sourced by the entity and, the first web site server including the comment when sending the data. 6. The computerized method of claim 5 , wherein the action of the first web site server receiving data indicating an actuation of the user interaction function further comprises receiving an indication that the comment is private. | 0.5 |
9,348,417 | 9 | 13 | 9. In a computing environment, a system comprising: a plurality of input devices that provide raw data corresponding to one or more input modalities; an input processor configured to process the raw data into input events; one or more sensors that provide environmental input; and a recommendation engine configured to: select a subset of the input events based on one or more of the following: user defined preferences, and a current operating mode of a program; determine a combined meaning of the subset of input events; and provide output data for input by the program, the output data corresponding to the combined meaning of the subset of input events and the environmental input provided by the one or more sensors. | 9. In a computing environment, a system comprising: a plurality of input devices that provide raw data corresponding to one or more input modalities; an input processor configured to process the raw data into input events; one or more sensors that provide environmental input; and a recommendation engine configured to: select a subset of the input events based on one or more of the following: user defined preferences, and a current operating mode of a program; determine a combined meaning of the subset of input events; and provide output data for input by the program, the output data corresponding to the combined meaning of the subset of input events and the environmental input provided by the one or more sensors. 13. The system of claim 9 wherein the input processor includes one or more of the following: an audio processing component, a visual processing component, a touch processing component, a gesture processing component, and a pointer processing component or a text processing component. | 0.518707 |
7,689,709 | 6 | 12 | 6. A method comprising: polling, by a first adapter of a sending application, a routing module and a mapping module of an integration server, the sending application sending a message to a receiving application, the message comprising message content in an original message format, the integration server being implemented on one or more processors and utilizing one or more open standard file formats, the polling comprising a request for an identity of the receiving application from the routing module and for a receiving application file format used by the receiving application from the mapping module; wrapping, at the first adapter, the message in a markup language file envelope that corresponds to one of the one or more open standard file formats of the integration server if the receiving application file format is identical to a sending application file format used by the sending application, the wrapping comprising adding a message header in the one of the one or more open standard file formats of the integration server while leaving the message content unchanged and without mapping or converting the message content to a file according to any of the one or more open standard file formats of the integration server; sending the message in the markup language file envelope to a second adapter of the receiving application via one or more pipeline services on the integration server; the one or more pipeline services utilizing the message header for logical routing of the message; unwrapping the message from the markup language file envelope at the second adapter; and passing the message content to the receiving application substantially in the original message format; wherein the markup language corresponds to extensible markup language (XML). | 6. A method comprising: polling, by a first adapter of a sending application, a routing module and a mapping module of an integration server, the sending application sending a message to a receiving application, the message comprising message content in an original message format, the integration server being implemented on one or more processors and utilizing one or more open standard file formats, the polling comprising a request for an identity of the receiving application from the routing module and for a receiving application file format used by the receiving application from the mapping module; wrapping, at the first adapter, the message in a markup language file envelope that corresponds to one of the one or more open standard file formats of the integration server if the receiving application file format is identical to a sending application file format used by the sending application, the wrapping comprising adding a message header in the one of the one or more open standard file formats of the integration server while leaving the message content unchanged and without mapping or converting the message content to a file according to any of the one or more open standard file formats of the integration server; sending the message in the markup language file envelope to a second adapter of the receiving application via one or more pipeline services on the integration server; the one or more pipeline services utilizing the message header for logical routing of the message; unwrapping the message from the markup language file envelope at the second adapter; and passing the message content to the receiving application substantially in the original message format; wherein the markup language corresponds to extensible markup language (XML). 12. The method in accordance with claim 6 , wherein the message format is an Idoc message format. | 0.9379 |
8,961,183 | 5 | 6 | 5. The system of claim 1 , wherein the system further comprises altering the specific audible answer to sound like a voice reading the prerecorded fill-in-the-blank story. | 5. The system of claim 1 , wherein the system further comprises altering the specific audible answer to sound like a voice reading the prerecorded fill-in-the-blank story. 6. The system of claim 5 , wherein the altering comprises changing a pitch of the specific audible answer to match a pitch of the prerecorded fill-in-the-blank story. | 0.5 |
7,822,762 | 11 | 12 | 11. The method of claim 9 , further comprising: at least one of explicitly or implicitly training the model based upon entity feedback. | 11. The method of claim 9 , further comprising: at least one of explicitly or implicitly training the model based upon entity feedback. 12. The method of claim 11 , further comprising automatically gathering data associated with the entity based on, at least in part, an objective, goal, mission, task, or purpose of the entity. | 0.5 |
9,348,736 | 19 | 21 | 19. The computer readable medium of claim 18 , wherein the identification rule further comprises a reference parameter within the SAUT used as a starting point of the identification rule. | 19. The computer readable medium of claim 18 , wherein the identification rule further comprises a reference parameter within the SAUT used as a starting point of the identification rule. 21. The computer readable medium of claim 19 , wherein a plurality of identification rules are combined to identify the element within the SAUT. | 0.785714 |
7,640,267 | 5 | 6 | 5. The method of claim 1 , wherein the information resource is detected before creating the second semantic object. | 5. The method of claim 1 , wherein the information resource is detected before creating the second semantic object. 6. The method of claim 5 , wherein the information resource is detected upon the information resource being published on the Internet. | 0.5 |
7,949,627 | 1 | 3 | 1. A computer-implemented user-interface method of selecting and presenting at least one content item in which the selection is based at least in part on learning periodicities of user selections of content items, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by the user for identifying desired content items; in response to the input entered by the user, presenting content items to the user; receiving actions from the user resulting in the selection of content items from the subset; analyzing the descriptive terms associated with the selected content items to identify sets of actions resulting in the selection of similar content items, wherein similarity is determined by comparing the descriptive terms associated with any one of the selected content items with any of the previously selected content items; analyzing the date, day, and time of at least two of the individual selection actions of the sets of actions to learn periodicities of user actions resulting in the selections of similar content items, wherein the periodicity corresponding to a particular set of actions for selecting similar content items indicates the amount of time between the user actions of the set; associating the learned periodicities of the sets of actions resulting in the selection of similar content items with the corresponding descriptive terms associated with the similar content items that were selected; and subsequent to learning at least one periodicity of the actions of the user, selecting and presenting at least one content item, wherein the selection of the at least one content item is based on at least one of the learned periodicities similar to the date, day, and time of said subsequent selecting and presenting of the at least one content item. | 1. A computer-implemented user-interface method of selecting and presenting at least one content item in which the selection is based at least in part on learning periodicities of user selections of content items, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by the user for identifying desired content items; in response to the input entered by the user, presenting content items to the user; receiving actions from the user resulting in the selection of content items from the subset; analyzing the descriptive terms associated with the selected content items to identify sets of actions resulting in the selection of similar content items, wherein similarity is determined by comparing the descriptive terms associated with any one of the selected content items with any of the previously selected content items; analyzing the date, day, and time of at least two of the individual selection actions of the sets of actions to learn periodicities of user actions resulting in the selections of similar content items, wherein the periodicity corresponding to a particular set of actions for selecting similar content items indicates the amount of time between the user actions of the set; associating the learned periodicities of the sets of actions resulting in the selection of similar content items with the corresponding descriptive terms associated with the similar content items that were selected; and subsequent to learning at least one periodicity of the actions of the user, selecting and presenting at least one content item, wherein the selection of the at least one content item is based on at least one of the learned periodicities similar to the date, day, and time of said subsequent selecting and presenting of the at least one content item. 3. The method of claim 1 , wherein the content items include at least one of television program items, movie items, audio/video media items, music items, contact information items, personal schedule items, web content items, and purchasable product items. | 0.829088 |
8,078,631 | 10 | 16 | 10. A computer-readable storage medium containing a program which, when executed, performs an operation for comparing query-related information, the operation comprising: providing a data abstraction layer which defines one or more logical fields, wherein a definition for each logical field specifies (i) a name, and (ii) an access method that maps the logical field to data in an underlying data repository; receiving from a first user a first set of abstract queries, associated with the first user, composed from the one or more logical fields defined in the data abstraction layer, wherein the first set of abstract queries comprises more than one query; receiving from a second user, different from the first user, a second set of abstract queries, associated with the second user, composed from the one or more logical fields defined in the data abstraction layer, wherein the second set of abstract queries comprises more than one query; comparing at least one query in the first set of abstract queries with at least one query in the second set of abstract queries to determine a degree of similarity between the first set of abstract queries and the second set of abstract queries; and issuing a notification of the degree of similarity. | 10. A computer-readable storage medium containing a program which, when executed, performs an operation for comparing query-related information, the operation comprising: providing a data abstraction layer which defines one or more logical fields, wherein a definition for each logical field specifies (i) a name, and (ii) an access method that maps the logical field to data in an underlying data repository; receiving from a first user a first set of abstract queries, associated with the first user, composed from the one or more logical fields defined in the data abstraction layer, wherein the first set of abstract queries comprises more than one query; receiving from a second user, different from the first user, a second set of abstract queries, associated with the second user, composed from the one or more logical fields defined in the data abstraction layer, wherein the second set of abstract queries comprises more than one query; comparing at least one query in the first set of abstract queries with at least one query in the second set of abstract queries to determine a degree of similarity between the first set of abstract queries and the second set of abstract queries; and issuing a notification of the degree of similarity. 16. The computer-readable storage medium of claim 10 , wherein the step of comparing at least one query in the first set of abstract queries with at least one query in the second set of abstract queries to determine a degree of similarity between the first set of abstract queries and the second set of abstract queries comprises at least one of: comparing query conditions of the at least one query in the first set of abstract queries with query conditions of the at least one query in the second set of abstract queries; comparing query results of the at least one query in the first set of abstract queries with query results of the at least one query in the second set of abstract queries; and comparing a query analysis routine associated with the at least one query in the first set of abstract queries to a query analysis routine associated with the at least one query in the second set of abstract queries. | 0.5 |
8,577,898 | 9 | 13 | 9. A writing rating method implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium including programming instructions operable to rate a writing written in any language, comprising the steps of: providing a style score based on how a language style of the writing is different from at least one training document; determining whether the style score is greater than a predetermined threshold, and when the style score is greater than the predetermined threshold, rejecting the writing; providing a punctuation score based on a comparison between the use of punctuation marks in the writing and the use of punctuation marks in the at least one training document; providing a spelling score based on spelling accuracy of the writing; providing a quotation score based on a comparison between sentences from the writing and the sentences from the at least one training document, wherein the providing the quotation score comprises dividing the writing into extracted sentences, comparing each of the extracted sentences to the at least one training document, and calculating a percentage of extracted sentences that match the at least one training document; providing an enrichment score based on new and accurate vocabularies used in the writing, wherein the providing the enrichment score comprises extracting basis words from the writing to obtain a total number of unique words in the writing and dividing the total number of unique words by a total number of words in the writing; providing a syntax analysis score based on grammar mistakes in the writing; providing a focus score based on a topic of the essay and a focus of the writing on that topic; providing an idea and cohesion scores based on whether the writing provides a close or far away cohesive correct answer; and providing the rating of the writing based on the style score, the punctuation score, the spelling score, the quotation score, the enrichment score, the syntax analysis score, the focus score, the idea score and the cohesion score, wherein the rating of the writing is an overall rating or detailed score for the writing that is generated from the style score, the punctuation score, the spelling score, the quotation score, the enrichment score, the syntax analysis score, the focus score, the idea score and the cohesion score. | 9. A writing rating method implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium including programming instructions operable to rate a writing written in any language, comprising the steps of: providing a style score based on how a language style of the writing is different from at least one training document; determining whether the style score is greater than a predetermined threshold, and when the style score is greater than the predetermined threshold, rejecting the writing; providing a punctuation score based on a comparison between the use of punctuation marks in the writing and the use of punctuation marks in the at least one training document; providing a spelling score based on spelling accuracy of the writing; providing a quotation score based on a comparison between sentences from the writing and the sentences from the at least one training document, wherein the providing the quotation score comprises dividing the writing into extracted sentences, comparing each of the extracted sentences to the at least one training document, and calculating a percentage of extracted sentences that match the at least one training document; providing an enrichment score based on new and accurate vocabularies used in the writing, wherein the providing the enrichment score comprises extracting basis words from the writing to obtain a total number of unique words in the writing and dividing the total number of unique words by a total number of words in the writing; providing a syntax analysis score based on grammar mistakes in the writing; providing a focus score based on a topic of the essay and a focus of the writing on that topic; providing an idea and cohesion scores based on whether the writing provides a close or far away cohesive correct answer; and providing the rating of the writing based on the style score, the punctuation score, the spelling score, the quotation score, the enrichment score, the syntax analysis score, the focus score, the idea score and the cohesion score, wherein the rating of the writing is an overall rating or detailed score for the writing that is generated from the style score, the punctuation score, the spelling score, the quotation score, the enrichment score, the syntax analysis score, the focus score, the idea score and the cohesion score. 13. The method of claim 9 , wherein providing the quotation score includes a training phase and a testing phase, and the training phase is performed offline on the at least one training document in order to index the at least one training document. | 0.535581 |
8,554,564 | 1 | 4 | 1. A speech end-pointer system, comprising: a computer processor; a voice triggering module configured to identify a portion of an audio stream comprising a speech segment; and a rule module in communication with the voice triggering module, the rule module comprising a plurality of rules used by the computer processor to analyze the audio stream and detect a beginning and an end of the speech segment, where the plurality of rules comprises one or more rules based on an energy counter; where the beginning of the speech segment and the end of the speech segment represent boundaries between speech and non-speech portions of the audio stream; and where the computer processor is configured to determine whether a frame of the audio stream has energy above a background noise level and increment the energy counter by a length of the frame in response to a determination that the frame has energy above the background noise level. | 1. A speech end-pointer system, comprising: a computer processor; a voice triggering module configured to identify a portion of an audio stream comprising a speech segment; and a rule module in communication with the voice triggering module, the rule module comprising a plurality of rules used by the computer processor to analyze the audio stream and detect a beginning and an end of the speech segment, where the plurality of rules comprises one or more rules based on an energy counter; where the beginning of the speech segment and the end of the speech segment represent boundaries between speech and non-speech portions of the audio stream; and where the computer processor is configured to determine whether a frame of the audio stream has energy above a background noise level and increment the energy counter by a length of the frame in response to a determination that the frame has energy above the background noise level. 4. The system of claim 1 , where the plurality of rules includes a rule configured to set the beginning of the speech segment or the end of the speech segment based on a comparison between an isolated energy event counter and a threshold. | 0.80363 |
9,754,020 | 1 | 8 | 1. A device for determining a measure of relevancy for a seed word-keyword pair (d,k) comprising: a word identifier for identifying each unique word in the set of documents as a search word; a word pair identifier in communication with said word identifier and for combining the identified search words to define search word pairs; a unit portioner for portioning the set of documents into user-definable units, said unit portioner in communication with said interface and with said word pair identifier; a co-occurrence matrix generator in communication with said unit portioner and said word pair identifier for determining, for each defined search word pair, the number of units in which the identified search word pair occurs and for storing the number of occurrences in a co-occurrence matrix a probability matrix generator in communication with said co-occurrence matrix generator and for generating a probability matrix as a function of the co-occurrence matrix, a calibrating column vector generator, ψ, in communication with said co-occurrence matrix generator for generating a calibrating column vector; a matrix normalizer in communication with said probability matrix generator for normalizing the probability matrix to form a transition matrix, R; a word pair selector in communication with said word pair identifier for selecting the seed word-keyword pair to be measured, wherein said word pair selector provides a first column vector, {right arrow over (Γ)}(d), relating to the seed word and a second column vector, {right arrow over (Γ)}(k), relating to the keyword; an expected search distance generator in communication with said word pair selector, said probability matrix generator and said matrix normalizer, for calculating the expected search distance of the seed word-keyword pair; a weighted average expected search distance generator in communication with said expected search distance generator, said probability matrix generator, said matrix normalizer, and said calibrating column vector, said weighted average expected search distance generator for determining a weighted average expected search distance for the keyword; and a calibrator in communication with said expected search distance generator and said weighted average expected search distance generator, wherein said calibrator determines the relevancy, s d,k , of the seed word to the key word, based upon said expected search distance and said weighted averaged expected search distance. | 1. A device for determining a measure of relevancy for a seed word-keyword pair (d,k) comprising: a word identifier for identifying each unique word in the set of documents as a search word; a word pair identifier in communication with said word identifier and for combining the identified search words to define search word pairs; a unit portioner for portioning the set of documents into user-definable units, said unit portioner in communication with said interface and with said word pair identifier; a co-occurrence matrix generator in communication with said unit portioner and said word pair identifier for determining, for each defined search word pair, the number of units in which the identified search word pair occurs and for storing the number of occurrences in a co-occurrence matrix a probability matrix generator in communication with said co-occurrence matrix generator and for generating a probability matrix as a function of the co-occurrence matrix, a calibrating column vector generator, ψ, in communication with said co-occurrence matrix generator for generating a calibrating column vector; a matrix normalizer in communication with said probability matrix generator for normalizing the probability matrix to form a transition matrix, R; a word pair selector in communication with said word pair identifier for selecting the seed word-keyword pair to be measured, wherein said word pair selector provides a first column vector, {right arrow over (Γ)}(d), relating to the seed word and a second column vector, {right arrow over (Γ)}(k), relating to the keyword; an expected search distance generator in communication with said word pair selector, said probability matrix generator and said matrix normalizer, for calculating the expected search distance of the seed word-keyword pair; a weighted average expected search distance generator in communication with said expected search distance generator, said probability matrix generator, said matrix normalizer, and said calibrating column vector, said weighted average expected search distance generator for determining a weighted average expected search distance for the keyword; and a calibrator in communication with said expected search distance generator and said weighted average expected search distance generator, wherein said calibrator determines the relevancy, s d,k , of the seed word to the key word, based upon said expected search distance and said weighted averaged expected search distance. 8. The device of claim 1 , wherein said weighted average expected search distance is provided by: c _ k = ∑ n = 1 g n [ ψ → ] T · [ ( I - Γ → ( k ) ⊗ Γ → ( k ) ) · R · ( I - Γ → ( k ) ⊗ Γ → ( k ) ) ] n - 1 · M · Γ → ( k ) wherein, I represents an identity matrix; {right arrow over (Γ)}(k) represents a column vector for selecting values in the transition matrix related to the word, k; {right arrow over (Ψ)} is a column vector representing the commonality of words in the co-occurrence matrix R represents the transition matrix; M represents the probability matrix; and g represents the upper limit of the summation as selected by the user. | 0.507508 |
9,600,842 | 29 | 71 | 29. A computer program product embodied on at least one non-transitory computer readable medium and configured to cause at least one hardware processor to operate, the computer program product comprising: code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to identify at least one computer-readable Extensible Markup Language (XML)-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and includes: a plurality of line items with a plurality of data values, and a plurality of computer-readable semantic tags that describe a semantic meaning of the data values, where the at least one computer-readable XML-compliant data document is capable of including multiple hierarchical relationships between two of the plurality of line items; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to parse the at least one computer-readable XML-compliant data document, by: receiving the at least one computer-readable XML-compliant data document, identifying the multiple hierarchical relationships between the two line items, and at least one of the computer-readable semantic tags that describes the semantic meaning of at least one of the data values included in the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to access a plurality of computer-readable rules including: a computer-readable datatype rule for validation of a type of data values, a computer-readable calculation rule for validation of a calculation involving data values, and a computer-readable unit rule for validation of a unit of data values; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to process the at least one computer-readable XML-compliant data document, by: identifying at least a subset of the computer-readable rules including at least one of: the computer-readable datatype rule for validation of the type of data values, the computer-readable calculation rule for validation of the calculation involving data values, or the computer-readable unit rule for validation of the unit of data values; and processing at least a portion of the data values of at least a portion of the plurality of line items of the at least one computer-readable XML-compliant data document, utilizing the at least subset of the computer-readable rules, and at least a portion of the computer-readable semantic tags of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to display a result of a validation of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to develop a report, by: identifying the at least one computer-readable semantic tag that describes the semantic meaning of the at least one data value included in the at least one computer-readable XML-compliant data document, and retrieving data from one or more sources to represent the at least one data value in the report. | 29. A computer program product embodied on at least one non-transitory computer readable medium and configured to cause at least one hardware processor to operate, the computer program product comprising: code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to identify at least one computer-readable Extensible Markup Language (XML)-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and includes: a plurality of line items with a plurality of data values, and a plurality of computer-readable semantic tags that describe a semantic meaning of the data values, where the at least one computer-readable XML-compliant data document is capable of including multiple hierarchical relationships between two of the plurality of line items; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to parse the at least one computer-readable XML-compliant data document, by: receiving the at least one computer-readable XML-compliant data document, identifying the multiple hierarchical relationships between the two line items, and at least one of the computer-readable semantic tags that describes the semantic meaning of at least one of the data values included in the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to access a plurality of computer-readable rules including: a computer-readable datatype rule for validation of a type of data values, a computer-readable calculation rule for validation of a calculation involving data values, and a computer-readable unit rule for validation of a unit of data values; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to process the at least one computer-readable XML-compliant data document, by: identifying at least a subset of the computer-readable rules including at least one of: the computer-readable datatype rule for validation of the type of data values, the computer-readable calculation rule for validation of the calculation involving data values, or the computer-readable unit rule for validation of the unit of data values; and processing at least a portion of the data values of at least a portion of the plurality of line items of the at least one computer-readable XML-compliant data document, utilizing the at least subset of the computer-readable rules, and at least a portion of the computer-readable semantic tags of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to display a result of a validation of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to develop a report, by: identifying the at least one computer-readable semantic tag that describes the semantic meaning of the at least one data value included in the at least one computer-readable XML-compliant data document, and retrieving data from one or more sources to represent the at least one data value in the report. 71. The computer program product of claim 29 , wherein the computer program product is operable such that the at least subset of the computer-readable rules includes the computer-readable datatype rule for validation of the type of data values, the computer-readable calculation rule for validation of the calculation involving data values, and the computer-readable unit rule for validation of the unit of data values. | 0.881168 |
7,689,529 | 4 | 6 | 4. A system for managing an application portfolio, comprising: means for providing a first fuzzy logic algorithm, a second frizzy logic algorithm, a third fuzzy logic algorithm and a fourth logic algorithm, each of the first fuzzy logic algorithm, the second fuzzy logic algorithm, the third fuzzy logic algorithm and the fourth frizzy logic algorithm being derived from an adaptive and learning expert knowledge base; means for collecting data for a plurality of decision drivers for each application in the application portfolio; means for processing questions relating to the decision drivers to output attributes based on a predetermined mapping; means for applying first fuzzy logic algorithm on the output attributes and performing scoring and filtering and categorizing the output attributes; and means for outputting application options based on performing at least one of scoring, filtering and categorizing; means for applying the second fuzzy logic algorithm to the output application options; and means for outputting application dispositions; means for applying the third fuzzy logic algorithm to said output application dispositions to group the output application options; and means for outputting a list of initiatives; means for applying the fourth fuzzy logic algorithm to perform costing, optimizing and scheduling on the list of initiatives; and means for outputting an implementation plan and a business case. | 4. A system for managing an application portfolio, comprising: means for providing a first fuzzy logic algorithm, a second frizzy logic algorithm, a third fuzzy logic algorithm and a fourth logic algorithm, each of the first fuzzy logic algorithm, the second fuzzy logic algorithm, the third fuzzy logic algorithm and the fourth frizzy logic algorithm being derived from an adaptive and learning expert knowledge base; means for collecting data for a plurality of decision drivers for each application in the application portfolio; means for processing questions relating to the decision drivers to output attributes based on a predetermined mapping; means for applying first fuzzy logic algorithm on the output attributes and performing scoring and filtering and categorizing the output attributes; and means for outputting application options based on performing at least one of scoring, filtering and categorizing; means for applying the second fuzzy logic algorithm to the output application options; and means for outputting application dispositions; means for applying the third fuzzy logic algorithm to said output application dispositions to group the output application options; and means for outputting a list of initiatives; means for applying the fourth fuzzy logic algorithm to perform costing, optimizing and scheduling on the list of initiatives; and means for outputting an implementation plan and a business case. 6. The method of claim 4 , further comprising means for updating at least one expert knowledge base upon validation of the implementation plan and business case. | 0.886938 |
8,930,971 | 1 | 3 | 1. A computer-system-implemented method for providing content, the method comprising: using the computer system, loading a document associated with a first domain, wherein the document includes an embedded document associated with a daughter domain, and wherein the embedded document includes an embedded advertisement associated with a granddaughter domain; receiving information in the granddaughter domain indicating that a viewer of the document activated the embedded advertisement; in response to receiving the information, determining if the document supports a cross-domain communication technique; if the document does not support the cross-domain communication technique, determining if the first domain is different than the granddaughter domain; if the first domain is different than the granddaughter domain, invoking, in the granddaughter domain, a series of windows corresponding to different candidate origins of the first domain; communicating access commands associated with the windows from the granddaughter domain to the document associated with the first domain, wherein a given access command includes one of the candidate origins, a content identifier for content associated with the embedded advertisement and a source location of the content; and processing one of the access commands having a candidate origin that is the same as that of the first domain using a cross-domain communication module executing in an environment of the first domain, wherein the processing involves linking to the content at the source location, which is displayed in one of the windows associated with the one of the access commands. | 1. A computer-system-implemented method for providing content, the method comprising: using the computer system, loading a document associated with a first domain, wherein the document includes an embedded document associated with a daughter domain, and wherein the embedded document includes an embedded advertisement associated with a granddaughter domain; receiving information in the granddaughter domain indicating that a viewer of the document activated the embedded advertisement; in response to receiving the information, determining if the document supports a cross-domain communication technique; if the document does not support the cross-domain communication technique, determining if the first domain is different than the granddaughter domain; if the first domain is different than the granddaughter domain, invoking, in the granddaughter domain, a series of windows corresponding to different candidate origins of the first domain; communicating access commands associated with the windows from the granddaughter domain to the document associated with the first domain, wherein a given access command includes one of the candidate origins, a content identifier for content associated with the embedded advertisement and a source location of the content; and processing one of the access commands having a candidate origin that is the same as that of the first domain using a cross-domain communication module executing in an environment of the first domain, wherein the processing involves linking to the content at the source location, which is displayed in one of the windows associated with the one of the access commands. 3. The method of claim 1 , wherein the cross-domain communication technique includes postMessage. | 0.776498 |
8,074,199 | 7 | 8 | 7. The computer-implemented system of claim 6 , wherein the XML snippet comprises a speech menu defining prompts and transitions in response to a nonresponsive user utterance. | 7. The computer-implemented system of claim 6 , wherein the XML snippet comprises a speech menu defining prompts and transitions in response to a nonresponsive user utterance. 8. The computer-implemented system of claim 7 , wherein the nonresponsive user utterance is one or more responses selected from a group consisting of a silence, a mumble, and a word not applicable in current context. | 0.5 |
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