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8,046,683 | 7 | 12 | 7. The method according to claim 1 , wherein using the schema and the portions of the markup language fragment respectively corresponding to the child nodes for data entry with the data entry fields further comprises displaying an electronic form on a user interface (UI) for interactive data entry with the electronic form. | 7. The method according to claim 1 , wherein using the schema and the portions of the markup language fragment respectively corresponding to the child nodes for data entry with the data entry fields further comprises displaying an electronic form on a user interface (UI) for interactive data entry with the electronic form. 12. The method as defined in claim 7 , wherein forming the markup language fragment further comprises creating the electronic form and associating the markup language fragment with the electronic form. | 0.849325 |
8,214,421 | 1 | 9 | 1. A computer-implemented method comprising: receiving, with a processor executing a sequence verifier, a plurality of messages exchanged between two or more participants, the sequence verifier being a single module that is distinct from the two or more participants, the plurality of messages comprising a first message sent from a first participant of the two or more participants to a second participant of the two or more participants and a second message sent from the second participant of the two or more participants to the first participant of the two or more participants, forming a sequence; and testing conformance of each of the plurality of messages, with the processor executing the sequence verifier, to a specific markup language standard without using a reference implementation of the markup language standard; wherein testing conformance compares the first message in the sequence of messages exchanged between the first participant and the second participant to a valid sequence in a protocol verification graph to test conformance of the first message, and compares the second message in the sequence of messages exchanged between the first participant and the second participant to a valid sequence in the protocol verification graph to test conformance of the second message, the testing conformance verifying that the first message and second message conform to an appropriate message type based on a standard schema and were exchanged in a correct order based on the protocol verification graph; wherein the protocol verification graph describes constraints on a message including message sequence constraints and message type constraints, the protocol verification graph being created by analyzing an Extensible Markup Language (XML) standards specification. | 1. A computer-implemented method comprising: receiving, with a processor executing a sequence verifier, a plurality of messages exchanged between two or more participants, the sequence verifier being a single module that is distinct from the two or more participants, the plurality of messages comprising a first message sent from a first participant of the two or more participants to a second participant of the two or more participants and a second message sent from the second participant of the two or more participants to the first participant of the two or more participants, forming a sequence; and testing conformance of each of the plurality of messages, with the processor executing the sequence verifier, to a specific markup language standard without using a reference implementation of the markup language standard; wherein testing conformance compares the first message in the sequence of messages exchanged between the first participant and the second participant to a valid sequence in a protocol verification graph to test conformance of the first message, and compares the second message in the sequence of messages exchanged between the first participant and the second participant to a valid sequence in the protocol verification graph to test conformance of the second message, the testing conformance verifying that the first message and second message conform to an appropriate message type based on a standard schema and were exchanged in a correct order based on the protocol verification graph; wherein the protocol verification graph describes constraints on a message including message sequence constraints and message type constraints, the protocol verification graph being created by analyzing an Extensible Markup Language (XML) standards specification. 9. The method of claim 1 , wherein said testing conformance is performed by an active intermediary of messages exchanged between the two or more participants, and is performed during runtime. | 0.776869 |
9,542,374 | 1 | 6 | 1. A computer-implemented method for electronically signing an electronically stored document that includes document content, comprising the steps of: providing at least a first user and a second user remote access to the electronically stored document; applying, by one or more processors, a first electronic signature to the electronically stored document to produce an initial signed version of the electronically stored document, wherein the first electronic signature includes information that associates the first electronic signature with the initial signed version of the electronically stored document, the first electronic signature verifies integrity of the document content of the initial signed version of the electronically stored document, and the first electronic signature includes a first cryptographic component; subsequent to applying the first electronic signature to the electronically stored document, modifying, by the one or more processors, the document content of the initial signed version of the electronically stored document thereby producing a first revision of the electronically stored document; subsequent to modifying the initial signed version of the electronically stored document, applying, by the one or more processors, a second electronic signature to the first revision of the electronically stored document, wherein the second electronic signature includes information that associates the second electronic signature with the first revision of the electronically stored document, the second electronic signature verifies integrity of the document content the first revision of the electronically stored document, and the second electronic signature includes a second cryptographic component; and generating a revision history of the electronically stored document, wherein the revision history associates the first electronic signature with the initial signed version of the electronically stored document and associates at least the second electronic signature with the first revision of the first electronically stored document. | 1. A computer-implemented method for electronically signing an electronically stored document that includes document content, comprising the steps of: providing at least a first user and a second user remote access to the electronically stored document; applying, by one or more processors, a first electronic signature to the electronically stored document to produce an initial signed version of the electronically stored document, wherein the first electronic signature includes information that associates the first electronic signature with the initial signed version of the electronically stored document, the first electronic signature verifies integrity of the document content of the initial signed version of the electronically stored document, and the first electronic signature includes a first cryptographic component; subsequent to applying the first electronic signature to the electronically stored document, modifying, by the one or more processors, the document content of the initial signed version of the electronically stored document thereby producing a first revision of the electronically stored document; subsequent to modifying the initial signed version of the electronically stored document, applying, by the one or more processors, a second electronic signature to the first revision of the electronically stored document, wherein the second electronic signature includes information that associates the second electronic signature with the first revision of the electronically stored document, the second electronic signature verifies integrity of the document content the first revision of the electronically stored document, and the second electronic signature includes a second cryptographic component; and generating a revision history of the electronically stored document, wherein the revision history associates the first electronic signature with the initial signed version of the electronically stored document and associates at least the second electronic signature with the first revision of the first electronically stored document. 6. The method of claim 1 , wherein the first electronic signature and the second electronic signature are both associated with the same user. | 0.70625 |
9,152,700 | 8 | 9 | 8. The system of claim 7 , the operations comprising determining the degree of similarity between the different query of the identified image relevance model and the received search query based a similarity metric applicable to queries. | 8. The system of claim 7 , the operations comprising determining the degree of similarity between the different query of the identified image relevance model and the received search query based a similarity metric applicable to queries. 9. The system of claim 8 , wherein the similarity metric comprises a measure of similarity of query terms in the received search query and query terms of the different query that has been identified as similar to the received search query. | 0.5 |
8,332,206 | 1 | 3 | 1. A computer-implemented method for providing a definition or a translation, comprising: receiving an input indicating a word selected by a user; determining a user's language; communicating the determined user's language to a definition server and a translation server; sending, simultaneously, a definition request for the word to the definition server along with sending a translation request for the word to the translation server; receiving a response to the definition request from the definition server, wherein the response to the definition request indicates whether there is at least one definition of the word in the user's language; receiving a response to the translation request from the translation server, wherein the response to the translation request indicates whether there is at least one translation of the word in the user's language, wherein the response to the definition request and the response to the translation request are received simultaneously; determining whether to provide the user with a definition or a translation of the word based on the responses from the definition server and the translation server, wherein the determination comprises: determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language; and determining to provide the user with the translation of the word when the response to the definition request indicates that there is no definition of the word in the user's language and the response to the translation request includes at least one translation of the word in the user's language; and providing the user with the definition or the translation of the word based on the determination of whether to provide the user with a definition or a translation of the word, wherein the providing comprises a bubble showing the at least one definition or the at least one translation of the selected word. | 1. A computer-implemented method for providing a definition or a translation, comprising: receiving an input indicating a word selected by a user; determining a user's language; communicating the determined user's language to a definition server and a translation server; sending, simultaneously, a definition request for the word to the definition server along with sending a translation request for the word to the translation server; receiving a response to the definition request from the definition server, wherein the response to the definition request indicates whether there is at least one definition of the word in the user's language; receiving a response to the translation request from the translation server, wherein the response to the translation request indicates whether there is at least one translation of the word in the user's language, wherein the response to the definition request and the response to the translation request are received simultaneously; determining whether to provide the user with a definition or a translation of the word based on the responses from the definition server and the translation server, wherein the determination comprises: determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language; and determining to provide the user with the translation of the word when the response to the definition request indicates that there is no definition of the word in the user's language and the response to the translation request includes at least one translation of the word in the user's language; and providing the user with the definition or the translation of the word based on the determination of whether to provide the user with a definition or a translation of the word, wherein the providing comprises a bubble showing the at least one definition or the at least one translation of the selected word. 3. The method of claim 1 , wherein determining whether to provide the user with a definition or a translation of the word comprises determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language, and the response to the translation request indicates a detected source language of the word matching the user's language. | 0.681684 |
9,654,347 | 1 | 3 | 1. A configuring method for managing appliances in a system on the basis of management rules defining at least one action to be executed by said system when at least one condition is fulfilled, said system comprising a rules engine intended to implement said management rules, the method comprising a configuring device: supplying semantic expressions of states and functions to a user interface; enabling a user, via the user interface, to define at least one management rule from at least one condition, on the basis of the semantic expressions of states, and at least one action, on the basis of the semantic expressions of functions; transcribing each management rule, defined semantically via the user interface, into instructions interpretable by the rules engine; wherein the configuring device: obtains a description of states in which each appliance in the system is able to be; obtains a description of functions that each appliance in the system is able to execute; and transcribes said descriptions of states and functions into respective semantic expressions for supplying said semantic expressions of states and functions to the user interface so that the user can understand. | 1. A configuring method for managing appliances in a system on the basis of management rules defining at least one action to be executed by said system when at least one condition is fulfilled, said system comprising a rules engine intended to implement said management rules, the method comprising a configuring device: supplying semantic expressions of states and functions to a user interface; enabling a user, via the user interface, to define at least one management rule from at least one condition, on the basis of the semantic expressions of states, and at least one action, on the basis of the semantic expressions of functions; transcribing each management rule, defined semantically via the user interface, into instructions interpretable by the rules engine; wherein the configuring device: obtains a description of states in which each appliance in the system is able to be; obtains a description of functions that each appliance in the system is able to execute; and transcribes said descriptions of states and functions into respective semantic expressions for supplying said semantic expressions of states and functions to the user interface so that the user can understand. 3. The configuring method according to claim 1 , comprising using the configuring device to transcribe said descriptions of the states and functions into semantic expressions in a predetermined language from a choice of several languages available via the user interface. | 0.755856 |
9,940,387 | 8 | 10 | 8. A method in a computer system for generating a legal search query, the method comprising: receiving the legal search query from a single text input field, the legal search query comprising a first query segment and a second query segment, wherein: the first query segment is distinct and independent from the second query segment in the single text input field, and the first query segment and the second query segment are distinct phrases of the legal search query resulting from individual auto-complete sessions; detecting a position of a text cursor within the first query segment or the second query segment; displaying one or more additional first query suggestions based at least in part on the position of the text cursor within the first query segment, and displaying one or more additional second query suggestions based at least in part on the position of the text cursor within the second query segment; receiving an operator in the single text input field, wherein the operator is added to the first query segment or the second query segment; splitting the first query segment or the second query segment into two or more split query segments based on a location of the operator within the single text input field, wherein the splitting results in an additional autocomplete session for each of the two or more split query segments; obtaining one or more query suggestions from a server computing device, the one or more query suggestions based at least in part on the first query segment, the second query segment, or the two or more split query segments; obtaining one or more first semantic suggestions based at least in part on the first query segment from a semantic suggestion server that is separate from the server computing device, wherein the one or more first semantic suggestions are semantically similar to the first query segment; obtaining one or more second semantic suggestions based at least in part on the second query segment from the semantic suggestion server, wherein the one or more second semantic suggestions are semantically similar to the second query segment and distinct from the one or more first semantic suggestions; obtaining one or more third semantic suggestions based at least in part on the two or more split query segments from the semantic suggestion server, wherein the one or more third semantic suggestions are semantically similar to the two or more split query segments and distinct from the one or more first semantic suggestions and the one or more second semantic suggestions; displaying the one or more query suggestions with the one or more first semantic suggestions, the one or more second semantic suggestions, and the one or more third semantic suggestions within a graphical user interface; generating the legal search query from one or more selections from a user via the graphical user interface; and searching a legal document database using the legal search query to return and display a set of retrieved legal documents. | 8. A method in a computer system for generating a legal search query, the method comprising: receiving the legal search query from a single text input field, the legal search query comprising a first query segment and a second query segment, wherein: the first query segment is distinct and independent from the second query segment in the single text input field, and the first query segment and the second query segment are distinct phrases of the legal search query resulting from individual auto-complete sessions; detecting a position of a text cursor within the first query segment or the second query segment; displaying one or more additional first query suggestions based at least in part on the position of the text cursor within the first query segment, and displaying one or more additional second query suggestions based at least in part on the position of the text cursor within the second query segment; receiving an operator in the single text input field, wherein the operator is added to the first query segment or the second query segment; splitting the first query segment or the second query segment into two or more split query segments based on a location of the operator within the single text input field, wherein the splitting results in an additional autocomplete session for each of the two or more split query segments; obtaining one or more query suggestions from a server computing device, the one or more query suggestions based at least in part on the first query segment, the second query segment, or the two or more split query segments; obtaining one or more first semantic suggestions based at least in part on the first query segment from a semantic suggestion server that is separate from the server computing device, wherein the one or more first semantic suggestions are semantically similar to the first query segment; obtaining one or more second semantic suggestions based at least in part on the second query segment from the semantic suggestion server, wherein the one or more second semantic suggestions are semantically similar to the second query segment and distinct from the one or more first semantic suggestions; obtaining one or more third semantic suggestions based at least in part on the two or more split query segments from the semantic suggestion server, wherein the one or more third semantic suggestions are semantically similar to the two or more split query segments and distinct from the one or more first semantic suggestions and the one or more second semantic suggestions; displaying the one or more query suggestions with the one or more first semantic suggestions, the one or more second semantic suggestions, and the one or more third semantic suggestions within a graphical user interface; generating the legal search query from one or more selections from a user via the graphical user interface; and searching a legal document database using the legal search query to return and display a set of retrieved legal documents. 10. The method of claim 8 , wherein: the legal search query comprises an additional query segment that is distinct from the first query segment and the second query segment; and the method further comprises: obtaining one or more additional semantic suggestions based at least in part on the additional query segment from the semantic suggestion server, wherein the one or more additional semantic suggestions are semantically similar to the additional query segment; and displaying the one or more additional semantic suggestions within the graphical user interface. | 0.5 |
5,551,039 | 2 | 3 | 2. The method of claim 1 in which during execution of said assembly language code in the data parallel computer elements of the arrays are evenly distributed to the processing elements, wherein step (1) comprises the steps of: (a) selecting one of the code blocks; (b) generating subgrid loop creation instructions to create a subgrid loop, wherein said subgrid loop creation instructions when executed in said processing element enable said processing element to process, over a predetermined number of iterations of said subgrid loop, the elements of the arrays distributed to said processing element, wherein X represents a value of an iteration counter; and (c) providing said subgrid loop creation instruction in said assembly language code. | 2. The method of claim 1 in which during execution of said assembly language code in the data parallel computer elements of the arrays are evenly distributed to the processing elements, wherein step (1) comprises the steps of: (a) selecting one of the code blocks; (b) generating subgrid loop creation instructions to create a subgrid loop, wherein said subgrid loop creation instructions when executed in said processing element enable said processing element to process, over a predetermined number of iterations of said subgrid loop, the elements of the arrays distributed to said processing element, wherein X represents a value of an iteration counter; and (c) providing said subgrid loop creation instruction in said assembly language code. 3. The method of claim 2 in which said selected code block comprises an elemental vector instruction designating a particular operation to perform using elements of at least one of the arrays, wherein step (1) further comprises the steps of: (d) generating a low-level vector instruction representing said elemental vector instruction, wherein said low-level vector instruction when executed in said processing element enables said processing element to perform said particular operation using a subset of the elements of said at least one of the arrays distributed to said processing element; and (e) providing said low-level vector instruction in said assembly language code such that said low-level vector instruction is executed by said processing element during each iteration of said subgrid loop. | 0.573326 |
8,515,828 | 3 | 4 | 3. The method of claim 2 , wherein the semantic analysis is conducted using a supervised or unsupervised machine learning algorithm. | 3. The method of claim 2 , wherein the semantic analysis is conducted using a supervised or unsupervised machine learning algorithm. 4. The method of claim 3 , wherein the semantic analysis further identifies product characteristic categories for use in mapping the negative sentiment key words to a product characteristic in the classification rubric. | 0.5 |
8,533,199 | 1 | 3 | 1. A computer-implemented method for creating an intelligent bookmark to a document, comprising: displaying the document comprising at least an address, a title, and a body; receiving a user selection of content from a portion of the body of the document and user supplemented information; generating the intelligent bookmark by retrieving the address of the document, and by automatically extracting identifier information from the body of the document within the user selection; and storing the address in association with the identifier information and the user supplemented information. | 1. A computer-implemented method for creating an intelligent bookmark to a document, comprising: displaying the document comprising at least an address, a title, and a body; receiving a user selection of content from a portion of the body of the document and user supplemented information; generating the intelligent bookmark by retrieving the address of the document, and by automatically extracting identifier information from the body of the document within the user selection; and storing the address in association with the identifier information and the user supplemented information. 3. The method of claim 1 , further comprising: automatically uploading the intelligent bookmark to a server for remote access. | 0.778169 |
8,041,918 | 6 | 7 | 6. The method of claim 5 , wherein the first reference bitmap belongs to a first private mark cache associated with a first thread. | 6. The method of claim 5 , wherein the first reference bitmap belongs to a first private mark cache associated with a first thread. 7. The method of claim 6 , wherein the second reference bitmap belongs to a second private mark cache associated with a second thread. | 0.5 |
9,251,143 | 22 | 23 | 22. A method of deploying a system for translating documents to natural language form, comprising: providing a computer infrastructure configured to: obtain, from an input document, document data wherein the document data is in a non-natural language form; determine, via communication with a detection and conversion database comprising records defining a plurality of data types, a data type of the document data; translate, based on the determine data type, the document data to a natural language form; and output, in natural language form, the translated document data in natural language form to an output data stream; wherein the plurality of data types comprises: document header data; document field data; table header data; table detail data; and signature data. | 22. A method of deploying a system for translating documents to natural language form, comprising: providing a computer infrastructure configured to: obtain, from an input document, document data wherein the document data is in a non-natural language form; determine, via communication with a detection and conversion database comprising records defining a plurality of data types, a data type of the document data; translate, based on the determine data type, the document data to a natural language form; and output, in natural language form, the translated document data in natural language form to an output data stream; wherein the plurality of data types comprises: document header data; document field data; table header data; table detail data; and signature data. 23. The method of claim 22 , wherein: the document data comprises plural different portions of data; the determining, the translating, and the outputting are respectively performed for each respective one of the plural different portions of data; the plural different portions of data are arranged in an order in the input document; the output translated document data comprises translated portions of data in the same order as the input document. | 0.5 |
9,448,994 | 16 | 17 | 16. The system of claim 13 , wherein the operations further comprise: identifying a term in the identified hyperlink text as an argument associated with the action initiation grammar. | 16. The system of claim 13 , wherein the operations further comprise: identifying a term in the identified hyperlink text as an argument associated with the action initiation grammar. 17. The system of claim 16 , wherein the argument is a value associated with a parameter of the form. | 0.5 |
9,277,287 | 6 | 7 | 6. The system of claim 5 , wherein the operations further comprise receiving a request to receive additional choices of programs after providing the sorted list of programs. | 6. The system of claim 5 , wherein the operations further comprise receiving a request to receive additional choices of programs after providing the sorted list of programs. 7. The system of claim 6 , wherein the operations further comprise providing an additional sorted list of programs in response to receiving the request. | 0.5 |
8,875,306 | 1 | 13 | 1. A method for restricting the customizability of a base metadata document, the base metadata document defining one or more characteristics of at least a portion of a software application, the method comprising: receiving, by a computer system, a type-level customization policy defined for a first object type of an object included in the base metadata document, the type-level customization policy indicating whether instances of objects having the object type may be customized by a first set of one or more users of the software application; receiving an instance-level customization policy defined for the object included in the base metadata document, the instance-level customization policy indicating whether an instance of the object may be customized by a second set of one or more users of the software application; and enforcing, by the computer system, the type-level customization policy and the instance-level customization policy at runtime of the software application to create or update a customization, the customization defining modifications to the base metadata document, the enforcing comprising: determining whether the instance of the object may be customized by a current user, based on how the object is instantiated, the type-level customization policy, the instance-level customization policy, and a set of precedence rules for the type-level customization policy and the instance-level customization policy, wherein how the object is instantiated comprises whether the object is instantiated as the first object type or as a second object type that is based on the first object type, and wherein the set of precedence rules for the type-level customization policy and the instance-level customization policy comprises one or more rules providing for a first case where the type-level customization policy and the instance-level customization policy apply without conflict, and one or more rules providing for a second case where the type-level customization policy and the instance-level customization policy apply with conflicting restrictions; determining whether a restriction of one of the type-level customization policy or the instance-level customization policy takes a higher precedence with respect to a conflicting restriction of the other of the type-level customization policy or the instance-level customization policy; wherein the customization is stored separately from the base metadata document, and wherein the customization is applied to the base metadata document to generate a customized metadata document used by the software application. | 1. A method for restricting the customizability of a base metadata document, the base metadata document defining one or more characteristics of at least a portion of a software application, the method comprising: receiving, by a computer system, a type-level customization policy defined for a first object type of an object included in the base metadata document, the type-level customization policy indicating whether instances of objects having the object type may be customized by a first set of one or more users of the software application; receiving an instance-level customization policy defined for the object included in the base metadata document, the instance-level customization policy indicating whether an instance of the object may be customized by a second set of one or more users of the software application; and enforcing, by the computer system, the type-level customization policy and the instance-level customization policy at runtime of the software application to create or update a customization, the customization defining modifications to the base metadata document, the enforcing comprising: determining whether the instance of the object may be customized by a current user, based on how the object is instantiated, the type-level customization policy, the instance-level customization policy, and a set of precedence rules for the type-level customization policy and the instance-level customization policy, wherein how the object is instantiated comprises whether the object is instantiated as the first object type or as a second object type that is based on the first object type, and wherein the set of precedence rules for the type-level customization policy and the instance-level customization policy comprises one or more rules providing for a first case where the type-level customization policy and the instance-level customization policy apply without conflict, and one or more rules providing for a second case where the type-level customization policy and the instance-level customization policy apply with conflicting restrictions; determining whether a restriction of one of the type-level customization policy or the instance-level customization policy takes a higher precedence with respect to a conflicting restriction of the other of the type-level customization policy or the instance-level customization policy; wherein the customization is stored separately from the base metadata document, and wherein the customization is applied to the base metadata document to generate a customized metadata document used by the software application. 13. The method of claim 1 , wherein the instance-level customization policy is implemented as one or more object annotations to the object. | 0.864786 |
8,510,347 | 15 | 16 | 15. The system of claim 10 , wherein the defining module is further configured for defining one or more intent meta-models corresponding to the at least one requirement, each intent meta-model describing the corresponding at least one requirement. | 15. The system of claim 10 , wherein the defining module is further configured for defining one or more intent meta-models corresponding to the at least one requirement, each intent meta-model describing the corresponding at least one requirement. 16. The system of claim 15 , wherein the defining module is further configured for defining one or more inference meta-models corresponding to each defined intent meta-model, each inference meta-model describing business and technical requirements required for generating at least one software artifact of the one or more software artifacts, the business and technical requirements being determined based on the at least one requirement. | 0.5 |
8,407,666 | 13 | 14 | 13. The system of claim 12 , wherein the backend connector performs one or more of: connecting to a selected backend data source; providing an interface for accessing a description of the selected backend data source; and providing for the identification of notification services configured for pushing notifications over the network to the electronic device. | 13. The system of claim 12 , wherein the backend connector performs one or more of: connecting to a selected backend data source; providing an interface for accessing a description of the selected backend data source; and providing for the identification of notification services configured for pushing notifications over the network to the electronic device. 14. The system of claim 13 , wherein the data source is a Web service or an SQL database and the description of the selected backend data source includes messages, operations and data type descriptions. | 0.5 |
10,008,207 | 1 | 4 | 1. A computer-implemented method comprising: receiving, by a first stage hotword detector of a multi-stage hotword detection system that includes at least (i) the first stage hotword detector that is implemented in hardware and that is associated with a memory, and (ii) a second stage hotword detector that is implemented in software and that is configured to output a signal indicating whether a given utterance likely includes a hotword, audio data that corresponds to an initial portion of an utterance; providing, by the first stage hotword detector that is implemented in hardware and to the second stage hotword detector that is implemented in software, and based on the first stage hotword detector determining that the initial portion of the utterance likely includes the hotword, data indicating an instruction to access the audio data that corresponds to the initial portion of the utterance and that is stored in the memory associated with the first stage hotword detector; receiving, by the first stage hotword detector that is implemented in hardware and from the second stage hotword detector that is implemented in software, audio data that corresponds to a subsequent portion of the utterance; receiving, from the second stage hotword detector that is implemented in software and by the first stage hotword detector that is implemented in hardware and based on the second stage hotword detector determining that the initial portion of the utterance likely includes the hotword, data indicating an instruction to cease providing, to the memory associated with the first stage hotword detector, audio data that corresponds to one or more subsequent portions of the utterance; and in response to receiving, from the second stage hotword detector that is implemented in software and by the first stage hotword detector that is implemented in hardware and based on the second stage hotword detector determining that the initial portion of the utterance likely includes the hotword, the data indicating the instruction to cease providing, to the memory associated with the first stage hotword detector, the audio data that corresponds to the one or more subsequent portions of the utterance, providing, for output by the multi-stage hotword detection system, a signal indicating that the utterance likely includes the hotword. | 1. A computer-implemented method comprising: receiving, by a first stage hotword detector of a multi-stage hotword detection system that includes at least (i) the first stage hotword detector that is implemented in hardware and that is associated with a memory, and (ii) a second stage hotword detector that is implemented in software and that is configured to output a signal indicating whether a given utterance likely includes a hotword, audio data that corresponds to an initial portion of an utterance; providing, by the first stage hotword detector that is implemented in hardware and to the second stage hotword detector that is implemented in software, and based on the first stage hotword detector determining that the initial portion of the utterance likely includes the hotword, data indicating an instruction to access the audio data that corresponds to the initial portion of the utterance and that is stored in the memory associated with the first stage hotword detector; receiving, by the first stage hotword detector that is implemented in hardware and from the second stage hotword detector that is implemented in software, audio data that corresponds to a subsequent portion of the utterance; receiving, from the second stage hotword detector that is implemented in software and by the first stage hotword detector that is implemented in hardware and based on the second stage hotword detector determining that the initial portion of the utterance likely includes the hotword, data indicating an instruction to cease providing, to the memory associated with the first stage hotword detector, audio data that corresponds to one or more subsequent portions of the utterance; and in response to receiving, from the second stage hotword detector that is implemented in software and by the first stage hotword detector that is implemented in hardware and based on the second stage hotword detector determining that the initial portion of the utterance likely includes the hotword, the data indicating the instruction to cease providing, to the memory associated with the first stage hotword detector, the audio data that corresponds to the one or more subsequent portions of the utterance, providing, for output by the multi-stage hotword detection system, a signal indicating that the utterance likely includes the hotword. 4. The method of claim 1 , comprising: receiving data that corresponds a first number of nodes and a second number of hidden layers for a neural network, wherein the second stage hotword detector receives data that corresponds to a third number of nodes and a fourth number of hidden layers for the neural network, the third number being greater than the first number and the fourth number being greater than the second number. | 0.798013 |
8,135,711 | 4 | 6 | 4. The method of claim 1 , further comprising: identifying a pattern of tonal usage on the part of an individual actor with respect to other actors; identifying deviations from the pattern of tonal usage; and associating specific topics, actors, events of importance, or changes in communications patterns associated with the deviation. | 4. The method of claim 1 , further comprising: identifying a pattern of tonal usage on the part of an individual actor with respect to other actors; identifying deviations from the pattern of tonal usage; and associating specific topics, actors, events of importance, or changes in communications patterns associated with the deviation. 6. The method of claim 4 , further comprising: classifying an item as hot or worthy of special examination, based on a tone associated with the item. | 0.5 |
9,798,833 | 6 | 7 | 6. The method according to claim 4 , wherein the rating comprises: assigning a score to each of the plurality of databases associated with the at least one of the plurality of database connections, based on the matching. | 6. The method according to claim 4 , wherein the rating comprises: assigning a score to each of the plurality of databases associated with the at least one of the plurality of database connections, based on the matching. 7. The method according to claim 6 , comprising: ranking at least a portion of the plurality of databases based on the assigned score; and outputting an indication of the ranking of the at least a portion of the plurality of databases. | 0.5 |
9,069,795 | 14 | 20 | 14. A system for building a catalog using visual objects, comprising: a clustering module configured to cluster a plurality of records, each record comprises at least one object image and at least one textual field associated with the object, to yield a plurality of clusters such that the object images in each cluster exhibit between them a visual similarity above a specified value; and an associating module configured to associate each cluster of the plurality of clusters with at least one representative image selected from the respective object images a labeling module adapted to associate each cluster of the plurality of clusters with a label, the label is generated by applying a dictionary function to the textual fields of each cluster, wherein the label reflects a common semantic factor of the textual fields of each cluster, wherein the common semantic factor has a value above a specified threshold, a category dictionary module adapted to select a category dictionary for each cluster of the plurality of clusters based on the textual fields of each cluster of the plurality of clusters; wherein the labeling module is adapted to edit each label by omitting or adding words based on a respective selected category dictionary; a user terminal module adapted to display a catalog presenting each of least some of the plurality clusters by the respective representative image and the respective label; wherein each label is a name for a cluster of records, wherein each record is comprised of fields such as text, numeric fields, logical fields, hyperlinks and visual objects, wherein an address of a file or content on a computer network, wherein at one of the modules is executed by at least one processor; wherein the visual similarity provides a measure of resemblances between two visual objects based on local descriptors in the visual objects. | 14. A system for building a catalog using visual objects, comprising: a clustering module configured to cluster a plurality of records, each record comprises at least one object image and at least one textual field associated with the object, to yield a plurality of clusters such that the object images in each cluster exhibit between them a visual similarity above a specified value; and an associating module configured to associate each cluster of the plurality of clusters with at least one representative image selected from the respective object images a labeling module adapted to associate each cluster of the plurality of clusters with a label, the label is generated by applying a dictionary function to the textual fields of each cluster, wherein the label reflects a common semantic factor of the textual fields of each cluster, wherein the common semantic factor has a value above a specified threshold, a category dictionary module adapted to select a category dictionary for each cluster of the plurality of clusters based on the textual fields of each cluster of the plurality of clusters; wherein the labeling module is adapted to edit each label by omitting or adding words based on a respective selected category dictionary; a user terminal module adapted to display a catalog presenting each of least some of the plurality clusters by the respective representative image and the respective label; wherein each label is a name for a cluster of records, wherein each record is comprised of fields such as text, numeric fields, logical fields, hyperlinks and visual objects, wherein an address of a file or content on a computer network, wherein at one of the modules is executed by at least one processor; wherein the visual similarity provides a measure of resemblances between two visual objects based on local descriptors in the visual objects. 20. The system according to claim 14 , further comprising a copyright filtering module configured to filter out copyrighted records, wherein a copyrighted object image of a copyrighted record exhibits a visual similarity above a specified level with an object image ranked above a specified level of relevance retrieved by an image search engine applied to at least one textual field associated with the object image. | 0.5 |
9,063,535 | 1 | 2 | 1. A method for controlling a robot comprising the steps of: storing a numerical control language program in a mass storage device connected to a central processing unit, the numerical control language program adapted to be executed by a computer numerical control machine tool to perform a manufacturing process; operating the central processing unit to convert the numerical control language program into a robot language program based upon a pre-defined conversion configuration table having discrete configuration instructions for converting each numerical control language positional command to a robot language positional command and converting each numerical control language miscellaneous code command to a robot language sub-program; storing the robot language positional commands and the robot language sub-programs as the robot language program in the mass storage device; and executing the robot language program with a robot controller connected to the mass storage device and the robot at a run-time of the robot to perform the manufacturing process. | 1. A method for controlling a robot comprising the steps of: storing a numerical control language program in a mass storage device connected to a central processing unit, the numerical control language program adapted to be executed by a computer numerical control machine tool to perform a manufacturing process; operating the central processing unit to convert the numerical control language program into a robot language program based upon a pre-defined conversion configuration table having discrete configuration instructions for converting each numerical control language positional command to a robot language positional command and converting each numerical control language miscellaneous code command to a robot language sub-program; storing the robot language positional commands and the robot language sub-programs as the robot language program in the mass storage device; and executing the robot language program with a robot controller connected to the mass storage device and the robot at a run-time of the robot to perform the manufacturing process. 2. The method according to claim 1 including storing a control program in a control program memory of the robot controller and performing the step of converting utilizing the control program. | 0.76125 |
8,463,715 | 68 | 70 | 68. The method of claim 67 , wherein the term of experience is rounded down to a unit of time. | 68. The method of claim 67 , wherein the term of experience is rounded down to a unit of time. 70. The method of claim 68 , wherein the unit of time is an integer. | 0.744361 |
10,015,124 | 1 | 10 | 1. A computer-executed method to automatically suggest content in a messaging application, the computer-executed method comprising: detecting a first image included within a first message received at a second device over a communication network from a first device of a first user; programmatically analyzing the first image to extract a first image content; retrieving a first semantic concept associated with the first image content; programmatically generating a suggested response to the first message based on the first semantic concept; and transmitting instructions causing rendering of the suggested response in the messaging application as a suggestion to a second user of the second device. | 1. A computer-executed method to automatically suggest content in a messaging application, the computer-executed method comprising: detecting a first image included within a first message received at a second device over a communication network from a first device of a first user; programmatically analyzing the first image to extract a first image content; retrieving a first semantic concept associated with the first image content; programmatically generating a suggested response to the first message based on the first semantic concept; and transmitting instructions causing rendering of the suggested response in the messaging application as a suggestion to a second user of the second device. 10. The computer-executed method of claim 1 , wherein programmatically generating the suggested response further comprises: determining a respective score for one or more of a plurality of suggested responses that include the suggested response; and selecting the suggested response based on the respective scores for the one or more of the plurality of suggested responses. | 0.5 |
9,223,399 | 16 | 20 | 16. A computer program product for translating gestures in a virtual world, comprising: a computer readable medium having computer readable program code embodied therein, the computer readable medium comprising: computer readable program code configured to receive an input gesture to be made by a first avatar directed to a second avatar in the virtual world; computer readable program code configured to display the input gesture on a first display; computer readable program code configured to translate the input gesture based at least in part on one or more environmental, cultural or social factors to generate at least one translated gesture for display; and computer readable program code configured to display the at least one translated gesture on a second display separate from the first display, wherein the at least one translated gesture is different than the input gesture. | 16. A computer program product for translating gestures in a virtual world, comprising: a computer readable medium having computer readable program code embodied therein, the computer readable medium comprising: computer readable program code configured to receive an input gesture to be made by a first avatar directed to a second avatar in the virtual world; computer readable program code configured to display the input gesture on a first display; computer readable program code configured to translate the input gesture based at least in part on one or more environmental, cultural or social factors to generate at least one translated gesture for display; and computer readable program code configured to display the at least one translated gesture on a second display separate from the first display, wherein the at least one translated gesture is different than the input gesture. 20. The computer program product of claim 16 , wherein said computer readable program code configured to translate the input gesture to generate at least one translated gesture for display comprises translating the input gesture based on at least one translation gesture associated with the second avatar. | 0.532209 |
8,184,022 | 6 | 7 | 6. The method according to claim 3 , further comprising determining that the operative language is German. | 6. The method according to claim 3 , further comprising determining that the operative language is German. 7. The method according to claim 6 , further comprising outputting as the determined output a diacritical version of a linguistic element used in German that corresponds with the enabled input. | 0.5 |
8,793,273 | 1 | 10 | 1. A method of efficiently extracting relationship information from an HTML web page or XML document that has tagged elements, including: receiving electronically a relationship template that includes at least one declarative specification and a scope pattern, wherein the declarative specification includes at least a subject and an object that together define a relationship, and declares a pair of pattern matching specifications to identify text associated with pairs of the subject and the object, and wherein the scope pattern defines how closely the subject and the object are found together in a hierarchically structured document that uses tags that contain elements, wherein the scope pattern is expressed in terms of the tags that contain the elements; and applying the pattern matching specifications and the scope pattern in the relationship template to select and output one or more one-to-one pairs of the subject and the object found in a web page or XML document. | 1. A method of efficiently extracting relationship information from an HTML web page or XML document that has tagged elements, including: receiving electronically a relationship template that includes at least one declarative specification and a scope pattern, wherein the declarative specification includes at least a subject and an object that together define a relationship, and declares a pair of pattern matching specifications to identify text associated with pairs of the subject and the object, and wherein the scope pattern defines how closely the subject and the object are found together in a hierarchically structured document that uses tags that contain elements, wherein the scope pattern is expressed in terms of the tags that contain the elements; and applying the pattern matching specifications and the scope pattern in the relationship template to select and output one or more one-to-one pairs of the subject and the object found in a web page or XML document. 10. The method of claim 1 , further including in the declarative specification cardinality specifications for the subject and the object, wherein the cardinality specifications describe whether the subject and the object are expected zero or one time or expected zero to many times. | 0.5 |
9,235,806 | 1 | 27 | 1. A method comprising: obtaining user context information associated with a user, wherein the user context information includes information regarding an attribute of the user, information regarding an activity of the user, and/or information provided by the user; identifying, based on a plurality of concepts in a first knowledge representation (KR), a group of one or more concepts relevant to the user context information; and providing the identified group of one or more concepts to the user, wherein the first KR includes a combination of modules, the modules including a kernel and a customized module, the kernel being accessible via a second KR, the customized module being customized for the user, and wherein the identifying and the providing are performed at least in part by using at least one processor and a data structure representing the first KR. | 1. A method comprising: obtaining user context information associated with a user, wherein the user context information includes information regarding an attribute of the user, information regarding an activity of the user, and/or information provided by the user; identifying, based on a plurality of concepts in a first knowledge representation (KR), a group of one or more concepts relevant to the user context information; and providing the identified group of one or more concepts to the user, wherein the first KR includes a combination of modules, the modules including a kernel and a customized module, the kernel being accessible via a second KR, the customized module being customized for the user, and wherein the identifying and the providing are performed at least in part by using at least one processor and a data structure representing the first KR. 27. The method of claim 1 , wherein: the data structure representing the first KR is a graph; the graph includes a first node, a second node, and an edge between the first and second nodes; the first node corresponds to a first concept of the first KR; the second node corresponds to a second concept of the first KR; and the edge corresponds to a relationship between the first and second concepts and/or represents a relevance of the first concept to the second concept. | 0.674931 |
8,495,042 | 1 | 6 | 1. A non-transitory information extraction computing apparatus including at least one processor with accessible input/output and at least one data store, said at least one processor being programmed for extracting data for review by a human curator from digital representations of documents comprising natural language text, the information extraction computing apparatus, in use, executing computer program instructions that cause the apparatus to provide a plurality of selectable operating modes in which the automatic information extraction apparatus extracts different data for review by a human curator, and, in at least two of the plurality of selectable operating modes, to extract data with different balances between precision and recall, whereby a balance that favours precision over recall will lead to fewer incorrect instances of data being extracted than a balance that favours recall over precision, but will omit more data which should have been extracted. | 1. A non-transitory information extraction computing apparatus including at least one processor with accessible input/output and at least one data store, said at least one processor being programmed for extracting data for review by a human curator from digital representations of documents comprising natural language text, the information extraction computing apparatus, in use, executing computer program instructions that cause the apparatus to provide a plurality of selectable operating modes in which the automatic information extraction apparatus extracts different data for review by a human curator, and, in at least two of the plurality of selectable operating modes, to extract data with different balances between precision and recall, whereby a balance that favours precision over recall will lead to fewer incorrect instances of data being extracted than a balance that favours recall over precision, but will omit more data which should have been extracted. 6. Automatic information extraction apparatus according to claim 1 , wherein the automatic information extraction apparatus is operable to identify individual instances of entities in a digital representation of a document. | 0.80507 |
8,615,664 | 1 | 4 | 1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. | 1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. 4. The system of claim 1 , wherein the one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message comprise: one or more sensors configured to sense at least one systemic physiological characteristic associated with the authoring user. | 0.823922 |
10,079,800 | 5 | 6 | 5. The method of claim 1 , further comprising: searching a cache associated with the equivalence class of the client for an answer corresponding to the DNS query; determining that the cache does not include the answer; based on the determination, querying, by a recursive server, an authoritative server using client subnet data associated with the equivalence class; receiving the answer from the authoritative server; storing the answer to the cache associated with the equivalency class; and serving the answer to the client. | 5. The method of claim 1 , further comprising: searching a cache associated with the equivalence class of the client for an answer corresponding to the DNS query; determining that the cache does not include the answer; based on the determination, querying, by a recursive server, an authoritative server using client subnet data associated with the equivalence class; receiving the answer from the authoritative server; storing the answer to the cache associated with the equivalency class; and serving the answer to the client. 6. The method of claim 5 , wherein the client subnet data includes the least client address in the equivalence class. | 0.5 |
8,510,664 | 12 | 13 | 12. The method of claim 1 , wherein the email-thread chart further comprises one or more nodes, wherein each node represents a single occurrence of an element in the email-thread. | 12. The method of claim 1 , wherein the email-thread chart further comprises one or more nodes, wherein each node represents a single occurrence of an element in the email-thread. 13. The method of claim 12 , wherein the one or more nodes contain a reference to a person within the email-thread. | 0.512712 |
8,423,546 | 7 | 8 | 7. The method as recited in claim 6 , wherein the weighting function considers for each of the textual phrases in said list: the frequency of occurrence of the textual phrase within the document, an inverse document frequency for the textual phrase within a corpus of documents including the document, the language model, and the length of the document. | 7. The method as recited in claim 6 , wherein the weighting function considers for each of the textual phrases in said list: the frequency of occurrence of the textual phrase within the document, an inverse document frequency for the textual phrase within a corpus of documents including the document, the language model, and the length of the document. 8. The method as recited in claim 7 , further comprising an act of approximating the inverse document frequency from the language model frequency for the textual phrases in the list. | 0.5 |
8,346,724 | 2 | 3 | 2. The method of claim 1 , further comprising: receiving an attribute value request, wherein the request specifies one or more criteria for the value; identifying one or more attribute instances that match the one or more criteria; pulling current values for the identified one or more attribute instances from a source of attribute values; determining if an attribute value is received, and processing the attribute value when received; and determining whether multiple attribute values are available for the attribute instances that match the one or more criteria, and mediating the multiple values when available. | 2. The method of claim 1 , further comprising: receiving an attribute value request, wherein the request specifies one or more criteria for the value; identifying one or more attribute instances that match the one or more criteria; pulling current values for the identified one or more attribute instances from a source of attribute values; determining if an attribute value is received, and processing the attribute value when received; and determining whether multiple attribute values are available for the attribute instances that match the one or more criteria, and mediating the multiple values when available. 3. The method of claim 2 , further comprising delivering previously received and stored attribute values that match the one or more criteria. | 0.834118 |
8,744,851 | 1 | 3 | 1. A method comprising: receiving text as part of a text-to-speech process; selecting, via a processor, a speech segment associated with the text, wherein the speech segment is selected from a primary speech database which has been modified by: identifying primary speech segments in the primary speech database which do not meet a need of the text-to-speech process, wherein the primary speech segments comprise one of half-phones, half-phonemes, demi-syllables, and polyphones; identifying replacement speech segments which satisfy the need in a secondary speech database; and enhancing the primary speech database by substituting, in the primary database, the primary speech segments with the replacement speech segments; and generating, via the processor, speech corresponding to the text using the speech segment. | 1. A method comprising: receiving text as part of a text-to-speech process; selecting, via a processor, a speech segment associated with the text, wherein the speech segment is selected from a primary speech database which has been modified by: identifying primary speech segments in the primary speech database which do not meet a need of the text-to-speech process, wherein the primary speech segments comprise one of half-phones, half-phonemes, demi-syllables, and polyphones; identifying replacement speech segments which satisfy the need in a secondary speech database; and enhancing the primary speech database by substituting, in the primary database, the primary speech segments with the replacement speech segments; and generating, via the processor, speech corresponding to the text using the speech segment. 3. The method of claim 1 , wherein the primary speech segments are one of diphones, triphones, and phonemes. | 0.886316 |
9,286,289 | 2 | 5 | 2. The computer system of claim 1 , wherein selecting the first subset of edges of the lexicon network comprises including a target edge into the first subset of edges according to a direction of the target edge. | 2. The computer system of claim 1 , wherein selecting the first subset of edges of the lexicon network comprises including a target edge into the first subset of edges according to a direction of the target edge. 5. The computer system of claim 2 , wherein the second node is assigned to a second level of the plurality of levels, and wherein assigning the first node comprises: when the first node points to the second node, selecting the first level so that the second level precedes the first level in the ordered sequence; and when the second node points to the first node, selecting the first level so that the first level precedes the second level in the ordered sequence. | 0.681507 |
8,280,434 | 1 | 5 | 1. A mobile wireless communications device, comprising: a transceiver configured to transmit and receive radio frequency (RF) signals carrying communications data of speech; a keyboard; a display; an adjunct comprising at least one of a speaker, LED, camera, and video module; a processor coupled to the adjunct, keyboard, display and transceiver and configured to: process the communications data of speech that is transmitted and received to and from the transceiver; convert communications data as speech received from the transceiver to text that is displayed on the display; convert text received at the keyboard into communications data of speech to be transmitted from the transceiver on an RF signal; and configure the adjunct to supplement the speech-to-text and text-to-speech conversion. | 1. A mobile wireless communications device, comprising: a transceiver configured to transmit and receive radio frequency (RF) signals carrying communications data of speech; a keyboard; a display; an adjunct comprising at least one of a speaker, LED, camera, and video module; a processor coupled to the adjunct, keyboard, display and transceiver and configured to: process the communications data of speech that is transmitted and received to and from the transceiver; convert communications data as speech received from the transceiver to text that is displayed on the display; convert text received at the keyboard into communications data of speech to be transmitted from the transceiver on an RF signal; and configure the adjunct to supplement the speech-to-text and text-to-speech conversion. 5. The mobile wireless communications device according to claim 1 , and further comprising a key that is depressed that automatically generates a signal as communications data for speech indicative of a greeting in a telephone call and a key that is depressed that automatically generates a signal as communications data for speech indicative of ending a telephone call. | 0.5 |
8,627,276 | 51 | 54 | 51. The device of claim 50 , where the first part includes a portion of the graphical model and the second part includes a segment of the code. | 51. The device of claim 50 , where the first part includes a portion of the graphical model and the second part includes a segment of the code. 54. The device of claim 51 , where the processor is further to: search the graphical model for the portion; and graphically relate the segment with the portion. | 0.659574 |
9,792,332 | 9 | 13 | 9. A system comprising: memory for storing event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device; and at least one computing device including a processor in communication with the memory, the at least one computing device operative to: generate a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, said score taking into consideration a first plurality of user-generated events by the first user reflecting a set of item affinities of the first user, and a second plurality of user-generated events by the second user reflecting a set of item affinities of the second user, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and based at least in part on the score, determine whether to output to the first user information about the second user. | 9. A system comprising: memory for storing event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device; and at least one computing device including a processor in communication with the memory, the at least one computing device operative to: generate a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, said score taking into consideration a first plurality of user-generated events by the first user reflecting a set of item affinities of the first user, and a second plurality of user-generated events by the second user reflecting a set of item affinities of the second user, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and based at least in part on the score, determine whether to output to the first user information about the second user. 13. The system of claim 9 , wherein the information output to the first user includes about item affinities of the second user. | 0.847722 |
8,086,442 | 14 | 18 | 14. A system for dividing an input into segments, the system comprising: a memory; a processor; and a segmentation component that is stored in said memory and that executes on said processor, wherein said segmentation component represents one or more segment breaking rules in a first regular expression, wherein said segmentation component combines a plurality of exceptions to said one or more segment breaking rules disjunctively into a second regular expression, said second regular expression being distinct from said first regular expression, wherein said segmentation component finds first strings in said input that match said second regular expression, wherein said segmentation component replaces said first strings with placeholders to create a second string, wherein said second string comprises said input but with said placeholders in place of said first strings, wherein said segmentation component uses said first regular expression to detect segment break points in said second string subsequent to finding of said first strings, and wherein said segmentation component replaces said placeholders in said second string with said first strings subsequent to detecting said segment break points. | 14. A system for dividing an input into segments, the system comprising: a memory; a processor; and a segmentation component that is stored in said memory and that executes on said processor, wherein said segmentation component represents one or more segment breaking rules in a first regular expression, wherein said segmentation component combines a plurality of exceptions to said one or more segment breaking rules disjunctively into a second regular expression, said second regular expression being distinct from said first regular expression, wherein said segmentation component finds first strings in said input that match said second regular expression, wherein said segmentation component replaces said first strings with placeholders to create a second string, wherein said second string comprises said input but with said placeholders in place of said first strings, wherein said segmentation component uses said first regular expression to detect segment break points in said second string subsequent to finding of said first strings, and wherein said segmentation component replaces said placeholders in said second string with said first strings subsequent to detecting said segment break points. 18. The system of claim 14 , wherein a first one of said one or more segment breaking rules has a before break rule, and wherein said first regular expression includes said before break rule as a positive lookbehind. | 0.71123 |
9,026,412 | 7 | 10 | 7. A computer system for a service oriented industry model repository architecture, the system comprising: a CPU, a computer readable memory, a non-transitory computer readable storage media, a plurality of service oriented architecture (SOA) industry model repositories (IMR) comprising a meta model service associated with a physical asset repository including model assets, requirement models, and document models, the meta model service comprising: at least one topic map meta model with data specific to a particular topic or industry vertical included within an information model repository common meta-meta model, the information model repository common meta-meta model included within a meta-meta-meta model with a topic map based index; first program instructions for defining boundaries and definitions of scope and scope propagation of topics, associations, and occurrences within the SOA IMR; second program instructions for managing boundaries and definitions of scope and scope propagation within the SOA IMR; and third program instructions for maintaining boundaries and definitions of scope and scope propagation within the SOA IMR; the first, second, and third program instructions are stored on the non-transitory computer readable storage media for execution by the CPU via the computer readable memory. wherein the scope is inheritance scoping. | 7. A computer system for a service oriented industry model repository architecture, the system comprising: a CPU, a computer readable memory, a non-transitory computer readable storage media, a plurality of service oriented architecture (SOA) industry model repositories (IMR) comprising a meta model service associated with a physical asset repository including model assets, requirement models, and document models, the meta model service comprising: at least one topic map meta model with data specific to a particular topic or industry vertical included within an information model repository common meta-meta model, the information model repository common meta-meta model included within a meta-meta-meta model with a topic map based index; first program instructions for defining boundaries and definitions of scope and scope propagation of topics, associations, and occurrences within the SOA IMR; second program instructions for managing boundaries and definitions of scope and scope propagation within the SOA IMR; and third program instructions for maintaining boundaries and definitions of scope and scope propagation within the SOA IMR; the first, second, and third program instructions are stored on the non-transitory computer readable storage media for execution by the CPU via the computer readable memory. wherein the scope is inheritance scoping. 10. The system of claim 7 , wherein the scope is industry vertical scoping. | 0.966216 |
8,019,893 | 27 | 28 | 27. A remote translation device to provide translation data to a network device, the remote translation device comprising: a receiver to receive from a network management device via a network at least one script to convert BNF strings to at least one other format, the receiver further to receive a translation request from a network device, the translation request including data to be translated and at least one identifier, the translation request identifying a format into which network data on the network device is to be translated, the network data comprising an input data string which is a string output from an IOS, the translation request further including at least one of an Internetwork Operating System (IOS) version provided on the network device or a hardware inventory of the network device; a memory to store the at least one script; a transmitter to communicate the at least one script to the network device, to execute the at least one script on the network device to translate the input data string to a selected format. | 27. A remote translation device to provide translation data to a network device, the remote translation device comprising: a receiver to receive from a network management device via a network at least one script to convert BNF strings to at least one other format, the receiver further to receive a translation request from a network device, the translation request including data to be translated and at least one identifier, the translation request identifying a format into which network data on the network device is to be translated, the network data comprising an input data string which is a string output from an IOS, the translation request further including at least one of an Internetwork Operating System (IOS) version provided on the network device or a hardware inventory of the network device; a memory to store the at least one script; a transmitter to communicate the at least one script to the network device, to execute the at least one script on the network device to translate the input data string to a selected format. 28. The translation device of claim 27 , wherein the translation request includes data to be translated in order for the network device to process the data to be translated for a routing or switching operation, the translation device further comprising: an identification module to identify a first data format associated with the received data and a second data format associated with the network device; and a translator to translate the received data corresponding to the first data format into translated data corresponding to the second data format, wherein the transmitter is configured to communicate the translated data to the network device. | 0.5 |
9,792,014 | 1 | 5 | 1. A computer-implemented method comprising: receiving an indication of an in-place menu selection for a first item of a list of items; providing an in-place menu and action commands for display in place of the first item, wherein the in-place menu replaces the space of the first item in a view of the first item; while the in-place menu and action commands are in the place of the first item, receiving an indication of an in-place menu selection for a second item of the list of items without receiving a pre-indication to invoke a multi-select mode; removing the in-place menu and action commands from the place of the first item while maintaining selection of the first item with a visual indication of the selection and providing the in-place menu and action commands for display in place of the second item, wherein the in-place menu replaces the space of the second item in a view of the second item; and in response to receiving a command selection of one of the action commands from the in-place menu, performing the action command for the at least the first item and the second item. | 1. A computer-implemented method comprising: receiving an indication of an in-place menu selection for a first item of a list of items; providing an in-place menu and action commands for display in place of the first item, wherein the in-place menu replaces the space of the first item in a view of the first item; while the in-place menu and action commands are in the place of the first item, receiving an indication of an in-place menu selection for a second item of the list of items without receiving a pre-indication to invoke a multi-select mode; removing the in-place menu and action commands from the place of the first item while maintaining selection of the first item with a visual indication of the selection and providing the in-place menu and action commands for display in place of the second item, wherein the in-place menu replaces the space of the second item in a view of the second item; and in response to receiving a command selection of one of the action commands from the in-place menu, performing the action command for the at least the first item and the second item. 5. The method of claim 1 , further comprising: determining a context of item type and providing action commands for the in-place menu according to the item type. | 0.937693 |
9,590,818 | 14 | 15 | 14. The method of claim 13 , further comprising: identifying, based on receiving the information based on the mode selection and the instruction for performing the device action, user information, the user information being identified based on speech information associated with the instruction for performing the device action. | 14. The method of claim 13 , further comprising: identifying, based on receiving the information based on the mode selection and the instruction for performing the device action, user information, the user information being identified based on speech information associated with the instruction for performing the device action. 15. The method of claim 14 , further comprising: generating, based on the speech information, text information; generating, based on the text information, one or more tags; and transmitting the one or more tags to the client device. | 0.5 |
8,510,296 | 2 | 7 | 2. The computer-implemented method of claim 1 , wherein said computing a first score for said query LAT associated with said input query comprises: extracting a set of features describing said determined query LAT; and, applying a model to the feature set to produce a LAT confidence value representing an estimated accuracy of the determined query LAT, said first score comprising said confidence value. | 2. The computer-implemented method of claim 1 , wherein said computing a first score for said query LAT associated with said input query comprises: extracting a set of features describing said determined query LAT; and, applying a model to the feature set to produce a LAT confidence value representing an estimated accuracy of the determined query LAT, said first score comprising said confidence value. 7. The computer-implemented method of claim 2 , wherein a feature of said extracted feature set comprises a co-reference information, said extracting a set of features further comprising: determining whether the candidate LAT word co-references some other word in said query recognized as a LAT. | 0.702621 |
8,996,975 | 10 | 11 | 10. The method of claim 1 , wherein identifying the relevant portion of the Web page is performed by a server in communication with the device. | 10. The method of claim 1 , wherein identifying the relevant portion of the Web page is performed by a server in communication with the device. 11. The method of claim 10 , wherein the server reorders frames in the Web page in accordance with the relevant portion. | 0.5 |
7,650,324 | 15 | 16 | 15. A computer-implemented method for providing contextual information associated with referenced objects in a description document by using a computer, the method comprising: receiving input for editing a shell document; receiving a request to insert a reference to an object within the shell document, the request including a parameter, wherein the shell document is separate from the object and the object is stored in a storage device of the computer; providing to display, a list of objects by searching through the storage device using the parameter as search criteria, the objects being stored in the storage device; receiving a selection of the object, the object being a known object of a first type and being selected from the list of fragment objects; comparing a predetermined rule associated with the object with the first type to determine an identity of a first property that is compatible with fragment object; searching, in the storage device, for the first property; determining whether a first property can be dynamically generated when the search is unsuccessful, wherein a message is provided to indicate that the first property is not available when the search result is unsuccessful and when the first property cannot bed dynamically generated; generating, based on the predetermined rule, the first property when it is determined that the first property can be dynamically generated, the first property including textual information describing a characteristic of the object; retrieving the first property from the storage device when the search is successful; generating, based on the request, response data including the reference to the object and the first property associated with the object, wherein the first property included in the response data is the retrieved first property when the search is successful, and wherein the first property included in the response data is the generated first property when the search is unsuccessful; editing the shell document by inserting the response data into the shell document, wherein the reference and the first property are inserted into an author identified location within the shell document, the reference being inserted without inserting the object, that is known, in the shell document; formatting the modified shell document based on commands inputted by the author; and rendering on a display device the modified and formatted shell document by including the response data describing a user-ascertainable characteristic of the object within the shell document by using the textual information included in the first property, wherein the user-ascertainable characteristic describes the characteristic of the object. | 15. A computer-implemented method for providing contextual information associated with referenced objects in a description document by using a computer, the method comprising: receiving input for editing a shell document; receiving a request to insert a reference to an object within the shell document, the request including a parameter, wherein the shell document is separate from the object and the object is stored in a storage device of the computer; providing to display, a list of objects by searching through the storage device using the parameter as search criteria, the objects being stored in the storage device; receiving a selection of the object, the object being a known object of a first type and being selected from the list of fragment objects; comparing a predetermined rule associated with the object with the first type to determine an identity of a first property that is compatible with fragment object; searching, in the storage device, for the first property; determining whether a first property can be dynamically generated when the search is unsuccessful, wherein a message is provided to indicate that the first property is not available when the search result is unsuccessful and when the first property cannot bed dynamically generated; generating, based on the predetermined rule, the first property when it is determined that the first property can be dynamically generated, the first property including textual information describing a characteristic of the object; retrieving the first property from the storage device when the search is successful; generating, based on the request, response data including the reference to the object and the first property associated with the object, wherein the first property included in the response data is the retrieved first property when the search is successful, and wherein the first property included in the response data is the generated first property when the search is unsuccessful; editing the shell document by inserting the response data into the shell document, wherein the reference and the first property are inserted into an author identified location within the shell document, the reference being inserted without inserting the object, that is known, in the shell document; formatting the modified shell document based on commands inputted by the author; and rendering on a display device the modified and formatted shell document by including the response data describing a user-ascertainable characteristic of the object within the shell document by using the textual information included in the first property, wherein the user-ascertainable characteristic describes the characteristic of the object. 16. The method of claim 15 , further comprising: displaying the message when the first property cannot be dynamically generated. | 0.5 |
8,856,638 | 14 | 16 | 14. A method for a multimedia seek sequence using a synchronization index and a mobile computing device, said method comprising the steps: providing a mobile computing device comprising a viewing screen and a touch-sensitive input interface; providing a synchronization index that comprises an electronic transcript that indicates text corresponding to audio from the multimedia and indicates respective times within multimedia corresponding to when a word or range of words is audible in the multimedia; providing a receiving device; displaying on said mobile computing device text from the synchronization index, wherein said text is displayed other than as a web page; receiving, by the mobile computing device, information indicating a user's selected mobile computing device touch-sensitive input interface gesture performed on a portion of said viewing screen corresponding to a word, or range of words, from said synchronization index; wherein said gesture is recognized by said touch-sensitive input interface; performing a timecode lookup using the synchronization index, wherein said synchronization index is referenced to provide data for a time location t1 that corresponds to said word or range of words; seeking on said receiving device multimedia corresponding to said synchronization index, and, if found, accessing multimedia at t1. | 14. A method for a multimedia seek sequence using a synchronization index and a mobile computing device, said method comprising the steps: providing a mobile computing device comprising a viewing screen and a touch-sensitive input interface; providing a synchronization index that comprises an electronic transcript that indicates text corresponding to audio from the multimedia and indicates respective times within multimedia corresponding to when a word or range of words is audible in the multimedia; providing a receiving device; displaying on said mobile computing device text from the synchronization index, wherein said text is displayed other than as a web page; receiving, by the mobile computing device, information indicating a user's selected mobile computing device touch-sensitive input interface gesture performed on a portion of said viewing screen corresponding to a word, or range of words, from said synchronization index; wherein said gesture is recognized by said touch-sensitive input interface; performing a timecode lookup using the synchronization index, wherein said synchronization index is referenced to provide data for a time location t1 that corresponds to said word or range of words; seeking on said receiving device multimedia corresponding to said synchronization index, and, if found, accessing multimedia at t1. 16. The method of claim 14 , further comprising: providing a second computing device; requesting from a second computing device delivery of multimedia beginning at time t1; delivering multimedia beginning at time t1, or providing instructions for the delivery of multimedia beginning at time t1, to a receiving device; and caching, within said receiving device, or memory accessible thereto, said multimedia or a portion thereof. | 0.660063 |
8,504,584 | 8 | 10 | 8. A non-transitory computer-readable memory device storing instructions, the instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to: identify a plurality of subsequent search queries that were received after a particular search query, as refinements of the particular search query; identify a first set of documents that is associated with a first subsequent search query, of the plurality of subsequent search queries; identify a second set of documents that is associated with a second subsequent search query, of the plurality of subsequent search queries; generate a first term vector for the first subsequent search query based on the identified first set of documents, and a second term vector for the second subsequent search query based on the identified second set of documents; cluster, based on the generated first term vector and the generated second term vector, the first subsequent search query into a first cluster and the second subsequent search query into a different, second cluster; select a particular subsequent search query from one or more of the first cluster or the different, second cluster; receive an indication that a client device has submitted a search query that includes the particular search query; and provide, to the client device, the selected particular subsequent search query from the one or more of the first cluster or the different, second cluster, as a refinement of the search query submitted by the client device. | 8. A non-transitory computer-readable memory device storing instructions, the instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to: identify a plurality of subsequent search queries that were received after a particular search query, as refinements of the particular search query; identify a first set of documents that is associated with a first subsequent search query, of the plurality of subsequent search queries; identify a second set of documents that is associated with a second subsequent search query, of the plurality of subsequent search queries; generate a first term vector for the first subsequent search query based on the identified first set of documents, and a second term vector for the second subsequent search query based on the identified second set of documents; cluster, based on the generated first term vector and the generated second term vector, the first subsequent search query into a first cluster and the second subsequent search query into a different, second cluster; select a particular subsequent search query from one or more of the first cluster or the different, second cluster; receive an indication that a client device has submitted a search query that includes the particular search query; and provide, to the client device, the selected particular subsequent search query from the one or more of the first cluster or the different, second cluster, as a refinement of the search query submitted by the client device. 10. The non-transitory computer-readable memory device of claim 8 , where the one or more instructions to select the particular subsequent search query further cause the one or more processors to: select a particular cluster, of the first cluster or the different, second cluster; and select one of the refinements, from the selected particular cluster, that was received a quantity of times after the particular search query and identified as a refinement of the particular search query, based on the quantity of times being greater than a quantity of times that other one of the refinements, of the selected particular cluster, were received after the particular search query and identified as refinements of the particular search query. | 0.674449 |
8,868,488 | 16 | 19 | 16. A method for automatically publishing unstructured data to a document container for an entity comprising the steps of: as one or more users interact with an application that manages structured accounting data for an entity, automatically publishing unstructured data including accounts receivable invoices, order confirmations, and shipment confirmations to a document container that is contained in a collaboration tool that has been integrated with the application, the unstructured data being automatically published based upon one or more rules that were specified for the document container; using an integration detail including at least one of: a location of the collaboration tool and a security setting for a user associated with the application, to authenticate the application to the collaboration tool, wherein the security setting is used to automatically create security roles and permissions in the collaboration tool upon site creation to enable interactions with the document container of the collaboration tool from within the application; enabling the one or more users to access the unstructured data in the document container from within the application; disabling management of the entity by the collaboration tool in response to detecting a disabled publish configuration on a configuration screen of the application; providing a view option for the document container to display the structured accounting data including pricing, credit details, and customer balance; in response to receiving a selection from the one or more users selecting a related documents option, prompting the collaboration tool to launch an associated screen to display the unstructured data; and providing an interface associated with the document container to manage the unstructured data by adding, editing, viewing, and deleting the unstructured data from another application. | 16. A method for automatically publishing unstructured data to a document container for an entity comprising the steps of: as one or more users interact with an application that manages structured accounting data for an entity, automatically publishing unstructured data including accounts receivable invoices, order confirmations, and shipment confirmations to a document container that is contained in a collaboration tool that has been integrated with the application, the unstructured data being automatically published based upon one or more rules that were specified for the document container; using an integration detail including at least one of: a location of the collaboration tool and a security setting for a user associated with the application, to authenticate the application to the collaboration tool, wherein the security setting is used to automatically create security roles and permissions in the collaboration tool upon site creation to enable interactions with the document container of the collaboration tool from within the application; enabling the one or more users to access the unstructured data in the document container from within the application; disabling management of the entity by the collaboration tool in response to detecting a disabled publish configuration on a configuration screen of the application; providing a view option for the document container to display the structured accounting data including pricing, credit details, and customer balance; in response to receiving a selection from the one or more users selecting a related documents option, prompting the collaboration tool to launch an associated screen to display the unstructured data; and providing an interface associated with the document container to manage the unstructured data by adding, editing, viewing, and deleting the unstructured data from another application. 19. The method of claim 16 , wherein at least some of the unstructured data is an order confirmation. | 0.756039 |
8,421,823 | 4 | 5 | 4. The apparatus of claim 1 , wherein the processor causes the image or emoticon to be sent to an audio video display device remote from the apparatus. | 4. The apparatus of claim 1 , wherein the processor causes the image or emoticon to be sent to an audio video display device remote from the apparatus. 5. The apparatus of claim 4 , wherein the processor receives user identification of the audio video display device remote from the apparatus. | 0.5 |
8,065,316 | 8 | 9 | 8. The method of claim 1 , further comprising: performing searches for each of the plurality of refinement query suggestions to identify at least one document based on the first search query; identifying terms within the identified at least one document; assigning weights to the identified terms; and generating a term vector for the identified at least one document based on the assigned weights to the identified terms, where the clustering is based on the generated term vector. | 8. The method of claim 1 , further comprising: performing searches for each of the plurality of refinement query suggestions to identify at least one document based on the first search query; identifying terms within the identified at least one document; assigning weights to the identified terms; and generating a term vector for the identified at least one document based on the assigned weights to the identified terms, where the clustering is based on the generated term vector. 9. The method of claim 8 , further comprising: normalizing the generated term vector for the identified at least one document. | 0.671875 |
8,014,634 | 8 | 19 | 8. A system comprising: a data processing apparatus with one or more processors; and a computer-readable memory in data communication with the data processing apparatus and storing instructions executable by the one or more processors and upon such execution cause the data processing apparatus to perform operations comprising: storing one or more graphical documents; storing content rating information associated with the one or more stored graphical documents; comparing graphical content of a graphical document under evaluation with graphical content of the one or more stored graphical documents to identify a matching graphical document; and granting a distribution approval to the graphical document under evaluation based on the match and content rating information associated with the matching graphical document. | 8. A system comprising: a data processing apparatus with one or more processors; and a computer-readable memory in data communication with the data processing apparatus and storing instructions executable by the one or more processors and upon such execution cause the data processing apparatus to perform operations comprising: storing one or more graphical documents; storing content rating information associated with the one or more stored graphical documents; comparing graphical content of a graphical document under evaluation with graphical content of the one or more stored graphical documents to identify a matching graphical document; and granting a distribution approval to the graphical document under evaluation based on the match and content rating information associated with the matching graphical document. 19. The system of claim 8 , wherein the instructions cause the data processing apparatus to compare at least one of the color scheme, objects, text, size, shape, formatting, file type, and source of the graphical document under evaluation with a corresponding color scheme, objects, text, size, shape, formatting, file type, and source of the one or more stored graphical documents. | 0.680067 |
8,914,361 | 16 | 17 | 16. The computer-implemented method of claim 15 , wherein identifying unrelated concepts comprise: determining a revised score for each local concept; determining said ranked global list of all local concepts based on the revised scores; removing local concepts whose combined revised score contributes less than a predetermined amount of a total score of the global list to produce a resulting list; identifying regions without a most relevant local concept on the resulting list; and removing local concepts expressed in the identified regions without a most relevant local concept from the resulting list to produce a list of relevant concepts. | 16. The computer-implemented method of claim 15 , wherein identifying unrelated concepts comprise: determining a revised score for each local concept; determining said ranked global list of all local concepts based on the revised scores; removing local concepts whose combined revised score contributes less than a predetermined amount of a total score of the global list to produce a resulting list; identifying regions without a most relevant local concept on the resulting list; and removing local concepts expressed in the identified regions without a most relevant local concept from the resulting list to produce a list of relevant concepts. 17. The computer-implemented method of claim 16 , wherein determining the source meaning comprises normalizing the revised scores for the relevant concepts. | 0.5 |
10,003,560 | 29 | 30 | 29. The apparatus of claim 23 , wherein the processor is further configured to: cause a continuous time series image flows representing the conversation streams to be displayed; identify overall sentiments for topics associated with the conversation streams; and cause indicators to be displayed in conjunction with the time series image flows to indicate changes in the overall sentiments for the topics associated with the conversation streams. | 29. The apparatus of claim 23 , wherein the processor is further configured to: cause a continuous time series image flows representing the conversation streams to be displayed; identify overall sentiments for topics associated with the conversation streams; and cause indicators to be displayed in conjunction with the time series image flows to indicate changes in the overall sentiments for the topics associated with the conversation streams. 30. The apparatus of claim 29 , wherein the processor is further configured to: identify a quantity of the social signals associated with each of the conversation streams; and cause different widths of the continuous time series image flows to be displayed based on the quantity of the social signals associated with each of the conversation streams. | 0.5 |
7,542,893 | 1 | 5 | 1. A machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-fragments stored in computer readable memory, each of the bi-fragments including a text fragment from the first language and a text fragment from the second language, at least some of the bi-fragments being modeled as elastic bi-fragments in which words of a fragment are spaced by a gap which is able to assume a variable size corresponding to a number of other words which are to occupy the gap; retrieving text fragments from the second language from the library corresponding to text fragments in the source text; generating, by a processor, at least one target hypothesis, each of said target hypotheses comprising text fragments selected from the second language; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions comprising a gap size scoring feature which favors hypotheses with statistically more probable gap sizes over hypotheses with statically less probable gap sizes. | 1. A machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-fragments stored in computer readable memory, each of the bi-fragments including a text fragment from the first language and a text fragment from the second language, at least some of the bi-fragments being modeled as elastic bi-fragments in which words of a fragment are spaced by a gap which is able to assume a variable size corresponding to a number of other words which are to occupy the gap; retrieving text fragments from the second language from the library corresponding to text fragments in the source text; generating, by a processor, at least one target hypothesis, each of said target hypotheses comprising text fragments selected from the second language; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions comprising a gap size scoring feature which favors hypotheses with statistically more probable gap sizes over hypotheses with statically less probable gap sizes. 5. The method of claim 1 , wherein the gap size scoring feature models gap sizes observed in a training corpus as a distribution which is expressed in terms of a parameter of the distribution. | 0.924883 |
8,682,394 | 19 | 28 | 19. A method comprising: associating a first color with a first message address characteristic and a second color with a second message address characteristic, wherein the first color is different from the second color; accepting, by a wireless communication device, a message address; examining the message address to identify a characteristic of the message address, wherein the characteristic is one of an email message recipient host name, a domain name, an approved email message recipient, and an unapproved email message recipient; and before transmission of a message including the message address, displaying message information including a name of a recipient associated with the message address on a display of a wireless communication device, wherein at least one of the name of the recipient and the message address is color-coded with the first color when the identified characteristic is the first message address characteristic and at least one of the name of the recipient and the message address is color-coded with the second color when the identified characteristic is the second message address characteristic. | 19. A method comprising: associating a first color with a first message address characteristic and a second color with a second message address characteristic, wherein the first color is different from the second color; accepting, by a wireless communication device, a message address; examining the message address to identify a characteristic of the message address, wherein the characteristic is one of an email message recipient host name, a domain name, an approved email message recipient, and an unapproved email message recipient; and before transmission of a message including the message address, displaying message information including a name of a recipient associated with the message address on a display of a wireless communication device, wherein at least one of the name of the recipient and the message address is color-coded with the first color when the identified characteristic is the first message address characteristic and at least one of the name of the recipient and the message address is color-coded with the second color when the identified characteristic is the second message address characteristic. 28. The method of claim 19 , further comprising displaying address information for each of a plurality of message addresses, wherein the address information includes visual cues to identify address information based on the identified characteristic. | 0.5 |
8,244,752 | 15 | 18 | 15. A computer-readable storage medium storing computer-executable instructions that, when executed, cause a computer system to perform a method for classifying search query traffic, said method comprising: receiving, from a search engine, labeled sample search query traffic, said labeled sample search traffic being labeled as human generated search query traffic or automatically generated search query traffic, said labeled sample search query traffic including one or more keywords for each search query submitted to said search engine and request times for a plurality of search queries submitted to said search engine within distinct user sessions; extracting features from said labeled sample search query traffic in accordance with a set of feature definitions partitioned into physical features related to physical limitations of human generated search queries and behavioral features of automatically generated search queries and keywords of the automatically generated search queries; generating a feature set comprising (i) said features extracted from said labeled sample search query traffic and (ii) a behavioral feature related to query word length entropy (WLE) that is calculated as: WL E ( l ij ) = - ∑ i ∑ j l ij log ( l ij ) , i being an index for each separate query submitted to a search engine by a single user ID and I ij being a length of an individual query term j in the ith query; generating a model using said labeled sample search query traffic and said feature set; receiving, from said search engine, search query traffic associated with a plurality of search queries submitted by a particular user identifier; classifying, using said model, said search query traffic associated with said plurality of search queries submitted by said particular user identifier as human generated search query traffic or automatically generated search query traffic; and altering a quality of service provided by said search engine to said user identifier when said search query traffic associated with said plurality of search queries submitted by said particular user identifier is classified as automatically generated search query traffic. | 15. A computer-readable storage medium storing computer-executable instructions that, when executed, cause a computer system to perform a method for classifying search query traffic, said method comprising: receiving, from a search engine, labeled sample search query traffic, said labeled sample search traffic being labeled as human generated search query traffic or automatically generated search query traffic, said labeled sample search query traffic including one or more keywords for each search query submitted to said search engine and request times for a plurality of search queries submitted to said search engine within distinct user sessions; extracting features from said labeled sample search query traffic in accordance with a set of feature definitions partitioned into physical features related to physical limitations of human generated search queries and behavioral features of automatically generated search queries and keywords of the automatically generated search queries; generating a feature set comprising (i) said features extracted from said labeled sample search query traffic and (ii) a behavioral feature related to query word length entropy (WLE) that is calculated as: WL E ( l ij ) = - ∑ i ∑ j l ij log ( l ij ) , i being an index for each separate query submitted to a search engine by a single user ID and I ij being a length of an individual query term j in the ith query; generating a model using said labeled sample search query traffic and said feature set; receiving, from said search engine, search query traffic associated with a plurality of search queries submitted by a particular user identifier; classifying, using said model, said search query traffic associated with said plurality of search queries submitted by said particular user identifier as human generated search query traffic or automatically generated search query traffic; and altering a quality of service provided by said search engine to said user identifier when said search query traffic associated with said plurality of search queries submitted by said particular user identifier is classified as automatically generated search query traffic. 18. The computer-readable storage medium of claim 15 , wherein said feature set comprises a behavioral feature related to a program specified field identifying a program source. | 0.5 |
9,761,247 | 17 | 20 | 17. A conversational understanding system for addressee detection, comprising: a computer processor and memory; an operating environment executed by the computer processor; and an addressee manager that is configured to perform actions comprising: receiving an utterance; extracting prosodic features from speech segments of the received utterance; performing an evaluation of the extracted prosodic features to determine whether the intended addressee is a computer or a human, wherein the evaluation is word-independent, context-independent, and speaker independent; in response to determining that the intended addressee is the computer, processing the utterance to generate a response for the received utterance; and outputting the response through the conversational understanding system. | 17. A conversational understanding system for addressee detection, comprising: a computer processor and memory; an operating environment executed by the computer processor; and an addressee manager that is configured to perform actions comprising: receiving an utterance; extracting prosodic features from speech segments of the received utterance; performing an evaluation of the extracted prosodic features to determine whether the intended addressee is a computer or a human, wherein the evaluation is word-independent, context-independent, and speaker independent; in response to determining that the intended addressee is the computer, processing the utterance to generate a response for the received utterance; and outputting the response through the conversational understanding system. 20. The system of claim 17 , wherein the performed actions further comprise: determining the intended addressee based on speech activity information, wherein the speech activity information comprises a length of initial final non-speech regions and a duration of non-speech regions. | 0.584071 |
9,781,178 | 11 | 15 | 11. A system comprising: a processor of a machine; a template generation module configured to generate, using the processor of the machine, a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; a user interface module configured to receive a content item from a first user of a group of users designated as contributors to the publication the user interface module further configured to receive, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and a generation module configured to generate the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user. | 11. A system comprising: a processor of a machine; a template generation module configured to generate, using the processor of the machine, a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; a user interface module configured to receive a content item from a first user of a group of users designated as contributors to the publication the user interface module further configured to receive, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and a generation module configured to generate the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user. 15. The system of claim 11 , wherein the publication commemorates a shared experience of a group of users connected on a social graph. | 0.83208 |
7,587,251 | 1 | 9 | 1. A computer-implemented system to facilitate industrial automation monitoring or control, comprising: at least one processor coupled to a memory, the processor executes: a receiver component that receives a request for a web page associated with a network adaptor; an execution component that executes instantiated objects within the web page to effectuate at least one of monitoring and control of an I/O module that is communicatively coupled to the network adaptor; an editor component that enables creation of new objects or editing of instantiated objects; a selection component that facilitates selection of a project associated with the instantiated objects; a saving component that facilitates saving the instantiated objects with respect to a selected project on at least one of a local drive and a network server drive; and a transaction component that enables the selection and purchase of additional objects to be utilized by the editor component while creating or editing web pages. | 1. A computer-implemented system to facilitate industrial automation monitoring or control, comprising: at least one processor coupled to a memory, the processor executes: a receiver component that receives a request for a web page associated with a network adaptor; an execution component that executes instantiated objects within the web page to effectuate at least one of monitoring and control of an I/O module that is communicatively coupled to the network adaptor; an editor component that enables creation of new objects or editing of instantiated objects; a selection component that facilitates selection of a project associated with the instantiated objects; a saving component that facilitates saving the instantiated objects with respect to a selected project on at least one of a local drive and a network server drive; and a transaction component that enables the selection and purchase of additional objects to be utilized by the editor component while creating or editing web pages. 9. The system of claim 1 , further comprising a requestor component that requests a Java plug-in to execute the instantiated objects upon the receiver component receiving the request. | 0.602174 |
7,877,732 | 9 | 12 | 9. A data processing system for stress testing a service oriented architecture based application, the data processing system comprising: a bus; a storage device connected to the bus, wherein the storage device contains computer usable code; at least one managed device connected to the bus; a communications unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to record a business process flow; extract an XML document from the recorded business process flow; create an XML document file for the extracted XML document, an XML document descriptor file comprising XPath queries for data elements in the XML document file, a configuration file comprising user input parameters obtained from the recorded business process flow, and a test input data file; generate a test script using input of the XML document file, the XML document descriptor file, and the configuration file and inserting data values from the test input data file into a template defined by the XML document file at locations specified by the XPath queries; and execute the test script. | 9. A data processing system for stress testing a service oriented architecture based application, the data processing system comprising: a bus; a storage device connected to the bus, wherein the storage device contains computer usable code; at least one managed device connected to the bus; a communications unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to record a business process flow; extract an XML document from the recorded business process flow; create an XML document file for the extracted XML document, an XML document descriptor file comprising XPath queries for data elements in the XML document file, a configuration file comprising user input parameters obtained from the recorded business process flow, and a test input data file; generate a test script using input of the XML document file, the XML document descriptor file, and the configuration file and inserting data values from the test input data file into a template defined by the XML document file at locations specified by the XPath queries; and execute the test script. 12. The data processing system of claim 9 , wherein the XML document and the XML document file conform to a business object document standard. | 0.867537 |
9,508,044 | 12 | 15 | 12. A configuration manager, comprising: a one or more rules generator configured to collect a plurality of configurations from a plurality of computing resources, respectively, and process the plurality of configurations to generate one or more rules, wherein the one or more rules is generated by an analyzer; a configuration analyzer, wherein the configuration analyzer is configured to analyze one or more first configurations out of the plurality of configurations to produce an analysis result, wherein the configuration analyzer is configured to analyze the one or more first configurations based on the one or more rules, and each of the first configuration(s) defines a configuration of a respective computing resource; and a Bayesian classifier, wherein the Bayesian classifier is configured to be trained using the analysis result, generate one or more weights during training, take as an input the first configurations of the respective computing resources, after the training, classify a second configuration, wherein the Bayesian classifier uses the weight(s) when classifying the second configuration, after the training, be modified in response to a modification of the classified second configuration, wherein the Bayesian classifier is configured to adjust at least one weight in response to the modification of the classified second configuration. | 12. A configuration manager, comprising: a one or more rules generator configured to collect a plurality of configurations from a plurality of computing resources, respectively, and process the plurality of configurations to generate one or more rules, wherein the one or more rules is generated by an analyzer; a configuration analyzer, wherein the configuration analyzer is configured to analyze one or more first configurations out of the plurality of configurations to produce an analysis result, wherein the configuration analyzer is configured to analyze the one or more first configurations based on the one or more rules, and each of the first configuration(s) defines a configuration of a respective computing resource; and a Bayesian classifier, wherein the Bayesian classifier is configured to be trained using the analysis result, generate one or more weights during training, take as an input the first configurations of the respective computing resources, after the training, classify a second configuration, wherein the Bayesian classifier uses the weight(s) when classifying the second configuration, after the training, be modified in response to a modification of the classified second configuration, wherein the Bayesian classifier is configured to adjust at least one weight in response to the modification of the classified second configuration. 15. The configuration manager of claim 12 , wherein each first configuration comprises one or more features that indicate the configuration of a respective resource, and the weight(s) are associated with the feature(s) of the first configuration(s). | 0.642241 |
8,515,999 | 5 | 6 | 5. The method of claim 1 , where validating comprises querying a facts database. | 5. The method of claim 1 , where validating comprises querying a facts database. 6. The method of claim 5 , where an output of the facts database is expressed as a facts XML instance. | 0.5 |
7,792,883 | 15 | 20 | 15. A computer-implemented method for performing a location search, comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a location search query; identifying geographical features that satisfy the location search query; ranking the identified geographical features in accordance with a score that is based, at least in part, on proximity of the geographical features to a geographical viewport region of a client system, to produce a set of ranked geographical features; and providing results, in accordance with the ranked geographical features, that identify at least one geographic feature corresponding to the at least one of the ranked geographical features. | 15. A computer-implemented method for performing a location search, comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a location search query; identifying geographical features that satisfy the location search query; ranking the identified geographical features in accordance with a score that is based, at least in part, on proximity of the geographical features to a geographical viewport region of a client system, to produce a set of ranked geographical features; and providing results, in accordance with the ranked geographical features, that identify at least one geographic feature corresponding to the at least one of the ranked geographical features. 20. The method of claim 15 , including: determining key words corresponding to the location search query; and identifying geographical features that match the key words in the location search query. | 0.5 |
9,030,699 | 12 | 15 | 12. A method, implemented in a computer system, of delivering content to an electronic device associated with a portable scanner, comprising: receiving, at a computer system and from a portable scanner, a device identifier scanned using the portable scanner, the device identifier being displayed on an electronic device; receiving, at the computer system and from the portable scanner, additional information scanned using the portable scanner; selecting, by the computer system, based at least in part on the device identifier, the electronic device to send the additional information scanned; identifying a network address of the selected electronic device identified by the device identifier; and communicating the additional information scanned to the network address associated with the selected electronic device. | 12. A method, implemented in a computer system, of delivering content to an electronic device associated with a portable scanner, comprising: receiving, at a computer system and from a portable scanner, a device identifier scanned using the portable scanner, the device identifier being displayed on an electronic device; receiving, at the computer system and from the portable scanner, additional information scanned using the portable scanner; selecting, by the computer system, based at least in part on the device identifier, the electronic device to send the additional information scanned; identifying a network address of the selected electronic device identified by the device identifier; and communicating the additional information scanned to the network address associated with the selected electronic device. 15. The method of claim 12 , further comprising: configuring the device for exclusive use by a person using the portable scanner for as long as the portable scanner is associated with the electronic device. | 0.752998 |
8,266,702 | 1 | 11 | 1. A system for analyzing access control configurations, comprising: a processor and memory; an operating system having resources and identifications of principals, the principals having access control privileges relating to the resources, the access control privileges described by access control metadata; an access control scanner component that receives the access control metadata, uses the metadata to determine relationships between the principals and the resources, and emits access control relations information, wherein the access control scanner component includes a mechanism layer that is configured to be specific to an operating system, and emits one or more sets of permissions in relation to resources, and a policy layer that is configured be general across multiple operating systems, the policy layer receives the one or more sets of permissions and generates one or more derivation trees that each indicate a possible vulnerability based on the relationships between the principals and the resources; and an access control inference engine that receives the emitted access control relations information and an access control policy model defining desired security policies, analyzes the received information and model, and emits a vulnerability report. | 1. A system for analyzing access control configurations, comprising: a processor and memory; an operating system having resources and identifications of principals, the principals having access control privileges relating to the resources, the access control privileges described by access control metadata; an access control scanner component that receives the access control metadata, uses the metadata to determine relationships between the principals and the resources, and emits access control relations information, wherein the access control scanner component includes a mechanism layer that is configured to be specific to an operating system, and emits one or more sets of permissions in relation to resources, and a policy layer that is configured be general across multiple operating systems, the policy layer receives the one or more sets of permissions and generates one or more derivation trees that each indicate a possible vulnerability based on the relationships between the principals and the resources; and an access control inference engine that receives the emitted access control relations information and an access control policy model defining desired security policies, analyzes the received information and model, and emits a vulnerability report. 11. The system of claim 1 wherein the access control scanner component can be substituted with a different access control scanner component for use with a different operating system. | 0.597345 |
8,661,338 | 8 | 11 | 8. A method comprising: comparing one or more elements of at least a portion of an original document against the same types of elements in at least a portion each of a plurality of stored documents, wherein the portion of the original document is the portion that requires adjustment or re-layout; determining a particular stored document in the plurality of stored documents, with the portion which is closest to the portion of the original document based on the comparing; identifying a designated output device and output device characteristics; applying one or more mutators to the portion of the original document which were applied to mutate the portion of the determined particular stored document, to form a mutated portion in the original document, having obtained one or more mutators from a list of stored mutators which correspond to the determined particular stored document, wherein the applying further comprises determining which of the one or more stored mutators to apply based on one or more of the characteristics of the designated output device and the identified particular stored document that matches the portion of the original document; and wherein the applying further comprises determining an order for the applying of the determined one or more mutators to the portion of the original document, according to stored priority order. | 8. A method comprising: comparing one or more elements of at least a portion of an original document against the same types of elements in at least a portion each of a plurality of stored documents, wherein the portion of the original document is the portion that requires adjustment or re-layout; determining a particular stored document in the plurality of stored documents, with the portion which is closest to the portion of the original document based on the comparing; identifying a designated output device and output device characteristics; applying one or more mutators to the portion of the original document which were applied to mutate the portion of the determined particular stored document, to form a mutated portion in the original document, having obtained one or more mutators from a list of stored mutators which correspond to the determined particular stored document, wherein the applying further comprises determining which of the one or more stored mutators to apply based on one or more of the characteristics of the designated output device and the identified particular stored document that matches the portion of the original document; and wherein the applying further comprises determining an order for the applying of the determined one or more mutators to the portion of the original document, according to stored priority order. 11. The method as set forth in claim 8 wherein the determining further comprises: generating a score for each of the comparisons of the portion of the original document against each of the portions of each of the plurality of stored documents; and identifying the particular stored document with the portion with the score which is closest to the portion of the original document based on the generated scores. | 0.625912 |
8,180,751 | 1 | 7 | 1. A method, comprising: crawling a computer network to identify documents that name an individual; generating, by a system having a processor, summaries of the documents with articles in an encyclopedia; building, by the system, a profile of the individual with the summaries; and searching the profile to provide responses to search queries. | 1. A method, comprising: crawling a computer network to identify documents that name an individual; generating, by a system having a processor, summaries of the documents with articles in an encyclopedia; building, by the system, a profile of the individual with the summaries; and searching the profile to provide responses to search queries. 7. The method of claim 1 further comprising: aggregating names of individuals with titles of articles from the encyclopedia to construct a database; searching the database for individuals with a specific expertise. | 0.660317 |
8,261,187 | 2 | 4 | 2. The method as claimed in claim 1 , wherein the fragment object includes a third set of data corresponding to a transformation of the document fragment of the source document, further comprising: (f) transforming the document fragment of the source document based on the third set of data; (g) incorporating the transformed data into the referencing document to generate a document; (h) changing the incorporated transformed data of the document; and (i) modifying fragment object referenced by the referencing document to include a fourth set of data, the fourth set of data corresponding to the change in the incorporated transformed data of the document. | 2. The method as claimed in claim 1 , wherein the fragment object includes a third set of data corresponding to a transformation of the document fragment of the source document, further comprising: (f) transforming the document fragment of the source document based on the third set of data; (g) incorporating the transformed data into the referencing document to generate a document; (h) changing the incorporated transformed data of the document; and (i) modifying fragment object referenced by the referencing document to include a fourth set of data, the fourth set of data corresponding to the change in the incorporated transformed data of the document. 4. The method as claimed in claim 2 , wherein the transformation of the document fragment of the source document is a summarization of the document fragment of the source document. | 0.77887 |
9,053,489 | 1 | 7 | 1. A computer-implemented method comprising: as implemented by one or more computing devices configured with specific computer-executable instructions, receiving a message from a sender communication device, wherein the message is configured to be sent to a recipient communication device using an identifier of the recipient communication device; identifying a word, for which advertising is available, from the message; receiving geographical location information from the recipient communication device; determining temporal information pertaining to the recipient communication device based at least on the geographical location information received from the recipient communication device; sending the word identified from the message and the temporal information to a third party; obtaining a plurality of advertisements from the third party based at least in part on the word identified in the message and the temporal information, wherein each advertisement of the plurality of advertisements is associated with a respective payment level, and wherein each respective payment level is based at least in part on the temporal information pertaining to the recipient communication device; associating in a data store of the one or more computing devices the word identified in the message with the plurality of advertisements and the identifier of the recipient communication device, wherein the one or more computing devices are remote from the sender communication device and the recipient communication device; sending the message to the recipient communication device; receiving, from the recipient communication device, the identifier of the recipient communication device; receiving, from the recipient communication device, a transcribed utterance that includes the word identified in the message; selecting at least one advertisement of the plurality of advertisements, wherein the selecting is based at least in part on the respective payment level of the at least one advertisement; and based at least in part on the word identified in the message being present in the transcribed utterance and being associated with the plurality of advertisements and the identifier of the recipient communication device, sending the at least one advertisement to the recipient communication device using the identifier of the recipient communication device. | 1. A computer-implemented method comprising: as implemented by one or more computing devices configured with specific computer-executable instructions, receiving a message from a sender communication device, wherein the message is configured to be sent to a recipient communication device using an identifier of the recipient communication device; identifying a word, for which advertising is available, from the message; receiving geographical location information from the recipient communication device; determining temporal information pertaining to the recipient communication device based at least on the geographical location information received from the recipient communication device; sending the word identified from the message and the temporal information to a third party; obtaining a plurality of advertisements from the third party based at least in part on the word identified in the message and the temporal information, wherein each advertisement of the plurality of advertisements is associated with a respective payment level, and wherein each respective payment level is based at least in part on the temporal information pertaining to the recipient communication device; associating in a data store of the one or more computing devices the word identified in the message with the plurality of advertisements and the identifier of the recipient communication device, wherein the one or more computing devices are remote from the sender communication device and the recipient communication device; sending the message to the recipient communication device; receiving, from the recipient communication device, the identifier of the recipient communication device; receiving, from the recipient communication device, a transcribed utterance that includes the word identified in the message; selecting at least one advertisement of the plurality of advertisements, wherein the selecting is based at least in part on the respective payment level of the at least one advertisement; and based at least in part on the word identified in the message being present in the transcribed utterance and being associated with the plurality of advertisements and the identifier of the recipient communication device, sending the at least one advertisement to the recipient communication device using the identifier of the recipient communication device. 7. The computer-implemented method of claim 1 , wherein selecting at least one advertisement of the plurality of advertisements based at least in part on the respective payment level of the at least one advertisement comprises selecting the advertisement with the highest respective payment level among the plurality of advertisements. | 0.587438 |
8,965,835 | 10 | 11 | 10. The apparatus of claim 7 , wherein the analysis unit further provides a recommendation to increase or decrease advertisement expenditure. | 10. The apparatus of claim 7 , wherein the analysis unit further provides a recommendation to increase or decrease advertisement expenditure. 11. The apparatus of claim 10 , wherein the advertisement expenditure is increased or decreased based on the correlation analysis between the at least two term taxonomies. | 0.5 |
9,275,411 | 14 | 15 | 14. The voice action system of claim 9 , wherein one or more of the electronic voice action bids comprise an offer to provide a benefit in exchange for modifying the voice action system to include a voice action associated with the respective electronic voice action bid for a limited amount of time. | 14. The voice action system of claim 9 , wherein one or more of the electronic voice action bids comprise an offer to provide a benefit in exchange for modifying the voice action system to include a voice action associated with the respective electronic voice action bid for a limited amount of time. 15. The voice action system of claim 14 , wherein the one or more of the electronic voice action bids comprise an offer to provide a benefit in exchange for modifying the voice action system to include a voice action associated with the respective electronic voice action bid on a particular date or a particular day of the week. | 0.5 |
6,065,001 | 2 | 4 | 2. An information associating apparatus according to claim 1 wherein: said query extraction unit extracts the search time for each search user and said query from queries used for searching during said extracted past predetermined time interval, said preprocessing unit calculating for each of said search users the minimal time interval which is the smallest value among the time intervals between the time one query was used among said plurality of extracted queries and the time a different query was used among said plurality of extracted queries, and said association degree calculation unit calculates for each of said predetermined search users the association degree between said one query and said different query according to said minimum time interval based on said smallest time interval among the predetermined search users, and calculates the interval association degree for key words by adding the degree of association calculated for said plurality of search users. | 2. An information associating apparatus according to claim 1 wherein: said query extraction unit extracts the search time for each search user and said query from queries used for searching during said extracted past predetermined time interval, said preprocessing unit calculating for each of said search users the minimal time interval which is the smallest value among the time intervals between the time one query was used among said plurality of extracted queries and the time a different query was used among said plurality of extracted queries, and said association degree calculation unit calculates for each of said predetermined search users the association degree between said one query and said different query according to said minimum time interval based on said smallest time interval among the predetermined search users, and calculates the interval association degree for key words by adding the degree of association calculated for said plurality of search users. 4. An information associating apparatus according to claim 2 wherein: said association degree calculation unit carries out further processing in which two key words according to one interval association degree and two key words according to another interval association degree are compiled into one group if the one key word among the two key words according to said one particular interval association degree and another key word according to another of said particular interval association degrees are identical when, after calculating the interval association degree of said key words, a plurality of particular interval degree association degrees exist in which said interval association degrees are equal to or greater then a particular interval association degree. | 0.524104 |
9,563,659 | 9 | 10 | 9. The system as recited in claim 8 , wherein the program instructions of the computer program further comprises: analyzing search queries used to locate said social learning playlist and content items within said social learning playlist to identify additional key concepts using said natural language processing; and analyzing social commentary of said social learning playlist to identify additional key concepts using said natural language processing. | 9. The system as recited in claim 8 , wherein the program instructions of the computer program further comprises: analyzing search queries used to locate said social learning playlist and content items within said social learning playlist to identify additional key concepts using said natural language processing; and analyzing social commentary of said social learning playlist to identify additional key concepts using said natural language processing. 10. The system as recited in claim 9 , wherein the program instructions of the computer program further comprises: prioritizing said identified key concepts using a weighting algorithm which are presented to a user for approval. | 0.5 |
8,180,624 | 15 | 18 | 15. A decoding apparatus, comprising: a memory that retains instructions for receiving sequence data requiring sequence translation; front-loading an estimated future distortion penalty in translating a remainder of the sequence of data; creating a search space of possible next-phrase translations; reducing the search space based in part on the estimated future distortion penalty; and selecting a translation candidate for the sequence data; and a processor that is configured to execute the instructions within the memory. | 15. A decoding apparatus, comprising: a memory that retains instructions for receiving sequence data requiring sequence translation; front-loading an estimated future distortion penalty in translating a remainder of the sequence of data; creating a search space of possible next-phrase translations; reducing the search space based in part on the estimated future distortion penalty; and selecting a translation candidate for the sequence data; and a processor that is configured to execute the instructions within the memory. 18. The decoding apparatus of claim 15 , the sequence translation is language translation from a first language to a second language. | 0.5 |
8,296,130 | 1 | 14 | 1. A method, comprising: receiving, using one or more data processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving, using the one or more data processors, a string of words, wherein a candidate word is selected from the string of words; calculating, using the one or more data processors, for each respective offensive word in the plurality of offensive words, a distance between the candidate word and the respective offensive word; calculating, using the one or more data processors, a plurality of offensiveness scores for the candidate word, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein the plurality of offensiveness scores are calculated according to one or more of:
offensiveness score= A *(( B−C )/ B );
offensiveness score= A *(( B−( 1/ C ))/ B );
offensiveness score=Max((( A−C )/ A ),0); and
offensiveness score=((( B−C )/ B )> T ); wherein, A is the severity score for an offensive word in the plurality of offensive words; B is a function of a length of the offensive word; C is the calculated distance between the candidate word and the offensive word; and T is a threshold value; and determining, using the one or more data processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value. | 1. A method, comprising: receiving, using one or more data processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving, using the one or more data processors, a string of words, wherein a candidate word is selected from the string of words; calculating, using the one or more data processors, for each respective offensive word in the plurality of offensive words, a distance between the candidate word and the respective offensive word; calculating, using the one or more data processors, a plurality of offensiveness scores for the candidate word, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein the plurality of offensiveness scores are calculated according to one or more of:
offensiveness score= A *(( B−C )/ B );
offensiveness score= A *(( B−( 1/ C ))/ B );
offensiveness score=Max((( A−C )/ A ),0); and
offensiveness score=((( B−C )/ B )> T ); wherein, A is the severity score for an offensive word in the plurality of offensive words; B is a function of a length of the offensive word; C is the calculated distance between the candidate word and the offensive word; and T is a threshold value; and determining, using the one or more data processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value. 14. The method of claim 1 , wherein the plurality of offensive words and severity score identifying each of the plurality of offensive words are identified by a user, a service administrator, a third-party, or any combination thereof. | 0.721429 |
8,015,144 | 11 | 12 | 11. The system of claim 9 , the inference model comprising a decision tree classifier, a Bayesian Net inference model, or a support vector machine inference model, or any combination of a decision tree classifier, a Bayesian Net inference model, or a support vector machine inference model. | 11. The system of claim 9 , the inference model comprising a decision tree classifier, a Bayesian Net inference model, or a support vector machine inference model, or any combination of a decision tree classifier, a Bayesian Net inference model, or a support vector machine inference model. 12. The system of claim 11 , comprising a post-processing mechanism coupled to the inference model, the post-processing mechanism configured to recalculate probabilities provided by the inference model into final probabilities using transition probabilities. | 0.5 |
8,515,025 | 6 | 7 | 6. The method of claim 1 , further comprising receiving, by the server from at least one of the client terminals, a query as to which participant uttered the second utterance, and wherein providing the identifier includes providing the identifier in response to the query. | 6. The method of claim 1 , further comprising receiving, by the server from at least one of the client terminals, a query as to which participant uttered the second utterance, and wherein providing the identifier includes providing the identifier in response to the query. 7. The method of claim 6 , wherein providing the identifier in response to the query includes providing a textual message representative of the identifier. | 0.503205 |
9,760,640 | 1 | 3 | 1. A method comprising: receiving, by a Web server over a communications network including the Internet, a request from a user client device to access content of a target domain, the request being addressed to a domain address of the target domain; identifying, by the Web server, a new content domain that is determined to be relevant to the request to access content of a target domain based on a combination of the domain address of the target domain, source context factors that characterize the user client device, and historical relevance data associated with the target domain, the historical relevance data including source context factors of multiple users who requested to access at least one given address from addresses belonging to the domain address of the target domain and interests of the multiple users, the interests of the multiple users based on pre-access behavior of the multiple users; and providing, by the Web server, the user client device with access to content of the identified new content domain over the communications network, responsive to the request. | 1. A method comprising: receiving, by a Web server over a communications network including the Internet, a request from a user client device to access content of a target domain, the request being addressed to a domain address of the target domain; identifying, by the Web server, a new content domain that is determined to be relevant to the request to access content of a target domain based on a combination of the domain address of the target domain, source context factors that characterize the user client device, and historical relevance data associated with the target domain, the historical relevance data including source context factors of multiple users who requested to access at least one given address from addresses belonging to the domain address of the target domain and interests of the multiple users, the interests of the multiple users based on pre-access behavior of the multiple users; and providing, by the Web server, the user client device with access to content of the identified new content domain over the communications network, responsive to the request. 3. The method of claim 1 wherein the operation of providing access to content of the identified new content domain comprises: accessing the content from the new content domain; and serving the content to the user client device. | 0.729762 |
7,542,820 | 13 | 14 | 13. The system of claim 10 wherein said rules define permissible values for said parameters. | 13. The system of claim 10 wherein said rules define permissible values for said parameters. 14. The a system of claim 13 wherein said rules define dependency between said parameters. | 0.5 |
8,515,816 | 41 | 42 | 41. One or more computer memories storing machine executable instructions which when executed by a computer cause the computer to: store information formatted in a communal text capture data structure, the communal text capture data structure comprising a plurality of entries, each entry indicating a text sequence captured from a rendered document; and use the contents of the communal text capture data structure to analyze aggregate text capture behavior. | 41. One or more computer memories storing machine executable instructions which when executed by a computer cause the computer to: store information formatted in a communal text capture data structure, the communal text capture data structure comprising a plurality of entries, each entry indicating a text sequence captured from a rendered document; and use the contents of the communal text capture data structure to analyze aggregate text capture behavior. 42. The computer memories of claim 41 wherein each indicated text sequence constitutes a proper subset of text appearing on a page of a rendered document. | 0.5 |
7,937,465 | 4 | 5 | 4. The computationally-implemented system of claim 2 , wherein said circuitry for receiving the subjective user state data comprises: circuitry for receiving the subjective user state data via a network interface. | 4. The computationally-implemented system of claim 2 , wherein said circuitry for receiving the subjective user state data comprises: circuitry for receiving the subjective user state data via a network interface. 5. The computationally-implemented system of claim 4 , wherein said circuitry for receiving the subjective user state data via a network interface comprises: circuitry for receiving data indicating the at least one subjective user state via a blog entry generated by the user. | 0.505376 |
7,996,753 | 4 | 5 | 4. The method of claim 1 , wherein the electronic advertisement comprises a text ad. | 4. The method of claim 1 , wherein the electronic advertisement comprises a text ad. 5. The method of claim 4 , wherein the suggested presentation content comprises a plurality of text items, and wherein the selection comprises a selected text item, and wherein the text ad comprises the selected text item. | 0.5 |
7,639,257 | 65 | 68 | 65. A computer readable medium encoded with a computer program for representing a character in a text document, the computer program comprising instructions that when executed by a programmable processor of a computer cause the programmable processor to perform operations comprising: inserting into the text document a reference identifying a glyphlet, the identified glyphlet being a data structure stored in a memory of the computer including both a set of one or more character attributes defining semantic information of a character and a set of one or more glyph attributes defining appearance information from which a glyph image of a glyph representing the character can be rendered, the glyph attributes including all the information necessary to render the glyph image, the reference representing the character in the text document; and displaying the character in the text document, the displayed character being rendered from the glyph attributes. | 65. A computer readable medium encoded with a computer program for representing a character in a text document, the computer program comprising instructions that when executed by a programmable processor of a computer cause the programmable processor to perform operations comprising: inserting into the text document a reference identifying a glyphlet, the identified glyphlet being a data structure stored in a memory of the computer including both a set of one or more character attributes defining semantic information of a character and a set of one or more glyph attributes defining appearance information from which a glyph image of a glyph representing the character can be rendered, the glyph attributes including all the information necessary to render the glyph image, the reference representing the character in the text document; and displaying the character in the text document, the displayed character being rendered from the glyph attributes. 68. The computer readable medium encoded with the computer program of claim 65 , wherein: the reference includes one or more in-band values that are interpreted to define the identified glyphlet. | 0.776888 |
9,710,223 | 11 | 12 | 11. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: monitoring an audio stream associated with a non-tactile gesture input stream; identifying a speech event, in the audio stream, from a first user; determining a temporal window associated with a time of the speech event, wherein the temporal window extends forward and backward from the time of the speech event; analyzing data from the non-tactile gesture input stream within the temporal window to identify, based on the speech event, a non-tactile gesture event; identifying clarifying information, in the audio stream, about the speech event from a second user; applying the clarifying information to the speech event to yield a clarification; and processing, based on the clarification, the speech event and the non-tactile gesture event to produce a multimodal command. | 11. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: monitoring an audio stream associated with a non-tactile gesture input stream; identifying a speech event, in the audio stream, from a first user; determining a temporal window associated with a time of the speech event, wherein the temporal window extends forward and backward from the time of the speech event; analyzing data from the non-tactile gesture input stream within the temporal window to identify, based on the speech event, a non-tactile gesture event; identifying clarifying information, in the audio stream, about the speech event from a second user; applying the clarifying information to the speech event to yield a clarification; and processing, based on the clarification, the speech event and the non-tactile gesture event to produce a multimodal command. 12. The system of claim 11 , wherein a non-tactile gesture in the non-tactile gesture input stream is directed to a display, but is remote from the display. | 0.753943 |
8,103,709 | 7 | 10 | 7. A method for invention life cycle tracking, comprising: providing a data storage configured to store a plurality of documents, including a first document and a second document; interacting with a user, from an invention disclosure module in a computer processor device, to tag the first document with an attribute indicating an invention, the invention being one of a plurality of inventions, when the first document is stored in the data storage and is not previously filed in an official intellectual property office; prompting the user, from a document creation module in the computer processor device, automatically without manual intervention, to select one of the plurality of inventions previously tagged to one of the plurality of documents, as the invention to which the second document is directed, when the second document is initially created; and tagging the second document with the attribute indicating the invention, when the second document is initially stored in the data storage, wherein the first and second documents collectively reflect progress in the invention life cycle, the attribute is in a predetermined hierarchy of a plurality of attributes, tagging one of the documents, which had not previously been tagged, with the attribute causes the one of the documents to be associated with the attribute and with parent attributes of the attribute according to the predetermined hierarchy, for later retrieval of the documents by searching for the invention and the parent attributes. | 7. A method for invention life cycle tracking, comprising: providing a data storage configured to store a plurality of documents, including a first document and a second document; interacting with a user, from an invention disclosure module in a computer processor device, to tag the first document with an attribute indicating an invention, the invention being one of a plurality of inventions, when the first document is stored in the data storage and is not previously filed in an official intellectual property office; prompting the user, from a document creation module in the computer processor device, automatically without manual intervention, to select one of the plurality of inventions previously tagged to one of the plurality of documents, as the invention to which the second document is directed, when the second document is initially created; and tagging the second document with the attribute indicating the invention, when the second document is initially stored in the data storage, wherein the first and second documents collectively reflect progress in the invention life cycle, the attribute is in a predetermined hierarchy of a plurality of attributes, tagging one of the documents, which had not previously been tagged, with the attribute causes the one of the documents to be associated with the attribute and with parent attributes of the attribute according to the predetermined hierarchy, for later retrieval of the documents by searching for the invention and the parent attributes. 10. The method of claim 7 , further comprising, in the computer processor device, inputting a product name in a search module as invention search criteria, searching a plurality of documents including the first document and the second document, and returning search results listing the first document and the second document tagged as being directed to the invention with the product name when the product name is input as search criteria. | 0.5 |
9,047,275 | 1 | 5 | 1. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; determining estimations reflecting correspondence between the first and the second fragments, wherein each estimation is based at least on a ratio between: (a) a number of words in at least one of the first segment or the second segment; and (b) a number of words in the first fragment that have a corresponding translation in the second fragment according to a normalized one-to-one dictionary; determining a degree of correspondence between the first and the second fragments based on the estimations, including adjusting the estimations by using weight coefficients selected on the basis of heuristics or training; and comparing the degree of correspondence to a predetermined threshold. | 1. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; determining estimations reflecting correspondence between the first and the second fragments, wherein each estimation is based at least on a ratio between: (a) a number of words in at least one of the first segment or the second segment; and (b) a number of words in the first fragment that have a corresponding translation in the second fragment according to a normalized one-to-one dictionary; determining a degree of correspondence between the first and the second fragments based on the estimations, including adjusting the estimations by using weight coefficients selected on the basis of heuristics or training; and comparing the degree of correspondence to a predetermined threshold. 5. The method of claim 1 wherein the estimations include the presence in the first and the second fragments of at least one of the following: dates, numbers, abbreviations, family names, or geographical names. | 0.645763 |
9,405,779 | 1 | 4 | 1. A system, comprising: a memory operable to store a search index associated with an ontology, wherein the ontology comprises at least one instance and the instance has a name; and a processor communicatively coupled to the memory and operable to: query the search index and the ontology in parallel, wherein the search index is generated based at least in part upon an unstructured data element by streaming and normalizing received data terms from a data source and the ontology is generated based at least in part upon an structured data element at least one data mitigation and classification rule; receive a first search request relating to information stored in an ontology; parse the first search request to determine if the first search request is an instance based search that comprises all or part of a name of at least a first instance in the ontology; perform a first query of the search index in response to determining that the first search request is an instance based search; receive a second search request relating to information stored in the ontology; parse the second search request to determine if the second search request is an instance based search that comprises all or part of a name of at least a second instance in the ontology; and perform a second query of at least the ontology in response to determining that the second search request is not an instance based search receive a third search request relating to information not stored in the ontology; parse the third search request to determine that the third search request is an instance based search that comprises all or part of a name of at least one instance in the ontology; perform a third query of the search index and retrieve metadata associated with the third instance from the search index, wherein the metadata comprises information about a data source associated with the third instance; and retrieve information from the data source that are not stored in the ontology. | 1. A system, comprising: a memory operable to store a search index associated with an ontology, wherein the ontology comprises at least one instance and the instance has a name; and a processor communicatively coupled to the memory and operable to: query the search index and the ontology in parallel, wherein the search index is generated based at least in part upon an unstructured data element by streaming and normalizing received data terms from a data source and the ontology is generated based at least in part upon an structured data element at least one data mitigation and classification rule; receive a first search request relating to information stored in an ontology; parse the first search request to determine if the first search request is an instance based search that comprises all or part of a name of at least a first instance in the ontology; perform a first query of the search index in response to determining that the first search request is an instance based search; receive a second search request relating to information stored in the ontology; parse the second search request to determine if the second search request is an instance based search that comprises all or part of a name of at least a second instance in the ontology; and perform a second query of at least the ontology in response to determining that the second search request is not an instance based search receive a third search request relating to information not stored in the ontology; parse the third search request to determine that the third search request is an instance based search that comprises all or part of a name of at least one instance in the ontology; perform a third query of the search index and retrieve metadata associated with the third instance from the search index, wherein the metadata comprises information about a data source associated with the third instance; and retrieve information from the data source that are not stored in the ontology. 4. The system of claim 1 , wherein performing the first query or the second query further comprises: identifying a symbol in the search index based on the search request, wherein the symbol corresponds to a particular instance in the ontology; submitting a query to the ontology based on the symbol; receiving, in response to either query, one or more instances from the ontology, wherein the one or more instances are related to the particular instance in the ontology. | 0.5 |
8,756,219 | 1 | 15 | 1. A computer-implemented method for determining relevant search categories and associated subcategories based on a query provided by a user, and displaying the relevant search categories and associated subcategories on an initial search results page after the query has been processed, the method comprising: receiving a user inputted query; determining a set of algorithmic search results that are algorithmically determined to be relevant to the user inputted query; accessing a database comprising a plurality of stored queries, each of the plurality of stored queries being associated with predetermined sets of search categories and correlated subcategories based on at least one of a frequency or a probability of previous users refining a search for the each of the stored queries using the predetermined sets of search categories and correlated subcategories; determining a stored query in the database that is similar to the user inputted query; identifying one or more predetermined search categories and one or more predetermined subcategories correlated with a corresponding search category of the one or more predetermined search categories that are associated in the database with the stored query, the one or more predetermined search categories and the one or more predetermined subcategories relevant to the user inputted query, wherein (1) each search category of the one or more predetermined search categories represents a vertical search category corresponding to a type of information, and wherein selection of the each search category provides a first set of search results corresponding to the type of information, and (2) each subcategory of the one or more predetermined subcategories represents a more refined type of information as compared to the each subcategory's correlated category, and wherein selection of the each subcategory provides a second set of search results corresponding to the more refined type of information; and generating the initial search results page, wherein the initial search results page is a first results page that is visible to the user after the user submits the query, the initial search results page comprising: (1) a first display area useable for presenting the set of algorithmic search results, and (2) a second display area useable for presenting a portion of the one or more predetermined search categories and the one or more predetermined subcategories, the second display area being displayed in a separate area than the first display area on the initial search results page. | 1. A computer-implemented method for determining relevant search categories and associated subcategories based on a query provided by a user, and displaying the relevant search categories and associated subcategories on an initial search results page after the query has been processed, the method comprising: receiving a user inputted query; determining a set of algorithmic search results that are algorithmically determined to be relevant to the user inputted query; accessing a database comprising a plurality of stored queries, each of the plurality of stored queries being associated with predetermined sets of search categories and correlated subcategories based on at least one of a frequency or a probability of previous users refining a search for the each of the stored queries using the predetermined sets of search categories and correlated subcategories; determining a stored query in the database that is similar to the user inputted query; identifying one or more predetermined search categories and one or more predetermined subcategories correlated with a corresponding search category of the one or more predetermined search categories that are associated in the database with the stored query, the one or more predetermined search categories and the one or more predetermined subcategories relevant to the user inputted query, wherein (1) each search category of the one or more predetermined search categories represents a vertical search category corresponding to a type of information, and wherein selection of the each search category provides a first set of search results corresponding to the type of information, and (2) each subcategory of the one or more predetermined subcategories represents a more refined type of information as compared to the each subcategory's correlated category, and wherein selection of the each subcategory provides a second set of search results corresponding to the more refined type of information; and generating the initial search results page, wherein the initial search results page is a first results page that is visible to the user after the user submits the query, the initial search results page comprising: (1) a first display area useable for presenting the set of algorithmic search results, and (2) a second display area useable for presenting a portion of the one or more predetermined search categories and the one or more predetermined subcategories, the second display area being displayed in a separate area than the first display area on the initial search results page. 15. The method of claim 1 , further comprising: receiving a selection of at least one of the one or more predetermined search categories or at least one of the one or more predetermined subcategories on the initial search results page; generating a second search results page comprising: (1) a first display area useable for presenting a new updated set of search results relevant to the selected at least one of the one or more predetermined search categories or the at least one of the one or more predetermined subcategories; and (2) a second display area useable for presenting the portion of the one or more predetermined search categories and the one or more predetermined subcategories in their entirety. | 0.5 |
8,095,544 | 1 | 10 | 1. A method for associating documents with searchable metadata, the method comprising: receiving as input at least one text document; and operating at least one programmed processor to perform acts of creating metadata to be associated with the at least one text document, the metadata comprising at least one text keyword, the creating comprising extracting a set of one or more data elements from text of the at least one text document, the set of one or more data elements comprising at least one keyword that appears in the text of the at least one text document; normalizing said set of data elements to create a set of normalized data elements, wherein the normalizing comprises, for a first keyword of the at least one keyword, determining at least one other keyword similar to the first keyword, the at least one other keyword not being a keyword appearing in the text of the at least one text document, and adding the at least one other keyword to the set of normalized data elements; identifying at least one previously-validated keyword that is associated as metadata with at least one previously-stored text document, the at least one previously-stored text document not being one of the at least one text document, the at least one previously-validated keyword not being in the set of normalized data elements; merging said set of normalized data elements with the at least one previously-validated keyword to form a preliminary set of data elements; presenting said preliminary set of data elements for review by a user; and receiving user input validating a validated set of data elements; and in response to the user input validating the validated set of data elements, storing the at least one text document and storing the validated set of data elements as the metadata, the metadata being associated with the at least one text document such that the at least one text document may be located through a search for any data element included in the validated set of data elements. | 1. A method for associating documents with searchable metadata, the method comprising: receiving as input at least one text document; and operating at least one programmed processor to perform acts of creating metadata to be associated with the at least one text document, the metadata comprising at least one text keyword, the creating comprising extracting a set of one or more data elements from text of the at least one text document, the set of one or more data elements comprising at least one keyword that appears in the text of the at least one text document; normalizing said set of data elements to create a set of normalized data elements, wherein the normalizing comprises, for a first keyword of the at least one keyword, determining at least one other keyword similar to the first keyword, the at least one other keyword not being a keyword appearing in the text of the at least one text document, and adding the at least one other keyword to the set of normalized data elements; identifying at least one previously-validated keyword that is associated as metadata with at least one previously-stored text document, the at least one previously-stored text document not being one of the at least one text document, the at least one previously-validated keyword not being in the set of normalized data elements; merging said set of normalized data elements with the at least one previously-validated keyword to form a preliminary set of data elements; presenting said preliminary set of data elements for review by a user; and receiving user input validating a validated set of data elements; and in response to the user input validating the validated set of data elements, storing the at least one text document and storing the validated set of data elements as the metadata, the metadata being associated with the at least one text document such that the at least one text document may be located through a search for any data element included in the validated set of data elements. 10. The method according to claim 1 , wherein presenting the preliminary set of data elements for review comprises displaying the preliminary set of data elements on a graphical display. | 0.799136 |
8,855,797 | 23 | 26 | 23. A system for synchronizing playback of content comprising: a data store that stores content synchronization information; a processor in communication with the data store, the processor operative to: during output of a visual content and an associated sequential content, maintain, based at least in part on the synchronization information, synchronization between an output pointer of the visual content and an associated position of the sequential content, wherein the associated position of the sequential content advances during output of the sequential content, and wherein the output pointer indicates a position within the visual content corresponding to a current output position of the sequential content; obtain an input pointer that references a location within the visual content being output; during advancement of the output pointer, determine, independent of the obtained input pointer, a position of the output pointer corresponding to the current output position of the sequential content; and modify an attribute associated with the output of the sequential content based at least in part on a difference between the determined position of the output pointer and the location within the visual content referenced by the input pointer. | 23. A system for synchronizing playback of content comprising: a data store that stores content synchronization information; a processor in communication with the data store, the processor operative to: during output of a visual content and an associated sequential content, maintain, based at least in part on the synchronization information, synchronization between an output pointer of the visual content and an associated position of the sequential content, wherein the associated position of the sequential content advances during output of the sequential content, and wherein the output pointer indicates a position within the visual content corresponding to a current output position of the sequential content; obtain an input pointer that references a location within the visual content being output; during advancement of the output pointer, determine, independent of the obtained input pointer, a position of the output pointer corresponding to the current output position of the sequential content; and modify an attribute associated with the output of the sequential content based at least in part on a difference between the determined position of the output pointer and the location within the visual content referenced by the input pointer. 26. The system of claim 23 , wherein the input pointer is obtained from an input device. | 0.959032 |
8,762,365 | 15 | 19 | 15. A system, comprising: at least one computing device; and a network site classification engine in the at least one computing device, the network site classification engine comprising: logic that computes a plurality of similarities between a first plurality of search queries and individual ones of a second plurality of search queries, the first plurality of search queries returning an unclassified network site and the second plurality of search queries returning a plurality of classified network sites, individual ones of the classified network sites having a respective category, wherein the plurality of similarities are based at least on a query importance comprising a click through and the query importance is associated with a search query in the first plurality of search queries and the second plurality of search queries; and logic that classifies the unclassified network site into the respective category of one of the classified network sites based at least in part on the plurality of similarities. | 15. A system, comprising: at least one computing device; and a network site classification engine in the at least one computing device, the network site classification engine comprising: logic that computes a plurality of similarities between a first plurality of search queries and individual ones of a second plurality of search queries, the first plurality of search queries returning an unclassified network site and the second plurality of search queries returning a plurality of classified network sites, individual ones of the classified network sites having a respective category, wherein the plurality of similarities are based at least on a query importance comprising a click through and the query importance is associated with a search query in the first plurality of search queries and the second plurality of search queries; and logic that classifies the unclassified network site into the respective category of one of the classified network sites based at least in part on the plurality of similarities. 19. The system of claim 15 , wherein the computing of similarities uses vector space calculations. | 0.841424 |
7,627,638 | 3 | 5 | 3. A computer-implemented method, comprising: receiving an audio input from a user; creating a verbal label comprising audio data representing the audio input from the user; labeling a plurality of electronic messages using the verbal label, wherein the verbal label is used to identify the plurality of electronic messages; and unifying the verbal label with a preexisting text label for the user, wherein the unifying includes: performing speech recognition on the audio input from the user or the audio data representing the audio input from the user, matching the preexisting text label for the user to the audio input from the user or the audio data representing the audio input from the user, and labeling the plurality of electronic messages with the matching preexisting text label for the user. | 3. A computer-implemented method, comprising: receiving an audio input from a user; creating a verbal label comprising audio data representing the audio input from the user; labeling a plurality of electronic messages using the verbal label, wherein the verbal label is used to identify the plurality of electronic messages; and unifying the verbal label with a preexisting text label for the user, wherein the unifying includes: performing speech recognition on the audio input from the user or the audio data representing the audio input from the user, matching the preexisting text label for the user to the audio input from the user or the audio data representing the audio input from the user, and labeling the plurality of electronic messages with the matching preexisting text label for the user. 5. The method of claim 3 , wherein the verbal label comprises digital audio data. | 0.765896 |
9,734,143 | 11 | 13 | 11. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for applying a translation model, the operations comprising: obtaining a content item associated with one or more multi-media items and comprising one or more input n-grams, wherein an n-gram is a digital representation of one or more words or groups of characters; identifying one or more multi-media labels for the one or more multi-media items associated with the content item; assigning to the identified one or more multi-media labels at least some of the one or more input n-grams of the content item; obtaining the translation model, wherein the translation model comprises a probability distribution indicating, for selected n-grams, a probability that an output n-gram is a translation of the selected n-gram, given one or more multi-media labels; and applying, to the content item, the obtained translation model by selecting one or more output n-grams that, based on the probability distribution, have a highest probability of being the translation of the at least some of the one or more input n-grams of the content item, given the identified one or more multi-media labels assigned to the at least some of the one or more input n-grams of the content item. | 11. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for applying a translation model, the operations comprising: obtaining a content item associated with one or more multi-media items and comprising one or more input n-grams, wherein an n-gram is a digital representation of one or more words or groups of characters; identifying one or more multi-media labels for the one or more multi-media items associated with the content item; assigning to the identified one or more multi-media labels at least some of the one or more input n-grams of the content item; obtaining the translation model, wherein the translation model comprises a probability distribution indicating, for selected n-grams, a probability that an output n-gram is a translation of the selected n-gram, given one or more multi-media labels; and applying, to the content item, the obtained translation model by selecting one or more output n-grams that, based on the probability distribution, have a highest probability of being the translation of the at least some of the one or more input n-grams of the content item, given the identified one or more multi-media labels assigned to the at least some of the one or more input n-grams of the content item. 13. The non-transitory computer-readable storage medium of claim 11 , wherein identifying the one or more multi-media labels for the one or more multi-media items associated with the selected content item comprises identifying, in at least one of the one or more multi-media items, at least one of: an object, a place, a person, or any combination thereof; and wherein the one or more multi-media labels are selected from a set of pre-defined labels. | 0.666172 |
6,151,576 | 23 | 25 | 23. A method of processing a mixed-media data stream, comprising: reading a mixed-media data stream comprising a text component and a digitized speech component, the text component comprising text segments identified in the mixed-media data stream as doubtful and the digitized speech component comprising digitized speech corresponding to the text segments identified as doubtful; converting the text not identified as doubtful to synthetic speech; and generating an audio waveform from the mixed-media data stream by combining the digitized speech and the synthetic speech. | 23. A method of processing a mixed-media data stream, comprising: reading a mixed-media data stream comprising a text component and a digitized speech component, the text component comprising text segments identified in the mixed-media data stream as doubtful and the digitized speech component comprising digitized speech corresponding to the text segments identified as doubtful; converting the text not identified as doubtful to synthetic speech; and generating an audio waveform from the mixed-media data stream by combining the digitized speech and the synthetic speech. 25. The method of claim 23, further comprising: speaking the audio waveform. | 0.881988 |
7,987,188 | 19 | 21 | 19. The system of claim 13 , wherein the classifier module is further configured to: build a model having n-grams of the domain-specific sentiment lexicon as features; and train the model on a training corpus having domain-specific documents having manually-labeled sentiment scores. | 19. The system of claim 13 , wherein the classifier module is further configured to: build a model having n-grams of the domain-specific sentiment lexicon as features; and train the model on a training corpus having domain-specific documents having manually-labeled sentiment scores. 21. The system of claim 19 , wherein the training generates sentiment scores for the n-grams of the domain-specific sentiment lexicon and wherein the storing module is further configured to: store the sentiment scores for the n-grams of the domain-specific sentiment lexicon with the domain-specific sentiment lexicon. | 0.5 |
9,367,235 | 4 | 18 | 4. A non-transitory computer-readable medium comprising program code for receiving a confirming gesture formed on or about a sensor panel, the program code for causing performance of a method comprising: detecting one or more images at a first time at the sensor panel; determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture; determining a centering parameter from the one or more images; associating the OK gesture with a user interface (UI) element coincident with the centering parameter, the UI element accepting a confirming input; and providing the confirming input to the UI element. | 4. A non-transitory computer-readable medium comprising program code for receiving a confirming gesture formed on or about a sensor panel, the program code for causing performance of a method comprising: detecting one or more images at a first time at the sensor panel; determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture; determining a centering parameter from the one or more images; associating the OK gesture with a user interface (UI) element coincident with the centering parameter, the UI element accepting a confirming input; and providing the confirming input to the UI element. 18. The computer-readable medium of claim 4 , wherein detecting the one or more images at the first time at the sensor panel comprises concurrently detecting the one or more images at the first time at the sensor panel. | 0.639803 |
9,734,151 | 8 | 11 | 8. A non-transitory computer readable medium storing instructions which, when executed by one or more processors, cause performance of steps comprising: sending voice input data received by a media device to a speech-to-text service; receiving, by the media device, a textual representation of the voice input from the speech-to-text service; generating a signature based on the entire textual representation of the voice input, wherein the signature is a hash value; searching a set of data entries stored by the media device for a data entry matching the signature generated based on the entire textual representation of the voice input, each data entry of the set of stored data entries specifying a mapping between a signature and one or more media device actions; updating the set of stored data entries by storing the mapping between the signature and the entire textual representation; in response to locating a particular stored data entry based on the generated signature, performing one or more particular media device actions associated with the particular stored data entry, the one or more particular media device actions including sending a media content query to a media search service; receiving, by the media device, one or more content item listings based on the media content query; causing display of at least a portion of the one or more content item listings. | 8. A non-transitory computer readable medium storing instructions which, when executed by one or more processors, cause performance of steps comprising: sending voice input data received by a media device to a speech-to-text service; receiving, by the media device, a textual representation of the voice input from the speech-to-text service; generating a signature based on the entire textual representation of the voice input, wherein the signature is a hash value; searching a set of data entries stored by the media device for a data entry matching the signature generated based on the entire textual representation of the voice input, each data entry of the set of stored data entries specifying a mapping between a signature and one or more media device actions; updating the set of stored data entries by storing the mapping between the signature and the entire textual representation; in response to locating a particular stored data entry based on the generated signature, performing one or more particular media device actions associated with the particular stored data entry, the one or more particular media device actions including sending a media content query to a media search service; receiving, by the media device, one or more content item listings based on the media content query; causing display of at least a portion of the one or more content item listings. 11. The non-transitory computer readable medium as recited in claim 8 , further comprising: receiving input from a user indicating a selection of one or more of the content item listings; in response to selection of one or more of the content item listings, storing information representing the selection. | 0.730088 |
9,275,291 | 2 | 5 | 2. The system of claim 1 , wherein the classification computer processor module is further configured to: automatically generate data classification rules based at least in part on a subset of the first set of selected codes, a subset of second set of selected codes, the set of data items in the training data set, the first trust score, and the second trust score; automatically apply the data classification rules to the first data set; and generate a set of selected classification codes for the first data set. | 2. The system of claim 1 , wherein the classification computer processor module is further configured to: automatically generate data classification rules based at least in part on a subset of the first set of selected codes, a subset of second set of selected codes, the set of data items in the training data set, the first trust score, and the second trust score; automatically apply the data classification rules to the first data set; and generate a set of selected classification codes for the first data set. 5. The system of claim 2 , wherein the classification computer processor module is further configured to automatically generate a final data analysis of the classified first data set. | 0.540201 |
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