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9,087,132 | 18 | 23 | 18. A method of tying a geospatial location to a PIDF-LO file, comprising: receiving, at a physical network server, a Presence Information Data Format-Location Object (PIDF-LO) file; determining, at said physical network server, that said PIDF-LO file lacks geospatial location information identifying a specific physical zone; identifying a universal resource locator (URL) of XML content relating to a location relevant to said PIDF-LO file; requesting, through said physical network server, said geospatial location information; associating, via a Session Initiation Protocol (SIP) protocol, said geospatial location information with said XML content; and inserting, at said physical network server, said URL of XML content into said PIDF-LO file. | 18. A method of tying a geospatial location to a PIDF-LO file, comprising: receiving, at a physical network server, a Presence Information Data Format-Location Object (PIDF-LO) file; determining, at said physical network server, that said PIDF-LO file lacks geospatial location information identifying a specific physical zone; identifying a universal resource locator (URL) of XML content relating to a location relevant to said PIDF-LO file; requesting, through said physical network server, said geospatial location information; associating, via a Session Initiation Protocol (SIP) protocol, said geospatial location information with said XML content; and inserting, at said physical network server, said URL of XML content into said PIDF-LO file. 23. The method of tying a geospatial location to a PIDF-LO file according to claim 18 , wherein: said geospatial location information is defined using a coordinate based polygon system. | 0.609705 |
9,679,252 | 13 | 17 | 13. A method for performing a context classification with adjustable granularity, the method comprising: receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; selecting a configuration parameter, from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input, wherein a configuration parameter for a granularity input indicating a high granularity level is associated with a high resource usage level and a configuration parameter for a granularity input indicating a low granularity level is associated with a low resource usage level; and performing the context classification according to the granularity input, indicating the granularity level of the context classification output, by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification. | 13. A method for performing a context classification with adjustable granularity, the method comprising: receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; selecting a configuration parameter, from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input, wherein a configuration parameter for a granularity input indicating a high granularity level is associated with a high resource usage level and a configuration parameter for a granularity input indicating a low granularity level is associated with a low resource usage level; and performing the context classification according to the granularity input, indicating the granularity level of the context classification output, by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification. 17. The method of claim 13 further comprising: identifying subsets of available outputs for the context classification; and assigning respective ones of the subsets of available outputs for the context classification to respective classifier granularity configurations, wherein the classifier granularity configurations define corresponding resource usage levels. | 0.817954 |
9,971,848 | 1 | 4 | 1. A method comprising: converting a medical document, having textual content and rich formatting, into a first XHTML document that retains the textual content and the rich formatting of the medical document, the first XHTML document including a first text string in rich formatting; generating from the first XHTML document a plain text document that retains the textual content and not the rich formatting of the first XHTML document, wherein generating the plain text document comprises extracting text nodes from the first XHTML document and forming the plain text document from the extracted text nodes, the plain text document including the first text string in plain text without rich formatting; generating one or more annotations of the plain text document by applying a natural language understanding (NLU) engine implemented on a processor to the plain text document, the one or more annotations including a first annotation linked to the first text string in the plain text document without rich formatting; and displaying an annotated XHTML document created by applying the one or more annotations of the plain text document to a tokenized XHTML document including the textual content and the rich formatting of the medical document, the tokenized XHTML document including the first text string in rich formatting, wherein displaying the annotated XHTML document comprises displaying the first annotation linked to the first text string in rich formatting in the tokenized XHTML document. | 1. A method comprising: converting a medical document, having textual content and rich formatting, into a first XHTML document that retains the textual content and the rich formatting of the medical document, the first XHTML document including a first text string in rich formatting; generating from the first XHTML document a plain text document that retains the textual content and not the rich formatting of the first XHTML document, wherein generating the plain text document comprises extracting text nodes from the first XHTML document and forming the plain text document from the extracted text nodes, the plain text document including the first text string in plain text without rich formatting; generating one or more annotations of the plain text document by applying a natural language understanding (NLU) engine implemented on a processor to the plain text document, the one or more annotations including a first annotation linked to the first text string in the plain text document without rich formatting; and displaying an annotated XHTML document created by applying the one or more annotations of the plain text document to a tokenized XHTML document including the textual content and the rich formatting of the medical document, the tokenized XHTML document including the first text string in rich formatting, wherein displaying the annotated XHTML document comprises displaying the first annotation linked to the first text string in rich formatting in the tokenized XHTML document. 4. The method of claim 1 , further comprising maintaining the one or more annotations in a document separate from the tokenized XHTML document. | 0.872093 |
8,773,359 | 4 | 5 | 4. The method of claim 1 wherein considering at least one likelihood of at least one interpretation of the key assertion comprises, at least in part, according a likelihood advantage to one particular interpretation of the key assertion. | 4. The method of claim 1 wherein considering at least one likelihood of at least one interpretation of the key assertion comprises, at least in part, according a likelihood advantage to one particular interpretation of the key assertion. 5. The method of claim 4 wherein the likelihood advantage is not necessarily dispositive. | 0.930793 |
9,875,299 | 1 | 3 | 1. A system for identifying relevant search results via an index, comprising: a query module to receive a search query and to generate a semantic representation for the query comprising a plurality of substructures as a semantic analysis of the search query and a list of key terms, wherein the key terms each comprise a term in the search query or a term related to one of the terms in the search query; an inverted index comprising a set of key terms each associated with a semantic representation for each of a plurality of passages comprising a plurality of substructures and further associated with a link to a reference document for the passage; a candidate module to identify one or more of the passages as retrieval candidates by comparing the semantic representations associated with the passages with the semantic representation of the search query, comprising: a term selection module to select a subset of the key terms from the search query and to query the inverted index with the key terms in the subset; a result module to identify within the inverted index a result set for each of the key terms in the subset; and a scoring module to score each of the results in the set based on a distance of relationships of the substructures in the semantic representation of the search query and the semantic representation of the passages and to identify a subset of the result sets as the retrieval candidates based on the scoring; and a candidate selection module to select one or more of the retrieval candidates based on a comparison of the semantic representation of the search query with the semantic representations for each of the retrieval candidates, wherein the modules are executed via a computer processor. | 1. A system for identifying relevant search results via an index, comprising: a query module to receive a search query and to generate a semantic representation for the query comprising a plurality of substructures as a semantic analysis of the search query and a list of key terms, wherein the key terms each comprise a term in the search query or a term related to one of the terms in the search query; an inverted index comprising a set of key terms each associated with a semantic representation for each of a plurality of passages comprising a plurality of substructures and further associated with a link to a reference document for the passage; a candidate module to identify one or more of the passages as retrieval candidates by comparing the semantic representations associated with the passages with the semantic representation of the search query, comprising: a term selection module to select a subset of the key terms from the search query and to query the inverted index with the key terms in the subset; a result module to identify within the inverted index a result set for each of the key terms in the subset; and a scoring module to score each of the results in the set based on a distance of relationships of the substructures in the semantic representation of the search query and the semantic representation of the passages and to identify a subset of the result sets as the retrieval candidates based on the scoring; and a candidate selection module to select one or more of the retrieval candidates based on a comparison of the semantic representation of the search query with the semantic representations for each of the retrieval candidates, wherein the modules are executed via a computer processor. 3. A system according to claim 1 , comprising: a refinement module to refine the identification of the retrieval candidates based upon one or more heuristically tuned thresholds. | 0.761394 |
8,468,122 | 38 | 40 | 38. A system for responding to a query initiated at a user device, comprising: one or more data stores having a knowledge base stored therein that includes data representing first knowledge about a plurality of objects using a plurality of relationships among the objects, the knowledge base further having natural language translation objects associated therewith operable to translate between natural language and syntax associated with the knowledge base; and one or more computing devices configured to generate a response to the query using at least one of the natural language translation objects and second knowledge not statically stored or represented in the at least one knowledge base prior to receipt of the query, the second knowledge being generated by inference from the first knowledge in response to the query, the inference including retrieving one or more first facts included in the first knowledge, the first facts corresponding to first ones of the objects and first ones of the relationships, and generating one or more second facts from the first facts that express at least one new relationship for at least one of the one or more first objects. | 38. A system for responding to a query initiated at a user device, comprising: one or more data stores having a knowledge base stored therein that includes data representing first knowledge about a plurality of objects using a plurality of relationships among the objects, the knowledge base further having natural language translation objects associated therewith operable to translate between natural language and syntax associated with the knowledge base; and one or more computing devices configured to generate a response to the query using at least one of the natural language translation objects and second knowledge not statically stored or represented in the at least one knowledge base prior to receipt of the query, the second knowledge being generated by inference from the first knowledge in response to the query, the inference including retrieving one or more first facts included in the first knowledge, the first facts corresponding to first ones of the objects and first ones of the relationships, and generating one or more second facts from the first facts that express at least one new relationship for at least one of the one or more first objects. 40. The system of claim 38 wherein the one or more computing devices are configured to use the at least one natural translation object to translate a natural language question corresponding to the query by generation of at least one sub-string from a string of text corresponding to the natural language question, and selection of at least one of a plurality of query template components corresponding to the at least one sub-string. | 0.712483 |
9,535,953 | 8 | 9 | 8. The method of claim 7 , further comprising: executing the at least two different query plans on the relational database; and providing runtime statistics that include a resource cost of execution for each of the at least two different query plans. | 8. The method of claim 7 , further comprising: executing the at least two different query plans on the relational database; and providing runtime statistics that include a resource cost of execution for each of the at least two different query plans. 9. The method of claim 8 , further comprising updating runtime statistics of the query record based on the provided runtime statistics. | 0.963573 |
9,218,530 | 20 | 29 | 20. A method comprising the acts: performing a digital watermark decoding or audio fingerprinting operation on received audio data to generate content identification data, said audio data representing samples of audio content for rendering into human-perceptible sound; identifying a first context factor of a first context class, said first context class being selected from the list consisting of (a) computing context; (b) user context; (c) physical context; (d) temporal context; and (e) historical information about any of (a)-(d); identifying a second context factor of a second context class, said second class being selected from said list and being different than the first context class; selecting software for rendering said audio data, based on circumstances including (i) the content identification data; (ii) the first context factor; and (iii) the second context factor; and rendering the received audio data to a user with said selected software; wherein at least one of said acts is performed using a mobile computing apparatus that includes a microphone and a camera. | 20. A method comprising the acts: performing a digital watermark decoding or audio fingerprinting operation on received audio data to generate content identification data, said audio data representing samples of audio content for rendering into human-perceptible sound; identifying a first context factor of a first context class, said first context class being selected from the list consisting of (a) computing context; (b) user context; (c) physical context; (d) temporal context; and (e) historical information about any of (a)-(d); identifying a second context factor of a second context class, said second class being selected from said list and being different than the first context class; selecting software for rendering said audio data, based on circumstances including (i) the content identification data; (ii) the first context factor; and (iii) the second context factor; and rendering the received audio data to a user with said selected software; wherein at least one of said acts is performed using a mobile computing apparatus that includes a microphone and a camera. 29. The method of claim 20 in which the first factor is of the user context class, and the second factor is of the temporal context class. | 0.655 |
8,190,988 | 4 | 5 | 4. The method of claim 1 wherein the operation of renaming at least one named form field comprises: renaming all named form fields in all of the electronic form instances of the selection to be unique across the selection of electronic form instances. | 4. The method of claim 1 wherein the operation of renaming at least one named form field comprises: renaming all named form fields in all of the electronic form instances of the selection to be unique across the selection of electronic form instances. 5. The method of claim 4 wherein the operation of renaming one or more references to the named form field comprises: renaming all references to the named form fields in the at least one script in all of the electronic form instances of the selection to match the renamed form fields. | 0.865622 |
9,361,381 | 8 | 10 | 8. A system, comprising: a data storage device; and one or more data processing apparatus that interact with the data storage device and execute instructions that cause the one or more data processing apparatus to perform operations comprising: determining, for a prefix that represents a portion of a search query, one or more completions that yield a completed search query when combined with the prefix; identifying one or more content items for the one or more completions; receiving, through a search engine input field presented at a user device, user input including the prefix; identifying, based on the user input, the one or more content items for the one or more completions; determining, based at least in part on display specifications of the user device, a visual format for a given content item from the one or more identified content items, wherein a first visual format presents a Uniform Resource Locator (URL) on a same line as other information in the given content item, and a second visual format presents the URL on a different line than the other information; and providing, prior to a completed search query being specified by the user input, the given content item with instructions that cause the given content item to be presented according to the determined visual format and at a display location corresponding to the one or more completions for which the given content item was identified. | 8. A system, comprising: a data storage device; and one or more data processing apparatus that interact with the data storage device and execute instructions that cause the one or more data processing apparatus to perform operations comprising: determining, for a prefix that represents a portion of a search query, one or more completions that yield a completed search query when combined with the prefix; identifying one or more content items for the one or more completions; receiving, through a search engine input field presented at a user device, user input including the prefix; identifying, based on the user input, the one or more content items for the one or more completions; determining, based at least in part on display specifications of the user device, a visual format for a given content item from the one or more identified content items, wherein a first visual format presents a Uniform Resource Locator (URL) on a same line as other information in the given content item, and a second visual format presents the URL on a different line than the other information; and providing, prior to a completed search query being specified by the user input, the given content item with instructions that cause the given content item to be presented according to the determined visual format and at a display location corresponding to the one or more completions for which the given content item was identified. 10. The system of claim 8 , wherein determining one or more completions that yield a completed search query when combined with the prefix comprises identifying the one or more completions based, at least in part, on a frequency of previously performed searches that included the one or more completions. | 0.501645 |
8,050,503 | 1 | 8 | 1. A system for computer vision, the system including: a plurality of images; a signature processor of at least one processing device adapted to generate a signature based at least in part on a curvelet transform, the signature including a portion of a plurality of curvelet coefficients of the curvelet transform that is significant, wherein the signature is a vector of real numbers with a length less than a number of corresponding image pixels; and a matching processor of the at least one processing device adapted to receive a query image, wherein the matching processor is adapted to determine a query signature for the query image using the signature processor, and wherein the matching processor is adapted to determine at least one matching image from the plurality of images based at least in part on the query signature. | 1. A system for computer vision, the system including: a plurality of images; a signature processor of at least one processing device adapted to generate a signature based at least in part on a curvelet transform, the signature including a portion of a plurality of curvelet coefficients of the curvelet transform that is significant, wherein the signature is a vector of real numbers with a length less than a number of corresponding image pixels; and a matching processor of the at least one processing device adapted to receive a query image, wherein the matching processor is adapted to determine a query signature for the query image using the signature processor, and wherein the matching processor is adapted to determine at least one matching image from the plurality of images based at least in part on the query signature. 8. The system of claim 1 , wherein the query image is an object to be identified. | 0.964783 |
8,145,655 | 14 | 17 | 14. A system in communication with a database, comprising: a computer readable storage medium; a compiler executed to perform operations, the operations comprising: translating source code including at least one query statement written in a database query language into executable object code in the computer readable storage medium; and generating a statement descriptor data structure in the object code including statement descriptor information for the translated at least one query statement including information on the at least one query statement as presented in the source code; and a monitor application executed to perform operations comprising—executing the object code to cause execution of the at least one query statement; accessing the statement descriptor information in the statement descriptor data structure in the object code for the at least one executed query statement; and processing the accessed statement descriptor in to output information on the at least one query statement included in the statement descriptor information. | 14. A system in communication with a database, comprising: a computer readable storage medium; a compiler executed to perform operations, the operations comprising: translating source code including at least one query statement written in a database query language into executable object code in the computer readable storage medium; and generating a statement descriptor data structure in the object code including statement descriptor information for the translated at least one query statement including information on the at least one query statement as presented in the source code; and a monitor application executed to perform operations comprising—executing the object code to cause execution of the at least one query statement; accessing the statement descriptor information in the statement descriptor data structure in the object code for the at least one executed query statement; and processing the accessed statement descriptor in to output information on the at least one query statement included in the statement descriptor information. 17. The system of claim 14 , wherein the operations further comprise: modifying the at least one query statement in the source code to produce at least one modified query statement; including the at least one modified query statement in the statement descriptor information; and translating the at least one modified query statement into the executable object code. | 0.607527 |
9,792,377 | 1 | 3 | 1. A method of determining sentiment trend visualization for localized events, the method being implemented on a system comprising a physical processor executing machine readable instructions, comprising: identifying, based on disseminated information from a first geographic region, an event occurring in the first geographic region, wherein the disseminated information from the first geographic region includes public commentary from the first geographic region; identifying a set of attributes that are related to the event; extracting a set of sentiment words relating to the identified event from the disseminated information, wherein the extracted set of sentiment words are in a local language of the first geographic region; and causing display, for a first attribute of the identified set of attributes, of a sentiment trend visualization that depicts a trend of determined sentiments for the first attribute, wherein the determined sentiments are based on the set of sentiment words for the first attribute. | 1. A method of determining sentiment trend visualization for localized events, the method being implemented on a system comprising a physical processor executing machine readable instructions, comprising: identifying, based on disseminated information from a first geographic region, an event occurring in the first geographic region, wherein the disseminated information from the first geographic region includes public commentary from the first geographic region; identifying a set of attributes that are related to the event; extracting a set of sentiment words relating to the identified event from the disseminated information, wherein the extracted set of sentiment words are in a local language of the first geographic region; and causing display, for a first attribute of the identified set of attributes, of a sentiment trend visualization that depicts a trend of determined sentiments for the first attribute, wherein the determined sentiments are based on the set of sentiment words for the first attribute. 3. The method of claim 1 , wherein the sentiment trend visualization depicts the trend of determined sentiments for the first attribute over a time period. | 0.905603 |
7,676,680 | 1 | 10 | 1. A computer assisted method of providing a private placement document to a potential investor in a private placement, the method comprising: generating the private placement document in an encrypted electronic format with a computer system comprising at least one processor and operatively associated memory, wherein generating the private placement document includes labeling the private placement document with a unique identifier and wherein the private placement document comprises a subscription document; providing the private placement document to the potential investor electronically with the computer system, wherein the subscription document is programmed to: (i) prompt the potential investor to enter information relating to the potential investor into the subscription document; (ii) conditioned upon the potential investor declining to enter the information relating to the potential investor into the subscription document, rendering the private placement document unreadable by the potential investor; (iii) conditioned upon the information relating to the potential investor failing to meet a pre-determined qualification standard, rendering the private placement document unreadable by the potential investor; and (iv) conditioned upon the potential investor failing to enter the information relating to the potential investor into the subscription document within a predetermined amount of time, rendering the private placement document unreadable by the potential investor; recording the unique identifier at a database in communication with the computer system, wherein the unique identifier is recorded at the database in association with the potential investor; electronically receiving the subscription document from the potential investor with the computer system, wherein the subscription document, when received from the potential investor, comprises the information relating to the potential investor; and verifying with the computer system that the information relating to the potential investor is correctly entered into the subscription document. | 1. A computer assisted method of providing a private placement document to a potential investor in a private placement, the method comprising: generating the private placement document in an encrypted electronic format with a computer system comprising at least one processor and operatively associated memory, wherein generating the private placement document includes labeling the private placement document with a unique identifier and wherein the private placement document comprises a subscription document; providing the private placement document to the potential investor electronically with the computer system, wherein the subscription document is programmed to: (i) prompt the potential investor to enter information relating to the potential investor into the subscription document; (ii) conditioned upon the potential investor declining to enter the information relating to the potential investor into the subscription document, rendering the private placement document unreadable by the potential investor; (iii) conditioned upon the information relating to the potential investor failing to meet a pre-determined qualification standard, rendering the private placement document unreadable by the potential investor; and (iv) conditioned upon the potential investor failing to enter the information relating to the potential investor into the subscription document within a predetermined amount of time, rendering the private placement document unreadable by the potential investor; recording the unique identifier at a database in communication with the computer system, wherein the unique identifier is recorded at the database in association with the potential investor; electronically receiving the subscription document from the potential investor with the computer system, wherein the subscription document, when received from the potential investor, comprises the information relating to the potential investor; and verifying with the computer system that the information relating to the potential investor is correctly entered into the subscription document. 10. The method of claim 1 , wherein the unique identifier is included on each page of the private placement document. | 0.848837 |
7,599,838 | 11 | 16 | 11. A system, comprising: a speech animation server; and a client application in communication with the speech animation server, wherein the client application is operable to perform the following operations: sending a request for speech animation to the speech animation server, the request identifying data to be used to generate the speech animation, the speech animation being speech synchronized with facial expressions; receiving a response from the speech animation engine, the response identifying the generated speech animation; and using the generated speech animation to animate a talking agent displayed on a user interface of the client application; and wherein the speech animation server is operable to perform the following operations: receiving the request for speech animation from the client application; retrieving the data identified in the request, wherein the retrieved data includes a tag having a parameter corresponding to a desired emotion and a reference to an application scenario of the requesting client application, the application scenario corresponding to a behavioral context that includes a set of expressions that are appropriate to the particular application scenario; determining which application scenario prompted the request based on other data information included in the first request; generating the speech animation based on the parameter using the retrieved data and further using the set of expressions defined in the behavioral context; and sending the response identifying the generated speech animation to the client application. | 11. A system, comprising: a speech animation server; and a client application in communication with the speech animation server, wherein the client application is operable to perform the following operations: sending a request for speech animation to the speech animation server, the request identifying data to be used to generate the speech animation, the speech animation being speech synchronized with facial expressions; receiving a response from the speech animation engine, the response identifying the generated speech animation; and using the generated speech animation to animate a talking agent displayed on a user interface of the client application; and wherein the speech animation server is operable to perform the following operations: receiving the request for speech animation from the client application; retrieving the data identified in the request, wherein the retrieved data includes a tag having a parameter corresponding to a desired emotion and a reference to an application scenario of the requesting client application, the application scenario corresponding to a behavioral context that includes a set of expressions that are appropriate to the particular application scenario; determining which application scenario prompted the request based on other data information included in the first request; generating the speech animation based on the parameter using the retrieved data and further using the set of expressions defined in the behavioral context; and sending the response identifying the generated speech animation to the client application. 16. The system of claim 11 , wherein the data specifies a pool of synonyms; and generating the speech animation includes selecting a synonym from the pool of synonyms. | 0.680077 |
8,909,639 | 16 | 23 | 16. A memory device having instructions stored thereon that, in response to execution by a processing device, cause the processing device to perform operations comprising: identifying, on a target digital page of a network accessible site, an occurrence of a key phase selected for providing contextually relevant content, the key phrase selected based at least in part on frequency of the key phrase on a peer group of digital pages associated with the target digital page and social media popularity of the key phrase, the peer group of digital pages of a plurality of network accessible sites; identifying said peer group of digital pages, at least in part, by identifying at least one of an outbound link from or an inbound link to the target digital page; wherein social media popularity of the key phrase is determined by monitoring interaction, by users of a social media service, with a social media content item that is associated with the key phrase; and transforming the occurrence of the key phrase into a user-selectable display element that is configured to initiate a display of the contextually relevant content in a panel on the target digital electronic page in response to actuation of the user-selectable display element. | 16. A memory device having instructions stored thereon that, in response to execution by a processing device, cause the processing device to perform operations comprising: identifying, on a target digital page of a network accessible site, an occurrence of a key phase selected for providing contextually relevant content, the key phrase selected based at least in part on frequency of the key phrase on a peer group of digital pages associated with the target digital page and social media popularity of the key phrase, the peer group of digital pages of a plurality of network accessible sites; identifying said peer group of digital pages, at least in part, by identifying at least one of an outbound link from or an inbound link to the target digital page; wherein social media popularity of the key phrase is determined by monitoring interaction, by users of a social media service, with a social media content item that is associated with the key phrase; and transforming the occurrence of the key phrase into a user-selectable display element that is configured to initiate a display of the contextually relevant content in a panel on the target digital electronic page in response to actuation of the user-selectable display element. 23. The memory device of claim 16 , wherein the target digital page is associated with a first domain, and wherein at least one of the digital pages of the peer group is associated with a second domain that is different than the first domain. | 0.50813 |
9,082,409 | 1 | 4 | 1. A method for executing voice applications to perform a voice-based function, the method comprising: receiving a first request for a document; retrieving the document in response to the first request; parsing the document to create a parse tree, the parse tree including an XML node; creating script code from the parse tree; translating the script code to bytecode segments; replacing the XML node with script code, thereby consuming part of the parse tree to create a reduced parse tree; storing the reduced parse tree in a cache for subsequent retrieval in response to a second request for the document, the reduced parse tree configured for use to perform the voice-based function; storing the bytecode segments in a cache for subsequent execution to perform the voice-based function receiving the second request to retrieve the document: in response to the second request, determining whether bytecode corresponding to the document is stored in a cache; and responsive to determining that bytecode corresponding to the document is already stored in the cache: bypassing the retrieving, parsing, creating, replacing, translating and storing steps associated with the second request; and executing the cached bytecode. | 1. A method for executing voice applications to perform a voice-based function, the method comprising: receiving a first request for a document; retrieving the document in response to the first request; parsing the document to create a parse tree, the parse tree including an XML node; creating script code from the parse tree; translating the script code to bytecode segments; replacing the XML node with script code, thereby consuming part of the parse tree to create a reduced parse tree; storing the reduced parse tree in a cache for subsequent retrieval in response to a second request for the document, the reduced parse tree configured for use to perform the voice-based function; storing the bytecode segments in a cache for subsequent execution to perform the voice-based function receiving the second request to retrieve the document: in response to the second request, determining whether bytecode corresponding to the document is stored in a cache; and responsive to determining that bytecode corresponding to the document is already stored in the cache: bypassing the retrieving, parsing, creating, replacing, translating and storing steps associated with the second request; and executing the cached bytecode. 4. The method of claim 1 , further comprising: in response to the second request, determining whether a reduced parse tree corresponding to the document is already stored in a cache; and responsive to determining that a reduced parse tree corresponding to the document is already stored in a cache: translating the script code to bytecode segments; and executing the cached bytecode segments. | 0.687898 |
8,812,593 | 12 | 13 | 12. The system of claim 11 , wherein content comprises an element related to a community topic and wherein the community engine is further adapted to: create a second user profile for a second user, the second user profile comprising a first user level, the first user level allowing the second user to access a first set of community tools; and wherein detect user activity comprises: receive element attributes associated with the element, the element attributes comprising a comment from the second user, a rating, and a label identifying a sub-topic of the community topic. | 12. The system of claim 11 , wherein content comprises an element related to a community topic and wherein the community engine is further adapted to: create a second user profile for a second user, the second user profile comprising a first user level, the first user level allowing the second user to access a first set of community tools; and wherein detect user activity comprises: receive element attributes associated with the element, the element attributes comprising a comment from the second user, a rating, and a label identifying a sub-topic of the community topic. 13. The system of claim 12 , wherein the community engine is further adapted to: determine points to award to the second user based on approval of the comment by the moderator. | 0.937098 |
5,555,343 | 5 | 8 | 5. A text processor according to claim 1, further comprising a look-up table, wherein said text generator generates text in accordance with said look-up table. | 5. A text processor according to claim 1, further comprising a look-up table, wherein said text generator generates text in accordance with said look-up table. 8. A text processor according to claim 5, wherein the look-up table is comprised by pre-designated text associated with punctuation and arithmetic symbols. | 0.939922 |
9,069,750 | 1 | 12 | 1. A computer-implemented method for facilitating a semantic search based on one or more previously analyzed and indexed corpuses of natural language texts, the method comprising: identifying the one or more previously analyzed and indexed corpuses of natural language texts, each corpus including a plurality of sentences and indexes where indexes include indexes of meanings of linguistic parameters of the sentences and of their lexical units and their relations; wherein the linguistic parameters comprise parameters determined based on syntactico-semantic analysis of at least one sentence in the corpuses; and the syntactico-semantic analysis of the at least one sentence comprises performing a rough syntactic analysis of the at least one sentence generating a graph of generalized constituents of the at least one sentence; performing a precise syntactic analysis on the graph of generalized constituents by generating one or more syntactic trees and determining a syntactic structure of the at least one sentence, wherein the performing of the precise syntactic analysis comprises assessing parts of the one or more syntactic trees using prior and statistical ratings, and generating the one or more syntactic trees in an order of decreasing assessment; semantically analyzing the syntactic structure of the sentence generating a language-independent semantic structure of the at least one sentence; and generating one or more of the parameters based on the language-independent semantic structure of the at least one sentence; creating a query for searching sentences satisfying the query; searching for sentences of the previously analyzed and indexed corpuses satisfying the query; and displaying the sentences satisfying the query. | 1. A computer-implemented method for facilitating a semantic search based on one or more previously analyzed and indexed corpuses of natural language texts, the method comprising: identifying the one or more previously analyzed and indexed corpuses of natural language texts, each corpus including a plurality of sentences and indexes where indexes include indexes of meanings of linguistic parameters of the sentences and of their lexical units and their relations; wherein the linguistic parameters comprise parameters determined based on syntactico-semantic analysis of at least one sentence in the corpuses; and the syntactico-semantic analysis of the at least one sentence comprises performing a rough syntactic analysis of the at least one sentence generating a graph of generalized constituents of the at least one sentence; performing a precise syntactic analysis on the graph of generalized constituents by generating one or more syntactic trees and determining a syntactic structure of the at least one sentence, wherein the performing of the precise syntactic analysis comprises assessing parts of the one or more syntactic trees using prior and statistical ratings, and generating the one or more syntactic trees in an order of decreasing assessment; semantically analyzing the syntactic structure of the sentence generating a language-independent semantic structure of the at least one sentence; and generating one or more of the parameters based on the language-independent semantic structure of the at least one sentence; creating a query for searching sentences satisfying the query; searching for sentences of the previously analyzed and indexed corpuses satisfying the query; and displaying the sentences satisfying the query. 12. The method of claim 1 , wherein the query for searching is expressed in a natural language with requested parameters, a part of which may be not defined, or may be defined by means of variables, or may be defined as a range of meanings of these variables. | 0.700924 |
10,114,900 | 16 | 17 | 16. A method for searching probabilistically searchable messages, the method comprising: obtaining, by a computing device, a textual query; extracting, by the computing device, from the textual query, at least one word; cryptographically hashing, by the computing device, the at least one word; mapping, by the computing device, the cryptographically hashed at least one word to a plurality of tokens; generating, by the computing device, a set of tokens associated with the textual query, the set of tokens including each plurality of tokens associated with each cryptographically hashed word; and receiving, by the computing device, from a search engine, at least one textual message including metadata comprising the set of tokens. | 16. A method for searching probabilistically searchable messages, the method comprising: obtaining, by a computing device, a textual query; extracting, by the computing device, from the textual query, at least one word; cryptographically hashing, by the computing device, the at least one word; mapping, by the computing device, the cryptographically hashed at least one word to a plurality of tokens; generating, by the computing device, a set of tokens associated with the textual query, the set of tokens including each plurality of tokens associated with each cryptographically hashed word; and receiving, by the computing device, from a search engine, at least one textual message including metadata comprising the set of tokens. 17. The method of claim 16 , wherein cryptographically hashing further comprises hashing each word using a key hash function. | 0.920584 |
7,610,546 | 14 | 16 | 14. A document processing method comprising: detecting video data designation information attached to electronic document data, the electronic document data including: (i) a first element having a first central activation value used to generate an index; (ii) a second element having a second central activation value used to generate said index; and (iii) read out audio attribute information; generating a summary of said electronic document data, wherein said generation of said summary includes spreading said first central activation value to said second central activation value; selecting video data in accordance with said detected video data designation information; storing a categorization model including a plurality of data categories; creating an automatic categorization based on any one of said video data and electronic document data in accordance with the categorization model; updating the categorization model with the automatic categorization; controlling an output of said summary of said electronic document data such that said summary of said electronic data being output is automatically progressed based on at least one of a size of a display area and a length of time displayed; controlling an output of said selected video data in correspondence with the output of said summary of said electronic document data such that said selected video data being output is output in synchronization with said progress of the said operation of outputting said summary of said electronic data; controlling an output of a read out audio based on read out audio attribute information in said electronic document to synthesize said read out audio; and automatically terminate the output of said video data upon completion of the outputting of said summary of said electronic document data regardless of whether an end of the video data has been reached. | 14. A document processing method comprising: detecting video data designation information attached to electronic document data, the electronic document data including: (i) a first element having a first central activation value used to generate an index; (ii) a second element having a second central activation value used to generate said index; and (iii) read out audio attribute information; generating a summary of said electronic document data, wherein said generation of said summary includes spreading said first central activation value to said second central activation value; selecting video data in accordance with said detected video data designation information; storing a categorization model including a plurality of data categories; creating an automatic categorization based on any one of said video data and electronic document data in accordance with the categorization model; updating the categorization model with the automatic categorization; controlling an output of said summary of said electronic document data such that said summary of said electronic data being output is automatically progressed based on at least one of a size of a display area and a length of time displayed; controlling an output of said selected video data in correspondence with the output of said summary of said electronic document data such that said selected video data being output is output in synchronization with said progress of the said operation of outputting said summary of said electronic data; controlling an output of a read out audio based on read out audio attribute information in said electronic document to synthesize said read out audio; and automatically terminate the output of said video data upon completion of the outputting of said summary of said electronic document data regardless of whether an end of the video data has been reached. 16. The document processing method of claim 14 , wherein said video data designation information is attached in the form of tag data to said electronic document. | 0.882824 |
7,685,620 | 11 | 17 | 11. A computer readable memory for causing a computer to identify a real-time television signal of interest to a user, comprising: a computer readable memory; a computer program stored in the computer readable memory; the computer readable memory so configured by the computer program, causes a logical unit to perform a plurality of steps comprising: receiving a search parameter entered by a user into the logical unit; simultaneously buffering a plurality of audio voice streams of a plurality of real-time television signals in a plurality of languages; translating the plurality of audio voice streams into text associated with each of the plurality of real-time television signals in the plurality of languages; buffering the text into a lexical buffer; searching the lexical buffer for the search parameter; displaying a list of the plurality of real-time television signals in the plurality of languages in order of relevance to the search parameter; and the user selecting a first real-time television signal from the list, whereby the first real-time television signal is displayed on a television in real-time; wherein the user specifies the plurality of real-time television signals, an amount of buffering time to be allocated for each of the plurality of real-time television signals, and a plurality of time periods for each of the plurality of real-time television signals to be buffered. | 11. A computer readable memory for causing a computer to identify a real-time television signal of interest to a user, comprising: a computer readable memory; a computer program stored in the computer readable memory; the computer readable memory so configured by the computer program, causes a logical unit to perform a plurality of steps comprising: receiving a search parameter entered by a user into the logical unit; simultaneously buffering a plurality of audio voice streams of a plurality of real-time television signals in a plurality of languages; translating the plurality of audio voice streams into text associated with each of the plurality of real-time television signals in the plurality of languages; buffering the text into a lexical buffer; searching the lexical buffer for the search parameter; displaying a list of the plurality of real-time television signals in the plurality of languages in order of relevance to the search parameter; and the user selecting a first real-time television signal from the list, whereby the first real-time television signal is displayed on a television in real-time; wherein the user specifies the plurality of real-time television signals, an amount of buffering time to be allocated for each of the plurality of real-time television signals, and a plurality of time periods for each of the plurality of real-time television signals to be buffered. 17. The computer readable memory of claim 11 further comprising comparing the search parameter to a dictionary. | 0.653125 |
9,824,313 | 9 | 16 | 9. A computer program product for determining compliance of content with a content policy, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: receiving a content item comprising text and one or more images; extracting a plurality of text signals from the text; extracting a plurality of image signals from the one or more images; inputting the plurality of text signals and the plurality of image signals into a two-tier classifier system by inputting the plurality of text signals into a text classifier model of a first tier of the two-tier classifier system, inputting the plurality of image signals into an image classifier model of the first tier of the two tier-classifier system, and inputting output classifications of the text classifier model and of the image classifier model into a second-tier classifier model, the second-tier classifier outputting a confidence value expressing likelihood of compliance with a content policy of an online system; comparing the confidence value against a pre-defined threshold value; and based on the comparison, assigning a compliance classification to the content item. | 9. A computer program product for determining compliance of content with a content policy, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: receiving a content item comprising text and one or more images; extracting a plurality of text signals from the text; extracting a plurality of image signals from the one or more images; inputting the plurality of text signals and the plurality of image signals into a two-tier classifier system by inputting the plurality of text signals into a text classifier model of a first tier of the two-tier classifier system, inputting the plurality of image signals into an image classifier model of the first tier of the two tier-classifier system, and inputting output classifications of the text classifier model and of the image classifier model into a second-tier classifier model, the second-tier classifier outputting a confidence value expressing likelihood of compliance with a content policy of an online system; comparing the confidence value against a pre-defined threshold value; and based on the comparison, assigning a compliance classification to the content item. 16. The computer program product of claim 9 , further comprising: responsive to the compliance classification determined for the content item indicating a likelihood of violating the content policy, performing at least one remedial action of: blocking the content item from being transmitted or displayed to a user, passing the content item to a human controller for manual review, and marking the content item with a tag. | 0.501182 |
9,785,452 | 1 | 7 | 1. A method, comprising: intercepting, at a client during execution of an application at a browser on the client, a JavaScript call, wherein a source code of the application indicates a timed sequence of execution of JavaScript files, wherein the JavaScript files comprise a first JavaScript file loaded into the client's memory element simultaneously with loading the application, a second JavaScript file having a dependency on the first JavaScript file and called during the timed sequence after the first JavaScript file is called, and a third JavaScript file not called after a certain duration of the timed sequence; accessing, by the client, a map file stored at a server upon intercepting the JavaScript call, wherein the map file is generated automatically at the server before execution of the application on the client, wherein the map file includes a dependency tree comprising the JavaScript files used in the source code, wherein the first JavaScript file is specified in an exclusion file, wherein the map file maps the second JavaScript file for lazy loading, wherein the map file maps Cascading Style Sheets (CSS) files with related map for class names to be used on the application; reverse mapping from the map file, at the client during runtime of the application, particular JavaScript files corresponding the JavaScript call, wherein the reverse mapping comprises checking the JavaScript call for dependency resolution according to the map file, wherein a resolution scope of lazily loaded files ends with first-level dependencies of such files, wherein the particular JavaScript files are selected for loading according to the dependency resolution; loading the particular JavaScript files from the server into the client's memory element according to the exclusion file and the map file, wherein the loading comprises loading the first JavaScript file according to the exclusion file, lazy loading the second JavaScript file asynchronously with timestamp according to the map file, and reverse mapping relevant CSS files in the loaded files using related class names from the map file; and deleting, during application execution, the third JavaScript file from the client's memory element after the certain duration of the timed sequence. | 1. A method, comprising: intercepting, at a client during execution of an application at a browser on the client, a JavaScript call, wherein a source code of the application indicates a timed sequence of execution of JavaScript files, wherein the JavaScript files comprise a first JavaScript file loaded into the client's memory element simultaneously with loading the application, a second JavaScript file having a dependency on the first JavaScript file and called during the timed sequence after the first JavaScript file is called, and a third JavaScript file not called after a certain duration of the timed sequence; accessing, by the client, a map file stored at a server upon intercepting the JavaScript call, wherein the map file is generated automatically at the server before execution of the application on the client, wherein the map file includes a dependency tree comprising the JavaScript files used in the source code, wherein the first JavaScript file is specified in an exclusion file, wherein the map file maps the second JavaScript file for lazy loading, wherein the map file maps Cascading Style Sheets (CSS) files with related map for class names to be used on the application; reverse mapping from the map file, at the client during runtime of the application, particular JavaScript files corresponding the JavaScript call, wherein the reverse mapping comprises checking the JavaScript call for dependency resolution according to the map file, wherein a resolution scope of lazily loaded files ends with first-level dependencies of such files, wherein the particular JavaScript files are selected for loading according to the dependency resolution; loading the particular JavaScript files from the server into the client's memory element according to the exclusion file and the map file, wherein the loading comprises loading the first JavaScript file according to the exclusion file, lazy loading the second JavaScript file asynchronously with timestamp according to the map file, and reverse mapping relevant CSS files in the loaded files using related class names from the map file; and deleting, during application execution, the third JavaScript file from the client's memory element after the certain duration of the timed sequence. 7. The method of claim 1 , further comprising: checking the JavaScript call for dependency resolution according to the map file, wherein the map file specifies a first set of dependent JavaScript files to be lazily loaded and a second set of dependent JavaScript files to be loaded during initial application load; lazily loading the first set of dependent JavaScript file; and loading the second set of dependent JavaScript file during initial application load. | 0.667626 |
9,436,287 | 21 | 22 | 21. The method of claim 18 , wherein processing the audio waveform in the second mode comprises correlating the audio waveform with a meaning that is different from a first meaning corresponding to the first mode. | 21. The method of claim 18 , wherein processing the audio waveform in the second mode comprises correlating the audio waveform with a meaning that is different from a first meaning corresponding to the first mode. 22. The method of claim 21 , wherein the meaning that is different from the first meaning comprises at least one of a command, a punctuation mark, or an action. | 0.954853 |
8,719,262 | 14 | 16 | 14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. | 14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. 16. The system of claim 14 , where the server is further to: receive the query via a network, and where, when identifying the documents, the server is to: identify the documents relating to the query by matching individual search terms in the query to an index of a corpus that includes a collection of web documents. | 0.72813 |
7,505,906 | 1 | 3 | 1. A method of performing automatic speech recognition, the method comprising: determining whether a user's utterances relate to one of a plurality of corpora of data having modified probabilities of certain words; if the user's utterances relate to one of the plurality of corpora of data, selecting the related corpora of data for use in speech recognition; receiving speech from a user, the speech including at least one speech error; and using the selected corpora of data having modified the probabilities to process the received speech to increase the probability of correctly interpreting the received speech with the at least one speech error. | 1. A method of performing automatic speech recognition, the method comprising: determining whether a user's utterances relate to one of a plurality of corpora of data having modified probabilities of certain words; if the user's utterances relate to one of the plurality of corpora of data, selecting the related corpora of data for use in speech recognition; receiving speech from a user, the speech including at least one speech error; and using the selected corpora of data having modified the probabilities to process the received speech to increase the probability of correctly interpreting the received speech with the at least one speech error. 3. The method of claim 1 , wherein the speech error comprises a plurality of error words, and the corpora of data relates to pluralities of words that are closely related in sound to the plurality of error words. | 0.53913 |
8,037,047 | 1 | 6 | 1. A method comprising: recognizing, via a computing device, at least a portion of an instant message entered into an instant messaging window on a first client computer as an inline search query, wherein the search query is communicated to a second client computer for display inline in an instant messaging window on the second client computer, wherein said recognizing comprises identifying a character string in the instant message as a search trigger; and causing, via the computing device, visible display of at least one search result inline in the instant messaging window on the first client computer and inline in the instant messaging window on the second client computer, the at least one search result from a search based on the search query. | 1. A method comprising: recognizing, via a computing device, at least a portion of an instant message entered into an instant messaging window on a first client computer as an inline search query, wherein the search query is communicated to a second client computer for display inline in an instant messaging window on the second client computer, wherein said recognizing comprises identifying a character string in the instant message as a search trigger; and causing, via the computing device, visible display of at least one search result inline in the instant messaging window on the first client computer and inline in the instant messaging window on the second client computer, the at least one search result from a search based on the search query. 6. The method according to claim 1 , wherein causing the display of at least one search result further comprises selecting a link to a sponsor web site from among the search results. | 0.763636 |
9,250,711 | 12 | 13 | 12. The device of claim 9 , wherein the processor is further structured to make a determination that a final set of characters of the potential artificial variant corresponds with an N-gram object associated with a frequency object having a frequency value above a predetermined threshold. | 12. The device of claim 9 , wherein the processor is further structured to make a determination that a final set of characters of the potential artificial variant corresponds with an N-gram object associated with a frequency object having a frequency value above a predetermined threshold. 13. The device of claim 12 , wherein the N-gram object, and the final set of characters of the potential artificial variant comprises three characters. | 0.951788 |
5,555,343 | 14 | 15 | 14. A text processor according to claim 13, wherein said look-up table is comprised by speech commands associated with text mark-up codes. | 14. A text processor according to claim 13, wherein said look-up table is comprised by speech commands associated with text mark-up codes. 15. A text processor according to claim 14, wherein said table is further comprised by pre-designated text associated with text mark-up codes, said text generator generating text in response to the pre-designated text in the look-up table. | 0.908848 |
8,103,677 | 1 | 7 | 1. A computer-implemented method for searching, comprising: identifying one or more matching objects matching one or more terms of a search request in a search index; executing one or more return path methods associated with each of the one or more matching objects; wherein each of the one or more return path methods traverses an object tree and returns a parent object, wherein the parent object is added to a list of search result parent objects, wherein the data associated with the parent object is stored along with modification dates, wherein the search request further comprises an evaluation date; and wherein the parent object is stored with one or more effective dates, wherein each effective date comprises a past, present or future date; and wherein an effective state of the parent object is determined at the evaluation date by comparing the evaluation date to one or more of the effective dates; ranking the list of search result parent objects according to a ranking function; and providing the ranked list of search result parent objects. | 1. A computer-implemented method for searching, comprising: identifying one or more matching objects matching one or more terms of a search request in a search index; executing one or more return path methods associated with each of the one or more matching objects; wherein each of the one or more return path methods traverses an object tree and returns a parent object, wherein the parent object is added to a list of search result parent objects, wherein the data associated with the parent object is stored along with modification dates, wherein the search request further comprises an evaluation date; and wherein the parent object is stored with one or more effective dates, wherein each effective date comprises a past, present or future date; and wherein an effective state of the parent object is determined at the evaluation date by comparing the evaluation date to one or more of the effective dates; ranking the list of search result parent objects according to a ranking function; and providing the ranked list of search result parent objects. 7. A method as in claim 1 , wherein the one or more return path methods each have an associated weight. | 0.906872 |
9,734,228 | 1 | 2 | 1. A digital analytics system comprising: a data management system including data extraction modules and a data storage system comprising storage units; an analytics engine system hosting and executing a plurality of analytics engines, each associated with a different application, wherein each of the data extraction modules and each of the storage units are assigned to a particular one of the analytics engines and the associated application for the analytics engine, and each of the data extraction modules extracts data from at least one data source and stores the data in the storage unit for the analytics engine or the associated application assigned to the data extraction module, and the storage unit segregates the stored data from data stored in any of the other storage units, and each of the data extraction modules includes translation rules for the assigned analytics engine and the associated application, the translation rules including instructions to re-format and filter the data from the at least one data source prior to storing the data in the storage unit, and to filter the data, the data extraction module receives, from the assigned analytics engine or the associated application, a query for a data set conforming to constraints in the query, runs the query on data from the at least one data source to identify query results from the data, prior to storing the query results in the corresponding storage unit, re-formats the query results according to the translation rules, and stores the re-formatted, query results in the corresponding storage unit, wherein the plurality of analytics engines include: a workforce planning (WFP) analytics engine associated with a WFP application, and an interface for the WFP analytics engine, wherein the interface retrieves sales data from the storage unit for the WFP analytics engine and provides the sales data to the WFP analytics engine, and the WFP analytics engine estimates sales for a future time period based on the sales data, and the WFP application uses the sales estimates to estimate a needed increase or decrease in workforce and interacts with a system of a client to identify and contact a user to provide an indication of the needed increase or decrease in workforce; and a utility plant performance analytics engine, an interface for the utility plant performance analytics engine, and a utility plant performance application, wherein the interface for the utility plant performance analytics engine retrieves data from a predetermined storage unit and provides the data to the utility plant performance analytics engine, the utility plant performance analytics engine estimates a utility plant metric for a future time period based on the data, and the utility plant performance application uses the estimated metric to schedule maintenance for the utility plant, wherein the data comprises maintenance logs for the utility plant, manufacturers' recommended maintenance instructions, and maintenance logs for other utility plants, and the utility plant performance analytics engine estimates when maintenance is due for the utility plant based on the data, and the utility plant performance application provides notification to the client of the estimates for maintenance; and an applications interface and storage storing the applications, wherein the applications are executed using information generated by at least one of prescriptive and descriptive analytics performed by the analytics engines, wherein the data extraction modules further include business intelligence rules including a list of prioritized data sources, wherein the data extraction modules are to determine whether same or similar data is available from multiple data sources, and in response to determining that the same or similar data is available from multiple data sources, the data extraction modules are to use the prioritized list of data sources to accept data from a plurality of the data sources in an order specified in the prioritized list. | 1. A digital analytics system comprising: a data management system including data extraction modules and a data storage system comprising storage units; an analytics engine system hosting and executing a plurality of analytics engines, each associated with a different application, wherein each of the data extraction modules and each of the storage units are assigned to a particular one of the analytics engines and the associated application for the analytics engine, and each of the data extraction modules extracts data from at least one data source and stores the data in the storage unit for the analytics engine or the associated application assigned to the data extraction module, and the storage unit segregates the stored data from data stored in any of the other storage units, and each of the data extraction modules includes translation rules for the assigned analytics engine and the associated application, the translation rules including instructions to re-format and filter the data from the at least one data source prior to storing the data in the storage unit, and to filter the data, the data extraction module receives, from the assigned analytics engine or the associated application, a query for a data set conforming to constraints in the query, runs the query on data from the at least one data source to identify query results from the data, prior to storing the query results in the corresponding storage unit, re-formats the query results according to the translation rules, and stores the re-formatted, query results in the corresponding storage unit, wherein the plurality of analytics engines include: a workforce planning (WFP) analytics engine associated with a WFP application, and an interface for the WFP analytics engine, wherein the interface retrieves sales data from the storage unit for the WFP analytics engine and provides the sales data to the WFP analytics engine, and the WFP analytics engine estimates sales for a future time period based on the sales data, and the WFP application uses the sales estimates to estimate a needed increase or decrease in workforce and interacts with a system of a client to identify and contact a user to provide an indication of the needed increase or decrease in workforce; and a utility plant performance analytics engine, an interface for the utility plant performance analytics engine, and a utility plant performance application, wherein the interface for the utility plant performance analytics engine retrieves data from a predetermined storage unit and provides the data to the utility plant performance analytics engine, the utility plant performance analytics engine estimates a utility plant metric for a future time period based on the data, and the utility plant performance application uses the estimated metric to schedule maintenance for the utility plant, wherein the data comprises maintenance logs for the utility plant, manufacturers' recommended maintenance instructions, and maintenance logs for other utility plants, and the utility plant performance analytics engine estimates when maintenance is due for the utility plant based on the data, and the utility plant performance application provides notification to the client of the estimates for maintenance; and an applications interface and storage storing the applications, wherein the applications are executed using information generated by at least one of prescriptive and descriptive analytics performed by the analytics engines, wherein the data extraction modules further include business intelligence rules including a list of prioritized data sources, wherein the data extraction modules are to determine whether same or similar data is available from multiple data sources, and in response to determining that the same or similar data is available from multiple data sources, the data extraction modules are to use the prioritized list of data sources to accept data from a plurality of the data sources in an order specified in the prioritized list. 2. The digital analytics system of claim 1 , wherein the translations rules specify a new data type for re-formatting the data for storage in the storage units. | 0.656652 |
9,852,130 | 1 | 15 | 1. A method for displaying caption data in a device, the method comprising: receiving content data including video data; if original caption data is included in the content data, performing error checking for the original caption data and generating corrected caption data by correcting one or more errors of the original caption data; extracting one or more high-difficulty words from the corrected caption data; generating explanation data corresponding to each of the one or more high-difficulty words, wherein the explanation data includes data for explaining each of the one or more high-difficulty words; determining at least one special effect corresponding to at least one word included in the original caption data or the explanation data, wherein the at least one special effect includes vibrations, color light, heat, chill, or fragrance corresponding to the at least one word included in the original caption data or the explanation data; and while displaying the video data, simultaneously providing the corrected caption data, the explanation data, and the at least one special effect. | 1. A method for displaying caption data in a device, the method comprising: receiving content data including video data; if original caption data is included in the content data, performing error checking for the original caption data and generating corrected caption data by correcting one or more errors of the original caption data; extracting one or more high-difficulty words from the corrected caption data; generating explanation data corresponding to each of the one or more high-difficulty words, wherein the explanation data includes data for explaining each of the one or more high-difficulty words; determining at least one special effect corresponding to at least one word included in the original caption data or the explanation data, wherein the at least one special effect includes vibrations, color light, heat, chill, or fragrance corresponding to the at least one word included in the original caption data or the explanation data; and while displaying the video data, simultaneously providing the corrected caption data, the explanation data, and the at least one special effect. 15. The method of claim 1 , wherein the one or more errors comprise at least one of a typographical error and a syntax error. | 0.895485 |
7,650,286 | 187 | 188 | 187. The method of claim 180 , wherein the job description comprises a document in an electronic format. | 187. The method of claim 180 , wherein the job description comprises a document in an electronic format. 188. The method of claim 187 , wherein the electronic format includes a standard digital document format. | 0.979815 |
7,975,238 | 23 | 28 | 23. A computer useable medium having stored thereon a computer readable program for tracking bookmarking in received Web documents in a Web communication network with user access via a plurality of data processor controlled interactive receiving display stations for displaying received hypertext documents, transmitted from sources on the Web, including at least one display page containing text, images arid a plurality of embedded hyperlinks. each hyperlink being user selectable to access and display a respective linked hypertext document, wherein the computer readable program when executed on a computer causes the computer to: bookmark, at one of said receiving display stations, selected received Web documents to thereby store, as bookmarks, direct links to the sources of said Web documents; compare said stored bookmarks to hyperlinks in each Web document received at said one display station to determine if said hyperlinks have been bookmarked; and visually distinguish each bookmarked hyperlink in said received displayed Web document. | 23. A computer useable medium having stored thereon a computer readable program for tracking bookmarking in received Web documents in a Web communication network with user access via a plurality of data processor controlled interactive receiving display stations for displaying received hypertext documents, transmitted from sources on the Web, including at least one display page containing text, images arid a plurality of embedded hyperlinks. each hyperlink being user selectable to access and display a respective linked hypertext document, wherein the computer readable program when executed on a computer causes the computer to: bookmark, at one of said receiving display stations, selected received Web documents to thereby store, as bookmarks, direct links to the sources of said Web documents; compare said stored bookmarks to hyperlinks in each Web document received at said one display station to determine if said hyperlinks have been bookmarked; and visually distinguish each bookmarked hyperlink in said received displayed Web document. 28. The computer usable medium of claim 23 , further including a Web browser program, which when executed on a computer causes said computer to: bookmark selected received Web documents to thereby store as bookmarks direct links to the sources of said Web documents; compare said stored bookmarks to hyperlinks in each Web document received at said one display station to determine if said hyperlinks have been bookmarked; and visually distinguish each bookmarked hyperlink in said received displayed Web document. | 0.556131 |
8,799,280 | 4 | 6 | 4. The process of claim 1 , wherein the process action of personalizing results of the search based on knowledge of the identified site or IO comprises the actions of: maintaining a record of the individuals' search or interaction history in the search engine; and displaying aspects of the individuals' search or interaction history record to the individuals. | 4. The process of claim 1 , wherein the process action of personalizing results of the search based on knowledge of the identified site or IO comprises the actions of: maintaining a record of the individuals' search or interaction history in the search engine; and displaying aspects of the individuals' search or interaction history record to the individuals. 6. The process of claim 4 , wherein, the individuals employ either a browser application, or a desktop application other than a browser application, or a mobile application other than a browser application to submit queries to the search engine, and the process action of displaying aspects of the individuals' search or interaction history record to the individuals comprises at least one of the following actions: emphasizing the sites or IOs residing in said record that were most frequently re-visited; or associating said most frequently re-visited sites or IOs with just the most recent query keywords. | 0.911267 |
8,817,028 | 2 | 3 | 2. The computer-implemented method of claim 1 , wherein the user-interface widget comprises a number of divisions, each division designating a respective one of the locations determined for placement of the new dimension annotation, and for the cursor hovering over a given division of the widget, displaying a preview of the rendered arrangement having the new dimension annotation placed in the respective determined location designated by the given division. | 2. The computer-implemented method of claim 1 , wherein the user-interface widget comprises a number of divisions, each division designating a respective one of the locations determined for placement of the new dimension annotation, and for the cursor hovering over a given division of the widget, displaying a preview of the rendered arrangement having the new dimension annotation placed in the respective determined location designated by the given division. 3. The computer-implemented method of claim 2 , wherein the widget is displayed with one division in an active state, and the rendered arrangement corresponds to the one division that is active. | 0.965493 |
9,971,893 | 16 | 17 | 16. The computer system of claim 14 , said method comprising: before said determining that the new text block includes malicious code, said first computer executing the new text block and copying the new text block to an output file in a data storage area. | 16. The computer system of claim 14 , said method comprising: before said determining that the new text block includes malicious code, said first computer executing the new text block and copying the new text block to an output file in a data storage area. 17. The computer system of claim 16 , wherein said determining that the new block includes malicious code comprises: analyzing the new text block on the output fife and at least one text block of the plurality of text blocks to ascertain that the new text block comprises text that (i) is not directly inferred from text appearing in the script and (ii) includes the malicious code. | 0.79958 |
8,554,539 | 16 | 17 | 16. The morpheme analyzer of claim 12 , wherein the morpheme analyzing unit further comprises: a morpheme analysis target analyzing unit configured to analyze the morpheme of the morpheme analysis target by referring to the morpheme dictionary. | 16. The morpheme analyzer of claim 12 , wherein the morpheme analyzing unit further comprises: a morpheme analysis target analyzing unit configured to analyze the morpheme of the morpheme analysis target by referring to the morpheme dictionary. 17. The morpheme analyzer of claim 16 , wherein the morpheme analyzing unit further comprises: a morpheme analysis target adder configured to add the morpheme analysis target to a frequently utilized word list for each category, and increase a number of times that a corresponding word is utilized, wherein the category information is expanded by using information of the frequently utilized word list in response to the morpheme analysis being performed. | 0.817122 |
9,621,602 | 1 | 7 | 1. A method comprising: storing, by a social networking system, a social graph comprising a plurality of nodes and edges, wherein a node represents a user or an entity and an edge represents one of a connection between users or an interaction between users performed via the social networking system; storing a plurality of baseline data profiles representing physical social interactions associated with users, wherein the baseline data profiles are created based at least in part on using a machine learning technique and a baseline data profile specifies a physical movement of a sensor; receiving, from a first sensor associated with a first user, a data profile characterizing an interaction between the first sensor and a second sensor associated with a second user as a function of a physical movement of the first sensor; receiving a user identifier corresponding to the first user and the data profile characterizing the interaction; comparing the received data profile characterizing the interaction to the plurality of baseline data profiles to identify a matching baseline data profile responsive to a matching of the physical movement specified by the data profile with the physical movement specified by the matching baseline data profile; identifying a physical social interaction associated with the first user and the second user based on the matching baseline data profile; adding a new edge to the social graph of the social networking system, the new edge representing the identified physical social interaction; and notifying one or more other users of the social networking system that the first user engaged in the physical social interaction with the second user. | 1. A method comprising: storing, by a social networking system, a social graph comprising a plurality of nodes and edges, wherein a node represents a user or an entity and an edge represents one of a connection between users or an interaction between users performed via the social networking system; storing a plurality of baseline data profiles representing physical social interactions associated with users, wherein the baseline data profiles are created based at least in part on using a machine learning technique and a baseline data profile specifies a physical movement of a sensor; receiving, from a first sensor associated with a first user, a data profile characterizing an interaction between the first sensor and a second sensor associated with a second user as a function of a physical movement of the first sensor; receiving a user identifier corresponding to the first user and the data profile characterizing the interaction; comparing the received data profile characterizing the interaction to the plurality of baseline data profiles to identify a matching baseline data profile responsive to a matching of the physical movement specified by the data profile with the physical movement specified by the matching baseline data profile; identifying a physical social interaction associated with the first user and the second user based on the matching baseline data profile; adding a new edge to the social graph of the social networking system, the new edge representing the identified physical social interaction; and notifying one or more other users of the social networking system that the first user engaged in the physical social interaction with the second user. 7. The method of claim 1 , wherein the second user is one of: a human user or an inanimate object. | 0.910584 |
8,657,603 | 7 | 8 | 7. The system for authoring knitting and crocheting patterns according to claim 6 , wherein said Repeat Number indicates any number of time to repeat said portion of the pattern from 1 to infinity. | 7. The system for authoring knitting and crocheting patterns according to claim 6 , wherein said Repeat Number indicates any number of time to repeat said portion of the pattern from 1 to infinity. 8. The system for authoring knitting and crocheting patterns according to claim 7 , wherein said enunciation engine interprets an infinity Repeat Number as an instruction to repeat said portion of the pattern continuously until manual intervention of said user at said playback user interface. | 0.913365 |
8,190,632 | 1 | 17 | 1. A computer-readable recording medium storing therein an information retrieving program that causes a computer to execute: acquiring a document to be searched and having a hierarchical structure; generating a path schema related to the acquired document; receiving input of a retrieval keyword, a retrieval condition for the retrieval keyword, and a retrieval equation specifying a retrieval range for the retrieval keyword; generating a single automaton that includes a hierarchy retrieval automaton that retrieves a hierarchy of the generated path schema and a hit keyword retrieval automaton that retrieves a hit keyword satisfying the input retrieval condition for the retrieval keyword, the single automaton making state transition between a hit hierarchical node at which the hit keyword in the hierarchy retrieval automaton is present and a set of nodes representing the hit keyword; retrieving, from the document and using the generated single automaton, the hit keyword within the retrieval range; and outputting a retrieval result obtained at the retrieving. | 1. A computer-readable recording medium storing therein an information retrieving program that causes a computer to execute: acquiring a document to be searched and having a hierarchical structure; generating a path schema related to the acquired document; receiving input of a retrieval keyword, a retrieval condition for the retrieval keyword, and a retrieval equation specifying a retrieval range for the retrieval keyword; generating a single automaton that includes a hierarchy retrieval automaton that retrieves a hierarchy of the generated path schema and a hit keyword retrieval automaton that retrieves a hit keyword satisfying the input retrieval condition for the retrieval keyword, the single automaton making state transition between a hit hierarchical node at which the hit keyword in the hierarchy retrieval automaton is present and a set of nodes representing the hit keyword; retrieving, from the document and using the generated single automaton, the hit keyword within the retrieval range; and outputting a retrieval result obtained at the retrieving. 17. The computer-readable recording medium according to claim 1 and storing therein the information retrieving program that causes the computer to further execute: converting a start tag representing each hierarchy in the document into a start tag that includes a hierarchy start indicator and a unique identifier assigned to each path making up the path schema, the converting further including converting an end tag representing each hierarchy in the document into a start tag that includes the hierarchy start indicator and the unique identifier assigned to a path whose end is a parent node to a hierarchical node specified by the hierarchical name of a start tag corresponding to the hierarchy start indicator and the end tag, wherein the generating of the path schema includes generating the path schema related to the document converted at the converting. | 0.500579 |
8,209,481 | 11 | 16 | 11. A computer-implemented system of realizing an associative memory capable of storing a set of documents and retrieving one or more of said stored documents similar to an inputted query document, said method comprising: coding each of said stored document or a part of it through a corresponding feature vector; arranging said feature vector in a matrix; and generating a query feature vector based on the query document. | 11. A computer-implemented system of realizing an associative memory capable of storing a set of documents and retrieving one or more of said stored documents similar to an inputted query document, said method comprising: coding each of said stored document or a part of it through a corresponding feature vector; arranging said feature vector in a matrix; and generating a query feature vector based on the query document. 16. The system of claim 11 wherein features coded by a feature vector for their presence or absence comprise one or more of the following; unigrams, digrams, multigrams, words, fragments of text, sentences, paragraphs, or a combination of them; semantic classes reflecting a certain meaning which elements in the text to be represented may have; concept classes reflecting an abstract concept to which elements in the text to be represented belong; one or more classification classes classifying the document according to a classification scheme; one or more attributes which may be assigned to a document. | 0.500824 |
7,508,984 | 1 | 4 | 1. A method of quantifying document image data, comprising: using a processor to implement the following steps: quantifying a predetermined number of consecutive characters in first document image data into first quantified data based upon layout characteristic information, the first document image data containing character lines, each of the character lines including characters, the layout characteristic information being based upon a minimal circumscribing rectangle around each of the characters, the layout characteristic information including a plurality of parameters, the parameters including a combination of information on a height of the minimal circumscribing rectangle starting from a bottom line in the character line, a height of the minimal circumscribing rectangle, a width of the minimal circumscribing rectangle, a black pixel density in the minimal circumscribing rectangle and a distance between two adjacent ones of the minimal circumscribing rectangles; converting the first quantified data into symbol series; and generating a table representing occurrence probabilities of the consecutive characters based upon the symbol series. | 1. A method of quantifying document image data, comprising: using a processor to implement the following steps: quantifying a predetermined number of consecutive characters in first document image data into first quantified data based upon layout characteristic information, the first document image data containing character lines, each of the character lines including characters, the layout characteristic information being based upon a minimal circumscribing rectangle around each of the characters, the layout characteristic information including a plurality of parameters, the parameters including a combination of information on a height of the minimal circumscribing rectangle starting from a bottom line in the character line, a height of the minimal circumscribing rectangle, a width of the minimal circumscribing rectangle, a black pixel density in the minimal circumscribing rectangle and a distance between two adjacent ones of the minimal circumscribing rectangles; converting the first quantified data into symbol series; and generating a table representing occurrence probabilities of the consecutive characters based upon the symbol series. 4. The method of quantifying document image data according to claim 1 further comprising additional steps of: inputting second document image data in an unknown language; converting the second document image data into second quantified data representing the predetermined number of the consecutive characters based upon the layout characteristic information; comparing the second quantified data in the table; totaling the occurrence probabilities for a predetermined amount of the second document image to generate a totaled occurrence probability result; and determining whether or not the second document image data is in the same language as the first document image data based upon the totaled occurrence probability result. | 0.674844 |
8,364,686 | 37 | 38 | 37. The system of claim 31 , where the one or more computer devices are further configured to: compare a pair of fingerprints to determine whether the pair of fingerprints indicates that documents, associated with the pair of fingerprints, correspond to near-duplicate documents, where the fingerprint is one of the fingerprints in the pair of fingerprints. | 37. The system of claim 31 , where the one or more computer devices are further configured to: compare a pair of fingerprints to determine whether the pair of fingerprints indicates that documents, associated with the pair of fingerprints, correspond to near-duplicate documents, where the fingerprint is one of the fingerprints in the pair of fingerprints. 38. The system of claim 37 , where the one or more computer devices are further configured to: provide the documents to a user as a single link when the documents are determined to be the near-duplicate documents based on the comparison of the pair of fingerprints associated with the documents. | 0.883858 |
7,634,501 | 4 | 6 | 4. An apparatus for allowing entities to cooperate for implementing at least one process, the apparatus being part of a computer system, comprising: a processor for: (a) producing objects by at least one entity; (b) associating each of the objects with at least one semantic term, said means for associating done by the at least one entity; (c) allocating a tuple to each of the at least one semantic terms, the tuple containing information provided by each of the objects corresponding to a meaning of the at least one semantic term, allowing the tuple to be found in at least one tuple space; (d) storing and retrieving information in the form of the tuple; (e) using the tuple to represent each of the objects involved in at least one process, wherein at least one tuple type is registered by the at least one entity; (f) representing conditions, under which the at least one entity can produce at least one of the objects by using at least one tuple template, the at least one tuple template generated by the at least one entity; (g) associating the at least one tuple template and the tuple with the at least one semantic term to form a type; (h) indicating the at least one semantic term in any order to represent a goal of the at least one process; and (i) generating streams representing chains of events composed of sequential events which terminate at the tuple corresponding to each of the at least one semantic terms. | 4. An apparatus for allowing entities to cooperate for implementing at least one process, the apparatus being part of a computer system, comprising: a processor for: (a) producing objects by at least one entity; (b) associating each of the objects with at least one semantic term, said means for associating done by the at least one entity; (c) allocating a tuple to each of the at least one semantic terms, the tuple containing information provided by each of the objects corresponding to a meaning of the at least one semantic term, allowing the tuple to be found in at least one tuple space; (d) storing and retrieving information in the form of the tuple; (e) using the tuple to represent each of the objects involved in at least one process, wherein at least one tuple type is registered by the at least one entity; (f) representing conditions, under which the at least one entity can produce at least one of the objects by using at least one tuple template, the at least one tuple template generated by the at least one entity; (g) associating the at least one tuple template and the tuple with the at least one semantic term to form a type; (h) indicating the at least one semantic term in any order to represent a goal of the at least one process; and (i) generating streams representing chains of events composed of sequential events which terminate at the tuple corresponding to each of the at least one semantic terms. 6. The apparatus of claim 4 , further comprising: a processor for: (j) replacing the at least one tuple template from the tuple, wherein the at least one tuple template and the tuple are of the same tuple type. | 0.50237 |
9,881,001 | 17 | 18 | 17. A non-transitory computer readable recording medium on which a program is recorded, said program executed on a computer to function as a system comprising: an input part for inputting image data; a word extracting part for extracting a word from texts contained in said image data; a synonym obtaining part for obtaining a synonym corresponding to said word, and for associating said obtained synonym with said word; a position identifying part for identifying a display position on said image data of said word with which said synonym is associated; a layer creating part for creating an accompanying layer to add to an original layer, which is said image data containing said word, and for embedding said synonym associated with said word within a position on said accompanying layer that is the same as the display position of the word in said original layer identified by said position identifying part so that the synonym in the accompanying layer overlaps the word in the original layer without replacing the word in the original layer, wherein the location of a first character of the synonym in the accompanying layer matches the location of a first character of the word in the original layer, or the display area of the synonym in the accompanying layer has the same size as the display area of the word in the original layer and is at the same location in the accompanying layer as the display area of the word in the original layer; and an output image generating part for generating output image data including said original layer containing said word and said accompanying layer within which said synonym is embedded and overlaps the word. | 17. A non-transitory computer readable recording medium on which a program is recorded, said program executed on a computer to function as a system comprising: an input part for inputting image data; a word extracting part for extracting a word from texts contained in said image data; a synonym obtaining part for obtaining a synonym corresponding to said word, and for associating said obtained synonym with said word; a position identifying part for identifying a display position on said image data of said word with which said synonym is associated; a layer creating part for creating an accompanying layer to add to an original layer, which is said image data containing said word, and for embedding said synonym associated with said word within a position on said accompanying layer that is the same as the display position of the word in said original layer identified by said position identifying part so that the synonym in the accompanying layer overlaps the word in the original layer without replacing the word in the original layer, wherein the location of a first character of the synonym in the accompanying layer matches the location of a first character of the word in the original layer, or the display area of the synonym in the accompanying layer has the same size as the display area of the word in the original layer and is at the same location in the accompanying layer as the display area of the word in the original layer; and an output image generating part for generating output image data including said original layer containing said word and said accompanying layer within which said synonym is embedded and overlaps the word. 18. The non-transitory computer readable recording medium according to claim 17 , wherein said layer creating part, when said synonym obtaining part obtains multiple synonyms corresponding to said single word, creates more than one said accompanying layers and embeds each of said multiple synonyms associated with said single word within said different accompanying layer. | 0.721226 |
8,073,804 | 1 | 10 | 1. A method for reaching conclusions in the form of a series of rules in an array structure having a hierarchical order of validity, the method comprising: receiving a set of inserted rules as an initial rules array and storing the initial rules in at least one memory store on a computer; configuring the rules, where an antecedent comprises a non-empty, sorted set and a consequent comprises a non-empty sequence; determining a hierarchy of validity for the rules, and sorting the rules according to said hierarchy of validity; determining at least one rule set which optimizes the selection of rules, said rule set meeting predetermined validity requirements; and ordering the rules in order of validity based on rank within the memory store. | 1. A method for reaching conclusions in the form of a series of rules in an array structure having a hierarchical order of validity, the method comprising: receiving a set of inserted rules as an initial rules array and storing the initial rules in at least one memory store on a computer; configuring the rules, where an antecedent comprises a non-empty, sorted set and a consequent comprises a non-empty sequence; determining a hierarchy of validity for the rules, and sorting the rules according to said hierarchy of validity; determining at least one rule set which optimizes the selection of rules, said rule set meeting predetermined validity requirements; and ordering the rules in order of validity based on rank within the memory store. 10. The method of claim 1 , further comprising: using networked processor clusters, and processing coherent or domain-specific knowledge in the respective clusters, thereby concentrating related knowledge in ones of the clusters to allow the individual clusters to share a maximal number of common antecedents and consequents. | 0.896966 |
8,204,950 | 1 | 30 | 1. A method of providing an in-page search of contents of a webpage, the method comprising: displaying, with a web browser, a visible portion of a webpage, the webpage comprising: markup text comprising text and formatting tags that format the text according to a markup language; executable code that performs an in-page search of contents of the webpage, the executable code being independent of search functionality of the web browser and included in the markup text; and an element that receives a user's search criteria; reading the user's search criteria with the executable code; searching contents of the webpage with the executable code to identify text matching the search criteria; providing on the webpage, with the executable code, a set of user interface controls for the user to select text formatting options for text identified as matching the search criteria; modifying, with the executable code, a set of markup tags corresponding to the identified text in accordance with the text formatting options selected by the user, based on a determination that the identified text matches the search criteria, to change the appearance of the identified text relative to other text on the webpage, wherein the modified set of markup tags make the identified text a hyperlink allowing the user to jump to a next match on the webpage, wherein modifying the set of markup tags corresponding to the identified text comprises: removing the identified text from the webpage using the executable code; adding formatting instructions in front of and behind the removed identified text using the executable code; and reinserting the removed identified text and the added formatting instructions into the webpage at an original location of the removed identified text; and redisplaying, with the executable code, the visible portion of the webpage with the modified set of markup tags. | 1. A method of providing an in-page search of contents of a webpage, the method comprising: displaying, with a web browser, a visible portion of a webpage, the webpage comprising: markup text comprising text and formatting tags that format the text according to a markup language; executable code that performs an in-page search of contents of the webpage, the executable code being independent of search functionality of the web browser and included in the markup text; and an element that receives a user's search criteria; reading the user's search criteria with the executable code; searching contents of the webpage with the executable code to identify text matching the search criteria; providing on the webpage, with the executable code, a set of user interface controls for the user to select text formatting options for text identified as matching the search criteria; modifying, with the executable code, a set of markup tags corresponding to the identified text in accordance with the text formatting options selected by the user, based on a determination that the identified text matches the search criteria, to change the appearance of the identified text relative to other text on the webpage, wherein the modified set of markup tags make the identified text a hyperlink allowing the user to jump to a next match on the webpage, wherein modifying the set of markup tags corresponding to the identified text comprises: removing the identified text from the webpage using the executable code; adding formatting instructions in front of and behind the removed identified text using the executable code; and reinserting the removed identified text and the added formatting instructions into the webpage at an original location of the removed identified text; and redisplaying, with the executable code, the visible portion of the webpage with the modified set of markup tags. 30. The method of claim 1 , further comprising: presenting, on the webpage, a summary of the identified text. | 0.84157 |
9,704,069 | 1 | 4 | 1. An image processing method for classifying each of a plurality of regions in an image to one of a plurality of predefined classes using classification confidences, the method comprising: a confidence generation step for generating, for each of a plurality of regions of the image, a set of classification confidences, each classification confidence corresponding to one of a plurality of predefined classes and representing the probability of the respective region belonging to the predefined class; and a classification step for classifying the regions in the image wherein for each of the regions for which an obvious match with one of the predefined classes exists based on the classification confidences associated with the region, classifying the region to the respective predefined class based on the classification confidences associated with the region, the method further comprising: a fuzzy region extraction step for extracting and designating as fuzzy regions one or more regions of the plurality of regions, which do not have an obvious match with one of the plurality of predefined classes based on their set of associated classification confidences; and a confidence update step for updating the classification confidence for each such fuzzy region based on the sets of classification confidences associated with adjacent regions thereof, wherein the classification step further classifies the fuzzy regions to respective predefined classes based on the updated classification confidences. | 1. An image processing method for classifying each of a plurality of regions in an image to one of a plurality of predefined classes using classification confidences, the method comprising: a confidence generation step for generating, for each of a plurality of regions of the image, a set of classification confidences, each classification confidence corresponding to one of a plurality of predefined classes and representing the probability of the respective region belonging to the predefined class; and a classification step for classifying the regions in the image wherein for each of the regions for which an obvious match with one of the predefined classes exists based on the classification confidences associated with the region, classifying the region to the respective predefined class based on the classification confidences associated with the region, the method further comprising: a fuzzy region extraction step for extracting and designating as fuzzy regions one or more regions of the plurality of regions, which do not have an obvious match with one of the plurality of predefined classes based on their set of associated classification confidences; and a confidence update step for updating the classification confidence for each such fuzzy region based on the sets of classification confidences associated with adjacent regions thereof, wherein the classification step further classifies the fuzzy regions to respective predefined classes based on the updated classification confidences. 4. The image processing method according to claim 1 , wherein the fuzzy region extraction step comprises: a confidence map generation step for creating a confidence map for each predefined class based on the classification confidence of each region; a region segmentation step for segmenting each confidence map into foreground and background regions of each predefined class based on the confidence maps and predefined thresholds; and a fuzzy region judgment step for judging a region, which is not segmented into the foreground region of one and only one predefined class, to be a fuzzy region. | 0.539413 |
9,377,948 | 10 | 17 | 10. An information handling device, comprising: a display; an input surface; one or more processors; a memory device storing instructions accessible to the one or more processors, the instructions being executable by the one or more processors to: accept, at the input surface, one or more inputs, the one or more inputs comprising handwriting inputs including a special handwriting input pre-associated with a request for assistance; determine, using the one or more processors, a candidate list of inputs based on the handwriting inputs and the special handwriting input; and provide, using the one or more processors, a display of the candidate list on the display. | 10. An information handling device, comprising: a display; an input surface; one or more processors; a memory device storing instructions accessible to the one or more processors, the instructions being executable by the one or more processors to: accept, at the input surface, one or more inputs, the one or more inputs comprising handwriting inputs including a special handwriting input pre-associated with a request for assistance; determine, using the one or more processors, a candidate list of inputs based on the handwriting inputs and the special handwriting input; and provide, using the one or more processors, a display of the candidate list on the display. 17. The information handling device of claim 10 , wherein the input surface is selected from the group consisting of a touch screen and a touch pad. | 0.785507 |
9,727,547 | 20 | 21 | 20. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further cause the processing device to: upon continued re-sizing of the media interface, determine that a total width of the media interface is large enough to display two primary content displays in the presentation pane; display an additional primary content display in the presentation pane in the media interface, wherein the vertical margin panes are reduced or removed to accommodate the additional primary content display; fade out the display of the note; and re-display the glyph in the presentation pane. | 20. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further cause the processing device to: upon continued re-sizing of the media interface, determine that a total width of the media interface is large enough to display two primary content displays in the presentation pane; display an additional primary content display in the presentation pane in the media interface, wherein the vertical margin panes are reduced or removed to accommodate the additional primary content display; fade out the display of the note; and re-display the glyph in the presentation pane. 21. The non-transitory computer-readable storage medium of claim 20 , wherein the instructions further cause the processing device to: upon continued re-sizing of the media interface, scale the glyph in accordance with the dynamically measured size of the vertical margin panes, wherein the glyph is scaled according to a scaling factor correlated to the size of the vertical margin panes. | 0.823182 |
7,668,873 | 7 | 10 | 7. A computer-readable storage medium having computer executable instructions for generating an accessible metadata store in a source document, the instructions comprising: generating a source document on a source application, wherein the source document includes surface view data that is exposed on a presentation layer when the source document is rendered and metadata that is unexposed on the presentation layer when the source document is rendered; structuring the metadata of the source document into a mark-up language (ML) document; storing the ML document that includes the metadata of the source document in the metadata store separate from the surface view data of the source document, wherein the metadata store and the surface view data are stored in the source document; attaching an ML schema file to the ML document that includes the metadata of the source document, wherein the ML schema file is stored in the metadata store of the source document; exposing application programming interfaces (APIs) to the metadata store, wherein the APIs provide other applications having application types different than the source application access to the ML document that includes the metadata of the source document via object models of the other applications, wherein the exposed APIs for the metadata store permit the other applications to: load the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, monitor modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, modify the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, when a modification of the metadata is received at the metadata store, receive a change notification from the metadata store of a modification to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, and undo modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data. | 7. A computer-readable storage medium having computer executable instructions for generating an accessible metadata store in a source document, the instructions comprising: generating a source document on a source application, wherein the source document includes surface view data that is exposed on a presentation layer when the source document is rendered and metadata that is unexposed on the presentation layer when the source document is rendered; structuring the metadata of the source document into a mark-up language (ML) document; storing the ML document that includes the metadata of the source document in the metadata store separate from the surface view data of the source document, wherein the metadata store and the surface view data are stored in the source document; attaching an ML schema file to the ML document that includes the metadata of the source document, wherein the ML schema file is stored in the metadata store of the source document; exposing application programming interfaces (APIs) to the metadata store, wherein the APIs provide other applications having application types different than the source application access to the ML document that includes the metadata of the source document via object models of the other applications, wherein the exposed APIs for the metadata store permit the other applications to: load the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, monitor modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, modify the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, when a modification of the metadata is received at the metadata store, receive a change notification from the metadata store of a modification to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, and undo modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data. 10. The computer-readable storage medium of claim 7 , wherein the ML document is validated by the ML schema file. | 0.942581 |
9,665,276 | 17 | 19 | 17. A non-transitory computer-readable storage medium encoded with instructions that, when executed, causes at least one processor of a computing device to perform operations comprising: outputting, for display, a graphical keyboard comprising a plurality of keys; receiving an indication of a continuous gesture comprising a first path in a first direction from a first key of the plurality of keys to a second key of the plurality of keys; determining that the continuous gesture comprises a second path from the second key that ends at the first key and retraces at least a portion of the first path from the first key to the second key, wherein the second path is in a second direction that is substantially reverse to the first direction; and responsive to determining that the second path ends at the first key and retraces at least the portion of the first path from the first key back to the second key in the second direction that is substantially reverse to the first direction, and that the continuous gesture further comprises a third path to a third key, outputting, for display, a character string a third character subsequent to the first character and without the second character output between the first character and third character. | 17. A non-transitory computer-readable storage medium encoded with instructions that, when executed, causes at least one processor of a computing device to perform operations comprising: outputting, for display, a graphical keyboard comprising a plurality of keys; receiving an indication of a continuous gesture comprising a first path in a first direction from a first key of the plurality of keys to a second key of the plurality of keys; determining that the continuous gesture comprises a second path from the second key that ends at the first key and retraces at least a portion of the first path from the first key to the second key, wherein the second path is in a second direction that is substantially reverse to the first direction; and responsive to determining that the second path ends at the first key and retraces at least the portion of the first path from the first key back to the second key in the second direction that is substantially reverse to the first direction, and that the continuous gesture further comprises a third path to a third key, outputting, for display, a character string a third character subsequent to the first character and without the second character output between the first character and third character. 19. The non-transitory computer-readable storage medium of claim 17 , encoded with instructions that, when executed, causes the at least one processor of the computing device to perform operations comprising: comparing at least the first character and the second character to a language model. | 0.674444 |
6,047,253 | 5 | 8 | 5. A method for decoding an encoded speech signal obtained by sinusoidal analytic encoding of an input speech signal, comprising the steps of: deciding whether the input speech signal is voiced or unvoiced; and adding a noise component to a sinusoidal synthesis waveform based on pitch intensity information as a parameter of pitch intensity detected in all bands of a voiced speech portion of the input speech signal on the basis of results of the step of deciding whether the input speech signal is voiced or unvoiced. | 5. A method for decoding an encoded speech signal obtained by sinusoidal analytic encoding of an input speech signal, comprising the steps of: deciding whether the input speech signal is voiced or unvoiced; and adding a noise component to a sinusoidal synthesis waveform based on pitch intensity information as a parameter of pitch intensity detected in all bands of a voiced speech portion of the input speech signal on the basis of results of the step of deciding whether the input speech signal is voiced or unvoiced. 8. The speech decoding method as claimed in claim 5, wherein a level and a bandwidth of the noise component added to the sinusoidal synthesis waveform are controlled in response to the pitch intensity information. | 0.817324 |
8,868,592 | 1 | 5 | 1. A computer-implemented method, comprising: obtaining first profile data for a first user that is associated with a computing device; obtaining second profile data for second users that submitted search queries, the second users being different from the first user; determining, based on the first profile data and the second profile data, similarity scores that are each indicative of a degree of similarity between the first user and at least one of the second users; selecting a proper subset of the search queries based on the similarity scores; generating an update for an autocomplete cache of the computing device associated with the first user using the selected subset of the search queries; and providing the update to the computing device associated with the first user. | 1. A computer-implemented method, comprising: obtaining first profile data for a first user that is associated with a computing device; obtaining second profile data for second users that submitted search queries, the second users being different from the first user; determining, based on the first profile data and the second profile data, similarity scores that are each indicative of a degree of similarity between the first user and at least one of the second users; selecting a proper subset of the search queries based on the similarity scores; generating an update for an autocomplete cache of the computing device associated with the first user using the selected subset of the search queries; and providing the update to the computing device associated with the first user. 5. The computer-implemented method of claim 1 , wherein: obtaining the first profile data for the first user comprises obtaining information that indicates a first context of the computing device; obtaining the second profile data for the second users comprises obtaining information that indicates second contexts in which the respective search queries were submitted; and determining the similarity scores comprises determining similarity scores that are each indicative of a degree of similarity between the first context and the respective second contexts. | 0.644219 |
7,711,571 | 17 | 19 | 17. The apparatus of claim 15 , wherein said subset of phrases is selected from a group comprising phrases for a hotel, airport, hospital, and restaurant. | 17. The apparatus of claim 15 , wherein said subset of phrases is selected from a group comprising phrases for a hotel, airport, hospital, and restaurant. 19. The apparatus of claim 17 , wherein the setting is sensed by, determined by, or signaled to the apparatus. | 0.963358 |
9,747,640 | 1 | 2 | 1. A method for calculating a trust score, the method comprising: retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; calculating a first component score based on the first data; retrieving, from a second database using the processing circuitry, second data associated with the first entity; calculating a second component score based on the second data; calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity; updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; wherein receiving, from the user device of the second entity, the data indicating an attribute associated with the first entity comprises receiving an indication of a user input from the second entity that validates the first data; and wherein recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity comprises increasing or decreasing the first component score by a predetermined amount until a threshold component score is reached. | 1. A method for calculating a trust score, the method comprising: retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; calculating a first component score based on the first data; retrieving, from a second database using the processing circuitry, second data associated with the first entity; calculating a second component score based on the second data; calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity; updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; wherein receiving, from the user device of the second entity, the data indicating an attribute associated with the first entity comprises receiving an indication of a user input from the second entity that validates the first data; and wherein recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity comprises increasing or decreasing the first component score by a predetermined amount until a threshold component score is reached. 2. The method of claim 1 , further comprising transmitting information intended to cause the user device of the second entity to display a representation related to the updated trust score for the first entity on the user device of the second entity. | 0.891681 |
8,341,554 | 19 | 24 | 19. A computer program product having a non-transitory computer readable medium with computer program logic recorded thereon, the computer program product comprising: program code for displaying a user interface of a first application for editing content, the user interface comprising a plurality of graphically-displayed function options, each of the plurality of graphically-displayed function options corresponding to one of a plurality of functions; program code for displaying a workspace of the first application, the workspace configured to display content for editing; wherein at least one of the plurality of graphically-displayed function options comprises a command to launch a second application to edit a selected object displayed in the workspace, and an icon corresponding to the second application, and to communicate information about the source file of the selected object to the second application, the second application configured to: open a source file for said selected object, display an edit session indicator to indicate that the second application was called from the first application; display a graphically-displayed function option corresponding to a command to complete the editing session; and export the edited source file of the selected object to the first application in response to receiving the command to complete the editing session. | 19. A computer program product having a non-transitory computer readable medium with computer program logic recorded thereon, the computer program product comprising: program code for displaying a user interface of a first application for editing content, the user interface comprising a plurality of graphically-displayed function options, each of the plurality of graphically-displayed function options corresponding to one of a plurality of functions; program code for displaying a workspace of the first application, the workspace configured to display content for editing; wherein at least one of the plurality of graphically-displayed function options comprises a command to launch a second application to edit a selected object displayed in the workspace, and an icon corresponding to the second application, and to communicate information about the source file of the selected object to the second application, the second application configured to: open a source file for said selected object, display an edit session indicator to indicate that the second application was called from the first application; display a graphically-displayed function option corresponding to a command to complete the editing session; and export the edited source file of the selected object to the first application in response to receiving the command to complete the editing session. 24. The computer program product of claim 19 , further comprising program code to deactivate the first application in response to receiving the command to launch a second application to edit a selected object. | 0.813725 |
4,046,382 | 1 | 3 | 1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon. | 1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon. 3. The game apparatus as claimed in claim 1, wherein each of said playing boards contain an odd number of words and an odd number of columns, the median row having a word with one less letter than the other said words, the median column intersecting said median row having "FREE" disposed therein. | 0.501678 |
8,275,729 | 1 | 2 | 1. Method for verifying linear hybrid automaton, the method comprising: using a reachability analysis of a linear transition system (LTS) to verify a linear hybrid automata (LHA) system; generating initial abstract model based on an original Linear-Time Temporal Logic (LTL) specification; validating a counterexample using an approach of linear constraints satisfaction; identifying a fragment in the counterexample by iteratively applying the approach of linear constraints satisfaction; and refining the original LTL specification based on the fragment derived. | 1. Method for verifying linear hybrid automaton, the method comprising: using a reachability analysis of a linear transition system (LTS) to verify a linear hybrid automata (LHA) system; generating initial abstract model based on an original Linear-Time Temporal Logic (LTL) specification; validating a counterexample using an approach of linear constraints satisfaction; identifying a fragment in the counterexample by iteratively applying the approach of linear constraints satisfaction; and refining the original LTL specification based on the fragment derived. 2. The method of claim 1 , wherein generating an initial abstract model comprises: transferring the LHA into the LTS, wherein the LTS is a discrete transition graph in combination with a set of real variables that consists of discrete dynamics that are modeled by discrete transitions, wherein each discrete transition has a linear transition relation function that relates the real variables before and after each discrete transition, wherein the abstract model includes the LTS discrete transition graph and does not include representations of reachable state sets. | 0.50088 |
8,930,337 | 1 | 7 | 1. A method for presenting visual feedback in an interface, the method including: receiving one or more mapped relationships between a given output and one or more inputs represented by input variables, at least one of the mapped relationships including a transformational expression executable on a data processing system, the transformational expression defining an output of a mapped relationship based on at least one input variable mapped to an element of an input dataset; receiving identification of elements of an output dataset mapped to outputs of respective mapped relationships; generating output data from the data processing system according to the transformational expression based on input data from the input dataset associated with the element of the input dataset mapped to the input variable, including applying the transformational expressions to input values in respective fields of input records of the input dataset and storing output values in respective fields of output records of the output dataset, including executing a dataflow graph including nodes representing data processing components, links representing data flows between the data processing components, a node representing the input dataset providing a data flow of the input records, and a node representing the output dataset receiving a data flow of the output records; determining validation information in response to the generated output data based on validation criteria defining one or more characteristics of valid values associated with one or more of the identified elements of the output dataset; and presenting in the interface visual feedback based on the determined validation information. | 1. A method for presenting visual feedback in an interface, the method including: receiving one or more mapped relationships between a given output and one or more inputs represented by input variables, at least one of the mapped relationships including a transformational expression executable on a data processing system, the transformational expression defining an output of a mapped relationship based on at least one input variable mapped to an element of an input dataset; receiving identification of elements of an output dataset mapped to outputs of respective mapped relationships; generating output data from the data processing system according to the transformational expression based on input data from the input dataset associated with the element of the input dataset mapped to the input variable, including applying the transformational expressions to input values in respective fields of input records of the input dataset and storing output values in respective fields of output records of the output dataset, including executing a dataflow graph including nodes representing data processing components, links representing data flows between the data processing components, a node representing the input dataset providing a data flow of the input records, and a node representing the output dataset receiving a data flow of the output records; determining validation information in response to the generated output data based on validation criteria defining one or more characteristics of valid values associated with one or more of the identified elements of the output dataset; and presenting in the interface visual feedback based on the determined validation information. 7. The method of claim 1 , further including presenting in the interface a value representing the generated output data. | 0.917469 |
9,547,998 | 1 | 12 | 1. A computer-implemented method for training a user, comprising: by a sensor, sensing at least one action performed by the user and data corresponding to the at least one action to yield sensed data, wherein: the sensor comprises a USB sensor device and the sensing comprises detecting that a user of an electronic device has connected a USB device to the electronic device, the sensor comprises a Wi-Fi sensor device and the sensing comprises detecting that the user has connected the electronic device to a Wi-Fi access point, the sensor comprises a Bluetooth headset usage detection sensor and the sensing comprises identifying Bluetooth headset use, the sensor comprises a camera coupled with a computer vision program, or the sensor comprises a physical location tracking sensor and the sensing comprises detecting a location of the user; by a computer system comprising a processor, executing computer-readable programming instructions that cause the system to: access a data storage device that stores a training needs model that comprises an estimate of at least one of a cost and a benefit of exposing the user to at least one available training action, apply, to the training needs model, the sensed data to identify a cybersecurity threat scenario for which the user is at risk, access a collection of available training actions and select, based on the sensed data and the cybersecurity threat scenario, at least one training action from the collection of available training actions, and cause the selected at least one cybersecurity training action to be delivered to the user. | 1. A computer-implemented method for training a user, comprising: by a sensor, sensing at least one action performed by the user and data corresponding to the at least one action to yield sensed data, wherein: the sensor comprises a USB sensor device and the sensing comprises detecting that a user of an electronic device has connected a USB device to the electronic device, the sensor comprises a Wi-Fi sensor device and the sensing comprises detecting that the user has connected the electronic device to a Wi-Fi access point, the sensor comprises a Bluetooth headset usage detection sensor and the sensing comprises identifying Bluetooth headset use, the sensor comprises a camera coupled with a computer vision program, or the sensor comprises a physical location tracking sensor and the sensing comprises detecting a location of the user; by a computer system comprising a processor, executing computer-readable programming instructions that cause the system to: access a data storage device that stores a training needs model that comprises an estimate of at least one of a cost and a benefit of exposing the user to at least one available training action, apply, to the training needs model, the sensed data to identify a cybersecurity threat scenario for which the user is at risk, access a collection of available training actions and select, based on the sensed data and the cybersecurity threat scenario, at least one training action from the collection of available training actions, and cause the selected at least one cybersecurity training action to be delivered to the user. 12. The method of claim 1 , wherein identifying the threat scenario includes, using the computer system, accessing and using information about the user other than the sensed at least one user action. | 0.878362 |
8,244,720 | 6 | 9 | 6. A computer-implemented device comprising: one or more memory devices to store instructions; and one or more processors executing the instructions to: receive a search query; identify a plurality of blog documents that are responsive to the search query; generate a relevance score for each blog document in the plurality of blog documents, where the relevance score for a particular blog document is based on a relevance of the particular blog document to the search query; generate a quality score for each blog document in the plurality of blog documents, where the quality score of the particular blog document is based on a quality of the particular blog document, independent of the search query, where the quality score is based on a plurality of indicators that include at least one of one or more positive indicators or one or more negative indicators, where the plurality of indicators include: a location of ads in the particular blog document, and an indication of whether multiple blog feeds, that are based on the particular blog document, include duplicate content; generate a ranking score for each of the plurality of blog documents based on the respective generated relevance and quality scores; rank the plurality of blog documents in an order based on the ranking scores of the plurality of blog documents; and present information regarding the plurality of blog documents in the ranked order. | 6. A computer-implemented device comprising: one or more memory devices to store instructions; and one or more processors executing the instructions to: receive a search query; identify a plurality of blog documents that are responsive to the search query; generate a relevance score for each blog document in the plurality of blog documents, where the relevance score for a particular blog document is based on a relevance of the particular blog document to the search query; generate a quality score for each blog document in the plurality of blog documents, where the quality score of the particular blog document is based on a quality of the particular blog document, independent of the search query, where the quality score is based on a plurality of indicators that include at least one of one or more positive indicators or one or more negative indicators, where the plurality of indicators include: a location of ads in the particular blog document, and an indication of whether multiple blog feeds, that are based on the particular blog document, include duplicate content; generate a ranking score for each of the plurality of blog documents based on the respective generated relevance and quality scores; rank the plurality of blog documents in an order based on the ranking scores of the plurality of blog documents; and present information regarding the plurality of blog documents in the ranked order. 9. The computer-implemented device of claim 6 , where the presented ranked order is different from a ranked order that is solely based on relevance of the blog documents to the search query. | 0.502618 |
9,430,563 | 9 | 10 | 9. The apparatus of claim 1 , wherein the probabilistic topic model comprises a Gaussian mixture model (GMM) including K-dimensional Gaussian components, the GMM including M Gaussian components corresponding to the M semantic topics. | 9. The apparatus of claim 1 , wherein the probabilistic topic model comprises a Gaussian mixture model (GMM) including K-dimensional Gaussian components, the GMM including M Gaussian components corresponding to the M semantic topics. 10. The apparatus of claim 9 , wherein in the performed document processing method, the applying includes: applying the learned GMM to generate a vector or histogram of topic probabilities representing the input document. | 0.943622 |
8,429,619 | 12 | 13 | 12. The computer program product of claim 9 , further comprising program instructions for receiving a sequence of user input commands invoking the high-level procedures via a command interface, wherein the program instructions for controlling the execution of the executable instruction stream are executed in response to the sequence of user input commands, and wherein the program instructions for generating generate a record of the sequence of user input commands that is subsequently repeated by the program instructions for executing controlling the execution of the trace file. | 12. The computer program product of claim 9 , further comprising program instructions for receiving a sequence of user input commands invoking the high-level procedures via a command interface, wherein the program instructions for controlling the execution of the executable instruction stream are executed in response to the sequence of user input commands, and wherein the program instructions for generating generate a record of the sequence of user input commands that is subsequently repeated by the program instructions for executing controlling the execution of the trace file. 13. The computer program product of claim 12 , wherein the program instructions for receiving further cause execution of the program instructions for executing of the trace file in response to receiving a command that specifies the trace file as a command script. | 0.90687 |
9,754,589 | 14 | 22 | 14. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text corresponding to at least a portion of a user input; executing a first natural language understanding (“NLU”) process using the text, wherein the first NLU process is associated with a first subject matter, wherein the first NLU process produces a first NLU result, and wherein the first NLU result is associated with a first score indicative of a confidence in the first NLU result; executing a second NLU process using the text, wherein the second NLU process is associated with a second subject matter, wherein the second NLU process generates a second NLU result, and wherein the second NLU result is associated with a second score indicative of a confidence in the second NLU result; selecting the first NLU result based at least partly on the first score and the second score; and generating a response based at least partly on the first NLU result. | 14. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text corresponding to at least a portion of a user input; executing a first natural language understanding (“NLU”) process using the text, wherein the first NLU process is associated with a first subject matter, wherein the first NLU process produces a first NLU result, and wherein the first NLU result is associated with a first score indicative of a confidence in the first NLU result; executing a second NLU process using the text, wherein the second NLU process is associated with a second subject matter, wherein the second NLU process generates a second NLU result, and wherein the second NLU result is associated with a second score indicative of a confidence in the second NLU result; selecting the first NLU result based at least partly on the first score and the second score; and generating a response based at least partly on the first NLU result. 22. The computer-implemented method of claim 14 , wherein the executing the second NLU process using the text comprises: obtaining hint data indicating the text is more likely associated with the first subject matter than the second subject matter; and generating the second score based at least partly on the hint data. | 0.733333 |
9,299,035 | 2 | 4 | 2. The method of claim 1 , wherein learning the predictive model comprises extracting a set of attributes from the execution traces. | 2. The method of claim 1 , wherein learning the predictive model comprises extracting a set of attributes from the execution traces. 4. The method of claim 2 , wherein learning the predictive model comprises: forming a matrix having rows that represent individual execution traces and columns that represent individual attributes; and performing machine learning on the matrix to generate the predictive model. | 0.868969 |
9,076,441 | 1 | 12 | 1. A speech recognition circuit comprising: a circuit for providing state identifiers which identify states corresponding to nodes or groups of adjacent nodes in a lexical tree, and for providing scores corresponding to said state identifiers, the lexical tree comprising a model of words; a memory structure for receiving and storing state identifiers identified by a node identifier identifying a node or group of adjacent nodes, said memory structure being adapted to allow lookup to identify particular state identifiers, reading of the scores corresponding to the state identifiers, and writing back of the scores to the memory structure after modification of the scores; an accumulator for receiving score updates corresponding to particular state identifiers from a score update generating circuit which generates the score updates using audio input, for receiving scores from the memory structure, and for modifying said scores by adding said score updates to said scores; and a selector circuit for selecting at least one node or group of adjacent nodes of the lexical tree according to said scores. | 1. A speech recognition circuit comprising: a circuit for providing state identifiers which identify states corresponding to nodes or groups of adjacent nodes in a lexical tree, and for providing scores corresponding to said state identifiers, the lexical tree comprising a model of words; a memory structure for receiving and storing state identifiers identified by a node identifier identifying a node or group of adjacent nodes, said memory structure being adapted to allow lookup to identify particular state identifiers, reading of the scores corresponding to the state identifiers, and writing back of the scores to the memory structure after modification of the scores; an accumulator for receiving score updates corresponding to particular state identifiers from a score update generating circuit which generates the score updates using audio input, for receiving scores from the memory structure, and for modifying said scores by adding said score updates to said scores; and a selector circuit for selecting at least one node or group of adjacent nodes of the lexical tree according to said scores. 12. The speech recognition circuit of claim 1 , wherein the memory structure comprises at least one content addressable memory and at least one random access memory, the content addressable memory being configured to output addresses of the random access memory. | 0.817294 |
9,436,758 | 5 | 7 | 5. The method of claim 1 , wherein the support content includes at least one support solution, and wherein partitioning the plurality of filtered documents includes partitioning the plurality of filtered documents based on the at least one support solution. | 5. The method of claim 1 , wherein the support content includes at least one support solution, and wherein partitioning the plurality of filtered documents includes partitioning the plurality of filtered documents based on the at least one support solution. 7. The method of claim 5 , where the at least one support solution comprises predetermined response. | 0.980024 |
9,009,170 | 2 | 3 | 2. The method of claim 1 , further comprising: receiving a relevance score for each of the plurality of distinct content items, the relevance score being a measure of relevance of the distinct content item to a search query; ranking the plurality of distinct content items based on the rank score and the relevance score; and ordering search results for the distinct content items, the search results being ordered according to the ranking of the plurality of distinct content items. | 2. The method of claim 1 , further comprising: receiving a relevance score for each of the plurality of distinct content items, the relevance score being a measure of relevance of the distinct content item to a search query; ranking the plurality of distinct content items based on the rank score and the relevance score; and ordering search results for the distinct content items, the search results being ordered according to the ranking of the plurality of distinct content items. 3. The method of claim 2 , wherein the rank score for each distinct content item is based on the matching uncommon word strings corresponding to distinct book content items that satisfy the search query. | 0.932781 |
9,430,583 | 6 | 7 | 6. The method of claim 1 , wherein the act of receiving user input comprises: for each of a plurality of selectable nodes of the document object model tree, determining a location and size of the node in the rendered version of the subject web page; receiving a mouse cursor location; and selecting one of the plurality of selectable nodes based upon the size determined for the node in the rendered version of the subject web page and location of the mouse cursor relative to the location determined for the node in the rendered version of the subject web page. | 6. The method of claim 1 , wherein the act of receiving user input comprises: for each of a plurality of selectable nodes of the document object model tree, determining a location and size of the node in the rendered version of the subject web page; receiving a mouse cursor location; and selecting one of the plurality of selectable nodes based upon the size determined for the node in the rendered version of the subject web page and location of the mouse cursor relative to the location determined for the node in the rendered version of the subject web page. 7. The method of claim 6 , wherein the selecting comprises selecting from among the nodes containing the location of the mouse cursor the node. | 0.972059 |
8,561,040 | 1 | 6 | 1. A computer-implemented method, comprising: prior to compilation of a program into machine code, generating directives about the program, the directives for directing compilation of the program into machine code by a just-in-time compiler; embedding the directives into a bytecode representation of the program, stored in a machine-readable medium, wherein at least a portion of the bytecode representation can be one-pass compiled into machine code by the just-in-time compiler directed by the embedded directives and compiling the at least a portion of the bytecode representation into machine code in one-pass with the just-in-time compiler using the embedded directives. | 1. A computer-implemented method, comprising: prior to compilation of a program into machine code, generating directives about the program, the directives for directing compilation of the program into machine code by a just-in-time compiler; embedding the directives into a bytecode representation of the program, stored in a machine-readable medium, wherein at least a portion of the bytecode representation can be one-pass compiled into machine code by the just-in-time compiler directed by the embedded directives and compiling the at least a portion of the bytecode representation into machine code in one-pass with the just-in-time compiler using the embedded directives. 6. The computer-implemented method of claim 1 , wherein said prior to compilation of a program into machine code, generating directives about the program, the directives for directing compilation of the program into machine code by a just-in-time compiler, comprises: generating the directives about the program for compilation of the program into machine code for a specific type of processing unit. | 0.843628 |
9,965,459 | 8 | 10 | 8. A computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a source document to be processed for contextual information relating to the source document; provide, for display on a representation of the source document on a user interface, a first input mechanism for a user; identify, based on a first user interaction with the first input mechanism, a first named entity included in the source document; identify, based on a second user interaction with the first input mechanism, a context associated with the source document by using context terms, of the source document, that are different than the first named entity; provide the first named entity as a search query; identify a first reference document based on providing the first named entity as the search query, the first reference document being associated with a result of the search query, and the first reference document being different from the source document; identify a second named entity included in the source document; identify a second reference document associated with the second named entity; analyze the first reference document and the second reference document; classify the first named entity as a primary entity based on analyzing the first reference document and the second reference document; classify the second named entity as a secondary entity based on analyzing the first reference document and the second reference document; perform a semantic similarity analysis using the context associated with the source document and based on classifying the first named entity as the primary entity and the second named entity as the secondary entity; provide, for display on the user interface, a second input mechanism for the user to cause contextual information to be provided; and identify contextual information, based on performing the semantic similarity analysis and based on a third user interaction with the second input mechanism, the contextual information including one or more reference text sections having a threshold semantic similarity score with respect to the secondary entity and the context associated with the source document, and not being included in the source document. | 8. A computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a source document to be processed for contextual information relating to the source document; provide, for display on a representation of the source document on a user interface, a first input mechanism for a user; identify, based on a first user interaction with the first input mechanism, a first named entity included in the source document; identify, based on a second user interaction with the first input mechanism, a context associated with the source document by using context terms, of the source document, that are different than the first named entity; provide the first named entity as a search query; identify a first reference document based on providing the first named entity as the search query, the first reference document being associated with a result of the search query, and the first reference document being different from the source document; identify a second named entity included in the source document; identify a second reference document associated with the second named entity; analyze the first reference document and the second reference document; classify the first named entity as a primary entity based on analyzing the first reference document and the second reference document; classify the second named entity as a secondary entity based on analyzing the first reference document and the second reference document; perform a semantic similarity analysis using the context associated with the source document and based on classifying the first named entity as the primary entity and the second named entity as the secondary entity; provide, for display on the user interface, a second input mechanism for the user to cause contextual information to be provided; and identify contextual information, based on performing the semantic similarity analysis and based on a third user interaction with the second input mechanism, the contextual information including one or more reference text sections having a threshold semantic similarity score with respect to the secondary entity and the context associated with the source document, and not being included in the source document. 10. The computer-readable medium of claim 8 , where the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: classify the first named entity as the primary entity based on a quantity of times that the first named entity is included in the second reference document. | 0.824223 |
8,224,656 | 10 | 11 | 10. The computer-readable device of claim 9 , wherein the displaying the alternates in a disambiguation dialog screen comprises displaying a text box showing a current alternate and an alternates box for displaying a list of additional alternates. | 10. The computer-readable device of claim 9 , wherein the displaying the alternates in a disambiguation dialog screen comprises displaying a text box showing a current alternate and an alternates box for displaying a list of additional alternates. 11. The computer-readable device of claim 10 , wherein the displaying a text box showing a current alternate comprises displaying an alternate ranked as being a most likely match to the transmitted audio. | 0.919874 |
8,965,129 | 1 | 23 | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. 23. The method of claim 1 , wherein the step of displaying is performed in augmented reality on a mobile camera device. | 0.915722 |
8,990,074 | 1 | 4 | 1. A method of noise-robust speech classification, comprising: inputting classification parameters to a speech classifier from external components; generating, in the speech classifier, internal classification parameters from at least one of the input classification parameters; setting a Normalized Auto-correlation Coefficient Function threshold, wherein setting the Normalized Auto-correlation Coefficient Function threshold comprises: increasing a first voicing threshold for classifying a current frame as unvoiced when a signal-to-noise ratio (SNR) fails to exceed a first SNR threshold, wherein the first voicing threshold is not adjusted if the SNR is above the first SNR threshold, and increasing an energy threshold for classifying the current frame as unvoiced when the noise estimate exceeds a noise estimate threshold, wherein the energy threshold is not adjusted if the noise estimate is below the noise estimate threshold; and determining a speech mode classification based on a the first voicing threshold and the energy threshold. | 1. A method of noise-robust speech classification, comprising: inputting classification parameters to a speech classifier from external components; generating, in the speech classifier, internal classification parameters from at least one of the input classification parameters; setting a Normalized Auto-correlation Coefficient Function threshold, wherein setting the Normalized Auto-correlation Coefficient Function threshold comprises: increasing a first voicing threshold for classifying a current frame as unvoiced when a signal-to-noise ratio (SNR) fails to exceed a first SNR threshold, wherein the first voicing threshold is not adjusted if the SNR is above the first SNR threshold, and increasing an energy threshold for classifying the current frame as unvoiced when the noise estimate exceeds a noise estimate threshold, wherein the energy threshold is not adjusted if the noise estimate is below the noise estimate threshold; and determining a speech mode classification based on a the first voicing threshold and the energy threshold. 4. The method of claim 1 , wherein the input parameters comprise voice activity information. | 0.932053 |
4,761,815 | 15 | 16 | 15. A method of recognizing speech as defined in claim 14 additionally comprising: increasing said error value by a preselected weighting function when the classification of a state in the spoken word array doesn't match a compared state in the template array. | 15. A method of recognizing speech as defined in claim 14 additionally comprising: increasing said error value by a preselected weighting function when the classification of a state in the spoken word array doesn't match a compared state in the template array. 16. A method of recognizing speech as defined in claim 15 comprising: increasing said error value by the absolute difference between the length of a spoken word state and a compared template word state where the classifications of said states match. | 0.940883 |
4,618,985 | 28 | 29 | 28. The arrangement as defined in claim 27 and comprising a playing surface; said motion into substantially perpendicular directions taking place upon said playing surface. | 28. The arrangement as defined in claim 27 and comprising a playing surface; said motion into substantially perpendicular directions taking place upon said playing surface. 29. An arrangement as defined in claim 28 wherein said additional means continuously responsive to operator input for controlling said vocal pitch variation is also located upon said playing surface and consists of a transducer means for sensing the net force exerted by the operator upon said playing surface. | 0.940997 |
9,753,923 | 19 | 20 | 19. A system comprising: a computer server comprising a processor and a database, the computer server configured to: access a plurality of content items authored by users of a social networking system; access a plurality of annotated events of time based broadcast media, the events having been aired during segments of time, the annotated events comprising metadata instances that have semantic information about the events; generate mappings between the content items and the annotated events, and between the content items and a plurality of topics; determine a first affinity score between a first population of the users who authored content items mapped to a first one of the events or a first one of the topics and a second population of the users who authored content items mapped to a second one of the events or a second one of the topics; determine a second affinity score between a third population of the users who authored content items mapped to a third one of the events or a third one of the topics and a fourth population of the users who authored content items mapped to a fourth one of the events or a fourth one of the topics; determine a third affinity score between the second population and the fourth population; and infer a fourth affinity score between the first population and third population based on the first, second, and third affinity scores. | 19. A system comprising: a computer server comprising a processor and a database, the computer server configured to: access a plurality of content items authored by users of a social networking system; access a plurality of annotated events of time based broadcast media, the events having been aired during segments of time, the annotated events comprising metadata instances that have semantic information about the events; generate mappings between the content items and the annotated events, and between the content items and a plurality of topics; determine a first affinity score between a first population of the users who authored content items mapped to a first one of the events or a first one of the topics and a second population of the users who authored content items mapped to a second one of the events or a second one of the topics; determine a second affinity score between a third population of the users who authored content items mapped to a third one of the events or a third one of the topics and a fourth population of the users who authored content items mapped to a fourth one of the events or a fourth one of the topics; determine a third affinity score between the second population and the fourth population; and infer a fourth affinity score between the first population and third population based on the first, second, and third affinity scores. 20. The system of claim 19 , wherein generating the mappings comprises performing a feature extraction process on pairs including one of the content items and one of the events or one of the topics, the feature extraction generating content features that identify co-occurring textual information between the content item and the metadata instances of the annotated event or one or more keywords associated with the topic of the pair; and generating scores for the content features indicating whether the content items refers to the annotated events or topics using a feature specific sub-function for the content feature. | 0.5024 |
9,805,006 | 11 | 12 | 11. A system for loading a web page, comprising: one or more processors and memory configured to: provide, via a computer network and to a computing device having one or more processors, a script configured for loading with a web page, the web page configured for display on the computing device, the script having a plurality of function definitions and configured for asynchronous loading such that the web page is operable while the script is loaded; receive an indication of a user interaction with the web page prior to complete loading of the plurality of function definitions on the web page; determine that the user interaction corresponds to a function definition of the plurality of function definitions that has not been loaded; subsequent to determining that the user interaction corresponds to the function definition that has not been loaded: instruct, using a variable, the computing device to queue a command string corresponding to the function definition; determine that the function has been loaded and instruct the computing device to retrieve the command string from the variable; and instruct the computing device to execute the function definition corresponding to the command string. | 11. A system for loading a web page, comprising: one or more processors and memory configured to: provide, via a computer network and to a computing device having one or more processors, a script configured for loading with a web page, the web page configured for display on the computing device, the script having a plurality of function definitions and configured for asynchronous loading such that the web page is operable while the script is loaded; receive an indication of a user interaction with the web page prior to complete loading of the plurality of function definitions on the web page; determine that the user interaction corresponds to a function definition of the plurality of function definitions that has not been loaded; subsequent to determining that the user interaction corresponds to the function definition that has not been loaded: instruct, using a variable, the computing device to queue a command string corresponding to the function definition; determine that the function has been loaded and instruct the computing device to retrieve the command string from the variable; and instruct the computing device to execute the function definition corresponding to the command string. 12. The system of claim 11 , wherein the variable is a global variable. | 0.833333 |
4,866,638 | 1 | 3 | 1. A method of operating a computer system for generating a human-computer interface prototype, the computer system including a display and means for indicating an x,y location on the display and generating an asynchronous event, comprising the steps of: a. describing an interface prototype in a high-level graphics language having a command for describing a graphic object that creates a graphic item on the display and links a specific behavior to the graphic item in response to an asynchronous event occurring within the graphic item, the object being defined independently of the x,y location of the graphic item on the display; b. compiling the high-level graphic language description to produce an intermediate low level code optimized for interpretation; and c. interpreting the intermediate lowlevel code produced in the previous step to implement the prototype interface. | 1. A method of operating a computer system for generating a human-computer interface prototype, the computer system including a display and means for indicating an x,y location on the display and generating an asynchronous event, comprising the steps of: a. describing an interface prototype in a high-level graphics language having a command for describing a graphic object that creates a graphic item on the display and links a specific behavior to the graphic item in response to an asynchronous event occurring within the graphic item, the object being defined independently of the x,y location of the graphic item on the display; b. compiling the high-level graphic language description to produce an intermediate low level code optimized for interpretation; and c. interpreting the intermediate lowlevel code produced in the previous step to implement the prototype interface. 3. The method claimed in claim 1, further including the step of: creating graphic objects for use in the interface prototype with a graphic editor. | 0.739362 |
7,634,728 | 1 | 2 | 1. A processor-implemented method for providing a runtime environment comprising: transforming a passive document into a first active document by creating a first shell exclusively for the first active document; wherein the first shell surrounds the first active document, and comprises: an executable code that provides management and connectivity features to the first active document; and an interface to provide access to the first active document; registering the first shell with a first helper upon activation of the first shell; wherein the first shell has a computational power that is substantially smaller than a computational power of the first helper; wherein the first helper provides to the first shell, at least some of the processing power of the first helper; wherein the first helper selectively performs, on demand, at least some of the tasks on behalf of the first shell; wherein the first shell operates in the runtime environment to coordinate the management and connectivity features and to distribute tasks; wherein the first active document is processable as a process rather than a passive document; and wherein the first active document gradually collects additional data and state information. | 1. A processor-implemented method for providing a runtime environment comprising: transforming a passive document into a first active document by creating a first shell exclusively for the first active document; wherein the first shell surrounds the first active document, and comprises: an executable code that provides management and connectivity features to the first active document; and an interface to provide access to the first active document; registering the first shell with a first helper upon activation of the first shell; wherein the first shell has a computational power that is substantially smaller than a computational power of the first helper; wherein the first helper provides to the first shell, at least some of the processing power of the first helper; wherein the first helper selectively performs, on demand, at least some of the tasks on behalf of the first shell; wherein the first shell operates in the runtime environment to coordinate the management and connectivity features and to distribute tasks; wherein the first active document is processable as a process rather than a passive document; and wherein the first active document gradually collects additional data and state information. 2. The method of claim 1 , further comprising the first shell sending a command to at least a second shell of a second active document. | 0.503676 |
8,438,648 | 1 | 3 | 1. A method, comprising: receiving, by a computing device, a request for a font file; determining whether the request is valid; in response to determining that the request is valid, embedding a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serving the font file. | 1. A method, comprising: receiving, by a computing device, a request for a font file; determining whether the request is valid; in response to determining that the request is valid, embedding a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serving the font file. 3. The method of claim 1 , wherein determining whether the request is valid includes evaluating a security token. | 0.88745 |
9,390,630 | 1 | 2 | 1. An apparatus, comprising: at least one processors; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following; detect a change in position of a body member of a performer relative to a performance element of a performance object with which an event is to be performed; generate a signal dependent on the detected change in position of the body member; record the signal so that a first sensory cue can be determined to indicate the change in position of the body member relative to the element of the performance object during a learning session; determine the first sensory cue dependent on the recorded signal; and apply the first sensory cue to indicate to a user during the learning session the change in position of the body member of the performer during the performance of the event, the first sensory cue being effective for stimulating a first processing center of a brain of the user, wherein the first sensory cue is an applied electrical signal dependent on the recorded signal effective to stimulate at least one of muscles and nerves of the user during the learning session to indicate to the user the position of the body member of the performer during the performance. | 1. An apparatus, comprising: at least one processors; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following; detect a change in position of a body member of a performer relative to a performance element of a performance object with which an event is to be performed; generate a signal dependent on the detected change in position of the body member; record the signal so that a first sensory cue can be determined to indicate the change in position of the body member relative to the element of the performance object during a learning session; determine the first sensory cue dependent on the recorded signal; and apply the first sensory cue to indicate to a user during the learning session the change in position of the body member of the performer during the performance of the event, the first sensory cue being effective for stimulating a first processing center of a brain of the user, wherein the first sensory cue is an applied electrical signal dependent on the recorded signal effective to stimulate at least one of muscles and nerves of the user during the learning session to indicate to the user the position of the body member of the performer during the performance. 2. An apparatus according to claim 1 ; wherein the body member is at least one of a hand and at least one finger of the performer; and wherein the event is piece of music to be performed on a musical instrument, the performance object is the musical instrument and the performance element is at least one of a key, a string and a valve of the musical instrument. | 0.926602 |
8,463,770 | 1 | 6 | 1. A system, comprising: a memory comprising program instructions; and one or more processors coupled to said memory, wherein the program instructions are executable by at least one of said one or more processors to implement a search result conditioning component configured to: determine a search result group comprising a plurality of search results, wherein the plurality of search results are results of a search query, wherein the search result group includes a connected graph comprising multiple nodes and multiple edges each connecting a distinct pair of nodes, wherein each node represents a search result of said plurality of search results, wherein each node includes a search result identifier that is different than the other nodes of the multiple nodes, wherein each edge indicates the pair of nodes connected by that edge are similar search results with a measure of similarity between the pair of nodes greater than a requisite measure of similarity; for each node representing a given search result of the search result group: apply one or more similarity criteria to each of the multiple nodes of the connected graph to identify a respective similar group of nodes that are similar to the given search result; sort the nodes of the similar group of nodes and the node representing the given search result into an order based on the respective search result identifiers of the nodes of the similar group of nodes and the node representing the given search result such that each sorted group includes a respective first node occurring before the one or more other nodes within the order of the sorted group; and responsive to the order of nodes resulting from the sort, label the given search result with the search result identifier of the respective first node from the sorted similar group of nodes; wherein at least some search results of the search result group are assigned the same label; modify the search result group, wherein to modify the search result group the search result conditioning component is configured to remove at least one search result from the search result group dependent upon the label assigned to the at least one search result being shared with at least one other search result of the search result group; and output the modified search result group. | 1. A system, comprising: a memory comprising program instructions; and one or more processors coupled to said memory, wherein the program instructions are executable by at least one of said one or more processors to implement a search result conditioning component configured to: determine a search result group comprising a plurality of search results, wherein the plurality of search results are results of a search query, wherein the search result group includes a connected graph comprising multiple nodes and multiple edges each connecting a distinct pair of nodes, wherein each node represents a search result of said plurality of search results, wherein each node includes a search result identifier that is different than the other nodes of the multiple nodes, wherein each edge indicates the pair of nodes connected by that edge are similar search results with a measure of similarity between the pair of nodes greater than a requisite measure of similarity; for each node representing a given search result of the search result group: apply one or more similarity criteria to each of the multiple nodes of the connected graph to identify a respective similar group of nodes that are similar to the given search result; sort the nodes of the similar group of nodes and the node representing the given search result into an order based on the respective search result identifiers of the nodes of the similar group of nodes and the node representing the given search result such that each sorted group includes a respective first node occurring before the one or more other nodes within the order of the sorted group; and responsive to the order of nodes resulting from the sort, label the given search result with the search result identifier of the respective first node from the sorted similar group of nodes; wherein at least some search results of the search result group are assigned the same label; modify the search result group, wherein to modify the search result group the search result conditioning component is configured to remove at least one search result from the search result group dependent upon the label assigned to the at least one search result being shared with at least one other search result of the search result group; and output the modified search result group. 6. The system of claim 1 , wherein the search result conditioning component is configured to receive said search query from an electronic marketplace interface configured to serve a plurality of clients, wherein said search result conditioning component is configured to provide the modified search result group to said electronic marketplace interface. | 0.705342 |
8,938,441 | 1 | 5 | 1. A computer-implemented method comprising: receiving a web page that includes text and images; selecting a first subset of the images that are not excluded content-type images, wherein an excluded content-type image is an image that is boilerplate content or that is advertising content; determining, for each of the images in the first subset, (I) whether the image has a size ratio that is within a predetermined size ratio range, (II) whether the image has greater than a predetermined quantity of pixels, or (III) whether the image is located between a defined minimum altitude and a defined maximum altitude on the web page; selecting a second subset of the images in the first subset based on the determinations for the images in the first subset; determining (i) a quantity of images in the second subset, and (ii) a ratio of the area of the web page that is covered by the images of the second subset to the total area of the web page; generating a score for the web page based at least on (i) the quantity of the images in the second subset, and (ii) the ratio of the area of the web page that is covered by the images to the total area of the web page; classifying the web page as a gallery web page based on the score for the web page meeting a predefined threshold; and based on classifying the web page as a gallery web page, formatting a search result that references the web page, among a set of search results that each reference a different web page, using a search result format that is designated for web pages that are classified as gallery web pages. | 1. A computer-implemented method comprising: receiving a web page that includes text and images; selecting a first subset of the images that are not excluded content-type images, wherein an excluded content-type image is an image that is boilerplate content or that is advertising content; determining, for each of the images in the first subset, (I) whether the image has a size ratio that is within a predetermined size ratio range, (II) whether the image has greater than a predetermined quantity of pixels, or (III) whether the image is located between a defined minimum altitude and a defined maximum altitude on the web page; selecting a second subset of the images in the first subset based on the determinations for the images in the first subset; determining (i) a quantity of images in the second subset, and (ii) a ratio of the area of the web page that is covered by the images of the second subset to the total area of the web page; generating a score for the web page based at least on (i) the quantity of the images in the second subset, and (ii) the ratio of the area of the web page that is covered by the images to the total area of the web page; classifying the web page as a gallery web page based on the score for the web page meeting a predefined threshold; and based on classifying the web page as a gallery web page, formatting a search result that references the web page, among a set of search results that each reference a different web page, using a search result format that is designated for web pages that are classified as gallery web pages. 5. The method of claim 1 , further comprising determining that the score for the web page meets a predefined threshold; wherein the web page is classified as a gallery web page in response to determining that the score for the web page meets the predefined threshold. | 0.722453 |
9,507,932 | 5 | 7 | 5. The apparatus of claim 1 , wherein, to assign the respective classifications to the topology elements, the processor is configured to: select one of the topology elements from topology element information determined from the topology information; identify, from the set of topology abstraction policies, one of the topology abstraction policies with which the one of the topology elements is associated; and assign the respective classification to the one of the topology elements based on evaluation of one or more policy rules of the one of the topology abstraction policies with which the one of the topology elements is associated. | 5. The apparatus of claim 1 , wherein, to assign the respective classifications to the topology elements, the processor is configured to: select one of the topology elements from topology element information determined from the topology information; identify, from the set of topology abstraction policies, one of the topology abstraction policies with which the one of the topology elements is associated; and assign the respective classification to the one of the topology elements based on evaluation of one or more policy rules of the one of the topology abstraction policies with which the one of the topology elements is associated. 7. The apparatus of claim 5 , wherein, to assign the respective classification to the one of the topology elements based on evaluation of one or more policy rules of the one of the topology abstraction policies with which the one of the topology elements is associated, the processor is configured to: identify one of the policy rules, of the one of the topology abstraction policies, having a condition satisfied by the one of the topology elements; and assign the respective classification to the one of the topology elements based on an action associated with the one of the policy rules, of the one of the topology abstraction policies, having the condition satisfied by the one of the topology elements. | 0.770428 |
7,966,304 | 1 | 5 | 1. A method of performing a search over a network, comprising: sending, from a mobile device to a server, a search request message that comprises at least one search term comprising an abbreviation, wherein the server associates context information with the at least one search term, and wherein the abbreviation is operative as a partial index; determining an interim result corresponding to the abbreviation by indexing the abbreviation into a partial index, the interim result comprising a name; and providing a result to the mobile device based on at least the interim result and the context information. | 1. A method of performing a search over a network, comprising: sending, from a mobile device to a server, a search request message that comprises at least one search term comprising an abbreviation, wherein the server associates context information with the at least one search term, and wherein the abbreviation is operative as a partial index; determining an interim result corresponding to the abbreviation by indexing the abbreviation into a partial index, the interim result comprising a name; and providing a result to the mobile device based on at least the interim result and the context information. 5. The method of claim 1 , wherein the context information comprises an area code for a telephone number associated with the mobile device. | 0.913233 |
9,135,915 | 15 | 17 | 15. An article of manufacture including a non-transitory computer-readable medium having instructions stored thereon that, when executed by a computing device, cause the computing device to perform functions comprising: receiving audio data representative of audio detected by a microphone, wherein the microphone is positioned on a head-mountable device (HMD); determining whether the received audio data comprises audio speech data in an audio-channel speech band or audio non-speech data outside the audio-channel speech band; receiving vibration data representative of vibrations detected by a sensor other than the microphone, wherein the sensor is positioned on the HMD; determining a degree of spectral coherency, with respect to a threshold, between the audio data and the vibration data; determining whether or not the audio data is causally related to the vibration data based on the determined degree of spectral coherency; and if the received audio data both: (a) comprises audio speech data in an audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then generating an indication that the audio data contains HMD-wearer speech and conditioning at least one of the audio data and the vibration data as speech data, wherein the conditioning comprises amplifying at least one of the audio data and the vibration; if the received audio data both: (a) comprises audio non-speech data outside the audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then conditioning at least one of the audio data and the vibration data as coherent non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data; and otherwise, determining that the received audio data and the vibration data are non-coherent and conditioning at least one of the audio data and the vibration data as non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data. | 15. An article of manufacture including a non-transitory computer-readable medium having instructions stored thereon that, when executed by a computing device, cause the computing device to perform functions comprising: receiving audio data representative of audio detected by a microphone, wherein the microphone is positioned on a head-mountable device (HMD); determining whether the received audio data comprises audio speech data in an audio-channel speech band or audio non-speech data outside the audio-channel speech band; receiving vibration data representative of vibrations detected by a sensor other than the microphone, wherein the sensor is positioned on the HMD; determining a degree of spectral coherency, with respect to a threshold, between the audio data and the vibration data; determining whether or not the audio data is causally related to the vibration data based on the determined degree of spectral coherency; and if the received audio data both: (a) comprises audio speech data in an audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then generating an indication that the audio data contains HMD-wearer speech and conditioning at least one of the audio data and the vibration data as speech data, wherein the conditioning comprises amplifying at least one of the audio data and the vibration; if the received audio data both: (a) comprises audio non-speech data outside the audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then conditioning at least one of the audio data and the vibration data as coherent non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data; and otherwise, determining that the received audio data and the vibration data are non-coherent and conditioning at least one of the audio data and the vibration data as non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data. 17. The article of manufacture of claim 15 , wherein the functions further comprise: in response to determining that the audio speech data is causally related to the vibration speech data, providing the audio speech data and/or the vibration speech data to a speech recognizer. | 0.501799 |
4,724,523 | 44 | 46 | 44. A method according to claim 41 in which said second pattern storing step comprises storing a signal representative of at least one of a partial verbal paradigm and a partial nominal paradigm. | 44. A method according to claim 41 in which said second pattern storing step comprises storing a signal representative of at least one of a partial verbal paradigm and a partial nominal paradigm. 46. A method according to claim 44 in which said partial paradigm storing step comprises storing a signal representative of a nominal suffix pattern. | 0.95755 |
8,725,752 | 7 | 9 | 7. A method for indexing advertisements in order to match an advertisement to a webpage, the method comprising: receiving click-through rate (CTR) data for an advertisement; extracting an advertisement feature from the advertisement and a webpage feature from the webpage that are relevant to each other, via a variable selection technique that includes at least one of: selection of the advertisement feature and the webpage feature using CTR data and views of the advertisement, or selection of the advertisement feature and the webpage feature using relevance scores of words of the advertisement that are independent of click feedback; calculating a coefficient representative of the relevancy between the advertisement feature and the webpage feature; computing a static score for the advertisement by using the CTR data and the coefficient as input to a logistic regression function, wherein the static score provides relevance of the advertisement feature with respect to the webpage feature, and wherein the logistic regression function uses a monotonically increasing linear function; generating a unique identification for the advertisement feature; and generating a unique advertisement identification for the advertisement according to the static score relative to other advertisements. | 7. A method for indexing advertisements in order to match an advertisement to a webpage, the method comprising: receiving click-through rate (CTR) data for an advertisement; extracting an advertisement feature from the advertisement and a webpage feature from the webpage that are relevant to each other, via a variable selection technique that includes at least one of: selection of the advertisement feature and the webpage feature using CTR data and views of the advertisement, or selection of the advertisement feature and the webpage feature using relevance scores of words of the advertisement that are independent of click feedback; calculating a coefficient representative of the relevancy between the advertisement feature and the webpage feature; computing a static score for the advertisement by using the CTR data and the coefficient as input to a logistic regression function, wherein the static score provides relevance of the advertisement feature with respect to the webpage feature, and wherein the logistic regression function uses a monotonically increasing linear function; generating a unique identification for the advertisement feature; and generating a unique advertisement identification for the advertisement according to the static score relative to other advertisements. 9. The method of claim 7 , wherein the advertisement feature or the webpage feature includes a phrase. | 0.826531 |
9,460,155 | 11 | 12 | 11. The contextual user engagement method of claim 10 , wherein the entity queried for additional information relevant to the system utterance comprises at least one of an SQL database, an application programming interface, an enterprise system connector or an engine for analyzing unstructured data. | 11. The contextual user engagement method of claim 10 , wherein the entity queried for additional information relevant to the system utterance comprises at least one of an SQL database, an application programming interface, an enterprise system connector or an engine for analyzing unstructured data. 12. The contextual user engagement method of claim 11 , wherein the inference rule comprises one or more functions that obtains a premise, analyzes a syntax of the premise, and returns one or more conclusions. | 0.957846 |
8,813,043 | 1 | 7 | 1. A memory coupled to a processor, the memory having stored thereon computer executable instructions causing the processor to execute a process, the process comprising: translating a program code to a logical representation that includes type-safety assertions by asserting at least one type-safety invariant at one or more program points of the logical representation, wherein the at least one type-safety invariant states that a memory location is well-typed such that a value at the memory location corresponds to a type declared for the memory location, and wherein the type-safety assertions include a portion containing user-defined types input directly into the logical representation, and wherein the translating of the program code comprises translating the program code other than the user-defined types into the logical representation; generating a verification condition from the translated program code; if the generated verification condition includes one or more universal quantifiers, removing the one or more universal quantifiers from the generated verification condition; and executing a decision procedure to prove or disprove the generated verification condition. | 1. A memory coupled to a processor, the memory having stored thereon computer executable instructions causing the processor to execute a process, the process comprising: translating a program code to a logical representation that includes type-safety assertions by asserting at least one type-safety invariant at one or more program points of the logical representation, wherein the at least one type-safety invariant states that a memory location is well-typed such that a value at the memory location corresponds to a type declared for the memory location, and wherein the type-safety assertions include a portion containing user-defined types input directly into the logical representation, and wherein the translating of the program code comprises translating the program code other than the user-defined types into the logical representation; generating a verification condition from the translated program code; if the generated verification condition includes one or more universal quantifiers, removing the one or more universal quantifiers from the generated verification condition; and executing a decision procedure to prove or disprove the generated verification condition. 7. The memory according to claim 1 , further comprising function pointer types added to the logical representation, the function pointer types comprising argument types, return types, preconditions, and postconditions. | 0.748268 |
7,912,846 | 1 | 6 | 1. A document processing method executed by a system established on one or more computers, the method comprising: acquiring a first structured document, including a plurality of document elements forming a structure, from a folder among a group of folders, the group of folders having a hierarchical structure in a document database; acquiring information of the hierarchical structure of the folders in the document database; creating integrated structure information by merging the structure of the document elements of the first structured document into a position of a folder, in the hierarchical structure formed by the folders, in which the first structured document is stored; adding a uniform resource locator attribute, created on the basis of an identification attribute of each folder or each document element in the integrated structure information, to the folder or the document element; and applying a template to the integrated structure information wherein in the process of applying the template to the integrated structure information, the uniform resource locator attribute added to each folder or document element is assigned to a corresponding variable in the template, and as a file name, the uniform resource locator attribute is attached to a file obtained by applying the template to the folder or the document element in the integrated structure information; wherein in the process of applying the template to the integrated structure information, a parse tree is determined by parsing a structure formed by elements of the template, a folder or a document element in the integrated structure information that matches the element in the template is determined through a matching process of the structure around the current element in the integrated structure information and the parse tree, and information of the matching folder or the matching document element in the integrated structure information is supplied to each element of the template, the template includes a string of one or more template elements and each template element of the string is an element of one of the types of a group including a text element, a variable element, a repetition element, and a selection element. | 1. A document processing method executed by a system established on one or more computers, the method comprising: acquiring a first structured document, including a plurality of document elements forming a structure, from a folder among a group of folders, the group of folders having a hierarchical structure in a document database; acquiring information of the hierarchical structure of the folders in the document database; creating integrated structure information by merging the structure of the document elements of the first structured document into a position of a folder, in the hierarchical structure formed by the folders, in which the first structured document is stored; adding a uniform resource locator attribute, created on the basis of an identification attribute of each folder or each document element in the integrated structure information, to the folder or the document element; and applying a template to the integrated structure information wherein in the process of applying the template to the integrated structure information, the uniform resource locator attribute added to each folder or document element is assigned to a corresponding variable in the template, and as a file name, the uniform resource locator attribute is attached to a file obtained by applying the template to the folder or the document element in the integrated structure information; wherein in the process of applying the template to the integrated structure information, a parse tree is determined by parsing a structure formed by elements of the template, a folder or a document element in the integrated structure information that matches the element in the template is determined through a matching process of the structure around the current element in the integrated structure information and the parse tree, and information of the matching folder or the matching document element in the integrated structure information is supplied to each element of the template, the template includes a string of one or more template elements and each template element of the string is an element of one of the types of a group including a text element, a variable element, a repetition element, and a selection element. 6. The document processing method according to claim 1 , further comprising: adding, as an access information attribute, access information created based on the identification attribute of a folder or a document element in the integrated structure information and information for specifying a template, for each template when application of a plurality of templates are instructed for the folder or the document element, wherein in the process of applying the template to the integrated structure information, each template is applied to the folder or the document element in the integrated structure information and data obtained by applying the templates to the folder or the document element in the integrated structure information are stored to allow access through the access information. | 0.761288 |
10,146,769 | 1 | 3 | 1. A method comprising: receiving, from a client device of a user, textual feedback associated with a metadata and a provider, the textual feedback including a plurality of words, the textual feedback describing a transportation service provided by the provider for the user; determining a feature vector for the textual feedback by characterizing the plurality of words and the metadata; determining a first safety sub-score by applying the feature vector to a first classifier associated with a first category of safety risk, the first classifier being a machine learning model trained using a first training feature vector characterizing a first set of textual feedback associated with the first category of safety risk; determining a second safety sub-score by applying the feature vector to a second classifier associated with a second category of safety risk different than the first category of safety risk, the second classifier being a different machine learning model trained using a second training feature vector characterizing a second set of textual feedback associated with the second category of safety risk; and determining a safety score for the provider using a third classifier based, at least in part, on the first safety sub-score and the second safety sub-score. | 1. A method comprising: receiving, from a client device of a user, textual feedback associated with a metadata and a provider, the textual feedback including a plurality of words, the textual feedback describing a transportation service provided by the provider for the user; determining a feature vector for the textual feedback by characterizing the plurality of words and the metadata; determining a first safety sub-score by applying the feature vector to a first classifier associated with a first category of safety risk, the first classifier being a machine learning model trained using a first training feature vector characterizing a first set of textual feedback associated with the first category of safety risk; determining a second safety sub-score by applying the feature vector to a second classifier associated with a second category of safety risk different than the first category of safety risk, the second classifier being a different machine learning model trained using a second training feature vector characterizing a second set of textual feedback associated with the second category of safety risk; and determining a safety score for the provider using a third classifier based, at least in part, on the first safety sub-score and the second safety sub-score. 3. The method of claim 1 , wherein the feature vector characterizes the plurality of words and the metadata using a plurality of dimensions associated with the plurality of words and one or more dimensions associated with the metadata. | 0.827713 |
4,689,737 | 1 | 2 | 1. A computer system including a memory and comprising: (a) means for the input of textual information; (b) means for the display of textual information; (c) a display manager associated with said text input means for receiving text therefrom, and further associated with said text display means for the perceptual representation of the text received from said text input means on a given one of one or more display levels, said levels being perceptually plane parallel successively posteriorly positioned with respect to a first given level; (d) an input text buffer associated with said text input means for receiving text therefrom; (e) a parser associated with said input buffer for periodically receiving text accumulated by said input text buffer and preparing an input text segment therefrom; (f) a list buffer including a plurality of synonymic text segments; and (g) a plurality of operative task elements stored in the memory, each associated with at least one of said synonymic text segments of said list buffer, said parser including a list processor for comparing said input text segment with said synonymic text segments and for causing performance of the task element associated with the synonymic text segment that corresponds to said input text segment, each of said task elements being further associated with said display manager whereby text provided by performed task elements is directed to and perceptually represented on said posterior display levels. | 1. A computer system including a memory and comprising: (a) means for the input of textual information; (b) means for the display of textual information; (c) a display manager associated with said text input means for receiving text therefrom, and further associated with said text display means for the perceptual representation of the text received from said text input means on a given one of one or more display levels, said levels being perceptually plane parallel successively posteriorly positioned with respect to a first given level; (d) an input text buffer associated with said text input means for receiving text therefrom; (e) a parser associated with said input buffer for periodically receiving text accumulated by said input text buffer and preparing an input text segment therefrom; (f) a list buffer including a plurality of synonymic text segments; and (g) a plurality of operative task elements stored in the memory, each associated with at least one of said synonymic text segments of said list buffer, said parser including a list processor for comparing said input text segment with said synonymic text segments and for causing performance of the task element associated with the synonymic text segment that corresponds to said input text segment, each of said task elements being further associated with said display manager whereby text provided by performed task elements is directed to and perceptually represented on said posterior display levels. 2. The system of claim 1 further characterized in that said input text buffer is further associated with said display manager whereby the text received from said text input means is directed to and perceptually represented on said first given display level. | 0.501938 |
8,060,489 | 1 | 10 | 1. A computer-implemented method for realizing a virtual bookshelf, comprising: initiating a search query to locate one or more desired books in either physical or soft copy digital form; producing search metadata corresponding to the one or more desired books; filtering metadata corresponding to books contained within the virtual bookshelf with the search metadata to determine whether the one or more desired books is present in the virtual bookshelf, wherein the virtual bookshelf comprises information representing books, in either physical or soft copy digital form, acquired by and particular to a user; and outputting results of the filtering indicative of whether the one or more desired books is present on the virtual bookshelf. | 1. A computer-implemented method for realizing a virtual bookshelf, comprising: initiating a search query to locate one or more desired books in either physical or soft copy digital form; producing search metadata corresponding to the one or more desired books; filtering metadata corresponding to books contained within the virtual bookshelf with the search metadata to determine whether the one or more desired books is present in the virtual bookshelf, wherein the virtual bookshelf comprises information representing books, in either physical or soft copy digital form, acquired by and particular to a user; and outputting results of the filtering indicative of whether the one or more desired books is present on the virtual bookshelf. 10. The computer-implemented method of claim 1 , further comprising: allowing the user to expand the search query to virtual bookshelves of an on-line community that the user has access rights to search. | 0.741071 |
8,438,648 | 1 | 2 | 1. A method, comprising: receiving, by a computing device, a request for a font file; determining whether the request is valid; in response to determining that the request is valid, embedding a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serving the font file. | 1. A method, comprising: receiving, by a computing device, a request for a font file; determining whether the request is valid; in response to determining that the request is valid, embedding a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serving the font file. 2. The method of claim 1 , further comprising: embedding a second watermark in the font file at least by inserting one or more data tables into one or more data structures of the font file, wherein the one or more data tables include a customer identifier. | 0.74502 |
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