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7,617,224 | 1 | 3 | 1. A method for managing hierarchically related software components, comprising: creating a first software component descriptor containing information about a first software component of a plurality of software components; creating a second software component descriptor containing information about a second software component of the plurality of software components; creating a plurality of aggregate descriptors, each descriptor containing information about relationships among the plurality of software components and aggregates of the plurality of software components; defining hierarchical interrelationships between the plurality of software components and the aggregate descriptors to produce a component hierarchy; managing lifecycles, access controls, interrelationships, versioning and a list of the plurality of software components to maintain the consistency of the component hierarchy; filtering the list of software components based upon the component hierarchy to produce a filtered list of software components; selecting a particular software component from the filtered list of software components; and integrating the particular software component into a software application; and modifying the component hierarchy based upon associations generated by the filtering. | 1. A method for managing hierarchically related software components, comprising: creating a first software component descriptor containing information about a first software component of a plurality of software components; creating a second software component descriptor containing information about a second software component of the plurality of software components; creating a plurality of aggregate descriptors, each descriptor containing information about relationships among the plurality of software components and aggregates of the plurality of software components; defining hierarchical interrelationships between the plurality of software components and the aggregate descriptors to produce a component hierarchy; managing lifecycles, access controls, interrelationships, versioning and a list of the plurality of software components to maintain the consistency of the component hierarchy; filtering the list of software components based upon the component hierarchy to produce a filtered list of software components; selecting a particular software component from the filtered list of software components; and integrating the particular software component into a software application; and modifying the component hierarchy based upon associations generated by the filtering. 3. The method of claim 1 , wherein the hierarchical interrelationships are defined based upon associations among the plurality of software components and the aggregate descriptors. | 0.648438 |
9,838,444 | 1 | 3 | 1. A method comprising: providing to a user device access to a document via a network; receiving an indication of a first locale of the user device, the first locale being associated with a first language; detecting an update to a language associated with the document in response to receiving an indication that the locale of the user device has changed, since the last time the user device accessed the document, from the first locale to a second locale, the second locale being different from the first locale and being associated with a second language different from the first language; determining fonts associated with the update to the language; comparing the fonts determined to be associated with the update to the language to a font list received from the user device to determine that at least one of the fonts associated with the update to the language is not available on the user device; and providing the at least one of the fonts associated with the update to the language that is not available on the user device to the user device, wherein when text is added to the document by a second user device that is coupled to the user device via the network, during simultaneous editing of the document by the user device and the second user device, and the text is indicative of a font that is not available on the user device, the method further comprises providing the font to the user device. | 1. A method comprising: providing to a user device access to a document via a network; receiving an indication of a first locale of the user device, the first locale being associated with a first language; detecting an update to a language associated with the document in response to receiving an indication that the locale of the user device has changed, since the last time the user device accessed the document, from the first locale to a second locale, the second locale being different from the first locale and being associated with a second language different from the first language; determining fonts associated with the update to the language; comparing the fonts determined to be associated with the update to the language to a font list received from the user device to determine that at least one of the fonts associated with the update to the language is not available on the user device; and providing the at least one of the fonts associated with the update to the language that is not available on the user device to the user device, wherein when text is added to the document by a second user device that is coupled to the user device via the network, during simultaneous editing of the document by the user device and the second user device, and the text is indicative of a font that is not available on the user device, the method further comprises providing the font to the user device. 3. The method of claim 1 , further comprising one of: determining new fonts associated with the update to the language; determining that at least one of the new fonts is not available on the user device; and providing the at least one of the new fonts to the user device. | 0.5 |
7,774,189 | 1 | 10 | 1. A computer-implemented method for simulating data flow using a dataflow computing system, the method comprising: a dataflow diagram that includes a plurality of operators, wherein each of the operators includes at least one input port or at least one output port; a plurality of arcs, wherein each of the arcs connects one of the output ports of one of the plurality operators to one of the input ports of a different one of the plurality of operators; a plurality of data items that flow in streams along the plurality of arcs between the plurality of operators; grouping the plurality of data items into a particle at a first operator included in the plurality of operators to form a particle grouping, wherein the first operator includes meta ports, wherein the meta ports include an arc-level meta port and a particle-level meta port, wherein the arc-level meta-port provides an arc-level meta-state that holds the state execution from a process initialization point to a process termination point, and wherein the particle-level meta-port provides a particle-level meta-state that provides an execution state of an input particle at any given point of time; performing, at the first operator, computations on the particle grouping, resulting in a computed plurality of data items; transmitting, from the first operator, the computed plurality of data items over one of the plurality of arcs to a second operator included in the plurality of operators; producing control data items at one of the meta ports included on the first operator based upon meta-state transitions that are in response to the computations performed by the first operator on the particle grouping; and transmitting the control data items from the first operator to one of the plurality of operators, wherein the control data items control the flow of the computed plurality of data items. | 1. A computer-implemented method for simulating data flow using a dataflow computing system, the method comprising: a dataflow diagram that includes a plurality of operators, wherein each of the operators includes at least one input port or at least one output port; a plurality of arcs, wherein each of the arcs connects one of the output ports of one of the plurality operators to one of the input ports of a different one of the plurality of operators; a plurality of data items that flow in streams along the plurality of arcs between the plurality of operators; grouping the plurality of data items into a particle at a first operator included in the plurality of operators to form a particle grouping, wherein the first operator includes meta ports, wherein the meta ports include an arc-level meta port and a particle-level meta port, wherein the arc-level meta-port provides an arc-level meta-state that holds the state execution from a process initialization point to a process termination point, and wherein the particle-level meta-port provides a particle-level meta-state that provides an execution state of an input particle at any given point of time; performing, at the first operator, computations on the particle grouping, resulting in a computed plurality of data items; transmitting, from the first operator, the computed plurality of data items over one of the plurality of arcs to a second operator included in the plurality of operators; producing control data items at one of the meta ports included on the first operator based upon meta-state transitions that are in response to the computations performed by the first operator on the particle grouping; and transmitting the control data items from the first operator to one of the plurality of operators, wherein the control data items control the flow of the computed plurality of data items. 10. The method of claim 1 further comprising: compiling the dataflow diagram into sequential executable code. | 0.872365 |
8,972,349 | 1 | 3 | 1. In a general purpose computer, a method for automatically testing a business intelligence artifact in a business intelligence system, comprising: authoring a business intelligence artifact in the business intelligence system, wherein the business intelligence artifact produces output when the business intelligence artifact is executed in the business intelligence system, and wherein the business intelligence artifact is selected from the group consisting of: a report specification, an analysis cube, and a metadata model; creating at least one assertion to determine whether the business intelligence artifact is functioning properly; testing, with an automated agent interfaced with the business intelligence system, the business intelligence artifact to verify its proper functioning by determining whether the conditions of the at least one assertion are satisfied upon execution of the business intelligence artifact in the business intelligence system; reporting if the conditions of the at least one assertion are not satisfied upon execution of the business intelligence artifact in the business intelligence system; and recording one or more corrections made to the business intelligence artifact as a subsequent version of the business intelligence artifact. | 1. In a general purpose computer, a method for automatically testing a business intelligence artifact in a business intelligence system, comprising: authoring a business intelligence artifact in the business intelligence system, wherein the business intelligence artifact produces output when the business intelligence artifact is executed in the business intelligence system, and wherein the business intelligence artifact is selected from the group consisting of: a report specification, an analysis cube, and a metadata model; creating at least one assertion to determine whether the business intelligence artifact is functioning properly; testing, with an automated agent interfaced with the business intelligence system, the business intelligence artifact to verify its proper functioning by determining whether the conditions of the at least one assertion are satisfied upon execution of the business intelligence artifact in the business intelligence system; reporting if the conditions of the at least one assertion are not satisfied upon execution of the business intelligence artifact in the business intelligence system; and recording one or more corrections made to the business intelligence artifact as a subsequent version of the business intelligence artifact. 3. The method of claim 1 , further comprising executing the business intelligence artifact in the business intelligence system to generate a business intelligence output. | 0.604651 |
7,818,313 | 28 | 33 | 28. In a continuous computation system, a method for distributing processing of a query over a cluster of servers, where the query subscribes to at least one input data stream, the method comprising: determining whether input messages for the query can be partitioned into groups that can be processed independent of each other by analyzing the semantics of the query; and in response to determining that input messages for the query can be partitioned into groups that can be processed independent of each other: installing identical logic for processing the query on two of more servers in the cluster, wherein such logic is installed prior to processing input messages; continuously running the query logic on such servers; receiving, at the continuous computation system, streaming input messages on one or more data streams, wherein input messages can arrive continuously; distributing the input messages among such servers by such groups, wherein messages are distributed while the query is running; generating partial outputs for the query on such servers; and combining such partial outputs to generate output data for the query. | 28. In a continuous computation system, a method for distributing processing of a query over a cluster of servers, where the query subscribes to at least one input data stream, the method comprising: determining whether input messages for the query can be partitioned into groups that can be processed independent of each other by analyzing the semantics of the query; and in response to determining that input messages for the query can be partitioned into groups that can be processed independent of each other: installing identical logic for processing the query on two of more servers in the cluster, wherein such logic is installed prior to processing input messages; continuously running the query logic on such servers; receiving, at the continuous computation system, streaming input messages on one or more data streams, wherein input messages can arrive continuously; distributing the input messages among such servers by such groups, wherein messages are distributed while the query is running; generating partial outputs for the query on such servers; and combining such partial outputs to generate output data for the query. 33. The method of claim 28 , where, in generating the partial outputs, the query operates on the input messages in accordance with a row-based window. | 0.503311 |
8,886,540 | 5 | 11 | 5. A method of entering information into a software application other than a speech recognition application resident on a device using a processor, comprising: recording speech presented by a user using a device-resident capture facility; transmitting the recording through a wireless communication facility to a speech recognition facility; transmitting contextual information relating to the software application to the speech recognition facility; receiving results generated utilizing the speech recognition facility using an unstructured language model based, at least in part, on the contextual information relating to the software application and the recording, wherein the contextual information includes an identity of the mobile communication facility, an identity of a non-speech recognition application resident on the mobile communication facility and a usage history of the non-speech recognition application resident on the mobile communication facility, and wherein user feedback is used to adapt the unstructured language model; loading the results into the software application; and simultaneously displaying the results as a set of words and as a set of application results based on those words. | 5. A method of entering information into a software application other than a speech recognition application resident on a device using a processor, comprising: recording speech presented by a user using a device-resident capture facility; transmitting the recording through a wireless communication facility to a speech recognition facility; transmitting contextual information relating to the software application to the speech recognition facility; receiving results generated utilizing the speech recognition facility using an unstructured language model based, at least in part, on the contextual information relating to the software application and the recording, wherein the contextual information includes an identity of the mobile communication facility, an identity of a non-speech recognition application resident on the mobile communication facility and a usage history of the non-speech recognition application resident on the mobile communication facility, and wherein user feedback is used to adapt the unstructured language model; loading the results into the software application; and simultaneously displaying the results as a set of words and as a set of application results based on those words. 11. The method of claim 5 , wherein the application is an application which is searching for information or content based on the set of words. | 0.777429 |
6,154,757 | 4 | 16 | 4. A method for using a computer system to generate a supplemental reference document associated with a section of electronic text comprising: a. using a first wordlist comprising words present in at least one section of text; b. using at least one additional wordlist created independently of the wordlist of step a; c. performing at least one operation on the wordlists of steps a and b to generate another wordlist; d. storing information about each word in the wordlist of step c on the computer system, a portion of said information obtained from a reference distinct from said section of electronic text; and e. generating a supplemental reference document containing at least one word from the wordlist of step c together with the related information of step d, wherein said supplemental reference document comprises entries based on the wordlist of step c. | 4. A method for using a computer system to generate a supplemental reference document associated with a section of electronic text comprising: a. using a first wordlist comprising words present in at least one section of text; b. using at least one additional wordlist created independently of the wordlist of step a; c. performing at least one operation on the wordlists of steps a and b to generate another wordlist; d. storing information about each word in the wordlist of step c on the computer system, a portion of said information obtained from a reference distinct from said section of electronic text; and e. generating a supplemental reference document containing at least one word from the wordlist of step c together with the related information of step d, wherein said supplemental reference document comprises entries based on the wordlist of step c. 16. The method of claim 4, wherein the information of step d comprises at least one picture related to the word. | 0.706806 |
8,635,240 | 1 | 5 | 1. A user-interface method of incrementally providing fully qualified links to a set of relevant search engines implemented by a computer comprising at least one processor, the method comprising: identifying a set of search engines and associating each search engine of the set with at least one descriptive category to which the subject matter of the corresponding search engine relates; receiving a partial search query entered on a keypad by a user; after at least one keypress received from the user, inferring a set of potential full queries intended by the user, wherein the inferring the set of potential full queries includes determining suggested query refinements based at least in part on the partial search query; selecting a subset of the identified search engines that are relevant to at least one of the set of inferred full queries based on comparing the inferred full queries with the descriptive categories associated with the search engines; and for each of the selected search engines, providing a fully qualified link designed to directly launch a search for a relevant query using the search engine. | 1. A user-interface method of incrementally providing fully qualified links to a set of relevant search engines implemented by a computer comprising at least one processor, the method comprising: identifying a set of search engines and associating each search engine of the set with at least one descriptive category to which the subject matter of the corresponding search engine relates; receiving a partial search query entered on a keypad by a user; after at least one keypress received from the user, inferring a set of potential full queries intended by the user, wherein the inferring the set of potential full queries includes determining suggested query refinements based at least in part on the partial search query; selecting a subset of the identified search engines that are relevant to at least one of the set of inferred full queries based on comparing the inferred full queries with the descriptive categories associated with the search engines; and for each of the selected search engines, providing a fully qualified link designed to directly launch a search for a relevant query using the search engine. 5. The method of claim 1 further comprising presenting at least one of the fully qualified links to the user. | 0.813993 |
7,668,888 | 44 | 45 | 44. A computer for providing at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the computer comprising a processor for: extracting the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. | 44. A computer for providing at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the computer comprising a processor for: extracting the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. 45. The computer of claim 44 , further comprising first storage means for storage of the generic data model in tables. | 0.5 |
9,690,991 | 2 | 4 | 2. The mobile device of claim 1 , wherein the at least one hardware processor is further configurable to track the at least one scene object in the digital representation in real-time as a function of the recognition features. | 2. The mobile device of claim 1 , wherein the at least one hardware processor is further configurable to track the at least one scene object in the digital representation in real-time as a function of the recognition features. 4. The mobile device of claim 2 , wherein the at least one hardware processor is further configurable to track the at least one scene object at a frame rate of a video rendering of the AR content on the display. | 0.567623 |
9,009,192 | 24 | 25 | 24. The system of claim 23 , wherein each edge in the first entity graph represents that two nodes connected by an edge have a computed probability that respective entities associated with the two nodes would be associated with a same resource more frequently than two entities that are independent of each other. | 24. The system of claim 23 , wherein each edge in the first entity graph represents that two nodes connected by an edge have a computed probability that respective entities associated with the two nodes would be associated with a same resource more frequently than two entities that are independent of each other. 25. The system of claim 24 , the operations further comprising removing nodes from the second entity graph that do not have outgoing edges. | 0.5 |
9,165,183 | 1 | 6 | 1. An estimating apparatus comprising: a memory that stores computer executable instructions; and a processor, coupled to the memory, that executes the computer executable instructions to perform operations, comprising: acquiring an image; extracting human feature quantity from the image; calculating, from the feature quantity, a first likelihood which indicates a degree of likelihood that the feature quantity belongs to for each of attribute classes, which comprises segments of consecutive attribute values relating to a person; designating one of the attribute classes as a target class, designating two or more of the attribute classes near the target class as selected, and summing up the first likelihood of the target class and the first likelihoods of selected classes to obtain the second likelihood of the target class; specifying one of the attribute classes as a specific attribute class, which has the highest second likelihood, from among the second likelihoods respectively for the attribute classes; calculating an estimated attribute value of the specific attribute class and estimated attribute values of the selected classes by setting the specific attribute class as the target class, respectively by using the feature quantity; and applying the second likelihood of the specific attribute class on the estimated attribute value of the specific attribute class as a weight to obtain a first value, applying the second likelihoods of the selected classes respectively on the estimated attribute values of the selected classes as weights to obtain a second value, and summing up the first value and the second value to obtain a corrected attribute value of the specific attribute class. | 1. An estimating apparatus comprising: a memory that stores computer executable instructions; and a processor, coupled to the memory, that executes the computer executable instructions to perform operations, comprising: acquiring an image; extracting human feature quantity from the image; calculating, from the feature quantity, a first likelihood which indicates a degree of likelihood that the feature quantity belongs to for each of attribute classes, which comprises segments of consecutive attribute values relating to a person; designating one of the attribute classes as a target class, designating two or more of the attribute classes near the target class as selected, and summing up the first likelihood of the target class and the first likelihoods of selected classes to obtain the second likelihood of the target class; specifying one of the attribute classes as a specific attribute class, which has the highest second likelihood, from among the second likelihoods respectively for the attribute classes; calculating an estimated attribute value of the specific attribute class and estimated attribute values of the selected classes by setting the specific attribute class as the target class, respectively by using the feature quantity; and applying the second likelihood of the specific attribute class on the estimated attribute value of the specific attribute class as a weight to obtain a first value, applying the second likelihoods of the selected classes respectively on the estimated attribute values of the selected classes as weights to obtain a second value, and summing up the first value and the second value to obtain a corrected attribute value of the specific attribute class. 6. The apparatus according to claim 1 , further comprising selecting as the selected classes the attribute classes directly adjacent to the target class or the attribute classes that are distanced from the target class, by one to ten of the attribute classes. | 0.784526 |
8,739,066 | 6 | 9 | 6. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by at least one processor, cause the at least one processor to: receive a first document; identify links in a plurality of second documents that each include a link to the first document; determine a second document of the plurality of second documents that has been used to access the first document more frequently than any other second document of the plurality of second documents; extract concepts associated with the determined second document; and associate the extracted concepts with the first document, at least one extracted concept, of the extracted concepts, being associated with anchor text in the determined second document. | 6. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by at least one processor, cause the at least one processor to: receive a first document; identify links in a plurality of second documents that each include a link to the first document; determine a second document of the plurality of second documents that has been used to access the first document more frequently than any other second document of the plurality of second documents; extract concepts associated with the determined second document; and associate the extracted concepts with the first document, at least one extracted concept, of the extracted concepts, being associated with anchor text in the determined second document. 9. The non-transitory computer-readable medium of claim 6 , the instructions further comprising: one or more instructions that, when executed by at least one processor, cause the at least one processor to: identify links in the first document pointing from the first document to a plurality of third documents; determine a third document of the plurality of third documents that has been used to access the first document more frequently than any other third document of the plurality of third documents; extract other concepts associated with the determined third document; and associate the other concepts with the first document. | 0.5 |
9,400,790 | 6 | 7 | 6. The non-transitory computer-readable medium of claim 5 , wherein the operations further comprise receiving, from an information source, information about the user. | 6. The non-transitory computer-readable medium of claim 5 , wherein the operations further comprise receiving, from an information source, information about the user. 7. The non-transitory computer-readable medium of claim 6 , wherein the information about the user provided by the information source comprises information retrieval patterns of the user, information usage patterns of the user, demographics of the user, and locations associated with the user. | 0.5 |
9,401,138 | 1 | 7 | 1. A segment information generation device comprising: a waveform cutout unit implemented at least by hardware including a processor that cuts out a speech waveform from natural speech at a time period not depending on a pitch frequency of the natural speech, continuously; a feature parameter extraction unit implemented at least by hardware including a processor that extracts a feature parameter of a speech waveform from the speech waveform cut out by the waveform cutout unit; a time domain waveform generation unit implemented at least by hardware including a processor that generates a time domain waveform based on the feature parameter; a spectrum shape change degree estimation unit implemented at least by hardware including a processor that estimates a degree of change in spectrum shape indicating a degree of change in spectrum shape of natural speech; and a period control unit implemented at least by hardware including a processor that determines a time period to cut out a speech waveform from the natural speech based on the degree of change in spectrum shape. | 1. A segment information generation device comprising: a waveform cutout unit implemented at least by hardware including a processor that cuts out a speech waveform from natural speech at a time period not depending on a pitch frequency of the natural speech, continuously; a feature parameter extraction unit implemented at least by hardware including a processor that extracts a feature parameter of a speech waveform from the speech waveform cut out by the waveform cutout unit; a time domain waveform generation unit implemented at least by hardware including a processor that generates a time domain waveform based on the feature parameter; a spectrum shape change degree estimation unit implemented at least by hardware including a processor that estimates a degree of change in spectrum shape indicating a degree of change in spectrum shape of natural speech; and a period control unit implemented at least by hardware including a processor that determines a time period to cut out a speech waveform from the natural speech based on the degree of change in spectrum shape. 7. The segment information generation device according to claim 1 , further comprising: a spectrum shape change degree estimation unit comprising a processor that estimates a degree of change in spectrum shape indicating a degree of change in spectrum shape of natural speech. | 0.522491 |
9,286,061 | 1 | 4 | 1. A system comprising: one or more processors; and one or more storage media storing processor-executable instructions that, when executed by the one or more processors, configure the system to perform operations comprising: presenting a document in a documentation display area of a user interface; presenting a list of external components in a macro display area of the user interface that is adjacent to the documentation display area, wherein an individual external component is configured to access a particular type of external medical data of a plurality of different types of external medical data accessible via the list of external components; determining a patient identifier associated with the document; receiving input, within the macro display area, that selects an external component from the list of external components, wherein selection of the external component initiates a macro that provides instructions to launch the selected external component; launching, based at least in part on the macro, the selected external component in a launched external component display area of the user interface, the launched external component display area being presented contemporaneously with the documentation display area and the macro display area; providing, to the launched external component, component-specific context data associated with the document thereby enabling the launched external component to access, via at least one remote storage location, external medical data of a particular type for a patient identified by the patient identifier; displaying the accessed external medical data within the launched external component display area; processing user interactions associated with the accessed external medical data displayed within the launched external component display area, the user interactions modifying the accessed external medical data to produce modified external medical data; capturing a message sent from the launched external component to the at least one remote storage location, the message including at least a portion of the modified external medical data; and automatically rendering a portion of the document presented in the documentation display area based at least in part on the portion of the modified external medical data included in the captured message. | 1. A system comprising: one or more processors; and one or more storage media storing processor-executable instructions that, when executed by the one or more processors, configure the system to perform operations comprising: presenting a document in a documentation display area of a user interface; presenting a list of external components in a macro display area of the user interface that is adjacent to the documentation display area, wherein an individual external component is configured to access a particular type of external medical data of a plurality of different types of external medical data accessible via the list of external components; determining a patient identifier associated with the document; receiving input, within the macro display area, that selects an external component from the list of external components, wherein selection of the external component initiates a macro that provides instructions to launch the selected external component; launching, based at least in part on the macro, the selected external component in a launched external component display area of the user interface, the launched external component display area being presented contemporaneously with the documentation display area and the macro display area; providing, to the launched external component, component-specific context data associated with the document thereby enabling the launched external component to access, via at least one remote storage location, external medical data of a particular type for a patient identified by the patient identifier; displaying the accessed external medical data within the launched external component display area; processing user interactions associated with the accessed external medical data displayed within the launched external component display area, the user interactions modifying the accessed external medical data to produce modified external medical data; capturing a message sent from the launched external component to the at least one remote storage location, the message including at least a portion of the modified external medical data; and automatically rendering a portion of the document presented in the documentation display area based at least in part on the portion of the modified external medical data included in the captured message. 4. The system according to claim 1 , wherein the launched external component display area comprises a pop-up window within the user interface that enables the portion of the modified external medical data to be automatically rendered within the portion of the document. | 0.5 |
8,517,738 | 1 | 17 | 1. A computer-implemented method of text passage difficulty estimation, comprising: generating, using a computer processing system, an informational text scoring model, wherein generating the informational text scoring model includes: identifying a plurality of texts from a corpus of texts that are informational texts; determining one or more metrics for the informational texts; and configuring the informational text scoring model using the one or more informational text metrics; and generating, using a computer processing system, a literary text scoring model, wherein generating the literary text scoring model includes: identifying a plurality of texts from the corpus of texts that are literary texts; determining one or more metrics for the literary texts, wherein the literary text metrics include one or more metrics that are not included in the informational text metrics; and configuring the literary text scoring model using the one or more literary text metrics, wherein for an input text passage: a set of text variation measures are computed including a text genre metric; the informational text scoring model or the literary text scoring model is selected based on the text genre metric; and a difficulty estimate and a plurality of text variation dimension sub-scores are determined using the selected model; when the difficulty estimate is within an acceptable range of a desired test difficulty level, the input text passage is selected for a test; when the difficulty estimate is outside of the acceptable range of the desired test difficulty level, the input text passage is iteratively adapted using a particular one of a plurality of adaptation strategies prior to being selected for the test, wherein the particular adaptation strategy is selected based on which of the text variation dimension sub-scores is furthest from the desired test difficulty level. | 1. A computer-implemented method of text passage difficulty estimation, comprising: generating, using a computer processing system, an informational text scoring model, wherein generating the informational text scoring model includes: identifying a plurality of texts from a corpus of texts that are informational texts; determining one or more metrics for the informational texts; and configuring the informational text scoring model using the one or more informational text metrics; and generating, using a computer processing system, a literary text scoring model, wherein generating the literary text scoring model includes: identifying a plurality of texts from the corpus of texts that are literary texts; determining one or more metrics for the literary texts, wherein the literary text metrics include one or more metrics that are not included in the informational text metrics; and configuring the literary text scoring model using the one or more literary text metrics, wherein for an input text passage: a set of text variation measures are computed including a text genre metric; the informational text scoring model or the literary text scoring model is selected based on the text genre metric; and a difficulty estimate and a plurality of text variation dimension sub-scores are determined using the selected model; when the difficulty estimate is within an acceptable range of a desired test difficulty level, the input text passage is selected for a test; when the difficulty estimate is outside of the acceptable range of the desired test difficulty level, the input text passage is iteratively adapted using a particular one of a plurality of adaptation strategies prior to being selected for the test, wherein the particular adaptation strategy is selected based on which of the text variation dimension sub-scores is furthest from the desired test difficulty level. 17. The method of claim 1 wherein the difficulty estimate is adjusted according to whether the impact of text cohesion variation is reduced, as in an informational genre, and whether the impact of text cohesion variation is increased, as in a literary genre. | 0.571429 |
7,860,968 | 1 | 19 | 1. A hierarchical, multi-tiered mapping and monitoring system usable with device networks, the system comprising: a service repository configured to store: a global service that is configured to track global device metadata associated with at least one device network; a local service that is configured to track local device metadata associated with the at least one device network and to update the global device metadata based thereon; a group leader service that is configured to query devices of the at least one device network and aggregate group-level device metadata for transmission to the local service and updating of the local device metadata; and a service mapper that is configured to associate service metadata of the global service, the local service, and the group leader service, respectively, with device metadata of at least one global device, at least one local device, and at least one group leader device, also respectively, and to perform a mapping of the services to the respective devices, based thereon, wherein the global service, the local service, and the group leader service are associated, respectively, with a global service monitor component, a local service monitor component, and a group leader service monitor component, respectively, and wherein the service monitor components are configured to provide monitor data associated with the at least one device network to the service mapper, the service mapper being configured to map a device network service to at least one device of the at least one device network. | 1. A hierarchical, multi-tiered mapping and monitoring system usable with device networks, the system comprising: a service repository configured to store: a global service that is configured to track global device metadata associated with at least one device network; a local service that is configured to track local device metadata associated with the at least one device network and to update the global device metadata based thereon; a group leader service that is configured to query devices of the at least one device network and aggregate group-level device metadata for transmission to the local service and updating of the local device metadata; and a service mapper that is configured to associate service metadata of the global service, the local service, and the group leader service, respectively, with device metadata of at least one global device, at least one local device, and at least one group leader device, also respectively, and to perform a mapping of the services to the respective devices, based thereon, wherein the global service, the local service, and the group leader service are associated, respectively, with a global service monitor component, a local service monitor component, and a group leader service monitor component, respectively, and wherein the service monitor components are configured to provide monitor data associated with the at least one device network to the service mapper, the service mapper being configured to map a device network service to at least one device of the at least one device network. 19. The system of claim 1 wherein the device metadata includes one or more of a device description, a device name, a device identifier, a device type, a device vendor, a software description, an operating system description, a service, a hardware description, a processor description, a connection description, a connection speed, a connection type, a memory description, a total memory, a free memory, a device status, or an execution platform. | 0.830282 |
8,401,987 | 7 | 8 | 7. The method of claim 5 , wherein the models generated by the first data mining algorithm comprise a plurality of association rule models, wherein each association rule model includes at least one association rule to predict a value in one column based on at least one value in at least one predictor column, and wherein the models generated by the second data mining algorithm comprise a predictive model predicting values in a user selected column; wherein determining the metrics for each record in the second data set comprises: determining for each association model association rules not satisfied by the data in the record; for each association rule model having association rules not satisfied by data in the record, determining an association rule model metric as a function of statistical values of the association rules in the association rule model not satisfied; determining from the predictive model a confidence level of a value in each column predicted by one predictive model; determining a predictive model metric for each predictive model as a function of the determined confidence level for each predictive model applied to the record. | 7. The method of claim 5 , wherein the models generated by the first data mining algorithm comprise a plurality of association rule models, wherein each association rule model includes at least one association rule to predict a value in one column based on at least one value in at least one predictor column, and wherein the models generated by the second data mining algorithm comprise a predictive model predicting values in a user selected column; wherein determining the metrics for each record in the second data set comprises: determining for each association model association rules not satisfied by the data in the record; for each association rule model having association rules not satisfied by data in the record, determining an association rule model metric as a function of statistical values of the association rules in the association rule model not satisfied; determining from the predictive model a confidence level of a value in each column predicted by one predictive model; determining a predictive model metric for each predictive model as a function of the determined confidence level for each predictive model applied to the record. 8. The method of claim 7 , wherein the statistical values comprise at least one of a confidence level, support and/or lift further comprising: generating a summary metric for each record in the second data set as a function of the determined association rule model metrics and the predictive model metrics. | 0.5 |
8,731,902 | 19 | 20 | 19. A computer system comprising: one or more processors; a software program, executable on said computer system, the software program configured to: store information in a datastore, the information corresponding to a plurality of computer applications, wherein the plurality of computer applications have associated annotations, the annotations comprising a verb describing one or more activities performed by an associated application and a noun describing work objects on which the activities are performed; receive an input from a user; provide a first verb and a first noun corresponding to a user intent based on said input; and specify one or more of said plurality of applications based on the verb and noun annotations for the plurality of applications and the first verb and first noun corresponding to the user intent. | 19. A computer system comprising: one or more processors; a software program, executable on said computer system, the software program configured to: store information in a datastore, the information corresponding to a plurality of computer applications, wherein the plurality of computer applications have associated annotations, the annotations comprising a verb describing one or more activities performed by an associated application and a noun describing work objects on which the activities are performed; receive an input from a user; provide a first verb and a first noun corresponding to a user intent based on said input; and specify one or more of said plurality of applications based on the verb and noun annotations for the plurality of applications and the first verb and first noun corresponding to the user intent. 20. The system of claim 19 wherein said specifying is based on semantically matching the first verb and first noun with the verb and noun annotations for the one or more specified applications. | 0.5 |
8,489,530 | 8 | 10 | 8. A system for root cause analysis of failure of a manufactured product, the system comprising: a. a knowledge model comprising a network of entities related to field of failure and manufacturing attributes of the manufactured product and interconnected in a cause-effect relationship, each entity comprising an instance of a parameter that is related to one of the field of failure and manufacturing attributes; b. a conversion module, the conversion module converting the knowledge model into a Bayesian network, the Bayesian network comprising one or more nodes, each node representing an entity of the knowledge model along with a corresponding conditional probability of occurrence of the entity; c. a parameter-instance selection module, the parameter-instance selection module selecting a one or more parameters and corresponding instances from a set of failure reports; d. an inference generating module, the inference module configured for i. mapping the one or more parameters and corresponding instances as a set of evidence to the Bayesian network; and ii. determining a root cause of failure along with a corresponding conditional probability based on the set of evidence; and e. a first data processing module, the first data processing module processing at least one of structured data and unstructured data in a plurality of failure reports to generate a set of field failure attributes of the manufactured product, wherein the first data processing module comprises: i. a data preparation module, the data preparation module for cleansing and transforming the unstructured data based on a predefined criterion; ii. a text-classification module, the text-classification module for associating one or more parts of the unstructured data with a set of named entities; and iii. a text-tagging and annotation module, the text-tagging and annotation module for semantic parsing of the unstructured data into annotated structured data based on a set of extraction rules and a set of extraction directories. | 8. A system for root cause analysis of failure of a manufactured product, the system comprising: a. a knowledge model comprising a network of entities related to field of failure and manufacturing attributes of the manufactured product and interconnected in a cause-effect relationship, each entity comprising an instance of a parameter that is related to one of the field of failure and manufacturing attributes; b. a conversion module, the conversion module converting the knowledge model into a Bayesian network, the Bayesian network comprising one or more nodes, each node representing an entity of the knowledge model along with a corresponding conditional probability of occurrence of the entity; c. a parameter-instance selection module, the parameter-instance selection module selecting a one or more parameters and corresponding instances from a set of failure reports; d. an inference generating module, the inference module configured for i. mapping the one or more parameters and corresponding instances as a set of evidence to the Bayesian network; and ii. determining a root cause of failure along with a corresponding conditional probability based on the set of evidence; and e. a first data processing module, the first data processing module processing at least one of structured data and unstructured data in a plurality of failure reports to generate a set of field failure attributes of the manufactured product, wherein the first data processing module comprises: i. a data preparation module, the data preparation module for cleansing and transforming the unstructured data based on a predefined criterion; ii. a text-classification module, the text-classification module for associating one or more parts of the unstructured data with a set of named entities; and iii. a text-tagging and annotation module, the text-tagging and annotation module for semantic parsing of the unstructured data into annotated structured data based on a set of extraction rules and a set of extraction directories. 10. The system according to claim 8 further comprising a first interactive user interface, the first interactive user interface facilitating selection of the one or more parameters and corresponding instances. | 0.729974 |
9,064,007 | 1 | 26 | 1. A computer-implemented method, comprising: identifying a first query and a second query from a same user session; identifying first related queries associated with the first query and second related queries associated with the second query, each of the first related queries associated with a relatedness weight indicating a strength of a relation between the first query and the respective first related query, and each of the second related queries associated with the relatedness weight indicating the weight of the relation between the second query and the respective second related query; identifying one or more first features for the first query, each first feature including at least one term from one of the first related queries; identifying one or more second features for the second query, each second feature including at least one term from one of the second related queries; creating a first feature vector for the first query, the first feature vector including one or more terms from the first related queries, and for each term, including the relatedness weight associated with the respective first related query that includes the respective term; creating a second feature vector for second query, the second feature vector including one or more terms from the second related queries, and for each term, including the relatedness weight associated with the respective second related query that includes the respective term; comparing the first feature vector and the second feature vector to determine a similarity of the first query and the second query; associating the first query with the second query as a keyword based on a determination that the similarity exceeds a threshold; identifying an electronic advertisement responsive to the second query based on the associating; and providing the electronic advertisement for display on a user device. | 1. A computer-implemented method, comprising: identifying a first query and a second query from a same user session; identifying first related queries associated with the first query and second related queries associated with the second query, each of the first related queries associated with a relatedness weight indicating a strength of a relation between the first query and the respective first related query, and each of the second related queries associated with the relatedness weight indicating the weight of the relation between the second query and the respective second related query; identifying one or more first features for the first query, each first feature including at least one term from one of the first related queries; identifying one or more second features for the second query, each second feature including at least one term from one of the second related queries; creating a first feature vector for the first query, the first feature vector including one or more terms from the first related queries, and for each term, including the relatedness weight associated with the respective first related query that includes the respective term; creating a second feature vector for second query, the second feature vector including one or more terms from the second related queries, and for each term, including the relatedness weight associated with the respective second related query that includes the respective term; comparing the first feature vector and the second feature vector to determine a similarity of the first query and the second query; associating the first query with the second query as a keyword based on a determination that the similarity exceeds a threshold; identifying an electronic advertisement responsive to the second query based on the associating; and providing the electronic advertisement for display on a user device. 26. The method of claim 1 , wherein the electronic advertisement comprises an electronic online advertisement served over a network, and the identifying identifies the electronic on-line advertisement responsive to the second query based on the associating; and the providing provides the electronic on-line advertisement for display on a user device. | 0.541775 |
9,367,526 | 7 | 11 | 7. In a language model defining a probability for sequences of words, the language model invoked by a production application responsive to an end user for performing statistical language recognition services, a method of assigning words to classes comprising: defining a language model for predicting a likelihood of sequences of words received from the production application, the language model having a classing function, the classing function for assigning words to classes, the word classes grouping words for receiving similar treatment as other words in the class; identifying a clustering, the clustering defining the number of words in sequence to which a prediction applies, in which an n-gram cluster defines a probability that, for an n−1 sequence of words, the successive nth word will be found; identifying a language context corresponding to the usage of the language as received by the production application; defining the classing function, the classing function for scanning a learning set and identifying the word classes by: employing a word based classing approach; backing off, if the word based approach indicates a null probability; and employing a class based approach; further comprising: determining seen and unseen clusters, the unseen clusters having a previously unoccurring sequence of words; employing the word based classification if the cluster has a previous occurrence, identifying a discount parameter, the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; and backing off using the discount parameter and employing a class based approach if the cluster is unseen, unseen clusters based on occurrence of any of the words in the cluster, the unseen words has occurred the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; the discount parameter defining an absolute discounting model, further comprising: identifying a discount parameter indicative; of a reduction of a word count of words in a cluster; determining if the cluster is to be pruned or retained in the corpus; count of the observed word based count of the cluster to compute a count of the observed word based count of the cluster to compute a discounted count; or defining the discount count of the cluster as zero if the cluster is pruned; applying the classing function to the learning set to generate the word classes, the word classes indicative of words statistically likely to be employed based on predetermined sequences of words in the learning set; and optimizing the classing function by selecting the word classes based on an objective of the production application, optimizing further including: analyzing word counts and class counts of the learning set; and analyzing word frequency within an assigned class; the objective of the production application defined by the identified language context. | 7. In a language model defining a probability for sequences of words, the language model invoked by a production application responsive to an end user for performing statistical language recognition services, a method of assigning words to classes comprising: defining a language model for predicting a likelihood of sequences of words received from the production application, the language model having a classing function, the classing function for assigning words to classes, the word classes grouping words for receiving similar treatment as other words in the class; identifying a clustering, the clustering defining the number of words in sequence to which a prediction applies, in which an n-gram cluster defines a probability that, for an n−1 sequence of words, the successive nth word will be found; identifying a language context corresponding to the usage of the language as received by the production application; defining the classing function, the classing function for scanning a learning set and identifying the word classes by: employing a word based classing approach; backing off, if the word based approach indicates a null probability; and employing a class based approach; further comprising: determining seen and unseen clusters, the unseen clusters having a previously unoccurring sequence of words; employing the word based classification if the cluster has a previous occurrence, identifying a discount parameter, the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; and backing off using the discount parameter and employing a class based approach if the cluster is unseen, unseen clusters based on occurrence of any of the words in the cluster, the unseen words has occurred the discount parameter reducing a count of word occurrences of a particular cluster in favor of a class count of words of the cluster; the discount parameter defining an absolute discounting model, further comprising: identifying a discount parameter indicative; of a reduction of a word count of words in a cluster; determining if the cluster is to be pruned or retained in the corpus; count of the observed word based count of the cluster to compute a count of the observed word based count of the cluster to compute a discounted count; or defining the discount count of the cluster as zero if the cluster is pruned; applying the classing function to the learning set to generate the word classes, the word classes indicative of words statistically likely to be employed based on predetermined sequences of words in the learning set; and optimizing the classing function by selecting the word classes based on an objective of the production application, optimizing further including: analyzing word counts and class counts of the learning set; and analyzing word frequency within an assigned class; the objective of the production application defined by the identified language context. 11. The method of claim 7 further comprising identifying seen and unseen clusters, the unseen clusters having a previously unoccurring sequence of words, wherein the classing function identifies unseen clusters by: employing the word based classification if the cluster has a previous occurrence, and employing the class based classification if the cluster is previously unseen. | 0.5 |
9,177,018 | 11 | 12 | 11. The system of claim 10 , further operable to perform operations comprising, in response to a selection of a first cross-language search result, providing second instructions to the client device that, when executed by the client device, cause the client device to present a user interface including a first translation corresponding to the first cross-language search result and the respective image search results that are responsive to the first translation. | 11. The system of claim 10 , further operable to perform operations comprising, in response to a selection of a first cross-language search result, providing second instructions to the client device that, when executed by the client device, cause the client device to present a user interface including a first translation corresponding to the first cross-language search result and the respective image search results that are responsive to the first translation. 12. The system of claim 11 , wherein: the second instructions further include instructions that, when executed by the client device, cause the client device to present the first image search query; the first image search query is selectable in the user interface; and in response to a selection of the first image search query, providing third instructions to the client device that, when executed by the client device, cause the client device to present a user interface including the first image search results. | 0.5 |
9,262,553 | 15 | 17 | 15. A non-transitory computer readable medium storing computer program instructions for generating a recommendation, which, when executed on a processor, cause the processor to perform operations comprising: selecting a plurality of members from a user defined community; retrieving a rating for a particular interest from each of the plurality of members, the particular interest based on a user-defined recommendation request; generating a respective perturbed rating for each rating from the plurality of members such that there is a predetermined probability that each rating is different from its respective perturbed rating; aggregating each of the perturbed ratings to generate an aggregated perturbed rating; and generating the recommendation based on the aggregated perturbed rating. | 15. A non-transitory computer readable medium storing computer program instructions for generating a recommendation, which, when executed on a processor, cause the processor to perform operations comprising: selecting a plurality of members from a user defined community; retrieving a rating for a particular interest from each of the plurality of members, the particular interest based on a user-defined recommendation request; generating a respective perturbed rating for each rating from the plurality of members such that there is a predetermined probability that each rating is different from its respective perturbed rating; aggregating each of the perturbed ratings to generate an aggregated perturbed rating; and generating the recommendation based on the aggregated perturbed rating. 17. The non-transitory computer readable medium of claim 15 , wherein the user defined community is defined based on a user defined declarative community definition comprising a predicate on user attributes. | 0.811818 |
8,037,070 | 1 | 2 | 1. A computer-implemented method of generating search queries based on digitized audio from conversations, the method executable by a computer including a processor and memory, comprising: providing a database stored in the memory containing a global hot-list comprising universal popular keywords or keyword phrases and containing a personalized entity list comprising keywords and keyword phrases used with a frequency above a determined threshold value in conversations involving a user; monitoring a conversation between at least two people, at least one of which is the user; identifying, by the processor, words or phrases in digitized audio of the monitored conversation through speech recognition; comparing, by the processor, the identified words or phrases to the keywords and keyword phrases in the database to find any matches; generating, by the processor, a search string, without the user requesting a search, based on words or phrases found to match the keyword or keyword phrases stored in the database; submitting, by the computer, the search string to a search engine as a search query; and serving, by the computer, a set of search results returned by the search engine based on the submitted search string to a display device of the user. | 1. A computer-implemented method of generating search queries based on digitized audio from conversations, the method executable by a computer including a processor and memory, comprising: providing a database stored in the memory containing a global hot-list comprising universal popular keywords or keyword phrases and containing a personalized entity list comprising keywords and keyword phrases used with a frequency above a determined threshold value in conversations involving a user; monitoring a conversation between at least two people, at least one of which is the user; identifying, by the processor, words or phrases in digitized audio of the monitored conversation through speech recognition; comparing, by the processor, the identified words or phrases to the keywords and keyword phrases in the database to find any matches; generating, by the processor, a search string, without the user requesting a search, based on words or phrases found to match the keyword or keyword phrases stored in the database; submitting, by the computer, the search string to a search engine as a search query; and serving, by the computer, a set of search results returned by the search engine based on the submitted search string to a display device of the user. 2. The method of claim 1 , wherein the conversations comprise conversations over telephones, the method further comprising: sensing a contextual piece of information within the monitored conversation or as related to a status of one or more of the telephones; and integrating the contextual piece of information with the search string to narrow the submitted search query to the search engine, to thereby affect the search results thereof. | 0.5 |
9,158,855 | 1 | 5 | 1. A method of extracting individual posts from a weblog, comprising: accessing a home page of the weblog; identifying at least one feed associated with the weblog; determining whether the at least one feed contains sufficient content for feed-guided segmentation; if the at least one feed contains sufficient content for feed-guided segmentation, determining whether the at least one feed contains full content or partial content of the weblog; if the at least one feed contains full content of the weblog, mapping data found in the at least one feed into a representation for weblog posts; and if the at least one feed contains partial content of the weblog, screen scraping the weblog into a representation for weblog posts using the data. | 1. A method of extracting individual posts from a weblog, comprising: accessing a home page of the weblog; identifying at least one feed associated with the weblog; determining whether the at least one feed contains sufficient content for feed-guided segmentation; if the at least one feed contains sufficient content for feed-guided segmentation, determining whether the at least one feed contains full content or partial content of the weblog; if the at least one feed contains full content of the weblog, mapping data found in the at least one feed into a representation for weblog posts; and if the at least one feed contains partial content of the weblog, screen scraping the weblog into a representation for weblog posts using the data. 5. The method of claim 1 , wherein identifying the at least one feed associated with the weblog further comprises: extracting a set of hyperlinks from a body of the weblog; and filtering the set of extracted hyperlinks using a classifier to identify hyperlinks that belong to the at least one feed for the weblog. | 0.797017 |
7,502,466 | 3 | 4 | 3. A method for secure communication of electronic documents comprising the steps of: receiving, at an associated user device, a document processing request, which document processing request includes document data representative of an unencrypted, electronic document; generating, at the user device, page job language information, which page job language information is adapted to control operation of an associated document processing device, in accordance with a received document processing request; generating, at the user device, a seed value; generating, at the user device, a random number from the seed value; encrypting, at the user device, the document data in accordance with the random number so as to generate encrypted document data; encrypting, at the user device, the seed value in connection with key data; embedding, at the user device, the encrypted seed value and page job language information associated with the encrypted document data and the document processing request in a header of the encrypted document data; communicating the encrypted document data and the header inclusive of the page job language information and the encrypted seed value to an associated document processing device via a user interface associated with the user device; receiving, at a document processing device user interface associated with the associated document processing device, the encrypted document data and the header inclusive of the page job language information and the encrypted seed value; storing a copy of the key data in a data storage associated with the document processing device; extracting, via the document processing device, the encrypted seed value from the header; decrypting, via the document processing device, the extracted encrypted seed value in accordance with a copy of the key data in the data storage; generating, via the document processing device, a random number from the decrypted seed value; decrypting, via the document processing device, the encrypted document data in accordance with the random number generated by the document processing device; and commencing a document processing operation on the document processing device on the decrypted document data in accordance with a received document processing request and the page job language information. | 3. A method for secure communication of electronic documents comprising the steps of: receiving, at an associated user device, a document processing request, which document processing request includes document data representative of an unencrypted, electronic document; generating, at the user device, page job language information, which page job language information is adapted to control operation of an associated document processing device, in accordance with a received document processing request; generating, at the user device, a seed value; generating, at the user device, a random number from the seed value; encrypting, at the user device, the document data in accordance with the random number so as to generate encrypted document data; encrypting, at the user device, the seed value in connection with key data; embedding, at the user device, the encrypted seed value and page job language information associated with the encrypted document data and the document processing request in a header of the encrypted document data; communicating the encrypted document data and the header inclusive of the page job language information and the encrypted seed value to an associated document processing device via a user interface associated with the user device; receiving, at a document processing device user interface associated with the associated document processing device, the encrypted document data and the header inclusive of the page job language information and the encrypted seed value; storing a copy of the key data in a data storage associated with the document processing device; extracting, via the document processing device, the encrypted seed value from the header; decrypting, via the document processing device, the extracted encrypted seed value in accordance with a copy of the key data in the data storage; generating, via the document processing device, a random number from the decrypted seed value; decrypting, via the document processing device, the encrypted document data in accordance with the random number generated by the document processing device; and commencing a document processing operation on the document processing device on the decrypted document data in accordance with a received document processing request and the page job language information. 4. The method for secure communication of electronic documents of claim 3 wherein in the seed value is a 32 bit sequence. | 0.5 |
10,095,488 | 5 | 6 | 5. A computer-implemented method for developing software applications from preexisting, comprehensive, and new models, the computer-implemented method comprising: generating, by a modeling module, an integrated graphical modeler that is viewable on a display of a user device; receiving, by the modeling module, input from the user device indicative of user input that specifies which of a plurality of business entities are to be used in constructing a model, wherein the user input is provided via the integrated graphical modeler that includes visual elements corresponding to the plurality of business entities; constructing, by the modeling module, the model that represents a business scenario involving the specified business entities by connecting the corresponding visual elements; expressing, by an application development module, the model as one or more application programming interfaces (APIs); deploying, by the application development module, the model in a simulation mode so that development data necessary for development of a software application is stored in an internal smart memory object-oriented database, wherein the development data simulates real data required by the software application upon deployment; retrieving and integrating, by a virtualization module, real data specified as necessary by the model, wherein the real data is retrieved from one or more real storage systems; configuring, by the virtualization module, integration access parameters; mapping, by the virtualization module, the real data and the integration access parameters to the model; and storing the model, the one or more APIs, the internal smart memory object-oriented database, the real data, or any combination thereof in a repository. | 5. A computer-implemented method for developing software applications from preexisting, comprehensive, and new models, the computer-implemented method comprising: generating, by a modeling module, an integrated graphical modeler that is viewable on a display of a user device; receiving, by the modeling module, input from the user device indicative of user input that specifies which of a plurality of business entities are to be used in constructing a model, wherein the user input is provided via the integrated graphical modeler that includes visual elements corresponding to the plurality of business entities; constructing, by the modeling module, the model that represents a business scenario involving the specified business entities by connecting the corresponding visual elements; expressing, by an application development module, the model as one or more application programming interfaces (APIs); deploying, by the application development module, the model in a simulation mode so that development data necessary for development of a software application is stored in an internal smart memory object-oriented database, wherein the development data simulates real data required by the software application upon deployment; retrieving and integrating, by a virtualization module, real data specified as necessary by the model, wherein the real data is retrieved from one or more real storage systems; configuring, by the virtualization module, integration access parameters; mapping, by the virtualization module, the real data and the integration access parameters to the model; and storing the model, the one or more APIs, the internal smart memory object-oriented database, the real data, or any combination thereof in a repository. 6. The computer-implemented method of claim 5 , wherein each of the plurality of business entities represents a customer, a company, an opportunity, a document, an invoice, an individual, or a department. | 0.5 |
9,477,991 | 1 | 14 | 1. A system, comprising: a processor; a network interface, coupled to the processor and configured to be coupled to a network; and a memory device coupled to the processor, wherein the memory device stores instructions that are executed by the processor, wherein the system: receives, from a computing device, via the network interface and the network, a first query of at least one social network media data source indicating search data and a first geographical search region, wherein the at least one social network media data source stores user-provided data from a plurality of users provided via a plurality of computing devices associated with at least the first geographical search region; determines the first geographical search region covers a first geographical area and at least a first portion of a geographic context region intersecting the first geographical search region, wherein a first location within the geographic context region is not within the first geographical search region and wherein first social media results of the at least one social network media data source in response to the first query will not include one or more second social media results associated with one or more second locations within both the first portion of the geographic context region and the first geographical search region, at least because the one or more second locations are associated with the geographic context region and the first location is not within the first geographical search region; in response to determining the first geographical search region covers the first geographical area and the at least a first portion of the geographic context region intersecting the first geographical search region, generates at least a second query of the at least one social network media data source indicating the search data and a second geographical search region covering a second geographical area including at least a second portion of the geographic context region including the first location and the one or more second locations within the geographic context region; provides, via the network interface and the network, the at least the second query to the at least one social network media data source; receives, from the at least one social network media data source via the network interface and the network, at least one result based on the at least the second query and based on the user-provided data stored via the at least one social network media data source, wherein the at least one result includes the one or more second social media results associated with the one or more second locations within the geographic context region and the first geographical search region; and provides the at least one result to the computing device. | 1. A system, comprising: a processor; a network interface, coupled to the processor and configured to be coupled to a network; and a memory device coupled to the processor, wherein the memory device stores instructions that are executed by the processor, wherein the system: receives, from a computing device, via the network interface and the network, a first query of at least one social network media data source indicating search data and a first geographical search region, wherein the at least one social network media data source stores user-provided data from a plurality of users provided via a plurality of computing devices associated with at least the first geographical search region; determines the first geographical search region covers a first geographical area and at least a first portion of a geographic context region intersecting the first geographical search region, wherein a first location within the geographic context region is not within the first geographical search region and wherein first social media results of the at least one social network media data source in response to the first query will not include one or more second social media results associated with one or more second locations within both the first portion of the geographic context region and the first geographical search region, at least because the one or more second locations are associated with the geographic context region and the first location is not within the first geographical search region; in response to determining the first geographical search region covers the first geographical area and the at least a first portion of the geographic context region intersecting the first geographical search region, generates at least a second query of the at least one social network media data source indicating the search data and a second geographical search region covering a second geographical area including at least a second portion of the geographic context region including the first location and the one or more second locations within the geographic context region; provides, via the network interface and the network, the at least the second query to the at least one social network media data source; receives, from the at least one social network media data source via the network interface and the network, at least one result based on the at least the second query and based on the user-provided data stored via the at least one social network media data source, wherein the at least one result includes the one or more second social media results associated with the one or more second locations within the geographic context region and the first geographical search region; and provides the at least one result to the computing device. 14. The system of claim 1 , provides, via the network interface and the network, the first query to the at least one social network media data source. | 0.930876 |
10,134,390 | 1 | 3 | 1. An electronic device comprising: a memory configured to store a user pronunciation lexicon; a voice inputter; and a processor configured to: control the voice inputter to receive a user voice, obtain a word corresponding to the user voice using the user pronunciation lexicon, obtain a first pronunciation for a phoneme included in the user voice, compare the first pronunciation and a second pronunciation pre stored for the word, identify a pronunciation pattern by using a result of the comparing, and update the user pronunciation lexicon according to a pronunciation pattern rule obtained based on the pronunciation pattern, wherein the pronunciation pattern rule is a rule that a user repeats according to at least one of a pronunciation habit of the user and a pronunciation characteristic of the user. | 1. An electronic device comprising: a memory configured to store a user pronunciation lexicon; a voice inputter; and a processor configured to: control the voice inputter to receive a user voice, obtain a word corresponding to the user voice using the user pronunciation lexicon, obtain a first pronunciation for a phoneme included in the user voice, compare the first pronunciation and a second pronunciation pre stored for the word, identify a pronunciation pattern by using a result of the comparing, and update the user pronunciation lexicon according to a pronunciation pattern rule obtained based on the pronunciation pattern, wherein the pronunciation pattern rule is a rule that a user repeats according to at least one of a pronunciation habit of the user and a pronunciation characteristic of the user. 3. The electronic device as claimed in claim 1 , wherein the processor is further configured to calculate reliability per phoneme included in the user voice and obtain the pronunciation pattern based on the calculated reliability. | 0.753219 |
9,712,331 | 8 | 11 | 8. A computer-readable storage device storing computer-executable instructions that, when executed by a processor of a policy intelligence rules system of a policy layer of a policy realization framework of a communications network, cause the processor to perform operations comprising: receiving, from a policy and charging rules function of a network layer of the policy realization framework, a policy request associated with a request for a network resource; sending, to a master policy repository, the policy request; receiving, from the master policy repository, a plurality of policies pertaining to the request for the network resource of the policy request, wherein the plurality of policies pertaining to the request for the network resource comprise at least one operator policy provided by a network operator and at least one subscriber specific policy provided by a subscriber associated with the request for the network resource; analyzing the plurality of policies to determine whether any policy conflicts exist between any of the plurality of policies; in response to determining that a policy conflict exists between a first policy of the plurality of policies and a second policy of the plurality of policies, determining that the first policy has precedence over the second policy, wherein the first policy comprises the at least one operator policy and the second policy comprises the at least one subscriber specific policy; resolving the policy conflict by giving precedence to the first policy over the second policy; generating, based on the first policy having precedence over the second policy, a rule describing a course of action for the communications network to take in response to the request for the network resource of the policy request; and sending the rule to a policy configuration and provisioning server of the policy layer for use in instructing the policy and charging rules function of the network layer of the policy realization framework. | 8. A computer-readable storage device storing computer-executable instructions that, when executed by a processor of a policy intelligence rules system of a policy layer of a policy realization framework of a communications network, cause the processor to perform operations comprising: receiving, from a policy and charging rules function of a network layer of the policy realization framework, a policy request associated with a request for a network resource; sending, to a master policy repository, the policy request; receiving, from the master policy repository, a plurality of policies pertaining to the request for the network resource of the policy request, wherein the plurality of policies pertaining to the request for the network resource comprise at least one operator policy provided by a network operator and at least one subscriber specific policy provided by a subscriber associated with the request for the network resource; analyzing the plurality of policies to determine whether any policy conflicts exist between any of the plurality of policies; in response to determining that a policy conflict exists between a first policy of the plurality of policies and a second policy of the plurality of policies, determining that the first policy has precedence over the second policy, wherein the first policy comprises the at least one operator policy and the second policy comprises the at least one subscriber specific policy; resolving the policy conflict by giving precedence to the first policy over the second policy; generating, based on the first policy having precedence over the second policy, a rule describing a course of action for the communications network to take in response to the request for the network resource of the policy request; and sending the rule to a policy configuration and provisioning server of the policy layer for use in instructing the policy and charging rules function of the network layer of the policy realization framework. 11. The computer-readable storage device of claim 8 , wherein the operations further comprise identifying the policy conflict, wherein identifying the policy conflict comprises tagging, for conflict resolution, the first policy and the second policy identified in the policy conflict. | 0.546326 |
7,664,778 | 3 | 4 | 3. The method of claim 2 , further comprising: identifying a portion of the filtered statements as resource intensive statements. | 3. The method of claim 2 , further comprising: identifying a portion of the filtered statements as resource intensive statements. 4. The method of claim 3 , further comprising: storing the resource intensive statements and the performance information for each resource intensive statement as a second persistent database object. | 0.5 |
9,336,310 | 1 | 5 | 1. A computer-implemented method for identifying on-line comments as being legitimate or illegitimate, the method comprising: receiving from a user of a computing service a comment directed to a first piece of on-line content; identifying results of reviews of one or more comments by the user directed to other pieces of on-line content; identifying a measure of trust associated with the user that is determined based at least on the results of the reviews of the one or more comments by the user directed to the other pieces of on-line content; determining whether to provide for review of the first piece of on-line content by using a random selection that randomly selects particular pieces of on-line content, from among a plurality of pieces of on-line content, to provide for review, wherein the determining comprises: selecting a number at random; adjusting the selected number up or down using the measure of trust associated with the user, and determining, based on the adjusted number, whether to provide the first piece of on-line content for review to determine whether the on-line content is legitimate or not, wherein a likelihood that the first piece of on-line content is provided for review is influenced based at least on the measure of trust associated with the user; taking action on changing a status of the first piece of on-line content based on the determination of whether to provide for review of the first piece of on-line content; iteratively providing, in a plurality of rounds that each correspond to a submission of a comment from the user, for review of a series of comments by the user and further adjusting the adjusted number up or down based on whether the reviews indicate that the comments are accurate or inaccurate; and determining, for each round of review, a bias level for a decision to trust the comment and a bias level for a decision to review the comment, and determining whether to make active the decision to trust the comment or the decision to review the comment, where making active defines which of the decisions will be used to control review of a comment. | 1. A computer-implemented method for identifying on-line comments as being legitimate or illegitimate, the method comprising: receiving from a user of a computing service a comment directed to a first piece of on-line content; identifying results of reviews of one or more comments by the user directed to other pieces of on-line content; identifying a measure of trust associated with the user that is determined based at least on the results of the reviews of the one or more comments by the user directed to the other pieces of on-line content; determining whether to provide for review of the first piece of on-line content by using a random selection that randomly selects particular pieces of on-line content, from among a plurality of pieces of on-line content, to provide for review, wherein the determining comprises: selecting a number at random; adjusting the selected number up or down using the measure of trust associated with the user, and determining, based on the adjusted number, whether to provide the first piece of on-line content for review to determine whether the on-line content is legitimate or not, wherein a likelihood that the first piece of on-line content is provided for review is influenced based at least on the measure of trust associated with the user; taking action on changing a status of the first piece of on-line content based on the determination of whether to provide for review of the first piece of on-line content; iteratively providing, in a plurality of rounds that each correspond to a submission of a comment from the user, for review of a series of comments by the user and further adjusting the adjusted number up or down based on whether the reviews indicate that the comments are accurate or inaccurate; and determining, for each round of review, a bias level for a decision to trust the comment and a bias level for a decision to review the comment, and determining whether to make active the decision to trust the comment or the decision to review the comment, where making active defines which of the decisions will be used to control review of a comment. 5. The method of claim 1 , further comprising saving the determined bias level for the decision to trust the comment and the determined bias level for the decision to review the comment, for use in a future round of a received user comment. | 0.823789 |
8,631,317 | 1 | 2 | 1. A method of manipulating display of document pages on a touchscreen computing device, the method comprising: recognizing, by the touchscreen computing device, finger motion selection gestures on a touchscreen of the touchscreen computing device; selecting, by the touchscreen computing device for each recognized finger motion selection gesture, a document page displayed on the touchscreen; recognizing, by the touchscreen computing device, a finger motion combination gesture on the touchscreen, wherein recognizing the finger motion combination gesture includes detecting simultaneous lifting of a plurality of fingers from the touchscreen; combining, by the touchscreen computing device responsive to the finger motion combination gesture, the selected document pages into a single concatenated document page; and displaying, by the touchscreen computing device, the single concatenated document page; recognizing, by the touchscreen computing device, a finger motion lock gesture on the touchscreen; locking, by the touchscreen computing device responsive to the finger motion lock gesture, position of the selected document pages within the single concatenated document page; recognizing, by the touchscreen computing device, a finger motion movement gesture on the touchscreen; and in response to recognition of the finger motion movement gesture when the position of the selected document pages are locked, moving, by the touchscreen computing device, the single concatenated document page. | 1. A method of manipulating display of document pages on a touchscreen computing device, the method comprising: recognizing, by the touchscreen computing device, finger motion selection gestures on a touchscreen of the touchscreen computing device; selecting, by the touchscreen computing device for each recognized finger motion selection gesture, a document page displayed on the touchscreen; recognizing, by the touchscreen computing device, a finger motion combination gesture on the touchscreen, wherein recognizing the finger motion combination gesture includes detecting simultaneous lifting of a plurality of fingers from the touchscreen; combining, by the touchscreen computing device responsive to the finger motion combination gesture, the selected document pages into a single concatenated document page; and displaying, by the touchscreen computing device, the single concatenated document page; recognizing, by the touchscreen computing device, a finger motion lock gesture on the touchscreen; locking, by the touchscreen computing device responsive to the finger motion lock gesture, position of the selected document pages within the single concatenated document page; recognizing, by the touchscreen computing device, a finger motion movement gesture on the touchscreen; and in response to recognition of the finger motion movement gesture when the position of the selected document pages are locked, moving, by the touchscreen computing device, the single concatenated document page. 2. The method of claim 1 further comprising: recognizing, by the touchscreen computing device, a finger motion rearrangement gesture on the touchscreen; and rearranging, by the touchscreen computing device responsive to the finger motion rearrangement gesture, positions of the selected document pages relative to each other within the single concatenated document page. | 0.539801 |
7,676,746 | 10 | 16 | 10. A method for enabling in-context authoring of substitute content for one or more non-textual objects, comprising: accessing an electronic document including content data that includes sentences and at least one non-textual object contextually placed in a first position within the sentences; and presenting substitute content positioned in the first position within the sentences, wherein the substitute content corresponds to the at least one non-textual object; presenting at least a portion of the sentences positioned adjacent to the first position to enable a user to contextually review the substitute content with respect to the sentences; editing the substitute content positioned in the first position within the sentences and in response to editing commands; and storing the substitute content in the electronic document. | 10. A method for enabling in-context authoring of substitute content for one or more non-textual objects, comprising: accessing an electronic document including content data that includes sentences and at least one non-textual object contextually placed in a first position within the sentences; and presenting substitute content positioned in the first position within the sentences, wherein the substitute content corresponds to the at least one non-textual object; presenting at least a portion of the sentences positioned adjacent to the first position to enable a user to contextually review the substitute content with respect to the sentences; editing the substitute content positioned in the first position within the sentences and in response to editing commands; and storing the substitute content in the electronic document. 16. A method according to claim 10 , further comprising: presenting at least one item selected from the group comprising a blank space, marker, text message and icon in lieu of the substitute content if the substitute content for the at least one non-textual object is unavailable. | 0.600852 |
8,249,347 | 16 | 18 | 16. A non-transitory computer-readable storage medium having a computer readable program code embodied therein for searching for information, the computer readable program code when executed by at least one processor causing the at least one processor to: receive a query from a user, the query requesting a search to be performed based at least in part on at least one image that has been captured by a digital camera of a mobile device, the at least one image being included in the query; process the at least one image to detect at least one portion of the image including text information and determine boundary information for the at least one portion; analyze the at least one portion of the image based at least in part on the boundary information to recognize one or more words in the text information; search one or more databases to identify one or more matching entries related to the one or more words obtained from the at least one image included in the query, wherein the one or more words are in a first language, and the one or more matching entries comprise one or more words in a second language that are translations of the one or more words in the first language; rank the one or more matching entries based at least in part upon weighted combinations of scores for each of the one or more matching entries in the one or more databases; and provide information relating to at least a selected portion of the one or more matching entries to the user in response to the query, the selected portion being based at least in part upon the ranking of the one or more matching entries. | 16. A non-transitory computer-readable storage medium having a computer readable program code embodied therein for searching for information, the computer readable program code when executed by at least one processor causing the at least one processor to: receive a query from a user, the query requesting a search to be performed based at least in part on at least one image that has been captured by a digital camera of a mobile device, the at least one image being included in the query; process the at least one image to detect at least one portion of the image including text information and determine boundary information for the at least one portion; analyze the at least one portion of the image based at least in part on the boundary information to recognize one or more words in the text information; search one or more databases to identify one or more matching entries related to the one or more words obtained from the at least one image included in the query, wherein the one or more words are in a first language, and the one or more matching entries comprise one or more words in a second language that are translations of the one or more words in the first language; rank the one or more matching entries based at least in part upon weighted combinations of scores for each of the one or more matching entries in the one or more databases; and provide information relating to at least a selected portion of the one or more matching entries to the user in response to the query, the selected portion being based at least in part upon the ranking of the one or more matching entries. 18. The non-transitory computer-readable storage medium of claim 16 , wherein causing the at least one processor to analyze the at least one portion includes causing the at least one processor to process the at least one portion using at least one optical character recognition process. | 0.603878 |
8,510,646 | 1 | 2 | 1. A method comprising the steps of: accessing an annotation engine resident on a web server, the annotation engine configured to generate a user interface for display to a plurality of users; accessing, via the annotation engine, an electronic record stored on the web server; receiving an indication of a portion of the electronic record corresponding to an annotation; generating, via the annotation engine, a discussion window at a location in the electronic record proximate to the indicated portion; receiving the annotation, the annotation input by one of the plurality of users; updating, via the annotation engine, the discussion window to display a plurality of successive annotations input by one of the plurality of users, each of the plurality of successive annotations time-tagged by the annotation engine relative to its time of input by a respective one of the plurality of users, each of the plurality of successive annotations corresponding to the annotation; associating, via the annotation engine, the electronic record with the plurality of successive annotations and storing the plurality of successive annotations in the electronic record on the web server upon receipt of each of the plurality of successive annotations; customizing the discussion window based on a determination made by one of the plurality of users; and customizing the discussion window by assigning a color code to the discussion window, wherein the assigning of the color code is based on at least one of: a categorization of the discussion window; importance of the discussion window; and a characteristic of the discussion window. | 1. A method comprising the steps of: accessing an annotation engine resident on a web server, the annotation engine configured to generate a user interface for display to a plurality of users; accessing, via the annotation engine, an electronic record stored on the web server; receiving an indication of a portion of the electronic record corresponding to an annotation; generating, via the annotation engine, a discussion window at a location in the electronic record proximate to the indicated portion; receiving the annotation, the annotation input by one of the plurality of users; updating, via the annotation engine, the discussion window to display a plurality of successive annotations input by one of the plurality of users, each of the plurality of successive annotations time-tagged by the annotation engine relative to its time of input by a respective one of the plurality of users, each of the plurality of successive annotations corresponding to the annotation; associating, via the annotation engine, the electronic record with the plurality of successive annotations and storing the plurality of successive annotations in the electronic record on the web server upon receipt of each of the plurality of successive annotations; customizing the discussion window based on a determination made by one of the plurality of users; and customizing the discussion window by assigning a color code to the discussion window, wherein the assigning of the color code is based on at least one of: a categorization of the discussion window; importance of the discussion window; and a characteristic of the discussion window. 2. The method according to claim 1 , further comprising the step of generating an email in response to a user request. | 0.893116 |
7,987,151 | 1 | 4 | 1. A system for problem solving, comprising: a brain agent configured to receive input data representing an input query from a peripheral device, the brain agent configured as processor-readable software code stored on a processor readable medium, the brain agent being configured to identify a predetermined data format associated with the input data and invokes a decomposition process associated with that predetermined data format, the decomposition step including outputting the data to a first intelligent agent configured as processor-readable software code stored on a computer readable medium, and the brain agent being configured to receive the input data in a textual form and conceptually parse the input data in textual form and a plurality of sub-queries; and a plurality of second intelligent agents, each configured to receive at least one of the plurality of sub-queries and the corresponding conceptually parsed text and provide responsive output to the brain agent based on the conceptually parsed text; the brain agent being further configured to generate an answer to the input query based upon at least the responsive output of the plurality of second intelligent agents. | 1. A system for problem solving, comprising: a brain agent configured to receive input data representing an input query from a peripheral device, the brain agent configured as processor-readable software code stored on a processor readable medium, the brain agent being configured to identify a predetermined data format associated with the input data and invokes a decomposition process associated with that predetermined data format, the decomposition step including outputting the data to a first intelligent agent configured as processor-readable software code stored on a computer readable medium, and the brain agent being configured to receive the input data in a textual form and conceptually parse the input data in textual form and a plurality of sub-queries; and a plurality of second intelligent agents, each configured to receive at least one of the plurality of sub-queries and the corresponding conceptually parsed text and provide responsive output to the brain agent based on the conceptually parsed text; the brain agent being further configured to generate an answer to the input query based upon at least the responsive output of the plurality of second intelligent agents. 4. The system as recited in claim 1 , the first intelligent agent being a language agent and the second agent being a knowledge agent, the system further comprising: a connector, the connector being embodied as processor-readable software code stored on a processor-readable medium, the connector being configured to facilitate selective interaction between one or more of said language agent and said knowledge agent with one of an external data structure and an external intelligent system. | 0.5 |
7,774,294 | 9 | 10 | 9. The method of claim 1 , wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. | 9. The method of claim 1 , wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 10. The method of claim 9 , wherein the input constrained device has a plurality of overloaded keys, each of the overloaded keys representing two or more characters. | 0.5 |
8,266,082 | 12 | 15 | 12. The context inference system according to claim 11 , wherein the context inference process comprises: receiving and collecting the at least one context information and the service information by using the information receiving unit and the information collection module; inferring the context based on the user preference information, the at least one context information, and the service information by using the inference module; and generating the recommendation information according to the context by using the inference module. | 12. The context inference system according to claim 11 , wherein the context inference process comprises: receiving and collecting the at least one context information and the service information by using the information receiving unit and the information collection module; inferring the context based on the user preference information, the at least one context information, and the service information by using the inference module; and generating the recommendation information according to the context by using the inference module. 15. The context inference system according to claim 12 , wherein the context inference process further comprises updating the user preference information to record that the user prefers the recommendation information when the user accepts the recommendation information. | 0.627072 |
8,095,544 | 1 | 2 | 1. A method for associating documents with searchable metadata, the method comprising: receiving as input at least one text document; and operating at least one programmed processor to perform acts of creating metadata to be associated with the at least one text document, the metadata comprising at least one text keyword, the creating comprising extracting a set of one or more data elements from text of the at least one text document, the set of one or more data elements comprising at least one keyword that appears in the text of the at least one text document; normalizing said set of data elements to create a set of normalized data elements, wherein the normalizing comprises, for a first keyword of the at least one keyword, determining at least one other keyword similar to the first keyword, the at least one other keyword not being a keyword appearing in the text of the at least one text document, and adding the at least one other keyword to the set of normalized data elements; identifying at least one previously-validated keyword that is associated as metadata with at least one previously-stored text document, the at least one previously-stored text document not being one of the at least one text document, the at least one previously-validated keyword not being in the set of normalized data elements; merging said set of normalized data elements with the at least one previously-validated keyword to form a preliminary set of data elements; presenting said preliminary set of data elements for review by a user; and receiving user input validating a validated set of data elements; and in response to the user input validating the validated set of data elements, storing the at least one text document and storing the validated set of data elements as the metadata, the metadata being associated with the at least one text document such that the at least one text document may be located through a search for any data element included in the validated set of data elements. | 1. A method for associating documents with searchable metadata, the method comprising: receiving as input at least one text document; and operating at least one programmed processor to perform acts of creating metadata to be associated with the at least one text document, the metadata comprising at least one text keyword, the creating comprising extracting a set of one or more data elements from text of the at least one text document, the set of one or more data elements comprising at least one keyword that appears in the text of the at least one text document; normalizing said set of data elements to create a set of normalized data elements, wherein the normalizing comprises, for a first keyword of the at least one keyword, determining at least one other keyword similar to the first keyword, the at least one other keyword not being a keyword appearing in the text of the at least one text document, and adding the at least one other keyword to the set of normalized data elements; identifying at least one previously-validated keyword that is associated as metadata with at least one previously-stored text document, the at least one previously-stored text document not being one of the at least one text document, the at least one previously-validated keyword not being in the set of normalized data elements; merging said set of normalized data elements with the at least one previously-validated keyword to form a preliminary set of data elements; presenting said preliminary set of data elements for review by a user; and receiving user input validating a validated set of data elements; and in response to the user input validating the validated set of data elements, storing the at least one text document and storing the validated set of data elements as the metadata, the metadata being associated with the at least one text document such that the at least one text document may be located through a search for any data element included in the validated set of data elements. 2. The method according to claim 1 , wherein extracting a set of data elements from the text comprises extracting at least one data element from the text that is an element from the group consisting of facts described in the text and concepts described in the text. | 0.713823 |
9,761,225 | 3 | 4 | 3. The method of claim 2 , comprising: identifying, by the at least one processor and from amongst the plurality of sets of NLU interpretations types, a group of sets of NLU interpretations types classified as corresponding to the first set of NLU interpretations type; identifying, by the at least one processor and from amongst the plurality of sets of NLU interpretations types, a group of sets of NLU interpretations types classified as corresponding to the second set of NLU interpretations type; and identifying, by the at least one processor and from amongst the plurality of sets of NLU interpretations types, multiple groups of sets of NLU interpretations types classified as corresponding to sets of NLU interpretations types different from both the first set of NLU interpretations type and the second set of NLU interpretations type. | 3. The method of claim 2 , comprising: identifying, by the at least one processor and from amongst the plurality of sets of NLU interpretations types, a group of sets of NLU interpretations types classified as corresponding to the first set of NLU interpretations type; identifying, by the at least one processor and from amongst the plurality of sets of NLU interpretations types, a group of sets of NLU interpretations types classified as corresponding to the second set of NLU interpretations type; and identifying, by the at least one processor and from amongst the plurality of sets of NLU interpretations types, multiple groups of sets of NLU interpretations types classified as corresponding to sets of NLU interpretations types different from both the first set of NLU interpretations type and the second set of NLU interpretations type. 4. The method of claim 3 , comprising: determining, by the at least one processor and based on a number of sets of NLU interpretations types classified as corresponding to the first set of NLU interpretations type, to generate the first specialized NLU interpretation selection model; and determining, by the at least one processor and based on a number of sets of NLU interpretations types classified as corresponding to the second set of NLU interpretations type, to generate the second specialized NLU interpretation selection model. | 0.826761 |
8,892,479 | 12 | 16 | 12. One or more computer readable memories storing information to enable a computing device to perform a process comprising: using a plurality of electromyography (EMG) sensors arbitrarily arranged on a user's forearm to obtain samples of EMG signals generated by muscle contractions of a user while the user is performing one or more predefined finger gestures; monitoring the predefined finger gestures using a secondary input mechanism to verify that correct gestures were performed; extracting feature samples from the sampled EMG signals and labeling feature samples according to the corresponding finger gestures that have been verified as correct by the secondary input mechanism; training a machine learning model with the labeled feature samples; and using the trained machine learning model to evaluate EMG signal samples obtained during arbitrary finger gestures to identify those arbitrary finger gestures relative to one or more of the predefined finger gestures performed by the user. | 12. One or more computer readable memories storing information to enable a computing device to perform a process comprising: using a plurality of electromyography (EMG) sensors arbitrarily arranged on a user's forearm to obtain samples of EMG signals generated by muscle contractions of a user while the user is performing one or more predefined finger gestures; monitoring the predefined finger gestures using a secondary input mechanism to verify that correct gestures were performed; extracting feature samples from the sampled EMG signals and labeling feature samples according to the corresponding finger gestures that have been verified as correct by the secondary input mechanism; training a machine learning model with the labeled feature samples; and using the trained machine learning model to evaluate EMG signal samples obtained during arbitrary finger gestures to identify those arbitrary finger gestures relative to one or more of the predefined finger gestures performed by the user. 16. The computer readable memories of claim 12 wherein one or more finger gestures include attempted finger movement against a resistive force causing corresponding muscle contractions in the user's forearm. | 0.772026 |
9,069,798 | 8 | 10 | 8. The method of claim 1 , wherein the classes are organized in a hierarchical structure, wherein each class corresponds to a node in the hierarchy, wherein nodes are assigned to different levels of the hierarchy, wherein different classification parameters are used for one or more of the levels of the hierarchy, wherein classification is performed by traversing the hierarchy to evaluate partial scores of the classes at each level conditioned on hypotheses of the classes at previous levels, and combining the partial scores of the classes at one or more of the levels to determine a joint score. | 8. The method of claim 1 , wherein the classes are organized in a hierarchical structure, wherein each class corresponds to a node in the hierarchy, wherein nodes are assigned to different levels of the hierarchy, wherein different classification parameters are used for one or more of the levels of the hierarchy, wherein classification is performed by traversing the hierarchy to evaluate partial scores of the classes at each level conditioned on hypotheses of the classes at previous levels, and combining the partial scores of the classes at one or more of the levels to determine a joint score. 10. The method of claim 8 , wherein the hierarchy is represented as a directed acyclic graph. | 0.760309 |
9,934,130 | 1 | 4 | 1. An integration testing apparatus comprising: a memory to store instructions; and a processor, connected to the memory, to execute the instructions to: determine a driver class file for an integration testing tool to connect to a specified unstructured database of a plurality of unstructured databases, where the driver class file includes parameters of the specified unstructured database, the parameters are validated to connect the integration testing tool to the specified unstructured database, the driver class file is determined from a plurality of files associated with the plurality of unstructured databases, the integration testing tool is to test at least one function performed by an application, and the application is to store data in the specified unstructured database responsive to performing the at least one function; generate a connectivity driver for the specified unstructured database, where the connectivity driver includes a path to a location of the driver class file, and the path is used to access the driver class file; determine dependency files for the specified unstructured database, where the dependency files are used to retrieve the data from the specified unstructured database, the dependency files are used to update the data in the specified unstructured database, and the dependency files are determined from the plurality of files associated with the plurality of unstructured databases; store the driver class file, the connectivity driver, and the dependency files in a library of the integration testing tool, where the library of the integration testing tool stores executable files for integration testing of the application; establish a connection between the integration testing tool and the specified unstructured database, where the connection is established using the driver class file and the connectivity driver; generate a query to access the data in the specified unstructured database, where the query is in a format compatible with the specified unstructured database, and the data represents a result based on performing the at least one function; send the query to the specified unstructured database for execution, where the dependency files are used, based on the query, to retrieve query results from the specified unstructured database; receive the query results based on performing the at least one function when the query is executed; compare the query results to validation data; and determine whether the at least one function operates in a determined manner based on the comparing. | 1. An integration testing apparatus comprising: a memory to store instructions; and a processor, connected to the memory, to execute the instructions to: determine a driver class file for an integration testing tool to connect to a specified unstructured database of a plurality of unstructured databases, where the driver class file includes parameters of the specified unstructured database, the parameters are validated to connect the integration testing tool to the specified unstructured database, the driver class file is determined from a plurality of files associated with the plurality of unstructured databases, the integration testing tool is to test at least one function performed by an application, and the application is to store data in the specified unstructured database responsive to performing the at least one function; generate a connectivity driver for the specified unstructured database, where the connectivity driver includes a path to a location of the driver class file, and the path is used to access the driver class file; determine dependency files for the specified unstructured database, where the dependency files are used to retrieve the data from the specified unstructured database, the dependency files are used to update the data in the specified unstructured database, and the dependency files are determined from the plurality of files associated with the plurality of unstructured databases; store the driver class file, the connectivity driver, and the dependency files in a library of the integration testing tool, where the library of the integration testing tool stores executable files for integration testing of the application; establish a connection between the integration testing tool and the specified unstructured database, where the connection is established using the driver class file and the connectivity driver; generate a query to access the data in the specified unstructured database, where the query is in a format compatible with the specified unstructured database, and the data represents a result based on performing the at least one function; send the query to the specified unstructured database for execution, where the dependency files are used, based on the query, to retrieve query results from the specified unstructured database; receive the query results based on performing the at least one function when the query is executed; compare the query results to validation data; and determine whether the at least one function operates in a determined manner based on the comparing. 4. The integration testing apparatus according to claim 1 , where the processor further executes the instructions to: test the connection between the integration testing tool and the specified unstructured database prior to establishing the connection between the integration testing tool and the specified unstructured database; in response to determining that the connection between the integration testing tool and the specified unstructured database is unsuccessful, and the driver class file is determined, search for an error related to dependencies, determine, based on the error related to dependencies, a dependency file to store in the library, where the dependency file is determined from the plurality of files associated with the plurality of unstructured databases, and the dependency file is added to the dependency files, and store the dependency files in the library; and re-test the connection between the integration testing tool and the specified unstructured database. | 0.711998 |
9,253,134 | 9 | 11 | 9. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining a first topic for a conversation received from a first user; determining location information related to a first location of a computing device associated with the first user; creating one or more conversation objects that include the first topic; tagging the one or more conversation objects with the location information; indexing the one or more conversation objects in one or more indexes that include one or more other conversation objects that include the first topic by: updating the one or more indexes of conversation objects to include the one or more conversation objects based on one or more conversation parameters, and wherein the one or more conversation parameters include the first topic, messages associated with each of the one or more conversation objects, and the location information associated with each of the one or more conversation objects; and sorting the one or more conversation objects and the one or more other conversation objects included in the one or more indexes based on locations associated with each of the conversation objects and each of the other conversation objects; receiving one or more search parameters from a second user, wherein the one or more search parameters include at least one second topic corresponding to the first topic for the conversation and at least one second location corresponding to the first location associated with the one or more conversation objects; and providing the sorted one or more conversation objects and the one or more other conversation topics to the second user in response to receiving the one or more search parameters. | 9. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining a first topic for a conversation received from a first user; determining location information related to a first location of a computing device associated with the first user; creating one or more conversation objects that include the first topic; tagging the one or more conversation objects with the location information; indexing the one or more conversation objects in one or more indexes that include one or more other conversation objects that include the first topic by: updating the one or more indexes of conversation objects to include the one or more conversation objects based on one or more conversation parameters, and wherein the one or more conversation parameters include the first topic, messages associated with each of the one or more conversation objects, and the location information associated with each of the one or more conversation objects; and sorting the one or more conversation objects and the one or more other conversation objects included in the one or more indexes based on locations associated with each of the conversation objects and each of the other conversation objects; receiving one or more search parameters from a second user, wherein the one or more search parameters include at least one second topic corresponding to the first topic for the conversation and at least one second location corresponding to the first location associated with the one or more conversation objects; and providing the sorted one or more conversation objects and the one or more other conversation topics to the second user in response to receiving the one or more search parameters. 11. The system of claim 9 , wherein the stored instructions include instructions that are further operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, from the first user, a list of one or more other users to invite to be associated with the one or more conversation objects; sending, to one or more of the other users included in the list, an invitation to be associated with the one or more conversation objects; receiving, from one or more of the other users, an acceptance of the invitation; and updating the one or more conversation objects to include indicators of the one or more other users that accepted the invitation. | 0.688489 |
9,104,435 | 16 | 17 | 16. A non-transitory computer storage medium having computer-executable instructions stored thereon that, in response to execution by a computer system, cause the computer system to: instruct to process annotations that include a dynamic annotation received at a target system and that is associated with data to be processed by the target system, wherein the dynamic annotation changes at the target system as a code block that is associated with the dynamic annotation is executed, wherein the dynamic annotation varies as a function of at least one of an available energy, an available memory or an available storage capacity; apply the processed annotations to at least one hardware component of the target system based on a hardware customization specified in the received annotations; instruct to process the data using the hardware customization that is specified by the received annotations, wherein the specified hardware customization is based upon a specified quality of service level to process the data with a reduced energy expenditure, and wherein the quality of service level is different from the reduced energy expenditure; instruct to modify at least one annotation of the processed annotations based on one or more values obtained from sensors at the target system; apply the modified at least one annotation to the at least one hardware component of the target system at a time when the code block that is associated with the dynamic annotation is executed; and reduce energy expended to process the data while maintaining the quality of service level through use of the hardware customization specified in the received annotations and the at least one hardware component of the target system to which the modified at least one annotation was applied, wherein one or more of the annotations are based, at least in part, on a system software configuration that is associated with a data block and wherein the one or more annotations specify how to process the data block when the code block is executed. | 16. A non-transitory computer storage medium having computer-executable instructions stored thereon that, in response to execution by a computer system, cause the computer system to: instruct to process annotations that include a dynamic annotation received at a target system and that is associated with data to be processed by the target system, wherein the dynamic annotation changes at the target system as a code block that is associated with the dynamic annotation is executed, wherein the dynamic annotation varies as a function of at least one of an available energy, an available memory or an available storage capacity; apply the processed annotations to at least one hardware component of the target system based on a hardware customization specified in the received annotations; instruct to process the data using the hardware customization that is specified by the received annotations, wherein the specified hardware customization is based upon a specified quality of service level to process the data with a reduced energy expenditure, and wherein the quality of service level is different from the reduced energy expenditure; instruct to modify at least one annotation of the processed annotations based on one or more values obtained from sensors at the target system; apply the modified at least one annotation to the at least one hardware component of the target system at a time when the code block that is associated with the dynamic annotation is executed; and reduce energy expended to process the data while maintaining the quality of service level through use of the hardware customization specified in the received annotations and the at least one hardware component of the target system to which the modified at least one annotation was applied, wherein one or more of the annotations are based, at least in part, on a system software configuration that is associated with a data block and wherein the one or more annotations specify how to process the data block when the code block is executed. 17. The computer storage medium of claim 16 , wherein the hardware customization comprises gating of unused memory blocks within the computer system, gating of cache memory within the computer system, and gating of processor cores within the computer system. | 0.5 |
8,239,287 | 2 | 3 | 2. The system of claim 1 , wherein the items comprise items in an electronic catalog. | 2. The system of claim 1 , wherein the items comprise items in an electronic catalog. 3. The system of claim 2 , wherein the item selections comprise one or more of purchases, views, downloads, rentals, and clicks. | 0.5 |
8,787,681 | 1 | 12 | 1. A non-transitory computer readable medium having computer executable program code embodied thereon, the computer executable program code configured to cause a computing device to perform the operations of: partitioning a digital real estate document into a set of token patterns; normalizing the set of token patterns to obtain a normalized set of token patterns; applying a first filter to the normalized set of token patterns to obtain a first score for the digital real estate document, wherein the first score indicates a first likelihood that the digital real estate document is a member of a first document classification associated with the first filter; applying a second filter to the normalized set of token patterns to obtain a second score for the digital real estate document, wherein the second score indicates a second likelihood that the digital real estate document is a member of a second document classification associated with the second filter; and determining a document classification of the digital real estate document based on a set of scores associated with the digital real estate document, wherein the set of scores includes the first score and the second score; wherein the first filter comprises a set of indicative token patterns and a set of non-indicative token patterns, wherein the indicative token patterns are those associated with the first document classification, wherein the non-indicative token patterns are those not associated with the first document classification, and wherein applying the first filter to the normalized set of token patterns to obtain the first score comprises determining the first score based on the set of indicative token patterns, the set of non-indicative token patterns, and the normalized set of token patterns. | 1. A non-transitory computer readable medium having computer executable program code embodied thereon, the computer executable program code configured to cause a computing device to perform the operations of: partitioning a digital real estate document into a set of token patterns; normalizing the set of token patterns to obtain a normalized set of token patterns; applying a first filter to the normalized set of token patterns to obtain a first score for the digital real estate document, wherein the first score indicates a first likelihood that the digital real estate document is a member of a first document classification associated with the first filter; applying a second filter to the normalized set of token patterns to obtain a second score for the digital real estate document, wherein the second score indicates a second likelihood that the digital real estate document is a member of a second document classification associated with the second filter; and determining a document classification of the digital real estate document based on a set of scores associated with the digital real estate document, wherein the set of scores includes the first score and the second score; wherein the first filter comprises a set of indicative token patterns and a set of non-indicative token patterns, wherein the indicative token patterns are those associated with the first document classification, wherein the non-indicative token patterns are those not associated with the first document classification, and wherein applying the first filter to the normalized set of token patterns to obtain the first score comprises determining the first score based on the set of indicative token patterns, the set of non-indicative token patterns, and the normalized set of token patterns. 12. The computer readable medium of claim 1 , wherein the non-indicative token patterns are tokens that are not indicative of a digital document belonging to the first filter's associated first document classification. | 0.757238 |
8,595,222 | 1 | 2 | 1. A computer-implemented method of using Resource Description Framework (RDF) reification to associate Semantic Web statements with start properties and stop properties related to lifetimes of the Semantic Web statements using a reification processor, comprising: accessing an RDF statement from a Semantic Web resource wherein the RDF statement includes a subject, a predicate, and an object; determining a lifetime of the subject of the RDF statement, wherein determining the lifetime of the subject is based on at least one of a start property of the subject and a stop property of the subject; determining a lifetime of the predicate of the RDF statement, wherein determining the lifetime of the predicate is based on at least one of a start property of the predicate and a stop property the predicate; determining a lifetime of the object of the RDF statement, wherein determining the lifetime of the object is based on at least one of a start property of the object and a stop property of the object; automatically determining a lifetime of the RDF statement based on an overlap of the lifetime of the subject, the lifetime of the predicate, and the lifetime of the object; generating a reified RDF statement, using the reification processor, wherein the reified RDF statement includes the subject, the predicate, the object and the lifetime of the RDF statement; and storing the reified RDF statement in the Semantic Web resource. | 1. A computer-implemented method of using Resource Description Framework (RDF) reification to associate Semantic Web statements with start properties and stop properties related to lifetimes of the Semantic Web statements using a reification processor, comprising: accessing an RDF statement from a Semantic Web resource wherein the RDF statement includes a subject, a predicate, and an object; determining a lifetime of the subject of the RDF statement, wherein determining the lifetime of the subject is based on at least one of a start property of the subject and a stop property of the subject; determining a lifetime of the predicate of the RDF statement, wherein determining the lifetime of the predicate is based on at least one of a start property of the predicate and a stop property the predicate; determining a lifetime of the object of the RDF statement, wherein determining the lifetime of the object is based on at least one of a start property of the object and a stop property of the object; automatically determining a lifetime of the RDF statement based on an overlap of the lifetime of the subject, the lifetime of the predicate, and the lifetime of the object; generating a reified RDF statement, using the reification processor, wherein the reified RDF statement includes the subject, the predicate, the object and the lifetime of the RDF statement; and storing the reified RDF statement in the Semantic Web resource. 2. The method of claim 1 , further comprising: receiving a Semantic Web query having an associated timeframe; determining if the query timeframe is within the lifetime of a reified RDF statement in the Semantic Web resource; and accessing the reified RDF statement in response to the determination. | 0.646081 |
9,170,826 | 9 | 14 | 9. A computer-program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising: obtaining a first textual expression contained within an application, wherein the first textual expression is expressed in a first language; generating a unique key from a hash of the first textual expression, the unique key being generated based on a location of where the first textual expression is used within the application and a type of object of the application using the first textual expression; determining a language code representative of a second language, the language code being associated with the unique key; determining, based on the generated unique key and the determined language code, a second textual expression in the second language representative of a translation from the first language into the second language indicated by the language code; and providing, based on the location and the type of object, the second textual expression to the application to replace the first textual expression in a view presented to a user. | 9. A computer-program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising: obtaining a first textual expression contained within an application, wherein the first textual expression is expressed in a first language; generating a unique key from a hash of the first textual expression, the unique key being generated based on a location of where the first textual expression is used within the application and a type of object of the application using the first textual expression; determining a language code representative of a second language, the language code being associated with the unique key; determining, based on the generated unique key and the determined language code, a second textual expression in the second language representative of a translation from the first language into the second language indicated by the language code; and providing, based on the location and the type of object, the second textual expression to the application to replace the first textual expression in a view presented to a user. 14. The computer-program product according to claim 9 , wherein the operations further comprise accessing an index containing a location where the first textual expression appears in the application. | 0.617308 |
9,558,739 | 9 | 12 | 9. A system for adapting a speech system of a vehicle, comprising: a computer readable medium comprising: a first module that, by a processor, logs speech data from the speech system; a second module that, by a processor, processes the speech data for a pattern of a user competence associated with an interaction behavior, that processes the pattern of user competence for parameters and measurements, and that calculates at least one setting based on the parameters and measurements of the pattern; and a third module that, by a processor, updates an interaction sequence based on the at least one setting, and wherein the third module updates the interaction sequence to include more system initiative after repeated errors by the user or the speech system are identified, and wherein the third module updates the interaction sequence to include more user initiative after it is determined that the user learned an interaction pattern. | 9. A system for adapting a speech system of a vehicle, comprising: a computer readable medium comprising: a first module that, by a processor, logs speech data from the speech system; a second module that, by a processor, processes the speech data for a pattern of a user competence associated with an interaction behavior, that processes the pattern of user competence for parameters and measurements, and that calculates at least one setting based on the parameters and measurements of the pattern; and a third module that, by a processor, updates an interaction sequence based on the at least one setting, and wherein the third module updates the interaction sequence to include more system initiative after repeated errors by the user or the speech system are identified, and wherein the third module updates the interaction sequence to include more user initiative after it is determined that the user learned an interaction pattern. 12. The system of claim 9 wherein the parameters and measurements are further associated with at least one of task completion rate, task completion time, time out events, response time, confirmation cycles, disambiguation cycles, and help requests. | 0.689223 |
8,429,171 | 10 | 11 | 10. A computer implemented information retrieval system for searching a corpus, the system comprising: a computer; a scoring module configured to, for each of one or more searches of at least a subset of the corpus, generate a confidence score for each of one or more putative occurrences of a search query in the at least a subset of the corpus; a threshold module configured to adjust a threshold to maintain a consistent user experience across the one or more searches according to a consistency criterion, wherein the threshold is adjusted according to at least one of a duration of the at least a subset of the corpus or an audio quality of the at least a subset of the corpus; and a display module configured to display putative occurrences of the search query having a confidence score greater than the threshold; wherein the retrieval system is further configured to modify the search algorithm to optimize the consistency criterion, and the consistency criterion is selected from the group consisting of a constant computation duration for each of the plurality of searches, and a constant amount of memory used for each of the one or more searches. | 10. A computer implemented information retrieval system for searching a corpus, the system comprising: a computer; a scoring module configured to, for each of one or more searches of at least a subset of the corpus, generate a confidence score for each of one or more putative occurrences of a search query in the at least a subset of the corpus; a threshold module configured to adjust a threshold to maintain a consistent user experience across the one or more searches according to a consistency criterion, wherein the threshold is adjusted according to at least one of a duration of the at least a subset of the corpus or an audio quality of the at least a subset of the corpus; and a display module configured to display putative occurrences of the search query having a confidence score greater than the threshold; wherein the retrieval system is further configured to modify the search algorithm to optimize the consistency criterion, and the consistency criterion is selected from the group consisting of a constant computation duration for each of the plurality of searches, and a constant amount of memory used for each of the one or more searches. 11. The system of claim 10 , wherein the system is configured to account for an audio quality of the active corpus in optimizing the consistency criterion. | 0.5 |
7,818,345 | 12 | 14 | 12. The method of claim 11 , further comprising: transferring the contents of the block corresponding to the text into a text file; integrating at least one specific basic code defined by a series of basic codes into said text file, the specific basic code being associated with said first part. | 12. The method of claim 11 , further comprising: transferring the contents of the block corresponding to the text into a text file; integrating at least one specific basic code defined by a series of basic codes into said text file, the specific basic code being associated with said first part. 14. The method of claim 12 , further comprising: interpreting the specific basic code into an specific interpreted code; associating said specific interpreted code with a location in the database. | 0.5 |
8,532,333 | 10 | 15 | 10. A computer system, comprising: a non-transitory computer-readable storage medium comprising executable computer program code for: recognizing one or more text strings in each of a plurality of geo-tagged images, each of the plurality of geo-tagged images indicating a geographical location of its corresponding geo-tagged image, identifying one or more establishments near the geographical locations of the plurality of geo-tagged images, for each specific establishment of the one or more establishments: (i) extracting one or more phrases from information associated with the specific establishment, (ii) comparing the one or more text strings recognized in the plurality of geo-tagged images with the extracted one or more phrases to derive one or more matches, (iii) determining one or more image-establishment pairs based on the one or more matches, each image-establishment pair pairing a specific geo-tagged image with the specific establishment, and (iv) selecting a representative geo-tagged image for the specific establishment from among the plurality of geo-tagged images based on the one or more image-establishment pairs; and at least one processor for executing the executable computer program code. | 10. A computer system, comprising: a non-transitory computer-readable storage medium comprising executable computer program code for: recognizing one or more text strings in each of a plurality of geo-tagged images, each of the plurality of geo-tagged images indicating a geographical location of its corresponding geo-tagged image, identifying one or more establishments near the geographical locations of the plurality of geo-tagged images, for each specific establishment of the one or more establishments: (i) extracting one or more phrases from information associated with the specific establishment, (ii) comparing the one or more text strings recognized in the plurality of geo-tagged images with the extracted one or more phrases to derive one or more matches, (iii) determining one or more image-establishment pairs based on the one or more matches, each image-establishment pair pairing a specific geo-tagged image with the specific establishment, and (iv) selecting a representative geo-tagged image for the specific establishment from among the plurality of geo-tagged images based on the one or more image-establishment pairs; and at least one processor for executing the executable computer program code. 15. The computer system of claim 10 , wherein comparing the one or more text strings recognized in the plurality of geo-tagged images with the extracted one or more phrases includes filtering the extracted one or more phrases. | 0.763103 |
8,224,650 | 52 | 54 | 52. A computer implemented method for defining a website application on a server in a server/client architecture, the website application providing markup to a client for performing recognition and/or audible prompting on the client, the method comprising: defining the website application by creating an authoring page with a first set of visual controls having attributes related to a first modality of interaction with a user of the client that being visual rendering on the client device, the attributes related to visual rendering including at least one of location for visual rendering, font, background color, and foreground color and with a second set of controls having attributes related to a second modality of interaction with a user of the client that being at least one of recognition and audibly prompting, the first set of controls and the second set of controls being related to client side markup executable by a client browser, wherein defining includes selectively associating controls of the second set of controls with at least one control of the first set of visual controls, the second set of controls comprising: a question control for generating markup related to audible prompting of a question; and an answer control for generating markup related to a grammar for recognition, the question and answer controls being associated with a semantic map comprising one or more semantic items that form a layer between individually associated visual domain primary controls and a non-visual recognition domain of the question and answer controls, the associated visual domain primary controls comprising markup; and processing the controls on the authoring page to generate client side markup including processing of the first set of visual controls to generate client side markup executable by the client browser on the client in the server/client system in accordance with the controls of the first set and the attributes of the controls of the first set to perform both visual rendering, and processing the controls of the second set to generate client side markup by incorporating the attributes in the controls that is executable by the client browser on the client in the server/client system in accordance with the controls of the second set. | 52. A computer implemented method for defining a website application on a server in a server/client architecture, the website application providing markup to a client for performing recognition and/or audible prompting on the client, the method comprising: defining the website application by creating an authoring page with a first set of visual controls having attributes related to a first modality of interaction with a user of the client that being visual rendering on the client device, the attributes related to visual rendering including at least one of location for visual rendering, font, background color, and foreground color and with a second set of controls having attributes related to a second modality of interaction with a user of the client that being at least one of recognition and audibly prompting, the first set of controls and the second set of controls being related to client side markup executable by a client browser, wherein defining includes selectively associating controls of the second set of controls with at least one control of the first set of visual controls, the second set of controls comprising: a question control for generating markup related to audible prompting of a question; and an answer control for generating markup related to a grammar for recognition, the question and answer controls being associated with a semantic map comprising one or more semantic items that form a layer between individually associated visual domain primary controls and a non-visual recognition domain of the question and answer controls, the associated visual domain primary controls comprising markup; and processing the controls on the authoring page to generate client side markup including processing of the first set of visual controls to generate client side markup executable by the client browser on the client in the server/client system in accordance with the controls of the first set and the attributes of the controls of the first set to perform both visual rendering, and processing the controls of the second set to generate client side markup by incorporating the attributes in the controls that is executable by the client browser on the client in the server/client system in accordance with the controls of the second set. 54. The computer implemented method of claim 52 wherein the second set of controls further includes means for confirming that a recognized result is correct; and wherein defining the website application with a second set of controls related to at least one of recognition and audibly prompting includes associating the means for confirming with a recognized result to be received. | 0.663717 |
9,310,999 | 1 | 4 | 1. A method comprising: displaying a keypad for text input to a user, the keypad including a plurality of keys, receiving input from the user indicating a selection of a key from the plurality of keys, the key representing a consonant, receiving a gesture input from the user, wherein the gesture input is associated with one gesture of a set of gestures, each gesture in the set being semantically linked as defined by the user to at least one property selected from: a phonological property and a diacritic property, and displaying a grapheme based upon the selected key and the at least one property semantically linked to the received gesture, wherein the grapheme is a modified version of a word associated with the selected key and the grapheme is predicted based on only the consonant and the at least one property associated with the received gesture. | 1. A method comprising: displaying a keypad for text input to a user, the keypad including a plurality of keys, receiving input from the user indicating a selection of a key from the plurality of keys, the key representing a consonant, receiving a gesture input from the user, wherein the gesture input is associated with one gesture of a set of gestures, each gesture in the set being semantically linked as defined by the user to at least one property selected from: a phonological property and a diacritic property, and displaying a grapheme based upon the selected key and the at least one property semantically linked to the received gesture, wherein the grapheme is a modified version of a word associated with the selected key and the grapheme is predicted based on only the consonant and the at least one property associated with the received gesture. 4. The method of claim 1 , further comprising predicting a character that is part of the grapheme. | 0.90631 |
8,494,857 | 2 | 8 | 2. The method of claim 1 , wherein analyzing the identified phonemes to identify prosodic characteristics comprises identifying pauses between the identified phonemes of the speech of the patient from the audio sample. | 2. The method of claim 1 , wherein analyzing the identified phonemes to identify prosodic characteristics comprises identifying pauses between the identified phonemes of the speech of the patient from the audio sample. 8. The method of claim 2 , wherein automatically measuring fluency comprises identifying an average duration of pauses of the speech of the patient of the audio sample. | 0.5 |
9,477,749 | 47 | 55 | 47. The non-transitory computer readable storage medium of claim 37 , further comprising instructions that if executed enable the computing system to: derive a satisfaction rating from unstructured document metadata; and analyze an aggregation of category topics to provide a measure of overall satisfaction. | 47. The non-transitory computer readable storage medium of claim 37 , further comprising instructions that if executed enable the computing system to: derive a satisfaction rating from unstructured document metadata; and analyze an aggregation of category topics to provide a measure of overall satisfaction. 55. The non-transitory computer readable storage medium of claim 47 , further comprising instructions that if executed enable the computing system to: present a non-trended report by displaying overall satisfaction aggregated over a non-time data dimension; and wherein the instructions for receiving an instruction to determine the one or more causal factors associated with the observation selected by the user further comprise instructions that if executed enable the computing system to: allow the user to select a specific data dimension value as the observation for investigating causal factors that show at least one of a statistically significant tendency to associate more with high degree satisfaction rather than a poor degree of satisfaction and a statistically significant tendency to associate more with a poor degree of satisfaction rather than high degree satisfaction. | 0.5 |
9,342,619 | 7 | 14 | 7. A method comprising: obtaining a webpage; reading markup language elements in the webpage; translating the markup language elements into graphical representations of the markup language elements, wherein the graphical representations include a current graphical element in the webpage and a target graphical element in the webpage; determining spatial locations of the current and target graphical elements in the webpage; determining a spatial relationship between the current and target graphical elements in the webpage; displaying the webpage using the graphical representations; generating a data structure having the markup language elements; assigning a keyboard shortcut to the determined spatial relationship; augmenting the generated data structure with data representing the assigned-keyboard shortcut; storing the augmented data structure; obtaining a selection of the keyboard-shortcut that indicates that a user wants to change focus of the webpage from the current graphical element to the target graphical element; and in response to the keyboard-shortcut selection, changing the focus in the webpage from the current graphical element to the target graphical element using the determined spatial locations, the determined spatial relationship and the stored augmented data structure. | 7. A method comprising: obtaining a webpage; reading markup language elements in the webpage; translating the markup language elements into graphical representations of the markup language elements, wherein the graphical representations include a current graphical element in the webpage and a target graphical element in the webpage; determining spatial locations of the current and target graphical elements in the webpage; determining a spatial relationship between the current and target graphical elements in the webpage; displaying the webpage using the graphical representations; generating a data structure having the markup language elements; assigning a keyboard shortcut to the determined spatial relationship; augmenting the generated data structure with data representing the assigned-keyboard shortcut; storing the augmented data structure; obtaining a selection of the keyboard-shortcut that indicates that a user wants to change focus of the webpage from the current graphical element to the target graphical element; and in response to the keyboard-shortcut selection, changing the focus in the webpage from the current graphical element to the target graphical element using the determined spatial locations, the determined spatial relationship and the stored augmented data structure. 14. A method according to claim 7 , wherein determining the spatial relationship between the current and target graphical elements includes using rectilinear coordinates of the webpage. | 0.868234 |
9,412,392 | 47 | 71 | 47. A method for processing voice commands, the method comprising: at a electronic device: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. | 47. A method for processing voice commands, the method comprising: at a electronic device: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. 71. The method of claim 47 , wherein the contextual information comprises information from an email application of the electronic device. | 0.795522 |
8,103,646 | 1 | 7 | 1. A computer-implemented method of managing information, comprising acts of: searching information sources containing audio data for tag and content relationship data; transcribing the audio data to produce transcribed text; creating a tag classification model based on the relationship data comprising taxonomy between tags and an associated corpus of tagged content to produce tag information; obtaining the tag information from the tag classification model and outputting the tag information as a short list of likely tags that have a likelihood of being appropriate and related to the transcribed text; selecting a tag that applies to the transcribed text based on the list of likely tags; and utilizing a processor that executes instructions stored in memory to perform at least one of the acts of searching, transcribing, creating, obtaining or selecting. | 1. A computer-implemented method of managing information, comprising acts of: searching information sources containing audio data for tag and content relationship data; transcribing the audio data to produce transcribed text; creating a tag classification model based on the relationship data comprising taxonomy between tags and an associated corpus of tagged content to produce tag information; obtaining the tag information from the tag classification model and outputting the tag information as a short list of likely tags that have a likelihood of being appropriate and related to the transcribed text; selecting a tag that applies to the transcribed text based on the list of likely tags; and utilizing a processor that executes instructions stored in memory to perform at least one of the acts of searching, transcribing, creating, obtaining or selecting. 7. The method of claim 1 , further comprising: accessing a speech model to transcribe the audio data from audio and/or video content; and training the speech model based on the audio and/or video content. | 0.699115 |
9,575,946 | 10 | 17 | 10. A method for processing text comprising: converting speech to text; displaying to a user on a first text display a first sequence of text items, an active text item, and an active cursor position, wherein ones of the first sequence of text items is limited to a maximum number of text items, wherein the first active text item corresponds to one of the sequence of text items, and wherein the active cursor position is associated with either a displayed text item or a text boundary; displaying on a second text display a second sequence of text items and a second active text item, wherein the second sequence of text items includes the first sequence of text items, and wherein the second text display is synchronized with the first text display so that the first active text item and second active text item are the same; receiving input from a user control to adjust the first active text item and the active cursor position with the first sequence of text items; determining the first sequence of text items to display from the second sequence of text items based upon the active cursor position and the maximum number of text items, receiving new text from the speech recognition processor; determining if the active cursor position is an active text boundary or an active text item; if the active cursor position is an text boundary, inserting the new text between the displayed text items separated by the active text boundary; and if the active cursor position is an active text item, replacing a displayed text item with the new text, wherein the first and second text displays are text displays within an automobile passenger compartment, wherein the first text display is positioned directly in front of an automobile driver, and wherein the second text display is positioned to one side of the automobile driver. | 10. A method for processing text comprising: converting speech to text; displaying to a user on a first text display a first sequence of text items, an active text item, and an active cursor position, wherein ones of the first sequence of text items is limited to a maximum number of text items, wherein the first active text item corresponds to one of the sequence of text items, and wherein the active cursor position is associated with either a displayed text item or a text boundary; displaying on a second text display a second sequence of text items and a second active text item, wherein the second sequence of text items includes the first sequence of text items, and wherein the second text display is synchronized with the first text display so that the first active text item and second active text item are the same; receiving input from a user control to adjust the first active text item and the active cursor position with the first sequence of text items; determining the first sequence of text items to display from the second sequence of text items based upon the active cursor position and the maximum number of text items, receiving new text from the speech recognition processor; determining if the active cursor position is an active text boundary or an active text item; if the active cursor position is an text boundary, inserting the new text between the displayed text items separated by the active text boundary; and if the active cursor position is an active text item, replacing a displayed text item with the new text, wherein the first and second text displays are text displays within an automobile passenger compartment, wherein the first text display is positioned directly in front of an automobile driver, and wherein the second text display is positioned to one side of the automobile driver. 17. The method of claim 10 wherein receiving input from a user control comprises receiving input from a multifunction control knob. | 0.771777 |
9,138,591 | 1 | 25 | 1. An external medical device, comprising: a housing; an energy storage module within the housing for storing an electrical charge; a defibrillation port for guiding via electrodes the stored electrical charge to a person; a user interface structured to deliver prompts to a user during a defibrillation session; and a language detector in the housing structured to determine a vicinity language, in which the prompts delivered by the user interface to the user during the defibrillation session are in a language that is selected based on the determined vicinity language, and further in which the language detector includes an optical character recognition (OCR) module, or both a voice recognition module and an OCR module. | 1. An external medical device, comprising: a housing; an energy storage module within the housing for storing an electrical charge; a defibrillation port for guiding via electrodes the stored electrical charge to a person; a user interface structured to deliver prompts to a user during a defibrillation session; and a language detector in the housing structured to determine a vicinity language, in which the prompts delivered by the user interface to the user during the defibrillation session are in a language that is selected based on the determined vicinity language, and further in which the language detector includes an optical character recognition (OCR) module, or both a voice recognition module and an OCR module. 25. The device of claim 1 , in which the language detector is structured to monitor ambient sounds. | 0.820652 |
8,949,231 | 1 | 6 | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on analyzing activity associated with content items having descriptive terms that describe the content items and promoting the presentation ranking of content items associated with descriptive terms that have an increased level of current activity, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by users for identifying desired content items; in response to the input entered by the users, presenting corresponding subsets of content items to the users; receiving actions from the users selecting content items from the corresponding subsets; analyzing the selection actions received from the users to detect an increased level of current activity relative to a normal level of activity associated with the content items selected by the users; selecting and ordering a collection of content items from the provided set of content items based on promoting the ranking of content items associated with descriptive terms that are associated with content items that have the increased level of current activity relative to the normal activity level; and presenting the collection of content items to at least one user. | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on analyzing activity associated with content items having descriptive terms that describe the content items and promoting the presentation ranking of content items associated with descriptive terms that have an increased level of current activity, the method comprising: providing access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by users for identifying desired content items; in response to the input entered by the users, presenting corresponding subsets of content items to the users; receiving actions from the users selecting content items from the corresponding subsets; analyzing the selection actions received from the users to detect an increased level of current activity relative to a normal level of activity associated with the content items selected by the users; selecting and ordering a collection of content items from the provided set of content items based on promoting the ranking of content items associated with descriptive terms that are associated with content items that have the increased level of current activity relative to the normal activity level; and presenting the collection of content items to at least one user. 6. The method of claim 1 , wherein the set of content items includes at least one of television program items, movie items, and audio / video media items and the at least one associated descriptive term includes at least one of title, cast, director, content description, and keywords associated with the content. | 0.702471 |
7,697,551 | 9 | 10 | 9. The system of claim 8 , wherein the first electronic device is further configured to initiate a call to the recipient when the user of the first electronic device selects a telephone number to contact from a contact list programmed into the first electronic device. | 9. The system of claim 8 , wherein the first electronic device is further configured to initiate a call to the recipient when the user of the first electronic device selects a telephone number to contact from a contact list programmed into the first electronic device. 10. The system of claim 9 , wherein the first electronic device includes a display module for displaying text and data. | 0.5 |
8,386,252 | 1 | 10 | 1. A method for enhancing communication understandability comprising: one or more of monitoring speech from a first participant in a conversation with a second participant or retrieving from a profile characteristics associated with the first participant; one or more of monitoring speech from the second participant in the conversation or retrieving from a profile characteristics associated with the second participant; identifying, by an enhancement understandability system having a processor and memory, characteristics that represent differences in style between the first and second participants; and utilizing one or more independently measurable components of speech that can affect understandability to provide an indication to each participant who is speaking of an estimated ease with which a participant in the conversation who is listening can understand the participant who is speaking. | 1. A method for enhancing communication understandability comprising: one or more of monitoring speech from a first participant in a conversation with a second participant or retrieving from a profile characteristics associated with the first participant; one or more of monitoring speech from the second participant in the conversation or retrieving from a profile characteristics associated with the second participant; identifying, by an enhancement understandability system having a processor and memory, characteristics that represent differences in style between the first and second participants; and utilizing one or more independently measurable components of speech that can affect understandability to provide an indication to each participant who is speaking of an estimated ease with which a participant in the conversation who is listening can understand the participant who is speaking. 10. One or more means for performing the method of claim 1 . | 0.885057 |
9,961,388 | 39 | 41 | 39. The system of claim 32 , wherein the client device: extends the security sandbox with a discovery algorithm and a relay algorithm through a discovery module and a relay module added to the security sandbox, and bypasses the pairing server having the discovery algorithm and the relay algorithm when establishing the communication session between the sandboxed application and the sandbox reachable service when the security is extended with the discovery algorithm and the relay algorithm through the discovery module and the relay module added to the security sandbox. | 39. The system of claim 32 , wherein the client device: extends the security sandbox with a discovery algorithm and a relay algorithm through a discovery module and a relay module added to the security sandbox, and bypasses the pairing server having the discovery algorithm and the relay algorithm when establishing the communication session between the sandboxed application and the sandbox reachable service when the security is extended with the discovery algorithm and the relay algorithm through the discovery module and the relay module added to the security sandbox. 41. The system of claim 39 : wherein the discovery algorithm utilizes a protocol comprising at least one of a Bonjour® protocol, a SSDP protocol, a LSD uTorrent® protocol, a multicast protocol, an anycast protocol, and another Local Area Network based protocol that discovers services in a Local Area Network based on a broadcast from any one of an operating system service, the security sandbox, the client device, the sandbox reachable service, and the networked device. | 0.747053 |
9,317,605 | 6 | 7 | 6. A method performed by data processing apparatus, the method comprising: receiving one or more characters from a user; transmitting the one or more characters to a forking engine; receiving, from the forking engine, data identifying (i) an auto-completion that corresponds to the one or more characters, and (ii) at least a first corpus, selected from a set of multiple corpora, that is associated with the auto-completion and to a first corpus score that satisfies a threshold and a universal search corpus that includes two or more of the multiple corpora and excludes the first corpus; and providing, for display in a drop down menu and to a user device, a first drop down entry that indicates a first representation of the auto-completion and that includes an icon representing the first corpus adjacent to the first representation of the auto-completion, and a second drop down entry that indicates a second representation of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus, wherein the universal search corpus includes two or more of a web search corpus, a places search corpus, a literature search corpus, a patent search corpus, an images search corpus, a videos search corpus, a news search corpus, a shopping search corpus, and a blogs search corpus. | 6. A method performed by data processing apparatus, the method comprising: receiving one or more characters from a user; transmitting the one or more characters to a forking engine; receiving, from the forking engine, data identifying (i) an auto-completion that corresponds to the one or more characters, and (ii) at least a first corpus, selected from a set of multiple corpora, that is associated with the auto-completion and to a first corpus score that satisfies a threshold and a universal search corpus that includes two or more of the multiple corpora and excludes the first corpus; and providing, for display in a drop down menu and to a user device, a first drop down entry that indicates a first representation of the auto-completion and that includes an icon representing the first corpus adjacent to the first representation of the auto-completion, and a second drop down entry that indicates a second representation of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus, wherein the universal search corpus includes two or more of a web search corpus, a places search corpus, a literature search corpus, a patent search corpus, an images search corpus, a videos search corpus, a news search corpus, a shopping search corpus, and a blogs search corpus. 7. The method of claim 6 , wherein: the one or more characters are received through a search box; and the first drop down entry that indicates the first representation of the auto-completion and that includes the icon representing the first corpus, and the second drop down entry that indicates the second representation of the auto-completion that corresponds to the universal search corpus are displayed in the drop down menu beneath the search box. | 0.712005 |
9,729,468 | 4 | 5 | 4. The system of claim 1 , wherein the profile-editing engine is further configured to, in response to the detecting of the manual selection of the graphical icon of the one of the concrete types of resources, display graphical icons of actual instances of resources in the infrastructure environment corresponding to the one of the concrete types of the resources. | 4. The system of claim 1 , wherein the profile-editing engine is further configured to, in response to the detecting of the manual selection of the graphical icon of the one of the concrete types of resources, display graphical icons of actual instances of resources in the infrastructure environment corresponding to the one of the concrete types of the resources. 5. The system of claim 4 , wherein the profile-editing engine is further configured to, in response to a detecting of a selection of a graphical icon of one of the actual instances of resources, establish a mapping between the one of the concrete types of the resources and the one of the actual instances of the resources. | 0.5 |
9,349,299 | 7 | 10 | 7. A method comprising: receiving, by an evaluation server, an educational standard and a lesson plan from a teacher client over a network; storing, by said evaluation server, said educational standard and said lesson plan in a database coupled to said evaluation server, wherein said database stores a student schedule; receiving, by said evaluation server, an educational standard selection and a lesson plan selection from said teacher client over said network, wherein said educational standard selection selects said educational standard stored in said database, wherein said lesson plan selection selects said lesson plan stored in said database; assigning, by said evaluation server, said educational standard to said lesson plan in said database based on said educational standard selection and said lesson plan selection such that said educational standard and said lesson plan are associated with said student schedule; receiving, by said evaluation server, a student login from a student client over said network; presenting, by said evaluation server, said educational standard and said lesson plan on said student client over said network based on said student schedule responsive to said receiving said student login; presenting, by said evaluation server, a Likert rating scale on said student client over said network based on said presenting said educational standard and said lesson plan on said student client; receiving, by said evaluation server, a rating from said student client over said network based on said Likert rating scale; storing, by said evaluation server, said rating in said database such that said rating is associated with said educational standard and said lesson plan, wherein said rating is anonymous to said teacher client based on said evaluation server not revealing a student identity associated with said student client to said teacher client, wherein said rating is not anonymous to an administrator client based on said evaluation server revealing said student identity to said administrator client; correlating, by said evaluation server, a test score with said rating associated with said educational standard and said lesson plan, wherein said test score is stored in said database; and providing, by said evaluation server, a notice to said administrator client over said network based on said correlating. | 7. A method comprising: receiving, by an evaluation server, an educational standard and a lesson plan from a teacher client over a network; storing, by said evaluation server, said educational standard and said lesson plan in a database coupled to said evaluation server, wherein said database stores a student schedule; receiving, by said evaluation server, an educational standard selection and a lesson plan selection from said teacher client over said network, wherein said educational standard selection selects said educational standard stored in said database, wherein said lesson plan selection selects said lesson plan stored in said database; assigning, by said evaluation server, said educational standard to said lesson plan in said database based on said educational standard selection and said lesson plan selection such that said educational standard and said lesson plan are associated with said student schedule; receiving, by said evaluation server, a student login from a student client over said network; presenting, by said evaluation server, said educational standard and said lesson plan on said student client over said network based on said student schedule responsive to said receiving said student login; presenting, by said evaluation server, a Likert rating scale on said student client over said network based on said presenting said educational standard and said lesson plan on said student client; receiving, by said evaluation server, a rating from said student client over said network based on said Likert rating scale; storing, by said evaluation server, said rating in said database such that said rating is associated with said educational standard and said lesson plan, wherein said rating is anonymous to said teacher client based on said evaluation server not revealing a student identity associated with said student client to said teacher client, wherein said rating is not anonymous to an administrator client based on said evaluation server revealing said student identity to said administrator client; correlating, by said evaluation server, a test score with said rating associated with said educational standard and said lesson plan, wherein said test score is stored in said database; and providing, by said evaluation server, a notice to said administrator client over said network based on said correlating. 10. The method of claim 7 , further comprising: receiving, by said evaluation server, a comment from said student client, wherein said comment is associated with said rating, wherein said rating and said comment are received contemporaneously. | 0.632931 |
9,576,041 | 7 | 11 | 7. A system for generating a database query, the system comprising: a user interface configured to receive a user selection from a user of one of a number of predetermined generic database queries; a processor which is coupled to a query statements database having a number of predetermined query statements and user specific query generator query statements associated with respective generic database queries, the processor also coupled to a user profile database having user profile data associated with the user, the user profile data comprising a user data statement table having a number of user data statements each comprising a relationship identifier and two or more data items; the processor configured to: automatically generate user specific data from the user profile data corresponding to the user, the user profile data comprising a user data statement table comprising a number of user data statements, wherein each user data statement comprises a relationship identifier and two or more data items, the user specific data being generated by: a) generating a user data items list comprising all of the data items comprised in the user data statement table; b) for each of a set of predetermined applicable query statements, each of the applicable query statements comprising an applicable relationship identifier, an applicable data item and a variable, inserting each of the data items held in the user data statement table into the applicable query statement and storing the applicable query statement in an applicability criteria data set if it matches one of the user data statements held in the user data statement table; c) for each of a set of predetermined effects query statements, each of the effects query statements comprising an effects relationship identifier and a variable, inserting each of the elements of the applicability criteria data set into the effects query statement and storing it in the user specific data if it matches one of the user data statements held in the user data statement table; the processor further configured to automatically apply the user specific data to a number of the user specific generator query statements in order to generate one or more user specific queries. | 7. A system for generating a database query, the system comprising: a user interface configured to receive a user selection from a user of one of a number of predetermined generic database queries; a processor which is coupled to a query statements database having a number of predetermined query statements and user specific query generator query statements associated with respective generic database queries, the processor also coupled to a user profile database having user profile data associated with the user, the user profile data comprising a user data statement table having a number of user data statements each comprising a relationship identifier and two or more data items; the processor configured to: automatically generate user specific data from the user profile data corresponding to the user, the user profile data comprising a user data statement table comprising a number of user data statements, wherein each user data statement comprises a relationship identifier and two or more data items, the user specific data being generated by: a) generating a user data items list comprising all of the data items comprised in the user data statement table; b) for each of a set of predetermined applicable query statements, each of the applicable query statements comprising an applicable relationship identifier, an applicable data item and a variable, inserting each of the data items held in the user data statement table into the applicable query statement and storing the applicable query statement in an applicability criteria data set if it matches one of the user data statements held in the user data statement table; c) for each of a set of predetermined effects query statements, each of the effects query statements comprising an effects relationship identifier and a variable, inserting each of the elements of the applicability criteria data set into the effects query statement and storing it in the user specific data if it matches one of the user data statements held in the user data statement table; the processor further configured to automatically apply the user specific data to a number of the user specific generator query statements in order to generate one or more user specific queries. 11. A system according to claim 7 , wherein the processor is further configured to receive a user identifier and determine which of the user profile data to apply based on the received user identifier. | 0.5 |
8,838,992 | 1 | 8 | 1. A computer-implemented method of identifying normal scripts, the method comprising: receiving a machine learning model and a feature set in a client computer, the machine learning model being trained using sample scripts that are known to be normal and sample scripts that are known to be potentially malicious and takes into account lexical and semantic characteristics of the sample scripts that are known to be normal and the sample scripts that are known to be potentially malicious; receiving a target script along with a web page in the client computer, the target script and the web page being received from a server computer over a computer network; extracting from the target script features that are included in the feature set; inputting the extracted features of the target script into the machine learning model to receive a classification of the target script from the machine learning model; and detecting that the target script is a normal script and not a potentially malicious script based on the classification of the target script. | 1. A computer-implemented method of identifying normal scripts, the method comprising: receiving a machine learning model and a feature set in a client computer, the machine learning model being trained using sample scripts that are known to be normal and sample scripts that are known to be potentially malicious and takes into account lexical and semantic characteristics of the sample scripts that are known to be normal and the sample scripts that are known to be potentially malicious; receiving a target script along with a web page in the client computer, the target script and the web page being received from a server computer over a computer network; extracting from the target script features that are included in the feature set; inputting the extracted features of the target script into the machine learning model to receive a classification of the target script from the machine learning model; and detecting that the target script is a normal script and not a potentially malicious script based on the classification of the target script. 8. The method of claim 1 further comprising: receiving another target script in the client computer; detecting that the other target script is a potentially malicious script based on a classification of the other target script by the machine learning model; and in response to detecting that the other target script is a potentially malicious script, initiating further examination of the other target script by an anti-malware running in the client computer. | 0.5 |
8,615,731 | 6 | 7 | 6. The system of claim 1 wherein in response to a first incoming event, the Run Time Framework generates a first web service using a first subset of the set of pre-built runtime services and not using a second subset of the set of pre-built runtime services. | 6. The system of claim 1 wherein in response to a first incoming event, the Run Time Framework generates a first web service using a first subset of the set of pre-built runtime services and not using a second subset of the set of pre-built runtime services. 7. The system of claim 6 wherein the second set of configuration files specifies that the first subset of the set of pre-built runtime services is to be used to generate the first web service. | 0.51269 |
7,672,845 | 4 | 5 | 4. The method of claim 1 , further comprising monitoring at least any one of a telephone call, an audio input, and a recording as a source of the speech. | 4. The method of claim 1 , further comprising monitoring at least any one of a telephone call, an audio input, and a recording as a source of the speech. 5. The method of claim 4 , wherein the monitoring includes monitoring a call delivered via one of a network, a digital phone line, an analog line, a voice-over-internet protocol (VOIP). | 0.5 |
9,954,805 | 6 | 7 | 6. The method of claim 1 , further comprising: storing the extracted features in a database. | 6. The method of claim 1 , further comprising: storing the extracted features in a database. 7. The method of claim 6 , wherein training the classifier model comprises: storing information about whether the user considered the email as graymail in the database; and performing supervised learning in the classifier model using the stored extracted features and stored information about whether the user considered the email as graymail. | 0.5 |
8,789,015 | 4 | 6 | 4. A computing device comprising: a processing system; one or more modules operable at least in part via hardware of the processing system to implement an integrated development environment (IDE) configured to: ascertain one or more languages selected by developer for translations of an application under development using the IDE; and during a build of the application via the IDE, create updated localization files for each of the selected languages in a designated file format established to facilitate translations used to generate a single multilingual resource file for the application, wherein creation of the updated localization files comprises: producing a log file in a system format that describes resources for the build of the application; parsing the log file to identify and extract localizable resources in the build; converting the extracted localizable resources to generate a source resource file for the build in the designated file format; and merging the source resource file with target localization files included in the project for the one or more languages to form localization files that are updated for the build, wherein the merging comprises, for each target localization file: comparing resources between the source resource file and the target localization file to find matching resources; and updating the resources in the source resource file with matching resources from the target localization file to form an updated version of the target localization file that incorporates modifications to resources for the build from the source resource file and previously translated resources from the target localization file. | 4. A computing device comprising: a processing system; one or more modules operable at least in part via hardware of the processing system to implement an integrated development environment (IDE) configured to: ascertain one or more languages selected by developer for translations of an application under development using the IDE; and during a build of the application via the IDE, create updated localization files for each of the selected languages in a designated file format established to facilitate translations used to generate a single multilingual resource file for the application, wherein creation of the updated localization files comprises: producing a log file in a system format that describes resources for the build of the application; parsing the log file to identify and extract localizable resources in the build; converting the extracted localizable resources to generate a source resource file for the build in the designated file format; and merging the source resource file with target localization files included in the project for the one or more languages to form localization files that are updated for the build, wherein the merging comprises, for each target localization file: comparing resources between the source resource file and the target localization file to find matching resources; and updating the resources in the source resource file with matching resources from the target localization file to form an updated version of the target localization file that incorporates modifications to resources for the build from the source resource file and previously translated resources from the target localization file. 6. The computing device of claim 4 , wherein the designated file format comprises extensible markup language localization interchange file format (XLIFF). | 0.832972 |
9,916,533 | 8 | 9 | 8. A computer program product for ingesting a plurality of content according to a statistical similarity of at least one portion of the ingested plurality of content into an online information handling system running on a first computer and capable of answering questions, wherein the ingested plurality of content is based on a received topic entered on a second computer and ingesting the plurality of content comprises ingesting a plurality of documents associated with the received topic, wherein the ingested plurality of documents are acquired from searching a plurality of online sources including a plurality of repositories and internet, the computer program product comprising: one or more computer-readable non-transitory storage devices and program instructions stored on at least one of the one or more computer readable non-transitory storage devices, the program instructions executable by a processor, the program instructions comprising: program instructions to determine at least one similarity between each document within the ingested plurality of documents based on a similarity criteria, wherein the similarity content comprises a predetermined threshold including a context, a number of times repeated, a confidence, a location, and an author; program instructions to apply a statistical model to characterize the determined at least one similarity between each document within the ingested plurality of documents; program instructions to create at least one pair-wise link between a word, an image, or a plurality of other media for each document within the ingested plurality of documents based on the applied statistical model, wherein the created at least one pair-wise link is a hyperlink between at least two documents within the ingested plurality of documents and is created using text mining techniques; program instructions to map the created at least one pair-wise link for a first document within the ingested plurality of documents to at least one other document within the ingested plurality of documents based on a context of the word, the image, or the plurality of other media; program instructions to generate a plurality of rules for ingesting a plurality of additional content based on the mapping of the created at least one pair-wise link; program instructions to store the generated plurality of rules in an online repository; program instructions to retrieve and utilize the stored plurality of rules when a plurality of future documents are loaded into the online information handling system; program instructions to create a plurality of hard and soft links between a word, an image, or a plurality of other media for each document within the ingested plurality of documents based on the applied statistical model, wherein each hard link within the plurality of hard and soft links meets or exceeds a predetermined threshold and each soft link within the plurality of hard and soft links falls below a predetermined threshold; and program instructions to create a single annotation between each document within the ingested plurality of documents based on each hard link and each soft link within the plurality of hard and soft links. | 8. A computer program product for ingesting a plurality of content according to a statistical similarity of at least one portion of the ingested plurality of content into an online information handling system running on a first computer and capable of answering questions, wherein the ingested plurality of content is based on a received topic entered on a second computer and ingesting the plurality of content comprises ingesting a plurality of documents associated with the received topic, wherein the ingested plurality of documents are acquired from searching a plurality of online sources including a plurality of repositories and internet, the computer program product comprising: one or more computer-readable non-transitory storage devices and program instructions stored on at least one of the one or more computer readable non-transitory storage devices, the program instructions executable by a processor, the program instructions comprising: program instructions to determine at least one similarity between each document within the ingested plurality of documents based on a similarity criteria, wherein the similarity content comprises a predetermined threshold including a context, a number of times repeated, a confidence, a location, and an author; program instructions to apply a statistical model to characterize the determined at least one similarity between each document within the ingested plurality of documents; program instructions to create at least one pair-wise link between a word, an image, or a plurality of other media for each document within the ingested plurality of documents based on the applied statistical model, wherein the created at least one pair-wise link is a hyperlink between at least two documents within the ingested plurality of documents and is created using text mining techniques; program instructions to map the created at least one pair-wise link for a first document within the ingested plurality of documents to at least one other document within the ingested plurality of documents based on a context of the word, the image, or the plurality of other media; program instructions to generate a plurality of rules for ingesting a plurality of additional content based on the mapping of the created at least one pair-wise link; program instructions to store the generated plurality of rules in an online repository; program instructions to retrieve and utilize the stored plurality of rules when a plurality of future documents are loaded into the online information handling system; program instructions to create a plurality of hard and soft links between a word, an image, or a plurality of other media for each document within the ingested plurality of documents based on the applied statistical model, wherein each hard link within the plurality of hard and soft links meets or exceeds a predetermined threshold and each soft link within the plurality of hard and soft links falls below a predetermined threshold; and program instructions to create a single annotation between each document within the ingested plurality of documents based on each hard link and each soft link within the plurality of hard and soft links. 9. The computer program product of claim 8 , further comprising: utilizing the generated plurality of rules for ingesting the plurality of additional content. | 0.5 |
9,965,461 | 1 | 2 | 1. A method comprising: using at least a processor and memory for performing syntactic and semantic analysis by: receiving a natural language predicating expression; determining, by the processor, a first thematic role sequence; determining, by the processor, a second thematic role sequence; applying, by the processor, the first thematic role sequence to the natural language predicating expression; applying, by the processor, the second thematic role sequence to the natural language predicating expression for determining a standardized order of thematic roles contained in the first thematic role sequence; constructing, by the processor, a representation of an artificial language predicating expression with the standardized order of thematic roles contained in the first thematic role sequence in which predicate arguments are represented using the applied second thematic role sequence, wherein the representation of the artificial language predicating expression comprises a specification of an artificial logical predicate and a specification of the predicate arguments of the logical predicate, wherein each of the arguments corresponds to at least one thematic role in the first thematic role sequences; and displaying in a user interface the representation of the artificial language predicating expression based on at least one thematic role included in the first thematic role sequence and the second thematic role sequence, wherein constructing the representation of an artificial language predicating expression with the standardized order by the processor, in which predicate arguments are presented, thereby constructing the representation of an artificial language predicating expression with the standardized order by the processor improves the processing speed and efficiency of syntactic and semantic analysis at the processor. | 1. A method comprising: using at least a processor and memory for performing syntactic and semantic analysis by: receiving a natural language predicating expression; determining, by the processor, a first thematic role sequence; determining, by the processor, a second thematic role sequence; applying, by the processor, the first thematic role sequence to the natural language predicating expression; applying, by the processor, the second thematic role sequence to the natural language predicating expression for determining a standardized order of thematic roles contained in the first thematic role sequence; constructing, by the processor, a representation of an artificial language predicating expression with the standardized order of thematic roles contained in the first thematic role sequence in which predicate arguments are represented using the applied second thematic role sequence, wherein the representation of the artificial language predicating expression comprises a specification of an artificial logical predicate and a specification of the predicate arguments of the logical predicate, wherein each of the arguments corresponds to at least one thematic role in the first thematic role sequences; and displaying in a user interface the representation of the artificial language predicating expression based on at least one thematic role included in the first thematic role sequence and the second thematic role sequence, wherein constructing the representation of an artificial language predicating expression with the standardized order by the processor, in which predicate arguments are presented, thereby constructing the representation of an artificial language predicating expression with the standardized order by the processor improves the processing speed and efficiency of syntactic and semantic analysis at the processor. 2. The method of claim 1 , further comprising receiving a grammar rule, wherein the first thematic role sequence and the second thematic role sequence are associated with the grammar rule. | 0.932374 |
7,856,472 | 1 | 43 | 1. In a computer system including a plurality of n-tuples, each of the plurality of n-tuples including n>1 text strings, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match one or more text strings in a first one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match the one or more text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a plurality of message summaries; wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages and second information derived from a second message of a plurality of second messages associated with at least one online forum; displaying, utilizing the at least one window, a first set of representations; receiving first input from the user indicating a selection of one of the first set of representations; displaying a second set of representations representing a set of hyperlinks, utilizing the at least one window, in response to receiving the first input; receiving second input from the user indicating a selection of one of the second set of representations; and navigating to a destination specified by the selected one of the second set of representations, in response to receiving the second input. | 1. In a computer system including a plurality of n-tuples, each of the plurality of n-tuples including n>1 text strings, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match one or more text strings in a first one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match the one or more text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a plurality of message summaries; wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages and second information derived from a second message of a plurality of second messages associated with at least one online forum; displaying, utilizing the at least one window, a first set of representations; receiving first input from the user indicating a selection of one of the first set of representations; displaying a second set of representations representing a set of hyperlinks, utilizing the at least one window, in response to receiving the first input; receiving second input from the user indicating a selection of one of the second set of representations; and navigating to a destination specified by the selected one of the second set of representations, in response to receiving the second input. 43. The method of claim 1 , wherein at least one field that is displayed with the message summaries is determined by a user selection. | 0.835381 |
6,035,269 | 1 | 4 | 1. A computer-implemented method for generating a substitute text string, comprising the steps of: providing a morphological graph including a first state, a last state, and at least one morpheme transition between the first state and the last state; receiving morpho-syntactical data associated with an original phrase, the morpho-syntactical data including a stem corresponding to the first state, at least one bound morpheme, and attribute bits describing the original phrase; applying a critique to the morpho-syntactical data, the critique including a trigger and an action; determining whether the trigger is satisfied by the morpho-syntactical data; and if the trigger is satisfied, performing the steps of: preparing a morpheme list and a bit list corresponding to the action; traversing the morphological graph by a first pass from the last state to the first state in a breadth-first manner, with a graph path of the first pass being determined by the contents of the morpheme list and the bit list; traversing the morphological by a second pass from the first state to the last state in a depth-first manner, with a reconstructed graph path being determined by nodes of the graph path of the first pass; and providing a substitute string corresponding to the reconstructed path. | 1. A computer-implemented method for generating a substitute text string, comprising the steps of: providing a morphological graph including a first state, a last state, and at least one morpheme transition between the first state and the last state; receiving morpho-syntactical data associated with an original phrase, the morpho-syntactical data including a stem corresponding to the first state, at least one bound morpheme, and attribute bits describing the original phrase; applying a critique to the morpho-syntactical data, the critique including a trigger and an action; determining whether the trigger is satisfied by the morpho-syntactical data; and if the trigger is satisfied, performing the steps of: preparing a morpheme list and a bit list corresponding to the action; traversing the morphological graph by a first pass from the last state to the first state in a breadth-first manner, with a graph path of the first pass being determined by the contents of the morpheme list and the bit list; traversing the morphological by a second pass from the first state to the last state in a depth-first manner, with a reconstructed graph path being determined by nodes of the graph path of the first pass; and providing a substitute string corresponding to the reconstructed path. 4. The method of claim 1, wherein the trigger defines a test condition associated with the attribute bits. | 0.825083 |
8,375,027 | 12 | 13 | 12. A computer program product comprising a computer readable storage recording medium having computer code thereon, said computer code causing a computer to execute the operations of: extracting a plurality of common keywords associated with a piece of searching object data; storing said plurality of extracted common keywords into storage means; accepting a selected keyword selected by a user from said plurality of common keywords stored in said storage means; calculating exclusion efficiency indicating a level of exclusion efficiency of data that is not associated with said selected keyword for an individual common keyword of said plurality of common keywords stored in said storage means except for said selected keyword when said common keyword is specified as an exclusion keyword; and providing said exclusion efficiency to a user; wherein said calculating exclusion efficiency utilizes the selection keyword, the exclusion keyword, a searching object population set, and a calculation of a set of document data in which the selection keyword or the exclusion keyword appears in the searching object population set and determines a first set, a second set and a third set; wherein the first set comprises a set of document data in which the selection keyword appears in the searching object population set; wherein the second set comprises a set of document data in which the exclusion keyword appears in the first set; wherein the third set comprises a set of document data in which the exclusion keyword appears in the searching object population set wherein said calculating exclusion efficiency is based on a combination of a first term and a second term; wherein the first term comprises a ratio of a difference between a number of elements in a first set and a total number of elements in a second set, and the number of elements in the first set; wherein the second term comprises a ratio of a total number of elements in a third set and a total number of elements in the searching object population set; wherein the first term is adjusted by a first weight, and wherein the second term is adjusted by a second weight; wherein the sum of the first weight and the second weight is 1. | 12. A computer program product comprising a computer readable storage recording medium having computer code thereon, said computer code causing a computer to execute the operations of: extracting a plurality of common keywords associated with a piece of searching object data; storing said plurality of extracted common keywords into storage means; accepting a selected keyword selected by a user from said plurality of common keywords stored in said storage means; calculating exclusion efficiency indicating a level of exclusion efficiency of data that is not associated with said selected keyword for an individual common keyword of said plurality of common keywords stored in said storage means except for said selected keyword when said common keyword is specified as an exclusion keyword; and providing said exclusion efficiency to a user; wherein said calculating exclusion efficiency utilizes the selection keyword, the exclusion keyword, a searching object population set, and a calculation of a set of document data in which the selection keyword or the exclusion keyword appears in the searching object population set and determines a first set, a second set and a third set; wherein the first set comprises a set of document data in which the selection keyword appears in the searching object population set; wherein the second set comprises a set of document data in which the exclusion keyword appears in the first set; wherein the third set comprises a set of document data in which the exclusion keyword appears in the searching object population set wherein said calculating exclusion efficiency is based on a combination of a first term and a second term; wherein the first term comprises a ratio of a difference between a number of elements in a first set and a total number of elements in a second set, and the number of elements in the first set; wherein the second term comprises a ratio of a total number of elements in a third set and a total number of elements in the searching object population set; wherein the first term is adjusted by a first weight, and wherein the second term is adjusted by a second weight; wherein the sum of the first weight and the second weight is 1. 13. The program product according to claim 12 , wherein said calculating operation comprises causing the computer to calculate said exclusion efficiency, for an individual common keyword of said plurality of common keywords stored in said storage means except for said selected keyword, based on a first parameter indicating a level of exclusion efficiency in a set of data that is associated with said selected keyword when said keyword is specified as the exclusion keyword and a second parameter indicating a level of exclusion efficiency in a set of all of said searching object data when said keyword is specified as the exclusion keyword. | 0.5 |
9,690,894 | 11 | 15 | 11. A system comprising: one or more memory devices at least collectively storing a non-transitory processor-executable code configured to implement instructions; one or more processing devices to execute the processor-executable code to implement the instructions, the instructions configured to cause operations to be performed including: accessing an algorithmic description representation of a circuit design, the algorithmic description representation being specified in a first language and including at least one programming language construct associated with a first safety data type; and compiling the algorithmic description representation of the circuit design, the compiling including: identifying the at least one programming language construct, accessing a first safety data type definition associated with the first safety data type, and generating a second representation of the circuit design based on the algorithmic description representation and the first safety data type definition, the second representation being provided in a second language and including at least one safety feature for a portion of the circuit design associated with the at least one programming language construct. | 11. A system comprising: one or more memory devices at least collectively storing a non-transitory processor-executable code configured to implement instructions; one or more processing devices to execute the processor-executable code to implement the instructions, the instructions configured to cause operations to be performed including: accessing an algorithmic description representation of a circuit design, the algorithmic description representation being specified in a first language and including at least one programming language construct associated with a first safety data type; and compiling the algorithmic description representation of the circuit design, the compiling including: identifying the at least one programming language construct, accessing a first safety data type definition associated with the first safety data type, and generating a second representation of the circuit design based on the algorithmic description representation and the first safety data type definition, the second representation being provided in a second language and including at least one safety feature for a portion of the circuit design associated with the at least one programming language construct. 15. The system of claim 11 , wherein the at least one programming language construct includes at least one variable defined using the first safety data type. | 0.692157 |
9,070,247 | 11 | 17 | 11. An apparatus for use with a separate electronic game, the apparatus comprising: an audio-video display; a stand for supporting the audio-video display and for placing the audio-video display in a standalone position near a separate electronic game; an interface for receiving standard output from the separate electronic game; a circumstances inventory (CI) engine that includes a game states queue and a player attributes queue, and wherein the CI engine is programmed with instructions to: collect current standard game states in the game states queue, and receive and store player information in the player attributes queue, wherein the player information is derived from a player tracking platform, wherein the player tracking platform is physically separate from the apparatus; an artificial intelligence (AI) engine in communication with the CI engine, and wherein the AI engine is configured with instructions to: create associations between received standard game states and possible emotions for a virtual human bystander, create associations between received player information and possible emotions for the virtual human bystander, save the associations, and select an emotion for the virtual human bystander based on the saved associations; a converter configured with instructions to translate the standard game output or a standard game state to an animated behavior and an animated speech for the virtual human bystander; and a projector configured with instructions to display on the audio-video display the virtual human bystander based on the animated behavior, the animated speech and the selected emotion for a current game state. | 11. An apparatus for use with a separate electronic game, the apparatus comprising: an audio-video display; a stand for supporting the audio-video display and for placing the audio-video display in a standalone position near a separate electronic game; an interface for receiving standard output from the separate electronic game; a circumstances inventory (CI) engine that includes a game states queue and a player attributes queue, and wherein the CI engine is programmed with instructions to: collect current standard game states in the game states queue, and receive and store player information in the player attributes queue, wherein the player information is derived from a player tracking platform, wherein the player tracking platform is physically separate from the apparatus; an artificial intelligence (AI) engine in communication with the CI engine, and wherein the AI engine is configured with instructions to: create associations between received standard game states and possible emotions for a virtual human bystander, create associations between received player information and possible emotions for the virtual human bystander, save the associations, and select an emotion for the virtual human bystander based on the saved associations; a converter configured with instructions to translate the standard game output or a standard game state to an animated behavior and an animated speech for the virtual human bystander; and a projector configured with instructions to display on the audio-video display the virtual human bystander based on the animated behavior, the animated speech and the selected emotion for a current game state. 17. The apparatus of claim 11 , wherein the created associations are marked according to one of a list consisting of weak, normal, strong and forbidden, wherein the marking assists the AI engine in selecting the emotion. | 0.580153 |
9,213,707 | 1 | 11 | 1. A computer implemented method for interrelating a plurality of source data files and providing access to said interrelated source data files, said computer implemented method comprising: providing an interrelated data integration application comprising an interlinear sort component and an interrelated data access component executable by at least one processor, wherein said interrelated data integration application is configured to sort and access a plurality of records in said source data files according to a graphical representation of a lineage relationship between said source data files defined in a configuration language; providing a parsing component executable by at least one processor, said parsing component configured to compile said configuration language and generate file descriptors usable by said interlinear sort component and said interrelated data access component of said interrelated data integration application, said configuration language configured to define: said lineage relationship between said source data files, each of said source data files containing one or more of said records, wherein said source data files are graphically related to each other in a tree structure using an array of symbols; one or more adopt key fields, wherein a common one of said one or more adopt key fields is configured to relate each child file containing one or more child file records to a corresponding parent file containing one or more parent file records in said tree structure; one or more order key fields configured to define ordering criteria for said records of one or more of said source data files; and one or more predetermined subprograms configured to process instances of one or more of said records from said source data files, a start point of one of a sequence and a subsequence of said records of said source data files, and an end point of said one of said sequence and said subsequence of said records of said source data files; sorting said each of said source data files based on one or more of said lineage relationship, said one or more order key fields, and said one or more adopt key fields defined in said configuration language, and attaching a position number to each of said records of said each of said source data files, by said interlinear sort component of said interrelated data integration application; accessing said records in said source data files reordered by said interlinear sort component based on said lineage relationship between said source data files, and using said position number to determine access of a subsequent one of said records, by said interrelated data access component of said interrelated data integration application; and outputting on a user device responsive to a user request at runtime a set of records comprising a common lineage relationship. | 1. A computer implemented method for interrelating a plurality of source data files and providing access to said interrelated source data files, said computer implemented method comprising: providing an interrelated data integration application comprising an interlinear sort component and an interrelated data access component executable by at least one processor, wherein said interrelated data integration application is configured to sort and access a plurality of records in said source data files according to a graphical representation of a lineage relationship between said source data files defined in a configuration language; providing a parsing component executable by at least one processor, said parsing component configured to compile said configuration language and generate file descriptors usable by said interlinear sort component and said interrelated data access component of said interrelated data integration application, said configuration language configured to define: said lineage relationship between said source data files, each of said source data files containing one or more of said records, wherein said source data files are graphically related to each other in a tree structure using an array of symbols; one or more adopt key fields, wherein a common one of said one or more adopt key fields is configured to relate each child file containing one or more child file records to a corresponding parent file containing one or more parent file records in said tree structure; one or more order key fields configured to define ordering criteria for said records of one or more of said source data files; and one or more predetermined subprograms configured to process instances of one or more of said records from said source data files, a start point of one of a sequence and a subsequence of said records of said source data files, and an end point of said one of said sequence and said subsequence of said records of said source data files; sorting said each of said source data files based on one or more of said lineage relationship, said one or more order key fields, and said one or more adopt key fields defined in said configuration language, and attaching a position number to each of said records of said each of said source data files, by said interlinear sort component of said interrelated data integration application; accessing said records in said source data files reordered by said interlinear sort component based on said lineage relationship between said source data files, and using said position number to determine access of a subsequent one of said records, by said interrelated data access component of said interrelated data integration application; and outputting on a user device responsive to a user request at runtime a set of records comprising a common lineage relationship. 11. The computer implemented method of claim 1 , wherein said accessing of said records in said source data files reordered by said interlinear sort component comprises: executing one of said one or more predetermined subprograms configured to process said instances of a current one of said records of a current one of said source data files; and accessing a subsequent one of said source data files using a parent position number attached to said current one of said records of said current one of said source data files. | 0.69977 |
7,694,145 | 1 | 12 | 1. A computer-implemented method for presenting status of digital signatures, the method comprising: receiving a digital document that defines a presentation structure and includes a digital signature, the digital document specifying a representation of the digital signature and a location in the presentation structure for the representation of the digital signature; determining a status for the digital signature; associating a status representation with the digital signature, the status representation identifying the status determined for the digital signature; without altering the representation of the digital signature, presenting at least a portion of the digital document and the status representation of the digital signature in a user interface, the status representation being presented in the presentation structure at a location that depends upon the location in the presentation structure for the representation of the digital signature; and presenting information in the user interface about the status determined for the digital signature in response to a user input, wherein the user input comprises an indication of a selection of the digital signature in the user interface. | 1. A computer-implemented method for presenting status of digital signatures, the method comprising: receiving a digital document that defines a presentation structure and includes a digital signature, the digital document specifying a representation of the digital signature and a location in the presentation structure for the representation of the digital signature; determining a status for the digital signature; associating a status representation with the digital signature, the status representation identifying the status determined for the digital signature; without altering the representation of the digital signature, presenting at least a portion of the digital document and the status representation of the digital signature in a user interface, the status representation being presented in the presentation structure at a location that depends upon the location in the presentation structure for the representation of the digital signature; and presenting information in the user interface about the status determined for the digital signature in response to a user input, wherein the user input comprises an indication of a selection of the digital signature in the user interface. 12. The method of claim 1 , wherein the presented information comprises an explanation of the determined status. | 0.929293 |
9,002,758 | 5 | 11 | 5. The process of claim 3 , wherein the process action of generating training data from the training set of tasks, comprises the actions of: for each task in the training set, for each input-output example in the task, establishing a set of transformation programs inductively synthesized from the input-output example, each of which produces the output string in the example from a tuple of input strings in the example, establishing a set of positive training sub-expressions from the set of transformation programs, establishing a set of negative training sub-expressions from the set of transformation programs, and generating the training data from each substring expression in the sets of positive and negative training sub-expressions. | 5. The process of claim 3 , wherein the process action of generating training data from the training set of tasks, comprises the actions of: for each task in the training set, for each input-output example in the task, establishing a set of transformation programs inductively synthesized from the input-output example, each of which produces the output string in the example from a tuple of input strings in the example, establishing a set of positive training sub-expressions from the set of transformation programs, establishing a set of negative training sub-expressions from the set of transformation programs, and generating the training data from each substring expression in the sets of positive and negative training sub-expressions. 11. The process of claim 5 , wherein the process action of establishing ranking schemes for regular expressions and position expressions, comprises an action of computing a dictionary that maps sub-expressions that generate an output substring that takes values from a set having a finite number of pre-defined tokens to a frequency-based score based on their frequencies in the sets of positive training sub-expressions. | 0.868847 |
9,288,543 | 5 | 6 | 5. The method of claim 1 , wherein the executing further performs: communicating an advertisement to a user with the media content. | 5. The method of claim 1 , wherein the executing further performs: communicating an advertisement to a user with the media content. 6. The method of claim 5 , wherein the executing further performs: selecting the advertisement based at least in part upon the respective profile of the user. | 0.75 |
9,153,284 | 1 | 4 | 1. A video signal generating apparatus comprising: a camera configured to generate a video signal; and circuitry configured to operate said camera, the circuitry having a plurality of options, each option corresponding to a different operation to be performed on a video signal receiving apparatus; generate text data in response selection of an option from the plurality of options on said circuitry; and insert said text data generated by said circuitry into said video signal, wherein said text data inserted into said video signal is representative of the operation corresponding to the selected option, the video signal receiving apparatus configured to receive said video signal, extract the inserted text from said video signal, interpret said inserted text data extracted from the video signal as the selected operation to be performed on said video signal by the video signal receiving apparatus, and automatically perform the selected operation on the video signal, wherein said video signal receiving apparatus is external to said video signal generating apparatus, and the video signal receiving apparatus performs the selected operation at a point in time in the video signal from which the inserted text corresponding to the selected operation was extracted. | 1. A video signal generating apparatus comprising: a camera configured to generate a video signal; and circuitry configured to operate said camera, the circuitry having a plurality of options, each option corresponding to a different operation to be performed on a video signal receiving apparatus; generate text data in response selection of an option from the plurality of options on said circuitry; and insert said text data generated by said circuitry into said video signal, wherein said text data inserted into said video signal is representative of the operation corresponding to the selected option, the video signal receiving apparatus configured to receive said video signal, extract the inserted text from said video signal, interpret said inserted text data extracted from the video signal as the selected operation to be performed on said video signal by the video signal receiving apparatus, and automatically perform the selected operation on the video signal, wherein said video signal receiving apparatus is external to said video signal generating apparatus, and the video signal receiving apparatus performs the selected operation at a point in time in the video signal from which the inserted text corresponding to the selected operation was extracted. 4. The video signal generating apparatus according to claim 1 , wherein said circuitry includes a video frame of interest executor configured to be operated regarding a video frame of interest so that the frame is communicated as a point of interest to said video signal receiving apparatus configured to receive said video signal with said inserted text data, and said circuitry further configured to generate text data designating said point of interest in response to the selected option. | 0.560823 |
7,823,054 | 1 | 6 | 1. A computer-implemented method performed by an application of a data processing system, the method comprising: accessing a first document presentation other than a default initial document presentation based on an address displayed within an address field of a window, wherein the first document presentation is displayed within a display area of the window; recording a first location of the first document presentation; accessing and displaying in the display area of the window a sequence of intermediate document presentations originated from the first document presentation; displaying a first snapback button associated with the address field; conducting a search via a search facility based on one or more search keywords entered in a search field of the window; displaying a search result in the display area of the window; in response to a first input received via the first snapback button, without having to select from a menu of document presentations, directly retrieving and displaying the first document presentation from the first location without having to access the intermediate document presentations again; and displaying a second snapback button associated with the search field, wherein the second snapback button is used to directly redisplay the search result in the display area of the window. | 1. A computer-implemented method performed by an application of a data processing system, the method comprising: accessing a first document presentation other than a default initial document presentation based on an address displayed within an address field of a window, wherein the first document presentation is displayed within a display area of the window; recording a first location of the first document presentation; accessing and displaying in the display area of the window a sequence of intermediate document presentations originated from the first document presentation; displaying a first snapback button associated with the address field; conducting a search via a search facility based on one or more search keywords entered in a search field of the window; displaying a search result in the display area of the window; in response to a first input received via the first snapback button, without having to select from a menu of document presentations, directly retrieving and displaying the first document presentation from the first location without having to access the intermediate document presentations again; and displaying a second snapback button associated with the search field, wherein the second snapback button is used to directly redisplay the search result in the display area of the window. 6. The method of claim 1 , further comprising: accessing a second document presentation from the first document presentation; and recording a second location of the second document presentation in response to a user request, wherein the recordation of the second location causes the first location to be unrecorded. | 0.659091 |
8,117,225 | 42 | 44 | 42. The computer program product of claim 15 , and further comprising: code for receiving a request to access a digital entity associated with at least one of the different online applications. | 42. The computer program product of claim 15 , and further comprising: code for receiving a request to access a digital entity associated with at least one of the different online applications. 44. The computer program product of claim 42 , wherein the digital entity includes a file. | 0.730539 |
7,792,808 | 1 | 16 | 1. A method of searching an electronic database having a plurality of database records that each include at least one alphanumeric search field, comprising, one or more processors that implement the steps of: inputting a search query that includes a virtual search parameter which is an attribute but not part of a requested database record, and the attribute being a characteristic of the requested database record but not unrequested database records; executing the search query; and selecting at least one database record that matches the search query but the attribute is not part of the at least one alphanumeric search field. | 1. A method of searching an electronic database having a plurality of database records that each include at least one alphanumeric search field, comprising, one or more processors that implement the steps of: inputting a search query that includes a virtual search parameter which is an attribute but not part of a requested database record, and the attribute being a characteristic of the requested database record but not unrequested database records; executing the search query; and selecting at least one database record that matches the search query but the attribute is not part of the at least one alphanumeric search field. 16. The method of claim 1 wherein the inputting step includes a step of vocalizing at least a portion of the search query to a voice recognition system. | 0.715356 |
7,496,514 | 15 | 16 | 15. The computer program product of claim 13 , wherein the set of computer instructions comprises further instructions to manage the audible rendering of responses based on a delivery mode subject to selection by the user. | 15. The computer program product of claim 13 , wherein the set of computer instructions comprises further instructions to manage the audible rendering of responses based on a delivery mode subject to selection by the user. 16. The computer program product of claim 15 , wherein the delivery mode is one of an immediate delivery mode and a delayed delivery mode. | 0.5 |
9,684,498 | 8 | 14 | 8. An electronic apparatus using an operating system, the electronic apparatus comprising: a processor and a memory including computer program code executed by the processor; the code comprising: a compiling module, for packaging a first package the which supports a plurality of language versions into a plurality of first single-language package files, wherein the plurality of first single-language package files correspond to the plurality of language versions, respectively, wherein names of the plurality of first single-language package files are strings corresponding to a name of the first package file and language codes related to the plurality of language versions; a package management system, for adding the plurality of first single-language package files to a plurality of language packages, respectively; and a resource management system, when changing a language version of an application to a specific language, the resource management system searching a system language package corresponding to the specific language in a system file, and when unable to find the system language package corresponding the specific language in the system file, the packet management system searching the language package corresponding to the specific language in the plurality of language packages, and loading the language package corresponding to the specific language. | 8. An electronic apparatus using an operating system, the electronic apparatus comprising: a processor and a memory including computer program code executed by the processor; the code comprising: a compiling module, for packaging a first package the which supports a plurality of language versions into a plurality of first single-language package files, wherein the plurality of first single-language package files correspond to the plurality of language versions, respectively, wherein names of the plurality of first single-language package files are strings corresponding to a name of the first package file and language codes related to the plurality of language versions; a package management system, for adding the plurality of first single-language package files to a plurality of language packages, respectively; and a resource management system, when changing a language version of an application to a specific language, the resource management system searching a system language package corresponding to the specific language in a system file, and when unable to find the system language package corresponding the specific language in the system file, the packet management system searching the language package corresponding to the specific language in the plurality of language packages, and loading the language package corresponding to the specific language. 14. The electronic apparatus of claim 8 , wherein the plurality of language packages are in a language package set. | 0.884073 |
7,956,844 | 5 | 8 | 5. A handheld electronic device comprising: an input apparatus comprising a plurality of input members, at least some of the input members each having a number of linguistic elements assigned thereto; a processor apparatus comprising a processor and a memory, the memory having stored therein a plurality of language objects and a number of word frames; at least some of the language objects each comprising a number of the linguistic elements; and the memory having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to be adapted to perform operations comprising: detecting an entry of a new language object not already stored in the memory, the new language object comprising a plurality of linguistic elements; determining that the at least a portion of the plurality of linguistic elements of the new language object comprises a sequential plurality of linguistic elements that are each assigned to a given input member; associating the new language object with a word frame, wherein the word frame is associated with a language object having a number of linguistic elements that is different from a number of linguistic elements of the new language object, and wherein the word frame comprises at least some of the plurality of linguistic elements of the new language object and a representation of the given input member in place of the sequential plurality of linguistic elements that are each assigned to the given input member. | 5. A handheld electronic device comprising: an input apparatus comprising a plurality of input members, at least some of the input members each having a number of linguistic elements assigned thereto; a processor apparatus comprising a processor and a memory, the memory having stored therein a plurality of language objects and a number of word frames; at least some of the language objects each comprising a number of the linguistic elements; and the memory having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to be adapted to perform operations comprising: detecting an entry of a new language object not already stored in the memory, the new language object comprising a plurality of linguistic elements; determining that the at least a portion of the plurality of linguistic elements of the new language object comprises a sequential plurality of linguistic elements that are each assigned to a given input member; associating the new language object with a word frame, wherein the word frame is associated with a language object having a number of linguistic elements that is different from a number of linguistic elements of the new language object, and wherein the word frame comprises at least some of the plurality of linguistic elements of the new language object and a representation of the given input member in place of the sequential plurality of linguistic elements that are each assigned to the given input member. 8. The handheld electronic device of claim 5 wherein the operations further comprise detecting as said entry one of: a number of input member actuations, and a quantity of received text. | 0.870654 |
8,706,742 | 1 | 2 | 1. A system for computerized derivation of leads from a huge body of data, the system comprising: an electronic repository including a multiplicity of accesses to a respective multiplicity of electronic documents and metadata including metadata parameters having metadata values characterizing each of said multiplicity of electronic documents; a document rater using a processor to run a first computer algorithm on said multiplicity of electronic documents which yields a score which rates each of said multiplicity of electronic documents; and a metadata-based document discriminator using the processor to run a second computer algorithm on at least some of said metadata which yields leads, each lead comprising at least one metadata value for at least one metadata parameter, whose value correlates with the score of said electronic documents, wherein said discriminator is operative to perform the following for each of a multiplicity of logical conditions defined over the individual documents' metadata: a. access a subset of said multiplicity of electronic documents wherein membership in said subset, of an individual document from among said multiplicity of electronic documents, is determined by whether or not a current logical condition defined over said individual documents' metadata, is true; b. compute at least one first value, including a proportion of documents having a relevance score whose value is “relevant”, over at least one subset; c. Provide a second value including a proportion of documents having a relevance score whose value is “relevant” from among all of said multiplicity of electronic documents; and d. compare said first value to the second value, define said logical condition defined over said individual documents' metadata as a lead when said first and second values differ by at least a predetermined extent and generate an output indication of the lead. | 1. A system for computerized derivation of leads from a huge body of data, the system comprising: an electronic repository including a multiplicity of accesses to a respective multiplicity of electronic documents and metadata including metadata parameters having metadata values characterizing each of said multiplicity of electronic documents; a document rater using a processor to run a first computer algorithm on said multiplicity of electronic documents which yields a score which rates each of said multiplicity of electronic documents; and a metadata-based document discriminator using the processor to run a second computer algorithm on at least some of said metadata which yields leads, each lead comprising at least one metadata value for at least one metadata parameter, whose value correlates with the score of said electronic documents, wherein said discriminator is operative to perform the following for each of a multiplicity of logical conditions defined over the individual documents' metadata: a. access a subset of said multiplicity of electronic documents wherein membership in said subset, of an individual document from among said multiplicity of electronic documents, is determined by whether or not a current logical condition defined over said individual documents' metadata, is true; b. compute at least one first value, including a proportion of documents having a relevance score whose value is “relevant”, over at least one subset; c. Provide a second value including a proportion of documents having a relevance score whose value is “relevant” from among all of said multiplicity of electronic documents; and d. compare said first value to the second value, define said logical condition defined over said individual documents' metadata as a lead when said first and second values differ by at least a predetermined extent and generate an output indication of the lead. 2. The system according to claim 1 wherein at least one of said accesses includes an individual one of said multiplicity of electronic documents. | 0.928922 |
10,115,215 | 36 | 39 | 36. The non-transitory computer readable media of claim 35 , the operations further comprising: initiating presentation of the pairing of the font and the at least one other font. | 36. The non-transitory computer readable media of claim 35 , the operations further comprising: initiating presentation of the pairing of the font and the at least one other font. 39. The non-transitory computer readable media of claim 36 , wherein initiating presentation of the pairing of the font and the at least one other font includes prioritizing the pairing for presentation based upon a stochastic process. | 0.5 |
9,230,562 | 1 | 4 | 1. An apparatus comprising: at least one processor; and at least one non-transitory computer-readable storage medium having encoded thereon executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method comprising: generating feedback information regarding a speaking performance of a person based at least in part on analyzing audio data of a sample of speech of the person and/or text corresponding to the sample of speech of the person, via automatic speech recognition; and outputting, for display in a user interface, the text corresponding to the sample of the speech and the feedback information, wherein outputting the feedback information comprises outputting the feedback information for display as annotations to the text in the user interface, wherein annotations are displayed in the user interface in a manner distinct from display of the text. | 1. An apparatus comprising: at least one processor; and at least one non-transitory computer-readable storage medium having encoded thereon executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method comprising: generating feedback information regarding a speaking performance of a person based at least in part on analyzing audio data of a sample of speech of the person and/or text corresponding to the sample of speech of the person, via automatic speech recognition; and outputting, for display in a user interface, the text corresponding to the sample of the speech and the feedback information, wherein outputting the feedback information comprises outputting the feedback information for display as annotations to the text in the user interface, wherein annotations are displayed in the user interface in a manner distinct from display of the text. 4. The apparatus of claim 1 , wherein analyzing the audio data and/or the text comprises analyzing the audio data to determine volume data for the speech. | 0.770149 |
9,734,228 | 10 | 11 | 10. A data management system comprising: data extraction modules executed by at least one processor; and a data storage system comprising storage units, wherein the data extraction modules are to extract data from data sources and store the data in the storage units, wherein each of the data extraction modules and each of the storage units are assigned to a particular one of a plurality of analytics engines and an associated application for each analytics engine, and each of the data extraction modules extracts data from at least one of the data sources and stores the data in the storage unit for the analytics engine and 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 re-formatting includes formatting the data for storage in the corresponding storage unit according to a new schema including different fields from the at least one data source, and wherein the data extraction modules are to determine whether same or similar data is available from more than one of the data sources, and in response to determining that the same or similar data is available from more than one of the data sources, the data extraction modules are to use the prioritized list to accept data from a plurality of the data sources in an order specified in the prioritized list, wherein the plurality of analytics engines includes 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, and 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. | 10. A data management system comprising: data extraction modules executed by at least one processor; and a data storage system comprising storage units, wherein the data extraction modules are to extract data from data sources and store the data in the storage units, wherein each of the data extraction modules and each of the storage units are assigned to a particular one of a plurality of analytics engines and an associated application for each analytics engine, and each of the data extraction modules extracts data from at least one of the data sources and stores the data in the storage unit for the analytics engine and 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 re-formatting includes formatting the data for storage in the corresponding storage unit according to a new schema including different fields from the at least one data source, and wherein the data extraction modules are to determine whether same or similar data is available from more than one of the data sources, and in response to determining that the same or similar data is available from more than one of the data sources, the data extraction modules are to use the prioritized list to accept data from a plurality of the data sources in an order specified in the prioritized list, wherein the plurality of analytics engines includes 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, and 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. 11. The data management system of claim 10 , wherein the data storage system is to communicate with interfaces for the plurality of analytics engines hosted at an analytics engine system and provide data from the storage units to the analytics engines via the interfaces, and the analytics engines perform at least one of prescriptive and descriptive analytics using the data. | 0.5 |
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