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7,921,184 | 9 | 16 | 9. A network device for responding to a request for a dynamically generated object from a plurality of clients, the network device comprising: means for receiving, by a cache manager operating on a network device, from a first client a first request for a dynamically generated object from an originating server; means for transmitting, by the cache manager, the first request to the originating server; means for receiving, by the cache manager, the response to the first request from the originating server, the response comprising the dynamically generated object; means for initiating transmission, by the cache manager, of the dynamically generated object to the first client in response to the first request, the dynamically generated object stored in a transmission buffer of a network stack of the network device while waiting to be transmitted; means for receiving, by the cache manager, from a second client a second request for the dynamically generated object prior to completing transmission of the response to the first request of the first client; means for determining, by the cache manager, that the dynamically generated object is currently in the transmission buffer of the network stack of the network device; means for transmitting, by the cache manager and responsive to the determination that the dynamically generated object is currently in the transmission buffer, the dynamically generated object to the second client from the transmission buffer in response to the second request; and means for flushing, by the cache manager, the dynamically generated object from the transmission buffer, upon and responsive to completion of transmission of the dynamically generated object to the first client and the second client. | 9. A network device for responding to a request for a dynamically generated object from a plurality of clients, the network device comprising: means for receiving, by a cache manager operating on a network device, from a first client a first request for a dynamically generated object from an originating server; means for transmitting, by the cache manager, the first request to the originating server; means for receiving, by the cache manager, the response to the first request from the originating server, the response comprising the dynamically generated object; means for initiating transmission, by the cache manager, of the dynamically generated object to the first client in response to the first request, the dynamically generated object stored in a transmission buffer of a network stack of the network device while waiting to be transmitted; means for receiving, by the cache manager, from a second client a second request for the dynamically generated object prior to completing transmission of the response to the first request of the first client; means for determining, by the cache manager, that the dynamically generated object is currently in the transmission buffer of the network stack of the network device; means for transmitting, by the cache manager and responsive to the determination that the dynamically generated object is currently in the transmission buffer, the dynamically generated object to the second client from the transmission buffer in response to the second request; and means for flushing, by the cache manager, the dynamically generated object from the transmission buffer, upon and responsive to completion of transmission of the dynamically generated object to the first client and the second client. 16. The network device of claim 9 , wherein the network device comprises one of an appliance or a computing device in communication between the client and the originating server. | 0.789598 |
9,106,759 | 16 | 17 | 16. The system of claim 15 wherein the selected file comprises a slide show. | 16. The system of claim 15 wherein the selected file comprises a slide show. 17. The system of claim 16 further configured to: record a voice annotation about the slide show; and store the recorded voice annotation in a database. | 0.5 |
8,886,520 | 16 | 17 | 16. The apparatus of claim 15 wherein the processor is further configured to (1) compile at least a portion of the story angle data into a plurality of database triggers, and (2) perform the processing operation using the database triggers. | 16. The apparatus of claim 15 wherein the processor is further configured to (1) compile at least a portion of the story angle data into a plurality of database triggers, and (2) perform the processing operation using the database triggers. 17. The apparatus of claim 16 wherein the processor is further configured to (1) receive the source data from a remote data source, (2) store the received source data in a database, and (3) perform the derived features computation operation, the processing operation, and the generation operation prior to the storage operation. | 0.5 |
8,260,772 | 1 | 2 | 1. A non-transitory computer readable storage medium, comprising executable instructions to: receive a selection of a first section of a website; add a report retrieval component to the selected first section of the website, the report retrieval component being a portable segment of code that is installed and executed within the selected first section of the website without access to source code of the website; receive a selection of a second section of the website; automatically extract, from the second selected section of the website, one or more keywords describing content on the second section of the website; search for reports corresponding to the one or more keywords, at least one report including information automatically retrieved from a data source by a report generation product, the report generation product structuring the information in accordance with a report schema that specifies the form in which the information is presented; retrieve additional information associated a user of the website comprising the user's role in an organization; filter the reports based on data access permissions associated with the user of the website and the retrieved additional information; and display a highly ranked report to supplement the data provided by the website, the highly ranked report comprising the reports that are ranked based on results of a query run by a web service, the query being associated with the one or more keywords. | 1. A non-transitory computer readable storage medium, comprising executable instructions to: receive a selection of a first section of a website; add a report retrieval component to the selected first section of the website, the report retrieval component being a portable segment of code that is installed and executed within the selected first section of the website without access to source code of the website; receive a selection of a second section of the website; automatically extract, from the second selected section of the website, one or more keywords describing content on the second section of the website; search for reports corresponding to the one or more keywords, at least one report including information automatically retrieved from a data source by a report generation product, the report generation product structuring the information in accordance with a report schema that specifies the form in which the information is presented; retrieve additional information associated a user of the website comprising the user's role in an organization; filter the reports based on data access permissions associated with the user of the website and the retrieved additional information; and display a highly ranked report to supplement the data provided by the website, the highly ranked report comprising the reports that are ranked based on results of a query run by a web service, the query being associated with the one or more keywords. 2. The computer readable storage medium of claim 1 , further comprising executable instructions to rank the reports by relevance to the user role in the organization. | 0.646809 |
7,752,204 | 33 | 34 | 33. The method of claim 32 , further comprising highlighting one or more terms related to the query in the returned text summarization segment. | 33. The method of claim 32 , further comprising highlighting one or more terms related to the query in the returned text summarization segment. 34. The method of claim 33 , wherein the form of highlighting of each highlighted term is based upon the respective computed weight. | 0.5 |
7,827,029 | 19 | 20 | 19. The system of claim 18 , in which the input/output circuit interprets user-interest information and the processor dynamically updates the condensate portion of the user-interest sensitive note based on the retrieved user-interest information. | 19. The system of claim 18 , in which the input/output circuit interprets user-interest information and the processor dynamically updates the condensate portion of the user-interest sensitive note based on the retrieved user-interest information. 20. The system of claim 19 , in which the user interest sensitive note is comprised of a condensate portion. | 0.5 |
9,507,805 | 10 | 12 | 10. A system comprising: one or more data processors; and a computer storage apparatus comprising instructions executable by the one or more data processors which, upon such execution, cause the one or more data processors to perform operations comprising: receiving, by a computing system, a search request that identifies an image; comparing, by the computing system, the image that is identified by the search request to multiple candidate images in order to identify a particular image of the multiple candidate images that matches the image that is identified by the search request; identifying, by the computing system, a keyword that has been determined to be relevant to the particular image of the multiple candidate images; and providing, by the computing system in response to the computing system having received the search request that identifies the image, multiple search results that are responsive to the keyword, wherein providing the multiple search results that are responsive to the keyword is performed by the computing system without user intervention after the computing system receives the search request. | 10. A system comprising: one or more data processors; and a computer storage apparatus comprising instructions executable by the one or more data processors which, upon such execution, cause the one or more data processors to perform operations comprising: receiving, by a computing system, a search request that identifies an image; comparing, by the computing system, the image that is identified by the search request to multiple candidate images in order to identify a particular image of the multiple candidate images that matches the image that is identified by the search request; identifying, by the computing system, a keyword that has been determined to be relevant to the particular image of the multiple candidate images; and providing, by the computing system in response to the computing system having received the search request that identifies the image, multiple search results that are responsive to the keyword, wherein providing the multiple search results that are responsive to the keyword is performed by the computing system without user intervention after the computing system receives the search request. 12. The system of claim 10 , wherein: the image that is identified by the search request includes information that identifies a drawing that was sketched by user input at a computing device, and providing the multiple search results includes providing the multiple search results to the computing device. | 0.530864 |
8,990,065 | 4 | 7 | 4. The method of claim 1 , the instructions further configured to, for respective messages, identify a language of the message. | 4. The method of claim 1 , the instructions further configured to, for respective messages, identify a language of the message. 7. The method of claim 4 : the device comprising a multilingual component comprising: a first language subcomponent configured to process messages in a first language, and a second language subcomponent configured to process messages in a second language that is different than the first language; and the instructions further configured to, upon identifying the language of the message, invoke a language subcomponent of the multilingual component configured to process messages in the language of the message. | 0.5 |
7,954,115 | 8 | 10 | 8. A system, comprising: a processor; a data bus coupled to said processor; and a computer-usable medium embodying computer code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for: providing a network-based community portal having a mashup platform integrated therewith; designating at least one pre-negotiated bartering agreement, in response to a particular user input by at least one user of said network-based community portal; and associating a management module with a network-based community portal that permits said at least one user of said network-based community portal to describe to said mashup platform said at least one pre-negotiated bartering agreement in order to permit said network-based community portal to manage the utilization of mashup applications associated with said mashup platform and at least one widget contained by said mashup applications. | 8. A system, comprising: a processor; a data bus coupled to said processor; and a computer-usable medium embodying computer code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for: providing a network-based community portal having a mashup platform integrated therewith; designating at least one pre-negotiated bartering agreement, in response to a particular user input by at least one user of said network-based community portal; and associating a management module with a network-based community portal that permits said at least one user of said network-based community portal to describe to said mashup platform said at least one pre-negotiated bartering agreement in order to permit said network-based community portal to manage the utilization of mashup applications associated with said mashup platform and at least one widget contained by said mashup applications. 10. The system of claim 8 wherein said mashup platform comprises a mashup application catalogue. | 0.816092 |
6,081,829 | 21 | 24 | 21. A method for processing documents in a network environment in a customized fashion, the method comprising: receiving, by a redirector from a browser, a request for a selected network document; redirecting at least a portion of the request for the selected network document to a network server hosting the selected document, thereby retrieving the selected document; retrieving, by the redirector, stored annotation information associated with the selected document; and modifying the selected document to include an annotation section for display of the annotation information, the annotation section being located separately from contents of the selected document. | 21. A method for processing documents in a network environment in a customized fashion, the method comprising: receiving, by a redirector from a browser, a request for a selected network document; redirecting at least a portion of the request for the selected network document to a network server hosting the selected document, thereby retrieving the selected document; retrieving, by the redirector, stored annotation information associated with the selected document; and modifying the selected document to include an annotation section for display of the annotation information, the annotation section being located separately from contents of the selected document. 24. The method of claim 21, further including: modifying the selected document to include a "delete annotation" button; and re-sending to the browser the document with the annotation information deleted when a user presses the "delete annotation" button. | 0.511538 |
9,262,742 | 13 | 16 | 13. The method of claim 1 , further comprising: receiving a query including one or more query terms that describes an audience that a consumer is attempting to target; searching the database for matching user lists based on the query terms; and presenting matching user lists responsive to the query. | 13. The method of claim 1 , further comprising: receiving a query including one or more query terms that describes an audience that a consumer is attempting to target; searching the database for matching user lists based on the query terms; and presenting matching user lists responsive to the query. 16. The method of claim 13 , wherein the received query includes a set of websites/pages that are of interest to the potential subscriber. | 0.780255 |
8,346,331 | 1 | 7 | 1. A method comprising: measuring near-infrared optical energy indicative of oxygenation levels in a blood supply of a cortex of a brain of a subject to obtain a plurality of neural responses of the subject each time the subject answers a question of a respective plurality of questions, wherein at least one of the plurality of questions is repeated a plurality of times; measuring near-infrared optical energy indicative of oxygenation levels in the blood supply of the cortex of the brain of the subject to obtain a neural response of the subject associated with the subject's response to a visual cue of an affirmation attestation, wherein the affirmation attestation is indicative of a query as to the truthfulness of a response to a previous one of the plurality of questions; comparing the oxygenation levels indicated by the measured near-infrared optical energy with a baseline oxygenation level, wherein the baseline oxygenation level is indicative of one of a known truthful response or a known false response; and if the oxygenation levels indicated by the measured near-infrared optical energy differs from the baseline oxygenation level, determining that the subject conducted at least one of deception in response to a question or malingered in response to a question. | 1. A method comprising: measuring near-infrared optical energy indicative of oxygenation levels in a blood supply of a cortex of a brain of a subject to obtain a plurality of neural responses of the subject each time the subject answers a question of a respective plurality of questions, wherein at least one of the plurality of questions is repeated a plurality of times; measuring near-infrared optical energy indicative of oxygenation levels in the blood supply of the cortex of the brain of the subject to obtain a neural response of the subject associated with the subject's response to a visual cue of an affirmation attestation, wherein the affirmation attestation is indicative of a query as to the truthfulness of a response to a previous one of the plurality of questions; comparing the oxygenation levels indicated by the measured near-infrared optical energy with a baseline oxygenation level, wherein the baseline oxygenation level is indicative of one of a known truthful response or a known false response; and if the oxygenation levels indicated by the measured near-infrared optical energy differs from the baseline oxygenation level, determining that the subject conducted at least one of deception in response to a question or malingered in response to a question. 7. The method of claim 1 , wherein the near-infrared optical energy comprises a wavelength in the range of 700 to 900 nanometers, inclusive. | 0.818182 |
9,652,134 | 1 | 11 | 1. A non-transitory computer readable medium encoded with a computer program, the program comprising instructions executable by a data processing apparatus, the instructions comprising instructions to: receive one or more inputs creating a personalized avatar; receive one or more inputs creating one or more triggers; associate the one or more triggers with the personalized avatar; detect an occurrence of one or more of the triggers; and display, in accordance with the detected occurrence, the personalized avatar, wherein creating a personalized avatar comprises modifying an existing avatar based, at least in part, on a composite of previously created avatars. | 1. A non-transitory computer readable medium encoded with a computer program, the program comprising instructions executable by a data processing apparatus, the instructions comprising instructions to: receive one or more inputs creating a personalized avatar; receive one or more inputs creating one or more triggers; associate the one or more triggers with the personalized avatar; detect an occurrence of one or more of the triggers; and display, in accordance with the detected occurrence, the personalized avatar, wherein creating a personalized avatar comprises modifying an existing avatar based, at least in part, on a composite of previously created avatars. 11. The non-transitory computer-readable medium of claim 1 , wherein at least one of the triggers comprises detecting a state of a device associated with the personalized avatar, the state of the device including at least one of a type of the device, a power level of the device, and a bandwidth of the device. | 0.642032 |
8,914,284 | 1 | 6 | 1. A method of converting and transmitting audio information, comprising: receiving spoken audio input; converting the received spoken audio input into digital data that is representative of the received spoken audio input, wherein converting the received spoken audio input into digital data comprises creating a stream of digital data pockets, each digital data packet having a payload of data representative of a portion of the received spoken audio input; generating a textual representation of the received spoken audio input; inserting portions of the textual representation of the received spoken audio input into one or more headers of the digital data packets; and transmitting corresponding portions of the digital data and the textual representation to a destination device at substantially the same time. | 1. A method of converting and transmitting audio information, comprising: receiving spoken audio input; converting the received spoken audio input into digital data that is representative of the received spoken audio input, wherein converting the received spoken audio input into digital data comprises creating a stream of digital data pockets, each digital data packet having a payload of data representative of a portion of the received spoken audio input; generating a textual representation of the received spoken audio input; inserting portions of the textual representation of the received spoken audio input into one or more headers of the digital data packets; and transmitting corresponding portions of the digital data and the textual representation to a destination device at substantially the same time. 6. The method of claim 1 , wherein the portion of the textual representation of the received spoken audio input that is inserted into the one or more headers of a digital data packet corresponds at least in part to a different portion of the received spoken audio input than the data in the payload of the digital data packet. | 0.5 |
9,128,906 | 1 | 5 | 1. A method comprising acts of: using at least one statistical model extracted from annotated training data to segment a text into text sections and to assign, for at least a first text section, a topic indicative of content of the first text section; generating, by at least one processor, a structured text by selecting a section heading from a plurality of section headings associated with the topic assigned to the first text section and inserting the section heading into the text in order to assign the section heading to the first text section; causing the structured text to be displayed to a user; processing at least one modification of the structured text, the at least one modification being received from the user. | 1. A method comprising acts of: using at least one statistical model extracted from annotated training data to segment a text into text sections and to assign, for at least a first text section, a topic indicative of content of the first text section; generating, by at least one processor, a structured text by selecting a section heading from a plurality of section headings associated with the topic assigned to the first text section and inserting the section heading into the text in order to assign the section heading to the first text section; causing the structured text to be displayed to a user; processing at least one modification of the structured text, the at least one modification being received from the user. 5. The method according to claim 1 , wherein the text sections are first text sections, the section heading is a first section heading, and the structured text is a first structured text, and wherein the act of processing at least one modification of the structured text comprises successively triggering acts of: segmenting the text into second text sections by making use of the at least one statistical model extracted from the training data and by making reference to the at least one modification; generating a second structured text by inserting a second section heading into the text by making reference to the at least one modification; and providing the second structured text to the user for review. | 0.5 |
7,930,167 | 1 | 4 | 1. A computer readable storage medium with computer executable instructions for a localizable video game, said instructions comprising: instructions for a video game; instructions for a language interface pack library, comprising: instructions for receiving a language preference; instructions for providing to said video game paths to most recent versions of localized video game resources corresponding to said language preference, and paths to fallback video game resources; and instructions for integrating, by said video game, video game resources identified by provided paths into a video game display. | 1. A computer readable storage medium with computer executable instructions for a localizable video game, said instructions comprising: instructions for a video game; instructions for a language interface pack library, comprising: instructions for receiving a language preference; instructions for providing to said video game paths to most recent versions of localized video game resources corresponding to said language preference, and paths to fallback video game resources; and instructions for integrating, by said video game, video game resources identified by provided paths into a video game display. 4. The computer readable storage medium of claim 1 , wherein said fallback video game resources are determined using said language preference. | 0.781538 |
8,606,681 | 18 | 20 | 18. The system according to claim 16 , wherein the extracting part of the system further comprises: the computer for selecting a third random selection of the received data values, the third random selection of received data values corresponding to all the common features comprised in the received data values; and the computer for processing the third random selection of received data values using a conditional independence test and at least one first prediction model comprising a classification and regression tree (CART) model, a multivariate adaptive regression splines (MARS) model, or a random forests model, wherein processing the third random selection of received data values identifies influential features from among the received common features and related dependence values for each influential feature. | 18. The system according to claim 16 , wherein the extracting part of the system further comprises: the computer for selecting a third random selection of the received data values, the third random selection of received data values corresponding to all the common features comprised in the received data values; and the computer for processing the third random selection of received data values using a conditional independence test and at least one first prediction model comprising a classification and regression tree (CART) model, a multivariate adaptive regression splines (MARS) model, or a random forests model, wherein processing the third random selection of received data values identifies influential features from among the received common features and related dependence values for each influential feature. 20. The system according to claim 18 , wherein the plurality of second prediction models and the first prediction model are the same prediction models, and wherein each of the first and the second prediction models use different or overlapping random selection of data values from the received data values according to the common features of the received data values. | 0.5 |
9,300,760 | 6 | 23 | 6. 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: identifying a plurality of client devices, each client device of the plurality of client devices having a respective web browser installed, the web browser comprising a plurality of components including a web page renderer component for rendering web pages, a first translator component for translating programs in a portable format to a machine-specific instruction set, and a sandbox component for executing programs translated to the machine-specific instruction set on the client device using software-based fault isolation; identifying one or more second client devices, from among the plurality of client devices, that have a given hardware configuration; and transmitting a second translator component and a second sandbox component to each of the second client devices wherein each of the second client devices is configured to: (i) receive the second translator component and the second sandbox component, and (ii) configure the respective web browser of the second client device to use the second translator component instead of using the first translator component to translate programs in the portable format to a machine-specific instruction set of the second client device and to use the second sandbox component instead of using the first sandbox component to execute programs translated to the machine-specific instruction set of the second client device. | 6. 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: identifying a plurality of client devices, each client device of the plurality of client devices having a respective web browser installed, the web browser comprising a plurality of components including a web page renderer component for rendering web pages, a first translator component for translating programs in a portable format to a machine-specific instruction set, and a sandbox component for executing programs translated to the machine-specific instruction set on the client device using software-based fault isolation; identifying one or more second client devices, from among the plurality of client devices, that have a given hardware configuration; and transmitting a second translator component and a second sandbox component to each of the second client devices wherein each of the second client devices is configured to: (i) receive the second translator component and the second sandbox component, and (ii) configure the respective web browser of the second client device to use the second translator component instead of using the first translator component to translate programs in the portable format to a machine-specific instruction set of the second client device and to use the second sandbox component instead of using the first sandbox component to execute programs translated to the machine-specific instruction set of the second client device. 23. The system of claim 6 , wherein: the first translator component is configured to translate programs in a manner that complies with one or more constraints of the first sandbox component, and the second translator component is configured to translate programs in a manner that complies with one or more constraints of the second sandbox component. | 0.5 |
9,479,911 | 29 | 35 | 29. A method of operating a transmitter-side terminal for supporting a translation-based communication service, the transmitter-side terminal comprising: receiving input of a text in a first language with voice-related characteristic information and a display unit having an input function, wherein the voice related characteristic information is used to generate a translation voice signal in a second language with a pitch and a tone similar to a voice signal in the first language; translating the text in the first language to a translation text in the second language by using a translation database stored in the transmitter-side terminal; and transmitting the translation text in the second language with the voice-related characteristic information. | 29. A method of operating a transmitter-side terminal for supporting a translation-based communication service, the transmitter-side terminal comprising: receiving input of a text in a first language with voice-related characteristic information and a display unit having an input function, wherein the voice related characteristic information is used to generate a translation voice signal in a second language with a pitch and a tone similar to a voice signal in the first language; translating the text in the first language to a translation text in the second language by using a translation database stored in the transmitter-side terminal; and transmitting the translation text in the second language with the voice-related characteristic information. 35. The method of claim 29 , further comprising: collecting a voice signal in the first language using a microphone, providing voice recognition of the voice signal in the first language using a voice recognition database. | 0.663636 |
10,049,380 | 7 | 10 | 7. The computer-implemented method of claim 6 , wherein the classifier is generated by performing supervised classification on the features included in a training set of comments included in the training data. | 7. The computer-implemented method of claim 6 , wherein the classifier is generated by performing supervised classification on the features included in a training set of comments included in the training data. 10. The computer-implemented method of claim 7 , wherein the features include semantic features and linguistic features. | 0.799331 |
9,454,602 | 3 | 4 | 3. The device of claim 2 , where the one or more processors are further to: calculate a requirement similarity score between a pair of requirements included in the set of requirements; determine that the requirement similarity score, for the pair of requirements, satisfies a second threshold; merge the pair of requirements to form a requirement cluster based on the requirement similarity score, for the pair of requirements, satisfying the second threshold; and provide information that identifies the requirement cluster. | 3. The device of claim 2 , where the one or more processors are further to: calculate a requirement similarity score between a pair of requirements included in the set of requirements; determine that the requirement similarity score, for the pair of requirements, satisfies a second threshold; merge the pair of requirements to form a requirement cluster based on the requirement similarity score, for the pair of requirements, satisfying the second threshold; and provide information that identifies the requirement cluster. 4. The device of claim 3 , where the one or more processors, when calculating the requirement similarity score between the pair of requirements, are to calculate the requirement similarity score based on at least one of: a semantic similarity score between the pair of requirements, a placement similarity score between the pair of requirements, or the semantic similarity score and the placement similarity score. | 0.550976 |
8,140,521 | 10 | 17 | 10. A computer program, stored on a tangible storage medium, for use in processing a database query, the query including an expression, the computer program including executable instructions that cause a computer to: perform expression optimization on the expression; perform further query optimization to produce a result; save the result in a machine memory; where the expression includes a sub-expression (“SE”), where expression optimization is performed before further query optimization, and where the computer program includes executable instructions that cause a computer to: represent the query as a tree structure; represent the expression in the tree structure as a parent node having a first child node and a second child node; where the first child node represents the sub-expression; where the second child node represents the portion of the expression that is not the sub-expression; and where the parent node represents an operation between the first child node and the second child node; determine that the second child node represents the constant 0 and that the parent node represents an arithmetic operation selected from the group consisting of addition and subtraction; and in response, remove the parent node and its children from the tree structure and insert the first child node in its place. | 10. A computer program, stored on a tangible storage medium, for use in processing a database query, the query including an expression, the computer program including executable instructions that cause a computer to: perform expression optimization on the expression; perform further query optimization to produce a result; save the result in a machine memory; where the expression includes a sub-expression (“SE”), where expression optimization is performed before further query optimization, and where the computer program includes executable instructions that cause a computer to: represent the query as a tree structure; represent the expression in the tree structure as a parent node having a first child node and a second child node; where the first child node represents the sub-expression; where the second child node represents the portion of the expression that is not the sub-expression; and where the parent node represents an operation between the first child node and the second child node; determine that the second child node represents the constant 0 and that the parent node represents an arithmetic operation selected from the group consisting of addition and subtraction; and in response, remove the parent node and its children from the tree structure and insert the first child node in its place. 17. The computer program of claim 10 , where further query optimization includes: selecting an optimal plan from executing the database query. | 0.809651 |
9,075,861 | 1 | 19 | 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 learned user preferences, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by a user for identifying desired content items; in response to the input entered by the user, presenting a subset of content items; receiving selection actions of selected content items of the subset from the user; learning preferred descriptive terms of the user by analyzing descriptive terms associated with the selected content items and by analyzing the date, day, and time of the selection actions and the descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items, wherein similarity of the similar content items is determined by comparing the descriptive terms associated with the selected content items with a previously selected content item, and wherein the periodicity indicates an amount of time between the selection actions of the similar content items relative to a reference point; associating the periodicity with the preferred descriptive terms associated with the similar content items; associating the preferred descriptive terms with the user; determining a measurement collection having measurements associated with the preferred descriptive terms, wherein the measurements represent relative preferences of the user for the preferred descriptive terms, wherein the measurement collection includes groups of the preferred descriptive terms, wherein the relative preferences of the user for the preferred descriptive terms in a particular group are treated as equal and the groups differentiate the relative preferences of the user for the preferred descriptive terms between the groups, and wherein a preferred descriptive term is included in the particular group at least in part based on at least one of (i) smoothing relatively smaller probability weights associated with less commonly expressed preferences of the relative preferences and (ii) aging preferences of the relative preferences of relative preferences captured in a relatively more distant past, and based further on bounding a range of values of the particular group using a relevance scale factor; and in response to receiving subsequent input entered by the user, selecting and ordering a collection of content items by promoting rankings of content items of the collection of content items associated with the preferred descriptive terms of the user according to differentiation provided by the measurement collection and further based on promoting rankings of those content items of the collection of content items associated with the preferred descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent input; wherein at least one of the input and the subsequent input are entered by the user on an input constrained device. | 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 learned user preferences, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by a user for identifying desired content items; in response to the input entered by the user, presenting a subset of content items; receiving selection actions of selected content items of the subset from the user; learning preferred descriptive terms of the user by analyzing descriptive terms associated with the selected content items and by analyzing the date, day, and time of the selection actions and the descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items, wherein similarity of the similar content items is determined by comparing the descriptive terms associated with the selected content items with a previously selected content item, and wherein the periodicity indicates an amount of time between the selection actions of the similar content items relative to a reference point; associating the periodicity with the preferred descriptive terms associated with the similar content items; associating the preferred descriptive terms with the user; determining a measurement collection having measurements associated with the preferred descriptive terms, wherein the measurements represent relative preferences of the user for the preferred descriptive terms, wherein the measurement collection includes groups of the preferred descriptive terms, wherein the relative preferences of the user for the preferred descriptive terms in a particular group are treated as equal and the groups differentiate the relative preferences of the user for the preferred descriptive terms between the groups, and wherein a preferred descriptive term is included in the particular group at least in part based on at least one of (i) smoothing relatively smaller probability weights associated with less commonly expressed preferences of the relative preferences and (ii) aging preferences of the relative preferences of relative preferences captured in a relatively more distant past, and based further on bounding a range of values of the particular group using a relevance scale factor; and in response to receiving subsequent input entered by the user, selecting and ordering a collection of content items by promoting rankings of content items of the collection of content items associated with the preferred descriptive terms of the user according to differentiation provided by the measurement collection and further based on promoting rankings of those content items of the collection of content items associated with the preferred descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent input; wherein at least one of the input and the subsequent input are entered by the user on an input constrained device. 19. The method of claim 1 , wherein at least one of receiving input, presenting the subset of content items, receiving the selection actions, analyzing the preferred descriptive terms, determining the measurement collection, and selecting and ordering the collection of content items is performed on a user client device. | 0.784274 |
8,041,021 | 25 | 30 | 25. A computer program product comprising computer-executable instructions embodied in a computer-readable medium for performing steps comprising: (a) receiving a signaling message that contains a global title address (GTA); (b) selecting a GTT mode from a plurality of different GTT modes based on an attribute of the received signaling message, wherein at least some of the different GTT modes use different combinations of address parameters associated with received signaling messages to search a GTT database, wherein each of the different GTT modes translates at least a signaling connection control part (SCCP) parameter into at least a message transfer part (MTP) destination point code; and (c) searching the GTT database using a combination of address parameters of the received signaling message specific to the selected GTT mode. | 25. A computer program product comprising computer-executable instructions embodied in a computer-readable medium for performing steps comprising: (a) receiving a signaling message that contains a global title address (GTA); (b) selecting a GTT mode from a plurality of different GTT modes based on an attribute of the received signaling message, wherein at least some of the different GTT modes use different combinations of address parameters associated with received signaling messages to search a GTT database, wherein each of the different GTT modes translates at least a signaling connection control part (SCCP) parameter into at least a message transfer part (MTP) destination point code; and (c) searching the GTT database using a combination of address parameters of the received signaling message specific to the selected GTT mode. 30. The computer program product of claim 25 wherein the plurality of different GTT modes are arranged in a predetermined hierarchy and wherein the method further comprises, in response to failing to locate a matching entry in the selected GTT mode, performing a GTT lookup according to a next GTT mode in the GTT hierarchy. | 0.709156 |
8,938,686 | 11 | 14 | 11. A method for analyzing organizational entity performance, the method being performed by one or more processors of one or more computers and comprising: receiving data associated with a geographic region, wherein the received data is transformed into an object model; analyzing the object model to associate the received data with at least one organizational entity and to associate the received data with a plurality of sub-geographic regions of the geographic region; applying a prediction model to the plurality of sub-geographic regions using the object model to determine a predicted performance for at least one entity location of the at least one organizational entity; determining actual performance for at least the entity location; providing a user interface that includes information associated with the predicted performance, the actual performance, or a combination of the predicted performance and the actual performance; and receiving a placement of a hypothetical entity location and wherein applying the prediction model further uses the placement of the hypothetical entity location to determine a predicted performance for the at least one entity location. | 11. A method for analyzing organizational entity performance, the method being performed by one or more processors of one or more computers and comprising: receiving data associated with a geographic region, wherein the received data is transformed into an object model; analyzing the object model to associate the received data with at least one organizational entity and to associate the received data with a plurality of sub-geographic regions of the geographic region; applying a prediction model to the plurality of sub-geographic regions using the object model to determine a predicted performance for at least one entity location of the at least one organizational entity; determining actual performance for at least the entity location; providing a user interface that includes information associated with the predicted performance, the actual performance, or a combination of the predicted performance and the actual performance; and receiving a placement of a hypothetical entity location and wherein applying the prediction model further uses the placement of the hypothetical entity location to determine a predicted performance for the at least one entity location. 14. The method of claim 11 wherein the determined actual performance includes determining the actual spend amount for the at least one entity location based on the object model and the predicted performance includes determining the predicted spend amount for the at least one entity location based on the object model. | 0.5 |
8,291,308 | 9 | 10 | 9. A computer program product comprising a computer usable storage medium storing computer usable program code for annotating collaborative information structures, the computer program product comprising: computer usable program code for creating a collaborative information structure document (ISD) with each of an object section and an annotation section; computer usable program code for adding a collaborative object in a collaborative computing environment to the object section of the collaborative ISD; computer usable program code for adding an annotation for the collaborative ISD to the annotation section of the collaborative ISD; and, computer usable program code for storing the collaborative ISD for use as a collaborative object in the collaborative computing environment. | 9. A computer program product comprising a computer usable storage medium storing computer usable program code for annotating collaborative information structures, the computer program product comprising: computer usable program code for creating a collaborative information structure document (ISD) with each of an object section and an annotation section; computer usable program code for adding a collaborative object in a collaborative computing environment to the object section of the collaborative ISD; computer usable program code for adding an annotation for the collaborative ISD to the annotation section of the collaborative ISD; and, computer usable program code for storing the collaborative ISD for use as a collaborative object in the collaborative computing environment. 10. The computer program product of claim 9 , wherein the computer usable program code for adding a collaborative object in a collaborative computing environment to the object section of the collaborative ISD, further comprises computer usable program code for adding a reference to a collaborative object in the collaborative computing environment to the object section of the collaborative ISD. | 0.5 |
8,527,270 | 4 | 5 | 4. The method of claim 1 , wherein the adjusting comprises: increasing the at least one probability corresponding to the at least one word that is included in the second set of one or more words but is not included in the first set of one or more words. | 4. The method of claim 1 , wherein the adjusting comprises: increasing the at least one probability corresponding to the at least one word that is included in the second set of one or more words but is not included in the first set of one or more words. 5. The method of claim 4 , wherein the increasing comprises: increasing a unigram probability for each word in the second set of one or more words; and renormalizing a set of unigram probabilities comprising a unigram probability for each word in at least one language model to sum to one. | 0.5 |
8,498,515 | 1 | 22 | 1. A method of reproducing text subtitle streams, the method comprising: receiving at least one text subtitle stream from an external source, each text subtitle stream including text data to be displayed within a region of a display screen, first information specifying a global style of the region, and second information specifying a local style for a portion of the text data; reading a playlist including at least one playitem and first and second subplayitems, the playitem specifying a time based playing interval from an in-time until an out-time associated with at least one audio/video stream, the first subplayitem specifying a time based playing interval from an in-time until an out-time associated with the at least one text subtitle stream, the first subplayitem for a reproducing of the text subtitle stream being synchronized with the playitem, the second subplayitem for a reproduction of browsable slideshow being not synchronized with the playitem; and decoding the text subtitle stream using the first information and the second information. | 1. A method of reproducing text subtitle streams, the method comprising: receiving at least one text subtitle stream from an external source, each text subtitle stream including text data to be displayed within a region of a display screen, first information specifying a global style of the region, and second information specifying a local style for a portion of the text data; reading a playlist including at least one playitem and first and second subplayitems, the playitem specifying a time based playing interval from an in-time until an out-time associated with at least one audio/video stream, the first subplayitem specifying a time based playing interval from an in-time until an out-time associated with the at least one text subtitle stream, the first subplayitem for a reproducing of the text subtitle stream being synchronized with the playitem, the second subplayitem for a reproduction of browsable slideshow being not synchronized with the playitem; and decoding the text subtitle stream using the first information and the second information. 22. The method of claim 1 , wherein the local style is specified by at least one of a new font identification, a new font style, a new font size, and a new font color defined in the second information. | 0.665 |
7,584,092 | 12 | 13 | 12. A computer-implemented method of selecting boundaries for application of a paraphrase alternation pattern to an input string, the method comprising: utilizing a computer processor that is a functional component of the computer to apply the paraphrase alternation pattern multiple times to the input string with multiple boundaries so as to create a plurality of alternation alternatives, wherein each alternation alternative is a different sequence of words included in the input string; generating a language model based on a set of test data and then applying the language model to the plurality of alternation alternatives to determine which, based on frequency within the set of test data, is a relatively commonly used sequence of words; and wherein applying so as to create a plurality of alternation alternatives comprise applying so as to switch different combinations of words around a word in the input string identified as being a pivot word. | 12. A computer-implemented method of selecting boundaries for application of a paraphrase alternation pattern to an input string, the method comprising: utilizing a computer processor that is a functional component of the computer to apply the paraphrase alternation pattern multiple times to the input string with multiple boundaries so as to create a plurality of alternation alternatives, wherein each alternation alternative is a different sequence of words included in the input string; generating a language model based on a set of test data and then applying the language model to the plurality of alternation alternatives to determine which, based on frequency within the set of test data, is a relatively commonly used sequence of words; and wherein applying so as to create a plurality of alternation alternatives comprise applying so as to switch different combinations of words around a word in the input string identified as being a pivot word. 13. The method of claim 12 , further comprising determining whether the paraphrase alternation pattern can be applied to the input string so as to preserve meaning. | 0.566138 |
8,838,562 | 28 | 29 | 28. A computer-implemented method for providing query parameters to a search engine, comprising: receiving, at a computer system, selection indicators that specify at least two locations of an electronic document, wherein the at least two locations define an area within an electronic document that has been selected by a user of the computer system; selecting, by the computer system, text that is contained within the defined area; extracting the selected text from the electronic document; determining that the selected text comprises a partial word; identifying unselected text that the user did not select and that is located outside of the defined area for augmenting the selected text, wherein the unselected text is identified from among a plurality of unselected text elements in the electronic document based on a determination that the unselected text, when appended to the selected text, will complete the partial word; appending the unselected text to the selected text; determining a context associated with the selected text based on the identified plurality of unselected text elements; generating one or more query terms based on the determined context, wherein the one or more query terms are different than the unselected text; creating a search query based on the selected text appended with the unselected text and the one or more query terms, wherein the creation of the search query is initiated by the selection of the text; and presenting the search query to a search engine. | 28. A computer-implemented method for providing query parameters to a search engine, comprising: receiving, at a computer system, selection indicators that specify at least two locations of an electronic document, wherein the at least two locations define an area within an electronic document that has been selected by a user of the computer system; selecting, by the computer system, text that is contained within the defined area; extracting the selected text from the electronic document; determining that the selected text comprises a partial word; identifying unselected text that the user did not select and that is located outside of the defined area for augmenting the selected text, wherein the unselected text is identified from among a plurality of unselected text elements in the electronic document based on a determination that the unselected text, when appended to the selected text, will complete the partial word; appending the unselected text to the selected text; determining a context associated with the selected text based on the identified plurality of unselected text elements; generating one or more query terms based on the determined context, wherein the one or more query terms are different than the unselected text; creating a search query based on the selected text appended with the unselected text and the one or more query terms, wherein the creation of the search query is initiated by the selection of the text; and presenting the search query to a search engine. 29. The method of claim 28 , wherein the selection indicators comprise input received from a computer mouse in association with a click-and-drag operation. | 0.5 |
8,196,053 | 11 | 12 | 11. The system of claim 10 , wherein the information includes: treatment information; information identifying citing documents that cite to the document; and treatment types reflecting the treatment of the document by the citing documents. | 11. The system of claim 10 , wherein the information includes: treatment information; information identifying citing documents that cite to the document; and treatment types reflecting the treatment of the document by the citing documents. 12. The system of claim 11 , further wherein the device further: reduces a number of the treatment types by aggregating at least two of the treatment types together; reformats the information into the metadata; and parses the metadata. | 0.5 |
10,152,973 | 1 | 6 | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: receive audio data from a client computing device separate from the system, wherein the audio data comprises data regarding an utterance of a user; produce first speech processing results using a base speech processing model and the audio data, wherein the base speech processing model is stored at the system; obtain a specialized speech processing model from a network-accessible data store separate from the system and separate from the client computing device, wherein the obtaining is initiated by the system subsequent to receipt of the audio data and prior to completion of producing the first speech processing results; determine, based at least partly on a time at which the specialized speech processing model is obtained, that the system is to produce second speech processing results using the specialized speech processing model subsequent to initiating production of the first speech processing results; and produce the second speech processing results using the specialized speech processing model and at least one of the audio data or the first speech processing results. | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: receive audio data from a client computing device separate from the system, wherein the audio data comprises data regarding an utterance of a user; produce first speech processing results using a base speech processing model and the audio data, wherein the base speech processing model is stored at the system; obtain a specialized speech processing model from a network-accessible data store separate from the system and separate from the client computing device, wherein the obtaining is initiated by the system subsequent to receipt of the audio data and prior to completion of producing the first speech processing results; determine, based at least partly on a time at which the specialized speech processing model is obtained, that the system is to produce second speech processing results using the specialized speech processing model subsequent to initiating production of the first speech processing results; and produce the second speech processing results using the specialized speech processing model and at least one of the audio data or the first speech processing results. 6. The system of claim 1 , wherein the executable instructions to determine, based at least partly on the time at which the specialized speech processing model is obtained, that the system is to produce the second speech processing results using the specialized speech processing model comprise executable instructions to determine, based on the specialized speech processing model being obtained prior to sending speech processing results to the client computing device, that the system is to produce the second speech processing results. | 0.5 |
7,716,188 | 11 | 12 | 11. The method as claimed in claim 1 , further comprising: storing the configuration structure as a tree structure with a plurality of hierarchic levels, within which tree structure the plurality of modules are hierarchically associated with one another. | 11. The method as claimed in claim 1 , further comprising: storing the configuration structure as a tree structure with a plurality of hierarchic levels, within which tree structure the plurality of modules are hierarchically associated with one another. 12. The method as claimed in claim 11 , wherein the plurality of modules comprise type modules and variant modules, and wherein successive hierarchic levels in the configuration structure alternately hold type modules and variant modules, with a first type module having at least one associated variant module directly subordinate to the first type module. | 0.5 |
10,152,469 | 15 | 17 | 15. A method implemented by a computing device comprising: creating an analytics report within a spreadsheet for a spreadsheet application that is configured to contain embedded analytics data from a marketing service that describes interactions of consumers with one or more web resources made available by a service provider, the report configured to contain a sub-set of the analytics data; building one or more form controls associated with cells of the spreadsheet application that are configured to enable selection of filter parameters to selectively filter the analytics data presented in the spreadsheet, wherein filter parameters include existing market segments, each market segment being a combination of segment parameters that describe information about a corresponding market segment; and populating the form controls with filter parameter values selectable through interaction with the form controls to cause updating of the spreadsheet by automatically querying the marketing service to refresh the spreadsheet with at least one sub-set of analytics data corresponding to selected filter parameter values, wherein said at least one sub-set of analytics data comprises a new and different combination of existing filtered analytics data, wherein building the one or more form controls comprises: providing an interactive dialog having one or more form control creation options associated with the one or more filter parameters operable to initiate the creation of form controls for selected filter parameters and specify cell locations for the form controls; and adding the form controls for selected filter parameters directly into the specified cell locations. | 15. A method implemented by a computing device comprising: creating an analytics report within a spreadsheet for a spreadsheet application that is configured to contain embedded analytics data from a marketing service that describes interactions of consumers with one or more web resources made available by a service provider, the report configured to contain a sub-set of the analytics data; building one or more form controls associated with cells of the spreadsheet application that are configured to enable selection of filter parameters to selectively filter the analytics data presented in the spreadsheet, wherein filter parameters include existing market segments, each market segment being a combination of segment parameters that describe information about a corresponding market segment; and populating the form controls with filter parameter values selectable through interaction with the form controls to cause updating of the spreadsheet by automatically querying the marketing service to refresh the spreadsheet with at least one sub-set of analytics data corresponding to selected filter parameter values, wherein said at least one sub-set of analytics data comprises a new and different combination of existing filtered analytics data, wherein building the one or more form controls comprises: providing an interactive dialog having one or more form control creation options associated with the one or more filter parameters operable to initiate the creation of form controls for selected filter parameters and specify cell locations for the form controls; and adding the form controls for selected filter parameters directly into the specified cell locations. 17. The method as described in claim 15 , wherein said creating, building and populating are performed by an analytics module configured as a plug-in for the spreadsheet application, and wherein the analytics module is further configured to perform operations comprising: responsive to a selection of filter parameter values from the form controls, querying the marketing service to obtain the corresponding sub-set of analytics data; and refreshing the analytics data presented in the spreadsheet in accordance with the querying. | 0.5 |
8,810,583 | 25 | 30 | 25. An apparatus configured to create an animation, the apparatus comprising: a script formatter configured to determine a domain format type of a web text that relates to a category of content of the web text, extract and classify elements from the web text according to the domain format type, and generate a domain format script according to the extracted and classified elements; an adaption engine configured to receive the domain format script, and generate a scenario script and animation elements according to the domain format script, the animation elements comprising media style information indicating a rhythm, or an atmosphere, or initial camera walks, or any combination thereof, of the animation; and a graphics engine configured to generate the animation using the scenario script and the animation elements. | 25. An apparatus configured to create an animation, the apparatus comprising: a script formatter configured to determine a domain format type of a web text that relates to a category of content of the web text, extract and classify elements from the web text according to the domain format type, and generate a domain format script according to the extracted and classified elements; an adaption engine configured to receive the domain format script, and generate a scenario script and animation elements according to the domain format script, the animation elements comprising media style information indicating a rhythm, or an atmosphere, or initial camera walks, or any combination thereof, of the animation; and a graphics engine configured to generate the animation using the scenario script and the animation elements. 30. The apparatus of claim 25 , wherein the adaption engine comprises: a text analysis unit configured to analyze text included in the web text, and extract sentence elements of the text using text analyzers; an animation content generation unit configured to generate animation contents based on the analyzed text; and a rule manager comprising knowledge of ontology and relations of the analyzed text, and configured to control the animation content generation unit to generate the animation contents based on the analyzed text. | 0.5 |
9,405,832 | 8 | 9 | 8. A non-transitory computer-readable storage medium containing program instructions, which when executed by a processor cause the processor to execute a method of responding to a search query requesting relevant software applications from a database of software applications, the method comprising: receiving, at a server, the search query from an electronic device of a user, the search query including one or more terms; analyzing the one or more terms to assign a search category to the search query, the search category being selected from a plurality of potential search categories, wherein each category of the plurality of potential search categories relates to a different search technique for searching the database of software applications, wherein a first search technique emphasizes exact textual matches more than a second search technique emphasizes exact textual matches, and wherein the analysis utilizes empirical data associated with the one or more terms; determining a search technique based on the search category; using the determined search technique to search, at the server, the database for one or more relevant software applications based on the search query; and sending, to the electronic device, a list of the one or more relevant software applications; wherein analyzing the one or more terms comprises: identifying a set of previous search queries from other users including the term or an equivalent term; identifying, for each search query in the set of previous search queries, an application selected or downloaded by a respective other user subsequent to receiving results from the previous search query; and analyzing a distribution over the selected or downloaded applications; and wherein analyzing the distribution includes: determining a statistical value of the distribution; and comparing the statistical value to a threshold, wherein the functional category is assigned to the search query when the statistical value exceeds the threshold. | 8. A non-transitory computer-readable storage medium containing program instructions, which when executed by a processor cause the processor to execute a method of responding to a search query requesting relevant software applications from a database of software applications, the method comprising: receiving, at a server, the search query from an electronic device of a user, the search query including one or more terms; analyzing the one or more terms to assign a search category to the search query, the search category being selected from a plurality of potential search categories, wherein each category of the plurality of potential search categories relates to a different search technique for searching the database of software applications, wherein a first search technique emphasizes exact textual matches more than a second search technique emphasizes exact textual matches, and wherein the analysis utilizes empirical data associated with the one or more terms; determining a search technique based on the search category; using the determined search technique to search, at the server, the database for one or more relevant software applications based on the search query; and sending, to the electronic device, a list of the one or more relevant software applications; wherein analyzing the one or more terms comprises: identifying a set of previous search queries from other users including the term or an equivalent term; identifying, for each search query in the set of previous search queries, an application selected or downloaded by a respective other user subsequent to receiving results from the previous search query; and analyzing a distribution over the selected or downloaded applications; and wherein analyzing the distribution includes: determining a statistical value of the distribution; and comparing the statistical value to a threshold, wherein the functional category is assigned to the search query when the statistical value exceeds the threshold. 9. The computer-readable medium of claim 8 wherein the first search technique comprises a navigational search technique and the second search technique comprises a functional search technique. | 0.529412 |
8,695,037 | 1 | 2 | 1. A display system comprising: a display; and a single graphical user interface window presented on the display, comprising: a representation of a set of channels; and a representation of individual content items associated with each of the channels, wherein the individual content items include television programming and interactive data; wherein the single graphical user interface window enables a user to select an individual content item associated with a displayed channel; wherein if the interactive data is selected, then the representation of the set of channels and the interactive data are both displayed within the single graphical user interface window; wherein the single graphical user interface window displays the representation of the individual content items associated with a channel upon selection of the channel by the user, wherein the single graphical user interface window does not involve overlaying; wherein the single graphical user interface window simultaneously displays categories, channels, and content, and permits navigation in the single graphical user interface therethrough, such that a plurality of sets of channels that each correspond to a plurality of categories respectively; and wherein upon selection of a single category of the plurality of categories by the user, the corresponding set of channels of the plurality of sets of channels is displayed. | 1. A display system comprising: a display; and a single graphical user interface window presented on the display, comprising: a representation of a set of channels; and a representation of individual content items associated with each of the channels, wherein the individual content items include television programming and interactive data; wherein the single graphical user interface window enables a user to select an individual content item associated with a displayed channel; wherein if the interactive data is selected, then the representation of the set of channels and the interactive data are both displayed within the single graphical user interface window; wherein the single graphical user interface window displays the representation of the individual content items associated with a channel upon selection of the channel by the user, wherein the single graphical user interface window does not involve overlaying; wherein the single graphical user interface window simultaneously displays categories, channels, and content, and permits navigation in the single graphical user interface therethrough, such that a plurality of sets of channels that each correspond to a plurality of categories respectively; and wherein upon selection of a single category of the plurality of categories by the user, the corresponding set of channels of the plurality of sets of channels is displayed. 2. The display system of claim 1 , wherein the single graphical user interface window comprises an area for displaying the representation of the individual content items, and wherein the area occupies a substantial portion of the display. | 0.504167 |
8,386,792 | 1 | 6 | 1. A process of fingerprinting a document for an information leakage prevention system, the process comprising: generating a sequence of hash values for a document, a portion of said hash values to be selected as fingerprints for the document; adaptively determining a size of a window, wherein the size of the window varies depending on a minimum guaranteed match percentage and a size of the document; selecting for the document using said adaptively-sized window; and adding the fingerprints for the document to a fingerprint set for content being protected by the information leakage prevention system. | 1. A process of fingerprinting a document for an information leakage prevention system, the process comprising: generating a sequence of hash values for a document, a portion of said hash values to be selected as fingerprints for the document; adaptively determining a size of a window, wherein the size of the window varies depending on a minimum guaranteed match percentage and a size of the document; selecting for the document using said adaptively-sized window; and adding the fingerprints for the document to a fingerprint set for content being protected by the information leakage prevention system. 6. The process of claim 1 , said selection of fingerprints for the document using said adaptively-sized window comprises: positioning a current window over a portion of the sequence of hash values; examining hash values starting from one end of the current window and selecting a first-encountered hash value that is 0 modulo P to be a fingerprint for the current window, wherein P is a predetermined number; and if no 0 modulo P hash value is found in the current window, then forcibly selecting a hash value to be a fingerprint for the current window. | 0.5 |
7,664,768 | 11 | 16 | 11. An information storage medium having a plurality of instructions adapted to direct an information processing device for mapping database object types to structural language type definition code, wherein user code is added to the structural language type definition code for the object types, the information storage medium comprising: code for parsing one or more database object types; code for re-generating structural language type definition code for the one or more database object types; code for determining positioning information indicating a position in the structural language type definition code of user code in the structural language type definition code; code for determining the position in the regenerated structural language type definition code based on the positioning information; code for determining whether user code should be inserted in the regenerated structural language type definition code; and code for, based on a determination that the user code should be inserted, inserting the user code in the regenerated structural language type definition code, wherein the inserted user code is positioned corresponding to the user code in the structural language type definition code. | 11. An information storage medium having a plurality of instructions adapted to direct an information processing device for mapping database object types to structural language type definition code, wherein user code is added to the structural language type definition code for the object types, the information storage medium comprising: code for parsing one or more database object types; code for re-generating structural language type definition code for the one or more database object types; code for determining positioning information indicating a position in the structural language type definition code of user code in the structural language type definition code; code for determining the position in the regenerated structural language type definition code based on the positioning information; code for determining whether user code should be inserted in the regenerated structural language type definition code; and code for, based on a determination that the user code should be inserted, inserting the user code in the regenerated structural language type definition code, wherein the inserted user code is positioned corresponding to the user code in the structural language type definition code. 16. The information storage medium of claim 11 , further comprising code for determining a hint usable to determine a change to the user code. | 0.699153 |
8,595,693 | 3 | 4 | 3. A computer program product for model driven deployment of component based applications, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for selecting a plurality of units representative of corresponding programmatic objects to be deployed into a target environment; computer readable program code for specifying a deployment topology for the target environment; computer readable program code for matching portions of the units to different automation signatures and filtering the different automation signatures to a set of automation signatures based upon the deployment topology; computer readable program code for ordering the set of automation signatures according to known dependencies of a corresponding deployment model; and, computer readable program code for bundling the ordered set of automation signatures into an automation workflow and publishing the automation workflow to an automation engine for execution to deploy the programmatic objects into the target environment. | 3. A computer program product for model driven deployment of component based applications, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for selecting a plurality of units representative of corresponding programmatic objects to be deployed into a target environment; computer readable program code for specifying a deployment topology for the target environment; computer readable program code for matching portions of the units to different automation signatures and filtering the different automation signatures to a set of automation signatures based upon the deployment topology; computer readable program code for ordering the set of automation signatures according to known dependencies of a corresponding deployment model; and, computer readable program code for bundling the ordered set of automation signatures into an automation workflow and publishing the automation workflow to an automation engine for execution to deploy the programmatic objects into the target environment. 4. The computer program product of claim 3 , further comprising computer readable program code for generating a plurality of configuration files separate from the automation workflow for different target environments. | 0.792543 |
8,577,818 | 1 | 9 | 1. A method comprising: performing on a processor, evaluating log data; determining at least one discrepancy between the log data and a system model; generating a candidate model based on the discrepancy and a model template; and updating the system model based on the candidate model. | 1. A method comprising: performing on a processor, evaluating log data; determining at least one discrepancy between the log data and a system model; generating a candidate model based on the discrepancy and a model template; and updating the system model based on the candidate model. 9. The method according to claim 1 , wherein the model template includes model generation implementation logic. | 0.691667 |
9,478,059 | 11 | 14 | 11. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause performance comprising: receiving a meta-language file comprising a conversion of a script file in a natural language format, the script file including a plurality of natural language statements; interpreting, by a first computing device, the meta-language file for execution of at least a first portion of the meta-language file; dynamically generating and displaying, on the first computing device, one or more visually animated graphical elements in accordance with the execution of the at least a first portion of the meta-language file; wherein the one or more visually animated graphical elements comprise an action element that relates to a background comprising a plurality of zones, and that causes displaying a first zone, of the plurality of zones, of the background; in response to a user interactive action taken on the one or more visually animated graphical elements of the at least a first portion of the meta-language file, by a first user on the first computing device, setting at least one parameter based on the user interactive action; wherein setting the at least one parameter causes a third meta-language file associated with the script file to particularly execute for a second user that is different from execution of the third meta-language file for the second user when the at least one parameter is not set; wherein setting the at least one parameter causes modifying the action element to cause displaying a second zone, of the plurality of zones, of the background; receiving a second meta-language file comprising a conversion of a second script file in a natural language format, the second script file including a plurality of natural language statements, the second script file separate and different from the script file; interpreting the second meta-language file for particular execution of at least a second portion of the second meta-language file in accordance with the at least one parameter, wherein the at least one parameter persists from the third meta-language file to the second meta-language file; dynamically generating and displaying one or more second visually animated graphical elements in accordance with the particular execution of the at least a second portion of the second meta-language file, including displaying the second zone of the background; wherein the at least a second portion of the second meta-language file executes differently from the particular execution when the at least one parameter is not set. | 11. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause performance comprising: receiving a meta-language file comprising a conversion of a script file in a natural language format, the script file including a plurality of natural language statements; interpreting, by a first computing device, the meta-language file for execution of at least a first portion of the meta-language file; dynamically generating and displaying, on the first computing device, one or more visually animated graphical elements in accordance with the execution of the at least a first portion of the meta-language file; wherein the one or more visually animated graphical elements comprise an action element that relates to a background comprising a plurality of zones, and that causes displaying a first zone, of the plurality of zones, of the background; in response to a user interactive action taken on the one or more visually animated graphical elements of the at least a first portion of the meta-language file, by a first user on the first computing device, setting at least one parameter based on the user interactive action; wherein setting the at least one parameter causes a third meta-language file associated with the script file to particularly execute for a second user that is different from execution of the third meta-language file for the second user when the at least one parameter is not set; wherein setting the at least one parameter causes modifying the action element to cause displaying a second zone, of the plurality of zones, of the background; receiving a second meta-language file comprising a conversion of a second script file in a natural language format, the second script file including a plurality of natural language statements, the second script file separate and different from the script file; interpreting the second meta-language file for particular execution of at least a second portion of the second meta-language file in accordance with the at least one parameter, wherein the at least one parameter persists from the third meta-language file to the second meta-language file; dynamically generating and displaying one or more second visually animated graphical elements in accordance with the particular execution of the at least a second portion of the second meta-language file, including displaying the second zone of the background; wherein the at least a second portion of the second meta-language file executes differently from the particular execution when the at least one parameter is not set. 14. The one or more non-transitory machine-readable media of claim 11 , wherein the instructions, when executed by the one or more processors, further cause performance comprising generating the script file based on user input of the plurality of natural language statements. | 0.915228 |
8,032,467 | 5 | 6 | 5. A method as set forth in claim 1 , wherein the act of optimizing a discount weight for assigning to each of the inputs further comprises acts of: identifying a set of variables in the Dempster-Shafer Reasoning System, where each variable in the set has at least one input basic probability assignment (bpa); identifying at least one output variable, the output variable having output bpa corresponding to the input bpa; defining a gradient of an objective function in terms of a discounting weight vector, an output bpa, and a partial derivative of the output bpa with respect to the discounting weight vector; at an initial time, calculating the output bpa without an input bpa being applied, and storing the result; for a next input at time k, calculating an output bpa with the input bpa being applied without discounting, and storing the result; redefining the gradient according to the act of defining the gradient, using the results obtained, at a time and a previous time, in the act of calculating an output bpa with the input bpa being applied; updating the discounting weight factor; and repeating the operations of calculating an output bpa with the input bpa being applied through updating the discounting weight factor until convergence of the discounting weight factor or until the input is exhausted. | 5. A method as set forth in claim 1 , wherein the act of optimizing a discount weight for assigning to each of the inputs further comprises acts of: identifying a set of variables in the Dempster-Shafer Reasoning System, where each variable in the set has at least one input basic probability assignment (bpa); identifying at least one output variable, the output variable having output bpa corresponding to the input bpa; defining a gradient of an objective function in terms of a discounting weight vector, an output bpa, and a partial derivative of the output bpa with respect to the discounting weight vector; at an initial time, calculating the output bpa without an input bpa being applied, and storing the result; for a next input at time k, calculating an output bpa with the input bpa being applied without discounting, and storing the result; redefining the gradient according to the act of defining the gradient, using the results obtained, at a time and a previous time, in the act of calculating an output bpa with the input bpa being applied; updating the discounting weight factor; and repeating the operations of calculating an output bpa with the input bpa being applied through updating the discounting weight factor until convergence of the discounting weight factor or until the input is exhausted. 6. A method as set forth in claim 5 , wherein in the act of defining a gradient of an objective function in terms of a discounting weight vector, the objective function is based on the combined bpa on a variable XεU, with variable frame Θ X , and is defined as: J ( α ) = ∑ k ∑ l [ ∑ j ( P kl ( a j ) - δ kj ) 2 + λ * m ( ϕ ) ] , where P kl is an (un-normalized) pignistic probability given by: P kl ( a j ) = ∑ C ⊆ Θ X , a j ∈ C m ( C ) C , ∀ a j ∈ Θ X , where m(·) is an un-normalized bpa on the variable frame of Θ X , and δ kj = { 1 if k = j 0 if k ≠ j represents a given truth bpa on a same variable frame , where φ represents an empty set, m(φ) represents mass on conflict as all bpa's refer to un-normalized bpa's, and ∥ ∥ denotes an operator. | 0.5 |
8,702,433 | 27 | 28 | 27. A method of training a user via an interactive electronic training system, the method comprising: providing information regarding a real or simulated person for display to a trainee via an interactive electronic training system terminal; at least partly causing the trainee to be instructed to verbally identify one or more needs of the person based on the information; at least partly causing an indication to be stored in computer readable memory as to whether the trainee correctly identified at least a first need; at least partly causing the trainee to be instructed to verbally identify at least one item that appropriately corresponds to the first need; at least partly causing an indication to be stored in computer readable memory as to whether the trainee correctly identified at least a first item, wherein the first item is a product and/or service, that appropriately corresponds to the first need; at least partly causing the trainee to be instructed to verbally explain why the first item corresponds to the first need; at least partly causing an indication to be stored in computer readable memory as to whether the trainee correctly explained why the first item corresponds to the first need; and calculating and reporting by the interactive electronic training a cumulative score based at least in part on one or more of the stored indications, including at least the indication as to whether the trainee correctly explained why the first item corresponds to the first need. | 27. A method of training a user via an interactive electronic training system, the method comprising: providing information regarding a real or simulated person for display to a trainee via an interactive electronic training system terminal; at least partly causing the trainee to be instructed to verbally identify one or more needs of the person based on the information; at least partly causing an indication to be stored in computer readable memory as to whether the trainee correctly identified at least a first need; at least partly causing the trainee to be instructed to verbally identify at least one item that appropriately corresponds to the first need; at least partly causing an indication to be stored in computer readable memory as to whether the trainee correctly identified at least a first item, wherein the first item is a product and/or service, that appropriately corresponds to the first need; at least partly causing the trainee to be instructed to verbally explain why the first item corresponds to the first need; at least partly causing an indication to be stored in computer readable memory as to whether the trainee correctly explained why the first item corresponds to the first need; and calculating and reporting by the interactive electronic training a cumulative score based at least in part on one or more of the stored indications, including at least the indication as to whether the trainee correctly explained why the first item corresponds to the first need. 28. The method as defined in claim 27 , the method further comprising: automatically starting a timer in coordination with the system presenting the instructed to verbally identify at least one item that appropriately corresponds to the first need; providing a stop timer control; and providing an instruction that the stop timer control be activated when the trainee begins responding to the instruction to verbally identify at least one item. | 0.5 |
9,000,887 | 13 | 18 | 13. An apparatus for communicating control information, comprising: a processing system configured to: determine a first movement of a first device wearable by a user based on a first set of data received from the first device by way of an antenna, wherein the first set of data relates to the first movement of the first device, wherein the first determined movement is used to create a first set of possibly performed gestures; determine a second movement of a second device wearable by the user based on a second set of data received from the second device by way of the antenna, wherein the second set of data relates to the second movement of the second device, wherein the first and second movements occur simultaneously, wherein the second determined movement is used to create a second set of possibly performed gestures, and wherein the second wearable device is separate from and not integrated with the first wearable device; and infer, from the first and second sets of possibly performed gestures, that the first movement is representative of an intended command and the second movement is not representative of the intended command; and a transmitter configured to transmit information based on the inference and wherein inferring that the first movement is representative of the intended command and the second movement is not representative of the intended command is based on the first and second sets of possibly performed gestures indicating that the first and second movements are in substantially the same direction. | 13. An apparatus for communicating control information, comprising: a processing system configured to: determine a first movement of a first device wearable by a user based on a first set of data received from the first device by way of an antenna, wherein the first set of data relates to the first movement of the first device, wherein the first determined movement is used to create a first set of possibly performed gestures; determine a second movement of a second device wearable by the user based on a second set of data received from the second device by way of the antenna, wherein the second set of data relates to the second movement of the second device, wherein the first and second movements occur simultaneously, wherein the second determined movement is used to create a second set of possibly performed gestures, and wherein the second wearable device is separate from and not integrated with the first wearable device; and infer, from the first and second sets of possibly performed gestures, that the first movement is representative of an intended command and the second movement is not representative of the intended command; and a transmitter configured to transmit information based on the inference and wherein inferring that the first movement is representative of the intended command and the second movement is not representative of the intended command is based on the first and second sets of possibly performed gestures indicating that the first and second movements are in substantially the same direction. 18. The apparatus of claim 13 , wherein the processing system is further configured to provide user feedback, upon inferring that the first movement is representative of the intended command, using at least one of a tactile feedback, a visual feedback, or an audible feedback. | 0.5 |
10,127,928 | 14 | 15 | 14. The system of claim 11 , wherein the determined first emotional state comprises a first intensity of emotion, and wherein the determined second emotional state comprises a second intensity of emotion. | 14. The system of claim 11 , wherein the determined first emotional state comprises a first intensity of emotion, and wherein the determined second emotional state comprises a second intensity of emotion. 15. The system of claim 14 , wherein the determined first emotional intensity is indicated on the timeline by a first color saturation, and wherein the determined second emotional intensity is indicated on the timeline by a second color saturation. | 0.5 |
8,284,922 | 13 | 18 | 13. A system for changing a communication quality of a communication session based on a meaning of speech data, the system comprising system components including: a parser component for parsing speech data exchanged between clients participating in a communication session; a service quality analyzer component for determining a meaning of the parsed speech data; and a quality controller component for performing an action to change a communication quality of the communication session based on the meaning of the parsed speech data, wherein at least one of the system components includes at least one electronic hardware component. | 13. A system for changing a communication quality of a communication session based on a meaning of speech data, the system comprising system components including: a parser component for parsing speech data exchanged between clients participating in a communication session; a service quality analyzer component for determining a meaning of the parsed speech data; and a quality controller component for performing an action to change a communication quality of the communication session based on the meaning of the parsed speech data, wherein at least one of the system components includes at least one electronic hardware component. 18. The system of claim 13 wherein the parser component includes a speech recognizer component configured for performing speech recognition on the speech data. | 0.931701 |
7,668,791 | 11 | 13 | 11. A computer readable storage medium containing executable program instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving a search term comprising a noun; finding relevant electronic resources that match the search term; displaying a list of relevant electronic resources and snippets of the relevant electronic resources in the list that comprise words matching the search term; parsing a plurality of relevant electronic documents to discover factual descriptions of sentences that comprise the noun of the search term and one or more verbs matching words of a fact-word table constructed to include a list of verbs determined to be indicative of fact expressions; eliminating portions of the relevant electronic documents from fact extraction processing that comprise words not matching the search term and words of the fact-word table; examining the discovered factual descriptions to identify the linguistic constituents of the factual descriptions after eliminating portions of the electronic documents; determining whether to present a factual description as a fact relevant to the search term based on the identified linguistic constituent by applying excluding rules to candidate factual descriptions in relation to the linguistic constituents, scoring candidate factual descriptions based on certainty of a matching fact-word and on individual weights of subject and object noun phrases, and eliminating candidate factual descriptions from consideration according to the excluding rules and scoring of the factual descriptions; and presenting at least a portion of a sentence that contains the search term and a factual description determined to be a fact relevant to the search term. | 11. A computer readable storage medium containing executable program instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving a search term comprising a noun; finding relevant electronic resources that match the search term; displaying a list of relevant electronic resources and snippets of the relevant electronic resources in the list that comprise words matching the search term; parsing a plurality of relevant electronic documents to discover factual descriptions of sentences that comprise the noun of the search term and one or more verbs matching words of a fact-word table constructed to include a list of verbs determined to be indicative of fact expressions; eliminating portions of the relevant electronic documents from fact extraction processing that comprise words not matching the search term and words of the fact-word table; examining the discovered factual descriptions to identify the linguistic constituents of the factual descriptions after eliminating portions of the electronic documents; determining whether to present a factual description as a fact relevant to the search term based on the identified linguistic constituent by applying excluding rules to candidate factual descriptions in relation to the linguistic constituents, scoring candidate factual descriptions based on certainty of a matching fact-word and on individual weights of subject and object noun phrases, and eliminating candidate factual descriptions from consideration according to the excluding rules and scoring of the factual descriptions; and presenting at least a portion of a sentence that contains the search term and a factual description determined to be a fact relevant to the search term. 13. The computer readable storage medium of claim 11 , wherein the acts further comprise obtaining the electronic documents and presenting factual descriptions prior to receiving the search term and searching the electronic documents and factual descriptions to find those electronic documents and corresponding factual descriptions that are relevant to the search term. | 0.593407 |
9,318,128 | 11 | 14 | 11. A non-transitory computer readable storage medium having stored thereon instructions, that when executed by a computing device, cause the computing device to perform functions comprising: receiving information indicating a plurality of actions that a given application is configured to perform, wherein the information indicating each respective action of the plurality of actions includes one or more parameters that are used to enable the given application to perform the respective action; receiving, for each respective action, one or more example instructions that, when recognized by the given application, causes the given application to perform the respective action, wherein the one or more example instructions comprise natural language; based on the one or more example instructions for each respective action, the plurality of actions, and the one or more parameters included for each respective action, determining a plurality of candidate instructions for each respective action that, when recognized by a voice interface of the given application, causes the given application to perform the respective action, wherein each candidate instruction of the plurality of candidate instructions comprises one or more grammars recognizable by the voice interface of the given application; receiving a plurality of acceptance information comprising, for each candidate instruction, respective acceptance information indicative of whether the candidate instruction is applicable to the respective action, wherein the plurality of acceptance information indicates, for each respective action of at least one of the plurality of actions, that at least one of the plurality of candidate instructions determined for the respective action is rejected; based on the plurality of acceptance information, storing, at the computing device, for each candidate instruction, a respective identifier associated with the candidate instruction and indicative of whether the candidate instruction is rejected; comparing at least a portion of the respective acceptance information with a stored acceptance information log so as to determine a correlation between the respective acceptance information and the stored acceptance information log, wherein the stored acceptance information log comprises a plurality of predetermined acceptance information associated with a plurality of predetermined example instructions; and based on the correlation, referring to the stored identifiers to determine a set of instructions that are recognizable by the voice interface and that, when recognized by the voice interface, causes the given application to perform one or more of the plurality of actions, wherein determining the set of instructions comprises, for each respective action, (i) selecting, based on the stored identifiers, one or more of the plurality of candidate instructions for the respective action to be included in the set of instructions and (ii) selecting, based on the stored identifiers, the at least one rejected candidate instruction for the respective action to not be included in the set of instructions and to not be recognizable by the voice interface to cause the given application to perform the respective action. | 11. A non-transitory computer readable storage medium having stored thereon instructions, that when executed by a computing device, cause the computing device to perform functions comprising: receiving information indicating a plurality of actions that a given application is configured to perform, wherein the information indicating each respective action of the plurality of actions includes one or more parameters that are used to enable the given application to perform the respective action; receiving, for each respective action, one or more example instructions that, when recognized by the given application, causes the given application to perform the respective action, wherein the one or more example instructions comprise natural language; based on the one or more example instructions for each respective action, the plurality of actions, and the one or more parameters included for each respective action, determining a plurality of candidate instructions for each respective action that, when recognized by a voice interface of the given application, causes the given application to perform the respective action, wherein each candidate instruction of the plurality of candidate instructions comprises one or more grammars recognizable by the voice interface of the given application; receiving a plurality of acceptance information comprising, for each candidate instruction, respective acceptance information indicative of whether the candidate instruction is applicable to the respective action, wherein the plurality of acceptance information indicates, for each respective action of at least one of the plurality of actions, that at least one of the plurality of candidate instructions determined for the respective action is rejected; based on the plurality of acceptance information, storing, at the computing device, for each candidate instruction, a respective identifier associated with the candidate instruction and indicative of whether the candidate instruction is rejected; comparing at least a portion of the respective acceptance information with a stored acceptance information log so as to determine a correlation between the respective acceptance information and the stored acceptance information log, wherein the stored acceptance information log comprises a plurality of predetermined acceptance information associated with a plurality of predetermined example instructions; and based on the correlation, referring to the stored identifiers to determine a set of instructions that are recognizable by the voice interface and that, when recognized by the voice interface, causes the given application to perform one or more of the plurality of actions, wherein determining the set of instructions comprises, for each respective action, (i) selecting, based on the stored identifiers, one or more of the plurality of candidate instructions for the respective action to be included in the set of instructions and (ii) selecting, based on the stored identifiers, the at least one rejected candidate instruction for the respective action to not be included in the set of instructions and to not be recognizable by the voice interface to cause the given application to perform the respective action. 14. The non-transitory computer readable storage medium of claim 11 , wherein the respective acceptance information includes one or more of: an acceptance of the candidate instruction, a rejection of the candidate instruction, a confidence score of the candidate instruction, and a rank of the candidate instruction with respect to at least one other candidate instruction of the plurality of candidate instructions. | 0.5 |
7,484,185 | 1 | 4 | 1. A method for displaying a multilevel treeview of hierarchical information within a pane of a computer display window, comprising: searching an information hierarchy for a plurality of occurrences of a specified information element of the information hierarchy, based upon a search criteria; displaying within the pane the multilevel treeview of the information hierarchy; displaying within the multilevel treeview an indicator which indicates whether a displayed element of the information hierarchy comprises sub-elements, on one side of the multilevel treeview; indicating within the multilevel treeview locations of the plurality of found occurrences of the specified information element; graphically connecting via a graphical connection, only the plurality of occurrences of the specified information element within the multilevel treeview, the graphical connection being positioned on an opposite side from the indicator with respect to the multilevel treeview, and comprising: a plurality of horizontal lines extending outward from each displayed found occurrence of the specified information element, and a vertical line positioned to intersect an outward end of each of the plurality of horizontal lines, the vertical line being terminated between a horizontal line corresponding to a first displayed found occurrence of the specified information element and a last displayed found occurrence of the specified information element; selecting an occurrence of the specified information element within the multilevel treeview; and displaying a pop-up menu positioned directly beneath the selected occurrence of the specified information element, the pop-up menu comprising: statistical information on the total number of occurrences of the specified information element, and a link to a next occurrence of the specified information element. | 1. A method for displaying a multilevel treeview of hierarchical information within a pane of a computer display window, comprising: searching an information hierarchy for a plurality of occurrences of a specified information element of the information hierarchy, based upon a search criteria; displaying within the pane the multilevel treeview of the information hierarchy; displaying within the multilevel treeview an indicator which indicates whether a displayed element of the information hierarchy comprises sub-elements, on one side of the multilevel treeview; indicating within the multilevel treeview locations of the plurality of found occurrences of the specified information element; graphically connecting via a graphical connection, only the plurality of occurrences of the specified information element within the multilevel treeview, the graphical connection being positioned on an opposite side from the indicator with respect to the multilevel treeview, and comprising: a plurality of horizontal lines extending outward from each displayed found occurrence of the specified information element, and a vertical line positioned to intersect an outward end of each of the plurality of horizontal lines, the vertical line being terminated between a horizontal line corresponding to a first displayed found occurrence of the specified information element and a last displayed found occurrence of the specified information element; selecting an occurrence of the specified information element within the multilevel treeview; and displaying a pop-up menu positioned directly beneath the selected occurrence of the specified information element, the pop-up menu comprising: statistical information on the total number of occurrences of the specified information element, and a link to a next occurrence of the specified information element. 4. The method of claim 1 , further comprising graphically connecting a compressed branch of the information hierarchy containing a specified information element with the plurality of graphically connected found occurrences of the specified information element within the multilevel treeview. | 0.633501 |
8,776,195 | 14 | 15 | 14. A computer program product according to claim 13 , wherein generating the set of questions from the facts in the common data format further includes: receiving a request to authenticate the customer; and performing a lookup operation on the database in response to the request, the lookup operation being configured to locate entries of the set of entries that include the identifier associated with the customer. | 14. A computer program product according to claim 13 , wherein generating the set of questions from the facts in the common data format further includes: receiving a request to authenticate the customer; and performing a lookup operation on the database in response to the request, the lookup operation being configured to locate entries of the set of entries that include the identifier associated with the customer. 15. A computer program product according to claim 14 , wherein each fact source is further associated with a fact category of a set of fact categories, wherein each entry of the set of entries of the database includes the fact category of the fact source from which the with which the entry is associated was received, wherein each question of the set of questions is associated with a question type of a set of question types, wherein performing the lookup operation on the database in response to the request includes: collecting fact categories of the entries of the set of entries including the identifier associated with the customer, and wherein generating the set of questions from the facts in the common data format further includes: for each question of the set of questions, selecting a question type of the set of question types based on the collected fact categories. | 0.5 |
10,078,499 | 1 | 14 | 1. A system comprising: a microprocessor; a memory coupled to the microprocessor; a plurality of grouping blocks wherein each of the plurality of grouping blocks displays summary information about at least one keyword contained within each of the plurality of grouping blocks; and a user interface for displaying and manipulating keywords, the user interface providing a general way to display and interact with groups and hierarchies using at least a first inverted “L” shaped block, wherein the at least a first inverted “L” shaped block represents a single keyword concept. | 1. A system comprising: a microprocessor; a memory coupled to the microprocessor; a plurality of grouping blocks wherein each of the plurality of grouping blocks displays summary information about at least one keyword contained within each of the plurality of grouping blocks; and a user interface for displaying and manipulating keywords, the user interface providing a general way to display and interact with groups and hierarchies using at least a first inverted “L” shaped block, wherein the at least a first inverted “L” shaped block represents a single keyword concept. 14. The system of claim 1 further comprising a plurality of grouping blocks wherein at least two of the plurality of grouping blocks are dragged and dropped to combine a plurality of keyword concepts associated with the at least two of the plurality of grouping blocks. | 0.862895 |
8,364,750 | 13 | 14 | 13. The computer-readable storage medium of claim 11 , the receiving comprising: receiving a service invocation result from the service host before returning from the sending. | 13. The computer-readable storage medium of claim 11 , the receiving comprising: receiving a service invocation result from the service host before returning from the sending. 14. The computer-readable storage medium of claim 13 : the generating comprising: receiving an asynchronous callback with the first logic; the sending comprising: returning from the sending upon sending the logic to the service host; and the receiving comprising: invoking the asynchronous callback upon receiving a service invocation result from the service host in response to the batch logic. | 0.5 |
8,539,024 | 18 | 19 | 18. The system of claim 1 , wherein the query message sent to the server system includes a request identification that is included by the server system in the corresponding server response message. | 18. The system of claim 1 , wherein the query message sent to the server system includes a request identification that is included by the server system in the corresponding server response message. 19. The system of claim 18 , wherein the usability of a server system response is determined by the client object by matching the request identification received in the server response message against a request identification on the client. | 0.5 |
9,635,101 | 12 | 16 | 12. One or more non-transitory computer readable media comprising program instructions, the program instructions to: determine a plurality of proposed solutions for a clustered storage system, wherein each of the plurality of proposed solutions comprises a set of configuration settings of the clustered storage system for the proposed solution and a set of one or more specific actions to execute on the clustered storage system to implement the proposed solution; for each of the plurality of proposed solutions, determine a service level objective evaluation value for a service level objective of a workload of the clustered storage system, wherein the instructions to determine the service level objective evaluation value comprises instructions to use a first predicted value for a first service level objective metric of the service level objective and a first target value of the service level objective metric; determine a proposed solution evaluation value for the proposed solution based, at least in part, on the service level objective evaluation value determined for the proposed solution and a first predicted value for a first cost metric corresponding to the proposed solution; select a first proposed solution from the plurality of proposed solutions based, at least in part, on the proposed solution evaluation values determined for the plurality of proposed solutions; and apply the selected first proposed solution to the clustered storage system. | 12. One or more non-transitory computer readable media comprising program instructions, the program instructions to: determine a plurality of proposed solutions for a clustered storage system, wherein each of the plurality of proposed solutions comprises a set of configuration settings of the clustered storage system for the proposed solution and a set of one or more specific actions to execute on the clustered storage system to implement the proposed solution; for each of the plurality of proposed solutions, determine a service level objective evaluation value for a service level objective of a workload of the clustered storage system, wherein the instructions to determine the service level objective evaluation value comprises instructions to use a first predicted value for a first service level objective metric of the service level objective and a first target value of the service level objective metric; determine a proposed solution evaluation value for the proposed solution based, at least in part, on the service level objective evaluation value determined for the proposed solution and a first predicted value for a first cost metric corresponding to the proposed solution; select a first proposed solution from the plurality of proposed solutions based, at least in part, on the proposed solution evaluation values determined for the plurality of proposed solutions; and apply the selected first proposed solution to the clustered storage system. 16. The non-transitory computer readable media of claim 12 further comprising program instructions to: for each of the plurality of proposed solutions, determine the first predicted value for the first cost metric corresponding to the proposed solution. | 0.801101 |
10,032,463 | 5 | 7 | 5. A computer-implemented method comprising: as performed by one or more computing devices configured with specific computer-executable instructions, generating language model input data regarding an utterance of a user, wherein the language model input data is generated using an acoustic model and audio data regarding the utterance, and wherein the language model input data is associated with a plurality of transcription hypotheses for the utterance; obtaining interaction history data regarding a prior interaction of the user with a computing system; obtaining encoder state data regarding an internal state of a neural-network-based encoder reached during generation of a prior interaction history vector for the user; restoring the internal state of the neural-network-based encoder using the encoder state data; processing at least a portion of the interaction history data using the neural-network-based encoder to generate an interaction history vector, wherein the interaction history vector comprises an encoded representation of at least a portion of a plurality of prior interactions of the user, and wherein the plurality of prior interactions comprises a verbal interaction, and a separate non-verbal interaction with displayed content; processing the language model input data and the interaction history vector using a neural-network-based decoder to generate scores for individual transcription hypotheses of the plurality of transcription hypotheses; and selecting a transcription of the utterance using the scores for the individual transcription hypotheses. | 5. A computer-implemented method comprising: as performed by one or more computing devices configured with specific computer-executable instructions, generating language model input data regarding an utterance of a user, wherein the language model input data is generated using an acoustic model and audio data regarding the utterance, and wherein the language model input data is associated with a plurality of transcription hypotheses for the utterance; obtaining interaction history data regarding a prior interaction of the user with a computing system; obtaining encoder state data regarding an internal state of a neural-network-based encoder reached during generation of a prior interaction history vector for the user; restoring the internal state of the neural-network-based encoder using the encoder state data; processing at least a portion of the interaction history data using the neural-network-based encoder to generate an interaction history vector, wherein the interaction history vector comprises an encoded representation of at least a portion of a plurality of prior interactions of the user, and wherein the plurality of prior interactions comprises a verbal interaction, and a separate non-verbal interaction with displayed content; processing the language model input data and the interaction history vector using a neural-network-based decoder to generate scores for individual transcription hypotheses of the plurality of transcription hypotheses; and selecting a transcription of the utterance using the scores for the individual transcription hypotheses. 7. The computer-implemented method of claim 5 , wherein the interaction history vector comprises a mapping of the interaction history data to a first point in n-dimensional space, wherein n is a positive integer. | 0.84593 |
8,881,004 | 1 | 6 | 1. A method of enabling a spell check function on a handheld electronic device having a plurality of language objects stored in a first data source available to the handheld electronic device and having a plurality of language objects stored in a second data source available to the handheld electronic device, the method comprising: detecting a text entry comprising a plurality of characters; employing the spell check function to identify in the first data source one or more a first language objects as one or more first proposed spell-check interpretations of the text entry when it is determined that no stored language object corresponds with the text entry; if the quantity of the one or more first proposed spell-check interpretations is less than a predetermined quantity, employing the spell check function to identify in the second data source one or more second language objects as one or more second proposed spell-check interpretations of the text entry; outputting the one or more first spell-check interpretations and, if the quantity of the one or more first language objects is less than the predetermined quantity, the one or more second proposed spell-check interpretations; and responsive to a predetermined input, outputting a menu including a plurality of selectable spell check options. | 1. A method of enabling a spell check function on a handheld electronic device having a plurality of language objects stored in a first data source available to the handheld electronic device and having a plurality of language objects stored in a second data source available to the handheld electronic device, the method comprising: detecting a text entry comprising a plurality of characters; employing the spell check function to identify in the first data source one or more a first language objects as one or more first proposed spell-check interpretations of the text entry when it is determined that no stored language object corresponds with the text entry; if the quantity of the one or more first proposed spell-check interpretations is less than a predetermined quantity, employing the spell check function to identify in the second data source one or more second language objects as one or more second proposed spell-check interpretations of the text entry; outputting the one or more first spell-check interpretations and, if the quantity of the one or more first language objects is less than the predetermined quantity, the one or more second proposed spell-check interpretations; and responsive to a predetermined input, outputting a menu including a plurality of selectable spell check options. 6. The method of claim 1 , further comprising outputting the first and second proposed spell-check interpretations in a list. | 0.636628 |
7,953,751 | 2 | 5 | 2. A method of searching for audio features within multimedia files, comprising: specifying a query criterion that comprises one or more classes of audio sounds, each of the classes comprising acoustic characteristics of a range of sounds; querying an audio track of a multimedia file to detect occurrences of the classes; and retrieving at least a segment of the searched multimedia file, if the segment contains at least one occurrence of the classes. | 2. A method of searching for audio features within multimedia files, comprising: specifying a query criterion that comprises one or more classes of audio sounds, each of the classes comprising acoustic characteristics of a range of sounds; querying an audio track of a multimedia file to detect occurrences of the classes; and retrieving at least a segment of the searched multimedia file, if the segment contains at least one occurrence of the classes. 5. The method of claim 2 , further comprising providing, to a user, a list of detections of the query criterion within the file. | 0.597484 |
8,744,607 | 2 | 3 | 2. The system of claim 1 , further comprising an objective autonomous learning engine that infers one or more functions for the manufacturing tool based on the modified manufacturing recipe processed by the manufacturing tool, wherein the one or more functions predict asset output metrics for the produced asset. | 2. The system of claim 1 , further comprising an objective autonomous learning engine that infers one or more functions for the manufacturing tool based on the modified manufacturing recipe processed by the manufacturing tool, wherein the one or more functions predict asset output metrics for the produced asset. 3. The system of claim 2 , further comprising an autonomous optimization engine that extracts a set of updated recipe parameters from a set of input measurements and the one or more functions to generate an adjusted recipe within a predefined tolerance of a target value for the asset output metrics. | 0.5 |
8,412,554 | 15 | 24 | 15. The system of claim 13 , wherein the controller processor device further generates task suggestion based on task descriptions, wherein a task description comprises task external description, task properties, task functionalities and task actions. | 15. The system of claim 13 , wherein the controller processor device further generates task suggestion based on task descriptions, wherein a task description comprises task external description, task properties, task functionalities and task actions. 24. The system of claim 15 wherein the user task description comprises a semantic ontology that provides interoperable description and interchange of descriptions. | 0.811778 |
9,177,051 | 1 | 2 | 1. A method for extracting information from a set of documents, the method comprising: receiving a set of documents; receiving a first concept, the first concept representing first information for extraction from the set of documents, wherein the first concept comprises a plurality of trigger phrases related to the first concept; updating the first concept into a first subset and a second subset, the first subset comprising one or more of the plurality of trigger phrases of the first concept, the second subset comprising remaining trigger phrases of the plurality of trigger phrases of the first concept; creating a second concept based on the first concept, the second concept having a definitional dependency from the first concept, the definitional dependency providing a contextual relationship to the second concept such that the second concept represents second information within a context of the first information; updating the second concept into a third concept and a fourth concept, the third concept depending on the first subset of the first concept, the fourth concept depending on the second subset of the first concept; selecting the second concept; and based on the selection of the second concept, extracting from the set of documents, the second information within the context of the first information. | 1. A method for extracting information from a set of documents, the method comprising: receiving a set of documents; receiving a first concept, the first concept representing first information for extraction from the set of documents, wherein the first concept comprises a plurality of trigger phrases related to the first concept; updating the first concept into a first subset and a second subset, the first subset comprising one or more of the plurality of trigger phrases of the first concept, the second subset comprising remaining trigger phrases of the plurality of trigger phrases of the first concept; creating a second concept based on the first concept, the second concept having a definitional dependency from the first concept, the definitional dependency providing a contextual relationship to the second concept such that the second concept represents second information within a context of the first information; updating the second concept into a third concept and a fourth concept, the third concept depending on the first subset of the first concept, the fourth concept depending on the second subset of the first concept; selecting the second concept; and based on the selection of the second concept, extracting from the set of documents, the second information within the context of the first information. 2. The method of claim 1 , wherein the second information within a context of the first information comprises the second information in a contiguous block of text in proximity of the first information. | 0.768433 |
10,157,365 | 9 | 10 | 9. A system comprising: a memory; and a processing device, operatively coupled to the memory to: identify, via a user interface, a plurality of service oriented candidates in a service-oriented architecture (SOA) service model, wherein the plurality of service oriented comprise a first service candidate, a second service candidate, and a composition candidate, and wherein the composition candidate comprises at least the first service candidate and the second service candidate; replace a composition candidate inventory presented in a first portion of the user interface with a service candidate inventory comprising the first service candidate and the second service candidate in response to a selection of the composition candidate from the composition candidate inventory; add, via drag and drop operations, the first service candidate and the second service candidate to the composition candidate, wherein a first visualization of the first service candidate and a second visualization of the second service candidate are comprised in a layout of the composition candidate in a second portion of the user interface; receive, via the user interface, information to define a relationship between the first service candidate and the second service candidate; responsive to a determination that the relationship complies with a SOA principle: add the relationship to the SOA service model; update one or more relationship counters associated with the composition candidate, wherein the one or more relationship counters are updated to track the relationship between the first service candidate and the second service candidate; and provide, in view of an indicated selected function of a modeling tool provided via the user interface, the one or more relationship counters on the user interface; and reuse, via the user interface, the first service candidate, the second service candidate, and the composition candidate according to the relationship and the one or more relationship counters. | 9. A system comprising: a memory; and a processing device, operatively coupled to the memory to: identify, via a user interface, a plurality of service oriented candidates in a service-oriented architecture (SOA) service model, wherein the plurality of service oriented comprise a first service candidate, a second service candidate, and a composition candidate, and wherein the composition candidate comprises at least the first service candidate and the second service candidate; replace a composition candidate inventory presented in a first portion of the user interface with a service candidate inventory comprising the first service candidate and the second service candidate in response to a selection of the composition candidate from the composition candidate inventory; add, via drag and drop operations, the first service candidate and the second service candidate to the composition candidate, wherein a first visualization of the first service candidate and a second visualization of the second service candidate are comprised in a layout of the composition candidate in a second portion of the user interface; receive, via the user interface, information to define a relationship between the first service candidate and the second service candidate; responsive to a determination that the relationship complies with a SOA principle: add the relationship to the SOA service model; update one or more relationship counters associated with the composition candidate, wherein the one or more relationship counters are updated to track the relationship between the first service candidate and the second service candidate; and provide, in view of an indicated selected function of a modeling tool provided via the user interface, the one or more relationship counters on the user interface; and reuse, via the user interface, the first service candidate, the second service candidate, and the composition candidate according to the relationship and the one or more relationship counters. 10. The system of claim 9 , the processing device to link a first operation candidate in the first service candidate to a second operation candidate in the second service candidate within the composition candidate. | 0.650327 |
6,088,731 | 1 | 13 | 1. In a computer system having a processor, a memory unit, an input device and an output device, a method for collecting site information from an Internet site, said method comprising computer implemented steps of: executing an intelligent assistant process on said computer system; establishing communication with said Internet site; detecting an intelligent assistant tag in said Internet site, said intelligent assistant tag containing embedded information; authorizing said computer system to collect said site information from said Internet site when said embedded information corresponds to a plug-in process of said intelligent assistant; collecting said site information from said Internet site; and altering said intelligent assistant process based on said site information. | 1. In a computer system having a processor, a memory unit, an input device and an output device, a method for collecting site information from an Internet site, said method comprising computer implemented steps of: executing an intelligent assistant process on said computer system; establishing communication with said Internet site; detecting an intelligent assistant tag in said Internet site, said intelligent assistant tag containing embedded information; authorizing said computer system to collect said site information from said Internet site when said embedded information corresponds to a plug-in process of said intelligent assistant; collecting said site information from said Internet site; and altering said intelligent assistant process based on said site information. 13. The method of claim 1 wherein said intelligent assistant process is stored in said memory unit of said computer system. | 0.757874 |
7,844,464 | 28 | 41 | 28. An apparatus comprising: A computer processor and a non-transitory computer-readable medium tangibly storing instructions executable by the computer processor to perform a method comprising: (A) deriving, from a region of a document and a corresponding region of a spoken audio stream, a likelihood that the region of the document correctly represents content in the corresponding region of the spoken audio stream; (B) selecting a measure of relevance of the region of the spoken audio stream, the measure of relevance representing a measure of importance that the region of the spoken audio stream be brought to the attention of a human proofreader; and (C) deriving, from the stored representation of the likelihood and the stored representation of the measure of relevance, an emphasis factor that modifies emphasis placed on the region of the spoken audio stream when played back, wherein (C) comprises: (C)(1) identifying a rule that identifies the emphasis factor based on the identified likelihood and the identified measure of relevance; and (C)(2) applying the rule to the identified likelihood and the identified measure of relevance to derive the emphasis factor; where (C)(2) comprises: (C)(2)(a) identifying a first weight associated with the identified likelihood; (C)(2)(b) identifying a second weight associated with the measure of relevance; and (C)(2)(c) deriving the emphasis factor from a combination of the identified likelihood and the measure of relevance weighted by the first and second weights, respectively. | 28. An apparatus comprising: A computer processor and a non-transitory computer-readable medium tangibly storing instructions executable by the computer processor to perform a method comprising: (A) deriving, from a region of a document and a corresponding region of a spoken audio stream, a likelihood that the region of the document correctly represents content in the corresponding region of the spoken audio stream; (B) selecting a measure of relevance of the region of the spoken audio stream, the measure of relevance representing a measure of importance that the region of the spoken audio stream be brought to the attention of a human proofreader; and (C) deriving, from the stored representation of the likelihood and the stored representation of the measure of relevance, an emphasis factor that modifies emphasis placed on the region of the spoken audio stream when played back, wherein (C) comprises: (C)(1) identifying a rule that identifies the emphasis factor based on the identified likelihood and the identified measure of relevance; and (C)(2) applying the rule to the identified likelihood and the identified measure of relevance to derive the emphasis factor; where (C)(2) comprises: (C)(2)(a) identifying a first weight associated with the identified likelihood; (C)(2)(b) identifying a second weight associated with the measure of relevance; and (C)(2)(c) deriving the emphasis factor from a combination of the identified likelihood and the measure of relevance weighted by the first and second weights, respectively. 41. The apparatus of claim 28 , wherein (B) comprises: identifying a prior relevance of the region of the document; and selecting the measure of relevance of the region of the spoken audio stream based on the identified prior relevance of the region of the document. | 0.569579 |
9,063,753 | 29 | 31 | 29. The system of claim 28 , wherein the scripting framework is further to: prepare data associated with the exit node, and update any changed data resulting from execution of the code snippet. | 29. The system of claim 28 , wherein the scripting framework is further to: prepare data associated with the exit node, and update any changed data resulting from execution of the code snippet. 31. The system of claim 29 , wherein the business object is associated with at least one of a business object service provider, a process agent, or a user interface. | 0.623288 |
10,032,450 | 1 | 10 | 1. A system for generating and updating user interface with machine learning output data relating to electronic communications and contact data, the system comprising: a data storage device storing a graph structure of nodes and edges, the nodes corresponding to contacts and the edges corresponding to relationship scores; a message routing plug in configured to intercept an electronic communication in real-time, the electronic communication having a reference to a contact for at least one of a sender, a recipient and another entity referred to in the electronic communication, the contact corresponding to a node in the graph structure; a machine learning processor configured to: process the electronic communication using classification rules to compute a relationship score, the classification rules comprising natural language processing rules for sentiment classification and formality classification, the relationship score indicating strength of a relationship between the contact and another contact; update the graph structure using the relationship score by updating or creating an edge connected to the node corresponding to the contact in the graph structure based on the relationship score and contact data; a presentation processor configured to process machine interpretable instructions to generate visual effects for at least a portion of the graph structure in response to search requests and queries identifying the contact, the presentation processor further configured to control rendering, on a display at a device, of a user interface including visual interface elements corresponding to the visual effects for the portion of the graph structure generated by the machine learning processor, the visual interface elements indicating contact nodes and relationship edges connecting the contact nodes, the visual effects indicating a contact node representing the node corresponding to the contact in the graph structure, a relationship edge representing the edge connected to the node corresponding to the contact, and an indication of the relationship score; the user interface adapted to render a button configured to be responsive to input representing an indication of the search requests and the queries identifying the contact for provision to the machine learning processor; responsive to the button, the presentation processor further configured to control updating, at the user interface, of the visual interface elements with the visual effects to indicate the contact node, the relationship edge, and the indication of the relationship score. | 1. A system for generating and updating user interface with machine learning output data relating to electronic communications and contact data, the system comprising: a data storage device storing a graph structure of nodes and edges, the nodes corresponding to contacts and the edges corresponding to relationship scores; a message routing plug in configured to intercept an electronic communication in real-time, the electronic communication having a reference to a contact for at least one of a sender, a recipient and another entity referred to in the electronic communication, the contact corresponding to a node in the graph structure; a machine learning processor configured to: process the electronic communication using classification rules to compute a relationship score, the classification rules comprising natural language processing rules for sentiment classification and formality classification, the relationship score indicating strength of a relationship between the contact and another contact; update the graph structure using the relationship score by updating or creating an edge connected to the node corresponding to the contact in the graph structure based on the relationship score and contact data; a presentation processor configured to process machine interpretable instructions to generate visual effects for at least a portion of the graph structure in response to search requests and queries identifying the contact, the presentation processor further configured to control rendering, on a display at a device, of a user interface including visual interface elements corresponding to the visual effects for the portion of the graph structure generated by the machine learning processor, the visual interface elements indicating contact nodes and relationship edges connecting the contact nodes, the visual effects indicating a contact node representing the node corresponding to the contact in the graph structure, a relationship edge representing the edge connected to the node corresponding to the contact, and an indication of the relationship score; the user interface adapted to render a button configured to be responsive to input representing an indication of the search requests and the queries identifying the contact for provision to the machine learning processor; responsive to the button, the presentation processor further configured to control updating, at the user interface, of the visual interface elements with the visual effects to indicate the contact node, the relationship edge, and the indication of the relationship score. 10. The system of claim 1 wherein the relationship scores is computed based on sentiment, formality, frequency and timing of the electronic communication. | 0.822581 |
9,697,194 | 1 | 3 | 1. A method of generating an auto-correct dictionary, the method comprising: analyzing, by a processor, contents of information accessed by a user via a first application, wherein: the contents of information include at least one of words and phrases that appear in the first application; identifying, by the processor, at least one of the words and the phrases that appear in the first application and are not included in a first dictionary; generating, by the processor, a temporary dictionary based, at least in part, on at least one of the words and the phrases identified in the first application that are not included in the first dictionary; and using, by the processor, the temporary dictionary to carry out auto-correct operations on text included in a second application. | 1. A method of generating an auto-correct dictionary, the method comprising: analyzing, by a processor, contents of information accessed by a user via a first application, wherein: the contents of information include at least one of words and phrases that appear in the first application; identifying, by the processor, at least one of the words and the phrases that appear in the first application and are not included in a first dictionary; generating, by the processor, a temporary dictionary based, at least in part, on at least one of the words and the phrases identified in the first application that are not included in the first dictionary; and using, by the processor, the temporary dictionary to carry out auto-correct operations on text included in a second application. 3. The method of claim 1 , wherein the access of the first application occurred within a predetermined time frame. | 0.855696 |
7,523,423 | 12 | 26 | 12. The method of claim 1 , wherein the step of determining a set of indication points further comprises: determining a first execution path indicates, in the input representation, an evaluation of an assignment. | 12. The method of claim 1 , wherein the step of determining a set of indication points further comprises: determining a first execution path indicates, in the input representation, an evaluation of an assignment. 26. The method of claim 12 , further comprising the following steps: identifying a first variable used to evaluate the assignment; representing the first variable by an intermediate representation comprising output elements, wherein each output element refers to a non-canonical DFG structure and to a path condition of the input representation; identifying a first set of output elements whose path condition intersect with a first path condition of the first execution path; and producing a first multiplexer, for the non-canonical DFG structure, corresponding to the first set of output elements; using the first multiplexer to build a non-canonical DFG structure that evaluates the assignment. | 0.5 |
8,233,726 | 21 | 25 | 21. A computer system for identifying a writing system associated with a document image containing one or more words written in the writing system, the system comprising: a non-transitory computer-readable storage medium encoded with executable computer program code comprising: a segmentation module adapted to identify a document image fragment based on the document image, wherein the document image fragment contains one or more pixels from one or more of the words in the document image; a feature extraction module adapted to generate a set of sequential features associated with the document image fragment, wherein each sequential feature describes one dimensional graphic information derived from the one or more pixels in the document image fragment; a feature classification module adapted to: identify a plurality of n-grams based on the set of sequential features, wherein each n-gram comprises an ordered subset of sequential features; and generate a classification score for the document image based at least in part on a frequency of occurrence of the n-grams in sets of sequential features associated with known writing systems, the classification score indicating a likelihood that the document image fragment is written in the writing system; and an optical character recognition module adapted to identify the writing system associated with the document image based at least in part on the classification score for the document image fragment; and a processor for executing the computer program code. | 21. A computer system for identifying a writing system associated with a document image containing one or more words written in the writing system, the system comprising: a non-transitory computer-readable storage medium encoded with executable computer program code comprising: a segmentation module adapted to identify a document image fragment based on the document image, wherein the document image fragment contains one or more pixels from one or more of the words in the document image; a feature extraction module adapted to generate a set of sequential features associated with the document image fragment, wherein each sequential feature describes one dimensional graphic information derived from the one or more pixels in the document image fragment; a feature classification module adapted to: identify a plurality of n-grams based on the set of sequential features, wherein each n-gram comprises an ordered subset of sequential features; and generate a classification score for the document image based at least in part on a frequency of occurrence of the n-grams in sets of sequential features associated with known writing systems, the classification score indicating a likelihood that the document image fragment is written in the writing system; and an optical character recognition module adapted to identify the writing system associated with the document image based at least in part on the classification score for the document image fragment; and a processor for executing the computer program code. 25. The system of claim 21 , wherein the feature classification module is further adapted to: generate a plurality of conditional probability values associated with the plurality of n-grams, wherein each conditional probability value is based at least in part on a frequency of occurrence of an n-gram in the plurality of sets of sequential features associated with known writing systems; and generate the classification score based on the plurality of conditional probability values. | 0.629403 |
8,977,690 | 11 | 12 | 11. The method of claim 4 , wherein the at least one distribution ring comprises at least one logical distribution ring. | 11. The method of claim 4 , wherein the at least one distribution ring comprises at least one logical distribution ring. 12. The method of claim 11 , wherein the network nodes are interconnected by a physical network including intermediate network elements and the network nodes are configured to transmit the information formatted in the markup language between network nodes by tunneling the information formatted in the markup language across the physical network. | 0.5 |
7,549,145 | 3 | 4 | 3. The method as described in claim 1 further comprising: prior to loading the virtual machine code into the common memory: running a first application program; in response to running the first application program, identifying a call to a software effect corresponding to the software code data; and loading the software code data into the common memory, wherein the processing of the software code data occurs during the running of the first application program and wherein the processing is completed prior to the first program calling the software effect. | 3. The method as described in claim 1 further comprising: prior to loading the virtual machine code into the common memory: running a first application program; in response to running the first application program, identifying a call to a software effect corresponding to the software code data; and loading the software code data into the common memory, wherein the processing of the software code data occurs during the running of the first application program and wherein the processing is completed prior to the first program calling the software effect. 4. The method as described in claim 3 further comprising: receiving, at the first processor, the executable instructions resulting from the processing performed by the second processor, wherein the executable instructions are adapted to perform a multimedia effect; and performing the multimedia effect on the first processor by executing the received executable instructions. | 0.5 |
7,985,243 | 1 | 8 | 1. An implant adapted to be implanted in a spine of a patient comprising: a shield with a shield cavity; a deflection rod that is mounted in said shield cavity; said deflection rod able to be deflected in said shield cavity and the motion of said deflection rod is limited by the shield cavity; a connector located at an end of said deflection rod; a rod connected to said connector; and a mount extending from said shield. | 1. An implant adapted to be implanted in a spine of a patient comprising: a shield with a shield cavity; a deflection rod that is mounted in said shield cavity; said deflection rod able to be deflected in said shield cavity and the motion of said deflection rod is limited by the shield cavity; a connector located at an end of said deflection rod; a rod connected to said connector; and a mount extending from said shield. 8. The implant of claim 1 wherein: said deflection rod has a first end and a second end with said first end fixed in said shield cavity; said deflection rod decreasing in size toward said second end; and said shield cavity increasing in size toward said second end of said deflection rod. | 0.538462 |
9,710,239 | 7 | 8 | 7. A software application lifecycle management platform computing device, comprising at least one processor and a memory coupled to the processor which is configured to execute programmed instructions comprising and stored in the memory to: obtain software application related data and one or more outcomes of prior corresponding software application deliveries from at least one of a knowledge repository or a learning repository based on the software application related data; generate a set of models based on the outcomes of the prior corresponding software application deliveries wherein the generating further comprises deriving a confidence level for each of the set of models, generating a search query based on the software application related data, and searching the knowledge repository for the outcomes of the prior corresponding software application deliveries based on the search query, wherein the searching is executed against the learning repository when there is no match in the knowledge repository; and output one or more options for selection based on the set of models along with the corresponding confidence level. | 7. A software application lifecycle management platform computing device, comprising at least one processor and a memory coupled to the processor which is configured to execute programmed instructions comprising and stored in the memory to: obtain software application related data and one or more outcomes of prior corresponding software application deliveries from at least one of a knowledge repository or a learning repository based on the software application related data; generate a set of models based on the outcomes of the prior corresponding software application deliveries wherein the generating further comprises deriving a confidence level for each of the set of models, generating a search query based on the software application related data, and searching the knowledge repository for the outcomes of the prior corresponding software application deliveries based on the search query, wherein the searching is executed against the learning repository when there is no match in the knowledge repository; and output one or more options for selection based on the set of models along with the corresponding confidence level. 8. The software application lifecycle management platform computing device of claim 7 , wherein the processor coupled to the memory is further configured to execute at least one additional programmed instruction to prompt a user to input a required outcome and a decision factor via a provided user interface, wherein the decision factor comprises a combination of input and desired output factors and requirement-to-requirement modeling, requirement-to-tasks modeling, requirement-to-test cases modeling, test cases-to-test cases modeling, or requirement-to-end-to-end solution modeling. | 0.5 |
8,788,476 | 18 | 19 | 18. The computer readable medium of claim 11 , wherein the trigger comprises a criterion which causes information of an observation to be provided to a guide to obtain a search result regarding the occurrence of the trigger. | 18. The computer readable medium of claim 11 , wherein the trigger comprises a criterion which causes information of an observation to be provided to a guide to obtain a search result regarding the occurrence of the trigger. 19. The computer readable medium of claim 18 , comprising: presenting an indicator of a resource for observing the trigger and a notification of an occurrence of the criterion to the guide when the criterion occurs; obtaining from the guide, selections of the indicator, a response and an advertisement when an action of the guide indicates that the trigger occurs based on the observation of the resource; and providing the response and the advertisement as a part of the search result. | 0.5 |
8,782,037 | 3 | 10 | 3. The method of claim 1 , wherein said analyzing said response according to said supervised training procedure comprises receiving a plurality of returned mark-up language documents, including the initial mark-up language document, and a relative rank of each returned mark-up language document; determining a relative rank of the initial mark-up language document with regard to said plurality of returned mark-up language documents; and analyzing at least one feature of the initial mark-up language document in comparison to said plurality of returned mark-up language documents and said relative rank of the initial mark-up language document. | 3. The method of claim 1 , wherein said analyzing said response according to said supervised training procedure comprises receiving a plurality of returned mark-up language documents, including the initial mark-up language document, and a relative rank of each returned mark-up language document; determining a relative rank of the initial mark-up language document with regard to said plurality of returned mark-up language documents; and analyzing at least one feature of the initial mark-up language document in comparison to said plurality of returned mark-up language documents and said relative rank of the initial mark-up language document. 10. The method of claim 3 wherein said metadata is selected from the group consisting of a mark-up tag and a description of a mark-up tag. | 0.763699 |
7,836,148 | 1 | 14 | 1. A method of dynamically generating a display page, comprising: using a processor to obtain an object tree comprising a plurality of hierarchically organized objects, each object containing data and methods for processing a corresponding definitional element of said display page; using the processor to modify said object tree at runtime; and using the processor to invoke said methods of the objects comprising the object tree as modified to generate, dynamically at runtime, a plurality of definitional statements, each definitional statement being associated with one or more definitional elements of said display page; wherein said methods for processing a corresponding definitional element of said display page comprise computer instructions which when executed generate said plurality of definitional statements; wherein said definitional statements comprise hypertext markup language (HTML) or other statements usable by a browser or other software to render the display page; and wherein the display page generated using the objects comprising the object tree as modified reflects the modification made to said object tree at runtime. | 1. A method of dynamically generating a display page, comprising: using a processor to obtain an object tree comprising a plurality of hierarchically organized objects, each object containing data and methods for processing a corresponding definitional element of said display page; using the processor to modify said object tree at runtime; and using the processor to invoke said methods of the objects comprising the object tree as modified to generate, dynamically at runtime, a plurality of definitional statements, each definitional statement being associated with one or more definitional elements of said display page; wherein said methods for processing a corresponding definitional element of said display page comprise computer instructions which when executed generate said plurality of definitional statements; wherein said definitional statements comprise hypertext markup language (HTML) or other statements usable by a browser or other software to render the display page; and wherein the display page generated using the objects comprising the object tree as modified reflects the modification made to said object tree at runtime. 14. The method of claim 1 , wherein obtaining the object tree comprises generating the object tree based at least in part on a template. | 0.824289 |
9,060,029 | 19 | 20 | 19. A data processing system, comprising: a processor; a memory accessible to the processor storing programs and data objects therein, the programs including a wizard, wherein execution of the programs cause the processor to perform the steps of: using the wizard for identifying properties of a target individual, comprising using a correlation processor to extract user identifiers from retrieved data items, and correlating the user identifiers from different web sites, thereby identifying properties of a target individual; building an initial social circle of the target individual by crawling a plurality of web sites from different social media providers to identify direct and indirect associations between users of the social media providers and the target individual, wherein the target individual has no direct connection with at least one of the social media providers; deriving references to the target individual from the direct and indirect associations; and compiling a dossier on the target individual from the references to the target individual. | 19. A data processing system, comprising: a processor; a memory accessible to the processor storing programs and data objects therein, the programs including a wizard, wherein execution of the programs cause the processor to perform the steps of: using the wizard for identifying properties of a target individual, comprising using a correlation processor to extract user identifiers from retrieved data items, and correlating the user identifiers from different web sites, thereby identifying properties of a target individual; building an initial social circle of the target individual by crawling a plurality of web sites from different social media providers to identify direct and indirect associations between users of the social media providers and the target individual, wherein the target individual has no direct connection with at least one of the social media providers; deriving references to the target individual from the direct and indirect associations; and compiling a dossier on the target individual from the references to the target individual. 20. The data processing system according to claim 19 , wherein execution of the programs cause the processor to perform the additional steps of: expanding the initial social circle by building respective new social circles having new associations by crawling the plurality of web sites; and deriving additional references to the target individual from the new associations in the new social circles. | 0.5 |
7,620,912 | 29 | 30 | 29. The system of claim 28 further comprising: means for deleting said associated behavior by visually deleting said at least one link line. | 29. The system of claim 28 further comprising: means for deleting said associated behavior by visually deleting said at least one link line. 30. The system of claim 29 further comprising: means for relocating the behavior relationship from said source object and said destination object to a different destination object through means for relocating at least one of said at least one link line to said different destination object. | 0.5 |
8,611,507 | 12 | 13 | 12. The system of claim 8 , wherein the operations further comprise, responsive to detecting the instruction, transmitting a communication. | 12. The system of claim 8 , wherein the operations further comprise, responsive to detecting the instruction, transmitting a communication. 13. The system of claim 12 , wherein the communication comprises a portion of the transcript. | 0.565421 |
8,140,362 | 16 | 17 | 16. A system for automatically processing dynamic first business rules in a content management system, comprising: a computer with a computer processor for processing dynamic first business rules; a business rule processing interface for authoring first business rules, and for receiving a set of first input data to which the first business rules apply; a business rule engine for configuring and managing the first business rules, and for mapping the first business rules to the first input data to identify the first business rules required by the first input data; the business rule engine further for creating a first set of the first business rules for testing the first input data for validity with respect to numeric and relationship categories; the business rule engine further for creating a second set of the first business rules for performing first operations on the first input data; the business rule engine further for creating a third set of the first business rules for initiating further action after an action has been taken to update a content management repository; the business rule engine further for checking integrity of the content management system based on a plurality of primary key and foreign key relationships; an inference engine using pattern matching for executing the first business rules in a specified order; a business rule processing connector for executing the identified first business rules against different backend data models, and for monitoring the first business rules to determine if a new business rule is introduced; and an outputting engine for outputting a reason for each of a plurality of results after applying one of the first business rules to the first input data, wherein the business rule engine performs file updates to reflect the new business rule, and executes the updated files. | 16. A system for automatically processing dynamic first business rules in a content management system, comprising: a computer with a computer processor for processing dynamic first business rules; a business rule processing interface for authoring first business rules, and for receiving a set of first input data to which the first business rules apply; a business rule engine for configuring and managing the first business rules, and for mapping the first business rules to the first input data to identify the first business rules required by the first input data; the business rule engine further for creating a first set of the first business rules for testing the first input data for validity with respect to numeric and relationship categories; the business rule engine further for creating a second set of the first business rules for performing first operations on the first input data; the business rule engine further for creating a third set of the first business rules for initiating further action after an action has been taken to update a content management repository; the business rule engine further for checking integrity of the content management system based on a plurality of primary key and foreign key relationships; an inference engine using pattern matching for executing the first business rules in a specified order; a business rule processing connector for executing the identified first business rules against different backend data models, and for monitoring the first business rules to determine if a new business rule is introduced; and an outputting engine for outputting a reason for each of a plurality of results after applying one of the first business rules to the first input data, wherein the business rule engine performs file updates to reflect the new business rule, and executes the updated files. 17. The system of claim 16 , wherein the business rule engine comprises a rule module and a rule engine. | 0.5 |
8,397,056 | 7 | 8 | 7. A computer-implemented method for providing a mashup, comprising: providing, in a processor, a mashup that performs an action on a resource included in the mashup; identifying an attribute of a user running the mashup to perform the action on the resource; and providing an access control, the mashup being associated to a permission artifact, the permission artifact specifying a principal and whether one of to permit and to prohibit the principal to take the action on the resource, wherein the access control is triggered only when the mashup attempts to perform the action on the resource, the access control (i) checks whether the attribute of the user running the mashup to perform the action is predefined as belonging to the principal specified in the permission artifact associated to the mashup, and then (ii) performs the one of to permit and to prohibit the action on the resource only when the attribute belongs to the principal, plural users that have a same single attribute belong to the principal when the same single attribute is defined as belonging to the principal, and the permission artifact further specifies: (i) the resource used by the mashup, and (ii) the action on the resource for which permission is needed. | 7. A computer-implemented method for providing a mashup, comprising: providing, in a processor, a mashup that performs an action on a resource included in the mashup; identifying an attribute of a user running the mashup to perform the action on the resource; and providing an access control, the mashup being associated to a permission artifact, the permission artifact specifying a principal and whether one of to permit and to prohibit the principal to take the action on the resource, wherein the access control is triggered only when the mashup attempts to perform the action on the resource, the access control (i) checks whether the attribute of the user running the mashup to perform the action is predefined as belonging to the principal specified in the permission artifact associated to the mashup, and then (ii) performs the one of to permit and to prohibit the action on the resource only when the attribute belongs to the principal, plural users that have a same single attribute belong to the principal when the same single attribute is defined as belonging to the principal, and the permission artifact further specifies: (i) the resource used by the mashup, and (ii) the action on the resource for which permission is needed. 8. The method of claim 7 , further comprising: changing whether the single attribute belongs to the principal, thereby changing whether one of to permit and to prohibit the action on the resource for all of the plural users that have the same single attribute. | 0.5 |
8,140,449 | 13 | 16 | 13. A computer-implemented method, comprising: identifying, by a processor, in a document of a plurality of documents, one or more textual sequences; identifying, by the processor, based on the one or more textual sequences, a presence of novel content in the document where the novel content includes content that does not occur in other documents of the plurality of documents; assigning, by the processor, a score to the document based on the identified novel content including each of the one or more textual sequences; and ranking, by the processor, the document among the plurality of documents based on the assigned score. | 13. A computer-implemented method, comprising: identifying, by a processor, in a document of a plurality of documents, one or more textual sequences; identifying, by the processor, based on the one or more textual sequences, a presence of novel content in the document where the novel content includes content that does not occur in other documents of the plurality of documents; assigning, by the processor, a score to the document based on the identified novel content including each of the one or more textual sequences; and ranking, by the processor, the document among the plurality of documents based on the assigned score. 16. The computer-implemented method of claim 13 , where identifying one or more textual sequences comprises: identifying one or more pairs of the one or more textual sequences that occur in close proximity to one another in the document. | 0.74295 |
9,971,995 | 1 | 3 | 1. A method comprising: for each of a plurality of e-mails contained in a first data repository, determining at least one score for the e-mail file, determining the at least one score comprising: determining whether the e-mail file contains at least one design element; responsive to determining that the e-mail file contains at least one design element, determining whether the design element is authored by a template developer; and determining whether the design element is a custom design element created specifically for a particular user; based on scores assigned to the plurality of e-mail files, automatically assigning, using a processor, a ranking to each of the plurality of e-mail files, the ranking assigned to each e-mail file indicating a priority of the e-mail file as a candidate for migration to a second data repository; based on the ranking assigned to each of the plurality of e-mail files, automatically identifying e-mail files having a ranking that at least meets a threshold value; responsive to automatically identifying e-mail files having the ranking that at least meets the threshold value, presenting to a user a selectable user interface element; and responsive to the user selecting the user interface element, automatically initiating migration of the e-mail files having the ranking that at least meets the threshold value to the second data repository. | 1. A method comprising: for each of a plurality of e-mails contained in a first data repository, determining at least one score for the e-mail file, determining the at least one score comprising: determining whether the e-mail file contains at least one design element; responsive to determining that the e-mail file contains at least one design element, determining whether the design element is authored by a template developer; and determining whether the design element is a custom design element created specifically for a particular user; based on scores assigned to the plurality of e-mail files, automatically assigning, using a processor, a ranking to each of the plurality of e-mail files, the ranking assigned to each e-mail file indicating a priority of the e-mail file as a candidate for migration to a second data repository; based on the ranking assigned to each of the plurality of e-mail files, automatically identifying e-mail files having a ranking that at least meets a threshold value; responsive to automatically identifying e-mail files having the ranking that at least meets the threshold value, presenting to a user a selectable user interface element; and responsive to the user selecting the user interface element, automatically initiating migration of the e-mail files having the ranking that at least meets the threshold value to the second data repository. 3. The method of claim 1 , wherein determining the at least one score further comprises determining a type of the design element and determining the score for the e-mail file based, at least in part, on the determined type of the design element. | 0.705529 |
9,165,554 | 15 | 16 | 15. The system of claim 10 , wherein the phonotactic grammar is an N-gram phonotactic grammar. | 15. The system of claim 10 , wherein the phonotactic grammar is an N-gram phonotactic grammar. 16. The system of claim 15 , wherein the N-gram phonotactic grammar is unsmoothed, recognizing only N-grams which have been seen in data used to train the N-gram phonotactic grammar. | 0.5 |
9,443,139 | 1 | 5 | 1. A method of obtaining information of interest from a binarized document, the method comprising: storing information associating a plurality of different label aliases with a first label for first information of interest; storing in a nodal structure, information representing an expected relationship between objects of a first label alias in said plurality of different label aliases, individual objects of said first label alias being linked in said nodal structure to other objects, each of the linked objects being a character or character string, individual links in said nodal structure having a probability associated with the individual link; scoring a first portion of the binarized document against said nodal structure to determine scores for multiple label aliases; determining based on said generated scores if said first label alias is present in said first portion of the binarized document; and in response to determining that said first label alias is present in said first portion of the binarized document, extracting information from the first portion document corresponding to said first label alias. | 1. A method of obtaining information of interest from a binarized document, the method comprising: storing information associating a plurality of different label aliases with a first label for first information of interest; storing in a nodal structure, information representing an expected relationship between objects of a first label alias in said plurality of different label aliases, individual objects of said first label alias being linked in said nodal structure to other objects, each of the linked objects being a character or character string, individual links in said nodal structure having a probability associated with the individual link; scoring a first portion of the binarized document against said nodal structure to determine scores for multiple label aliases; determining based on said generated scores if said first label alias is present in said first portion of the binarized document; and in response to determining that said first label alias is present in said first portion of the binarized document, extracting information from the first portion document corresponding to said first label alias. 5. The method of claim 1 , wherein the links in said nodal structure correspond to candidate object sequences. | 0.864865 |
7,920,742 | 12 | 13 | 12. An image processing method to enable a computer to perform a process for document registration processing, the process comprising: inputting document data of a document; identifying a position of a string in the document; identifying a mark handwritten from a highlighter and is non-textual, the mark being separate from the string, given in the document; and detecting an orientation of the mark, wherein the mark is defined by a range from a start position and an end position based on the detected orientation, and extracting a new character string based on the position of the identified string and the identified mark, and the mark identified and defined based on the detected orientation. | 12. An image processing method to enable a computer to perform a process for document registration processing, the process comprising: inputting document data of a document; identifying a position of a string in the document; identifying a mark handwritten from a highlighter and is non-textual, the mark being separate from the string, given in the document; and detecting an orientation of the mark, wherein the mark is defined by a range from a start position and an end position based on the detected orientation, and extracting a new character string based on the position of the identified string and the identified mark, and the mark identified and defined based on the detected orientation. 13. The image processing method of claim 12 , further comprising: extracting the string based on the identified position and whether the string overlaps the identified mark. | 0.5 |
8,458,154 | 1 | 3 | 1. A method to analyze electronic messages, the method comprising: sorting a set of messages based on a set of probabilities, the set of probabilities indicating a likelihood that the set of messages belong to a first classification; assigning a first subset of first consecutive ones of the sorted set of messages to a first bucket; assigning a second subset of second consecutive ones of the sorted set of messages to a second bucket, wherein a first message of the second subset of messages is consecutive to a last message of the first subset of messages with reference to the set of probabilities; determining a mean of probabilities of the first subset of messages assigned to the first bucket; storing the mean in a tangible memory; and storing, for respective ones of the messages assigned to the first bucket, an indication that the respective message is assigned to the first bucket in the tangible memory, wherein storing the mean in a tangible memory further comprises: moving a boundary between the first bucket and the second bucket; recalculating the mean of probabilities of messages assigned to the first bucket in response to moving the boundary; repeatedly (1) moving the boundary and (2) recalculating the mean until deviations of the probabilities within the first bucket with respect to the mean are equal to or less than a threshold; and storing a last recalculated mean as representative of the first bucket. | 1. A method to analyze electronic messages, the method comprising: sorting a set of messages based on a set of probabilities, the set of probabilities indicating a likelihood that the set of messages belong to a first classification; assigning a first subset of first consecutive ones of the sorted set of messages to a first bucket; assigning a second subset of second consecutive ones of the sorted set of messages to a second bucket, wherein a first message of the second subset of messages is consecutive to a last message of the first subset of messages with reference to the set of probabilities; determining a mean of probabilities of the first subset of messages assigned to the first bucket; storing the mean in a tangible memory; and storing, for respective ones of the messages assigned to the first bucket, an indication that the respective message is assigned to the first bucket in the tangible memory, wherein storing the mean in a tangible memory further comprises: moving a boundary between the first bucket and the second bucket; recalculating the mean of probabilities of messages assigned to the first bucket in response to moving the boundary; repeatedly (1) moving the boundary and (2) recalculating the mean until deviations of the probabilities within the first bucket with respect to the mean are equal to or less than a threshold; and storing a last recalculated mean as representative of the first bucket. 3. The method as defined in claim 1 , wherein the mean is stored in the tangible memory in a first data structure associating an identifier for the first bucket with the mean and wherein the set of messages are stored in the tangible memory in a second data structure different from the first data structure, the second data structure associating one of the messages in the set of messages with an identifier for the first bucket. | 0.5 |
8,689,101 | 1 | 4 | 1. A method comprising: (i) for each of a plurality of client devices, storing a corresponding client profile at a server, each corresponding client profile comprising a font capabilities list for a respective one of the plurality of client devices, each font capabilities list comprising a list of fonts for which the respective client device has font structure data stored in a client font data store of the respective client device, the font structure data defining the structure in which text formatted with the respective font is to be rendered on the respective client device; (ii) receiving an electronic data transfer at the server, addressed to a designated one of the plurality of client devices, the electronic data transfer comprising text data and one or more font identifiers identifying one or more fonts to use to render the text data on the designated one of the plurality of client devices; (iii) comparing the one or more font identifiers in the electronic data transfer with a current version of the fonts in the capabilities list stored by the server for the designated device, to determine fonts in the electronic data transfer for which the designated device lacks font structure data; (iv) transferring, from the server to the designated device, the font structure data of the fonts determined to be lacked by the designated device and the text data, wherein the font structure data lacked by the designated device and the text data are included in the same electronic data transfer, and wherein the designated device stores the received font structure data in the client font data store; and (v) updating the font capabilities list stored by the server for the designated device to include, in a new version of the font capabilities list, the fonts whose font structure data are transferred to the designated device. | 1. A method comprising: (i) for each of a plurality of client devices, storing a corresponding client profile at a server, each corresponding client profile comprising a font capabilities list for a respective one of the plurality of client devices, each font capabilities list comprising a list of fonts for which the respective client device has font structure data stored in a client font data store of the respective client device, the font structure data defining the structure in which text formatted with the respective font is to be rendered on the respective client device; (ii) receiving an electronic data transfer at the server, addressed to a designated one of the plurality of client devices, the electronic data transfer comprising text data and one or more font identifiers identifying one or more fonts to use to render the text data on the designated one of the plurality of client devices; (iii) comparing the one or more font identifiers in the electronic data transfer with a current version of the fonts in the capabilities list stored by the server for the designated device, to determine fonts in the electronic data transfer for which the designated device lacks font structure data; (iv) transferring, from the server to the designated device, the font structure data of the fonts determined to be lacked by the designated device and the text data, wherein the font structure data lacked by the designated device and the text data are included in the same electronic data transfer, and wherein the designated device stores the received font structure data in the client font data store; and (v) updating the font capabilities list stored by the server for the designated device to include, in a new version of the font capabilities list, the fonts whose font structure data are transferred to the designated device. 4. The method of claim 1 further comprising between steps iii and iv: determining whether another font identifier exists that is the same as the font identifier for which font structure data is lacking. | 0.798403 |
8,694,540 | 2 | 3 | 2. The computer-implemented method of claim 1 , further comprising: applying at least one of the identified predictive models to the database table to obtain one or more predicted values; and adding the one or more predicted values to the database table. | 2. The computer-implemented method of claim 1 , further comprising: applying at least one of the identified predictive models to the database table to obtain one or more predicted values; and adding the one or more predicted values to the database table. 3. The computer-implemented method of claim 2 , wherein adding the one or more predicted values to the database table comprises replacing a missing column value in the database table. | 0.593333 |
8,090,722 | 5 | 6 | 5. The non-transitory computer-readable medium of claim 3 , where determining the relevance of the expanded document includes, upon determining that two or more query terms appear in the expanded document, computing a nearness value for the two or more terms. | 5. The non-transitory computer-readable medium of claim 3 , where determining the relevance of the expanded document includes, upon determining that two or more query terms appear in the expanded document, computing a nearness value for the two or more terms. 6. The non-transitory computer-readable medium of claim 5 , including, upon determining that a first query term appears in a first document included in the expanded document and that a second query term appears in a second document included in the expanded document, updating the nearness value with a document size. | 0.5 |
9,888,086 | 1 | 4 | 1. A method comprising: receiving a request to disassociate with a first topic from a first user; identifying one or more entity representations associated with the first topic; retrieving data describing content items associated with the first topic; identifying an existing label, an estimated label and one or more refined topics associated with the first topic; determining a first occurrence pattern for the existing label based on a first number of the content items that are associated with the first topic and are marked with the existing label; determining a second occurrence pattern for the estimated label based on a second number of the content items that are associated with the first topic and are estimated to be associated with the estimated label; identifying a plurality of second users that connects the first user in a social graph and also shares the first topic as a common interest with the first user; determining an association pattern for the first topic based on how the identified plurality of second users associate or disassociate with the first topic; determining a topic structure that includes one or more from the group of: the existing label, the estimated label, the one or more refined topics, the one or more entity representations, one or more keywords, one or more confidence scores for one or more labels and one or more links to one or more associated objects; and determining an association recommendation relevant to the first user from the one or more refined topics, the first occurrence pattern and the second occurrence pattern based on the determined association pattern and the determined topic structure. | 1. A method comprising: receiving a request to disassociate with a first topic from a first user; identifying one or more entity representations associated with the first topic; retrieving data describing content items associated with the first topic; identifying an existing label, an estimated label and one or more refined topics associated with the first topic; determining a first occurrence pattern for the existing label based on a first number of the content items that are associated with the first topic and are marked with the existing label; determining a second occurrence pattern for the estimated label based on a second number of the content items that are associated with the first topic and are estimated to be associated with the estimated label; identifying a plurality of second users that connects the first user in a social graph and also shares the first topic as a common interest with the first user; determining an association pattern for the first topic based on how the identified plurality of second users associate or disassociate with the first topic; determining a topic structure that includes one or more from the group of: the existing label, the estimated label, the one or more refined topics, the one or more entity representations, one or more keywords, one or more confidence scores for one or more labels and one or more links to one or more associated objects; and determining an association recommendation relevant to the first user from the one or more refined topics, the first occurrence pattern and the second occurrence pattern based on the determined association pattern and the determined topic structure. 4. The method of claim 1 , further comprising: receiving data describing a selection of the association recommendation from the first user; and creating an association between the first user and the association recommendation. | 0.597865 |
9,600,806 | 74 | 76 | 74. A non-transitory computer readable medium encoded with a computer program including instructions to cause a processor to: analyze electronic messages of a first user with respect to one or more features associated with the electronic messages; associate descriptive tags with the electronic messages of the first user based on analysis results; and perform tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages, including to organize the electronic messages of the first user into a first organization based on metadata associated with the electronic messages and contents of the electronic messages, and present a first body of information associated with the electronic messages through a graphical user interface in accordance with the first organization. | 74. A non-transitory computer readable medium encoded with a computer program including instructions to cause a processor to: analyze electronic messages of a first user with respect to one or more features associated with the electronic messages; associate descriptive tags with the electronic messages of the first user based on analysis results; and perform tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages, including to organize the electronic messages of the first user into a first organization based on metadata associated with the electronic messages and contents of the electronic messages, and present a first body of information associated with the electronic messages through a graphical user interface in accordance with the first organization. 76. The non-transitory computer readable medium of claim 74 , further including instructions to cause the processor to: present the first and second bodies of information under corresponding first and second tabs of the graphical user interface. | 0.689873 |
8,205,263 | 2 | 5 | 2. The method of claim 1 , further comprising processing the unverified executable file according to an unverified file policy if the file is identified as being obfuscated by an unknown obfuscator program. | 2. The method of claim 1 , further comprising processing the unverified executable file according to an unverified file policy if the file is identified as being obfuscated by an unknown obfuscator program. 5. The method of claim 2 , wherein the unverified file policy comprises instructions to block the execution of the unverified executable file. | 0.596591 |
9,990,436 | 8 | 11 | 8. An information processing system, comprising: a processor device comprising hardware; and a memory operably coupled with the processor device, the memory comprising computer-executable instructions causing a computer to perform acts of: determining first trending topics associated with a user; receiving, via a first network communication, an in-stream feed of second trending topics based on on-line activity of the user; augmenting a social timeline associated with the user with at least one of the second trending topics to produce an interim list of third trending topics, wherein the social timeline is produced by logging content, retrieved via a second network communication, posted on one or more accounts of the user, wherein recently posted content on the social timeline corresponds to a summary of the first trending topics; ranking the third trending topics using a frequency index; selecting a subset of highest ranked third trending topics; and controlling a graphical user interface on a computer display to display a personalized trends module highlighting at least some of the subset of the highest ranked third trending topics to distinguish at least some of the subset of the highest ranked third trending topics from one or more other topics by allocating one or more positions to at least some of the subset of the highest ranked third trending topics to customize an online experience of the user with customized trending topics. | 8. An information processing system, comprising: a processor device comprising hardware; and a memory operably coupled with the processor device, the memory comprising computer-executable instructions causing a computer to perform acts of: determining first trending topics associated with a user; receiving, via a first network communication, an in-stream feed of second trending topics based on on-line activity of the user; augmenting a social timeline associated with the user with at least one of the second trending topics to produce an interim list of third trending topics, wherein the social timeline is produced by logging content, retrieved via a second network communication, posted on one or more accounts of the user, wherein recently posted content on the social timeline corresponds to a summary of the first trending topics; ranking the third trending topics using a frequency index; selecting a subset of highest ranked third trending topics; and controlling a graphical user interface on a computer display to display a personalized trends module highlighting at least some of the subset of the highest ranked third trending topics to distinguish at least some of the subset of the highest ranked third trending topics from one or more other topics by allocating one or more positions to at least some of the subset of the highest ranked third trending topics to customize an online experience of the user with customized trending topics. 11. The information processing system of claim 8 wherein the computer-executable instructions further comprise instructions for: presenting an identifier of the user in the personalized trends module. | 0.776286 |
8,041,559 | 3 | 4 | 3. The method according to claim 2 wherein the step of generating a domain specific lexicon based on a diacritized training corpus pertaining to a specific domain, comprises the further steps of: keeping in the generic lexicon: stems that have the highest number of morphological variants identified in the diacritized training corpus, when multiple stems with identical character sequences exist; stems that have no other identical sequence of characters; any stem randomly selected among stems that: are not related to words in the diacritized training corpus, and have multiple identical character sequences, deleting from the generic lexicon all other stems and therefore generating a domain specific lexicon from the generic lexicon. | 3. The method according to claim 2 wherein the step of generating a domain specific lexicon based on a diacritized training corpus pertaining to a specific domain, comprises the further steps of: keeping in the generic lexicon: stems that have the highest number of morphological variants identified in the diacritized training corpus, when multiple stems with identical character sequences exist; stems that have no other identical sequence of characters; any stem randomly selected among stems that: are not related to words in the diacritized training corpus, and have multiple identical character sequences, deleting from the generic lexicon all other stems and therefore generating a domain specific lexicon from the generic lexicon. 4. The method according to claim 3 wherein the step of disambiguating non diacritized words in a text and restoring vowels, comprises the further steps of: for each word in the non diacritized text: segmenting the word into a stem, and affixes if any; disambiguating the word using the domain specific lexicon, said domain specific lexicon comprising a unique vowelization pattern for each stem; determining the vowelization pattern of the stem; diacritizing the word by concatenating the diacritized stem with diacritized affixes if any. | 0.5 |
7,519,588 | 1 | 3 | 1. A method comprising: receiving, by a computing device, a first collection of documents and/or objects determined by a first process to be relevant to a keyword, wherein the first process comprises searching a multiplicity of documents and/or objects; processing, by the computing device, the first collection of documents and/or objects to extract one or more keyword characterizations from within at least one of the documents and/or objects of the first collection, wherein the processing comprises generating, by the computing device, a spectrum of n-grams to characterize the one or more keywords, where n is an integer equal to or greater than 1; and receiving, by the computing device, a second collection of documents and/or objects determined by a second process to be relevant to the one or more keyword characterizations, wherein the second process comprises using at least one of the one or more keyword characterizations as proxies for the keyword. | 1. A method comprising: receiving, by a computing device, a first collection of documents and/or objects determined by a first process to be relevant to a keyword, wherein the first process comprises searching a multiplicity of documents and/or objects; processing, by the computing device, the first collection of documents and/or objects to extract one or more keyword characterizations from within at least one of the documents and/or objects of the first collection, wherein the processing comprises generating, by the computing device, a spectrum of n-grams to characterize the one or more keywords, where n is an integer equal to or greater than 1; and receiving, by the computing device, a second collection of documents and/or objects determined by a second process to be relevant to the one or more keyword characterizations, wherein the second process comprises using at least one of the one or more keyword characterizations as proxies for the keyword. 3. The method of claim 1 , wherein a selected one of the first and the second collection of documents and/or objects comprises at least one of: web pages determined to be potentially relevant to the keyword, documents from an electronic information corpus, and data objects including at least one of images, video files, audio files, executable applications, and abstractions of physical objects. | 0.785482 |
8,423,352 | 1 | 4 | 1. A computer implemented method for enhancing language detection in short communications, comprising: storing a short communication in an element of a line cache accessible to an application executing in a data processing system, the element being an element in a set of elements in the line cache; assembling a compound text from contents of a subset of the elements of the line cache; receiving a language identifier (language ID) for the compound text from a language detection algorithm; storing the language ID in a language cache element of a language ID cache accessible to the application, the language ID cache including a set of language cache elements; and determining, using contents of a subset of language cache elements, a language of the short communication. | 1. A computer implemented method for enhancing language detection in short communications, comprising: storing a short communication in an element of a line cache accessible to an application executing in a data processing system, the element being an element in a set of elements in the line cache; assembling a compound text from contents of a subset of the elements of the line cache; receiving a language identifier (language ID) for the compound text from a language detection algorithm; storing the language ID in a language cache element of a language ID cache accessible to the application, the language ID cache including a set of language cache elements; and determining, using contents of a subset of language cache elements, a language of the short communication. 4. The computer implemented method of claim 1 , further comprising: determining whether the line cache has an available element to store the short communication; and responsive to no available elements, clearing a second element in the line cache to store the short communication. | 0.822109 |
9,786,296 | 22 | 23 | 22. The electronic device of claim 15 , wherein the download management unit is configured to receive, via the communication network, an application file, wherein the application file includes the keyword data file, and further comprising an extracting unit configured to extract the keyword data file from the application file, wherein the keyword setting unit is configured to assign the particular target keyword to the application file for activating the application in response to detecting the particular target keyword in the input sound based on the keyword model. | 22. The electronic device of claim 15 , wherein the download management unit is configured to receive, via the communication network, an application file, wherein the application file includes the keyword data file, and further comprising an extracting unit configured to extract the keyword data file from the application file, wherein the keyword setting unit is configured to assign the particular target keyword to the application file for activating the application in response to detecting the particular target keyword in the input sound based on the keyword model. 23. The electronic device of claim 22 , further comprising: a sound sensor configured to receive the input sound; a keyword detection unit configured to detect whether the particular target keyword is included in the input sound based on the keyword model; and a function management unit configured to activate the application in response to detecting the particular target keyword is included in the input sound. | 0.5 |
9,141,690 | 13 | 18 | 13. An article of manufacture comprising a computer readable storage medium having content stored thereon, which when executed, cause a machine to perform operations including: receiving a query at a multitenant database system (MTS), wherein the MTS stores data for multiple client organizations each identified by a tenant identifier (ID) and one or more users are associated with the tenant ID, wherein the one or more users of each client organization access data identified by the tenant ID associated with the respective client organization, and wherein the multitenant database is hosted by an entity separate from the client organization; categorizing the semantic terms of the query into one or more categories based on a multidimensional categorization scheme stored in the MTS, the multidimensional categorization scheme associated with a tenant ID of a user that originated the query; accessing relationship metadata of records in the MTS previously categorized into one or more of the same categories as the query, including accessing first and second relationship types, wherein: the first relationship type metadata indicate a record relationship between one record in the MTS to another record in the MTS, and the second relationship type metadata indicate a category relationship between one of the categories of the one record in the MTS and other available categories of the multidimensional categorization scheme associated with the user's tenant ID, the category relationship based on a previously determined statistical similarity of the categories; retrieving records from the MTS: previously categorized into one or more of the same categories as the query, having record relationships with any of the already retrieved records, and previously categorized in a category having category relationships with one or more categories of any of the already retrieved records; computing a statistical likelihood that each retrieved record is a desired solution to the query meriting inclusion in a result set for the query, the statistical likelihood computed based on usage statistics accumulated for each retrieved record, including usage statistics accumulate for the record relationships and category relationships to other retrieved records; monitoring usage of the result set, including whether and for how long a record included in the result set is used, with greater usage associated with solutions of greater desirability and lesser usage associated with solutions of lesser desirability; and updating usage statistics indicating statistical similarity of records based on usage of the result set, including weighting more heavily records, record relationships and category relationships identified as being a desired solution to the query. | 13. An article of manufacture comprising a computer readable storage medium having content stored thereon, which when executed, cause a machine to perform operations including: receiving a query at a multitenant database system (MTS), wherein the MTS stores data for multiple client organizations each identified by a tenant identifier (ID) and one or more users are associated with the tenant ID, wherein the one or more users of each client organization access data identified by the tenant ID associated with the respective client organization, and wherein the multitenant database is hosted by an entity separate from the client organization; categorizing the semantic terms of the query into one or more categories based on a multidimensional categorization scheme stored in the MTS, the multidimensional categorization scheme associated with a tenant ID of a user that originated the query; accessing relationship metadata of records in the MTS previously categorized into one or more of the same categories as the query, including accessing first and second relationship types, wherein: the first relationship type metadata indicate a record relationship between one record in the MTS to another record in the MTS, and the second relationship type metadata indicate a category relationship between one of the categories of the one record in the MTS and other available categories of the multidimensional categorization scheme associated with the user's tenant ID, the category relationship based on a previously determined statistical similarity of the categories; retrieving records from the MTS: previously categorized into one or more of the same categories as the query, having record relationships with any of the already retrieved records, and previously categorized in a category having category relationships with one or more categories of any of the already retrieved records; computing a statistical likelihood that each retrieved record is a desired solution to the query meriting inclusion in a result set for the query, the statistical likelihood computed based on usage statistics accumulated for each retrieved record, including usage statistics accumulate for the record relationships and category relationships to other retrieved records; monitoring usage of the result set, including whether and for how long a record included in the result set is used, with greater usage associated with solutions of greater desirability and lesser usage associated with solutions of lesser desirability; and updating usage statistics indicating statistical similarity of records based on usage of the result set, including weighting more heavily records, record relationships and category relationships identified as being a desired solution to the query. 18. The article of manufacture of claim 13 , further comprising content to provide instructions for sending the query to a human agent if none of the retrieved records is used as a solution to the query; and updating the statistics responsive to a solution provided by the human agent. | 0.603064 |
9,607,216 | 9 | 10 | 9. A computer program product for analyzing an image, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to a document that includes (i) at least one image and (ii) unstructured text that is situated proximate to the image, wherein both the image and the unstructured text are concurrently displayed in the document; program instructions to one or more potential locations depicted in the image included in the identified document, based on an analysis of the unstructured text that is situated proximate to the image; program instructions to identify a set of images of a first potential location from the identified one or more potential locations; responsive to determining that an image in the set of images of the first potential location substantially matches the image included in the identified document, program instructions to determine that the location depicted in the image that substantially matches the image included in the identified document is the location depicted in the image included in the identified document; program instructions to identify an updated image that includes the location depicted in the image included in the identified document, wherein the updated image is associated with a date that is more recent than a date associated with the image included in the identified document; and program instructions to initiate display of the identified updated image within the identified document. | 9. A computer program product for analyzing an image, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to a document that includes (i) at least one image and (ii) unstructured text that is situated proximate to the image, wherein both the image and the unstructured text are concurrently displayed in the document; program instructions to one or more potential locations depicted in the image included in the identified document, based on an analysis of the unstructured text that is situated proximate to the image; program instructions to identify a set of images of a first potential location from the identified one or more potential locations; responsive to determining that an image in the set of images of the first potential location substantially matches the image included in the identified document, program instructions to determine that the location depicted in the image that substantially matches the image included in the identified document is the location depicted in the image included in the identified document; program instructions to identify an updated image that includes the location depicted in the image included in the identified document, wherein the updated image is associated with a date that is more recent than a date associated with the image included in the identified document; and program instructions to initiate display of the identified updated image within the identified document. 10. The computer program product of claim 9 , wherein identifying the updated image that includes the location depicted in the image included in the identified document further comprises: responsive to determining that an image in the set of images of the first potential location substantially matches the image included in the identified document, identify a set of tagged images that are tagged with metadata indicating location information that corresponds to metadata associated with the determined matching image in the set of images of the first potential location; and determine an updated image of the image included in the identified document from the identified set of tagged images, wherein the determined updated image is the image of the identified set of tagged images that includes metadata indicating a most recent date. | 0.5 |
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