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10. One or more non-transitory computer-readable media storing executable instructions that, when executed by a processor, cause a device to: receive a sequence of speech features that characterize an unknown speech input, the sequence of speech features including speech portions and non-speech portions; determine, using voice activity detection (VAD), the speech portions of the sequence of speech features; determine a mean C 0 value for the sequence of speech features, wherein C 0 comprises an average log-energy of a given speech frame of the sequence of speech features, normalize selected speech features of the sequence of speech features using a plurality of different feature normalizing functions including a first function used only for the speech portions and a second function used only for the non-speech portions, wherein the first function normalizes the C 0 by subtracting a max C 0 that is estimated at a start of an utterance including the given speech frame and subsequently updated throughout the utterance; and combine the normalized selected speech features to produce a sequence of mixed normalized speech features for automatic speech recognition of the speech portions of the sequence of speech features. | 10. One or more non-transitory computer-readable media storing executable instructions that, when executed by a processor, cause a device to: receive a sequence of speech features that characterize an unknown speech input, the sequence of speech features including speech portions and non-speech portions; determine, using voice activity detection (VAD), the speech portions of the sequence of speech features; determine a mean C 0 value for the sequence of speech features, wherein C 0 comprises an average log-energy of a given speech frame of the sequence of speech features, normalize selected speech features of the sequence of speech features using a plurality of different feature normalizing functions including a first function used only for the speech portions and a second function used only for the non-speech portions, wherein the first function normalizes the C 0 by subtracting a max C 0 that is estimated at a start of an utterance including the given speech frame and subsequently updated throughout the utterance; and combine the normalized selected speech features to produce a sequence of mixed normalized speech features for automatic speech recognition of the speech portions of the sequence of speech features. 16. The non-transitory computer-readable media of claim 10 , wherein the normalized selected speech features are combined using linear discriminant analysis (LDA) to produce the sequence of mixed normalized speech features. | 0.798561 |
1. An apparatus, comprising least one processor and at least one memory including computer program code, the memory and the computer program code configured to, working with the processor, cause the apparatus to perform at least the following: receive a multiple touch input comprising a first touch input having a first text position within a first word such that the first text position is a text position between a first character of the first word and a last letter of the first word, and a second touch input having a second text position such that the second text position is a text position between a first character of a second word and a last letter of the second word; determine a first text selection point positioned outside of the first word based at least in part on the first text position being within the first word, such that the first text selection point is at least one of a text position preceding a first character of the first word, or a text position following a last letter of the first word; determine a second text selection point positioned outside of the second word based at least in part on the second text position, such that the second text selection point is at least one of a text position preceding a first character of the second word, or a text position following a last letter of the second word; and select text information between the first text selection point and the second text selection point. | 1. An apparatus, comprising least one processor and at least one memory including computer program code, the memory and the computer program code configured to, working with the processor, cause the apparatus to perform at least the following: receive a multiple touch input comprising a first touch input having a first text position within a first word such that the first text position is a text position between a first character of the first word and a last letter of the first word, and a second touch input having a second text position such that the second text position is a text position between a first character of a second word and a last letter of the second word; determine a first text selection point positioned outside of the first word based at least in part on the first text position being within the first word, such that the first text selection point is at least one of a text position preceding a first character of the first word, or a text position following a last letter of the first word; determine a second text selection point positioned outside of the second word based at least in part on the second text position, such that the second text selection point is at least one of a text position preceding a first character of the second word, or a text position following a last letter of the second word; and select text information between the first text selection point and the second text selection point. 15. The apparatus of claim 1 , wherein the memory includes computer program code configured to, working with the processor, cause the apparatus to: receive a change in the first touch input to a third text position such that the third text position is a text position between a first character of a third word and a last letter of the third word; determine a third text selection point positioned outside of the third word based at least in part on the third text position being within the third word, such that the third text selection point is at least one of a text position preceding a first character of the third word, or a text position following a last letter of the third word; and select text information between the third text selection point and the second text selection point. | 0.5 |
9. The apparatus of claim 8 further comprising a user interface in communication with said processor for delivering proximately each particular first marker audio data with corresponding second marker text on said user interface. | 9. The apparatus of claim 8 further comprising a user interface in communication with said processor for delivering proximately each particular first marker audio data with corresponding second marker text on said user interface. 11. The apparatus of claim 9 wherein each first marker audio data is delivered on said user interface as a selectable connection which when selected will enable said processor to deliver to said user interface corresponding said second marker text. | 0.876717 |
1. A non-transitory computer readable medium having computer executable instructions for performing a method of processing expense information, the method comprising: receiving scanned information of a receipt from a scanner, the scanned information including information regarding various types of receipts having various formats and having different sizes, each of said receipts containing expense information printed thereon; processing said scanned information including numerical data in the receipt to obtain said expense information from said scanned information; categorizing said expense information for each receipt into one or more predetermined categories to obtain categorized information for each receipt, wherein said categorized information for each receipt is combined with categorized information for other said receipts to produce report information for one or more of said predetermined categories, wherein the various types of receipts include grocery receipts, purchase receipts, credit card receipts and bank statements. | 1. A non-transitory computer readable medium having computer executable instructions for performing a method of processing expense information, the method comprising: receiving scanned information of a receipt from a scanner, the scanned information including information regarding various types of receipts having various formats and having different sizes, each of said receipts containing expense information printed thereon; processing said scanned information including numerical data in the receipt to obtain said expense information from said scanned information; categorizing said expense information for each receipt into one or more predetermined categories to obtain categorized information for each receipt, wherein said categorized information for each receipt is combined with categorized information for other said receipts to produce report information for one or more of said predetermined categories, wherein the various types of receipts include grocery receipts, purchase receipts, credit card receipts and bank statements. 3. A non-transitory computer readable medium as claimed in claim 1 , wherein the scanned information from the scanned receipts is automatically received from the scanner, and the expense information for each receipt is captured from the scanned information for each receipt and categorized into one or more of said predetermined categories. | 0.5 |
1. A method comprising: identifying, by one or more devices, documents relating to a query; generating, by the one or more devices, a plurality of substrings from the query; calculating, by the one or more devices and for a particular substring of the plurality of substrings, a value that corresponds to a comparison between the identified documents and the particular substring; determining, by the one or more devices, that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; selecting, by the one or more devices and from two or more of the plurality of substrings, the particular substring as a semantic unit based on the calculated value for the particular substring satisfying the particular threshold; and obtaining, by the one or more devices, a refined list of documents by refining the identified documents based on the semantic unit. | 1. A method comprising: identifying, by one or more devices, documents relating to a query; generating, by the one or more devices, a plurality of substrings from the query; calculating, by the one or more devices and for a particular substring of the plurality of substrings, a value that corresponds to a comparison between the identified documents and the particular substring; determining, by the one or more devices, that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; selecting, by the one or more devices and from two or more of the plurality of substrings, the particular substring as a semantic unit based on the calculated value for the particular substring satisfying the particular threshold; and obtaining, by the one or more devices, a refined list of documents by refining the identified documents based on the semantic unit. 2. The method of claim 1 , where identifying the documents includes: generating an initial list of relevant documents; and selecting a predetermined number of documents, in the initial list of relevant documents, as the identified documents. | 0.656947 |
1. A method of making optimal medical decisions, comprising: (a) collecting a medical evidence about a patient comprising standardized medical facts, (b) providing a model of the evidence linking said medical evidence with a set of probable current states of the disease, (c) providing a model of the progression of the disease linking each of said probable current states of the disease with a set of probable future states of the disease, (d) providing a model of the progression of the disease linking probable current states of the disease with the probable future states of the disease for a plurality of medical decisions, (e) providing a model of costs and benefits associating a set of probable costs and benefits along with their probabilities for each of said probable current states of the disease, and for each of said probable future states of the disease, (f) providing a preference function of costs and benefits outputting a utility value for a combination of costs and benefits approximately reflecting real individual preferences of said combination of costs and benefits, (g) generating an expected utility value by summing the values of said preference function of costs and benefits weighted with probabilities of costs and benefits for each of said medical decisions, (h) selecting a resulting medical decision having the largest expected utility value, whereby said medical decision will be approximately optimal with respect to the expected progression of the disease, and with respect to costs and benefits, and with respect to individual preferences. | 1. A method of making optimal medical decisions, comprising: (a) collecting a medical evidence about a patient comprising standardized medical facts, (b) providing a model of the evidence linking said medical evidence with a set of probable current states of the disease, (c) providing a model of the progression of the disease linking each of said probable current states of the disease with a set of probable future states of the disease, (d) providing a model of the progression of the disease linking probable current states of the disease with the probable future states of the disease for a plurality of medical decisions, (e) providing a model of costs and benefits associating a set of probable costs and benefits along with their probabilities for each of said probable current states of the disease, and for each of said probable future states of the disease, (f) providing a preference function of costs and benefits outputting a utility value for a combination of costs and benefits approximately reflecting real individual preferences of said combination of costs and benefits, (g) generating an expected utility value by summing the values of said preference function of costs and benefits weighted with probabilities of costs and benefits for each of said medical decisions, (h) selecting a resulting medical decision having the largest expected utility value, whereby said medical decision will be approximately optimal with respect to the expected progression of the disease, and with respect to costs and benefits, and with respect to individual preferences. 7. The method of making optimal medical decisions of claim 1 , wherein said preference function of costs and benefits is a function of costs, benefits and parameters representing approximate value of the combination of costs and benefits for the provider of medical care. | 0.690049 |
21. A non-transitory computer-readable storage medium with an executable program stored thereon, wherein the program instructs a microprocessor to: enable, via a user interface of a message communication device, a first message configuration to be used when replying to a first electronic message received from a source internal to a particular organization, the first message configuration including a first text, wherein the particular organization represents a category, users internal to the particular organization are included in the category and users external to the particular organization are not included in the category, and the category is one of personal, customer, and supplier; enable, via the user interface of the message communication device, a second message configuration to be used when replying to a second electronic message received from a source external to the particular organization, the second message configuration including a second text; store the first message configuration and the second message configuration; receive a message from a source; after receiving the message, receive, from a user of the message communication device, a third text, wherein the third text is a new reply electronic message corresponding to the received message, and the third text is different than text of the received message; and automatically append one of the first text of the first message configuration or the second text of the second message configuration to the third text for the new reply electronic message based on the source of the received message associated with the new reply electronic message. | 21. A non-transitory computer-readable storage medium with an executable program stored thereon, wherein the program instructs a microprocessor to: enable, via a user interface of a message communication device, a first message configuration to be used when replying to a first electronic message received from a source internal to a particular organization, the first message configuration including a first text, wherein the particular organization represents a category, users internal to the particular organization are included in the category and users external to the particular organization are not included in the category, and the category is one of personal, customer, and supplier; enable, via the user interface of the message communication device, a second message configuration to be used when replying to a second electronic message received from a source external to the particular organization, the second message configuration including a second text; store the first message configuration and the second message configuration; receive a message from a source; after receiving the message, receive, from a user of the message communication device, a third text, wherein the third text is a new reply electronic message corresponding to the received message, and the third text is different than text of the received message; and automatically append one of the first text of the first message configuration or the second text of the second message configuration to the third text for the new reply electronic message based on the source of the received message associated with the new reply electronic message. 29. The computer-readable storage medium of claim 21 , wherein a source's relationship to the particular organization, internal to the particular organization or external to the particular organization, is reflected in at least a part of an address portion of electronic messages sent by or on behalf of the source. | 0.524527 |
10. The method of claim 1 , wherein submitting, by the portable program module, the query to an item search server comprises inserting the subset of the keywords received from the container document as arguments of the query. | 10. The method of claim 1 , wherein submitting, by the portable program module, the query to an item search server comprises inserting the subset of the keywords received from the container document as arguments of the query. 11. The method of claim 10 , further comprising determining, by the portable program module located in the container document, that the subset of the keywords received from the container document will obtain a result from the item search server. | 0.891643 |
11. A communications system comprising: a speech interface for accessing a speech recognizer operable for receiving speech input during limited time recognition window, means for mapping available time of the recognition window to a spatial representation in animated form using one of a graphical modality, haptic modality or auditory modality. | 11. A communications system comprising: a speech interface for accessing a speech recognizer operable for receiving speech input during limited time recognition window, means for mapping available time of the recognition window to a spatial representation in animated form using one of a graphical modality, haptic modality or auditory modality. 18. A system according to claim 11 wherein the animation diminishes in size as the available time diminishes. | 0.753511 |
1. A computer-implemented method comprising: identifying, by one or more computing devices, a content source that was referenced by search results for each of two or more different queries that have been previously received from users; determining, by one or more computing devices and for each query from the two or more queries, a number of user interactions with the search results that referenced the content source and were provided to the users in response to the query; ranking, by one or more computing devices, the queries based on the number of user interactions with the content source when presented to the users as a search result for each query; determining, by one or more computing devices, that a term provided by an advertiser matches a query from the two or more queries; determining, by one or more computing devices, that the number of user interactions with the content source corresponding to the matched query meets a threshold number of user interactions; and providing data to the advertiser identifying the content source as a presentation location for the advertiser's content. | 1. A computer-implemented method comprising: identifying, by one or more computing devices, a content source that was referenced by search results for each of two or more different queries that have been previously received from users; determining, by one or more computing devices and for each query from the two or more queries, a number of user interactions with the search results that referenced the content source and were provided to the users in response to the query; ranking, by one or more computing devices, the queries based on the number of user interactions with the content source when presented to the users as a search result for each query; determining, by one or more computing devices, that a term provided by an advertiser matches a query from the two or more queries; determining, by one or more computing devices, that the number of user interactions with the content source corresponding to the matched query meets a threshold number of user interactions; and providing data to the advertiser identifying the content source as a presentation location for the advertiser's content. 2. The method of claim 1 , wherein providing data to the advertiser comprises providing a list of content sources ranked in order of the number of user interactions relative to the matched query. | 0.613287 |
19. The method of claim 5 , wherein the at least one feature includes at least one of a set of features, including: a parse-tree-word-level confidence score calculated based on respective word-level confidence scores of a plurality of words of the respective sub-tree and/or its surrounding sub-trees; a POS-tag confidence score based on respective POS-tag scores computed for the POS tag assignments of the plurality of words of the respective sub-tree and/or its surrounding sub-trees; a linking score representing a conditional probability of a link of a highest level of the respective sub-tree, the link including a dependency relation and a directionality; a linking score representing a conditional probability of a link of a highest level of the surrounding sub-trees, the link including a dependency relation and a directionality; a history score which includes, for each of at least one child sub-tree of the surrounding sub-trees, the surrounding child sub-trees' previously computed confidence score; each of a plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; a dependency relation characteristic; a single level joint head and dependency relation (SL-JHD) characteristic; a single level joint mod and dependency relation (SL-JMD) characteristic; a single level joint head, mod, and dependency relation (SL-JHMD) characteristic; a joint dependency relation (JDR) characteristic; a multi-level joint head and dependency relation (ML-JHD) characteristic; a multi-level joint mod and dependency relation (ML-JMD) characteristic; a multi-level joint head, mod, and dependency relation (ML-JHMD) characteristic; a head, dependency, and left and right neighbors (HDLRN) characteristic; a sub-tree size characteristic; and a semantic slot feature. | 19. The method of claim 5 , wherein the at least one feature includes at least one of a set of features, including: a parse-tree-word-level confidence score calculated based on respective word-level confidence scores of a plurality of words of the respective sub-tree and/or its surrounding sub-trees; a POS-tag confidence score based on respective POS-tag scores computed for the POS tag assignments of the plurality of words of the respective sub-tree and/or its surrounding sub-trees; a linking score representing a conditional probability of a link of a highest level of the respective sub-tree, the link including a dependency relation and a directionality; a linking score representing a conditional probability of a link of a highest level of the surrounding sub-trees, the link including a dependency relation and a directionality; a history score which includes, for each of at least one child sub-tree of the surrounding sub-trees, the surrounding child sub-trees' previously computed confidence score; each of a plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; a dependency relation characteristic; a single level joint head and dependency relation (SL-JHD) characteristic; a single level joint mod and dependency relation (SL-JMD) characteristic; a single level joint head, mod, and dependency relation (SL-JHMD) characteristic; a joint dependency relation (JDR) characteristic; a multi-level joint head and dependency relation (ML-JHD) characteristic; a multi-level joint mod and dependency relation (ML-JMD) characteristic; a multi-level joint head, mod, and dependency relation (ML-JHMD) characteristic; a head, dependency, and left and right neighbors (HDLRN) characteristic; a sub-tree size characteristic; and a semantic slot feature. 28. The method of claim 19 , wherein the at least one feature includes the sub-tree size characteristic, and the sub-tree size characteristic includes: a first value equal to a number of pre-terminals of the surrounding sub-trees; a second value equal to a number of non-terminals of a left child sub-tree corresponding to a level immediately below the highest level of the surrounding sub-trees; and a third value equal to a number of non-terminals of a right child sub-tree corresponding to the level immediately below the highest level of the surrounding sub-trees. | 0.505224 |
5. The method of claim 1 further comprising combining other information associated with the brand in the combination content item. | 5. The method of claim 1 further comprising combining other information associated with the brand in the combination content item. 10. The method of claim 5 wherein the other information includes additional links associated with the brand. | 0.978627 |
1. A method for providing a natural language voice user interface, comprising: receiving a natural language utterance from an input device associated with a computing device, wherein the natural language utterance relates to navigation, and wherein the computing device is moving; determining a current location and direction of travel of the computing device; selecting, from among a plurality of sets of location-specific grammar information, a set of location-specific grammar information based on proximity between the current location and a location associated with the set of location-specific grammar information and based on whether the direction of travel of the computing device corresponds with movement towards the location associated with the set of location-specific grammar information; generating a recognition grammar with the set of location-specific grammar information; generating one or more interpretations of the natural language utterance using the recognition grammar; identifying, by a navigation agent executing on the computing device, one or more requests in the natural language utterance that relate to navigation from the one or more interpretations of the natural language utterance; and resolving, by the navigation agent executing on the computing device, the one or more requests. | 1. A method for providing a natural language voice user interface, comprising: receiving a natural language utterance from an input device associated with a computing device, wherein the natural language utterance relates to navigation, and wherein the computing device is moving; determining a current location and direction of travel of the computing device; selecting, from among a plurality of sets of location-specific grammar information, a set of location-specific grammar information based on proximity between the current location and a location associated with the set of location-specific grammar information and based on whether the direction of travel of the computing device corresponds with movement towards the location associated with the set of location-specific grammar information; generating a recognition grammar with the set of location-specific grammar information; generating one or more interpretations of the natural language utterance using the recognition grammar; identifying, by a navigation agent executing on the computing device, one or more requests in the natural language utterance that relate to navigation from the one or more interpretations of the natural language utterance; and resolving, by the navigation agent executing on the computing device, the one or more requests. 15. The method of claim 1 , wherein the computing device comprises a memory that stores one or more sets of location-specific grammar information, and wherein the generating the recognition grammar comprises: retrieving the selected set of location-specific grammar information; detecting redundant information within the selected set of location-specific grammar information or among the one or more of sets of location-specific grammar information; and storing the selected set of location-specific grammar information in the memory without having the redundant information stored in the memory. | 0.51991 |
11. A computer-implemented method of providing navigational instructions, comprising: receiving unabbreviated instructions that direct navigation over a geographical route from a starting location to a destination location; segmenting the unabbreviated instructions into logical groups; selecting one or more of the logical groups for abbreviation processing based on suitability factors; and abbreviating the instructions of the one or more logical groups. | 11. A computer-implemented method of providing navigational instructions, comprising: receiving unabbreviated instructions that direct navigation over a geographical route from a starting location to a destination location; segmenting the unabbreviated instructions into logical groups; selecting one or more of the logical groups for abbreviation processing based on suitability factors; and abbreviating the instructions of the one or more logical groups. 18. The method of claim 11 , further comprising abbreviating the instructions based on an inference of a level of user familiarity with a region based on user location and location history. | 0.568008 |
8. The method of claim 7 wherein the development environment comprises an interpreter component that uses the output of the first-phase translation tool comprising: an instruction interpreter which emulates the hardware platform in the execution of platform-specific hardware instructions; a dataflow simulator which emulates a streaming data environment, providing inputs to and collecting outputs from state machine streams; and a program execution flow controller to examine computations and data in-flight and drive computations back and forth. | 8. The method of claim 7 wherein the development environment comprises an interpreter component that uses the output of the first-phase translation tool comprising: an instruction interpreter which emulates the hardware platform in the execution of platform-specific hardware instructions; a dataflow simulator which emulates a streaming data environment, providing inputs to and collecting outputs from state machine streams; and a program execution flow controller to examine computations and data in-flight and drive computations back and forth. 9. The method of claim 8 wherein the first-phase translation tool comprises a simulated publisher-subscriber multiplexer, commonly called a message broker, to facilitate the exchange of simulated messages from a plurality of publishers to a plurality of subscribers within a debugging environment. | 0.865585 |
8. A computerized method for reducing false alarms in a speech recognition system, the method comprising: receiving a plurality of training examples, each training example comprising a representation of a spoken word and a local context; generating at least one model of an acoustic context based on the plurality of training examples, wherein the generation of the model includes compact representation of the acoustic context in the form of spectral, cepstral or sinusoidal descriptions; generating at least one model of a phonetic context based on the plurality of training examples, wherein the generation of the model includes compact representation of the phonetic context in the form of spectral, cepstral or sinusoidal descriptions; generating at least one model of a linguistic context based on the plurality of training examples, wherein the generation of the model includes compact representation of the linguistic context in the form of spectral, cepstral or sinusoidal descriptions; receiving at least one test word, the at least one test word comprising an external context; comparing the at least one test word against a threshold associated with each of the model of the acoustic context, the model of the phonetic context, and the model of the linguistic context; and rejecting the at least one test word if it is not within the thresholds. | 8. A computerized method for reducing false alarms in a speech recognition system, the method comprising: receiving a plurality of training examples, each training example comprising a representation of a spoken word and a local context; generating at least one model of an acoustic context based on the plurality of training examples, wherein the generation of the model includes compact representation of the acoustic context in the form of spectral, cepstral or sinusoidal descriptions; generating at least one model of a phonetic context based on the plurality of training examples, wherein the generation of the model includes compact representation of the phonetic context in the form of spectral, cepstral or sinusoidal descriptions; generating at least one model of a linguistic context based on the plurality of training examples, wherein the generation of the model includes compact representation of the linguistic context in the form of spectral, cepstral or sinusoidal descriptions; receiving at least one test word, the at least one test word comprising an external context; comparing the at least one test word against a threshold associated with each of the model of the acoustic context, the model of the phonetic context, and the model of the linguistic context; and rejecting the at least one test word if it is not within the thresholds. 14. The method of claim 8 , wherein the generating at least one model of an acoustic context step includes generating a left internal model, a right internal model, a left external model, and a right external model for each spoken word in the plurality of training examples. | 0.604557 |
17. A non-transitory computer-readable medium comprising a set of code instruction retained therein that, in response to execution, cause a computing system including at least one processor to perform operations, comprising: receiving a manufacturing recipe for an asset produced by a manufacturing tool; generating another manufacturing recipe by adjusting the manufacturing recipe based on a set of variables and a probability distribution function that determines a degree of change between a set of recipe parameters included in the manufacturing recipe and a set of other recipe parameters included in the other manufacturing recipe; and determining a function that predicts a set of output metrics for the asset based on the other manufacturing recipe, comprising relaxing a constraint for the set of output metrics to infer the function for the manufacturing tool. | 17. A non-transitory computer-readable medium comprising a set of code instruction retained therein that, in response to execution, cause a computing system including at least one processor to perform operations, comprising: receiving a manufacturing recipe for an asset produced by a manufacturing tool; generating another manufacturing recipe by adjusting the manufacturing recipe based on a set of variables and a probability distribution function that determines a degree of change between a set of recipe parameters included in the manufacturing recipe and a set of other recipe parameters included in the other manufacturing recipe; and determining a function that predicts a set of output metrics for the asset based on the other manufacturing recipe, comprising relaxing a constraint for the set of output metrics to infer the function for the manufacturing tool. 20. The non-transitory computer-readable medium of claim 17 , further comprising learning a set of relationships associated with product output based on the adjusting of the manufacturing recipe. | 0.566477 |
19. A computer program product comprising: a computer-usable medium comprising computer-usable program code that dynamically adapts a sensitivity of at least one user interface component on an electronic device, the computer-usable medium comprising: computer-usable program code that identifies a device context corresponding to the electronic device; computer-usable program code that processes the device context in real time to identify a potential user intent and to determine a probability that the potential user intent corresponds to an actual user intent; computer-usable program code that selects a user input sensitivity parameter based on the potential user intent and the determined probability; and computer-usable program code that adapts the sensitivity of the at least one user interface component to correspond to the user input sensitivity parameter. | 19. A computer program product comprising: a computer-usable medium comprising computer-usable program code that dynamically adapts a sensitivity of at least one user interface component on an electronic device, the computer-usable medium comprising: computer-usable program code that identifies a device context corresponding to the electronic device; computer-usable program code that processes the device context in real time to identify a potential user intent and to determine a probability that the potential user intent corresponds to an actual user intent; computer-usable program code that selects a user input sensitivity parameter based on the potential user intent and the determined probability; and computer-usable program code that adapts the sensitivity of the at least one user interface component to correspond to the user input sensitivity parameter. 20. The computer program product of claim 19 , wherein the computer-usable medium further comprises: computer-usable program code that solicits at least one user input prior to adapting the sensitivity of the at least one user interface component when the probability that the potential user intent corresponds to the actual user intent is below or above a threshold. | 0.5 |
15. A computer readable article of manufacture comprising a tangible, computer-readable recordable storage medium tangibly embodying, in a non-transitory manner, computer readable instructions which cause at least one hardware processor to execute a method, said method comprising the steps of: storing positional information on at least a first avatar and a second avatar; receiving (i) at least one utterance from said first avatar and (ii) at least one utterance strength representing an importance or attention level of said at least one utterance; calculating at least one interest level between said first avatar and said second avatar based on said positional information; generating at least one message from said at least one utterance in accordance with a value calculated from said at least one interest level and said at least one utterance strength; and transmitting said at least one message to said second avatar; wherein, in said step of generating said at least one message, said message is generated from said at least one utterance only when a value calculated from said at least one interest level and said at least one utterance strength is not less than a predetermined threshold value; and wherein said computer readable instructions further comprise computer readable instructions which cause said at least one hardware processor to calculate said at least one interest level by: calculating cosine of an angle between a facing direction of said first avatar and a line connecting said first and second avatars; dividing said cosine by a distance between said first and second avatars; and multiplying said cosine by a normalization factor which satisfies a requirement such that a sum of all interest levels between said first avatar and a number of avatars in a circle having a predetermined radius and centered about said first avatar is unity. | 15. A computer readable article of manufacture comprising a tangible, computer-readable recordable storage medium tangibly embodying, in a non-transitory manner, computer readable instructions which cause at least one hardware processor to execute a method, said method comprising the steps of: storing positional information on at least a first avatar and a second avatar; receiving (i) at least one utterance from said first avatar and (ii) at least one utterance strength representing an importance or attention level of said at least one utterance; calculating at least one interest level between said first avatar and said second avatar based on said positional information; generating at least one message from said at least one utterance in accordance with a value calculated from said at least one interest level and said at least one utterance strength; and transmitting said at least one message to said second avatar; wherein, in said step of generating said at least one message, said message is generated from said at least one utterance only when a value calculated from said at least one interest level and said at least one utterance strength is not less than a predetermined threshold value; and wherein said computer readable instructions further comprise computer readable instructions which cause said at least one hardware processor to calculate said at least one interest level by: calculating cosine of an angle between a facing direction of said first avatar and a line connecting said first and second avatars; dividing said cosine by a distance between said first and second avatars; and multiplying said cosine by a normalization factor which satisfies a requirement such that a sum of all interest levels between said first avatar and a number of avatars in a circle having a predetermined radius and centered about said first avatar is unity. 16. The article of manufacture according to claim 15 , wherein said computer readable instructions further comprise computer readable instructions which cause said at least one hardware processor to execute at least one of: receiving said positional information; and transmitting said positional information. | 0.646488 |
5. The method of claim 1 , further comprising: identifying one or more sets of matching web pages from the plurality of web pages, each set of matching web pages being a two or more web pages that each have a characteristic that matches a characteristic of another web page in the set of matching web pages; and identifying one or more sets of matching labels from the set of initial labels, each set of matching labels including two or more initial labels having at least a threshold measure of similarity. | 5. The method of claim 1 , further comprising: identifying one or more sets of matching web pages from the plurality of web pages, each set of matching web pages being a two or more web pages that each have a characteristic that matches a characteristic of another web page in the set of matching web pages; and identifying one or more sets of matching labels from the set of initial labels, each set of matching labels including two or more initial labels having at least a threshold measure of similarity. 8. The method of claim 5 , wherein identifying one or more sets of matching labels comprises identifying at least one set of matching labels in which each label references a same topic. | 0.935906 |
11. A system for converting a source application to a platform-independent application, the system comprising: at least one computing device; and at least one memory device coupled to the at least one computing device, wherein the at least one memory device contains executable instructions that, if executed on the at least one computing device, result in the implementation of operations comprising: translating source programming language code of the source application to target programming language code of the platform-independent application, wherein the source programming language code comprises Connected Limited Device Configuration (CLDC) code, and wherein the target programming language code of the platform-independent application is in a platform-independent programming language that is independent of one or more device platforms; converting one or more source resources associated with and configured to be used by the source application to one or more target resources configured to be used by the platform-independent application, wherein the source resources are not included within the source programming language code of the source application and the target resources are not included within the target programming language code of the platform-independent application; and providing a configuration of the source application to the platform-independent application, wherein the configuration includes data defining settings of the source application; wherein the translating is implemented by a first series of steps; wherein the converting is implemented by a second series of steps; and wherein the first series of steps for the translating are different from, and independent from, the second series of steps for the converting. | 11. A system for converting a source application to a platform-independent application, the system comprising: at least one computing device; and at least one memory device coupled to the at least one computing device, wherein the at least one memory device contains executable instructions that, if executed on the at least one computing device, result in the implementation of operations comprising: translating source programming language code of the source application to target programming language code of the platform-independent application, wherein the source programming language code comprises Connected Limited Device Configuration (CLDC) code, and wherein the target programming language code of the platform-independent application is in a platform-independent programming language that is independent of one or more device platforms; converting one or more source resources associated with and configured to be used by the source application to one or more target resources configured to be used by the platform-independent application, wherein the source resources are not included within the source programming language code of the source application and the target resources are not included within the target programming language code of the platform-independent application; and providing a configuration of the source application to the platform-independent application, wherein the configuration includes data defining settings of the source application; wherein the translating is implemented by a first series of steps; wherein the converting is implemented by a second series of steps; and wherein the first series of steps for the translating are different from, and independent from, the second series of steps for the converting. 15. The system of claim 11 , wherein translating the source programming language code comprises: tokenizing one or more characters of one or more input files of the source programming language code to generate a list of tokens; parsing the list of tokens to generate one or more document object models; generating an environment document object model comprising the one or more document object models, wherein the one or more input files are cross-referenced within the one or more document object models of the environment document object model; and analyzing the environment document object model to generate one or more characters of one or more output files of the target programming language code. | 0.5 |
1. A query plan execution system comprising: a memory; one or more processors; a plan guide metadata store that stores one or more plan guides that are each associated with one or more queries, wherein each plan guide comprises one or more hints that are supplied by a user independently of the creation of and without modifying the associated one or more queries, wherein each plan guide is one of multiple types including object, SQL, and template types; and an execution environment that, upon receiving a query to be executed, accesses the plan guide metadata store to determine whether the query is associated with one or more of the plan guides, and upon locating a matching plan guide, modifies at least one query statement of the query with the one or more hints of the matching plan guide such that the one or more hints are used to guide an optimization process that generates a query plan for the query wherein: when the query is part of a stored procedure, the matching plan guide is of type object, when the query is part of a batch of query statements, the matching plan guide is of type SQL, and when the matching plan guide is of type template, the matching plan guide directs the execution environment to force parameterization of the query. | 1. A query plan execution system comprising: a memory; one or more processors; a plan guide metadata store that stores one or more plan guides that are each associated with one or more queries, wherein each plan guide comprises one or more hints that are supplied by a user independently of the creation of and without modifying the associated one or more queries, wherein each plan guide is one of multiple types including object, SQL, and template types; and an execution environment that, upon receiving a query to be executed, accesses the plan guide metadata store to determine whether the query is associated with one or more of the plan guides, and upon locating a matching plan guide, modifies at least one query statement of the query with the one or more hints of the matching plan guide such that the one or more hints are used to guide an optimization process that generates a query plan for the query wherein: when the query is part of a stored procedure, the matching plan guide is of type object, when the query is part of a batch of query statements, the matching plan guide is of type SQL, and when the matching plan guide is of type template, the matching plan guide directs the execution environment to force parameterization of the query. 5. The system of claim 1 , wherein only plan guides scoped to a current database are available to the execution environment. | 0.780702 |
21. A tangible machine-readable storage medium bearing instructions for obtaining representative text items from a plurality of text items in an active computer tasks, the instructions upon execution by a data processing system causing the data processing system to perform the steps of: receiving first information indicative of a first computer task, the first information including a first plurality of text items and a stylistic attribute associated with a first text item in the first plurality of text items; determining a genre associated with the first active computer task; determining a first representative stylistic attribute value of the first plurality of text items based on a first frequency of occurrence of the stylistic attribute in the first active computer task; for each of the first plurality of text items, assigning a first weight with a first magnitude, the first magnitude being determined based on the genre and the first representative stylistic attribute; ranking the first plurality of text items based on the first weight assigned to each of the first plurality of text items to produce a first plurality of ranked text items; generating and storing first representative text items based on the first plurality of ranked text items; wherein the first active computer task is a task other than entering search terms for the purpose of retrieving information; receiving second information indicative of a second active computer task, the second active computer task being different than the first active computer task, the second information including a second plurality of text items and a stylistic attribute associated with a second text item in the second plurality of text items, wherein the second plurality of text items is different than the first plurality of text items; determining a second representative stylistic attribute value of the second plurality of text items based on a second frequency of occurrence of the stylistic attribute in the second active computer task, the second representative stylistic attribute value being different than the first representative stylistic attribute value; for each of the second plurality of text items, assigning a second weight with a second magnitude being different than the first magnitude; ranking the second plurality of text items based on the second weight assigned to each of the second plurality of text items to produce a second plurality of ranked text items; and generating and storing second representative text items based on the second plurality of ranked text items; wherein the second active computer task is a task other than entering search terms for the purpose of retrieving information. | 21. A tangible machine-readable storage medium bearing instructions for obtaining representative text items from a plurality of text items in an active computer tasks, the instructions upon execution by a data processing system causing the data processing system to perform the steps of: receiving first information indicative of a first computer task, the first information including a first plurality of text items and a stylistic attribute associated with a first text item in the first plurality of text items; determining a genre associated with the first active computer task; determining a first representative stylistic attribute value of the first plurality of text items based on a first frequency of occurrence of the stylistic attribute in the first active computer task; for each of the first plurality of text items, assigning a first weight with a first magnitude, the first magnitude being determined based on the genre and the first representative stylistic attribute; ranking the first plurality of text items based on the first weight assigned to each of the first plurality of text items to produce a first plurality of ranked text items; generating and storing first representative text items based on the first plurality of ranked text items; wherein the first active computer task is a task other than entering search terms for the purpose of retrieving information; receiving second information indicative of a second active computer task, the second active computer task being different than the first active computer task, the second information including a second plurality of text items and a stylistic attribute associated with a second text item in the second plurality of text items, wherein the second plurality of text items is different than the first plurality of text items; determining a second representative stylistic attribute value of the second plurality of text items based on a second frequency of occurrence of the stylistic attribute in the second active computer task, the second representative stylistic attribute value being different than the first representative stylistic attribute value; for each of the second plurality of text items, assigning a second weight with a second magnitude being different than the first magnitude; ranking the second plurality of text items based on the second weight assigned to each of the second plurality of text items to produce a second plurality of ranked text items; and generating and storing second representative text items based on the second plurality of ranked text items; wherein the second active computer task is a task other than entering search terms for the purpose of retrieving information. 27. The machine-readable medium of claim 21 , wherein assigning the weight is based on a user's role in an organization. | 0.568647 |
16. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause: classifying a video file according to one or more scene classes, the video file including a plurality of frames, where each frame of the plurality of frames includes a plurality of pixels, and where each pixel of the plurality of pixels is associated with a vector of material classification scores describing material content in its respective frame: for each frame of the plurality of frames, generating one or more scene classification scores associated with each of the one or more scene classes by: dividing the frame into a plurality of grid cells; retrieving the vector of material classification scores for each pixel in the frame; for each grid cell of the plurality of grid cells, averaging the material classification scores across each pixel in the grid cell to form a material occurrence vector for the grid cell; concatenating the material occurrence vectors for each grid cell of the plurality of grid cells to generate a material arrangement vector for the frame; and based on the material arrangement vector generated for the frame, generating the one or more scene classification scores associated with each of the one or more scene classes for using one or more scene classifiers; based on the one or more scene classification scores generated for each frame of the plurality of frames, generating a representative scene classification score for each of the one or more scene classes; and for each of the generated representative scene classification scores that is above a predetermined threshold value, labeling the video file according to the respective scene classes associated with the scene classification scores that are above the predetermined threshold value. | 16. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause: classifying a video file according to one or more scene classes, the video file including a plurality of frames, where each frame of the plurality of frames includes a plurality of pixels, and where each pixel of the plurality of pixels is associated with a vector of material classification scores describing material content in its respective frame: for each frame of the plurality of frames, generating one or more scene classification scores associated with each of the one or more scene classes by: dividing the frame into a plurality of grid cells; retrieving the vector of material classification scores for each pixel in the frame; for each grid cell of the plurality of grid cells, averaging the material classification scores across each pixel in the grid cell to form a material occurrence vector for the grid cell; concatenating the material occurrence vectors for each grid cell of the plurality of grid cells to generate a material arrangement vector for the frame; and based on the material arrangement vector generated for the frame, generating the one or more scene classification scores associated with each of the one or more scene classes for using one or more scene classifiers; based on the one or more scene classification scores generated for each frame of the plurality of frames, generating a representative scene classification score for each of the one or more scene classes; and for each of the generated representative scene classification scores that is above a predetermined threshold value, labeling the video file according to the respective scene classes associated with the scene classification scores that are above the predetermined threshold value. 17. The one or more non-transitory storage media of claim 16 , where generating a scene classification score associated with each of the one or more scene classes is performed two or more times using varying numbers of grid cells. | 0.508753 |
31. The computer program product of claim 30 wherein the filtering of the structured document comprises extracting, from the structured document, structural elements having classification identifiers corresponding to the second user classification of the session copy of the second user profile and writing the extracted structural elements into the session structured document in the session document. | 31. The computer program product of claim 30 wherein the filtering of the structured document comprises extracting, from the structured document, structural elements having classification identifiers corresponding to the second user classification of the session copy of the second user profile and writing the extracted structural elements into the session structured document in the session document. 32. The computer program product of claim 31 further comprising: computer instructions, recorded on the storage device, for filtering the presentation grammar, in dependence upon the extracted structural elements, into a session grammar in the session document. | 0.924302 |
11. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executable by the computer to perform the method steps for three-dimensional contour tracking comprising the steps of: providing a database of a plurality of shape models and a plurality of appearance models, wherein shape models are curves and surfaces, appearance models are voxel intensity patterns, wherein said models include 2-dimensional shape models, 3-dimensional shape models and dynamical models that describe how a contour changes as it is propagated along on object in an image; providing a learning and classification algorithm trained using said shape models and appearance models; providing a digitized volumetric image comprising a plurality of intensities corresponding to an N×N×N domain of points in a 3-dimensional space; extracting one or more candidate data patches of an object from one of said images; calculating features from said data patches and applying said learning and classification algorithm to said features to localize said object; searching for a shape and appearance counterpart of said candidate object among said stored shape models and appearance models that most closely matches said object to initialize a contour; and tracking said contour along said object in 3D incorporating said learning and classification algorithm; initializing said contour about an object in a low-resolution version of said image; tracking said contour along said object in said reduced resolution image to obtain a contour surface about said object; and re-tracking said contour surface along said object in said N×N×N image to correct errors in said contour surface in said reduced resolution image. | 11. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executable by the computer to perform the method steps for three-dimensional contour tracking comprising the steps of: providing a database of a plurality of shape models and a plurality of appearance models, wherein shape models are curves and surfaces, appearance models are voxel intensity patterns, wherein said models include 2-dimensional shape models, 3-dimensional shape models and dynamical models that describe how a contour changes as it is propagated along on object in an image; providing a learning and classification algorithm trained using said shape models and appearance models; providing a digitized volumetric image comprising a plurality of intensities corresponding to an N×N×N domain of points in a 3-dimensional space; extracting one or more candidate data patches of an object from one of said images; calculating features from said data patches and applying said learning and classification algorithm to said features to localize said object; searching for a shape and appearance counterpart of said candidate object among said stored shape models and appearance models that most closely matches said object to initialize a contour; and tracking said contour along said object in 3D incorporating said learning and classification algorithm; initializing said contour about an object in a low-resolution version of said image; tracking said contour along said object in said reduced resolution image to obtain a contour surface about said object; and re-tracking said contour surface along said object in said N×N×N image to correct errors in said contour surface in said reduced resolution image. 19. The non-transitory computer readable program storage device of claim 11 , wherein searching for a shape counterpart comprises using a matching algorithm that uses shape and appearance features learned during training of said learning and classification algorithm, and applying their associated shapes to the candidate data patches to localize said contour. | 0.507983 |
9. A method performed by one or more processors associated with one or more server devices, the method comprising: determining, by the one or more processors associated with the one or more server devices, a webscore for each of a plurality of business listings associated with a location; receiving, by a communication interface or an input device associated with the one or more server devices, a local search request over a computer network; identifying, by the one or more processors, business listings based on the local search request; ranking, by the one or more processors associated with the one or more server devices, the identified business listings based on the webscores determined for the identified business listings; and providing, by the communication interface or an output device associated with the one or more server devices, the ranked business listings over the computer network; where determining the webscore for any one of the plurality of business listings further comprises: identifying a business listing title; and determining a number of search results returned by querying a search engine with the business listing title when a size of the business listing title is greater than a threshold, and determining the number of search results returned by querying the search engine with the business listing title and the location associated with the business listing when the size of the business listing title is less than the threshold. | 9. A method performed by one or more processors associated with one or more server devices, the method comprising: determining, by the one or more processors associated with the one or more server devices, a webscore for each of a plurality of business listings associated with a location; receiving, by a communication interface or an input device associated with the one or more server devices, a local search request over a computer network; identifying, by the one or more processors, business listings based on the local search request; ranking, by the one or more processors associated with the one or more server devices, the identified business listings based on the webscores determined for the identified business listings; and providing, by the communication interface or an output device associated with the one or more server devices, the ranked business listings over the computer network; where determining the webscore for any one of the plurality of business listings further comprises: identifying a business listing title; and determining a number of search results returned by querying a search engine with the business listing title when a size of the business listing title is greater than a threshold, and determining the number of search results returned by querying the search engine with the business listing title and the location associated with the business listing when the size of the business listing title is less than the threshold. 12. The method of claim 9 , where the size of the business listing title is determined from a number of characters in the business listing title. | 0.640539 |
1. A method for issuing an alert in response to detecting a content of interest in a conference, the method comprising: reading a plurality of monitoring preferences for a conference, including: (a) preferences for monitoring and recording verbal utterances exchanged during the conference, and (b) preferences for determining contents of interest of the conference, wherein each content of interest corresponds to one or more items from a group consisting of specific topics, specific persons, and specific names; determining one or more target contents of interest of the conference; based on the monitoring preferences, monitoring verbal utterances exchanged during the conference to: i. determine an occurrence of one or more contents of interest, and ii. produce a real time transcript of the verbal utterances including providing a name of a corresponding utterance speaker for each utterance; and in response to detecting a content of interest, simultaneously: i. displaying a selected portion of the transcript related to the detected content of interest, and ii. issuing one or more alert notifications alerting of the occurrence of an identified content of interest of the conference. | 1. A method for issuing an alert in response to detecting a content of interest in a conference, the method comprising: reading a plurality of monitoring preferences for a conference, including: (a) preferences for monitoring and recording verbal utterances exchanged during the conference, and (b) preferences for determining contents of interest of the conference, wherein each content of interest corresponds to one or more items from a group consisting of specific topics, specific persons, and specific names; determining one or more target contents of interest of the conference; based on the monitoring preferences, monitoring verbal utterances exchanged during the conference to: i. determine an occurrence of one or more contents of interest, and ii. produce a real time transcript of the verbal utterances including providing a name of a corresponding utterance speaker for each utterance; and in response to detecting a content of interest, simultaneously: i. displaying a selected portion of the transcript related to the detected content of interest, and ii. issuing one or more alert notifications alerting of the occurrence of an identified content of interest of the conference. 4. The method of claim 1 , wherein recording a transcript further comprises: determining a speaker of a particular portion of the detected content; and tagging portions of the transcript to actual words spoken by each individual speaker of the conference, in their order of occurrence. | 0.628189 |
10. A system comprising: an annotations profile mechanism to define one or more annotations profiles, each annotations profile defining one or more annotations, each annotation corresponding to and representing a functional concern of an abstract model; an annotation association mechanism to associate each of a plurality of modeling elements of the abstract model with an annotation corresponding to a non-functional concern pertaining to the modeling element; and, a transformation mechanism to transform the abstract model to a specific implementation platform, such that execution of the abstract model results in the non-functional concerns represented by the annotations associated with the modeling elements being consumed. | 10. A system comprising: an annotations profile mechanism to define one or more annotations profiles, each annotations profile defining one or more annotations, each annotation corresponding to and representing a functional concern of an abstract model; an annotation association mechanism to associate each of a plurality of modeling elements of the abstract model with an annotation corresponding to a non-functional concern pertaining to the modeling element; and, a transformation mechanism to transform the abstract model to a specific implementation platform, such that execution of the abstract model results in the non-functional concerns represented by the annotations associated with the modeling elements being consumed. 17. The system of claim 10 , wherein the annotation association mechanism comprises a model annotator by which associations of the annotations with multiple modeling elements are capable of being created, viewed, and modified by a user. | 0.745248 |
10. A system for navigating model objects, comprising: a processor; and hardware logic coupled to the processor and performing operations, the operations comprising: displaying the model objects in models in a models stack; in response to a model object in a model of the models stack being selected as an initial context, displaying one or more navigation paths associated with the selected model object, wherein each of the navigation paths has nodes represented as graphical components that are built in real time and that represent the selected model object and other model objects from the models in the models stack; and in response to a user selecting a node in one of the one or more navigation paths, navigating to a new model object represented by the selected node in the models stack in one of a forward direction and a backward direction to provide bidirectional navigation between the model objects in the models without loosing the initial context; and displaying one or more navigation paths associated with the new model object and at least one appended node that represents a previously traversed model object. | 10. A system for navigating model objects, comprising: a processor; and hardware logic coupled to the processor and performing operations, the operations comprising: displaying the model objects in models in a models stack; in response to a model object in a model of the models stack being selected as an initial context, displaying one or more navigation paths associated with the selected model object, wherein each of the navigation paths has nodes represented as graphical components that are built in real time and that represent the selected model object and other model objects from the models in the models stack; and in response to a user selecting a node in one of the one or more navigation paths, navigating to a new model object represented by the selected node in the models stack in one of a forward direction and a backward direction to provide bidirectional navigation between the model objects in the models without loosing the initial context; and displaying one or more navigation paths associated with the new model object and at least one appended node that represents a previously traversed model object. 12. The system of claim 10 , wherein the operations further comprise: providing a user interface to allow a user to be able to navigate between the model objects. | 0.799854 |
10. An electronic device, comprising: a display device; two or more cameras; one or more processors; and a memory operatively coupled to the one or more processors, the display device, and the two or more cameras of the device, the memory storing instructions executable by the one or more processors to: obtain contextual data relating to a picture taking context, wherein the picture taking context is associated with a side of the device selected from a first side of the device and a side substantially opposite of the first side of the device and wherein the contextual data is associated with a hand contact position with respect to the device; identify that the contextual data matches to a predetermined picture taking context, wherein the predetermined picture taking context is assigned to a camera from two or more cameras of the device; wherein one of the two or more cameras is disposed on the first side of the device and wherein a second of the two or more cameras is disposed on the side of the device substantially opposite of the first side of the device; activate, automatically without additional user input, the camera assigned to the predetermined picture taking context; determine that the predetermined picture taking context does not match a first camera; thereafter, automatically switch to a second camera; and responsive to switching, display a notification thereof. | 10. An electronic device, comprising: a display device; two or more cameras; one or more processors; and a memory operatively coupled to the one or more processors, the display device, and the two or more cameras of the device, the memory storing instructions executable by the one or more processors to: obtain contextual data relating to a picture taking context, wherein the picture taking context is associated with a side of the device selected from a first side of the device and a side substantially opposite of the first side of the device and wherein the contextual data is associated with a hand contact position with respect to the device; identify that the contextual data matches to a predetermined picture taking context, wherein the predetermined picture taking context is assigned to a camera from two or more cameras of the device; wherein one of the two or more cameras is disposed on the first side of the device and wherein a second of the two or more cameras is disposed on the side of the device substantially opposite of the first side of the device; activate, automatically without additional user input, the camera assigned to the predetermined picture taking context; determine that the predetermined picture taking context does not match a first camera; thereafter, automatically switch to a second camera; and responsive to switching, display a notification thereof. 13. The electronic device of claim 10 , further comprising one or more device sensors that sense device acceleration, wherein the contextual data includes device accelerometer data. | 0.547431 |
5. A method for mitigating digital abuse and/or digital fraud occurring using online services, the method comprising: receiving, via an application program interface, a request for a global digital threat score, the global digital threat score indicating a likelihood of digital fraud and/or digital abuse; collecting digital event data, via a network, from at least one remote source of digital event data, wherein the digital event data comprises data relating to one or more activities and/or events performed using one or more online services of a service provider; using the collected digital event data as input into a machine learning system of a digital threat mitigation platform, the machine learning system comprising one or more computing servers implementing a primary machine learning ensemble that predicts the likelihood of digital fraud and/or digital abuse from the collected digital event data; generating by the machine learning system the global digital threat score based on the input of the collected digital event data, wherein the global digital threat score is agnostic to a category of digital abuse type; identifying a sub-request for a specific digital threat score for a digital abuse type, wherein the digital abuse type relates to one of a plurality of digital abuse types defined by digital fraud and/or digital abuse activities that is committed by an online user of the online services of the service provider; in response to identifying the sub-request, generating by a machine learning classifier a digital abuse label that identifies one specific digital abuse type of a plurality of specific digital abuse types based on the collected digital event data, wherein the one specific digital abuse type indicates a category of digital fraud or digital abuse activity that was perpetrated in the collected digital event data by a user; using the generated digital abuse label to warp the primary machine learning ensemble to a secondary machine learning ensemble that generates a specific digital threat score for the one specific digital abuse type based on the input of the collected digital event data, wherein the specific digital threat score indicates a probability or likelihood that the one specific digital abuse type was committed by the user; transmitting, via a score application program interface, the specific digital threat score for the identified digital abuse type in response to the sub-request. | 5. A method for mitigating digital abuse and/or digital fraud occurring using online services, the method comprising: receiving, via an application program interface, a request for a global digital threat score, the global digital threat score indicating a likelihood of digital fraud and/or digital abuse; collecting digital event data, via a network, from at least one remote source of digital event data, wherein the digital event data comprises data relating to one or more activities and/or events performed using one or more online services of a service provider; using the collected digital event data as input into a machine learning system of a digital threat mitigation platform, the machine learning system comprising one or more computing servers implementing a primary machine learning ensemble that predicts the likelihood of digital fraud and/or digital abuse from the collected digital event data; generating by the machine learning system the global digital threat score based on the input of the collected digital event data, wherein the global digital threat score is agnostic to a category of digital abuse type; identifying a sub-request for a specific digital threat score for a digital abuse type, wherein the digital abuse type relates to one of a plurality of digital abuse types defined by digital fraud and/or digital abuse activities that is committed by an online user of the online services of the service provider; in response to identifying the sub-request, generating by a machine learning classifier a digital abuse label that identifies one specific digital abuse type of a plurality of specific digital abuse types based on the collected digital event data, wherein the one specific digital abuse type indicates a category of digital fraud or digital abuse activity that was perpetrated in the collected digital event data by a user; using the generated digital abuse label to warp the primary machine learning ensemble to a secondary machine learning ensemble that generates a specific digital threat score for the one specific digital abuse type based on the input of the collected digital event data, wherein the specific digital threat score indicates a probability or likelihood that the one specific digital abuse type was committed by the user; transmitting, via a score application program interface, the specific digital threat score for the identified digital abuse type in response to the sub-request. 8. The method of claim 5 , wherein, in response to identifying the sub-request for the specific digital threat score for the specific digital abuse type, warping the primary machine learning ensemble to generate the secondary machine learning ensemble, wherein warping the primary machine learning ensemble includes applying warping parameters for the identified digital abuse type to the primary machine learning ensemble to reconfigure one or more weights and/or one or more features of machine learning models defining the primary machine learning ensemble. | 0.545767 |
29. A system for graphically characterizing statements about an object, comprising: a sub system configured, as a result of the computing hardware and programmable memory, to apply frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; a sub system configured, as a result of the computing hardware and programmable memory, to identify a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a sentiment of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a polarity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize an intensity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to determine a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; a sub system configured, as a result of the computing hardware and programmable memory, to produce a first graphical representation, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and a sub-system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a second axis, in accordance with the net intensity measure. | 29. A system for graphically characterizing statements about an object, comprising: a sub system configured, as a result of the computing hardware and programmable memory, to apply frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; a sub system configured, as a result of the computing hardware and programmable memory, to identify a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a sentiment of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a polarity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize an intensity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to determine a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; a sub system configured, as a result of the computing hardware and programmable memory, to produce a first graphical representation, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and a sub-system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a second axis, in accordance with the net intensity measure. 36. The system of claim 29 , further comprising: a sub-system configured to identify a first plurality of object-specific corpuses, each of which is a subset of the first corpus, where all the statements, of an object-specific corpus, are about a same object and the first object-specific corpus is part of the first plurality of object-specific corpuses; a sub-system configured to determine a total number of statements across the first plurality of object-specific corpuses; a sub-system configured to produce a first relative value, of a first number of statements contained in the first object-specific corpus considered relative to the total number of statements; and a sub-system configured to produce the first graphical representation of the first object-specific corpus with an area proportional to the first relative value. | 0.600927 |
13. At least one computer readable medium comprising instructions that, when executed by at least one processor, perform a method comprising acts of: identifying a preexisting presentation document for the presentation, the presentation document including a presentation grammar and a structured document having a plurality of structural elements, including a first structural element classified with a first classification identifier and a second structural element classified with a second classification identifier; identifying user participants for the presentation, the user participants each having a user profile comprising a user classification, the user participants including at least one user in a first user classification and at least one user in a second user classification; filtering the presentation document based upon the user classifications of the user participants and the classification identifiers to generate session data targeted for the participants of the presentation, wherein the filtering comprises: presenting first session data targeted to the at least one user in the first user classification, the first session data comprising the first structural element, but not the second structural element; and presenting second session data targeted to the at least one user in the second user classification, the second session data comprising both the first and second structural elements; presenting a structural element from the session data structure responsive to speech input by a user participant of the user participants; streaming speech to the user participant from one or more user participants; detecting a total sound level for the user participant; detecting an ambient noise level component of the total sound level; and displaying a textual transcription of the speech to the user participant if a ratio of the total sound level to the ambient noise level is less than a predetermined value. | 13. At least one computer readable medium comprising instructions that, when executed by at least one processor, perform a method comprising acts of: identifying a preexisting presentation document for the presentation, the presentation document including a presentation grammar and a structured document having a plurality of structural elements, including a first structural element classified with a first classification identifier and a second structural element classified with a second classification identifier; identifying user participants for the presentation, the user participants each having a user profile comprising a user classification, the user participants including at least one user in a first user classification and at least one user in a second user classification; filtering the presentation document based upon the user classifications of the user participants and the classification identifiers to generate session data targeted for the participants of the presentation, wherein the filtering comprises: presenting first session data targeted to the at least one user in the first user classification, the first session data comprising the first structural element, but not the second structural element; and presenting second session data targeted to the at least one user in the second user classification, the second session data comprising both the first and second structural elements; presenting a structural element from the session data structure responsive to speech input by a user participant of the user participants; streaming speech to the user participant from one or more user participants; detecting a total sound level for the user participant; detecting an ambient noise level component of the total sound level; and displaying a textual transcription of the speech to the user participant if a ratio of the total sound level to the ambient noise level is less than a predetermined value. 15. The at least one computer readable medium of claim 13 , wherein the method further comprises: temporarily interrupting the speech streaming to the user participant and measuring an ambient sound level on a voice channel associated with the user participant during the interruption and while the user participant is not speaking; and displaying the textual transcription of the speech to the user participant if the ambient noise level is above a predetermined threshold. | 0.5 |
4. A method comprising: receiving at a query transcoding device from a first query rewrite source device, a first set of query rewrite data, wherein the first set of query rewrite data comprises constraint data, metaflag data, and rewrite data, wherein the constraint data comprises at least a first trigger value, wherein the constraint data identifies a first merchant website, and wherein the rewrite data identifies at least a first query rewrite value associated with the first trigger value; processing the first set of query data to identify the first trigger and the first query rewrite value; analyzing the first set of query data to identify a first query rewrite type associated with the first set of query rewrite data from a plurality of query rewrite types; generating a first query rewrite input language (QRIL) record from the first set of query rewrite data, wherein the first QRIL record comprises the first trigger value, the first query rewrite value, and a first metaflag element that identifies the first QRIL record as associated with the first query rewrite type, and wherein the first QRIL record comprises a website constraint element that specifies that the first query rewrite value will be applied to the trigger only when the trigger is received at a search engine as part of a query associated with the first merchant website; storing the first QRIL record in a QRIL record database with a plurality of QRIL records; and associating the first query rewrite source device with the first merchant website in response to an authorization associated with the first merchant device; following the generating of the first QRIL record, receiving a second set of query rewrite data from the first query rewrite source device; and automatically generating a second website constraint element for a second QRIL generated from the second set of query rewrite data in response to a determination that the second set of query rewrite data is received from the first query rewrite source device and the authorization associated with the first merchant device. | 4. A method comprising: receiving at a query transcoding device from a first query rewrite source device, a first set of query rewrite data, wherein the first set of query rewrite data comprises constraint data, metaflag data, and rewrite data, wherein the constraint data comprises at least a first trigger value, wherein the constraint data identifies a first merchant website, and wherein the rewrite data identifies at least a first query rewrite value associated with the first trigger value; processing the first set of query data to identify the first trigger and the first query rewrite value; analyzing the first set of query data to identify a first query rewrite type associated with the first set of query rewrite data from a plurality of query rewrite types; generating a first query rewrite input language (QRIL) record from the first set of query rewrite data, wherein the first QRIL record comprises the first trigger value, the first query rewrite value, and a first metaflag element that identifies the first QRIL record as associated with the first query rewrite type, and wherein the first QRIL record comprises a website constraint element that specifies that the first query rewrite value will be applied to the trigger only when the trigger is received at a search engine as part of a query associated with the first merchant website; storing the first QRIL record in a QRIL record database with a plurality of QRIL records; and associating the first query rewrite source device with the first merchant website in response to an authorization associated with the first merchant device; following the generating of the first QRIL record, receiving a second set of query rewrite data from the first query rewrite source device; and automatically generating a second website constraint element for a second QRIL generated from the second set of query rewrite data in response to a determination that the second set of query rewrite data is received from the first query rewrite source device and the authorization associated with the first merchant device. 16. The method of claim 4 wherein the trigger comprises a set of token words in a first language; and wherein the first query rewrite value comprises a set of token words in a second language that is associated with the first country; and wherein the first query rewrite value comprises a token identifying a merchant located in the first country. | 0.575332 |
23. A system for responding to an inquiry comprising: means for retrieving a first web page and a second web page, the first web page associated with a first layout and the second web page associated with a second layout; means for comparing the first layout and the second layout; means for generating stored question-answer pairs based on the comparing the first layout and the second layout; means for receiving the inquiry via a network; means for analyzing stored question-answer pairs based on the inquiry; means for determining meta-level features of the stored question-answer pairs to define relationships among the stored question-answer pairs, the meta-level features of a particular stored question-answer pair based at least in part on the meta-level features of a previous related stored question-answer pair and a first related stored question-answer pair; means for clarifying the inquiry based on follow-up procedures including asking follow-up questions; means for determining a plurality of responses to the inquiry based on the analysis of the stored question-answer pairs, the relationships among the stored question-answer pairs, and the follow-up procedures; means for providing the plurality of responses; means for receiving a selection of a particular response from among the plurality of responses; and means for storing a measure of the eligibility of the particular response to be a response to the inquiry based on the selection. | 23. A system for responding to an inquiry comprising: means for retrieving a first web page and a second web page, the first web page associated with a first layout and the second web page associated with a second layout; means for comparing the first layout and the second layout; means for generating stored question-answer pairs based on the comparing the first layout and the second layout; means for receiving the inquiry via a network; means for analyzing stored question-answer pairs based on the inquiry; means for determining meta-level features of the stored question-answer pairs to define relationships among the stored question-answer pairs, the meta-level features of a particular stored question-answer pair based at least in part on the meta-level features of a previous related stored question-answer pair and a first related stored question-answer pair; means for clarifying the inquiry based on follow-up procedures including asking follow-up questions; means for determining a plurality of responses to the inquiry based on the analysis of the stored question-answer pairs, the relationships among the stored question-answer pairs, and the follow-up procedures; means for providing the plurality of responses; means for receiving a selection of a particular response from among the plurality of responses; and means for storing a measure of the eligibility of the particular response to be a response to the inquiry based on the selection. 31. The system of claim 23 further comprising means for checking question-answer pair layouts on a web page of a site with other question-answer pair layouts on other web pages of the site. | 0.537634 |
8. The method of claim 1 , further comprising: applying a linguistic model to the new audio file; and using the application of the linguistic model to identify the specific speaker in the diarization of the new audio file. | 8. The method of claim 1 , further comprising: applying a linguistic model to the new audio file; and using the application of the linguistic model to identify the specific speaker in the diarization of the new audio file. 9. The method of claim 8 , further comprising: comparing an identification of the specific speaker based upon the acoustic voiceprint to an identification of the specific speaker based upon the linguistic model to select portions of each of the identifications in the diarization of the new audio file. | 0.922845 |
1. A method comprising: accessing a baseline language model that associates a respective baseline probability of occurrence with each of multiple different terms; obtaining information related to recent language usage from recent search queries that were submitted by multiple users of a search engine within a predetermined period of time; determining a quantity of occurrences of a particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; selectively modifying the baseline language model to independently revise the baseline probability of occurrence associated with the particular term based at least on the quantity of occurrences of the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time while maintaining unchanged a baseline probability of occurrence associated with a different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time by assigning a first probability to the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time that is greater than a second probability for the different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; and generating, by an automated speech recognizer using the modified language model, a transcription of one or more utterances of one or more different users of the search engine. | 1. A method comprising: accessing a baseline language model that associates a respective baseline probability of occurrence with each of multiple different terms; obtaining information related to recent language usage from recent search queries that were submitted by multiple users of a search engine within a predetermined period of time; determining a quantity of occurrences of a particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; selectively modifying the baseline language model to independently revise the baseline probability of occurrence associated with the particular term based at least on the quantity of occurrences of the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time while maintaining unchanged a baseline probability of occurrence associated with a different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time by assigning a first probability to the particular term in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time that is greater than a second probability for the different term that does not occur in the recent search queries that were submitted by the multiple users of the search engine within the predetermined period of time; and generating, by an automated speech recognizer using the modified language model, a transcription of one or more utterances of one or more different users of the search engine. 11. The method of claim 1 , wherein the language model includes weightings for co-concurrence events between two or more words. | 0.579746 |
34. The program storage device as recited in claim 26 , wherein the instructions for processing the extracted features using a behavior model include instructions for calculating a first probability representing a likelihood that the user is authorized to interact with the system based on the user's current interaction behavior. | 34. The program storage device as recited in claim 26 , wherein the instructions for processing the extracted features using a behavior model include instructions for calculating a first probability representing a likelihood that the user is authorized to interact with the system based on the user's current interaction behavior. 35. The program storage device as recited in claim 34 , wherein the first probability is compared to a threshold probability to determine if the user is authorized to use the system. | 0.884268 |
1. A method for translating stenographic strokes, the method comprising: receiving a series of stenographic strokes on a stenographic keyboard; creating a table of translations of one or more strokes within the series of strokes using a steno-to-text dictionary; sequentially assigning a score to each of the one or more strokes; determining at least one alternate translation to at least one of the translations in the table of translations, the at least one alternate translation determined using at least one of a phonetic matching algorithm and an approximate matching algorithm, the at least one alternate translation beginning with a first stroke in the series of stenographic strokes; ranking the translations and alternate translations based on an accumulation of the score of the strokes within; and selecting at least one of: one of the ranked translations; and one of the ranked alternate translations, based on a best score. | 1. A method for translating stenographic strokes, the method comprising: receiving a series of stenographic strokes on a stenographic keyboard; creating a table of translations of one or more strokes within the series of strokes using a steno-to-text dictionary; sequentially assigning a score to each of the one or more strokes; determining at least one alternate translation to at least one of the translations in the table of translations, the at least one alternate translation determined using at least one of a phonetic matching algorithm and an approximate matching algorithm, the at least one alternate translation beginning with a first stroke in the series of stenographic strokes; ranking the translations and alternate translations based on an accumulation of the score of the strokes within; and selecting at least one of: one of the ranked translations; and one of the ranked alternate translations, based on a best score. 8. The method according to claim 1 , wherein the approximate matching algorithm provides an improvement in accuracy by narrowing down a search space. | 0.706924 |
65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document. | 65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document. 69. The system of claim 65 , wherein said at least one software engine further comprising associate a second electronic document that is derived from a first electronic document, wherein said associate said second electronic document that is derived from said first electronic document comprising: a. generate a unique code, b. embed said unique code into said second electronic document, and c. embed said unique code into said first electronic document. | 0.516399 |
15. A system, comprising: a data store storing queries that were previously received from users and data identifying images that were referenced in search results responsive to the queries; and an image quality subsystem coupled to the data store, the image quality subsystem including at least one processor operable to compute, for a query, query specific quality scores for images based on initial quality scores for the images and a transformation factor for the query, the transformation factor for the query representing a measure of importance of image quality for computing relevance scores for the images for the query, the transformation factor being selected based, at least in part, on a comparison of a first number of previous user selections of high quality images for the query to a second number of previous user selections of high quality images for one or more other queries, a high quality image being an image having an initial quality score that meets a threshold score. | 15. A system, comprising: a data store storing queries that were previously received from users and data identifying images that were referenced in search results responsive to the queries; and an image quality subsystem coupled to the data store, the image quality subsystem including at least one processor operable to compute, for a query, query specific quality scores for images based on initial quality scores for the images and a transformation factor for the query, the transformation factor for the query representing a measure of importance of image quality for computing relevance scores for the images for the query, the transformation factor being selected based, at least in part, on a comparison of a first number of previous user selections of high quality images for the query to a second number of previous user selections of high quality images for one or more other queries, a high quality image being an image having an initial quality score that meets a threshold score. 16. The system of claim 15 , wherein the image quality subsystem is further operable to compute adjusted relevance score for the images based on the query specific quality scores and initial relevance scores for the images. | 0.623043 |
1. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the non-transitory computer readable storage medium, where executed by a processor, the computer usable code causes a computer to: receive a search query by a user that is to include a stated expectation with respect to a general product to be identified in the search query by a general product type; parse the search query to identify an intensifier that is to indicate a quality of interest to the user for the product and to distinguish between the product and the stated expectation; dynamically define an attribute for the product distinguished by the parse or a synonym thereof, wherein the defined attribute is to include the stated expectation distinguished by the parse or a synonym thereof; filter consumer generated content using the defined attribute to obtain one or more specific products to be identified in the search results by a manufacturer of the one or more specific products; rate the one or more specific products based on one or more opinions that are to mention the defined attribute to be expressed in the consumer generated content to identify in the search results closest matching specific products for the general product; and present the search results to the user including the closest matching specific products identified by the manufacturer. | 1. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the non-transitory computer readable storage medium, where executed by a processor, the computer usable code causes a computer to: receive a search query by a user that is to include a stated expectation with respect to a general product to be identified in the search query by a general product type; parse the search query to identify an intensifier that is to indicate a quality of interest to the user for the product and to distinguish between the product and the stated expectation; dynamically define an attribute for the product distinguished by the parse or a synonym thereof, wherein the defined attribute is to include the stated expectation distinguished by the parse or a synonym thereof; filter consumer generated content using the defined attribute to obtain one or more specific products to be identified in the search results by a manufacturer of the one or more specific products; rate the one or more specific products based on one or more opinions that are to mention the defined attribute to be expressed in the consumer generated content to identify in the search results closest matching specific products for the general product; and present the search results to the user including the closest matching specific products identified by the manufacturer. 4. The computer program product of claim 1 , wherein executed by a processor, the computer usable code causes a computer to filter the consumer generated content based on contextual information to obtain the one or more specific products. | 0.516838 |
5. The method according to claim 1 , further comprising: detecting vertical and horizontal lines in the document image; generating a graphic lines mask from the detected horizontal and vertical lines; and using the graphic lines mask from the vertical and horizontal lines, to segment the document image into horizontal and vertical graphic line fragments. | 5. The method according to claim 1 , further comprising: detecting vertical and horizontal lines in the document image; generating a graphic lines mask from the detected horizontal and vertical lines; and using the graphic lines mask from the vertical and horizontal lines, to segment the document image into horizontal and vertical graphic line fragments. 6. The method according to claim 5 , further comprising: generating a combined mask of the aligned text mask and the graphic lines mask by combining the aligned text mask and the graphic lines mask; and using the combined mask to segment the document image into remainder fragments, wherein the remainder fragments fall outside the bounds of lines of machine printed text or neatly written text. | 0.838735 |
1. An apparatus that is configured to transform an input data stream comprising spatio-temporal data that is expressed at least in part in a non-linguistic format into a format that can be expressed at least in part via a linguistic representation in a textual output, the apparatus comprising: a memory coupled to at least one processor; and the at least one processor, configured to: receive a set of eventualities, the set of eventualities describing at least one of a domain event and a domain state, the at least one of the domain event and the domain state derived from a set of spatio-temporal data and the set of eventualities associated with a particular region and a particular time period; organize the set of eventualities according to a domain model; wherein organizing the set of eventualities comprises determining an importance score for one or more of the set of eventualities using the domain model that comprises a set of importance rules for one or more of the set of eventualities, wherein the importance rules provide an importance score based on an externally specified importance value for an eventuality type, a number of spatial points in the eventuality, and a time period of the eventuality; organizing the set of eventualities based on the importance scores; and at least one of filtering out one or more eventualities, partitioning one or more of the set of eventualities into a portion of the particular region, and ordering the set of eventualities into a particular order; generate a document plan, wherein the document plan is generated based on the organized set of eventualities; instantiate the document plan with one or more messages that describe each eventuality of the organized set of eventualities; and generate a linguistic representation of the one or more messages using the document plan, wherein the linguistic representation of the one or more messages is displayable via a user interface. | 1. An apparatus that is configured to transform an input data stream comprising spatio-temporal data that is expressed at least in part in a non-linguistic format into a format that can be expressed at least in part via a linguistic representation in a textual output, the apparatus comprising: a memory coupled to at least one processor; and the at least one processor, configured to: receive a set of eventualities, the set of eventualities describing at least one of a domain event and a domain state, the at least one of the domain event and the domain state derived from a set of spatio-temporal data and the set of eventualities associated with a particular region and a particular time period; organize the set of eventualities according to a domain model; wherein organizing the set of eventualities comprises determining an importance score for one or more of the set of eventualities using the domain model that comprises a set of importance rules for one or more of the set of eventualities, wherein the importance rules provide an importance score based on an externally specified importance value for an eventuality type, a number of spatial points in the eventuality, and a time period of the eventuality; organizing the set of eventualities based on the importance scores; and at least one of filtering out one or more eventualities, partitioning one or more of the set of eventualities into a portion of the particular region, and ordering the set of eventualities into a particular order; generate a document plan, wherein the document plan is generated based on the organized set of eventualities; instantiate the document plan with one or more messages that describe each eventuality of the organized set of eventualities; and generate a linguistic representation of the one or more messages using the document plan, wherein the linguistic representation of the one or more messages is displayable via a user interface. 3. The apparatus of claim 1 , wherein the processor is further configured to organize the set of eventualities based on the importance by placing a most important eventuality first in the document plan. | 0.585206 |
13. The computer storage medium of claim 12 , further comprising instructions operable to perform operations including: receiving a search query; identifying resources responsive to the search query; generating initial search results identifying the resources responsive to the search query; filtering the initial search results based on resources corresponding to entries in the list to produce filtered search results; and presenting filtered search results in response to the received search query. | 13. The computer storage medium of claim 12 , further comprising instructions operable to perform operations including: receiving a search query; identifying resources responsive to the search query; generating initial search results identifying the resources responsive to the search query; filtering the initial search results based on resources corresponding to entries in the list to produce filtered search results; and presenting filtered search results in response to the received search query. 15. The computer storage medium of claim 13 , where filtering includes removing search results that do not match entries in the list. | 0.860046 |
9. A system, comprising: a host system computer; and an application executing on the host system computer, the application implementing a method, the method including: generating an ontological domain for an individual based upon information elements, the information elements representing aspects of detectable behaviors of the individual over time, at least a portion of the detectable behaviors being captured via user-generated input of the individual monitored by the host system computer, and at least another portion of the detectable behaviors being received from a source that is independent of the host system computer and absent any user-generated input of the individual, the generating the ontological domain comprising creating subdomains of contextually organized collections of the information elements by topic; comparing the information elements across the subdomains; determining orthogonal relationships of the information elements across topics indicated by the subdomains based on common features associated with the information elements; determining a relevance of orthogonal relationships among the information elements across the subdomains based on measurable aspects of the information elements with respect to frequency of occurrence, geolocation, time, or a combination thereof, wherein the orthogonal relationships determined to be relevant are identified as an interest of the individual; searching sources of information using the information elements having the orthogonal relationships determined to be relevant; and identifying a solution for satisfying the interest responsive to the searching. | 9. A system, comprising: a host system computer; and an application executing on the host system computer, the application implementing a method, the method including: generating an ontological domain for an individual based upon information elements, the information elements representing aspects of detectable behaviors of the individual over time, at least a portion of the detectable behaviors being captured via user-generated input of the individual monitored by the host system computer, and at least another portion of the detectable behaviors being received from a source that is independent of the host system computer and absent any user-generated input of the individual, the generating the ontological domain comprising creating subdomains of contextually organized collections of the information elements by topic; comparing the information elements across the subdomains; determining orthogonal relationships of the information elements across topics indicated by the subdomains based on common features associated with the information elements; determining a relevance of orthogonal relationships among the information elements across the subdomains based on measurable aspects of the information elements with respect to frequency of occurrence, geolocation, time, or a combination thereof, wherein the orthogonal relationships determined to be relevant are identified as an interest of the individual; searching sources of information using the information elements having the orthogonal relationships determined to be relevant; and identifying a solution for satisfying the interest responsive to the searching. 11. The system of claim 9 , wherein the searching sources of information further comprises: creating a search string from the information elements having the orthogonal relationships determined to be relevant; gathering data in response to the searching using the search string and comparing the data to the information elements having the orthogonal relationships determined to be relevant; and identifying matches between the data and the information elements having the orthogonal relationships determined to be relevant; wherein the solution is identified based on a threshold number of the matches. | 0.568639 |
16. A server computer, comprising: memory; a processor; and a program for composing a web page, wherein the program is stored in the memory and executed by the processor, the program including: instructions, which, when executed, transmit an authoring web page including an embedded authoring tool to a client computer of a publisher of the web page using a network, the authoring tool for composing the web page; and instructions, which, when executed, receive from the client computer web-page content corresponding to the composed web page, wherein the composed web page includes one or more advertisement regions that are placeholders designated for displaying one or more advertisements having one or more links to one or more content locations; wherein the composed web page is configured for display at run-time at respective clients of visitors who download the composed web page from a web page server; and wherein the one or more advertisement regions do not contain any of the web-page content. | 16. A server computer, comprising: memory; a processor; and a program for composing a web page, wherein the program is stored in the memory and executed by the processor, the program including: instructions, which, when executed, transmit an authoring web page including an embedded authoring tool to a client computer of a publisher of the web page using a network, the authoring tool for composing the web page; and instructions, which, when executed, receive from the client computer web-page content corresponding to the composed web page, wherein the composed web page includes one or more advertisement regions that are placeholders designated for displaying one or more advertisements having one or more links to one or more content locations; wherein the composed web page is configured for display at run-time at respective clients of visitors who download the composed web page from a web page server; and wherein the one or more advertisement regions do not contain any of the web-page content. 26. The server computer of claim 16 , wherein the web-page content includes one or more instances of predefined structured fields in the composed web page and associated field content within the one or more instances of the predefined structured fields. | 0.535572 |
3. The method of claim 1 , wherein determining the similarity relationship comprises: identifying an additional candidate security threat target that experienced a pair of actual security threat attacks; and determining that the specific candidate security threat target experienced one of the pair of actual security threat attacks. | 3. The method of claim 1 , wherein determining the similarity relationship comprises: identifying an additional candidate security threat target that experienced a pair of actual security threat attacks; and determining that the specific candidate security threat target experienced one of the pair of actual security threat attacks. 4. The method of claim 3 , wherein predicting that the specific candidate security threat target will experience the future security threat attack comprises predicting that the specific candidate security threat target will experience the other of the pair of actual security threat attacks. | 0.887152 |
2. The apparatus of claim 1 wherein said text is a transcript of said audio security disclosure data. | 2. The apparatus of claim 1 wherein said text is a transcript of said audio security disclosure data. 41. The apparatus of claim 2 wherein the insertion of said second marker in the text is based on statistics of contextual information. | 0.955853 |
9. The computer-implemented method of claim 1 , wherein the estimated box annotations of the given target object are generated further based on Kalman filtering applied to the video sequence. | 9. The computer-implemented method of claim 1 , wherein the estimated box annotations of the given target object are generated further based on Kalman filtering applied to the video sequence. 10. The computer-implemented method of claim 9 , wherein the Kalman filtering performs filtering using the set of already provided annotations and the optical flow information to output (i) a set of best estimated bounding boxes across each of the plurality of frames and (2) the annotation uncertainty measure for any of the plurality of frames that include one of the best estimated bounding boxes from the set. | 0.803045 |
15. A non-transitory computer-readable media encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving transaction information associated with user actions during use by a first user of a business intelligence tool, each user action associated with an operation in a particular stage of processing on business data obtained from one or more databases, the transaction information for a particular user action including: a user identifier identifying the first user performing the particular user action; stage information identifying the particular stage of the processing in which the particular user action occurs; the operation associated with the particular user action; and one or more parameters used in the operation; storing the transaction information; monitoring subsequent user actions by the first user in a current session, wherein monitoring subsequent user actions includes determining a time at which stage conditions associated with the current session for the first user match a portion of the stored transaction information corresponding to the first user and the stage information; and in response to determining that stage conditions exist in the stored transaction information that match the first user and the stage conditions of the current context: identifying pertinent transactions associated with the matching stage conditions; creating one or more suggestions for presentation to the first user, each suggestion of the one or more suggestions being associated with groups of one or more transactions of the pertinent transactions; and providing the one or more suggestions for presentation to the first user. | 15. A non-transitory computer-readable media encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving transaction information associated with user actions during use by a first user of a business intelligence tool, each user action associated with an operation in a particular stage of processing on business data obtained from one or more databases, the transaction information for a particular user action including: a user identifier identifying the first user performing the particular user action; stage information identifying the particular stage of the processing in which the particular user action occurs; the operation associated with the particular user action; and one or more parameters used in the operation; storing the transaction information; monitoring subsequent user actions by the first user in a current session, wherein monitoring subsequent user actions includes determining a time at which stage conditions associated with the current session for the first user match a portion of the stored transaction information corresponding to the first user and the stage information; and in response to determining that stage conditions exist in the stored transaction information that match the first user and the stage conditions of the current context: identifying pertinent transactions associated with the matching stage conditions; creating one or more suggestions for presentation to the first user, each suggestion of the one or more suggestions being associated with groups of one or more transactions of the pertinent transactions; and providing the one or more suggestions for presentation to the first user. 19. The non-transitory computer-readable media of claim 15 , the operations further comprising ranking the suggestions to produce ranked suggestions. | 0.617102 |
5. The method of claim 2 in which the step of determining which portions of document content are comprised in the second customized document but which are not comprised in the amended first customized document comprises the step of comparing the inclusion information associated with each document. | 5. The method of claim 2 in which the step of determining which portions of document content are comprised in the second customized document but which are not comprised in the amended first customized document comprises the step of comparing the inclusion information associated with each document. 6. The method of claim 5 comprising the further step of modifying the inclusion information associated with the amended first customized document to indicate that the portions of document content which have been copied from the second customized document are included in the amended first customized document. | 0.803055 |
1. A computer program product for XPath evaluation in an XML data repository, comprising: a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: generate a simple path file comprising an XML file by merging nodes of hierarchical architectures of a plurality of XML files in the data repository to form a hierarchical architecture, the simple path file including a tree-like structure for the hierarchical architecture comprising nodes corresponding to storage blocks in the data repository that store data from the plurality of XML files, each of at least one node in the hierarchical architecture of the simple path file corresponding to a plurality of nodes with at least two of the plurality of nodes from different ones of the plurality of XML files, and node names of nodes in the generated XML file are generated by recording tag information of respective nodes in the plurality of XML files in the data repository; store data in the data repository in an orderly manner according to each node in the hierarchical architecture of the simple path file; parse an input XPath query by applying the XPath query to the hierarchical architecture of the simple path file to generate an execution tree for the XPath query, wherein the execution tree includes a tree-like structure with nodes including identifiers referencing nodes in the hierarchical architecture of the simple path file for obtaining data; and execute the execution tree for the data repository to generate a final evaluation result by retrieving data of the plurality of XML files from the storage blocks in the data repository corresponding to the nodes of the hierarchical architecture of the simple path file referenced by the execution tree and combining the retrieved data to produce the final evaluation result. | 1. A computer program product for XPath evaluation in an XML data repository, comprising: a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: generate a simple path file comprising an XML file by merging nodes of hierarchical architectures of a plurality of XML files in the data repository to form a hierarchical architecture, the simple path file including a tree-like structure for the hierarchical architecture comprising nodes corresponding to storage blocks in the data repository that store data from the plurality of XML files, each of at least one node in the hierarchical architecture of the simple path file corresponding to a plurality of nodes with at least two of the plurality of nodes from different ones of the plurality of XML files, and node names of nodes in the generated XML file are generated by recording tag information of respective nodes in the plurality of XML files in the data repository; store data in the data repository in an orderly manner according to each node in the hierarchical architecture of the simple path file; parse an input XPath query by applying the XPath query to the hierarchical architecture of the simple path file to generate an execution tree for the XPath query, wherein the execution tree includes a tree-like structure with nodes including identifiers referencing nodes in the hierarchical architecture of the simple path file for obtaining data; and execute the execution tree for the data repository to generate a final evaluation result by retrieving data of the plurality of XML files from the storage blocks in the data repository corresponding to the nodes of the hierarchical architecture of the simple path file referenced by the execution tree and combining the retrieved data to produce the final evaluation result. 9. The computer program product according to claim 1 , wherein the simple path file includes the tree-like structure comprising a root node and child nodes. | 0.52968 |
15. A non-transitory computer readable storage medium storing at least executable code for learning by using excess capacity of a database system configured to operate at a limited capacity below its full capacity, wherein the database system includes one or more processors operable to process data stored in the database in a database environment, and wherein the executable code includes: executable code that learns about optimization of execution of one or more selected database queries that do not meet at least one performance criteria associated with a target performance for processing the one or more selected database queries with the limited capacity in the database environment; executable code that allows at least a portion of the excess capacity available to the database system to be used to perform one or more learning activities associated with learning about optimization of execution of the one or more selected database queries that do not meet at least one performance criteria in the database environment; and executable code that does not allow the at least one portion of the excess capacity available to the database system to be used to perform other activities not associated with the learning about optimization of execution of the one or more selected database queries in the database environment. | 15. A non-transitory computer readable storage medium storing at least executable code for learning by using excess capacity of a database system configured to operate at a limited capacity below its full capacity, wherein the database system includes one or more processors operable to process data stored in the database in a database environment, and wherein the executable code includes: executable code that learns about optimization of execution of one or more selected database queries that do not meet at least one performance criteria associated with a target performance for processing the one or more selected database queries with the limited capacity in the database environment; executable code that allows at least a portion of the excess capacity available to the database system to be used to perform one or more learning activities associated with learning about optimization of execution of the one or more selected database queries that do not meet at least one performance criteria in the database environment; and executable code that does not allow the at least one portion of the excess capacity available to the database system to be used to perform other activities not associated with the learning about optimization of execution of the one or more selected database queries in the database environment. 16. The non-transitory computer readable storage medium of claim 15 , wherein the one or more learning operations include one or more operations associated with learning based analysis for optimizing database queries of the database. | 0.581857 |
3. A computer-implemented method of selecting documents in a document collection in response to a query, the method comprising: receiving a query including a first phrase and a second phrase; retrieving a posting list of documents containing the first phrase; for each document in the posting list: accessing a list indicating related phrases of the first phrase that are present in the document, the first phrase predicting the occurrence of each of the related phrases in the document collection, wherein the first phrase predicts a related phrase based on a measure of an actual co-occurrence rate of the related phrase and the first phrase exceeding an expected co-occurrence rate of the related phrase and the first phrase in the document collection, the expected co-occurrence rate of the related phrase and the first phrase being a function of a plurality of occurrences of the related phrase and the first phrase in the document collection; responsive to the list of related phrases indicating that the second phrase is present in a document, selecting the document to include in a result to the query, without retrieving a posting list of documents containing the second phrase; and storing the selected documents in a memory as part of a search result. | 3. A computer-implemented method of selecting documents in a document collection in response to a query, the method comprising: receiving a query including a first phrase and a second phrase; retrieving a posting list of documents containing the first phrase; for each document in the posting list: accessing a list indicating related phrases of the first phrase that are present in the document, the first phrase predicting the occurrence of each of the related phrases in the document collection, wherein the first phrase predicts a related phrase based on a measure of an actual co-occurrence rate of the related phrase and the first phrase exceeding an expected co-occurrence rate of the related phrase and the first phrase in the document collection, the expected co-occurrence rate of the related phrase and the first phrase being a function of a plurality of occurrences of the related phrase and the first phrase in the document collection; responsive to the list of related phrases indicating that the second phrase is present in a document, selecting the document to include in a result to the query, without retrieving a posting list of documents containing the second phrase; and storing the selected documents in a memory as part of a search result. 6. The method of claim 3 , further comprising: storing the list of related phrases for a first phrase with respect to a document in a bit vector, wherein a bit of the bit vector is set for each related phrase of the first phrase that is present in the document, and a bit of the vector is unset for each related phrase of the first phrase that is not present in the document, wherein the bit vector has a numerical value; and scoring a selected document by determining an adjusted value of the bit vector according to the bits set for related phrases of the first phrase that are present in the document. | 0.5 |
8. A vehicle communication system, in communication with a nomadic device, comprising: for a processor configured to receive a language or country designation as part of a packet sent from a communication point to the nomadic device, the designation having been added to the packet by the communication point; and wherein the processor is further configured to set a local-language emergency database (LLED) as a basis for a vehicle-spoken language when placing emergency calls, wherein, if an emergency call is originated by the vehicle computing system, outgoing spoken communication produced by the vehicle computing system is performed based on words and/or phrases stored in the LLED. | 8. A vehicle communication system, in communication with a nomadic device, comprising: for a processor configured to receive a language or country designation as part of a packet sent from a communication point to the nomadic device, the designation having been added to the packet by the communication point; and wherein the processor is further configured to set a local-language emergency database (LLED) as a basis for a vehicle-spoken language when placing emergency calls, wherein, if an emergency call is originated by the vehicle computing system, outgoing spoken communication produced by the vehicle computing system is performed based on words and/or phrases stored in the LLED. 13. The system of claim 8 , wherein the processor is configured to determine a word or phrase to be communicated to an emergency operator from the vehicle computing system, look up the determined word or phrase in a lookup table to determine a corresponding sound bite to be played, and play the determined corresponding sound bite over an outgoing communication with an emergency operator, such that the sound bite communicates the determined phrase in the local language to the emergency operator. | 0.557515 |
10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: receive a natural language content upon which a reasoning operation is to be performed; generate a first parse representation of the natural language content by performing natural language processing on the natural language content; generate a logical parse of the first parse by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content; and perform a reasoning operation on the logical parse to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content, wherein the computer readable program further causes the data processing system to generate the first parse representation of the natural language content at least by: parsing the natural language content into one or more atomic logical terms that lack explicit or implicit logic; and connecting the one or more atomic logical terms by logical operators in the first parse representation to specify a logical relationship between the one or more atomic logical terms. | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: receive a natural language content upon which a reasoning operation is to be performed; generate a first parse representation of the natural language content by performing natural language processing on the natural language content; generate a logical parse of the first parse by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content; and perform a reasoning operation on the logical parse to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content, wherein the computer readable program further causes the data processing system to generate the first parse representation of the natural language content at least by: parsing the natural language content into one or more atomic logical terms that lack explicit or implicit logic; and connecting the one or more atomic logical terms by logical operators in the first parse representation to specify a logical relationship between the one or more atomic logical terms. 17. The computer program product of claim 10 , wherein the computer readable program further causes the data processing system to process each of the logical operators in the logical parse at least by processing logical OR operators first, processing logical AND operators second, and processing logical NOT operators last. | 0.632224 |
9. A method for identifying a set of identity attributes for determining the identity of an entity, the method comprising: identifying a particular name that occurs more often than other names in a set of documents; identifying a plurality of candidate identity attribute sets by analyzing the particular name and at least one document in the set of documents using a plurality of different processes that each identifies (i) a set of candidate identities corresponding to the particular name and (ii) a candidate identity attribute set for each identified candidate identity, wherein at least one of the different processes analyzes a stored plurality of identities to identify candidate identities having the particular name and that are related to an entity to which the at least one document is also related; for each candidate identity attribute set of the plurality of candidate identity attribute sets, calculating a relevance score for each candidate identity attribute in the set that measures a level of correspondence between the particular name and the candidate identity attribute; and identifying, based on the relevance scores calculated for the candidate identity attributes of the different candidate identity attribute sets, a particular candidate identity attribute set for a particular identity that corresponds to the particular name. | 9. A method for identifying a set of identity attributes for determining the identity of an entity, the method comprising: identifying a particular name that occurs more often than other names in a set of documents; identifying a plurality of candidate identity attribute sets by analyzing the particular name and at least one document in the set of documents using a plurality of different processes that each identifies (i) a set of candidate identities corresponding to the particular name and (ii) a candidate identity attribute set for each identified candidate identity, wherein at least one of the different processes analyzes a stored plurality of identities to identify candidate identities having the particular name and that are related to an entity to which the at least one document is also related; for each candidate identity attribute set of the plurality of candidate identity attribute sets, calculating a relevance score for each candidate identity attribute in the set that measures a level of correspondence between the particular name and the candidate identity attribute; and identifying, based on the relevance scores calculated for the candidate identity attributes of the different candidate identity attribute sets, a particular candidate identity attribute set for a particular identity that corresponds to the particular name. 10. The method of claim 9 , wherein identifying the plurality of candidate identity attribute sets comprises identifying a candidate identity attribute set based on a lexical analysis of the at least one document. | 0.581658 |
21. The apparatus according to claim 12 further comprising: a generator for generating an complex properties table having a node identifier field and a value field. | 21. The apparatus according to claim 12 further comprising: a generator for generating an complex properties table having a node identifier field and a value field. 22. The apparatus according to claim 21 , wherein said complex properties table further comprises a sub-property field. | 0.965628 |
26. The improvement of claim 25 wherein besides said voice source signal, said digital filters receive signals from a noise source means which generates signals representing air turbulence in the voice tract. | 26. The improvement of claim 25 wherein besides said voice source signal, said digital filters receive signals from a noise source means which generates signals representing air turbulence in the voice tract. 27. The improvement of claim 26 wherein said one noise source means comprises: an aspiration source means for generating signals representing air turbulence at the vocal cords; and a frication source means using frications from real speech for generating signals representing air turbulence in vocal cavities of the pharynx, mouth and nose. | 0.765746 |
54. A method of analyzing patent documents comprising the steps of: providing a dataset containing a plurality of patent documents; identifying within each patent document a portion of said document containing a set of claims; generating a first representation of each set of claims within said plurality of patent documents; and determining a first utility measure of at least one claim within at least one set of claims based upon similarity of said at least one claim with a query document. | 54. A method of analyzing patent documents comprising the steps of: providing a dataset containing a plurality of patent documents; identifying within each patent document a portion of said document containing a set of claims; generating a first representation of each set of claims within said plurality of patent documents; and determining a first utility measure of at least one claim within at least one set of claims based upon similarity of said at least one claim with a query document. 59. The method of claim 54 further comprising the step of parsing each set of claims to identify each individual claim within said each set and all claims referenced by said each individual claim. | 0.820447 |
1. A computer-implemented method comprising: obtaining, at a search system, a token sequence for a resource, wherein each token in the token sequence comprises one or more characters; selecting, at the search system, a particular token from the token sequence, wherein the particular token comprises two or more characters that comprise at least one numeric portion having at least one contiguous numeric character, and at least one non-numeric portion having at least one non-numeric character; generating, at the search system and for each of the at least one numeric portion that is not separately a token in the token sequence, a new token comprising the respective at least one numeric portion of the particular token without the at least one non-numeric portion of the particular token; and storing, in a search engine index, (i) data indicating the particular token and data indicating the new token as index terms for the resource, and (ii) data indicating that the particular token and the at least one numeric portion correspond to the same token in the resource. | 1. A computer-implemented method comprising: obtaining, at a search system, a token sequence for a resource, wherein each token in the token sequence comprises one or more characters; selecting, at the search system, a particular token from the token sequence, wherein the particular token comprises two or more characters that comprise at least one numeric portion having at least one contiguous numeric character, and at least one non-numeric portion having at least one non-numeric character; generating, at the search system and for each of the at least one numeric portion that is not separately a token in the token sequence, a new token comprising the respective at least one numeric portion of the particular token without the at least one non-numeric portion of the particular token; and storing, in a search engine index, (i) data indicating the particular token and data indicating the new token as index terms for the resource, and (ii) data indicating that the particular token and the at least one numeric portion correspond to the same token in the resource. 3. The method of claim 1 , further comprising: determining a relative position of each of the at least one numeric portion within the particular token; and storing data indicating the relative position of each of the at least one numeric portion. | 0.797541 |
1. A method for displaying geographic address element candidates at a user device, comprising: receiving a textual input from a user via an application; retrieving a profile metadata based on the textual input, wherein the profile metadata is generated based on data that is independent from the user, the profile metadata includes a total number of geographic street candidates in a first category and a total number of geographic street element candidates in a second category associated with the textual input, the geographic street element candidates are street attributes other than street candidates, and each of the total number is a positive integer greater than one; and generating a script based on the profile metadata for transmission of the script to the application, wherein the script is generated using the total number of the geographic street candidates in the first category when the total number of the geographic street candidates is less than or equal to a predetermined threshold that is a positive integer, and the script is generated using the geographic street element candidates in the second category when the total number of the geographic street candidates in the first category is more than the predetermined threshold, and the script executes auto-completion of information corresponding to the textual input using at least one of the geographic street element candidates in the second category to display the geographic address element candidates at the user device, wherein the textual input specifies geographic addressing information other than a geographic address element corresponding to the geographic address element candidates, and the script executes the auto-completion by displaying the geographic address element candidates prior to the user inputs any portion of the geographic address element. | 1. A method for displaying geographic address element candidates at a user device, comprising: receiving a textual input from a user via an application; retrieving a profile metadata based on the textual input, wherein the profile metadata is generated based on data that is independent from the user, the profile metadata includes a total number of geographic street candidates in a first category and a total number of geographic street element candidates in a second category associated with the textual input, the geographic street element candidates are street attributes other than street candidates, and each of the total number is a positive integer greater than one; and generating a script based on the profile metadata for transmission of the script to the application, wherein the script is generated using the total number of the geographic street candidates in the first category when the total number of the geographic street candidates is less than or equal to a predetermined threshold that is a positive integer, and the script is generated using the geographic street element candidates in the second category when the total number of the geographic street candidates in the first category is more than the predetermined threshold, and the script executes auto-completion of information corresponding to the textual input using at least one of the geographic street element candidates in the second category to display the geographic address element candidates at the user device, wherein the textual input specifies geographic addressing information other than a geographic address element corresponding to the geographic address element candidates, and the script executes the auto-completion by displaying the geographic address element candidates prior to the user inputs any portion of the geographic address element. 2. The method according to claim 1 , wherein the textual input specifies a portion of geographic addressing information, and the information that is auto-completed is a remaining portion of the geographic addressing information. | 0.595376 |
20. A device comprising: a processor; a communication interface operably coupled to the processor; and a computer-readable medium including computer-readable instructions stored therein that, upon execution by the processor, cause the processor to send a first menu list of words or phrases associated with a plurality of concepts to a device; receive a first selection of at least one of the words or phrases in the first menu list from the device, the received first selection identifying a concept for a query to be formed; identify a second menu list of words or phrases based at least in part on the received first selection; send the identified second menu list to the device; receive a second selection of at least one of the words or phrases in the second menu list from the device, the second selection identifying a first segment of the query; form the query as a natural language query based at least in part on the received first selection and the received second selection, wherein the natural language query does not include the identified concept; and provide a response to the query to the device. | 20. A device comprising: a processor; a communication interface operably coupled to the processor; and a computer-readable medium including computer-readable instructions stored therein that, upon execution by the processor, cause the processor to send a first menu list of words or phrases associated with a plurality of concepts to a device; receive a first selection of at least one of the words or phrases in the first menu list from the device, the received first selection identifying a concept for a query to be formed; identify a second menu list of words or phrases based at least in part on the received first selection; send the identified second menu list to the device; receive a second selection of at least one of the words or phrases in the second menu list from the device, the second selection identifying a first segment of the query; form the query as a natural language query based at least in part on the received first selection and the received second selection, wherein the natural language query does not include the identified concept; and provide a response to the query to the device. 21. The device of claim 20 , wherein the second menu list is dynamically generated based on the first selection. | 0.576597 |
11. A non-transitory computer-readable medium having stored thereon instructions that, when executed by at least one processor, cause a computing system to perform operations including: assigning each phrase identified in a document collection a phrase number based on frequency of occurrence of the phrase in the document collection, wherein each document has a respective document identifier; and creating a phrase-sharded index for a search engine by, for each identified phrase: assigning the phrase to a server of a plurality of index servers based on a hash of the assigned phrase number, and storing a posting list of identifiers of documents of the document collection that contain the phrase on the assigned index server; identifying, using the index, documents responsive to a search query; and providing information about the identified documents to a requestor of the search query. | 11. A non-transitory computer-readable medium having stored thereon instructions that, when executed by at least one processor, cause a computing system to perform operations including: assigning each phrase identified in a document collection a phrase number based on frequency of occurrence of the phrase in the document collection, wherein each document has a respective document identifier; and creating a phrase-sharded index for a search engine by, for each identified phrase: assigning the phrase to a server of a plurality of index servers based on a hash of the assigned phrase number, and storing a posting list of identifiers of documents of the document collection that contain the phrase on the assigned index server; identifying, using the index, documents responsive to a search query; and providing information about the identified documents to a requestor of the search query. 17. The computer-readable medium of claim 11 , wherein most frequently occurring phrases have lower phrase numbers. | 0.784188 |
4. The computer system of claim 1 , wherein the search results are based on a specified search attribute, and wherein the search result ranking is associated with the specified search attribute. | 4. The computer system of claim 1 , wherein the search results are based on a specified search attribute, and wherein the search result ranking is associated with the specified search attribute. 5. The computer system of claim 4 , wherein the tuning input is applied to a value associated with the search attribute. | 0.973206 |
7. The apparatus of claim 6 , wherein the apparatus is further caused to: determine that a communicating party has requested the conversion of the textual information. | 7. The apparatus of claim 6 , wherein the apparatus is further caused to: determine that a communicating party has requested the conversion of the textual information. 8. The apparatus of claim 7 , wherein the apparatus is further caused to: transmit one or more identifiers; and interact with the communicating party to receive the request for the conversion of the textual information. | 0.920195 |
1. A method comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; receiving the query from a user during a second time period that chronologically follows the plurality of time periods; obtaining search results responsive to the query; adjusting a ranking of the first search result in the obtained search results during the second time period; and providing the search results including the adjusted ranking of the first search result to the user. | 1. A method comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; receiving the query from a user during a second time period that chronologically follows the plurality of time periods; obtaining search results responsive to the query; adjusting a ranking of the first search result in the obtained search results during the second time period; and providing the search results including the adjusted ranking of the first search result to the user. 2. The method of claim 1 , wherein the adjustment of the ranking of the first search result is in proportion to a magnitude of a change of the historical click-through rate of the first search result relative to a change of the historical click-through rate of the second search result during the first time period. | 0.577003 |
26. A computer readable medium containing executable code for carrying out a method comprising: receiving text from the patent document, the text comprising a preamble and at least one substantive claim limitation, said at least one first substantive claim limitation recites a limitation to an invention; segmenting the preamble into at least one title phrase and at least one attribute phrase, wherein the attribute phrase comprises at least one second substantive claim limitation; and identifying an opening and a closing of the at least one substantive claim limitation to extract the substantive claim limitation from a remainder of the text; and displaying the preamble and the at least one first substantive claim limitation in a position indicating hierarchical subordination to the preamble. | 26. A computer readable medium containing executable code for carrying out a method comprising: receiving text from the patent document, the text comprising a preamble and at least one substantive claim limitation, said at least one first substantive claim limitation recites a limitation to an invention; segmenting the preamble into at least one title phrase and at least one attribute phrase, wherein the attribute phrase comprises at least one second substantive claim limitation; and identifying an opening and a closing of the at least one substantive claim limitation to extract the substantive claim limitation from a remainder of the text; and displaying the preamble and the at least one first substantive claim limitation in a position indicating hierarchical subordination to the preamble. 27. The computer readable medium of claim 26 , wherein identifying the opening and the closing further comprises storing the at least one first substantive claim limitation with an opening tag positioned at the opening and a closing tag positioned at the closing. | 0.741499 |
2. The method of claim 1 , wherein receiving the information associated with the focused-on item includes receiving the information associated with the focused-on item in a format associated with each of a plurality of media types, and further comprising providing access to the information associated with the focused-on item in the format associated with each of the plurality of media types via the displayed user interface. | 2. The method of claim 1 , wherein receiving the information associated with the focused-on item includes receiving the information associated with the focused-on item in a format associated with each of a plurality of media types, and further comprising providing access to the information associated with the focused-on item in the format associated with each of the plurality of media types via the displayed user interface. 3. The method of claim 2 , wherein providing access to the information associated with the focused-on item in the format associated with each of the plurality of media types includes providing an audio file that may be selected from the displayed user interface for providing the information associated with the focused-on item in audio format. | 0.912353 |
1. A mobile device for processing multi-modal natural language inputs, comprising: a conversational voice user interface that receives a multi-modal natural language input from a user, the multi-modal natural language input including a natural language utterance and a non-speech input, the conversational voice user interface coupled to a transcription module that transcribes the non-speech input to create a non-speech-based transcription; a conversational speech analysis engine that identifies the user that provided the multi-modal natural language input, the conversational speech analysis engine using a speech recognition engine and a semantic knowledge-based model to create a speech-based transcription of the natural language utterance, wherein the semantic knowledge-based model includes a personalized cognitive model derived from one or more prior interactions between the identified user and the mobile device, a general cognitive model derived from one or more prior interactions between a plurality of users and the mobile device, and an environmental model derived from an environment of the identified user and the mobile device; a merging module that merges the speech-based transcription and the non-speech-based transcription to create a merged transcription; a knowledge-enhanced speech recognition engine that identifies one or more entries in a context stack matching information contained in the merged transcription and determines a most likely context for the multi-modal natural language input based on the identified entries; and a response generating module that identifies a domain agent associated with the most likely context for the multi-modal input, communicates a request to the identified domain agent, and generates a response to the user from content provided by the identified domain agent as a result of processing the request. | 1. A mobile device for processing multi-modal natural language inputs, comprising: a conversational voice user interface that receives a multi-modal natural language input from a user, the multi-modal natural language input including a natural language utterance and a non-speech input, the conversational voice user interface coupled to a transcription module that transcribes the non-speech input to create a non-speech-based transcription; a conversational speech analysis engine that identifies the user that provided the multi-modal natural language input, the conversational speech analysis engine using a speech recognition engine and a semantic knowledge-based model to create a speech-based transcription of the natural language utterance, wherein the semantic knowledge-based model includes a personalized cognitive model derived from one or more prior interactions between the identified user and the mobile device, a general cognitive model derived from one or more prior interactions between a plurality of users and the mobile device, and an environmental model derived from an environment of the identified user and the mobile device; a merging module that merges the speech-based transcription and the non-speech-based transcription to create a merged transcription; a knowledge-enhanced speech recognition engine that identifies one or more entries in a context stack matching information contained in the merged transcription and determines a most likely context for the multi-modal natural language input based on the identified entries; and a response generating module that identifies a domain agent associated with the most likely context for the multi-modal input, communicates a request to the identified domain agent, and generates a response to the user from content provided by the identified domain agent as a result of processing the request. 12. The mobile device of claim 1 , wherein the identified domain agent processes the request by querying one or more local or network information sources. | 0.529975 |
9. An apparatus for discriminating among a first alphabetic form and a second alphabetic form and the numeric form of an alpha-numeric character field scanned by a character recognition machine, comprising: a character recognition machine adapted to scan the characters in a character field, to output on a first output line the alphabetic character of the aforesaid first alphabetic form which most nearly matches each character scaned, as of the aforesaid first alphabetic form for all characters scanned in said character field, to output on a second output line the alphabetic character of the aforesaid second alphabetic form which most nearly matches each character scanned, as of the aforesaid second alphabetic form for all characters scanned in said character field, and to output on a third output line a numeric character which most nearly matches each character scanned, as of a numeric form for all characters scanned in said character field; a storage means connected to said output lines, having stored therein a first type of conditional probability that a certain alphabetic character of the aforesaid first alphabetic form was inferred by the character recognition machine given that a certain alphabetic character of the aforesaid second alphabetic form and a certain numeric character were each scanned, for combinations of alphabetic characters with numeric characters, said storage means being sequentially accessed by corresponding character trios in said alphabetic and numeric fields on said output lines to yield the first type conditional probability that an alphabetic character of the aforesaid second alphabetic form on the second output line and that a numeric character on the third output line were each misread by the character recognition machine as the corresponding alphabetic character on the first output line; said storage means having stored therein a second type of conditional probability that a certain alphabetic character of the aforesaid second alphabetic form was inferred by the character recognition machine given that a certain alphabetic character of the aforesaid first character form and a certain numeric character were each scanned, for combinations of alphabetic characters with numeric characters, said storage means being sequentially accessed by corresponding character trios in said alphabetic and numeric fields on said output lines to yield the second type conditional probability that an alphabetic character of the aforesaid first alphabetic form on the first output line and that a numeric character on the third output line were each misread by the character recognition machine as the corresponding alphabetic character on the second output line; said storage means having stored therein a third type of conditional probability that a certain numeric character was inferred by the character recognition machine given that a certain alphabetic character of the aforesaid first form and that a certain alphabetic character of the aforesaid second alphabetic form were each scanned, for combinations of alphabetic characters with numeric characters, said storage means being sequentially accessed by correponding character trios in said alphabetic and numeric fields on said output lines to yield the third type conditional probability that the alphabetic characters on the first and second output lines were each misread by the character recognition machine as the corresponding numeric character on the third output line; a multiplier means having an input connected to said storage means for calculating a first product of all the first type conditional probabilities accessed from said storage means for said character field, said first product being a first total conditional probability that all alphabetic characters of the aforesaid second alphabetic form outputted on said second output line and that all numeric characters outputted on said third output line were each misread by the character recognition machine, for calculating a second product of all the second type conditional probabilities accessed from said storage means for said character field, said second product being a second total conditional probability that all alphabetic characters in the aforesaid first alphabetic form outputted on said first output line and that all numeric characters outputted on said third output line were each misread by the character recognition machine, and for calculating a third product of all the third type conditional probabilities accessed from said storage means, said third product being a third total conditional probability that the alphabetic characters outputted on said first and second output lines were each misread by the character recognition machine; a comparator connected to said multiplier means for comparing the magnitudes of said first, second and third total conditional probabilities and outputting an indication that the scanned character field is alphabetic of the aforesaid first alphabetic form when said first total conditional probability is greater than said second or third total conditional probabilities, and is alphabetic of the aforesaid second alphabetic form when said second total conditional probability is greater than said first or third total conditional probabilities, and is numeric when said third total conditional probability is greater than said first or second total conditional probabilities. | 9. An apparatus for discriminating among a first alphabetic form and a second alphabetic form and the numeric form of an alpha-numeric character field scanned by a character recognition machine, comprising: a character recognition machine adapted to scan the characters in a character field, to output on a first output line the alphabetic character of the aforesaid first alphabetic form which most nearly matches each character scaned, as of the aforesaid first alphabetic form for all characters scanned in said character field, to output on a second output line the alphabetic character of the aforesaid second alphabetic form which most nearly matches each character scanned, as of the aforesaid second alphabetic form for all characters scanned in said character field, and to output on a third output line a numeric character which most nearly matches each character scanned, as of a numeric form for all characters scanned in said character field; a storage means connected to said output lines, having stored therein a first type of conditional probability that a certain alphabetic character of the aforesaid first alphabetic form was inferred by the character recognition machine given that a certain alphabetic character of the aforesaid second alphabetic form and a certain numeric character were each scanned, for combinations of alphabetic characters with numeric characters, said storage means being sequentially accessed by corresponding character trios in said alphabetic and numeric fields on said output lines to yield the first type conditional probability that an alphabetic character of the aforesaid second alphabetic form on the second output line and that a numeric character on the third output line were each misread by the character recognition machine as the corresponding alphabetic character on the first output line; said storage means having stored therein a second type of conditional probability that a certain alphabetic character of the aforesaid second alphabetic form was inferred by the character recognition machine given that a certain alphabetic character of the aforesaid first character form and a certain numeric character were each scanned, for combinations of alphabetic characters with numeric characters, said storage means being sequentially accessed by corresponding character trios in said alphabetic and numeric fields on said output lines to yield the second type conditional probability that an alphabetic character of the aforesaid first alphabetic form on the first output line and that a numeric character on the third output line were each misread by the character recognition machine as the corresponding alphabetic character on the second output line; said storage means having stored therein a third type of conditional probability that a certain numeric character was inferred by the character recognition machine given that a certain alphabetic character of the aforesaid first form and that a certain alphabetic character of the aforesaid second alphabetic form were each scanned, for combinations of alphabetic characters with numeric characters, said storage means being sequentially accessed by correponding character trios in said alphabetic and numeric fields on said output lines to yield the third type conditional probability that the alphabetic characters on the first and second output lines were each misread by the character recognition machine as the corresponding numeric character on the third output line; a multiplier means having an input connected to said storage means for calculating a first product of all the first type conditional probabilities accessed from said storage means for said character field, said first product being a first total conditional probability that all alphabetic characters of the aforesaid second alphabetic form outputted on said second output line and that all numeric characters outputted on said third output line were each misread by the character recognition machine, for calculating a second product of all the second type conditional probabilities accessed from said storage means for said character field, said second product being a second total conditional probability that all alphabetic characters in the aforesaid first alphabetic form outputted on said first output line and that all numeric characters outputted on said third output line were each misread by the character recognition machine, and for calculating a third product of all the third type conditional probabilities accessed from said storage means, said third product being a third total conditional probability that the alphabetic characters outputted on said first and second output lines were each misread by the character recognition machine; a comparator connected to said multiplier means for comparing the magnitudes of said first, second and third total conditional probabilities and outputting an indication that the scanned character field is alphabetic of the aforesaid first alphabetic form when said first total conditional probability is greater than said second or third total conditional probabilities, and is alphabetic of the aforesaid second alphabetic form when said second total conditional probability is greater than said first or third total conditional probabilities, and is numeric when said third total conditional probability is greater than said first or second total conditional probabilities. 10. The apparatus of claim 9 which further comprises: a gating means having data inputs connected to said output lines, a control input connected to the output of said comparator and an output connected to a fourth output line for selectively transmitting to said fourth output line the alphabetic field of the aforesaid first alphabetic form outputted on said first output line when said comparator indicates the character field to be of the aforesaid first alphabetic form, for selectively transmitting to said fourth output line the alphabetic field of the aforesaid second alphabetic form outputted on said second output line when said comparator indicates the character field to be of the aforesaid second alphabetic form, and for selectively transmitting to said fourth output line the numeric field outputted on said third output line when said comparator indicates said scanned character field is numeric. | 0.53818 |
9. A computer program product stored on a non-transitory computer-readable medium that when executed by a processor, performs a method of providing a structured topic drift for a displayed set of user comments on an article, comprising: determining an ordered sequence of topical recommendations based on one or more properties of the displayed set of user comments and user characteristics using a sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the ordered sequence to produce a set of one or more user comments; appending, one by one, the one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments; and updating the sequential recommendation model based on a user response to the one or more user comments for each of the topical recommendations; determining a second ordered sequence of topical recommendations using the sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the second ordered sequence to produce a second set of one or more user comments; and appending, one by one, the second set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments. | 9. A computer program product stored on a non-transitory computer-readable medium that when executed by a processor, performs a method of providing a structured topic drift for a displayed set of user comments on an article, comprising: determining an ordered sequence of topical recommendations based on one or more properties of the displayed set of user comments and user characteristics using a sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the ordered sequence to produce a set of one or more user comments; appending, one by one, the one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments; and updating the sequential recommendation model based on a user response to the one or more user comments for each of the topical recommendations; determining a second ordered sequence of topical recommendations using the sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the second ordered sequence to produce a second set of one or more user comments; and appending, one by one, the second set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments. 14. The computer program product as claimed in claim 9 , wherein the one or more user comments for each of the topical recommendations are sampled based on a ranking. | 0.68911 |
13. The method of claim 1 comprising selecting one or more captions and subtitles from the one or more segments. | 13. The method of claim 1 comprising selecting one or more captions and subtitles from the one or more segments. 16. The method of claim 13 comprising: querying an index maintaining one or more index entries identifying terms and phrases associated with the selected captions and subtitles from the one or more segments; retrieving the one or more terms and phrases associated with the selected captions and subtitles; and generating one or more descriptions of the video and audio content corresponding to the selected captions and subtitles using the one or more retrieved terms and phrases. | 0.747917 |
23. A method of generating attribute models for use in a navigation system in a vehicle, the method comprising: for each of a plurality of driving sessions, during which the user travelled over a plurality of road segments in the vehicle: collecting sensor data of the vehicle for each of the plurality road segments travelled during a driving session; and associating the sensor data with at least one of a plurality of conditions, each condition descriptive of the driving session at the time the user travelled on the road segment; for each of the plurality of road segments, determining a value of a road familiarity of the road segment based upon the sensor data collected for that road segment, and associated with at least one of the conditions; and for each of the plurality of conditions, storing the values of the road familiarity in a conditional variant model associated with the condition. | 23. A method of generating attribute models for use in a navigation system in a vehicle, the method comprising: for each of a plurality of driving sessions, during which the user travelled over a plurality of road segments in the vehicle: collecting sensor data of the vehicle for each of the plurality road segments travelled during a driving session; and associating the sensor data with at least one of a plurality of conditions, each condition descriptive of the driving session at the time the user travelled on the road segment; for each of the plurality of road segments, determining a value of a road familiarity of the road segment based upon the sensor data collected for that road segment, and associated with at least one of the conditions; and for each of the plurality of conditions, storing the values of the road familiarity in a conditional variant model associated with the condition. 24. The method of claim 23 , wherein at least one of the plurality of conditions is from a group consisting of a level of user hurriedness, an environmental condition, and a level of traffic. | 0.636364 |
1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a first search request comprising a first search argument indicative of desired information; correlating, using at least one non-precise technique, the first search argument and the user profile data to first particular information in a database; providing the first particular information to the user as a first search result; updating the user profile data based on at least one of the first search argument, user selection of certain of the first particular information in the first search result, and user non-selection of certain of the first particular information in the first search result; receiving from the user a subsequent search request comprising a subsequent search argument indicative of the desired information; correlating, using the at least one non-precise technique, the received subsequent search argument and the updated user profile data to subsequent particular information in the database to provide a subsequent search result; and providing the subsequent search result to the user. | 1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a first search request comprising a first search argument indicative of desired information; correlating, using at least one non-precise technique, the first search argument and the user profile data to first particular information in a database; providing the first particular information to the user as a first search result; updating the user profile data based on at least one of the first search argument, user selection of certain of the first particular information in the first search result, and user non-selection of certain of the first particular information in the first search result; receiving from the user a subsequent search request comprising a subsequent search argument indicative of the desired information; correlating, using the at least one non-precise technique, the received subsequent search argument and the updated user profile data to subsequent particular information in the database to provide a subsequent search result; and providing the subsequent search result to the user. 13. The method of claim 1 , wherein the database is a contextual database. | 0.558659 |
21. The computer program of claim 20 , wherein each standard text type comprises: a standard text technology; and publishing characteristics. | 21. The computer program of claim 20 , wherein each standard text type comprises: a standard text technology; and publishing characteristics. 22. The computer program of claim 21 , wherein the standard text technology is selected from the group consisting of flat text, HyperText Markup Language (HTML), Extensible Markup Language (XML), and a Uniform Resource Locator (URL). | 0.933182 |
15. A computer program product stored in a non-transitory computer readable medium, comprising computer instructions that, when executed by an information handling system, causes the information handling system to perform actions comprising: identifying an expansion clause within a Structured Query Language (SQL) statement, wherein the SQL statement identifies a relational database table; comparing one or more column attributes associated with the identified relational database table to one or more attributes included in the identified expansion clause; selecting one or more columns included in the relational database table based on the comparison; generating a plurality of SQL column selection statements, with each of the generated SQL column selection statements corresponding to a different one of the selected one or more columns; and including the generated SQL column selection statements in the SQL statement. | 15. A computer program product stored in a non-transitory computer readable medium, comprising computer instructions that, when executed by an information handling system, causes the information handling system to perform actions comprising: identifying an expansion clause within a Structured Query Language (SQL) statement, wherein the SQL statement identifies a relational database table; comparing one or more column attributes associated with the identified relational database table to one or more attributes included in the identified expansion clause; selecting one or more columns included in the relational database table based on the comparison; generating a plurality of SQL column selection statements, with each of the generated SQL column selection statements corresponding to a different one of the selected one or more columns; and including the generated SQL column selection statements in the SQL statement. 19. The computer program product of claim 15 wherein the actions further comprise: identifying one or more naming attributes included in the identified expansion clause; comparing the identified naming attributes to one or more column names corresponding to the selected columns, the comparing resulting in one or more renamed columns; generating an SQL AS clause corresponding to each of the renamed columns wherein each of the SQL AS clauses includes a new name derived from one of the identified naming attributes; and modifying each of the generated plurality of SQL column selection statements corresponding to each of the renamed columns by adding the respective SQL AS clause. | 0.512456 |
1. A non-transitory computer readable medium comprising computer executable instructions stored thereon to cause one or more processing units of a processing device to: obtain a first plurality of unencrypted documents, wherein each document in the first plurality of unencrypted documents comprises: a Small Index of tags based, at least in part, on a content of the respective document; and a Large Index of tags based, at least in part, on a predictive analysis of the tags in the Small Index of the respective document; obtain a second encrypted document, wherein the second encrypted document comprises a Small Index of tags based, at least in part, on a content of the second encrypted document; create one or more associations between the second encrypted document and one or more documents of the first plurality of unencrypted documents based, at least in part, on the Small Index of tags of the second encrypted document and the respective Small Index of tags of the one or more of the first plurality of unencrypted documents; generate a Large Index of tags for the second encrypted document based, at least in part, on a predictive analysis of the tags in the Small Index of tags of the second encrypted document; augment the Large Index of tags for the second encrypted document based, at least in part, on the respective Large Index of tags for the one or more associated documents of the first plurality of unencrypted documents; receive a query from a first user, wherein the query matches at least one tag in the augmented Large Index of tags for the second encrypted document; and generate a result set of documents in response to the received query, wherein the result set comprises the second encrypted document. | 1. A non-transitory computer readable medium comprising computer executable instructions stored thereon to cause one or more processing units of a processing device to: obtain a first plurality of unencrypted documents, wherein each document in the first plurality of unencrypted documents comprises: a Small Index of tags based, at least in part, on a content of the respective document; and a Large Index of tags based, at least in part, on a predictive analysis of the tags in the Small Index of the respective document; obtain a second encrypted document, wherein the second encrypted document comprises a Small Index of tags based, at least in part, on a content of the second encrypted document; create one or more associations between the second encrypted document and one or more documents of the first plurality of unencrypted documents based, at least in part, on the Small Index of tags of the second encrypted document and the respective Small Index of tags of the one or more of the first plurality of unencrypted documents; generate a Large Index of tags for the second encrypted document based, at least in part, on a predictive analysis of the tags in the Small Index of tags of the second encrypted document; augment the Large Index of tags for the second encrypted document based, at least in part, on the respective Large Index of tags for the one or more associated documents of the first plurality of unencrypted documents; receive a query from a first user, wherein the query matches at least one tag in the augmented Large Index of tags for the second encrypted document; and generate a result set of documents in response to the received query, wherein the result set comprises the second encrypted document. 7. The non-transitory computer readable medium of claim 1 , further comprising instructions to: augment the Small Index of tags for the second encrypted document based, at least in part, on the respective Small Index of tags for the one or more associated documents of the first plurality of unencrypted documents. | 0.621622 |
1. A portable electronic system comprising: a processor; a bus coupled to said processor; an electronic display device coupled to said bus; a memory device coupled to said bus; and a user removable data input device providing a plurality of different methods of data input to the portable electronic system coupled to said bus, said user removable data input device comprising: a data input surface for detecting a gesture performed thereon by a user and for facilitating recognition of said gesture as corresponding to a particular data input, wherein said data input surface is responsive to a touch thereon and is in a location relative to a perimeter of said electronic display device that is spaced from the electronic display device, wherein said data input surface has one of a plurality of marking configurations, wherein each marking configuration facilitates operating said data input surface in one of a plurality of functional configurations, wherein said data input surface includes a first data input area and a second data input area, wherein said first data input area is configured to facilitate recognition of one or more first gestures, and wherein said second data input area is configured to facilitate recognition of one or more second gestures associated with one of said functional configurations, and wherein said user removable data input device is configured to couple to said portable electronic system and to uncouple from said portable electronic system. | 1. A portable electronic system comprising: a processor; a bus coupled to said processor; an electronic display device coupled to said bus; a memory device coupled to said bus; and a user removable data input device providing a plurality of different methods of data input to the portable electronic system coupled to said bus, said user removable data input device comprising: a data input surface for detecting a gesture performed thereon by a user and for facilitating recognition of said gesture as corresponding to a particular data input, wherein said data input surface is responsive to a touch thereon and is in a location relative to a perimeter of said electronic display device that is spaced from the electronic display device, wherein said data input surface has one of a plurality of marking configurations, wherein each marking configuration facilitates operating said data input surface in one of a plurality of functional configurations, wherein said data input surface includes a first data input area and a second data input area, wherein said first data input area is configured to facilitate recognition of one or more first gestures, and wherein said second data input area is configured to facilitate recognition of one or more second gestures associated with one of said functional configurations, and wherein said user removable data input device is configured to couple to said portable electronic system and to uncouple from said portable electronic system. 7. An electronic system as recited in claim 1 wherein said electronic system comprises a first module and a second module, wherein said first module includes said electronic display device, and wherein said second module includes said user removable data input device. | 0.5 |
7. A computer-readable storage medium encoded with a plurality of instructions that, when executed by at least one computer, perform a method of searching for content to display and/or playback on a digitally-tunable electronic device configured to display scheduled programming content, the method comprising: receiving a search query from a user, wherein the search query comprises a search for the content to display and/or playback on the electronic device, wherein the search query comprises voice input; determining, based on the search query, an action the user wants to perform, wherein the action is related to the display and/or playback of content specified in the search query; determining from among a plurality of data sources, at least two data sources to search based, at least in part, on the action the user wants to perform; storing one or more rules associating a particular type of action with a particular order for searching the at least two data sources; and searching based, at least in part, on the search query, the at least two data sources for the content to display and/or playback on the electronic device, wherein searching the at least two data sources comprises searching the at least two data sources in the particular order specified by the one or more rules. | 7. A computer-readable storage medium encoded with a plurality of instructions that, when executed by at least one computer, perform a method of searching for content to display and/or playback on a digitally-tunable electronic device configured to display scheduled programming content, the method comprising: receiving a search query from a user, wherein the search query comprises a search for the content to display and/or playback on the electronic device, wherein the search query comprises voice input; determining, based on the search query, an action the user wants to perform, wherein the action is related to the display and/or playback of content specified in the search query; determining from among a plurality of data sources, at least two data sources to search based, at least in part, on the action the user wants to perform; storing one or more rules associating a particular type of action with a particular order for searching the at least two data sources; and searching based, at least in part, on the search query, the at least two data sources for the content to display and/or playback on the electronic device, wherein searching the at least two data sources comprises searching the at least two data sources in the particular order specified by the one or more rules. 8. The computer-readable storage medium of claim 7 , wherein determining the action the user wants to perform comprises determining that the user wants to listen to media content, and wherein determining at least two data sources to search comprises determining a music data source as at least one of the at least two data sources. | 0.526975 |
11. A system, comprising: an interface operable to provide a list of a plurality of users of a network and respective presence information regarding each of the plurality of users; a processor operable to: prior to establishing a communication connection between an endpoint and a particular user of the plurality of users, receive a request from the endpoint to receive an audio representation of a name of the particular user of the plurality of users; and after the audio representation is provided to the endpoint, receive a request from the endpoint to establish the communication connection with the particular user; a transmission module operable to provide the audio representation to the endpoint; and wherein the audio representation of the name at least generally approximates a pronunciation of the name as pronounced by the particular user; and wherein the processor is further operable to receive a request from the endpoint to receive an audio representation of a name of the particular user of the plurality of users by receiving notification that an icon associated with the particular user has been selected from a plurality of icons. | 11. A system, comprising: an interface operable to provide a list of a plurality of users of a network and respective presence information regarding each of the plurality of users; a processor operable to: prior to establishing a communication connection between an endpoint and a particular user of the plurality of users, receive a request from the endpoint to receive an audio representation of a name of the particular user of the plurality of users; and after the audio representation is provided to the endpoint, receive a request from the endpoint to establish the communication connection with the particular user; a transmission module operable to provide the audio representation to the endpoint; and wherein the audio representation of the name at least generally approximates a pronunciation of the name as pronounced by the particular user; and wherein the processor is further operable to receive a request from the endpoint to receive an audio representation of a name of the particular user of the plurality of users by receiving notification that an icon associated with the particular user has been selected from a plurality of icons. 12. The system of claim 11 , wherein the audio representation comprises a voiceprint of the name that was recorded by the particular user. | 0.630469 |
1. A computer-implemented method, comprising: for each one of a plurality of documents, identifying a plurality of queries which resulted in user selection of the one of the plurality of documents from among search results provided in response to the queries; identifying itemsets within the queries, at least some of the itemsets representing recurring patterns in the queries; for each one of the plurality of documents, generating a representation of the corresponding one of the plurality of documents, wherein the representation of the one of the plurality of documents is generated based, at least in part, upon the itemsets identified within the corresponding queries which resulted in user selection of the document from among the search results provided in response to the corresponding queries; and for each one of the plurality of documents, classifying the one of the plurality of documents using the corresponding representation; wherein, for each one of the plurality of documents, the representation of the one of the plurality of documents comprises a vector including a plurality of scalar values, each scalar value representing a frequency with which a represented one of the itemsets appears within the corresponding queries. | 1. A computer-implemented method, comprising: for each one of a plurality of documents, identifying a plurality of queries which resulted in user selection of the one of the plurality of documents from among search results provided in response to the queries; identifying itemsets within the queries, at least some of the itemsets representing recurring patterns in the queries; for each one of the plurality of documents, generating a representation of the corresponding one of the plurality of documents, wherein the representation of the one of the plurality of documents is generated based, at least in part, upon the itemsets identified within the corresponding queries which resulted in user selection of the document from among the search results provided in response to the corresponding queries; and for each one of the plurality of documents, classifying the one of the plurality of documents using the corresponding representation; wherein, for each one of the plurality of documents, the representation of the one of the plurality of documents comprises a vector including a plurality of scalar values, each scalar value representing a frequency with which a represented one of the itemsets appears within the corresponding queries. 6. The method of claim 1 wherein the documents comprise web pages. | 0.666399 |
1. A method performed by data processing apparatus, the method comprising: identifying one or more queries that were received with a reference to a given factual entity, wherein the one or more queries identified for the given factual entity are different from one or more queries identified for one or more other factual entities; identifying one or more resources related to the given query; obtaining search results that are responsive to a received query; determining that the given factual entity is referenced by the received query; identifying a type of entity for the given factual entity; identifying, from a set of different knowledge panel templates, a knowledge panel template specified for the type of entity, the identified knowledge panel template including placeholders for content relevant to the type of entity; selecting, from the one or more resources related to the given factual entity, content for display in a knowledge panel for the given factual entity, the selected content including a first content item obtained from a first resource and a second content item obtained from a second resource different than the first resource, each given content item of the selected content being selected based on a number of the one or more received queries that reference both (i) the given factual entity and (ii) information presented by the given content item; generating the knowledge panel for the given factual entity by populating the placeholders of the identified knowledge panel template with the selected content; and providing data that causes the identified search results and the knowledge panel to be presented on a search results page, the knowledge panel presenting the selected content in a knowledge panel area alongside at least a portion of the search results. | 1. A method performed by data processing apparatus, the method comprising: identifying one or more queries that were received with a reference to a given factual entity, wherein the one or more queries identified for the given factual entity are different from one or more queries identified for one or more other factual entities; identifying one or more resources related to the given query; obtaining search results that are responsive to a received query; determining that the given factual entity is referenced by the received query; identifying a type of entity for the given factual entity; identifying, from a set of different knowledge panel templates, a knowledge panel template specified for the type of entity, the identified knowledge panel template including placeholders for content relevant to the type of entity; selecting, from the one or more resources related to the given factual entity, content for display in a knowledge panel for the given factual entity, the selected content including a first content item obtained from a first resource and a second content item obtained from a second resource different than the first resource, each given content item of the selected content being selected based on a number of the one or more received queries that reference both (i) the given factual entity and (ii) information presented by the given content item; generating the knowledge panel for the given factual entity by populating the placeholders of the identified knowledge panel template with the selected content; and providing data that causes the identified search results and the knowledge panel to be presented on a search results page, the knowledge panel presenting the selected content in a knowledge panel area alongside at least a portion of the search results. 11. The method of claim 1 , wherein the identified knowledge panel template specified for a given type of entity includes a placeholder for a first type of content item and each other knowledge panel template of the set of different knowledge panel templates does not include a placeholder for the first type of content item. | 0.799261 |
1. A method for storing, on a cloud storage site, a secondary copy of an original data set, the method comprising: receiving, with a computing device, a primary copy of an original data set; updating, with the computing device, a content index to reflect at least some of data content in the original data set; identifying, with the computing device, a target cloud storage site on which to store a secondary copy of the original data set, wherein a network connection is to be established between the target cloud storage site and a media file system agent, and wherein the established network connection has an associated latency and bandwidth; determining, with the computing device, a size for a container file to utilize when deduplicating the primary copy of the original data set, wherein the container file size is determined at least in part on the latency, bandwidth, or both, associated with the network connection to be established; deduplicating, with the computing device, at least some of the data content in the primary copy in order to create one or more container files containing deduplicated data, wherein at least one of the container files has the determined size; establishing, with the computing device, the network connection between the target cloud storage site and the media file system agent; and transferring, with the computing device, the one or more container files to the target cloud storage site. | 1. A method for storing, on a cloud storage site, a secondary copy of an original data set, the method comprising: receiving, with a computing device, a primary copy of an original data set; updating, with the computing device, a content index to reflect at least some of data content in the original data set; identifying, with the computing device, a target cloud storage site on which to store a secondary copy of the original data set, wherein a network connection is to be established between the target cloud storage site and a media file system agent, and wherein the established network connection has an associated latency and bandwidth; determining, with the computing device, a size for a container file to utilize when deduplicating the primary copy of the original data set, wherein the container file size is determined at least in part on the latency, bandwidth, or both, associated with the network connection to be established; deduplicating, with the computing device, at least some of the data content in the primary copy in order to create one or more container files containing deduplicated data, wherein at least one of the container files has the determined size; establishing, with the computing device, the network connection between the target cloud storage site and the media file system agent; and transferring, with the computing device, the one or more container files to the target cloud storage site. 10. The method of claim 1 , wherein identifying the target cloud storage site on which to store the secondary copy further comprises selecting a cloud storage site based at least in part on an operator of the cloud storage site having operations in a developing country. | 0.913197 |
1. A computer-readable storage medium storing executable instructions for configuring a computing appliance, which, when executed, performs an operation for refining asset classifications, the operation comprising: receiving a plurality of assets, each asset having a classification of a term, wherein each term is selected from a business glossary which provides a hierarchy of controlled vocabulary of terms used within an organization and wherein each asset is characterized using a set of attributes selected from a domain ontology; and upon determining a first term assigned to a first one of the assets satisfies a set of refinement criteria, refining the classification of the first asset by assigning the first asset a second term from the business glossary, wherein the second term is more precise in the business glossary than the first term and wherein the refinement criteria includes: determining that the term of a second one of the assets comprises a descendent of the classification of the first asset, and determining that each attribute of the first asset is at a lower level in the domain ontology than a corresponding attribute in the second asset. | 1. A computer-readable storage medium storing executable instructions for configuring a computing appliance, which, when executed, performs an operation for refining asset classifications, the operation comprising: receiving a plurality of assets, each asset having a classification of a term, wherein each term is selected from a business glossary which provides a hierarchy of controlled vocabulary of terms used within an organization and wherein each asset is characterized using a set of attributes selected from a domain ontology; and upon determining a first term assigned to a first one of the assets satisfies a set of refinement criteria, refining the classification of the first asset by assigning the first asset a second term from the business glossary, wherein the second term is more precise in the business glossary than the first term and wherein the refinement criteria includes: determining that the term of a second one of the assets comprises a descendent of the classification of the first asset, and determining that each attribute of the first asset is at a lower level in the domain ontology than a corresponding attribute in the second asset. 6. The computer-readable storage medium of claim 1 , wherein the operation further comprises, training a machine learning classifier based on the classifications assigned to the plurality of assets and further based on the refined classification assigned to the first asset. | 0.540816 |
28. The communication system of claim 26 wherein the captioned device is configured to establish communication with the hard of hearing user's phone device in response to a user input. | 28. The communication system of claim 26 wherein the captioned device is configured to establish communication with the hard of hearing user's phone device in response to a user input. 29. The communication system of claim 28 wherein the captioned device further comprises a button and wherein the captioned device is further configured to receive the hearing user's voice signal responsive to a detection of a user selecting the button. | 0.875104 |
17. A storage medium have instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client. | 17. A storage medium have instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client. 23. The storage medium of claim 17 wherein the graphical user interface presented on the client is for a spreadsheet application, a word processor application, or an email application. | 0.5 |
1. A method on a first computing device for determining a set of keywords associated with a document for use as suggested search terms, comprising: receiving from a second computing device via a network a document to classify into a taxonomy, the taxonomy including a plurality of categories, each category of the plurality of categories being represented by a concatenation of a corresponding set of documents; determining a categorization ranking for each category of the plurality of categories for the received document; determining a set of categories of the taxonomy having highest categorization rankings of the plurality of categories for the received document; combining together, using one or more processors, the documents representing the categories of the determined set of categories within the taxonomy into a cumulative representative text that includes a plurality of terms; determining a term corpus importance score for each term in the cumulative representative text for each category of the set of categories based on a term frequency and an inverse category frequency; determining a cumulative term corpus importance score for each term in the cumulative representative text by combining the term corpus importance scores generated for each term for categories of the set of categories, the cumulative term corpus importance score for a particular term indicating an importance of the particular term in a context of the cumulative representative text; selecting a set of terms of the cumulative representative text having highest cumulative term corpus importance scores of the plurality of terms as the keywords, the set of terms including at least one term that is not included in the received document; and providing one or more of the keywords as one or more suggested search terms to the second computing device via the network. | 1. A method on a first computing device for determining a set of keywords associated with a document for use as suggested search terms, comprising: receiving from a second computing device via a network a document to classify into a taxonomy, the taxonomy including a plurality of categories, each category of the plurality of categories being represented by a concatenation of a corresponding set of documents; determining a categorization ranking for each category of the plurality of categories for the received document; determining a set of categories of the taxonomy having highest categorization rankings of the plurality of categories for the received document; combining together, using one or more processors, the documents representing the categories of the determined set of categories within the taxonomy into a cumulative representative text that includes a plurality of terms; determining a term corpus importance score for each term in the cumulative representative text for each category of the set of categories based on a term frequency and an inverse category frequency; determining a cumulative term corpus importance score for each term in the cumulative representative text by combining the term corpus importance scores generated for each term for categories of the set of categories, the cumulative term corpus importance score for a particular term indicating an importance of the particular term in a context of the cumulative representative text; selecting a set of terms of the cumulative representative text having highest cumulative term corpus importance scores of the plurality of terms as the keywords, the set of terms including at least one term that is not included in the received document; and providing one or more of the keywords as one or more suggested search terms to the second computing device via the network. 2. The method of claim 1 , wherein each category of the plurality of categories is represented as a subset of all the words of the corresponding concatenated set of documents, the subset including words having importance scores meeting predetermined importance criteria. | 0.715721 |
1. A method, comprising: receiving, by a computing device, a request for a font file; determining whether the request is valid; in response to determining that the request is valid, embedding a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serving the font file. | 1. A method, comprising: receiving, by a computing device, a request for a font file; determining whether the request is valid; in response to determining that the request is valid, embedding a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serving the font file. 5. The method of claim 1 , wherein determining whether the request is valid includes evaluating a referrer string. | 0.76184 |
1. A method comprising: constructing, based on a set of data, a bipartite graph; wherein the set of data comprises a set of visual words, a set of linguistic words, and a set of associations between the set of visual words and the set of linguistic words; wherein each association in the set of associations is an association between a visual word in the set of visual words and a linguistic word in the set of linguistic words; wherein constructing the bipartite graph includes constructing a first partition and a second partition; wherein the first partition comprises a first set of nodes; wherein each node in the first set of nodes represents a linguistic word in the set of linguistic words; wherein the second partition comprises a second set of nodes; wherein each node in the second set of nodes represents a visual word in the set of visual words; deriving and storing in volatile or non-volatile memory, based on the bipartite graph, an association score between a first node of said bipartite graph and a second node of said bipartite graph; wherein the association score is derived, at least in part, on a random walk through the bipartite graph, wherein the random walk is performed based, at least in part, on probabilities labeled on directed edges in connections between nodes in the first set of nodes and nodes in the second set of nodes; and wherein the probability associated with a directed edge from one node to another node is based, at least in part, on the probability that one word represented by the one node is associated with any image in a set of images with which another word represented by the other node is associated; wherein the method is performed by one or more computing devices. | 1. A method comprising: constructing, based on a set of data, a bipartite graph; wherein the set of data comprises a set of visual words, a set of linguistic words, and a set of associations between the set of visual words and the set of linguistic words; wherein each association in the set of associations is an association between a visual word in the set of visual words and a linguistic word in the set of linguistic words; wherein constructing the bipartite graph includes constructing a first partition and a second partition; wherein the first partition comprises a first set of nodes; wherein each node in the first set of nodes represents a linguistic word in the set of linguistic words; wherein the second partition comprises a second set of nodes; wherein each node in the second set of nodes represents a visual word in the set of visual words; deriving and storing in volatile or non-volatile memory, based on the bipartite graph, an association score between a first node of said bipartite graph and a second node of said bipartite graph; wherein the association score is derived, at least in part, on a random walk through the bipartite graph, wherein the random walk is performed based, at least in part, on probabilities labeled on directed edges in connections between nodes in the first set of nodes and nodes in the second set of nodes; and wherein the probability associated with a directed edge from one node to another node is based, at least in part, on the probability that one word represented by the one node is associated with any image in a set of images with which another word represented by the other node is associated; wherein the method is performed by one or more computing devices. 9. The method of claim 1 wherein the first node represents a first visual word, the second node represents a second visual word, and the association score indicates a degree of association between the first visual word and the second visual word. | 0.746529 |
1. A method implemented in a device, the method comprising: receiving a named entity input; identifying a target sense for which the named entity input is to be extracted from a set of documents; and generating, based at least in part on both the named entity input and the set of documents, an extraction complexity feature that indicates how difficult it is deemed to be to identify the named entity input for the target sense in the set of documents, the generating including building an undirected graph based on the named entity input and the set of documents and looking for contexts in the undirected graph that are related to the target sense, the undirected graph including multiple vertices and multiple edges. | 1. A method implemented in a device, the method comprising: receiving a named entity input; identifying a target sense for which the named entity input is to be extracted from a set of documents; and generating, based at least in part on both the named entity input and the set of documents, an extraction complexity feature that indicates how difficult it is deemed to be to identify the named entity input for the target sense in the set of documents, the generating including building an undirected graph based on the named entity input and the set of documents and looking for contexts in the undirected graph that are related to the target sense, the undirected graph including multiple vertices and multiple edges. 2. A method as recited in claim 1 , further comprising providing the extraction complexity feature to a named entity recognition module that identifies the named entity input in the set of documents based at least in part on the extraction complexity feature. | 0.671863 |
1. A computer-implemented method for generating specialty imaging effects from layered documents, comprising: providing a layered document to computer memory, the layered document comprising at least one page including: at least one layer designated as an effect layer, and at least one layer designated as a visual layer; for the at least one page of the layered document, identifying the at least one visual layer; for each of the at least one identified visual layers: identifying at least one visual graphical element within the at least one identified visual layer; and for each of the at least one identified visual graphical element in a visual layer: (i) using a computer processor, identifying, as a next effect layer, a closest effect layer above the visual layer which includes an effect graphical element that overlaps, at least in part, the at least one identified visual graphical element; (ii) cropping the effect graphical element that overlaps to more closely match a size and a location of the identified visual graphical element; (iii) creating a new graphical element by merging at least part of the identified visual graphical element with at least part of the overlapping effect graphical element of the identified next effect layer, such that the resulting new graphical element is printable by a printer configured to print both the visual graphical element and the effect graphical element; and (iv) transforming the input layered document to form a transformed document by replacing the identified visual graphical element on the visual layer with the new graphical element; and outputting the transformed document. | 1. A computer-implemented method for generating specialty imaging effects from layered documents, comprising: providing a layered document to computer memory, the layered document comprising at least one page including: at least one layer designated as an effect layer, and at least one layer designated as a visual layer; for the at least one page of the layered document, identifying the at least one visual layer; for each of the at least one identified visual layers: identifying at least one visual graphical element within the at least one identified visual layer; and for each of the at least one identified visual graphical element in a visual layer: (i) using a computer processor, identifying, as a next effect layer, a closest effect layer above the visual layer which includes an effect graphical element that overlaps, at least in part, the at least one identified visual graphical element; (ii) cropping the effect graphical element that overlaps to more closely match a size and a location of the identified visual graphical element; (iii) creating a new graphical element by merging at least part of the identified visual graphical element with at least part of the overlapping effect graphical element of the identified next effect layer, such that the resulting new graphical element is printable by a printer configured to print both the visual graphical element and the effect graphical element; and (iv) transforming the input layered document to form a transformed document by replacing the identified visual graphical element on the visual layer with the new graphical element; and outputting the transformed document. 11. The method of claim 1 , wherein the outputting includes outputting the transformed document to at least one of: computer memory, a hot folder, a raster imaging processor, and a specialty imaging printer. | 0.667045 |
7. The computer-implemented method of claim 2 , wherein the browse relevance data includes popularity data. | 7. The computer-implemented method of claim 2 , wherein the browse relevance data includes popularity data. 8. The computer-implemented method of claim 7 , wherein the popularity data includes category fit data. | 0.968179 |
11. A system, comprising: one or more computer processors; a memory containing a program, which when executed by the one or more computer processors is configured to perform an operation comprising: receiving a database request having a projection operation for all of a plurality of columns in one or more tables, wherein the projection operation comprises a SELECT statement having a column list that includes having (i) a shorthand that specifies all of the plurality of columns and (ii) a substitute clause that specifies a column from the plurality of columns and an expression, wherein the shorthand comprises a wildcard that expands to specify all of the plurality of columns, the shorthand being less than a plurality of column references to the plurality of columns; responsive to the request, retrieving one or more data records having the plurality of columns including the specified column; evaluating the specified expression to generate an expression result corresponding to a respective data record of the one or more data records; and generating a result set comprised of the one of more data records having the plurality of columns, such that, for the respective data record, a value for the specified column is replaced with the corresponding expression result, wherein a number of columns in the result set is the same as the number of the plurality of columns in the one or more tables and specified by the shorthand. | 11. A system, comprising: one or more computer processors; a memory containing a program, which when executed by the one or more computer processors is configured to perform an operation comprising: receiving a database request having a projection operation for all of a plurality of columns in one or more tables, wherein the projection operation comprises a SELECT statement having a column list that includes having (i) a shorthand that specifies all of the plurality of columns and (ii) a substitute clause that specifies a column from the plurality of columns and an expression, wherein the shorthand comprises a wildcard that expands to specify all of the plurality of columns, the shorthand being less than a plurality of column references to the plurality of columns; responsive to the request, retrieving one or more data records having the plurality of columns including the specified column; evaluating the specified expression to generate an expression result corresponding to a respective data record of the one or more data records; and generating a result set comprised of the one of more data records having the plurality of columns, such that, for the respective data record, a value for the specified column is replaced with the corresponding expression result, wherein a number of columns in the result set is the same as the number of the plurality of columns in the one or more tables and specified by the shorthand. 13. The system of claim 11 , wherein the expression comprises a function having a column reference to the specified column. | 0.773453 |
9. A method, comprising: employing at least one processor to facilitate execution of code instructions retained in at least one memory device, the at least one processor, in response to execution of the code instructions, perform operations comprising: identifying, at a first moment in time, television-related content within a sequence of television-related content presented by a communication device that includes or is associated with a television-related communication device; identifying contextual information in or associated with the television-related content, wherein the contextual information comprises one or more terms that at least indicate an identifier of the television-related content; generating a content identifier timestamp associated with the television-related content, wherein the content identifier timestamp includes or is associated with the contextual information and facilitates establishing a correlation between the content identifier timestamp and user activity of a user associated with at least one of the communication device or a second communication device; receiving, at a second moment in time, a search query containing a plurality of search terms; determining whether one or more search terms of the contextual information are related to one or more terms of the plurality of search terms; pairing the communication device with a second communication device; transmitting the contextual information to the second communication device to facilitate generating the search query comprising the contextual information by the second communication device, wherein, in response to determining that the one or more terms of the contextual information are related to the one or more terms of the plurality of search terms, the search query is modified by appending the one or more terms of the contextual information that indicate the identifier of the television-related content to the search query; and transmitting the search query with the appended one or more terms of the contextual information. | 9. A method, comprising: employing at least one processor to facilitate execution of code instructions retained in at least one memory device, the at least one processor, in response to execution of the code instructions, perform operations comprising: identifying, at a first moment in time, television-related content within a sequence of television-related content presented by a communication device that includes or is associated with a television-related communication device; identifying contextual information in or associated with the television-related content, wherein the contextual information comprises one or more terms that at least indicate an identifier of the television-related content; generating a content identifier timestamp associated with the television-related content, wherein the content identifier timestamp includes or is associated with the contextual information and facilitates establishing a correlation between the content identifier timestamp and user activity of a user associated with at least one of the communication device or a second communication device; receiving, at a second moment in time, a search query containing a plurality of search terms; determining whether one or more search terms of the contextual information are related to one or more terms of the plurality of search terms; pairing the communication device with a second communication device; transmitting the contextual information to the second communication device to facilitate generating the search query comprising the contextual information by the second communication device, wherein, in response to determining that the one or more terms of the contextual information are related to the one or more terms of the plurality of search terms, the search query is modified by appending the one or more terms of the contextual information that indicate the identifier of the television-related content to the search query; and transmitting the search query with the appended one or more terms of the contextual information. 11. The method of claim 9 , further comprising: facilitating at least one of disambiguating the search query or promoting at least one search result over another search result in the subset of search results, based at least in part on the contextual information in the search query, to facilitate the customizing of the subset of search results. | 0.563391 |
12. The system of claim 11 , wherein the support application is further configured to: refine the query context, wherein refining the query context includes: presenting one or more search result contexts related to the first results to the user; receiving input from the user regarding a user-chosen search result context; and modifying the query context based on the user-chosen search result context; search second data for second results, wherein the searching is limited by the refined query context; and provide second results to the user. | 12. The system of claim 11 , wherein the support application is further configured to: refine the query context, wherein refining the query context includes: presenting one or more search result contexts related to the first results to the user; receiving input from the user regarding a user-chosen search result context; and modifying the query context based on the user-chosen search result context; search second data for second results, wherein the searching is limited by the refined query context; and provide second results to the user. 13. The system of claim 12 wherein the second data is the first results. | 0.978834 |
1. A method, comprising: receiving, at an interactive program guide, search criteria from a client device; receiving, at the interactive program guide and from the client device, a user identifier and a selection from predetermined genres, wherein the predetermined genres are mapped to a set of television programming; determining, with the interactive program guide, one or more search results in response to the search criteria, the user identifier and the selection from the predetermined genres; querying one or more databases of attributes with portions of the search results, wherein the attributes include genre terms; comparing each of the search results to the attributes to determine matches between selection from the predetermined genres, the portions of the search results and the genre terms; customizing search result attribute correlations and correlation weights for each of the search results based on the user identifier, matches between 1) the portions of the search results, 2) the genre terms and 3) the selection from predetermined genres; calculating result weights for each of the search results by summing the correlation weights associated with each search result; sorting the search results so the search results are returned in order of relevance according to the result weights; and returning the search results. | 1. A method, comprising: receiving, at an interactive program guide, search criteria from a client device; receiving, at the interactive program guide and from the client device, a user identifier and a selection from predetermined genres, wherein the predetermined genres are mapped to a set of television programming; determining, with the interactive program guide, one or more search results in response to the search criteria, the user identifier and the selection from the predetermined genres; querying one or more databases of attributes with portions of the search results, wherein the attributes include genre terms; comparing each of the search results to the attributes to determine matches between selection from the predetermined genres, the portions of the search results and the genre terms; customizing search result attribute correlations and correlation weights for each of the search results based on the user identifier, matches between 1) the portions of the search results, 2) the genre terms and 3) the selection from predetermined genres; calculating result weights for each of the search results by summing the correlation weights associated with each search result; sorting the search results so the search results are returned in order of relevance according to the result weights; and returning the search results. 5. The method of claim 1 , further comprising: updating the correlation weights on a periodic basis. | 0.604984 |
1. A cellular phone with scanning capability, comprising: an antenna for receiving and transmitting modulated wireless signals; received signal processing circuitry for demodulating the modulated wireless signals received by the antenna; output circuitry for transforming the demodulated signals into output data signals for presentation to a user; input circuitry for transforming input from the user into input data signals; input data signal processing circuitry for modulating the input data signals into modulated wireless signals for transmission by the antenna; scanner optics including an array of photosensing elements for detecting light reflected from scanned media; a motion sensor for detecting positional motion of the scanner optics relative to the scanned media; scanner control circuitry for generating light intensity data signals based on reflected light detected by the array of photosensing elements, and for generating positional data signals based on positional motion detected by the motion sensor circuitry; and scanner data signal processing circuitry for processing the light intensity data signals in coordination with the positional data signals to provide image data signals representative of the scanned media; wherein the scanner data signal processing circuitry and the input data signal processing circuitry are coupled and configured to enable transmission by the antenna of modulated wireless signals representative of the image data signals; the scanner data signal processing circuitry comprises circuitry configured with optical character recognition capability to provide image data signals representative of text data in the scanned media, and with text-to-speech conversion capability to convert the text data representative image data signals to voice audio signals representative of the text data in spoken form; and the input data processing circuitry comprises circuitry for modulating the voice audio signals for transmission of modulated wireless signals representing the spoken text data by the antenna. | 1. A cellular phone with scanning capability, comprising: an antenna for receiving and transmitting modulated wireless signals; received signal processing circuitry for demodulating the modulated wireless signals received by the antenna; output circuitry for transforming the demodulated signals into output data signals for presentation to a user; input circuitry for transforming input from the user into input data signals; input data signal processing circuitry for modulating the input data signals into modulated wireless signals for transmission by the antenna; scanner optics including an array of photosensing elements for detecting light reflected from scanned media; a motion sensor for detecting positional motion of the scanner optics relative to the scanned media; scanner control circuitry for generating light intensity data signals based on reflected light detected by the array of photosensing elements, and for generating positional data signals based on positional motion detected by the motion sensor circuitry; and scanner data signal processing circuitry for processing the light intensity data signals in coordination with the positional data signals to provide image data signals representative of the scanned media; wherein the scanner data signal processing circuitry and the input data signal processing circuitry are coupled and configured to enable transmission by the antenna of modulated wireless signals representative of the image data signals; the scanner data signal processing circuitry comprises circuitry configured with optical character recognition capability to provide image data signals representative of text data in the scanned media, and with text-to-speech conversion capability to convert the text data representative image data signals to voice audio signals representative of the text data in spoken form; and the input data processing circuitry comprises circuitry for modulating the voice audio signals for transmission of modulated wireless signals representing the spoken text data by the antenna. 12. The cellular phone of claim 1 , wherein the scanner optics further comprises a light source positioned for illuminating the scanned media. | 0.599023 |
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