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8,214,219 | 7 | 14 | 7. A method of operating a speech communications system in a vehicle, the method which comprises: detecting audio information with a microphone system provided in a vehicle interior, the microphone system including a first microphone array and a second microphone array, each of the microphone arrays including at least two microphones that do not operate as loudspeakers and that are not configured to be switched to an audio playback state, the at least two microphones of the first microphone array being disposed at respective positions which define a direction and a normal with respect to the direction such that the normal and the direction intersect at a center of the first microphone array, the at least two microphones of the second microphone array being disposed at respective positions which define a direction and a normal with respect to the direction such that the normal and the direction intersect at a center of the second microphone array, the center of the first microphone array and the center of the second microphone array being spaced from one another by a given spacing distance wherein the first microphone array is disposed on a first side of the vehicle interior and the second microphone array is disposed on a second side of the vehicle interior; running an interruptible text-to-speech operation based on a dialog context in order to provide a speech output; running a speech recognition operation for providing a speech recognition result; requesting voice information for a maximum number of times if insufficient voice information or no voice information is provided in response to the speech output provided by the interruptible text-to-speech operation; saving a dialog context of an unfinished speech interaction; determining a first sound source angle as a function of audio information provided by the first microphone array of the microphone system; determining a second sound source angle as a function of audio information provided by the second microphone array of the microphone system; and determining a positional sound source location based on the first sound source angle and the second sound source angle. | 7. A method of operating a speech communications system in a vehicle, the method which comprises: detecting audio information with a microphone system provided in a vehicle interior, the microphone system including a first microphone array and a second microphone array, each of the microphone arrays including at least two microphones that do not operate as loudspeakers and that are not configured to be switched to an audio playback state, the at least two microphones of the first microphone array being disposed at respective positions which define a direction and a normal with respect to the direction such that the normal and the direction intersect at a center of the first microphone array, the at least two microphones of the second microphone array being disposed at respective positions which define a direction and a normal with respect to the direction such that the normal and the direction intersect at a center of the second microphone array, the center of the first microphone array and the center of the second microphone array being spaced from one another by a given spacing distance wherein the first microphone array is disposed on a first side of the vehicle interior and the second microphone array is disposed on a second side of the vehicle interior; running an interruptible text-to-speech operation based on a dialog context in order to provide a speech output; running a speech recognition operation for providing a speech recognition result; requesting voice information for a maximum number of times if insufficient voice information or no voice information is provided in response to the speech output provided by the interruptible text-to-speech operation; saving a dialog context of an unfinished speech interaction; determining a first sound source angle as a function of audio information provided by the first microphone array of the microphone system; determining a second sound source angle as a function of audio information provided by the second microphone array of the microphone system; and determining a positional sound source location based on the first sound source angle and the second sound source angle. 14. The method according to claim 7 , which comprises: determining a positional sound source location in the vehicle interior; and selectively enabling and disabling a user-controllable function in dependence on the positional sound source location. | 0.531955 |
6,023,677 | 8 | 13 | 8. A method for recognizing a spoken sentence composed of words selected from a predetermined vocabulary from which a plurality of permissible sentences can be formed, comprising: (a) selecting a subset of the predetermined vocabulary; (b) recognizing a word in the subset selected in step (a) as the first word of the spoken sentence; (c) selecting another subset of the predetermined vocabulary, based at least in part on the previously recognized word; (d) recognizing a word in the subset selected in step (c) as the next word of the spoken sentence; and (e) repeating steps (c) and (d) until the last word of the spoken sentence is recognized, wherein a given word in the predetermined vocabulary appears in a first syntactical position in at least one of the permissible sentences and also appears in a second syntactical position in at least one of the permissible sentences, and wherein step (c) is conducted so that if the given word appears in its first syntactical position in the spoken sentence, the subset selected following recognition of the given word is a first subset, and if the given word appears in its second syntactical position in the spoken sentence, the subset selected following recognition of the given word is a second subset that differs from the first subset. | 8. A method for recognizing a spoken sentence composed of words selected from a predetermined vocabulary from which a plurality of permissible sentences can be formed, comprising: (a) selecting a subset of the predetermined vocabulary; (b) recognizing a word in the subset selected in step (a) as the first word of the spoken sentence; (c) selecting another subset of the predetermined vocabulary, based at least in part on the previously recognized word; (d) recognizing a word in the subset selected in step (c) as the next word of the spoken sentence; and (e) repeating steps (c) and (d) until the last word of the spoken sentence is recognized, wherein a given word in the predetermined vocabulary appears in a first syntactical position in at least one of the permissible sentences and also appears in a second syntactical position in at least one of the permissible sentences, and wherein step (c) is conducted so that if the given word appears in its first syntactical position in the spoken sentence, the subset selected following recognition of the given word is a first subset, and if the given word appears in its second syntactical position in the spoken sentence, the subset selected following recognition of the given word is a second subset that differs from the first subset. 13. The method of claim 8, wherein steps (b) and (d) are conducted using a pronunciation dictionary having entries, an entry in the pronunciation dictionary being assigned to the given word, which entry is associated with the first and second syntactical positions of the given word by word end nodes. | 0.711686 |
7,886,225 | 8 | 9 | 8. A method of interpellating source data into an interlanguage DTD format for use in transferring data marked up in a first schema of data having one structure or semantics into a second schema of data having a second structure or semantics, the method comprising: providing a quantum of source data of said first schema to a processing and storing apparatus; machine-reading the said source data into a DTD according to a schematic structure of a particular source ontology; automatically reading the structure and semantics ontology immanent in the source data by interpreting this both from the DTD and the way the DTD is realised in that particular instance; applying a plurality of filters including a delicacy filter, a synonomy filter, a contiguity filter and a subset filter; determining from the DTD and its particular instantiation an inherent taxonomic or schematic structure forming the interlanguage DTD comprising of relationships of tags that are unambiguous based on the readable structure of the DTD and evidence drawn from its instantiation in the source data. | 8. A method of interpellating source data into an interlanguage DTD format for use in transferring data marked up in a first schema of data having one structure or semantics into a second schema of data having a second structure or semantics, the method comprising: providing a quantum of source data of said first schema to a processing and storing apparatus; machine-reading the said source data into a DTD according to a schematic structure of a particular source ontology; automatically reading the structure and semantics ontology immanent in the source data by interpreting this both from the DTD and the way the DTD is realised in that particular instance; applying a plurality of filters including a delicacy filter, a synonomy filter, a contiguity filter and a subset filter; determining from the DTD and its particular instantiation an inherent taxonomic or schematic structure forming the interlanguage DTD comprising of relationships of tags that are unambiguous based on the readable structure of the DTD and evidence drawn from its instantiation in the source data. 9. The method according to claim 8 , further comprising: providing a structured query for assessment of ambiguous relationships of tags and receiving an assessed response to the structured query to add to the interlanguage DTD. | 0.549603 |
7,640,563 | 14 | 15 | 14. The method as recited in claim 13 , wherein: the receiving a third description comprises receiving the third description from a third description provider, the third description provider being associated with a third trust level; the assigning comprises determining the first degree based on the first trust level and the second degree based on the second and third trust levels. | 14. The method as recited in claim 13 , wherein: the receiving a third description comprises receiving the third description from a third description provider, the third description provider being associated with a third trust level; the assigning comprises determining the first degree based on the first trust level and the second degree based on the second and third trust levels. 15. The method as recited in claim 14 , wherein the first and second trust levels are numerical, and wherein the determining comprises: calculating a preliminary first degree by multiplying the first trust level by 100; calculating a preliminary second degree by multiplying a sum of the second trust level and the third trust level by 100; calculating the first degree by dividing a product of the preliminary first degree and 100 by a sum of the preliminary first degree and the preliminary second degree; and calculating the second degree by dividing a product of the preliminary second degree and 100 by the sum of the preliminary first degree and the preliminary second degree. | 0.5 |
5,452,442 | 1 | 16 | 1. A method for operating a digital data processor to obtain one or more valid signatures of an undesirable software entity, the digital data processor including a memory that is bidirectionally coupled to the digital data processor, the method comprising the steps of: storing in the memory a corpus of computer programs that are representative of computer programs that are likely to be infected by an undesirable software entity; inputting to the digital data processor at least one portion of the undesirable software entity, the at least one portion including a sequence of bytes of the undesirable software entity that are likely to remain substantially invariant from a first instance of the undesirable software entity to a second instance of the undesirable software entity; storing the at least one inputted portion in the memory; selecting at least one candidate signature of the undesirable software entity from the stored at least one portion of the undesirable software entity; constructing with the digital data processor a list of unique n-grams from the sequence of bytes, each of the unique n-grams being comprised of from one to a chosen maximal number of sequential bytes (B) of the sequence of bytes, the constructed list of unique n-grams being stored in the memory; for each of the unique n-grams of the stored list, estimating with the digital data processor a probability of an occurrence of the unique n-gram within sequences of bytes obtained from the stored corpus of computer programs; for each candidate signature that is comprised of one or more of the unique n-grams, estimating with the digital data processor a false-positive probability of an occurrence of the candidate signature within the sequences of bytes obtained from the corpus of computer programs; comparing the estimated false-positive probabilities of the candidate signatures with one another and with a set threshold probabilities, the threshold probabilities having values selected to reduce a likelihood of an occurrence of a false positive indication during the use of a signature; and outputting at least one signature for subsequent use in identifying an occurrence of the undesirable software entity or a modified version of the undesirable software entity, the outputted at least one signature being determined to exhibit a false alarm probability that is comparable to or less than a lowest false alarm probability of others of the candidate signatures. | 1. A method for operating a digital data processor to obtain one or more valid signatures of an undesirable software entity, the digital data processor including a memory that is bidirectionally coupled to the digital data processor, the method comprising the steps of: storing in the memory a corpus of computer programs that are representative of computer programs that are likely to be infected by an undesirable software entity; inputting to the digital data processor at least one portion of the undesirable software entity, the at least one portion including a sequence of bytes of the undesirable software entity that are likely to remain substantially invariant from a first instance of the undesirable software entity to a second instance of the undesirable software entity; storing the at least one inputted portion in the memory; selecting at least one candidate signature of the undesirable software entity from the stored at least one portion of the undesirable software entity; constructing with the digital data processor a list of unique n-grams from the sequence of bytes, each of the unique n-grams being comprised of from one to a chosen maximal number of sequential bytes (B) of the sequence of bytes, the constructed list of unique n-grams being stored in the memory; for each of the unique n-grams of the stored list, estimating with the digital data processor a probability of an occurrence of the unique n-gram within sequences of bytes obtained from the stored corpus of computer programs; for each candidate signature that is comprised of one or more of the unique n-grams, estimating with the digital data processor a false-positive probability of an occurrence of the candidate signature within the sequences of bytes obtained from the corpus of computer programs; comparing the estimated false-positive probabilities of the candidate signatures with one another and with a set threshold probabilities, the threshold probabilities having values selected to reduce a likelihood of an occurrence of a false positive indication during the use of a signature; and outputting at least one signature for subsequent use in identifying an occurrence of the undesirable software entity or a modified version of the undesirable software entity, the outputted at least one signature being determined to exhibit a false alarm probability that is comparable to or less than a lowest false alarm probability of others of the candidate signatures. 16. A method as set forth in claim 1 and including the steps of: segregating the corpus into a probe set, a training set and a test set; selecting byte-strings from the probe set as candidate signatures; evaluating the byte-strings against the training set to determine exact-match and fuzzy-match probabilities; determining a frequency of occurrence of the candidate signatures within the test set, including fuzzy-matches of the signatures within the test set; for each candidate signature, producing lists of an estimated probability of occurrence within the training set and a determined frequency of occurrence of exact-matches and fuzzy-matches within the test set; and determining the set of threshold probabilities in accordance with a criteria that provides an acceptable false-positive probability while not excluding a significant number of the candidate signatures. | 0.5 |
7,831,614 | 11 | 14 | 11. Software for generating a structured query language (SQL) script based on a template, the software embodied in a memory for storing software and operable when executed by a computer to: select one object from a plurality of objects in a data model; automatically select, without user input, at least one first instruction based, at least in part, on a type of the selected object; select a first template string based on the selected at least one first instruction; select a second object from the plurality of objects in the data model; select at least one second instruction based, at least in part, on a type of the second object; select a second template string based on the selected at least one second instruction; automatically, and without user input, sorting and concatenating the template strings from the selected objects in an order identified by the first and second instructions and based on the types of the first and second objects; automatically generate at least a portion of the SQL script based on the sorted and concatenated first and second template strings in the order identified by the first and second instructions. | 11. Software for generating a structured query language (SQL) script based on a template, the software embodied in a memory for storing software and operable when executed by a computer to: select one object from a plurality of objects in a data model; automatically select, without user input, at least one first instruction based, at least in part, on a type of the selected object; select a first template string based on the selected at least one first instruction; select a second object from the plurality of objects in the data model; select at least one second instruction based, at least in part, on a type of the second object; select a second template string based on the selected at least one second instruction; automatically, and without user input, sorting and concatenating the template strings from the selected objects in an order identified by the first and second instructions and based on the types of the first and second objects; automatically generate at least a portion of the SQL script based on the sorted and concatenated first and second template strings in the order identified by the first and second instructions. 14. The software of claim 11 further operable to: determine the existence of one or more macros in a selected template string of the selected template strings; and in response, at least in part, to locating one or more macros in the selected template string, process the located one or more macros. | 0.5 |
6,064,998 | 11 | 12 | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal-based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve indicia representative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate examples into the simulation to provide assistance with achieving the goal; (c) a code segment that monitors answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individual coaching messages that further provides the student with assistance with achieving the goal; and (d) a code segment that provides information to assist with a next step in achieving the goal. | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal-based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve indicia representative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate examples into the simulation to provide assistance with achieving the goal; (c) a code segment that monitors answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individual coaching messages that further provides the student with assistance with achieving the goal; and (d) a code segment that provides information to assist with a next step in achieving the goal. 12. A computer program embodied on a computer-readable medium that creates a multimedia business simulation as recited in claim 11, including a code segment that links information that motivates accomplishment of the goal to the simulation. | 0.5 |
9,910,849 | 7 | 8 | 7. A system to provide multilingual support, the system comprising: a hardware processor system comprising software configured to cause the hardware processor system to: receive a user entered communication in a first language entered by a first user determine that the user entered communication is in the first language and not in a predetermined standard language of the multilingual support system based on a first user profile that specifies the first language as a preferred language associated with the first user, wherein the predetermined standard language is a language used by the multilingual support system to store user-entered communications received in any one of a plurality of different languages; in response to the determination that user entered communication is in the first language and not in the predetermined standard language, execute a first machine translation of the user-entered communication from the first language into the predetermined standard language of the multilingual support system; store, in association with the user-entered communication in the first language, the first translation of the user-entered communication in the predetermined standard language; receive, after execution of the first machine translation of the user-entered communication from the first language into the predetermined standard language, a request to access the user-entered communication from a second user; determine, by the multilingual support system, that the request is a request to access the user-entered communication in a second language based on a second user profile associated with the second user; determining, by the multilingual support system, whether the second language is the same language as the first language or the predetermined standard language; in response to a determination that the second language is not the same language as the first language or the predetermined standard language, executing a second machine translation of the user-entered communication in which the user-entered communication is translated from the first language into the second language, wherein the second machine translation is made from the stored user-entered communication in the first language to the second language; store the translated user-entered communication in the second language in association with the user-entered communication in the first language and in the predetermined standard language; and provide the translated user-entered communication in the second language to the second user to at least partially satisfy the request. | 7. A system to provide multilingual support, the system comprising: a hardware processor system comprising software configured to cause the hardware processor system to: receive a user entered communication in a first language entered by a first user determine that the user entered communication is in the first language and not in a predetermined standard language of the multilingual support system based on a first user profile that specifies the first language as a preferred language associated with the first user, wherein the predetermined standard language is a language used by the multilingual support system to store user-entered communications received in any one of a plurality of different languages; in response to the determination that user entered communication is in the first language and not in the predetermined standard language, execute a first machine translation of the user-entered communication from the first language into the predetermined standard language of the multilingual support system; store, in association with the user-entered communication in the first language, the first translation of the user-entered communication in the predetermined standard language; receive, after execution of the first machine translation of the user-entered communication from the first language into the predetermined standard language, a request to access the user-entered communication from a second user; determine, by the multilingual support system, that the request is a request to access the user-entered communication in a second language based on a second user profile associated with the second user; determining, by the multilingual support system, whether the second language is the same language as the first language or the predetermined standard language; in response to a determination that the second language is not the same language as the first language or the predetermined standard language, executing a second machine translation of the user-entered communication in which the user-entered communication is translated from the first language into the second language, wherein the second machine translation is made from the stored user-entered communication in the first language to the second language; store the translated user-entered communication in the second language in association with the user-entered communication in the first language and in the predetermined standard language; and provide the translated user-entered communication in the second language to the second user to at least partially satisfy the request. 8. The system of claim 7 , wherein the processor is further configured to: receive another request to access the user-entered comment in the predetermined standard language; and responsive to the language associated with the other request to access the user-entered communication being the same as the predetermined standard language, provide the stored user-entered communication in the predetermined standard language to at least partially satisfy the other request. | 0.5 |
9,710,449 | 1 | 2 | 1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations to automatically generate a promotional message for a company in response to a post by a user on a competitor's webpage, the operations comprising: employing sentiment analysis to determine a user sentiment in the post and to identify a feature of a product or service of the competitor discussed in the post as a subject of the user sentiment; automatically generating the promotional message promoting the product or service of the company by: retrieving, from a promotional content data store, information tagged with metadata corresponding with the feature of the product or service identified as the subject of the user sentiment, the information describing a feature of a product or service of the company corresponding to the feature of the product or service of the competitor, and assembling content of the promotional message from the information retrieved from the promotional content data store; and electronically communicating the promotional message for presentation to the user on a user device in response to the post. | 1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations to automatically generate a promotional message for a company in response to a post by a user on a competitor's webpage, the operations comprising: employing sentiment analysis to determine a user sentiment in the post and to identify a feature of a product or service of the competitor discussed in the post as a subject of the user sentiment; automatically generating the promotional message promoting the product or service of the company by: retrieving, from a promotional content data store, information tagged with metadata corresponding with the feature of the product or service identified as the subject of the user sentiment, the information describing a feature of a product or service of the company corresponding to the feature of the product or service of the competitor, and assembling content of the promotional message from the information retrieved from the promotional content data store; and electronically communicating the promotional message for presentation to the user on a user device in response to the post. 2. The one or more computer storage media of claim 1 , wherein the promotional message is provided as a reply to the user post, a general post delivered via the user's social networking service account, or a promoted post delivered via the user's social networking service account. | 0.670188 |
7,991,720 | 13 | 17 | 13. A non-transitory machine readable medium containing executable computer program instructions which when executed by a data processing system cause said system to perform a method to organize information in the data processing system, the method comprising: determining a mathematical representation of a document, wherein the document is an electronic mail received through an electronic mail system, wherein said document is not part of a collection of documents; comparing said mathematical representation of said document to a collective mathematical representation of the collection of documents; and categorizing said document as being associated with said collection based on said comparing, wherein the content of said document is not known to a user of said data processing system upon said categorizing. | 13. A non-transitory machine readable medium containing executable computer program instructions which when executed by a data processing system cause said system to perform a method to organize information in the data processing system, the method comprising: determining a mathematical representation of a document, wherein the document is an electronic mail received through an electronic mail system, wherein said document is not part of a collection of documents; comparing said mathematical representation of said document to a collective mathematical representation of the collection of documents; and categorizing said document as being associated with said collection based on said comparing, wherein the content of said document is not known to a user of said data processing system upon said categorizing. 17. A medium as in claim 13 , wherein said comparing comprises: determining a similarity indicator from said mathematical representation of said document and said collective mathematical presentation. | 0.598394 |
8,688,603 | 15 | 20 | 15. A system, comprising: a memory; and one or more processors coupled to the memory, wherein the memory comprises program instructions executable by the one or more processors to: based on reference data that includes pairs of information items and labels that each indicate whether a given pair of information items have a specific relationship, generate a first machine learning model for determining whether pairs of information items have said specific relationship; identify one or more false positive pairs, wherein a given false positive pair is a pair of information items that the first machine learning model indicates as having said specific relationship and which are labeled within the reference data as not having said specific relationship; generate an indication of one or more of the identified false positive pairs as candidates to be corrected within the reference data. | 15. A system, comprising: a memory; and one or more processors coupled to the memory, wherein the memory comprises program instructions executable by the one or more processors to: based on reference data that includes pairs of information items and labels that each indicate whether a given pair of information items have a specific relationship, generate a first machine learning model for determining whether pairs of information items have said specific relationship; identify one or more false positive pairs, wherein a given false positive pair is a pair of information items that the first machine learning model indicates as having said specific relationship and which are labeled within the reference data as not having said specific relationship; generate an indication of one or more of the identified false positive pairs as candidates to be corrected within the reference data. 20. The system of claim 15 , wherein the first machine learning model and the new machine model are different types of machine learning models. | 0.877986 |
9,875,743 | 1 | 4 | 1. A method of blind diarization comprising: receiving audio data at a communication interface of a computing system on a frame by frame basis, representing segments of the audio data according to respective feature vectors; clustering respective segments of the audio data according to the respective feature vectors, such that agglomerative clusters of similar feature vectors are gathered as super segments of the audio data; building respective voiceprint models for speakers from the super segments according to a size of respective agglomerative clusters; creating a background model from a first diagonal Gaussian distribution that includes all segments associated with those feature vectors not representing a speaker; wherein building respective voiceprint models comprises: training a respective diagonal Gaussian distribution for each of the agglomerative clusters of super segments; assigning a weighting value to each respective diagonal Gaussian distribution, wherein the weighting value is proportional to a total number of super-segments in the agglomerative cluster composing the respective diagonal Gaussian distribution; merging the respective diagonal Gaussian distributions, wherein the respective diagonal Gaussian distributions are included in a merged Gaussian distribution according to the respective weighting values; utilizing the respectively merged Gaussian distributions as respective voiceprint models and using the respective voiceprint models and the background model to label the segments of audio data with an identification of one of the speakers or a different identification as background data; iteratively refining each of the respective voiceprint models on an audio segment by audio segment basis by calculating a log likelihood of a presence of the respective segments as fitting within either the background model or within one of the respective voiceprint models; within each iteration, reassigning the segments of the audio data as fitting either one of the respective voiceprint models or the background model and repeating the step of utilizing the respective voiceprint models and the background model to label the segments; verifying each of the respective voiceprint models when a comparison to sample agent models stored in a memory indicates a match at a threshold quality; and decoding the segments identified as a speaker segment in accordance with one of the respective voiceprint models. | 1. A method of blind diarization comprising: receiving audio data at a communication interface of a computing system on a frame by frame basis, representing segments of the audio data according to respective feature vectors; clustering respective segments of the audio data according to the respective feature vectors, such that agglomerative clusters of similar feature vectors are gathered as super segments of the audio data; building respective voiceprint models for speakers from the super segments according to a size of respective agglomerative clusters; creating a background model from a first diagonal Gaussian distribution that includes all segments associated with those feature vectors not representing a speaker; wherein building respective voiceprint models comprises: training a respective diagonal Gaussian distribution for each of the agglomerative clusters of super segments; assigning a weighting value to each respective diagonal Gaussian distribution, wherein the weighting value is proportional to a total number of super-segments in the agglomerative cluster composing the respective diagonal Gaussian distribution; merging the respective diagonal Gaussian distributions, wherein the respective diagonal Gaussian distributions are included in a merged Gaussian distribution according to the respective weighting values; utilizing the respectively merged Gaussian distributions as respective voiceprint models and using the respective voiceprint models and the background model to label the segments of audio data with an identification of one of the speakers or a different identification as background data; iteratively refining each of the respective voiceprint models on an audio segment by audio segment basis by calculating a log likelihood of a presence of the respective segments as fitting within either the background model or within one of the respective voiceprint models; within each iteration, reassigning the segments of the audio data as fitting either one of the respective voiceprint models or the background model and repeating the step of utilizing the respective voiceprint models and the background model to label the segments; verifying each of the respective voiceprint models when a comparison to sample agent models stored in a memory indicates a match at a threshold quality; and decoding the segments identified as a speaker segment in accordance with one of the respective voiceprint models. 4. The method according to claim 1 , further comprising using a single diagonal Gaussian distribution on those feature vectors not representing a speaker. | 0.83617 |
8,379,027 | 11 | 14 | 11. A system comprising: a memory to store a graphical reference image for a rendered character, the graphical reference image was produced by a source known to produce correct images; a display device, coupled to the memory, the display device providing a bitmapped display screen to present the graphical reference image and the rendered character produced by a text rendering engine being tested to facilitate a visual comparison between a visual representation of the graphical reference image produced by the source known to produce correct images and a visual representation of the rendered character produced by the text rendering engine to be tested; and a processor, coupled to the memory and the display device, to receive user input indicating user evaluation of the graphical reference image and the rendered character, the user evaluation being based on the comparison between the visual representation of the graphical reference image and the visual representation of the rendered character, the user evaluation identifying one or more differences between the graphical reference image produced by the source known to produce correct images and the rendered character produced by the text rendering engine to be tested, and to store the user evaluation in a database for subsequent debugging of the text rendering engine. | 11. A system comprising: a memory to store a graphical reference image for a rendered character, the graphical reference image was produced by a source known to produce correct images; a display device, coupled to the memory, the display device providing a bitmapped display screen to present the graphical reference image and the rendered character produced by a text rendering engine being tested to facilitate a visual comparison between a visual representation of the graphical reference image produced by the source known to produce correct images and a visual representation of the rendered character produced by the text rendering engine to be tested; and a processor, coupled to the memory and the display device, to receive user input indicating user evaluation of the graphical reference image and the rendered character, the user evaluation being based on the comparison between the visual representation of the graphical reference image and the visual representation of the rendered character, the user evaluation identifying one or more differences between the graphical reference image produced by the source known to produce correct images and the rendered character produced by the text rendering engine to be tested, and to store the user evaluation in a database for subsequent debugging of the text rendering engine. 14. The system of claim 11 , wherein a difference between the graphical reference image and the rendered character indicates at least one of an error in the graphical reference image, an error in encoding the rendered character, an error in a font of the rendered character or an error in a text rendering process. | 0.621687 |
7,623,710 | 17 | 18 | 17. A computer device comprising: a processor; and a memory coupled to the processor, the memory comprising computer-readable instructions executable by the processor, the computer-readable instructions, when executed by the processor, perform operations comprising: determining a content and structure via a visual representation of the document in the first format, the content including textual content and the structure including document layout characteristics; translating the textual content of the document into machine-editable text; translating the document layout characteristics to a second format; and importing the translated machine-editable text together with the translated document layout characteristics into the second format. | 17. A computer device comprising: a processor; and a memory coupled to the processor, the memory comprising computer-readable instructions executable by the processor, the computer-readable instructions, when executed by the processor, perform operations comprising: determining a content and structure via a visual representation of the document in the first format, the content including textual content and the structure including document layout characteristics; translating the textual content of the document into machine-editable text; translating the document layout characteristics to a second format; and importing the translated machine-editable text together with the translated document layout characteristics into the second format. 18. The computing device of claim 17 , wherein the computer-readable instructions further perform operations comprising heuristically determining if the content and structure from the first format is recognizable in the second format. | 0.5 |
8,108,509 | 23 | 26 | 23. The server computer of claim 22 , further comprising: a circuit to receive the content data; and a circuit to transmit the altered content data to the computer over the bi-directional communications network. | 23. The server computer of claim 22 , further comprising: a circuit to receive the content data; and a circuit to transmit the altered content data to the computer over the bi-directional communications network. 26. The server computer according to claim 23 , wherein the bi-directional communications network comprises an interactive network, and wherein the server computer and the one or more client computers include game consoles configured to execute an interactive game. | 0.5 |
9,208,776 | 17 | 18 | 17. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: retrieving information describing media available in a media content retrieval system, to yield retrieved information; constructing a graph that models how the media are interconnected based on the retrieved information, the graph interconnecting disparate categories of the media; weighting the graph based on the retrieved information, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; ranking the retrieved information describing the media based on the normalized weighted graph, to yield ranked information; and generating a speech recognition model based on the ranked information. | 17. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: retrieving information describing media available in a media content retrieval system, to yield retrieved information; constructing a graph that models how the media are interconnected based on the retrieved information, the graph interconnecting disparate categories of the media; weighting the graph based on the retrieved information, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; ranking the retrieved information describing the media based on the normalized weighted graph, to yield ranked information; and generating a speech recognition model based on the ranked information. 18. The computer-readable storage device of claim 17 , wherein ranking the information describing the media is based on an algorithm that ranks pages. | 0.5 |
7,729,594 | 6 | 7 | 6. The medium of claim 1 , wherein the PES packet comprises stream identification, PES packet length, and packet data. | 6. The medium of claim 1 , wherein the PES packet comprises stream identification, PES packet length, and packet data. 7. The medium of claim 6 , wherein the stream identification (ID) indicates a type of the PES packet. | 0.68038 |
9,830,784 | 1 | 4 | 1. A method, comprising: at an electronic device with one or more haptic output devices and one or more audio output devices: detecting occurrence of a plurality of conditions in a plurality of software applications, wherein the electronic device is configured to: for conditions of a same type, generate respective alerts that include same haptic components that indicate that the conditions are of the same type, and for conditions of different types, generate respective alerts that include different respective haptic components that indicate that the conditions are of different types, regardless of respective software applications in the plurality of software applications in which the conditions in the plurality of conditions were detected; for conditions detected in a same software application in the plurality of software applications, generate respective alerts that include same audio components that indicate that the conditions occurred in the same software application, and for conditions detected in different software applications in the plurality of software applications, generate respective alerts that include different audio components that indicate that the conditions occurred in different software applications, regardless of respective types of the conditions; wherein detecting the occurrence of the plurality of conditions in the plurality of software applications includes: detecting occurrence of a first condition of a first type in a first software application at the electronic device, wherein the first condition of the first type indicates failure of an operation requested by a user to occur; in response to detecting the occurrence of the first condition in the first software application, generating a first alert corresponding to the first condition that includes: a first haptic component that indicates that the first condition of the first type has occurred; and a first audio component that corresponds to the first software application; detecting occurrence at the electronic device of the first condition of the first type in a second software application that is different from the first software application; in response to detecting the occurrence of the first condition in the second software application, generating a second alert corresponding to the first condition that includes: the first haptic component that indicates that the first condition of the first type has occurred; and a second audio component, different from the first audio component, the second audio component corresponding to the second software application; detecting occurrence at the electronic device of a second condition of a second type in the first software application, the second type different than the first type; and in response to detecting the occurrence of the second condition in the first software application, generating a third alert corresponding to the second condition that includes: a second haptic component that indicates that the second condition of the second type has occurred, the second haptic component different than the first haptic component; and the first audio component corresponding to the first software application. | 1. A method, comprising: at an electronic device with one or more haptic output devices and one or more audio output devices: detecting occurrence of a plurality of conditions in a plurality of software applications, wherein the electronic device is configured to: for conditions of a same type, generate respective alerts that include same haptic components that indicate that the conditions are of the same type, and for conditions of different types, generate respective alerts that include different respective haptic components that indicate that the conditions are of different types, regardless of respective software applications in the plurality of software applications in which the conditions in the plurality of conditions were detected; for conditions detected in a same software application in the plurality of software applications, generate respective alerts that include same audio components that indicate that the conditions occurred in the same software application, and for conditions detected in different software applications in the plurality of software applications, generate respective alerts that include different audio components that indicate that the conditions occurred in different software applications, regardless of respective types of the conditions; wherein detecting the occurrence of the plurality of conditions in the plurality of software applications includes: detecting occurrence of a first condition of a first type in a first software application at the electronic device, wherein the first condition of the first type indicates failure of an operation requested by a user to occur; in response to detecting the occurrence of the first condition in the first software application, generating a first alert corresponding to the first condition that includes: a first haptic component that indicates that the first condition of the first type has occurred; and a first audio component that corresponds to the first software application; detecting occurrence at the electronic device of the first condition of the first type in a second software application that is different from the first software application; in response to detecting the occurrence of the first condition in the second software application, generating a second alert corresponding to the first condition that includes: the first haptic component that indicates that the first condition of the first type has occurred; and a second audio component, different from the first audio component, the second audio component corresponding to the second software application; detecting occurrence at the electronic device of a second condition of a second type in the first software application, the second type different than the first type; and in response to detecting the occurrence of the second condition in the first software application, generating a third alert corresponding to the second condition that includes: a second haptic component that indicates that the second condition of the second type has occurred, the second haptic component different than the first haptic component; and the first audio component corresponding to the first software application. 4. The method of claim 1 , wherein: the first audio component is generated based on an audio waveform that is designated for use by the first software application; and the second audio component is generated based on an audio waveform that is designated for use by the second software application. | 0.84434 |
8,171,013 | 11 | 16 | 11. A method for indexing a product identifier and logical parts thereof, comprising: receiving a product identifier; splitting the product identifier into logical parts; storing the product identifiers and logical parts into a document; indexing the product identifier and the individual logical parts in an index; and storing the index, wherein different weights are assigned to separate fields based on the field types such as product identifier or logical parts of the product identifier field, wherein the fields and weights are encoded to word positions in the document, wherein the weights affect a score generated upon performing a query using the index. | 11. A method for indexing a product identifier and logical parts thereof, comprising: receiving a product identifier; splitting the product identifier into logical parts; storing the product identifiers and logical parts into a document; indexing the product identifier and the individual logical parts in an index; and storing the index, wherein different weights are assigned to separate fields based on the field types such as product identifier or logical parts of the product identifier field, wherein the fields and weights are encoded to word positions in the document, wherein the weights affect a score generated upon performing a query using the index. 16. The method as recited in claim 11 , wherein the product identifier is indexed in a field for full terms, wherein the logical parts are indexed in a field for partial terms. | 0.640816 |
9,396,185 | 1 | 10 | 1. A method for providing a contextual description of an object, the method comprising: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt, wherein at least one of the preceding actions is performed on at least one electronic hardware component. | 1. A method for providing a contextual description of an object, the method comprising: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt, wherein at least one of the preceding actions is performed on at least one electronic hardware component. 10. The method of claim 1 wherein prior to presenting the linguistic prompt to the one of the first and second users, the method comprises: analyzing the linguistic prompt to detect grammatical errors in the linguistic prompt; and correcting any detected grammatical errors. | 0.797935 |
8,364,202 | 13 | 16 | 13. A method for a communication device comprising a microphone, a speaker, an input device, a camera, a display, a vibrator, and an antenna, said method comprising: a voice communicating implementing step, wherein voice communication is implemented with another device in a wireless fashion; a device vibration implementing step, wherein said communication device is vibrated by said vibrator when a certain event is determined to be occurred; an image quality setting implementing step, wherein the output of said camera is stored in said communication device with the quality identified by the user; and a multiple language mode implementing step, wherein the language mode selected by the user is implemented, wherein said language mode selected is one of a plurality of language modes including a first language mode and a second language mode; wherein when said first language mode is selected by the user, a first command which is the command for the user to manipulate said communication device in a first manner and a second command which is the command for the user to manipulate said communication device in a second manner are displayed by utilizing a first language data; wherein when said second language mode is selected by the user, said first command which is the command for the user to manipulate said communication device in said first manner and said second command which is the command for the user to manipulate said communication device in said second manner are displayed by utilizing a second language data; wherein when said communication device is powered off under said first language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said first language data; and wherein when said communication device is powered off under said second language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said second language data. | 13. A method for a communication device comprising a microphone, a speaker, an input device, a camera, a display, a vibrator, and an antenna, said method comprising: a voice communicating implementing step, wherein voice communication is implemented with another device in a wireless fashion; a device vibration implementing step, wherein said communication device is vibrated by said vibrator when a certain event is determined to be occurred; an image quality setting implementing step, wherein the output of said camera is stored in said communication device with the quality identified by the user; and a multiple language mode implementing step, wherein the language mode selected by the user is implemented, wherein said language mode selected is one of a plurality of language modes including a first language mode and a second language mode; wherein when said first language mode is selected by the user, a first command which is the command for the user to manipulate said communication device in a first manner and a second command which is the command for the user to manipulate said communication device in a second manner are displayed by utilizing a first language data; wherein when said second language mode is selected by the user, said first command which is the command for the user to manipulate said communication device in said first manner and said second command which is the command for the user to manipulate said communication device in said second manner are displayed by utilizing a second language data; wherein when said communication device is powered off under said first language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said first language data; and wherein when said communication device is powered off under said second language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said second language data. 16. The method of claim 13 , wherein said voice communication and one of said first language mode and said second language mode selected by the user are implemented simultaneously. | 0.5 |
9,020,866 | 11 | 14 | 11. A computing device, comprising: at least one processor; and memory including instructions that, when executed by the processor, cause the computing device to: train a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; train a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and rank the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request. | 11. A computing device, comprising: at least one processor; and memory including instructions that, when executed by the processor, cause the computing device to: train a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; train a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and rank the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request. 14. The computing device of claim 11 , wherein the index is a search engine index that is accessible at time of receiving the search request. | 0.794461 |
8,244,689 | 1 | 2 | 1. A computer-implemented method of determining if a first object and a second object represent a same entity, the method comprising: identifying one or more common attributes between the first object and the second object, wherein the first object and the second object are included in a fact repository located on one or more computer systems; determining an entropy for each of the one or more common attributes, wherein a respective entropy for a respective attribute in the one or more common attributes comprises a respective numeric value measuring a respective amount of information carried by the respective attribute; identifying a subset of the one or more common attributes whose respective values are equivalent; determining whether the first object and the second object represent the same entity by comparing a sum of entropies for the subset of the one or more common attributes to an entropy threshold measure; and in response to determining that the first object and the second object represent the same entity, merging the first object and the second object in the fact repository. | 1. A computer-implemented method of determining if a first object and a second object represent a same entity, the method comprising: identifying one or more common attributes between the first object and the second object, wherein the first object and the second object are included in a fact repository located on one or more computer systems; determining an entropy for each of the one or more common attributes, wherein a respective entropy for a respective attribute in the one or more common attributes comprises a respective numeric value measuring a respective amount of information carried by the respective attribute; identifying a subset of the one or more common attributes whose respective values are equivalent; determining whether the first object and the second object represent the same entity by comparing a sum of entropies for the subset of the one or more common attributes to an entropy threshold measure; and in response to determining that the first object and the second object represent the same entity, merging the first object and the second object in the fact repository. 2. The method of claim 1 wherein identifying the subset of the one or more common attributes whose respective values are equivalent comprises comparing values of the attributes for the first object and the second object. | 0.88172 |
9,666,098 | 33 | 40 | 33. A computer-implemented method comprising: generating, by a computer, a first set of one or more graphical user interfaces configured to display at a computing device of a learner, one or more interactive assessments comprising one or more baseline distractors associated with one or more language skills, each respective baseline distractor having a distractor difficulty score; receiving, by the computer, via the one or more graphical user interfaces of the first set, one or more inputs corresponding to the one or more language skills; automatically determining, by the computer, for each respective language skill an ability score of the learner based upon an input received via a graphical user interface of the first set displaying an interactive assessment, and the distractor difficulty score of the respective interactive assessment, in response to receiving the one or more inputs of the interactive assessment displayed via at least one graphical user interface of the first set; responsive to determining at least one ability score for the learner: automatically determining, by the computer, a language proficiency level of the learner based on the at least one ability score of the learner; receiving, by the computer, a learner content interest and a learner goal transmitted from the computing device of the learner; storing, by the computer, a learner profile associated with the learner in non-transitory machine-readable storage media of a user data store, wherein the learner profile comprises one or more abilities of the learner corresponding respectively to one or more language skills, the language proficiency level, the learner content interest, and the learner goal; selecting, by the computer, from a resource store configured to store one or more resources and one or more content values indicating a type of content, a resource associated with a content value corresponding to the learner content interest in the learner profile; generating, by the computer, a set of one or more distractors using one or more keywords parsed from the resource selected form the resource store, each having a distractor difficulty score corresponding to the one or more language skills of the learner; generating, by the computer, a second set of one or more graphical user interfaces configured display at the computing device of the learner, one or more learning activities comprising each of the one or more distractors generated using the one or more keywords parsed from the resource. | 33. A computer-implemented method comprising: generating, by a computer, a first set of one or more graphical user interfaces configured to display at a computing device of a learner, one or more interactive assessments comprising one or more baseline distractors associated with one or more language skills, each respective baseline distractor having a distractor difficulty score; receiving, by the computer, via the one or more graphical user interfaces of the first set, one or more inputs corresponding to the one or more language skills; automatically determining, by the computer, for each respective language skill an ability score of the learner based upon an input received via a graphical user interface of the first set displaying an interactive assessment, and the distractor difficulty score of the respective interactive assessment, in response to receiving the one or more inputs of the interactive assessment displayed via at least one graphical user interface of the first set; responsive to determining at least one ability score for the learner: automatically determining, by the computer, a language proficiency level of the learner based on the at least one ability score of the learner; receiving, by the computer, a learner content interest and a learner goal transmitted from the computing device of the learner; storing, by the computer, a learner profile associated with the learner in non-transitory machine-readable storage media of a user data store, wherein the learner profile comprises one or more abilities of the learner corresponding respectively to one or more language skills, the language proficiency level, the learner content interest, and the learner goal; selecting, by the computer, from a resource store configured to store one or more resources and one or more content values indicating a type of content, a resource associated with a content value corresponding to the learner content interest in the learner profile; generating, by the computer, a set of one or more distractors using one or more keywords parsed from the resource selected form the resource store, each having a distractor difficulty score corresponding to the one or more language skills of the learner; generating, by the computer, a second set of one or more graphical user interfaces configured display at the computing device of the learner, one or more learning activities comprising each of the one or more distractors generated using the one or more keywords parsed from the resource. 40. The method according to claim 33 , further comprising updating, by the computer, the goal of the learner according to a new goal input from the computing device of the learner. | 0.788732 |
10,120,858 | 12 | 15 | 12. A method for analyzing queries, the method comprising: receiving a query from a user; determining, based on the user's natural language, a correct grammatical structure for the query; dissecting the query into a plurality of words; assigning, based on a predetermined ontology and the determined correct grammatical structure, an ontological threshold score to each of the words; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query and the correct grammatical structure; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query and the correct grammatical structure; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis defined by the word, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech. | 12. A method for analyzing queries, the method comprising: receiving a query from a user; determining, based on the user's natural language, a correct grammatical structure for the query; dissecting the query into a plurality of words; assigning, based on a predetermined ontology and the determined correct grammatical structure, an ontological threshold score to each of the words; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query and the correct grammatical structure; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query and the correct grammatical structure; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis defined by the word, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech. 15. The method of claim 12 , wherein the enabling further comprises displaying, in a vertical drop-down menu orthogonal to the horizontal axis, and directly vertically under the concepts associated with each word, a predetermined list of concepts relating to each word having an assigned ontological threshold score that is at or above the predetermined threshold. | 0.517241 |
9,241,195 | 18 | 20 | 18. The network device of claim 10 , wherein the transmitter is configured to transmit identifications of more than one of the programs associated with matching dialog text; and wherein the processor is configured to assign a rank the more than one of the programs for displaying according to the rank based on a particular preference of the particular user stored in the particular profile. | 18. The network device of claim 10 , wherein the transmitter is configured to transmit identifications of more than one of the programs associated with matching dialog text; and wherein the processor is configured to assign a rank the more than one of the programs for displaying according to the rank based on a particular preference of the particular user stored in the particular profile. 20. The network device of claim 18 , wherein the processor is configured to associate a different plurality of images with each program of the more than one of the programs, wherein each image is associated with a different grouping of dialog text associated with each program; and wherein the processor is configured to determine, for each program of the more than one of the programs and, one of the plurality of images associated with the matching dialog text for displaying to the particular user. | 0.5 |
7,505,463 | 15 | 16 | 15. A device, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions configured to: receive a plurality of packet flow rules from multiple network services, wherein each packet flow rule comprises a packet filter and an action list including one or more prioritized actions, wherein each network service has a priority, and wherein the packet flow rules from each network service comprise a priority expressed either by longest prefix, or ordered precedence; generate a unified rule set according to the received packet flow rules, wherein said generating comprises: identify conflicts between rule pairs, wherein each rule pair includes a higher priority rule and a lower priority rule; and resolve the identified conflicts according to a priority relationship between the higher priority rule and the lower priority rule. | 15. A device, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions configured to: receive a plurality of packet flow rules from multiple network services, wherein each packet flow rule comprises a packet filter and an action list including one or more prioritized actions, wherein each network service has a priority, and wherein the packet flow rules from each network service comprise a priority expressed either by longest prefix, or ordered precedence; generate a unified rule set according to the received packet flow rules, wherein said generating comprises: identify conflicts between rule pairs, wherein each rule pair includes a higher priority rule and a lower priority rule; and resolve the identified conflicts according to a priority relationship between the higher priority rule and the lower priority rule. 16. The device of claim 15 , wherein in said resolving the program instructions are configured to modify the action list of one or more of the conflicting rules. | 0.873028 |
8,010,525 | 1 | 6 | 1. A computer-implemented method comprising: receiving a search query; generating first search results that identify resources that a search engine has identified as being responsive to the search query; identifying search modes based on the search query, the resources, or both the search query and the resources; providing a first user interface that presents for display at least a portion of the first search results and a respective search mode selector for each of one or more of the identified search modes; receiving user input selecting a first search mode by selecting one of the search mode selectors, wherein: the first search mode is associated with a first collection of records that share a first common attribute structure, a second of the search modes is associated with a second collection of records that share a second common attribute structure, and the first common attribute structure is different from the second common attribute structure; generating second search results that satisfy the search query and that refer to mode-specific records from the first collection of records that are associated with the first search mode, each of the search modes being associated with a particular collection of records from among multiple collections of records; formatting a plurality of the second search results using a mode-specific presentation template that is associated with the first search mode to generate formatted search results; and providing a second user interface that presents for display the formatted search results. | 1. A computer-implemented method comprising: receiving a search query; generating first search results that identify resources that a search engine has identified as being responsive to the search query; identifying search modes based on the search query, the resources, or both the search query and the resources; providing a first user interface that presents for display at least a portion of the first search results and a respective search mode selector for each of one or more of the identified search modes; receiving user input selecting a first search mode by selecting one of the search mode selectors, wherein: the first search mode is associated with a first collection of records that share a first common attribute structure, a second of the search modes is associated with a second collection of records that share a second common attribute structure, and the first common attribute structure is different from the second common attribute structure; generating second search results that satisfy the search query and that refer to mode-specific records from the first collection of records that are associated with the first search mode, each of the search modes being associated with a particular collection of records from among multiple collections of records; formatting a plurality of the second search results using a mode-specific presentation template that is associated with the first search mode to generate formatted search results; and providing a second user interface that presents for display the formatted search results. 6. The computer-implemented method of claim 1 , wherein identifying search modes comprises: determining that one or more of the resources are associated with respective one or more records from among the multiple collections of records, the one or more records being associated with the search modes. | 0.782923 |
9,613,067 | 1 | 2 | 1. A method comprising: providing an entity-relationship (ER)-extensible markup language (XML) hybrid data model of a relational database comprising XML data; receiving a user setting of a first annotation of a first entity in the ER-XML hybrid data model marking the first entity as not to be transformed as XML data; receiving a user setting of a second annotation of a second entity in the ER-XML hybrid data model marking the second entity as to be transformed as XML data; and transforming, by a computing processor, the ER-XML hybrid data model to a physical data model of the relational database, comprising: based on the first annotation of the first entity marking the first entity as not to be transformed as XML data, transforming the first entity in the ER-XML hybrid data model to a first table in the physical data model; based on the second annotation of the second entity marking the second entity as to be transformed as XML data, determining whether the second entity has a parent entity in the ER-ML hybrid data model with a third annotation marking the parent entity as not to be transformed as XML data; and in response to determining that the second entity has the parent entity with the third annotation marking the parent entity as not to be transformed as XML data: transforming the second entity and a transitive closure of the second entity to an XML column in a second table in the physical data model, the second table representing the parent entity in the ER-XML hybrid data model marked as not to be transformed as XML data; generating an XML schema document (XSD) for the XML column; and associating the XSD with the XML column in the physical data model. | 1. A method comprising: providing an entity-relationship (ER)-extensible markup language (XML) hybrid data model of a relational database comprising XML data; receiving a user setting of a first annotation of a first entity in the ER-XML hybrid data model marking the first entity as not to be transformed as XML data; receiving a user setting of a second annotation of a second entity in the ER-XML hybrid data model marking the second entity as to be transformed as XML data; and transforming, by a computing processor, the ER-XML hybrid data model to a physical data model of the relational database, comprising: based on the first annotation of the first entity marking the first entity as not to be transformed as XML data, transforming the first entity in the ER-XML hybrid data model to a first table in the physical data model; based on the second annotation of the second entity marking the second entity as to be transformed as XML data, determining whether the second entity has a parent entity in the ER-ML hybrid data model with a third annotation marking the parent entity as not to be transformed as XML data; and in response to determining that the second entity has the parent entity with the third annotation marking the parent entity as not to be transformed as XML data: transforming the second entity and a transitive closure of the second entity to an XML column in a second table in the physical data model, the second table representing the parent entity in the ER-XML hybrid data model marked as not to be transformed as XML data; generating an XML schema document (XSD) for the XML column; and associating the XSD with the XML column in the physical data model. 2. The method of claim 1 , wherein the generating of the XSD for the XML column comprises: including information on the second entity in the XSD; including information on any subtype entity of the second entity in the XSD; including information on any supertype entity of the second entity in the XSD; and including information on any child entity of a relationship referencing the second entity as parent in the XSD. | 0.793155 |
8,639,509 | 19 | 23 | 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. 23. The method of claim 19 , wherein the at least one feature includes nine SL-JMD features, including three for each of the highest level of the surrounding sub-trees and left and right child sub-trees corresponding to a level immediately below the highest level of the surrounding sub-trees. | 0.755833 |
9,910,924 | 1 | 7 | 1. A method of searching online social profiles of real-world entities on an online social network, the method including: specifying one or more core entity attributes as a first search attribute set for use in searching an online social network; electronically receiving, responsive to searching the online social network based on the first search attribute set, entity reflections that include supplemental entity attributes for real-world entities; and using a combination of the core entity attributes and one or more supplemental entity attributes to electronically receive more entity reflections that include meta entity attributes for the real-world entities. | 1. A method of searching online social profiles of real-world entities on an online social network, the method including: specifying one or more core entity attributes as a first search attribute set for use in searching an online social network; electronically receiving, responsive to searching the online social network based on the first search attribute set, entity reflections that include supplemental entity attributes for real-world entities; and using a combination of the core entity attributes and one or more supplemental entity attributes to electronically receive more entity reflections that include meta entity attributes for the real-world entities. 7. The method of claim 1 , wherein the entity reflections represent one or more online social mentions of the real-world entities. | 0.72103 |
8,876,611 | 9 | 12 | 9. The method of claim 8 , further comprising at least one of: modifying the character; modifying the environment; modifying the era; or modifying the scenes-a-faire of the online game. | 9. The method of claim 8 , further comprising at least one of: modifying the character; modifying the environment; modifying the era; or modifying the scenes-a-faire of the online game. 12. The method of claim 9 , further comprising: the character adapting a selected motif advantageously. | 0.612782 |
9,378,738 | 17 | 18 | 17. The computer-readable storage device of claim 15 , wherein the stability of the identified content of the identified content is determined using stability probability. | 17. The computer-readable storage device of claim 15 , wherein the stability of the identified content of the identified content is determined using stability probability. 18. The computer-readable storage device of claim 17 , wherein the stability probability is determined using a machine learning algorithm on a corpus of speech utterances. | 0.5 |
8,117,192 | 1 | 12 | 1. A computer-implemented method for generating an interactive patent data summary report, the interactive report comprising data for each of a plurality of years on a target law firm entity, the method comprising: a. receiving first information, wherein the first information is indicative of the target law firm entity, wherein the target law firm entity is of a first entity type; b. using one or more processors to issue one or more database system queries, at least one of the one or more queries comprising at least a portion of the first information to a database system comprising at least one database table stored on a computer readable medium to identify a plurality of company entity records, the plurality of company entity records being a subset of all company entity records stored in the at least one database table and comprising information on a plurality of company entities being assignees of at least one of a plurality of patent documents, wherein the target law firm entity being an attorney listed on each of the plurality of patent documents, each of the plurality of company entities being of a second entity type and wherein the subset of the stored all company entity records constituting the plurality of company entity records is determined using the issued one or more database system queries; c. using the one or more processors for extracting the information on the plurality of company entities from the plurality of company entity records; d. incorporating using the one or more processors the extracted information on at least two of the plurality of company entities of the second entity type into the interactive report; e. using the one or more processors for determining, for each pair comprising a year from the plurality of years and a company entity from at least two of the plurality of company entities, a quantity of patent documents in the plurality of patent documents corresponding to the pair, each of the plurality of patent documents listing the target law firm entity as an attorney; f. generating using the one or more processors a graphical chart, the graphical chart incorporating, for each pair comprising the year of the plurality of years and the company entity from the at least two of the plurality of company entities, a graphical representation of the determined quantity of patent documents; g. incorporating using the one or more processors the generated graphical chart into the interactive report or associating the graphical chart with the interactive report; and h. causing the interactive report to be provided to the user, wherein the interactive report comprises a user interface portion usable in connection with a web browser; wherein the interactive report comprises a plurality of information items capable of being activated by the user, the plurality of information items forming the user interface portion of the interactive report; and wherein receipt of an indication that at least one information item of the plurality of information items of the user interface portion of the interactive report has been activated by the user causes the one or more processors to generate a second report based on the activated information item and cause the second report to be provided to the user. | 1. A computer-implemented method for generating an interactive patent data summary report, the interactive report comprising data for each of a plurality of years on a target law firm entity, the method comprising: a. receiving first information, wherein the first information is indicative of the target law firm entity, wherein the target law firm entity is of a first entity type; b. using one or more processors to issue one or more database system queries, at least one of the one or more queries comprising at least a portion of the first information to a database system comprising at least one database table stored on a computer readable medium to identify a plurality of company entity records, the plurality of company entity records being a subset of all company entity records stored in the at least one database table and comprising information on a plurality of company entities being assignees of at least one of a plurality of patent documents, wherein the target law firm entity being an attorney listed on each of the plurality of patent documents, each of the plurality of company entities being of a second entity type and wherein the subset of the stored all company entity records constituting the plurality of company entity records is determined using the issued one or more database system queries; c. using the one or more processors for extracting the information on the plurality of company entities from the plurality of company entity records; d. incorporating using the one or more processors the extracted information on at least two of the plurality of company entities of the second entity type into the interactive report; e. using the one or more processors for determining, for each pair comprising a year from the plurality of years and a company entity from at least two of the plurality of company entities, a quantity of patent documents in the plurality of patent documents corresponding to the pair, each of the plurality of patent documents listing the target law firm entity as an attorney; f. generating using the one or more processors a graphical chart, the graphical chart incorporating, for each pair comprising the year of the plurality of years and the company entity from the at least two of the plurality of company entities, a graphical representation of the determined quantity of patent documents; g. incorporating using the one or more processors the generated graphical chart into the interactive report or associating the graphical chart with the interactive report; and h. causing the interactive report to be provided to the user, wherein the interactive report comprises a user interface portion usable in connection with a web browser; wherein the interactive report comprises a plurality of information items capable of being activated by the user, the plurality of information items forming the user interface portion of the interactive report; and wherein receipt of an indication that at least one information item of the plurality of information items of the user interface portion of the interactive report has been activated by the user causes the one or more processors to generate a second report based on the activated information item and cause the second report to be provided to the user. 12. The computer-implemented method of claim 1 , wherein the plurality of company entities are listed in the interactive report in a ranked manner in accordance with corresponding quantities of patent documents in the plurality of patent documents. | 0.593443 |
8,698,657 | 4 | 5 | 4. The method of claim 1 , wherein determining at least one subpart that correlates the block of data to compress comprises computing fingerprints of several subparts of the block of data to compress as hash values of said subparts and comparing the computed fingerprints with a bank of fingerprints corresponding to subparts of the secondary dictionary. | 4. The method of claim 1 , wherein determining at least one subpart that correlates the block of data to compress comprises computing fingerprints of several subparts of the block of data to compress as hash values of said subparts and comparing the computed fingerprints with a bank of fingerprints corresponding to subparts of the secondary dictionary. 5. The method of claim 4 , wherein determining at least one subpart that correlates with the block of data to compress comprises obtaining a list of subparts of the secondary dictionary, the corresponding fingerprints of which matching with fingerprints for the block of data to compress, and selecting at least one subpart from the list as subpart or subparts to insert into the initial compression dictionary. | 0.608571 |
9,737,759 | 13 | 14 | 13. The non-transitory computer readable media of claim 12 , wherein upon an exercise match not being found in said searching, then searching a user population history for previous matches, and selecting an exercise that has been most often tracked as said exercise to be tracked. | 13. The non-transitory computer readable media of claim 12 , wherein upon an exercise match not being found in said searching, then searching a user population history for previous matches, and selecting an exercise that has been most often tracked as said exercise to be tracked. 14. The non-transitory computer readable media of claim 13 , wherein upon an exercise match not being found in said user population history, processing said parsed cleaned text using a search string modifying algorithm to create a modified text string; performing a fuzzy search on an exercise database for exercise results relevant to said modified text string; scoring said exercise results to create an exercise text match score; and selecting as said exercise to be tracked an exercise having the top score. | 0.5 |
7,730,011 | 15 | 16 | 15. The machine readable medium of claim 13 , wherein the instructions further cause the processor to store the tag in a tag database. | 15. The machine readable medium of claim 13 , wherein the instructions further cause the processor to store the tag in a tag database. 16. The machine-readable medium of claim 15 , wherein the instructions further cause the processor to store the captured object on a storage medium. | 0.5 |
9,553,922 | 1 | 8 | 1. A method for presenting social media content items associated with time-based media events, the method comprising: generating a graph interface element including a set of positions along a time axis, where each position is associated with a different portion of a broadcasted media event, the graph interface element depicting a measure of a plurality of content items that have been authored by one or more users of a social networking system and that have been determined to be correlated with the portions of the broadcasted media event associated with the set of positions; generating a movable interface element that enables selection among the set of positions included in the graph interface element; populating a content timeline interface element with the content items arranged in chronological order, each portion of the content timeline interface element including content items correlated with a different portion of the broadcasted media event; providing a concurrent display of the content interface element, the graph interface element, and the movable interface element; determining selection of a first of the set of positions based on the movable interface element having been visually moved to select the first position; and in response to the selection of the first position, causing the provided content timeline interface element to vertically scroll to a first portion of the content timeline interface element that includes content items correlated with a first portion of the broadcasted media event associated with the selected first position; extracting non-textual content from a plurality of the content items correlated with the first portion of the broadcasted media event; combining the extracted non-textual content to generate a vignette representing the first portion of the broadcasted media event; and including the vignette in a visually distinct portion of the concurrent display. | 1. A method for presenting social media content items associated with time-based media events, the method comprising: generating a graph interface element including a set of positions along a time axis, where each position is associated with a different portion of a broadcasted media event, the graph interface element depicting a measure of a plurality of content items that have been authored by one or more users of a social networking system and that have been determined to be correlated with the portions of the broadcasted media event associated with the set of positions; generating a movable interface element that enables selection among the set of positions included in the graph interface element; populating a content timeline interface element with the content items arranged in chronological order, each portion of the content timeline interface element including content items correlated with a different portion of the broadcasted media event; providing a concurrent display of the content interface element, the graph interface element, and the movable interface element; determining selection of a first of the set of positions based on the movable interface element having been visually moved to select the first position; and in response to the selection of the first position, causing the provided content timeline interface element to vertically scroll to a first portion of the content timeline interface element that includes content items correlated with a first portion of the broadcasted media event associated with the selected first position; extracting non-textual content from a plurality of the content items correlated with the first portion of the broadcasted media event; combining the extracted non-textual content to generate a vignette representing the first portion of the broadcasted media event; and including the vignette in a visually distinct portion of the concurrent display. 8. The method of claim 1 , further comprising displaying to a user a content compose interface that enables the user to compose content items related to the broadcasted media event, the content compose interface being pre-populated with information related to the broadcasted media event. | 0.786667 |
9,781,594 | 8 | 11 | 8. A method comprising: determining, with a computing device, a context for a mobile device based on received electronic signals, wherein the context is either a personal context or a work context; automatically switching the mobile device between different operational modes with the computing device in response to and based upon whether the determined context is the personal context or the work context, automatically accessing and displaying on the mobile device a type of information from a work data storage in response to the determined context being the work context; automatically accessing and displaying on the mobile device the type of information from a personal data storage in response to the determined context being the personal context, wherein the received electronic signals are for an event on the mobile device and wherein determining the context comprises identifying a keyword from the received electronic signals and using the keyword to determine the context; and retrieving and displaying supplemental information for the event based on the keyword, wherein the event comprises a communication with another person and wherein the supplemental information is information related to the other person and wherein the supplemental information related to the other person is selected from a group of supplemental information related to the other person consisting of: biographical/contact information of the other person, prior communications with the other person, prior documents composer reviewed by the other person and information regarding prior meetings held with the other person. | 8. A method comprising: determining, with a computing device, a context for a mobile device based on received electronic signals, wherein the context is either a personal context or a work context; automatically switching the mobile device between different operational modes with the computing device in response to and based upon whether the determined context is the personal context or the work context, automatically accessing and displaying on the mobile device a type of information from a work data storage in response to the determined context being the work context; automatically accessing and displaying on the mobile device the type of information from a personal data storage in response to the determined context being the personal context, wherein the received electronic signals are for an event on the mobile device and wherein determining the context comprises identifying a keyword from the received electronic signals and using the keyword to determine the context; and retrieving and displaying supplemental information for the event based on the keyword, wherein the event comprises a communication with another person and wherein the supplemental information is information related to the other person and wherein the supplemental information related to the other person is selected from a group of supplemental information related to the other person consisting of: biographical/contact information of the other person, prior communications with the other person, prior documents composer reviewed by the other person and information regarding prior meetings held with the other person. 11. The method of claim 8 , wherein the determination of the context for the mobile device based on the received signals is based upon a combination of multiple differently weighted criteria based upon a user input weighting scheme. | 0.56391 |
7,539,982 | 4 | 5 | 4. The method of claim 1 , wherein the current element node of the XML script comprises a component name that references a component, the component being one of a built-in function, a built-in method, a user-defined function, and a user-defined method. | 4. The method of claim 1 , wherein the current element node of the XML script comprises a component name that references a component, the component being one of a built-in function, a built-in method, a user-defined function, and a user-defined method. 5. The method of claim 4 , wherein the component is defined externally to XML and the XML script. | 0.5 |
9,026,944 | 1 | 3 | 1. A method executed at least in part in a computing device for providing a context based menu to manage displayed content, the method comprising: in response to detecting one of: a tap action on a launcher, a tap action on a selection of a portion of displayed content, a tap action on an insertion point gripper, a swipe action on the launcher slower than a predefined speed, a mouse input, and a keyboard input, presenting the context based menu in relation to the displayed content on a user interface, wherein the context based menu includes at least one from a set of: a command and a link to a submenu; in response to detecting a gesture associated with the context based menu, rotating the context based menu, wherein the context based menu rotates without expanding; in response to detecting a press and hold action, displaying a sectional view of the context based menu in a minimized state according to a peek period beginning with the press and hold action and ending upon a withdrawal of the press and hold action to conserve available space on the user interface, wherein a display of the sectional view is in proportion to the peek period; detecting one of a gesture and a touch based action associated with the context based menu, wherein the action includes one of: a selection of a displayed context based menu item and a swipe over a portion of the context based menu; and one of: executing a command and displaying a submenu in response to the detected action, wherein multiple finger gestures are enabled such that swiping over the command with one finger executes the command and swiping over the command with two fingers rotates the context based menu. | 1. A method executed at least in part in a computing device for providing a context based menu to manage displayed content, the method comprising: in response to detecting one of: a tap action on a launcher, a tap action on a selection of a portion of displayed content, a tap action on an insertion point gripper, a swipe action on the launcher slower than a predefined speed, a mouse input, and a keyboard input, presenting the context based menu in relation to the displayed content on a user interface, wherein the context based menu includes at least one from a set of: a command and a link to a submenu; in response to detecting a gesture associated with the context based menu, rotating the context based menu, wherein the context based menu rotates without expanding; in response to detecting a press and hold action, displaying a sectional view of the context based menu in a minimized state according to a peek period beginning with the press and hold action and ending upon a withdrawal of the press and hold action to conserve available space on the user interface, wherein a display of the sectional view is in proportion to the peek period; detecting one of a gesture and a touch based action associated with the context based menu, wherein the action includes one of: a selection of a displayed context based menu item and a swipe over a portion of the context based menu; and one of: executing a command and displaying a submenu in response to the detected action, wherein multiple finger gestures are enabled such that swiping over the command with one finger executes the command and swiping over the command with two fingers rotates the context based menu. 3. The method of claim 1 , further comprising: providing a Most Recently Used (MRU) menu item on the context based menu representing a most recently used item in an associated submenu. | 0.87517 |
9,892,109 | 1 | 7 | 1. A method programmed in a non-transitory memory of a device comprising: a. analyzing a first social networking web page, including parsing the first social networking web page into parsed segments; b. fact checking the first social networking web page to determine a factual accuracy of the first social networking web page by comparing the parsed segments with source information to generate fact check results; c. generating a second social networking web page including generating and naming a new web page file; d. coding, using the device, the fact check results in the second social networking web page based on the comparison of the parsed segments with the source information, wherein coding the fact check results of the first social networking web page in the second social networking web page includes automatically writing programming information and the fact check results in the new web page file, including coding each fact check result after an associated parsed segment; and e. predicting when a user will visit the first social networking web page, and fact checking the first social networking web page before the user visits the first social networking web page, so that when the user attempts to visit the first social networking web page, the user visits the second social networking web page coded with the fact check results, wherein predicting when the user will visit the first social networking web page includes determining locations of links on a current web page by locating link tags and respective pixel positions on a screen, tracking input movements by detecting previous and current pixel positions of a cursor including determining if the cursor is over a link or if the cursor is moving toward the link by projecting a line along a current path of the cursor, and if the cursor is over or going towards the link, the link is predicted to be clicked. | 1. A method programmed in a non-transitory memory of a device comprising: a. analyzing a first social networking web page, including parsing the first social networking web page into parsed segments; b. fact checking the first social networking web page to determine a factual accuracy of the first social networking web page by comparing the parsed segments with source information to generate fact check results; c. generating a second social networking web page including generating and naming a new web page file; d. coding, using the device, the fact check results in the second social networking web page based on the comparison of the parsed segments with the source information, wherein coding the fact check results of the first social networking web page in the second social networking web page includes automatically writing programming information and the fact check results in the new web page file, including coding each fact check result after an associated parsed segment; and e. predicting when a user will visit the first social networking web page, and fact checking the first social networking web page before the user visits the first social networking web page, so that when the user attempts to visit the first social networking web page, the user visits the second social networking web page coded with the fact check results, wherein predicting when the user will visit the first social networking web page includes determining locations of links on a current web page by locating link tags and respective pixel positions on a screen, tracking input movements by detecting previous and current pixel positions of a cursor including determining if the cursor is over a link or if the cursor is moving toward the link by projecting a line along a current path of the cursor, and if the cursor is over or going towards the link, the link is predicted to be clicked. 7. The method of claim 1 wherein the second social networking web page coded with the fact check results of the first social networking web page is temporarily saved but is deleted when an associated cookie is deleted or expires. | 0.943204 |
9,811,399 | 13 | 18 | 13. A computer system for filtering notifications to a user from a device based on an enhanced white list comprising a static white list set by the user and a temporary white list, the computer system comprising: at least one processor, one or more memories, and program instructions executable by the computer to perform a method comprising: monitoring, by the computer, applications and activities on the device which generate notifications to the user to create and maintain a temporary white list to be used with a static white list for notifications to the user; monitoring, by the computer, the applications and activities on the device which generate notifications and determining which of the monitored applications and activities on the device are not present on the static white list; searching for and analyzing, by the computer, activities of the device and user interaction with the device to extract at least keywords and context associated with the activities and user interaction of the device; determining, by the computer, whether the keywords and context extracted are associated with a dependency list between applications of the device and context; and if the keywords and context extracted are present on the dependency list, adding, by the computer, the application and activity on the device as an expiring entry on the temporary white list; receiving, by the computer, a notification from an application of the device for the user; and if the application is on the enhanced white list, allowing the notification from the application to audibly sound to the user through the device. | 13. A computer system for filtering notifications to a user from a device based on an enhanced white list comprising a static white list set by the user and a temporary white list, the computer system comprising: at least one processor, one or more memories, and program instructions executable by the computer to perform a method comprising: monitoring, by the computer, applications and activities on the device which generate notifications to the user to create and maintain a temporary white list to be used with a static white list for notifications to the user; monitoring, by the computer, the applications and activities on the device which generate notifications and determining which of the monitored applications and activities on the device are not present on the static white list; searching for and analyzing, by the computer, activities of the device and user interaction with the device to extract at least keywords and context associated with the activities and user interaction of the device; determining, by the computer, whether the keywords and context extracted are associated with a dependency list between applications of the device and context; and if the keywords and context extracted are present on the dependency list, adding, by the computer, the application and activity on the device as an expiring entry on the temporary white list; receiving, by the computer, a notification from an application of the device for the user; and if the application is on the enhanced white list, allowing the notification from the application to audibly sound to the user through the device. 18. The computer system of claim 13 , wherein the device is in a silent mode, preventing notifications absent from the enhanced white list from sounding to the user. | 0.852415 |
6,094,506 | 1 | 5 | 1. A method in a computer system for generating a shape feature probability matrix for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters each sample handwritten character representing a character and having a sequence of one or more strokes each stroke represented by one of a plurality of shape features that describes a shape of the stroke; determining for each sample handwritten character a shape feature string that represents that character, the shape feature string having the shape feature of each stroke in the sequence of one or more strokes for that character, each of the shape features in a shape feature string having a place within the shape feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible combination of pairs of the plurality of shape features, generating a match count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings, in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings, and in which each of the pair of shape feature strings represents the same character; generating a total count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings and in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the combination of the shape features in the shape feature probability matrix, so that the stored probability values can be used to recognize handwritten characters. | 1. A method in a computer system for generating a shape feature probability matrix for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters each sample handwritten character representing a character and having a sequence of one or more strokes each stroke represented by one of a plurality of shape features that describes a shape of the stroke; determining for each sample handwritten character a shape feature string that represents that character, the shape feature string having the shape feature of each stroke in the sequence of one or more strokes for that character, each of the shape features in a shape feature string having a place within the shape feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible combination of pairs of the plurality of shape features, generating a match count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings, in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings, and in which each of the pair of shape feature strings represents the same character; generating a total count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings and in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the combination of the shape features in the shape feature probability matrix, so that the stored probability values can be used to recognize handwritten characters. 5. The method of claim 1 wherein calculating the probability value includes dividing the generated match count by the generated total count. | 0.943685 |
10,102,288 | 10 | 14 | 10. A computer-implemented method, comprising: receiving a search query from a client application associated with a first user; generating a processed query based on the search query; providing search results to a search result list for the search query, the search results comprising a document and a plurality of other documents; mapping the search query into a query board based on similarity between the processed query and an existing processed query; receiving a control directive from the client application to share the document, wherein the control directive is received from the first client application associated with the first user, and further wherein the control directive causes the document to be shared with at least a second client application associated with a second user without causing at least one of the plurality of other documents to be shared with the second client application associated with the second user; adding the document to be shared to the query board as a shared document; and providing the shared document from the query board to a writable topic board such that a graphical user interface associated with the writable topic board displays shared document, the writable topic board being part of a user interface view of a client application and including one or more search result items as shared documents that can be modified by and shared among multiple users. | 10. A computer-implemented method, comprising: receiving a search query from a client application associated with a first user; generating a processed query based on the search query; providing search results to a search result list for the search query, the search results comprising a document and a plurality of other documents; mapping the search query into a query board based on similarity between the processed query and an existing processed query; receiving a control directive from the client application to share the document, wherein the control directive is received from the first client application associated with the first user, and further wherein the control directive causes the document to be shared with at least a second client application associated with a second user without causing at least one of the plurality of other documents to be shared with the second client application associated with the second user; adding the document to be shared to the query board as a shared document; and providing the shared document from the query board to a writable topic board such that a graphical user interface associated with the writable topic board displays shared document, the writable topic board being part of a user interface view of a client application and including one or more search result items as shared documents that can be modified by and shared among multiple users. 14. The computer-implemented method of claim 10 , comprising: receiving control directives to a shared document contained in a private datastore of a remote device; determining access control information to the private datastore of the remote device; and filtering the shared document to be provided to the writable topic board based on the access control information. | 0.642023 |
4,849,732 | 19 | 22 | 19. The input device according to claim 16, wherein at least one of said input means is a four-directional momentary dip-switch. | 19. The input device according to claim 16, wherein at least one of said input means is a four-directional momentary dip-switch. 22. The input device according to claim 19, wherein said switch is located in said key array of a plurality of input means and mounted to be operably accessible to the thumb of the hand. | 0.5 |
9,564,120 | 2 | 3 | 2. The method of claim 1 , wherein the first speech output is a navigational instruction and the second speech output is a navigational variable. | 2. The method of claim 1 , wherein the first speech output is a navigational instruction and the second speech output is a navigational variable. 3. The method of claim 2 , wherein the navigational instruction is a directional maneuver and the navigational variable is a street name. | 0.5 |
9,678,998 | 10 | 11 | 10. The method of claim 1 , wherein obtaining a content record involves: determining a remote content-name-resolution server associated with at least a portion of the HSVLI; and sending, to the remote content-name-resolution server, a request for the content record associated with the portion of the HSVLI. | 10. The method of claim 1 , wherein obtaining a content record involves: determining a remote content-name-resolution server associated with at least a portion of the HSVLI; and sending, to the remote content-name-resolution server, a request for the content record associated with the portion of the HSVLI. 11. The method of claim 10 , further comprising: responsive to receiving the content record from the remote content-name-resolution server, storing the content record in association with the portion of the HSVLI. | 0.5 |
8,533,211 | 16 | 18 | 16. An article of manufacture for bridging terminology differences between at least two subject areas, comprising a non-transitory computer readable storage medium including one or more computer programs that when executed by a computer perform the steps of: computing a first affinity measure between a first term in a first corpus, corresponding to a first subject area, and a bridge term; computing a second affinity measure between a second term in a second corpus, corresponding to a second subject area, and the bridge term; and computing a third affinity measure between the first term and the second term based on the first affinity measure and the second affinity measure; wherein the bridge term is a term that appears in both the first corpus and the second corpus, and wherein computing at least one of the first affinity measure and the second affinity measure comprises computing a transitive closure of an affinity matrix of at least one of the first corpus and the second corpus; and assigning a score for a pair of terms in the transitive closure of the affinity matrix using a composite path probability, wherein the composite path probability is a computation of a sum of path probabilities for n paths between the pair of terms, wherein n is an integer greater than 0. | 16. An article of manufacture for bridging terminology differences between at least two subject areas, comprising a non-transitory computer readable storage medium including one or more computer programs that when executed by a computer perform the steps of: computing a first affinity measure between a first term in a first corpus, corresponding to a first subject area, and a bridge term; computing a second affinity measure between a second term in a second corpus, corresponding to a second subject area, and the bridge term; and computing a third affinity measure between the first term and the second term based on the first affinity measure and the second affinity measure; wherein the bridge term is a term that appears in both the first corpus and the second corpus, and wherein computing at least one of the first affinity measure and the second affinity measure comprises computing a transitive closure of an affinity matrix of at least one of the first corpus and the second corpus; and assigning a score for a pair of terms in the transitive closure of the affinity matrix using a composite path probability, wherein the composite path probability is a computation of a sum of path probabilities for n paths between the pair of terms, wherein n is an integer greater than 0. 18. The article of claim 16 , wherein the bridge term is selected by a user. | 0.814634 |
8,645,248 | 31 | 32 | 31. A computer implemented method of providing integrated customer communications, comprising: generating documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from at least one component of the account opening system, and static content for the templates received from a content repository, wherein said generating comprises: receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; managing documents associated with the communications; and maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; transmitting the communications via one or more transmission channels; managing the templates and the content; and storing, retrieving, and managing storage of the documents, wherein he managing the templates comprises creating, previewing, editing, maintaining and deleting communication templates for different channels, defining what data items are included in the communication, inserting dynamic variables that vary by at least one of channel and communication type, defining a source of the dynamic data for the communication, and making deployments to various environments for validation. | 31. A computer implemented method of providing integrated customer communications, comprising: generating documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from at least one component of the account opening system, and static content for the templates received from a content repository, wherein said generating comprises: receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; managing documents associated with the communications; and maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; transmitting the communications via one or more transmission channels; managing the templates and the content; and storing, retrieving, and managing storage of the documents, wherein he managing the templates comprises creating, previewing, editing, maintaining and deleting communication templates for different channels, defining what data items are included in the communication, inserting dynamic variables that vary by at least one of channel and communication type, defining a source of the dynamic data for the communication, and making deployments to various environments for validation. 32. The computer implemented method of providing customer communications of claim 31 , further comprising transmitting the documents to at least one of multiple channels and multiple recipients. | 0.844051 |
7,870,163 | 17 | 18 | 17. The computer-readable storage medium of claim 16 , wherein the one or more sequences of instructions, when executed by the one or more processors, further cause the one or more processors to perform determining a kidnum value for the new element. | 17. The computer-readable storage medium of claim 16 , wherein the one or more sequences of instructions, when executed by the one or more processors, further cause the one or more processors to perform determining a kidnum value for the new element. 18. The computer-readable storage medium of claim 17 , wherein the kidnum value for the new element comprises a value greater than the highest kidnum value associated with a kidnum value for each attribute in a set of attributes. | 0.575926 |
8,254,647 | 1 | 4 | 1. A method comprising: capturing, by a camera of a mobile computing device, an image; generating, by the mobile computing device, a facial detection confidence score based at least in part on a likelihood that a representation of at least a portion of a face is included in the image; generating, by the mobile computing device, a facial landmark detection confidence score based at least in part on a likelihood that representations of facial landmarks are accurately identified in the image; generating, by the mobile computing device, a geometric consistency score based at least in part on a difference between a point of intersection between a nose base and a line segment that passes through each eye and a midpoint of the line segment in the image; generating, by the mobile computing device, an image quality score based at least in part on a combination of the facial detection confidence score, the facial landmark detection confidence score, and the geometric consistency score; and classifying, by the mobile computing device, a quality of the image based at least in part on the image quality score. | 1. A method comprising: capturing, by a camera of a mobile computing device, an image; generating, by the mobile computing device, a facial detection confidence score based at least in part on a likelihood that a representation of at least a portion of a face is included in the image; generating, by the mobile computing device, a facial landmark detection confidence score based at least in part on a likelihood that representations of facial landmarks are accurately identified in the image; generating, by the mobile computing device, a geometric consistency score based at least in part on a difference between a point of intersection between a nose base and a line segment that passes through each eye and a midpoint of the line segment in the image; generating, by the mobile computing device, an image quality score based at least in part on a combination of the facial detection confidence score, the facial landmark detection confidence score, and the geometric consistency score; and classifying, by the mobile computing device, a quality of the image based at least in part on the image quality score. 4. The method of claim 1 , wherein the facial landmarks comprise at least the nose base and each eye. | 0.922901 |
8,126,837 | 1 | 8 | 1. A method, comprising: receiving a portion of text from a document; associating a document type with the document based on at least one of the portion of text or an identifier associated with the document; and selecting, based on the document type, a document template having a plurality of sections, each section from the plurality of sections being associated with a document category, at least one section from the plurality of sections being associated with at least one policy preference. | 1. A method, comprising: receiving a portion of text from a document; associating a document type with the document based on at least one of the portion of text or an identifier associated with the document; and selecting, based on the document type, a document template having a plurality of sections, each section from the plurality of sections being associated with a document category, at least one section from the plurality of sections being associated with at least one policy preference. 8. The method of claim 1 , wherein the receiving includes receiving in response to a request to access content associated with the document. | 0.794118 |
8,612,202 | 1 | 2 | 1. An information analysis device that uses a plurality of linguistic expressions as an analysis target, comprising: a link information generating unit and a correlation value calculation unit, the link information generating unit and the correlation value calculation unit being implemented by a CPU, wherein the link information generating unit extracts time information included in each of a plurality of electronic documents including at least any one of the plurality of linguistic expressions and a relationship between the electronic documents in the plurality of electronic documents from the plurality of electronic documents, detects a link between one linguistic expression and another linguistic expression in the plurality of linguistic expressions and an appearance time of the link based on the extracted time information and the relationship between the electronic documents, and generates link information specifying the extracted link and the appearance time of the link, and the correlation value calculation unit specifies the number of appearances of links between the one linguistic expression and the other linguistic expression and an appearance time of each link based on the link information, and calculates a correlation value between the one linguistic expression and the other linguistic expression by using the specified number of appearances of the link and the appearance time of each link, the calculation of the correlation value being made by using a function that increases depending on a difference between first appearance time of one link and second appearance time of another link. | 1. An information analysis device that uses a plurality of linguistic expressions as an analysis target, comprising: a link information generating unit and a correlation value calculation unit, the link information generating unit and the correlation value calculation unit being implemented by a CPU, wherein the link information generating unit extracts time information included in each of a plurality of electronic documents including at least any one of the plurality of linguistic expressions and a relationship between the electronic documents in the plurality of electronic documents from the plurality of electronic documents, detects a link between one linguistic expression and another linguistic expression in the plurality of linguistic expressions and an appearance time of the link based on the extracted time information and the relationship between the electronic documents, and generates link information specifying the extracted link and the appearance time of the link, and the correlation value calculation unit specifies the number of appearances of links between the one linguistic expression and the other linguistic expression and an appearance time of each link based on the link information, and calculates a correlation value between the one linguistic expression and the other linguistic expression by using the specified number of appearances of the link and the appearance time of each link, the calculation of the correlation value being made by using a function that increases depending on a difference between first appearance time of one link and second appearance time of another link. 2. The information analysis device according to claim 1 , wherein the link information generating unit extracts a reference relationship between the one linguistic expression and the other linguistic expression in the plurality of electronic documents as the relationship between the electronic documents in the plurality of electronic documents. | 0.688849 |
8,938,455 | 28 | 29 | 28. The method of claim 27 , further comprising providing a result to the user in response to the one or more user-entered queries. | 28. The method of claim 27 , further comprising providing a result to the user in response to the one or more user-entered queries. 29. The method of claim 28 , further comprising forming the result before providing the results to the user. | 0.5 |
9,152,979 | 14 | 15 | 14. The non-transitory processor readable medium of claim 12 , wherein the processor executable instructions when executed by the processor cause the processor to execute a bidding function in which the one or more selected branded visual content is presented to a user of the user device based on a bid placed by the one or more advertiser. | 14. The non-transitory processor readable medium of claim 12 , wherein the processor executable instructions when executed by the processor cause the processor to execute a bidding function in which the one or more selected branded visual content is presented to a user of the user device based on a bid placed by the one or more advertiser. 15. The non-transitory processor readable medium of claim 14 , wherein the bidding function causes the branded visual content associated with a highest bid to receive a highest priority for transmission to the user device. | 0.5 |
9,899,019 | 1 | 17 | 1. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: receive an input from a user; determine, using a first n-gram language model, a first probability of a stem based at least on a first portion of a previously-input word in the received input; determine, using a second n-gram language model, a second probability of a first suffix based at least on a second portion of the previously-input word in the received input; determine, using a third n-gram language model, a third probability of a second suffix different from the first suffix based at least on a third portion of the previously-input word in the received input, wherein the third n-gram language model includes a tense suffix n-gram language model, and the determining of the third probability of the second suffix includes determining the third probability of a tense suffix based at least in part on a second tense suffix of the previously-input word; determine a fourth probability of at least one predicted word based on the first probability, the second probability and the third probability; and provide an output of the at least one predicted word to the user based on the fourth probability, wherein providing the output comprises at least one of displaying the predicted word or providing an audible playback of the predicted word. | 1. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: receive an input from a user; determine, using a first n-gram language model, a first probability of a stem based at least on a first portion of a previously-input word in the received input; determine, using a second n-gram language model, a second probability of a first suffix based at least on a second portion of the previously-input word in the received input; determine, using a third n-gram language model, a third probability of a second suffix different from the first suffix based at least on a third portion of the previously-input word in the received input, wherein the third n-gram language model includes a tense suffix n-gram language model, and the determining of the third probability of the second suffix includes determining the third probability of a tense suffix based at least in part on a second tense suffix of the previously-input word; determine a fourth probability of at least one predicted word based on the first probability, the second probability and the third probability; and provide an output of the at least one predicted word to the user based on the fourth probability, wherein providing the output comprises at least one of displaying the predicted word or providing an audible playback of the predicted word. 17. The non-transitory computer-readable storage medium of claim 1 , wherein the received input is a voice input. | 0.88745 |
9,426,110 | 10 | 13 | 10. A computer system for filtering messages of a social network, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify a set of languages included in a settings file of a first user of a social network; program instructions to determine which language is used to compose a message sent or received by the first user of the social network, by accessing a language library, wherein the message sent or received by the first user of the social network is an audio message that is converted in part to text using speech recognition and audio language libraries for determining a language in which the audio message is composed; program instructions to determine whether a language that is used to compose the message that is sent or received is included in the set of languages of the settings file of the first user of the social network; in response to determining that the message that is received is composed in a language that is not included in the set of languages of the settings file of the first user, program instructions to prompt the first user to indicate whether the language is to be added to the set of languages of the first user; in response to determining that the message that is sent is composed in a language that is not included in the set of languages of the settings file of the first user, program instructions to prompt the first user to indicate whether the language is to be added to the set of languages of the first user; in response to receiving a confirmation from the first user to add the second language to the set of languages of the first user, program instructions to add the language to the set of languages of the first user; and in response to a denial by the first user to add the language to the set of languages of the first user, program instructions to filter messages composed in the language that are directed to the first user from the social network, wherein the messages that are filtered are blocked from display to the first user of the social network. | 10. A computer system for filtering messages of a social network, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify a set of languages included in a settings file of a first user of a social network; program instructions to determine which language is used to compose a message sent or received by the first user of the social network, by accessing a language library, wherein the message sent or received by the first user of the social network is an audio message that is converted in part to text using speech recognition and audio language libraries for determining a language in which the audio message is composed; program instructions to determine whether a language that is used to compose the message that is sent or received is included in the set of languages of the settings file of the first user of the social network; in response to determining that the message that is received is composed in a language that is not included in the set of languages of the settings file of the first user, program instructions to prompt the first user to indicate whether the language is to be added to the set of languages of the first user; in response to determining that the message that is sent is composed in a language that is not included in the set of languages of the settings file of the first user, program instructions to prompt the first user to indicate whether the language is to be added to the set of languages of the first user; in response to receiving a confirmation from the first user to add the second language to the set of languages of the first user, program instructions to add the language to the set of languages of the first user; and in response to a denial by the first user to add the language to the set of languages of the first user, program instructions to filter messages composed in the language that are directed to the first user from the social network, wherein the messages that are filtered are blocked from display to the first user of the social network. 13. The computer system of claim 10 , further comprising: in response to the computer processor receiving a confirmation from the first user to add the language to the set of languages of the settings file of the first user, program instructions to suppress subsequent prompting of the first user to confirm adding the language to the set of languages in the settings file of the first user. | 0.5 |
9,298,943 | 10 | 22 | 10. The system of claim 1 , further comprising a plurality of profiles stored in memory of the electronic device, the geotag profile being one of the plurality of profiles. | 10. The system of claim 1 , further comprising a plurality of profiles stored in memory of the electronic device, the geotag profile being one of the plurality of profiles. 22. The system of claim 10 , wherein one of the plurality of profiles is a customized profile including a custom location, and the metadata modification component selects one or more relevant profiles; wherein when the one or more relevant profiles includes the customized profile, the metadata modification component overwrites any geolocation metadata in the selected content metadata with the custom location when generating the sharing version of the selected content metadata. | 0.5 |
8,055,642 | 1 | 6 | 1. A method comprising: providing a first set of instructions configured to cause a client device to: parse a displayed portion of content, locate a set of terms in the displayed portion of content, based on the parsing; and, in response to locating the set of terms, send the set of terms to a server; receiving, at the server, from the client device, a first request comprising the set of terms; based on the set of terms, the server identifying one or more coupon offers; in response to the first request, the server sending to the client device a second set of instructions configured to cause the client device to: display, in association with a particular term in the displayed portion of content, an interface comprising information about the one or more coupon offers and a control for selecting a particular coupon offer of the one or more coupon offers; and, upon a user selecting the control, send information identifying the particular coupon offer to a coupon distribution server; wherein the second set of instructions is further configured to cause display of a plurality of interfaces, each interface of the plurality of interfaces configured to appear in association with a different term of the set of terms, and each interface of the plurality of interfaces comprising information about at least one coupon offer, of the one or more coupon offers, that was identified by the server based on the different term in association with which the interface is configured to appear; receiving, at the coupon distribution server, from the client device, a second request identifying the particular coupon offer; in response to the second request, the coupon distribution server providing the user with a coupon corresponding to the particular coupon offer; wherein at least the steps of identifying one or more coupon offers and providing the coupon are performed by one or more computing devices. | 1. A method comprising: providing a first set of instructions configured to cause a client device to: parse a displayed portion of content, locate a set of terms in the displayed portion of content, based on the parsing; and, in response to locating the set of terms, send the set of terms to a server; receiving, at the server, from the client device, a first request comprising the set of terms; based on the set of terms, the server identifying one or more coupon offers; in response to the first request, the server sending to the client device a second set of instructions configured to cause the client device to: display, in association with a particular term in the displayed portion of content, an interface comprising information about the one or more coupon offers and a control for selecting a particular coupon offer of the one or more coupon offers; and, upon a user selecting the control, send information identifying the particular coupon offer to a coupon distribution server; wherein the second set of instructions is further configured to cause display of a plurality of interfaces, each interface of the plurality of interfaces configured to appear in association with a different term of the set of terms, and each interface of the plurality of interfaces comprising information about at least one coupon offer, of the one or more coupon offers, that was identified by the server based on the different term in association with which the interface is configured to appear; receiving, at the coupon distribution server, from the client device, a second request identifying the particular coupon offer; in response to the second request, the coupon distribution server providing the user with a coupon corresponding to the particular coupon offer; wherein at least the steps of identifying one or more coupon offers and providing the coupon are performed by one or more computing devices. 6. The method of claim 1 , further comprising: in response to the first request, the coupon distribution server identifying a plurality of coupon offers based on the set of terms; the coupon distribution server returning a presentation of information about the plurality of coupon offers, the presentation being prioritized based on the number of times coupons have previously printed or redeemed coupons for each coupon offer in the plurality of coupon offers. | 0.5 |
7,779,002 | 1 | 6 | 1. A method comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and presenting the set of final search results. | 1. A method comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and presenting the set of final search results. 6. The method of claim 1 wherein the set of final search results includes Web pages. | 0.925926 |
7,499,893 | 13 | 15 | 13. A method for creating a digital life form, comprising: defining a digital life form; providing access for the digital life form to an environment; defining a plurality of potential actions for the digital life form; providing at least one object in the environment; providing the object with at least one characteristic; providing the digital life form with the ability to form percepts based on the characteristics of objects encountered, to store the formed percepts, and to use the stored percepts to identify subsequently encountered objects; providing the digital life form with the ability to select from said plurality of potential actions based, at least in part, on the percepts; and providing consequences to the digital life form for such actions; wherein the digital life form selects from said plurality of potential actions in order to avoid certain of the consequences with a primary objective being the continued existence of the digital life form; the digital life form arbitrarily selects an action when there is insufficient data to determine whether an action will further the primary objective; and the digital life form stores data indicative of the effectiveness of selected actions in furthering the primary objective for use in future action selections. | 13. A method for creating a digital life form, comprising: defining a digital life form; providing access for the digital life form to an environment; defining a plurality of potential actions for the digital life form; providing at least one object in the environment; providing the object with at least one characteristic; providing the digital life form with the ability to form percepts based on the characteristics of objects encountered, to store the formed percepts, and to use the stored percepts to identify subsequently encountered objects; providing the digital life form with the ability to select from said plurality of potential actions based, at least in part, on the percepts; and providing consequences to the digital life form for such actions; wherein the digital life form selects from said plurality of potential actions in order to avoid certain of the consequences with a primary objective being the continued existence of the digital life form; the digital life form arbitrarily selects an action when there is insufficient data to determine whether an action will further the primary objective; and the digital life form stores data indicative of the effectiveness of selected actions in furthering the primary objective for use in future action selections. 15. The method of claim 13 , wherein: said environment is a computer generated simulated environment. | 0.728495 |
10,115,215 | 2 | 3 | 2. The computing device implemented method of claim 1 , further comprising: initiating presentation of the pairing of the font and the at least one other font. | 2. The computing device implemented method of claim 1 , further comprising: initiating presentation of the pairing of the font and the at least one other font. 3. The computing device implemented method of claim 2 , wherein initiating presentation of the pairing of the font and the at least one other font includes prioritizing the pairing for presentation based upon customer interest. | 0.506522 |
8,495,595 | 9 | 11 | 9. A computer program product, comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to receive an application written in a domain-specific language (DSL) for a programming task, wherein the application includes a plurality of components configured by expressions; computer readable program code configured to select from a plurality of techniques for evaluating the expressions a technique that most quickly implements the programming task; and computer readable program code configured to configure a compiler, which compiles the DSL application to generate general-purpose programming language (GPL) code, to use the selected expression evaluation technique, wherein in response to selecting an expression evaluation technique, the computer readable program code of the computer readable storage medium further comprises: computer readable program code configured to evaluate parts of expressions that do not require knowledge of run-time values; computer readable program code configured to replace the evaluated parts of the expressions with placeholder variables; computer readable program code configured to compile the DSL application to generate GPL code, wherein partially evaluated expressions and code to load values of the placeholder variables are embedded into the generated GPL code, wherein the partially evaluated expressions comprise expressions including the evaluated expression parts that were replaced with the placeholder variables; computer readable program code configured to compile the generated GPL code into native processor instructions; and computer readable program code configured to load the values of the placeholder variables and execute the partially evaluated expressions in response to running the native processor instructions. | 9. A computer program product, comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to receive an application written in a domain-specific language (DSL) for a programming task, wherein the application includes a plurality of components configured by expressions; computer readable program code configured to select from a plurality of techniques for evaluating the expressions a technique that most quickly implements the programming task; and computer readable program code configured to configure a compiler, which compiles the DSL application to generate general-purpose programming language (GPL) code, to use the selected expression evaluation technique, wherein in response to selecting an expression evaluation technique, the computer readable program code of the computer readable storage medium further comprises: computer readable program code configured to evaluate parts of expressions that do not require knowledge of run-time values; computer readable program code configured to replace the evaluated parts of the expressions with placeholder variables; computer readable program code configured to compile the DSL application to generate GPL code, wherein partially evaluated expressions and code to load values of the placeholder variables are embedded into the generated GPL code, wherein the partially evaluated expressions comprise expressions including the evaluated expression parts that were replaced with the placeholder variables; computer readable program code configured to compile the generated GPL code into native processor instructions; and computer readable program code configured to load the values of the placeholder variables and execute the partially evaluated expressions in response to running the native processor instructions. 11. The computer program product of claim 9 , wherein in response to selecting an expression evaluation technique, the computer readable program code of the computer readable storage medium further comprises: computer readable program code configured to compile the DSL application to generate GPL code, wherein expressions that are used to parameterize the components are directly embedded into the generated GPL code; and computer readable program code configured to compile the generated GPL code into native processor instructions. | 0.683057 |
5,382,100 | 1 | 7 | 1. A wordprocessing device wherein characters having a first size add a second size different from said first size are able to be mixedly arranged on a line, said device comprises: justifying means for justifying a plurality of characters over a plurality of lines by inserting additional spaces that includes a first space and a second space different from said first space between respective pairs of adjacent characters on respective lines to be justified wherein the second character size is smaller than the first character size and the second space is smaller than the first space and said second means determines said second space is to be inserted between an adjacent pair of characters when both characters of said pair of adjacent characters are the second size; first means for determining a total space to be distributed over each line of said plurality of lines; and second means for determining the first and second space for the additional space to be inserted between each pair of characters on each line based upon the total space determined by said first determining means in accordance with the first and second size of the character sizes of said pair of characters. | 1. A wordprocessing device wherein characters having a first size add a second size different from said first size are able to be mixedly arranged on a line, said device comprises: justifying means for justifying a plurality of characters over a plurality of lines by inserting additional spaces that includes a first space and a second space different from said first space between respective pairs of adjacent characters on respective lines to be justified wherein the second character size is smaller than the first character size and the second space is smaller than the first space and said second means determines said second space is to be inserted between an adjacent pair of characters when both characters of said pair of adjacent characters are the second size; first means for determining a total space to be distributed over each line of said plurality of lines; and second means for determining the first and second space for the additional space to be inserted between each pair of characters on each line based upon the total space determined by said first determining means in accordance with the first and second size of the character sizes of said pair of characters. 7. The wordprocessing device according to claim 1 which further comprises a print means for printing said characters on a recording medium. | 0.735741 |
10,049,147 | 48 | 49 | 48. The apparatus of claim 27 is configured to: upon receiving a sending command for the designated document or any one of the at least one multimedia resources in the designated document, send the at least one multimedia resource corresponding to the sending command to a subject as indicated by the sending command. | 48. The apparatus of claim 27 is configured to: upon receiving a sending command for the designated document or any one of the at least one multimedia resources in the designated document, send the at least one multimedia resource corresponding to the sending command to a subject as indicated by the sending command. 49. The apparatus of claim 48 is configured to perform at least one of: in case that the sending command carries a personal contact, send the designated document or the at least one multimedia resource corresponding to the sending command to the personal contact; in case that the sending command is a sharing command, share the designated document corresponding to the sending command or the first resource identification associated with the multimedia resource; and in case that the sending command is an uploading command, upload the designated document corresponding to the sending command or the multimedia resource to a personal dynamic information display platform. | 0.5 |
7,734,619 | 1 | 3 | 1. A method of presenting to a user a lineage diagram representing a query plan, the method comprising: receiving by a computer a query plan from a query engine during a query planning mode when a logical query is processed by the query engine to generate the query plan, the query plan containing transformations used to convert the logical query into one or more native queries that are applicable to databases storing data relevant to the native queries; generating, during the query planning mode, a lineage diagram representing the query plan using one or more query subjects and one or more symbolic links representing the transformations and conceptual data streams between the query subjects connected by the symbolic links, wherein at least a first query subject in the lineage diagram references a second query subject defined by a metadata model describing a plurality of layers of abstraction of the database storing data relevant to the native queries, and wherein at least one query subject in the lineage diagram references a database table present in one of the databases storing data relevant to the native queries; receiving user selection of a query subject presented in the lineage diagram; changing, in the lineage diagram, presentation of the selected query subject to show one or more corresponding query subjects that are represented by the selected query subject such that lineage of the selected query subject is interactively shown in the diagram using the corresponding query subjects in a same or different layer of the metadata model; allowing the user to select one of the symbolic links visual in a current view; and expanding or collapsing the selected symbolic link to show or hide one or more query subjects that are represented by the selected symbolic link based on the user's selection. | 1. A method of presenting to a user a lineage diagram representing a query plan, the method comprising: receiving by a computer a query plan from a query engine during a query planning mode when a logical query is processed by the query engine to generate the query plan, the query plan containing transformations used to convert the logical query into one or more native queries that are applicable to databases storing data relevant to the native queries; generating, during the query planning mode, a lineage diagram representing the query plan using one or more query subjects and one or more symbolic links representing the transformations and conceptual data streams between the query subjects connected by the symbolic links, wherein at least a first query subject in the lineage diagram references a second query subject defined by a metadata model describing a plurality of layers of abstraction of the database storing data relevant to the native queries, and wherein at least one query subject in the lineage diagram references a database table present in one of the databases storing data relevant to the native queries; receiving user selection of a query subject presented in the lineage diagram; changing, in the lineage diagram, presentation of the selected query subject to show one or more corresponding query subjects that are represented by the selected query subject such that lineage of the selected query subject is interactively shown in the diagram using the corresponding query subjects in a same or different layer of the metadata model; allowing the user to select one of the symbolic links visual in a current view; and expanding or collapsing the selected symbolic link to show or hide one or more query subjects that are represented by the selected symbolic link based on the user's selection. 3. The method as claimed in claim 1 , wherein generating the lineage diagram uses one or more process nodes having symbols to indicate the transformations. | 0.606599 |
9,922,344 | 1 | 9 | 1. A method performed by data processing apparatus, the method comprising: receiving, from a search interface presented at a user device, a request for advertisements, the request specifying a set of query suggestions, wherein the set of query suggestions has been identified for a partial query received from the search interface presented by the user device in response to a time delay between characters having been entered in a query input field of the search interface; accessing an index that includes a ranking of the query suggestions, wherein the ranking was performed prior to receiving the request for advertisements and is based, at least in part, on a probability of each query suggestion being selected by a user that input the partial query, and is based, at least in part, on a length of each query suggestion, wherein the query suggestions have been ranked (i) by the probability of each query suggestion being selected by the user, such that the query suggestion is ranked higher when the query suggestion has a higher probability of being selected by the user, and (ii) by the length of each query suggestion, such that a shorter query suggestion is ranked higher among multiple query suggestions that each have a similar probability of being selected by the user; selecting a proper subset of the query suggestions, the proper subset including at least a highest ranked query suggestion based on the ranking, a second query suggestion, and a third query suggestion, wherein each query suggestion of the proper subset of the query suggestions has been classified with a corresponding topic; identifying a topic of the highest ranked query suggestion, a topic of the second query suggestion, and a topic of the third query suggestion; identifying a first advertisement based on the highest ranked query suggestion; determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion, wherein the second query suggestion of the proper subset is different from the highest ranked query suggestion; determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion, wherein the third query suggestion of the proper subset is different from the highest ranked query suggestion and the second query suggestion; identifying a second advertisement based on the third query suggestion as a result of determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion and determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion; providing, to the user device, data that causes presentation of the identified first and second advertisements at the user device; and dynamically updating the search interface presented by the user device to include the first advertisement and the second advertisement. | 1. A method performed by data processing apparatus, the method comprising: receiving, from a search interface presented at a user device, a request for advertisements, the request specifying a set of query suggestions, wherein the set of query suggestions has been identified for a partial query received from the search interface presented by the user device in response to a time delay between characters having been entered in a query input field of the search interface; accessing an index that includes a ranking of the query suggestions, wherein the ranking was performed prior to receiving the request for advertisements and is based, at least in part, on a probability of each query suggestion being selected by a user that input the partial query, and is based, at least in part, on a length of each query suggestion, wherein the query suggestions have been ranked (i) by the probability of each query suggestion being selected by the user, such that the query suggestion is ranked higher when the query suggestion has a higher probability of being selected by the user, and (ii) by the length of each query suggestion, such that a shorter query suggestion is ranked higher among multiple query suggestions that each have a similar probability of being selected by the user; selecting a proper subset of the query suggestions, the proper subset including at least a highest ranked query suggestion based on the ranking, a second query suggestion, and a third query suggestion, wherein each query suggestion of the proper subset of the query suggestions has been classified with a corresponding topic; identifying a topic of the highest ranked query suggestion, a topic of the second query suggestion, and a topic of the third query suggestion; identifying a first advertisement based on the highest ranked query suggestion; determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion, wherein the second query suggestion of the proper subset is different from the highest ranked query suggestion; determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion, wherein the third query suggestion of the proper subset is different from the highest ranked query suggestion and the second query suggestion; identifying a second advertisement based on the third query suggestion as a result of determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion and determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion; providing, to the user device, data that causes presentation of the identified first and second advertisements at the user device; and dynamically updating the search interface presented by the user device to include the first advertisement and the second advertisement. 9. The method of claim 1 , further comprising: receiving query data defining the partial query, the partial query being query input from the user device and having one or more characters ordered in an input sequence that defines an order in which the one or more characters were input as the query input; and identifying the set of query suggestions based on the partial query. | 0.673875 |
9,720,898 | 11 | 12 | 11. The computer-implemented system of claim 10 , wherein the row height measurement module is responsive to scrolling inputs from users viewing a view of the document model, and is programmed to determine a view area around a current viewport being displayed to the user. | 11. The computer-implemented system of claim 10 , wherein the row height measurement module is responsive to scrolling inputs from users viewing a view of the document model, and is programmed to determine a view area around a current viewport being displayed to the user. 12. The computer-implemented system of claim 11 , wherein at least part of the current viewport differs from a prior viewport for the document. | 0.5 |
9,460,344 | 9 | 10 | 9. The method of claim 8 , wherein the one or more logogram phrases are generated in response to a usage history. | 9. The method of claim 8 , wherein the one or more logogram phrases are generated in response to a usage history. 10. The method of claim 9 , wherein the usage history comprises one or more of a personal usage frequency for a plurality of logogram phrases and a communal usage frequency for the plurality of logogram phrases. | 0.5 |
8,794,972 | 6 | 8 | 6. The method of claim 1 further comprising the steps of: determining whether one of the sentences in the legal text includes a primary conjunction; and in response to a determination that one of the sentences in the legal text includes a primary conjunction, applying the primary conjunction marking to the legal text such that the primary conjunction is visually enhanced. | 6. The method of claim 1 further comprising the steps of: determining whether one of the sentences in the legal text includes a primary conjunction; and in response to a determination that one of the sentences in the legal text includes a primary conjunction, applying the primary conjunction marking to the legal text such that the primary conjunction is visually enhanced. 8. The method of claim 6 wherein the primary conjunction marking comprises a box that surrounds the primary conjunction. | 0.842932 |
8,155,943 | 1 | 4 | 1. A computer system for converting a computer aided design drawing file of an electrical power system comprising a plurality of components into one or more component objects for power analytic analysis and simulation, the computer system comprising: at least one processor; a memory; at least one executable software module configured to, when executed by the at least one processor, import the computer aided design drawing file to the memory, parse the computer aided design drawing file into a plurality of component objects corresponding to the plurality of components of the electrical power system, each of the plurality of component objects comprising a component symbol, assign a component classification to the component symbol of each of the plurality of component objects, wherein the component classification comprises one or more attributes which define at least one of an electrical characteristic, connectivity characteristic, and interdependency characteristic of the associated component object, receive a modification of one or more attributes of a component classification, and update the computer aided design drawing file based on the modification; a virtual system model of the electrical power system, wherein the virtual system model comprises virtual component data corresponding to the plurality of components of the electrical power system; and an analytics engine configured to monitor real-time data from one or more sensors interfaced with the electrical power system, monitor predicted operational data generated using the virtual system model, synchronize the virtual system model in real-time based on a difference between the real-time data and the predicted operational data, and update the virtual system model based on the updated computer aided design drawing file. | 1. A computer system for converting a computer aided design drawing file of an electrical power system comprising a plurality of components into one or more component objects for power analytic analysis and simulation, the computer system comprising: at least one processor; a memory; at least one executable software module configured to, when executed by the at least one processor, import the computer aided design drawing file to the memory, parse the computer aided design drawing file into a plurality of component objects corresponding to the plurality of components of the electrical power system, each of the plurality of component objects comprising a component symbol, assign a component classification to the component symbol of each of the plurality of component objects, wherein the component classification comprises one or more attributes which define at least one of an electrical characteristic, connectivity characteristic, and interdependency characteristic of the associated component object, receive a modification of one or more attributes of a component classification, and update the computer aided design drawing file based on the modification; a virtual system model of the electrical power system, wherein the virtual system model comprises virtual component data corresponding to the plurality of components of the electrical power system; and an analytics engine configured to monitor real-time data from one or more sensors interfaced with the electrical power system, monitor predicted operational data generated using the virtual system model, synchronize the virtual system model in real-time based on a difference between the real-time data and the predicted operational data, and update the virtual system model based on the updated computer aided design drawing file. 4. The computer system for converting a computer aided design drawing file of an electrical power system into one or more component objects for power analytic analysis and simulation, as recited in claim 1 , wherein the computer aided design drawing file is imported from a storage device that is communicatively connected to the memory. | 0.58701 |
7,822,749 | 8 | 11 | 8. A computer-readable media whose contents cause a single computing device to perform a method, the method comprising: identifying a first set of data stored within a data store, the first set of data generated by a first application; automatically determining, by a first data agent specific to only the first application that generated the first set of data, a first set of classifications that describe the first set of data, wherein the first set of classifications describe characteristics of the first set of data, and wherein at least some of the first set of classifications are not stored with the first set of data and are based on information about the first application that generated the first set of data; creating a first set of metadata containing information about the first set of data including the determined first set of classifications; identifying a second set of data stored within the data store, the second set of data generated by a second application different from the first application; automatically determining, by a second data agent specific to only the second application that generated the second set of data, a second set of classifications that describe the second set of data, wherein the second set of classifications describe characteristics of the second set of data, and wherein at least some of the second set of classifications are not stored with the second set of data and are based on information about the second application that generated the second set of data; creating a second set of metadata containing information about the second set of data including the determined first second of classifications; and storing the first and second sets of metadata in a non-volatile storage device. | 8. A computer-readable media whose contents cause a single computing device to perform a method, the method comprising: identifying a first set of data stored within a data store, the first set of data generated by a first application; automatically determining, by a first data agent specific to only the first application that generated the first set of data, a first set of classifications that describe the first set of data, wherein the first set of classifications describe characteristics of the first set of data, and wherein at least some of the first set of classifications are not stored with the first set of data and are based on information about the first application that generated the first set of data; creating a first set of metadata containing information about the first set of data including the determined first set of classifications; identifying a second set of data stored within the data store, the second set of data generated by a second application different from the first application; automatically determining, by a second data agent specific to only the second application that generated the second set of data, a second set of classifications that describe the second set of data, wherein the second set of classifications describe characteristics of the second set of data, and wherein at least some of the second set of classifications are not stored with the second set of data and are based on information about the second application that generated the second set of data; creating a second set of metadata containing information about the second set of data including the determined first second of classifications; and storing the first and second sets of metadata in a non-volatile storage device. 11. The computer-readable media of claim 8 wherein automatically determining, by the first data agent, comprises identifying keywords within the first set of data. | 0.557065 |
9,984,376 | 9 | 16 | 9. An issue identification system for automatically identifying one or more issues in one or more tickets of an organization, the issue identification system comprising: a processor; and a memory communicatively coupled to the processor, wherein the memory stores the processor-executable instructions, which, on execution, causes the processor to: receive ticket data of one or more tickets related to a service category from one or more data sources; generate one or more first sub-sequence patterns of n-grams for the one or more tickets from a sequence pattern retrieved from the ticket data; determine frequency of occurrence of each of the one or more first sub-sequence patterns of the n-grams and a Part-of-Speech (POS) weightage of the one or more first sub-sequence patterns of the n-grams; determine a first score for each of the one or more first sub-sequence patterns of the n-grams based on the frequency of occurrence and the POS weightage; identify automatically, one or more issues in the one or more tickets based on the first sub-sequence pattern of the n-grams and the first score; identify the sequence pattern corresponding to the one or more first sub-sequence patterns of the n-grams having the first score less than a predefined value for each of the one or more tickets; generate one or more second sub-sequence patterns of the n-grams by removing one or more words in the sequence pattern in order of occurrence, wherein a distance value is associated with each of the one or more second sub-sequence patterns based on the one or more words removed in the sequence pattern; determine a frequency of occurrence of each of the one or more second sub-sequence patterns of the n-grams and a POS weightage of the one or more second sub-sequence patterns of the n-grams; determine a second score for each of the one or more second sub-sequence patterns of the n-grams based on the frequency of occurrence and the POS weightage of the one or more second sub-sequence patterns of the n-grams; and update automatically, the one or more issues in the one or more tickets by merging the second sub-sequence pattern with the first sub-sequence pattern based on the first score and the second score. | 9. An issue identification system for automatically identifying one or more issues in one or more tickets of an organization, the issue identification system comprising: a processor; and a memory communicatively coupled to the processor, wherein the memory stores the processor-executable instructions, which, on execution, causes the processor to: receive ticket data of one or more tickets related to a service category from one or more data sources; generate one or more first sub-sequence patterns of n-grams for the one or more tickets from a sequence pattern retrieved from the ticket data; determine frequency of occurrence of each of the one or more first sub-sequence patterns of the n-grams and a Part-of-Speech (POS) weightage of the one or more first sub-sequence patterns of the n-grams; determine a first score for each of the one or more first sub-sequence patterns of the n-grams based on the frequency of occurrence and the POS weightage; identify automatically, one or more issues in the one or more tickets based on the first sub-sequence pattern of the n-grams and the first score; identify the sequence pattern corresponding to the one or more first sub-sequence patterns of the n-grams having the first score less than a predefined value for each of the one or more tickets; generate one or more second sub-sequence patterns of the n-grams by removing one or more words in the sequence pattern in order of occurrence, wherein a distance value is associated with each of the one or more second sub-sequence patterns based on the one or more words removed in the sequence pattern; determine a frequency of occurrence of each of the one or more second sub-sequence patterns of the n-grams and a POS weightage of the one or more second sub-sequence patterns of the n-grams; determine a second score for each of the one or more second sub-sequence patterns of the n-grams based on the frequency of occurrence and the POS weightage of the one or more second sub-sequence patterns of the n-grams; and update automatically, the one or more issues in the one or more tickets by merging the second sub-sequence pattern with the first sub-sequence pattern based on the first score and the second score. 16. The issue identification system as claimed in claim 9 , wherein the processor is further configured to: compare each of the one or more words in at least one of the first or the second sub-sequence patterns of the n-grams with one or more predefined domain keywords; obtain at least one of the one or more first subsequence patterns and the one or more second sub-sequence patterns comprising the one or more predefined domain keywords as a pattern with the highest score based on the comparison; and identify automatically, one or more issues in each of the one or more tickets based on the pattern with the highest score. | 0.5 |
9,454,518 | 6 | 8 | 6. A computer program product comprising: a non-transitory computer-readable medium having instructions recorded thereon that, when executed by one or more computer processors, cause the one or more computer processors to: access a file containing one or more designations, wherein each of the one or more designations identifies a portion of content within a textual transcript; analyze the file containing the one or more designations in accordance with one or more designation parameters to identify designations that contain errors; quarantine the designations identified as containing errors; and generate, based at least in part on the quarantining, a processed file, wherein the processed file is generated by: omitting the designations identified as containing errors from the processed file; and including, within the processed file, designations that were not identified as containing errors. | 6. A computer program product comprising: a non-transitory computer-readable medium having instructions recorded thereon that, when executed by one or more computer processors, cause the one or more computer processors to: access a file containing one or more designations, wherein each of the one or more designations identifies a portion of content within a textual transcript; analyze the file containing the one or more designations in accordance with one or more designation parameters to identify designations that contain errors; quarantine the designations identified as containing errors; and generate, based at least in part on the quarantining, a processed file, wherein the processed file is generated by: omitting the designations identified as containing errors from the processed file; and including, within the processed file, designations that were not identified as containing errors. 8. The computer program product of claim 6 , wherein the instructions further cause the one or more computer processors to: receive, by the one or more computer processors, user selections regarding a configuration of the one or more designation parameters, the one or more designation parameters including at least one of: a line range parameter, a remove overlap parameter, and a combine adjacent designations parameter, wherein the line range parameter identifies a range of valid line numbers within the textual transcript or one or more designation sets, wherein the user selections regarding the configuration of the line range parameter set beginning and ending line ranges for at least one of the textual transcript or the one or more designation sets, and wherein a particular designation is identified as containing an error when the particular designation specifies a line number that is not within the range of valid line numbers identified by the line range parameter; wherein the user selections regarding the configuration of the remove overlap parameter indicate whether to remove a portion of a first designation that overlaps with at least a portion of a second designation; or wherein the user selections regarding the configuration of the combine adjacent designations parameter indicate whether two or more designations identifying adjacent portions of the content within the textual transcript should be combined into a single designation; and generate the processed file in accordance with the user selections. | 0.5 |
8,467,716 | 14 | 16 | 14. A system for building a trait model for essay evaluation, the system comprising: a data processor; and computer-readable memory in communication with the data processor encoded with instructions for commanding the data processor to execute steps comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files. and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model. | 14. A system for building a trait model for essay evaluation, the system comprising: a data processor; and computer-readable memory in communication with the data processor encoded with instructions for commanding the data processor to execute steps comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files. and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model. 16. The system of claim 14 , wherein information associated with the plurality of features is stored to the plurality of vector files. | 0.936852 |
8,435,038 | 30 | 48 | 30. A non-transitory computer-readable medium comprising program code for causing a computer to perform a method, comprising: receiving, for each learner, a video feed generated by a camera at the learner's location, the video feed at least partially depicting both the learner and a subject on which the learner is demonstrating the practical skill; simultaneously displaying two or more of the video feeds for the plurality of learners at a location of the teacher; receiving and displaying one or more private questions to the teacher from one or more learners, the private questions not being conveyed to the other learners unless authorized by the teacher; and allowing the teacher to select one of the learners for individualized instruction by selecting an indication of the corresponding displayed private question; wherein the private questions can be submitted by one or more selected learners via a text message, an audio or a video; wherein the teacher responds to the one or more selected learners by a text message, audio or video by establishing a private video and/or audio communication channel between the teacher's computer system and the selected learner; wherein the teacher broadcasts the text, audio or video messages to a group of the selected learners by allowing the communication channel to be non-private for the group of selected learners to receive the instruction provided by the teacher; wherein allowing the teacher to store the video feed, annotating the stored video feed and selectively transmit the annotated stored video feed to one or more selected learners. | 30. A non-transitory computer-readable medium comprising program code for causing a computer to perform a method, comprising: receiving, for each learner, a video feed generated by a camera at the learner's location, the video feed at least partially depicting both the learner and a subject on which the learner is demonstrating the practical skill; simultaneously displaying two or more of the video feeds for the plurality of learners at a location of the teacher; receiving and displaying one or more private questions to the teacher from one or more learners, the private questions not being conveyed to the other learners unless authorized by the teacher; and allowing the teacher to select one of the learners for individualized instruction by selecting an indication of the corresponding displayed private question; wherein the private questions can be submitted by one or more selected learners via a text message, an audio or a video; wherein the teacher responds to the one or more selected learners by a text message, audio or video by establishing a private video and/or audio communication channel between the teacher's computer system and the selected learner; wherein the teacher broadcasts the text, audio or video messages to a group of the selected learners by allowing the communication channel to be non-private for the group of selected learners to receive the instruction provided by the teacher; wherein allowing the teacher to store the video feed, annotating the stored video feed and selectively transmit the annotated stored video feed to one or more selected learners. 48. The non-transitory computer-readable medium of claim 30 , further comprising program code for causing a computer to perform a method comprising: capturing a demonstration video feed depicting at least a subject on which the teacher is demonstrating the practical skill using one or more cameras at the teacher's location; and transmitting the demonstration video feed from the teacher's location to one or more of the learners for display on display screens at the respective learners' locations. | 0.5 |
8,160,984 | 7 | 8 | 7. The method of claim 1 , wherein the known attribute of the unclassified item is a physical attribute. | 7. The method of claim 1 , wherein the known attribute of the unclassified item is a physical attribute. 8. The method of claim 7 , wherein the physical attribute is a flavor. | 0.583333 |
7,716,593 | 4 | 5 | 4. The method of claim 3 , whereby if more than one electronic mail message is displayed in the conversation grouping record, displaying each of the plurality of electronic mail messages in successive lines beneath the conversation grouping heading. | 4. The method of claim 3 , whereby if more than one electronic mail message is displayed in the conversation grouping record, displaying each of the plurality of electronic mail messages in successive lines beneath the conversation grouping heading. 5. The method of claim 4 , further comprising displaying each of the more than one electronic mail messages that comprise a common conversation thread in an indented orientation relative to a preceding displayed electronic mail message belonging to the common conversation thread. | 0.5 |
8,881,116 | 1 | 2 | 1. A method, comprising: receiving computer code, the receiving being performed by a device; performing a static verification analysis of the computer code to locate a point in the code that, under at least one set of states of variables in the computer code, causes an error in an execution of the computer code, the static analysis being performed by analyzing a first plurality of possible execution paths of the computer code based on an over-approximation of states, and the performing is being performed by the device; back-propagating, from the located point, through a second plurality of possible execution paths, the second plurality of possible execution paths being obtained based on an under-approximation of the states that were over-approximated, and the back-propagating being performed by the device; determining, based on the back-propagating, a second point in the computer code as a potential cause of the error, the determining being performed by the device; analyzing, using empiric techniques and based on semantic information for the computer code, the computer code to determine a category for the potential cause of the error, the analyzing the computer code being performed by the device, and the category comprising one of: a first category when the cause of the error is determined to be within the computer code, or a second category when the cause of the error is determined to be due to an input to the computer code; and storing output information associated with the second point in the computer code, the storing being performed by the device. | 1. A method, comprising: receiving computer code, the receiving being performed by a device; performing a static verification analysis of the computer code to locate a point in the code that, under at least one set of states of variables in the computer code, causes an error in an execution of the computer code, the static analysis being performed by analyzing a first plurality of possible execution paths of the computer code based on an over-approximation of states, and the performing is being performed by the device; back-propagating, from the located point, through a second plurality of possible execution paths, the second plurality of possible execution paths being obtained based on an under-approximation of the states that were over-approximated, and the back-propagating being performed by the device; determining, based on the back-propagating, a second point in the computer code as a potential cause of the error, the determining being performed by the device; analyzing, using empiric techniques and based on semantic information for the computer code, the computer code to determine a category for the potential cause of the error, the analyzing the computer code being performed by the device, and the category comprising one of: a first category when the cause of the error is determined to be within the computer code, or a second category when the cause of the error is determined to be due to an input to the computer code; and storing output information associated with the second point in the computer code, the storing being performed by the device. 2. The method of claim 1 , where the static verification is performed through an abstract interpretation of variable states in the computer code. | 0.860577 |
8,583,087 | 9 | 11 | 9. A system for presenting information to a user, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the system to perform the operations of: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; rendering advertisements in the display of the wireless phone, the advertisements responsive to the received sequence of ambiguous characters; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. | 9. A system for presenting information to a user, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the system to perform the operations of: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; rendering advertisements in the display of the wireless phone, the advertisements responsive to the received sequence of ambiguous characters; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. 11. The system of claim 9 , wherein the memory stores further instructions that, when executed by the processor, cause the system to perform the operations of: identifying several user applications based on the disambiguated terms; and rendering the results in a manner that indicates which one of the several user applications will be launched in response to selection of a given result. | 0.695925 |
9,355,272 | 11 | 17 | 11. A method of operation of a computing system comprising: determining a sharing for representing a scenario surrounding sharing of a content; determine a user's past sharing selection for the sharing context, wherein the user's past sharing selection is for representing prior sharing of previous information similar to the content or associated with same instance of the sharing context; calculate a personalization degree for representing a match between a current personalization setting and the sharing context; generating with a control unit a sharing option for the sharing context based on a default set for the sharing context, the user's past sharing selection for the sharing context, and the personalization degree for the sharing context; and estimating a user's privacy preference based on the sharing option. | 11. A method of operation of a computing system comprising: determining a sharing for representing a scenario surrounding sharing of a content; determine a user's past sharing selection for the sharing context, wherein the user's past sharing selection is for representing prior sharing of previous information similar to the content or associated with same instance of the sharing context; calculate a personalization degree for representing a match between a current personalization setting and the sharing context; generating with a control unit a sharing option for the sharing context based on a default set for the sharing context, the user's past sharing selection for the sharing context, and the personalization degree for the sharing context; and estimating a user's privacy preference based on the sharing option. 17. The method as claimed in claim 11 further comprising: selecting a default option for the sharing context; ranking the default option in the default set; and providing the default set having a top ranked sharing option from the default option. | 0.805071 |
9,294,591 | 1 | 6 | 1. A method comprising: receiving, by a server comprising a processor, a request from a calling device for a call session with a terminating device over a communication network, wherein the request includes a fully qualified domain name identifying the calling device; transmitting to a domain naming server, by the server, a query comprising the fully qualified domain name; receiving, by the server, a response from the domain naming server; analyzing, by the server, the response that is received to determine an answer combination; transmitting to the calling device, by the server, a first response message via an internet protocol version 4 address if the answer combination comprises the internet protocol version 4 address with a first non-error indicator and an internet protocol version 6 address with a first error indicator; and transmitting to the calling device, by the server, a second response message via the internet protocol version 6 address if the answer combination comprises the internet protocol version 4 address with a second error indicator and the internet protocol version 6 address with a second non-error indicator. | 1. A method comprising: receiving, by a server comprising a processor, a request from a calling device for a call session with a terminating device over a communication network, wherein the request includes a fully qualified domain name identifying the calling device; transmitting to a domain naming server, by the server, a query comprising the fully qualified domain name; receiving, by the server, a response from the domain naming server; analyzing, by the server, the response that is received to determine an answer combination; transmitting to the calling device, by the server, a first response message via an internet protocol version 4 address if the answer combination comprises the internet protocol version 4 address with a first non-error indicator and an internet protocol version 6 address with a first error indicator; and transmitting to the calling device, by the server, a second response message via the internet protocol version 6 address if the answer combination comprises the internet protocol version 4 address with a second error indicator and the internet protocol version 6 address with a second non-error indicator. 6. The method of claim 1 , comprising determining by a configuration whether the response message comprises the internet protocol version 4 address or the internet protocol version 6 address. | 0.704334 |
9,582,781 | 1 | 2 | 1. A method for managing operations for organizations over a network using one or more network computers that include one or more processors that perform actions, comprising: when a plurality of Operations events are provided, performing further actions, including: providing, by the one or more processors, one or more event clusters that are associated with one or more Operations events of the plurality of Operations events, wherein the one or more Operations events are associated with the one or more event clusters based on one or more characteristics of the one or more Operations events; associating, by the one or more processors, one or more resolution metrics with the one or more event clusters, wherein the association is based on one or more of human-validated interface applications or generalized models; employing, by the one or more processors, a modeling engine to train one or more models based on the one or more Operations events, the one or more event clusters, and the one or more resolution metrics, wherein the trained model is configured to correlate and predict the one or more resolution metrics from one or more real-time Operations events; configuring and arranging, by the one or more processors, a non-transitory computer readable media for storing the one or more trained models; storing, by the one or more processors, the one or more trained models in the non-transitory computer readable media; and when the one or more real-time Operations events are provided, performing further actions including: retrieving, by the one or more processors, the one or more trained models from the non-transitory computer readable memory; and employing, by the one or more processors, the one or more trained models to identify the one or more resolution metrics that are associated with the one or more real-time Operations events. | 1. A method for managing operations for organizations over a network using one or more network computers that include one or more processors that perform actions, comprising: when a plurality of Operations events are provided, performing further actions, including: providing, by the one or more processors, one or more event clusters that are associated with one or more Operations events of the plurality of Operations events, wherein the one or more Operations events are associated with the one or more event clusters based on one or more characteristics of the one or more Operations events; associating, by the one or more processors, one or more resolution metrics with the one or more event clusters, wherein the association is based on one or more of human-validated interface applications or generalized models; employing, by the one or more processors, a modeling engine to train one or more models based on the one or more Operations events, the one or more event clusters, and the one or more resolution metrics, wherein the trained model is configured to correlate and predict the one or more resolution metrics from one or more real-time Operations events; configuring and arranging, by the one or more processors, a non-transitory computer readable media for storing the one or more trained models; storing, by the one or more processors, the one or more trained models in the non-transitory computer readable media; and when the one or more real-time Operations events are provided, performing further actions including: retrieving, by the one or more processors, the one or more trained models from the non-transitory computer readable memory; and employing, by the one or more processors, the one or more trained models to identify the one or more resolution metrics that are associated with the one or more real-time Operations events. 2. The method of claim 1 , further comprising, transforming, by the one or more processors, each Operations event in the plurality of Operations events into a common event format. | 0.777363 |
8,849,755 | 5 | 9 | 5. The configuration information management apparatus according to claim 1 , further comprising: an operation history management unit that stores therein operation histories of the configuration items and the attribute items in the data management unit; and a dictionary candidate management unit that stores therein the dictionary candidates retrieved by the dictionary candidate retrieval unit, wherein the dictionary generation unit includes a history synchronization counter unit that acquires the operation history of each of the dictionary candidates being managed by the dictionary candidate management unit at the same timing of the attribute items of the corresponding dictionary candidate, determines whether data are synchronized in the operation histories of the attribute items, and counts the number of times of history synchronization when the data are synchronized, a dictionary candidate selection unit that selects the dictionary candidate of a dictionary target from the dictionary candidates being managed by the dictionary candidate management unit based on the number of times of history synchronization for each of the dictionary candidates, and wherein the dictionary generation unit generates the dictionary information based on the dictionary candidate of the dictionary target selected by the dictionary candidate selection unit. | 5. The configuration information management apparatus according to claim 1 , further comprising: an operation history management unit that stores therein operation histories of the configuration items and the attribute items in the data management unit; and a dictionary candidate management unit that stores therein the dictionary candidates retrieved by the dictionary candidate retrieval unit, wherein the dictionary generation unit includes a history synchronization counter unit that acquires the operation history of each of the dictionary candidates being managed by the dictionary candidate management unit at the same timing of the attribute items of the corresponding dictionary candidate, determines whether data are synchronized in the operation histories of the attribute items, and counts the number of times of history synchronization when the data are synchronized, a dictionary candidate selection unit that selects the dictionary candidate of a dictionary target from the dictionary candidates being managed by the dictionary candidate management unit based on the number of times of history synchronization for each of the dictionary candidates, and wherein the dictionary generation unit generates the dictionary information based on the dictionary candidate of the dictionary target selected by the dictionary candidate selection unit. 9. The configuration information management apparatus according to claim 5 , wherein when selecting the dictionary candidate of the dictionary target among the dictionary candidates being managed by the dictionary candidate management unit, the dictionary candidate selection unit deletes the dictionary candidate having the attribute name of the attribute item of the selected dictionary candidate from the dictionary candidate management unit. | 0.788899 |
9,940,016 | 1 | 9 | 1. An apparatus comprising: at least one device processor; and at least one computer readable storage medium storing instructions which, when executed by the at least one device processor, cause the at least one device processor to: operate a keyboard configured to implement shape-writing of words and radial entry of individual characters; obtain input data identifying an input to the keyboard that is directed to a primary character, the input moving in a specific direction usable to select an auxiliary character associated with the primary character; evaluate the input data to disambiguate whether the input is a shape-writing input to enter a particular word or a radial entry input to enter the auxiliary character; in a first instance when the input is disambiguated as the shape-writing input, enter the particular word, the particular word including the primary character; and in a second instance when the input is disambiguated as the radial entry input, enter the auxiliary character associated with the primary character. | 1. An apparatus comprising: at least one device processor; and at least one computer readable storage medium storing instructions which, when executed by the at least one device processor, cause the at least one device processor to: operate a keyboard configured to implement shape-writing of words and radial entry of individual characters; obtain input data identifying an input to the keyboard that is directed to a primary character, the input moving in a specific direction usable to select an auxiliary character associated with the primary character; evaluate the input data to disambiguate whether the input is a shape-writing input to enter a particular word or a radial entry input to enter the auxiliary character; in a first instance when the input is disambiguated as the shape-writing input, enter the particular word, the particular word including the primary character; and in a second instance when the input is disambiguated as the radial entry input, enter the auxiliary character associated with the primary character. 9. The apparatus of claim 1 , wherein the instructions, when executed by the at least one device processor, cause the at least one device processor to: determine, from the input data, an observed velocity of the input; and disambiguate the input data based at least on the observed velocity of the input. | 0.803618 |
7,782,203 | 7 | 8 | 7. The system of claim 1 , the at least one component is at least one of an internal logical element or an event handler. | 7. The system of claim 1 , the at least one component is at least one of an internal logical element or an event handler. 8. The system of claim 7 , the event handler is a portion of managed code running in a context of the RFID business process that processes the event. | 0.5 |
5,488,725 | 15 | 19 | 15. The process according to claim 12 where the maximum probable frequency, f.sub.max, and the minimum probable frequency, f.sub.min, are calculated in accordance with the relationships ##EQU6## where n.sub.i is the number of gaps between documents in the sample containing the selected representation, n.sub.c is the number of documents in the collection, x.sub.i is the number of documents in the sample, s.sub.i is the greater of x.sub.i /n.sub.i or the standard deviation of the n.sub.i gaps, and z is the standard critical value for normal distribution for a preselected reliability. | 15. The process according to claim 12 where the maximum probable frequency, f.sub.max, and the minimum probable frequency, f.sub.min, are calculated in accordance with the relationships ##EQU6## where n.sub.i is the number of gaps between documents in the sample containing the selected representation, n.sub.c is the number of documents in the collection, x.sub.i is the number of documents in the sample, s.sub.i is the greater of x.sub.i /n.sub.i or the standard deviation of the n.sub.i gaps, and z is the standard critical value for normal distribution for a preselected reliability. 19. The process according to claim 15 where the preselected reliability is 0.995 and z is 2.8070. | 0.894336 |
8,122,057 | 12 | 14 | 12. A computer-readable storage medium storing instructions, which when executed on at least one processor, causes the at least one processor to perform a method comprising: obtaining data from a plurality of computers; applying text patterns to the obtained data and placing the data in a data file; transforming the data in the data file into a uniform and semantically structured data structure format that is compatible with a plurality of interfaces; and generating grammatical sentences based on the text patterns, wherein the grammatical sentences are compatible with the a specific canonical interface and are generated by transforming the uniform and semantically structured text patterns into an interface specific format. | 12. A computer-readable storage medium storing instructions, which when executed on at least one processor, causes the at least one processor to perform a method comprising: obtaining data from a plurality of computers; applying text patterns to the obtained data and placing the data in a data file; transforming the data in the data file into a uniform and semantically structured data structure format that is compatible with a plurality of interfaces; and generating grammatical sentences based on the text patterns, wherein the grammatical sentences are compatible with the a specific canonical interface and are generated by transforming the uniform and semantically structured text patterns into an interface specific format. 14. The computer-readable storage medium of claim 12 , wherein the method performed by the at least one processor further comprises: generating the text patterns based on at least one of attribute phrase grammars and term arrangement rules. | 0.533074 |
10,089,072 | 27 | 35 | 27. A method comprising: at a first electronic device having a microphone: sampling, with the microphone at the first electronic device, an audio input specifying a task; identifying, with the first electronic device, a confidence value indicative of a likelihood that the audio input was provided by a particular user; broadcasting, with the first electronic device, a first set of one or more values based on the sampled audio input, wherein a first value of the first set of values is based on the confidence value; receiving, with the first electronic device, a second set of one or more values from a second electronic device, wherein the second set of one or more values is based on the audio input; determining, with the first electronic device, whether a type of the first electronic device meets a requirement of the task; and in accordance with a determination that the type of the first electronic device meets the requirement of the task; determining, with the first electronic device, whether the first electronic device is to respond to the audio input based on the first set of one or more values, the second set of one or more values, and the requirement of the task; in accordance with a determination that the first electronic device is to respond to the audio input, responding to the audio input; in accordance with a determination that the first electronic device is not to respond to the audio input, foregoing responding to the audio input; and in accordance with a determination that the type of the first electronic device does not meet the requirement of the task, foregoing responding to the audio input with the first electronic device. | 27. A method comprising: at a first electronic device having a microphone: sampling, with the microphone at the first electronic device, an audio input specifying a task; identifying, with the first electronic device, a confidence value indicative of a likelihood that the audio input was provided by a particular user; broadcasting, with the first electronic device, a first set of one or more values based on the sampled audio input, wherein a first value of the first set of values is based on the confidence value; receiving, with the first electronic device, a second set of one or more values from a second electronic device, wherein the second set of one or more values is based on the audio input; determining, with the first electronic device, whether a type of the first electronic device meets a requirement of the task; and in accordance with a determination that the type of the first electronic device meets the requirement of the task; determining, with the first electronic device, whether the first electronic device is to respond to the audio input based on the first set of one or more values, the second set of one or more values, and the requirement of the task; in accordance with a determination that the first electronic device is to respond to the audio input, responding to the audio input; in accordance with a determination that the first electronic device is not to respond to the audio input, foregoing responding to the audio input; and in accordance with a determination that the type of the first electronic device does not meet the requirement of the task, foregoing responding to the audio input with the first electronic device. 35. The method of claim 27 , further comprising: receiving, with the first electronic device, data indicative of the requirement of the task from a server. | 0.872951 |
8,055,647 | 1 | 5 | 1. A system for searching through multiple databases based on a search expression, said system comprising: a memory containing a set of instructions, the instructions including: defining instructions for defining a distribution of records corresponding to search keys in the multiple databases; dividing instructions for dividing the search expression into multiple search expressions based in part on the distribution of records, and determining respective target search ranges for the multiple search expressions such that each of a number of the distribution records to be searched with each of said multiple search expressions is approximately constant to others of the number of the distribution of records, wherein the dividing instructions use a data distribution table to divide the search expression, wherein the data distribution table indicates how the records are distributed in each table of a plurality of tables, wherein ones of the plurality of tables correspond to ones of the multiple databases, and wherein the records correspond to a common key; executing instructions for executing the multiple search expressions in respective target search ranges of the multiple search expressions; and a processing unit for executing the set of instructions. | 1. A system for searching through multiple databases based on a search expression, said system comprising: a memory containing a set of instructions, the instructions including: defining instructions for defining a distribution of records corresponding to search keys in the multiple databases; dividing instructions for dividing the search expression into multiple search expressions based in part on the distribution of records, and determining respective target search ranges for the multiple search expressions such that each of a number of the distribution records to be searched with each of said multiple search expressions is approximately constant to others of the number of the distribution of records, wherein the dividing instructions use a data distribution table to divide the search expression, wherein the data distribution table indicates how the records are distributed in each table of a plurality of tables, wherein ones of the plurality of tables correspond to ones of the multiple databases, and wherein the records correspond to a common key; executing instructions for executing the multiple search expressions in respective target search ranges of the multiple search expressions; and a processing unit for executing the set of instructions. 5. The system according to claim 1 , wherein the search keys are classified based on classification codes and the dividing instructions divides the search expression based in part on the classification codes. | 0.877934 |
4,350,342 | 2 | 4 | 2. The game apparatus of claim 1 wherein each letter supply means provides fifty letter selections. | 2. The game apparatus of claim 1 wherein each letter supply means provides fifty letter selections. 4. The game apparatus of claim 2 wherein said letter selections include a letter distribution defined by plural numbers of certain of said letters differs from the letter distribution of said second letter supply. | 0.5 |
7,487,190 | 5 | 8 | 5. A computer-readable storage medium having stored thereon computer-executable instructions that, when executed, cause a computer to perform a process comprising: determining that a unit of content in an updated version of a structured document and a related unit of content in a previous version of the structured document are associated with the same entry, wherein determining comprises: accessing a base topic set having a single topic identifier associated with each unit of content in the previous version of the structured document; accessing an updated topic set having a single topic identifier associated with each unit of content in the updated version of the structured document; identifying a particular topic identifier in the updated topic set that corresponds to the same particular topic identifier in the base topic set; comparing the unit of content associated with the particular topic identifier in the updated version with the related unit of content associated with the particular topic identifier in the previous version to determine whether the unit of content in the updated version has been modified with respect to the related unit of content; generating a table of contents associated with the updated version of the structured document, the table of contents having one entry associated with each unit of content in the updated version of the structured document; and marking a first entry in the table of contents if the unit of content associated with the first entry has been modified a predetermined degree from a previous version of the content, wherein the predetermined degree is represented by a difference metric as determined by a content comparator, such that: in an event that the difference is counted as a modification, the difference metric represents each change in words, tags, and formatting, wherein the changes comprise changes in font, color, size, inserted content, and deleted content between the respective units of content in the updated version and the previous version; and in an event that not all differences arc counted as modifications, changes are classified by type such that changes of meaning are classified in a different type than changes in form, wherein changes in form include rephrasing that does not change the meaning of the content, and the difference metric represents the number of changes of meaning within each unit of content. | 5. A computer-readable storage medium having stored thereon computer-executable instructions that, when executed, cause a computer to perform a process comprising: determining that a unit of content in an updated version of a structured document and a related unit of content in a previous version of the structured document are associated with the same entry, wherein determining comprises: accessing a base topic set having a single topic identifier associated with each unit of content in the previous version of the structured document; accessing an updated topic set having a single topic identifier associated with each unit of content in the updated version of the structured document; identifying a particular topic identifier in the updated topic set that corresponds to the same particular topic identifier in the base topic set; comparing the unit of content associated with the particular topic identifier in the updated version with the related unit of content associated with the particular topic identifier in the previous version to determine whether the unit of content in the updated version has been modified with respect to the related unit of content; generating a table of contents associated with the updated version of the structured document, the table of contents having one entry associated with each unit of content in the updated version of the structured document; and marking a first entry in the table of contents if the unit of content associated with the first entry has been modified a predetermined degree from a previous version of the content, wherein the predetermined degree is represented by a difference metric as determined by a content comparator, such that: in an event that the difference is counted as a modification, the difference metric represents each change in words, tags, and formatting, wherein the changes comprise changes in font, color, size, inserted content, and deleted content between the respective units of content in the updated version and the previous version; and in an event that not all differences arc counted as modifications, changes are classified by type such that changes of meaning are classified in a different type than changes in form, wherein changes in form include rephrasing that does not change the meaning of the content, and the difference metric represents the number of changes of meaning within each unit of content. 8. A computer-readable storage medium as recited in claim 5 further comprising marking a second entry in the table of contents if the unit of content associated with the second entry is a new unit of content with respect to a previous version of the structured document, wherein a new unit of content corresponds to a unit of content which had not previously been addressed. | 0.5 |
8,768,852 | 5 | 6 | 5. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: determining a statistically improbable phrase that appears in a source, the statistically improbable phrase appearing in the source more than a threshold number of times; determining words that compose the statistically improbable phrase; determining phrases that are associated with at least one of the determined words; and providing at least a portion of the determined phrases for selection by a user for association with an aspect of an account of the user. | 5. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: determining a statistically improbable phrase that appears in a source, the statistically improbable phrase appearing in the source more than a threshold number of times; determining words that compose the statistically improbable phrase; determining phrases that are associated with at least one of the determined words; and providing at least a portion of the determined phrases for selection by a user for association with an aspect of an account of the user. 6. One or more non-transitory computer-readable media as recited in claim 5 , wherein the source comprises a book, a magazine, online content, audio content or video content. | 0.827038 |
9,321,969 | 1 | 8 | 1. A computer-implemented method for enabling users of social-networking applications to interact using virtual personas, at least a portion of the method being performed by at least one physical computing device comprising at least one hardware processor, the method comprising: creating, by the physical computing device, a social-networking identity associated with a user of a social-networking application; creating, by the physical computing device and as part of the user's social-networking identity, a plurality of virtual personas that represent different real-life roles of the user, the plurality of virtual personas comprising: a first virtual persona of the user; a second virtual persona of the user; after creating the user's virtual personas, receiving a request at the physical computing device to establish a social-networking relationship between the first virtual persona and another user of the social-networking application; in response to receiving the request, directing the social-networking application by the physical computing device to establish the social-networking relationship between the first virtual persona and the other user without establishing a social-networking relationship between the second virtual persona and the other user; defining, by the physical computing device and based at least in part on input from the user of the social-networking application, a first geo-location associated with the first virtual persona and a second geo-location associated with the second virtual persona; upon defining the first and second geo-locations: enabling the user to share, under the first virtual persona, at least one content instance that identifies the user's location while the user is located at the first geo-location; preventing the user from sharing, under the second virtual persona, the content instance that identifies the user's location while the user is located at the first geo-location due at least in part to the first geo-location being associated with the first virtual persona and not being associated with the second virtual persona; associating at least one photograph previously shared via the social-networking application with the first virtual persona by: enabling the user to assume the first virtual persona within the social-networking application; after the user has assumed the first virtual persona: identifying a tag request submitted by the user to tag the user in the photograph previously shared via the social-networking application; ensuring that the user's tag in the photograph is associated with the first virtual persona and not associated with the second virtual persona due at least in part to the user having assumed the first virtual persona prior to submitting the tag request. | 1. A computer-implemented method for enabling users of social-networking applications to interact using virtual personas, at least a portion of the method being performed by at least one physical computing device comprising at least one hardware processor, the method comprising: creating, by the physical computing device, a social-networking identity associated with a user of a social-networking application; creating, by the physical computing device and as part of the user's social-networking identity, a plurality of virtual personas that represent different real-life roles of the user, the plurality of virtual personas comprising: a first virtual persona of the user; a second virtual persona of the user; after creating the user's virtual personas, receiving a request at the physical computing device to establish a social-networking relationship between the first virtual persona and another user of the social-networking application; in response to receiving the request, directing the social-networking application by the physical computing device to establish the social-networking relationship between the first virtual persona and the other user without establishing a social-networking relationship between the second virtual persona and the other user; defining, by the physical computing device and based at least in part on input from the user of the social-networking application, a first geo-location associated with the first virtual persona and a second geo-location associated with the second virtual persona; upon defining the first and second geo-locations: enabling the user to share, under the first virtual persona, at least one content instance that identifies the user's location while the user is located at the first geo-location; preventing the user from sharing, under the second virtual persona, the content instance that identifies the user's location while the user is located at the first geo-location due at least in part to the first geo-location being associated with the first virtual persona and not being associated with the second virtual persona; associating at least one photograph previously shared via the social-networking application with the first virtual persona by: enabling the user to assume the first virtual persona within the social-networking application; after the user has assumed the first virtual persona: identifying a tag request submitted by the user to tag the user in the photograph previously shared via the social-networking application; ensuring that the user's tag in the photograph is associated with the first virtual persona and not associated with the second virtual persona due at least in part to the user having assumed the first virtual persona prior to submitting the tag request. 8. The method of claim 1 , wherein directing the social-networking application to establish the social-networking application comprises: obtaining the other user's consent to establish the social-networking relationship; in response to obtaining the other user's consent, directing the social-networking application to establish the social-networking relationship. | 0.806589 |
10,025,569 | 2 | 3 | 2. The method of claim 1 , further comprising: identifying variables within the HLL program; and wherein performing the data flow analysis on the initial control flow graph operates separately for each identified variable, retains data corresponding to a variable for which the data flow analysis converges, and discards data corresponding to a variable for which the data flow analysis does not converge. | 2. The method of claim 1 , further comprising: identifying variables within the HLL program; and wherein performing the data flow analysis on the initial control flow graph operates separately for each identified variable, retains data corresponding to a variable for which the data flow analysis converges, and discards data corresponding to a variable for which the data flow analysis does not converge. 3. The method of claim 2 , wherein performing the data flow analysis over the initial control flow graph includes: determining that a first variable converges if data corresponding to the first variable does not change between iterations of the data flow analysis; and determining that a second variable does not converge if data corresponding to the second variable changes between a next to last iteration of the data flow analysis and a last iteration of the data flow analysis. | 0.5 |
8,332,188 | 1 | 6 | 1. A tangible computer-readable medium having recorded thereon statements and instructions for execution by a computer of a method to generate at least one mathematical expression describing a performance characteristic of a system, the system associated with variables and with pre-determined data related to the performance characteristic of the system, the method comprising steps of: generating at least one initial mathematical expression having a pre-defined canonical form and being a function of the variables, the at least one initial mathematical expression having operators operating on the variables, the operators being selected from a pre-defined group of operators, the at least one initial mathematical expression describing the performance characteristic of the system; wherein, the variables of the system are representable as a vector {right arrow over (x)} and the canonical form of an expression F({right arrow over (x)}) is representable as F ( x ) = w offset + ∑ i = 0 n w i × f i ( x ) × NL i ( x ) , “n” being an integer, w offset , being an offset value, w i being weights, f i (x) including at least one of a polynomial function of the variables and a rational function of the variables, and NL i ({right arrow over (x)}) being a non-linear function of the variables, with NL 0 (x)=1; generating calculated data using the at least one initial mathematical expression; calculating an output of a goal function in accordance with the pre-determined data and the calculated data; determining that the goal function is outside a pre-defined range; and iteratively performing the following steps a-c until an additional output of the goal function is within the pre-defined range: a. modifying at least one input mathematical expression in accordance with a search algorithm to produce at least one modified mathematical expression having the canonical form and being a function of the variables, the search algorithm to search at least the pre-defined group of operators to identify operators with which to modify the at least one input mathematical expression, the at least one input mathematical expression being the at least one initial mathematical expression in a first iteration of steps a-c, the at least one input mathematical expression being the at least one modified mathematical expression in subsequent iterations of steps a-c; b. generating additional calculated data using the at least one modified mathematical expression; and c. calculating the additional output of the goal function based on the additional calculated data and the pre-determined data. | 1. A tangible computer-readable medium having recorded thereon statements and instructions for execution by a computer of a method to generate at least one mathematical expression describing a performance characteristic of a system, the system associated with variables and with pre-determined data related to the performance characteristic of the system, the method comprising steps of: generating at least one initial mathematical expression having a pre-defined canonical form and being a function of the variables, the at least one initial mathematical expression having operators operating on the variables, the operators being selected from a pre-defined group of operators, the at least one initial mathematical expression describing the performance characteristic of the system; wherein, the variables of the system are representable as a vector {right arrow over (x)} and the canonical form of an expression F({right arrow over (x)}) is representable as F ( x ) = w offset + ∑ i = 0 n w i × f i ( x ) × NL i ( x ) , “n” being an integer, w offset , being an offset value, w i being weights, f i (x) including at least one of a polynomial function of the variables and a rational function of the variables, and NL i ({right arrow over (x)}) being a non-linear function of the variables, with NL 0 (x)=1; generating calculated data using the at least one initial mathematical expression; calculating an output of a goal function in accordance with the pre-determined data and the calculated data; determining that the goal function is outside a pre-defined range; and iteratively performing the following steps a-c until an additional output of the goal function is within the pre-defined range: a. modifying at least one input mathematical expression in accordance with a search algorithm to produce at least one modified mathematical expression having the canonical form and being a function of the variables, the search algorithm to search at least the pre-defined group of operators to identify operators with which to modify the at least one input mathematical expression, the at least one input mathematical expression being the at least one initial mathematical expression in a first iteration of steps a-c, the at least one input mathematical expression being the at least one modified mathematical expression in subsequent iterations of steps a-c; b. generating additional calculated data using the at least one modified mathematical expression; and c. calculating the additional output of the goal function based on the additional calculated data and the pre-determined data. 6. The tangible computer-readable medium of claim 1 wherein, the goal function is at least for minimizing a normalized root mean square error between the pre-determined data and either the calculated data generated using the at least one initial mathematical expression or the additional calculated data generated using the at least one modified mathematical expressions. | 0.5 |
8,291,039 | 17 | 18 | 17. One or more non-transitory machine-readable media that store instructions for use in transferring data via a communication session between a client application on a first network and a server application on a second network, the instructions for causing one or more processing devices to perform operations comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application is on the second network behind a second firewall that is different from the first firewall. | 17. One or more non-transitory machine-readable media that store instructions for use in transferring data via a communication session between a client application on a first network and a server application on a second network, the instructions for causing one or more processing devices to perform operations comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application is on the second network behind a second firewall that is different from the first firewall. 18. The one or more non-transitory machine-readable media of claim 17 , wherein the intermediary protocol is different from the local protocol. | 0.657895 |
8,775,403 | 29 | 30 | 29. The system of claim 21 , wherein the function is a product of two factors selected from the group consisting of the determined query-independent score, the determined content change frequency of the corresponding document, and the age of the corresponding document. | 29. The system of claim 21 , wherein the function is a product of two factors selected from the group consisting of the determined query-independent score, the determined content change frequency of the corresponding document, and the age of the corresponding document. 30. The system of claim 29 , wherein a factor is raised to a power. | 0.5 |
8,452,783 | 7 | 9 | 7. The document processing apparatus according to claim 1 , further comprising: a filter storing unit configured to store a plurality of filters associated with application programs, respectively; and a filter selecting unit configured to select a filter associated with the first application program from the filter storing unit, wherein the character string extracting unit is configured to detect the one or more character strings using the filter selected by the filter selecting unit. | 7. The document processing apparatus according to claim 1 , further comprising: a filter storing unit configured to store a plurality of filters associated with application programs, respectively; and a filter selecting unit configured to select a filter associated with the first application program from the filter storing unit, wherein the character string extracting unit is configured to detect the one or more character strings using the filter selected by the filter selecting unit. 9. The document processing apparatus according to claim 7 , further comprising: a user setting unit configure to display one or more filters stored by the filter storing unit as a candidate for selection to the user to enable the user to select at least one of the one or more filters to be used in the character string extracting unit in preference to a relationship between an application program and a filter determined by the filter storing unit. | 0.516129 |
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