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16. A system comprising: one or more processors to: receive a search query that includes one or more keywords; obtain a geographical identifier; determine a geographic location based, at least in part, on the geographical identifier, identify an area of interest within a certain distance of the geographic location, where the certain distance is dynamically determined based, at least in part, on the one or more keywords; identify documents that are associated with addresses located within the area of interest; determine ones of the identified documents that match the one or more keywords as relevant documents; group the relevant documents into one or more clusters based, at least in part, on the addresses associated with the relevant documents, each of the one or more clusters corresponding to a different one of the addresses; score the relevant documents based on at least one of a distance factor or a relevancy factor, the distance factor for a first of the relevant documents being based, at least in part, on a distance that an address associated with the first of the relevant documents is from the geographic center of the area of interest and the relevancy factor for a second of the relevant documents being based, at least in part, on a number of the one or more keywords present in the second of the relevant documents or a measure of how prominently the one or more keywords appear in the second of the relevant documents; rank the relevant documents within each of the one or more clusters based, at least in part, on the scoring; and present the one or more clusters. | 16. A system comprising: one or more processors to: receive a search query that includes one or more keywords; obtain a geographical identifier; determine a geographic location based, at least in part, on the geographical identifier, identify an area of interest within a certain distance of the geographic location, where the certain distance is dynamically determined based, at least in part, on the one or more keywords; identify documents that are associated with addresses located within the area of interest; determine ones of the identified documents that match the one or more keywords as relevant documents; group the relevant documents into one or more clusters based, at least in part, on the addresses associated with the relevant documents, each of the one or more clusters corresponding to a different one of the addresses; score the relevant documents based on at least one of a distance factor or a relevancy factor, the distance factor for a first of the relevant documents being based, at least in part, on a distance that an address associated with the first of the relevant documents is from the geographic center of the area of interest and the relevancy factor for a second of the relevant documents being based, at least in part, on a number of the one or more keywords present in the second of the relevant documents or a measure of how prominently the one or more keywords appear in the second of the relevant documents; rank the relevant documents within each of the one or more clusters based, at least in part, on the scoring; and present the one or more clusters. 22. The system of claim 16 , where, when grouping the relevant documents into one or more clusters, the one or more processors are further to: identify a first address associated with a first one of the relevant documents, determine one or more second ones of the relevant documents that are also associated with the first address, and group the first of the relevant documents and the one or more second relevant documents into a cluster. | 0.5 |
14. A non-transitory computer readable medium for storing computer instructions that, when executed by at least one processor causes the at least one processor to perform a method for saving a search string as metadata with an image comprising: receiving a first set of image search results from a first search comprising an image search string; receiving one or more image files for storage based on at least one user selection from the image search results; generating metadata based on the image search string; storing the one or more images files with the metadata; accessing the metadata based on detecting a selection of a stored image file from the one or more stored image files; based on the metadata, providing, for presentation in a graphical user interface on a display device, an option to perform a second search using only the image search string; performing the second search with only the image search string in response to a selection of the option; in response to performing the second search, receiving a second set of image search results that matches the first set of image search results; comparing the second set of image search results to the one or more stored image files; and providing, in the graphical user interface, the second set of image search results excluding the one or more stored image files. | 14. A non-transitory computer readable medium for storing computer instructions that, when executed by at least one processor causes the at least one processor to perform a method for saving a search string as metadata with an image comprising: receiving a first set of image search results from a first search comprising an image search string; receiving one or more image files for storage based on at least one user selection from the image search results; generating metadata based on the image search string; storing the one or more images files with the metadata; accessing the metadata based on detecting a selection of a stored image file from the one or more stored image files; based on the metadata, providing, for presentation in a graphical user interface on a display device, an option to perform a second search using only the image search string; performing the second search with only the image search string in response to a selection of the option; in response to performing the second search, receiving a second set of image search results that matches the first set of image search results; comparing the second set of image search results to the one or more stored image files; and providing, in the graphical user interface, the second set of image search results excluding the one or more stored image files. 18. The non-transitory computer readable medium of claim 14 , wherein providing the second set of image search results excluding the one or more stored image files comprises: providing the second set of image search results excluding the one or more stored image files in a first portion of the graphical user interface; and providing the one or more stored image files in a second portion of the graphical user interface, the second portion of the graphical user interface being in a separate application tab. | 0.542948 |
9. The method according to claim 1 , further comprising a step of establishing a user dependant list of semantic expressions retrieved from speech material related to the activities of the user, and using said list for adapting said user profile. | 9. The method according to claim 1 , further comprising a step of establishing a user dependant list of semantic expressions retrieved from speech material related to the activities of the user, and using said list for adapting said user profile. 12. The method according to claim 9 , wherein said user profile depends on the time at which said semantic expressions have been gathered or spoken. | 0.886121 |
15. A computer readable medium storing instructions for controlling a computing device to monitor labelers of the speech data where an annotation guide is used to label utterances in the speech data with a call type, the instructions comprising: presenting via a processor a test utterance to a labeler; receiving input from the labeler that selects a particular call type from a list of call types; determining via the processor if the labeler labeled the test utterance correctly; and based on the determining step, performing at least one of: revising the annotation guide, retraining the labeler or altering the test utterance. | 15. A computer readable medium storing instructions for controlling a computing device to monitor labelers of the speech data where an annotation guide is used to label utterances in the speech data with a call type, the instructions comprising: presenting via a processor a test utterance to a labeler; receiving input from the labeler that selects a particular call type from a list of call types; determining via the processor if the labeler labeled the test utterance correctly; and based on the determining step, performing at least one of: revising the annotation guide, retraining the labeler or altering the test utterance. 19. The computer readable medium of claim 15 , wherein the test utterance has an existing call type. | 0.625332 |
1. A computer apparatus for exhibiting the properties and structure of matter comprising: a visual display unit; a data entry device; and a data processing system connected to said visual display unit and said data entry device, said data processing system having atomic structure program means for constructing mathematical atomic models, and a text/graphic interactive user interface having program selection means for permitting a user to interact with and perform operations on said atomic structure program means via said data entry device and said visual display unit, an atomic data base containing atomic information for use by said atomic structure program means for constructing said mathematical atomic models, an atomic data display means for displaying on said visual display unit atomic select buttons and said atomic information in response to selections made by said user via said atomic select buttons and said data entry device, and a graphic display means for displaying graphical representations of said mathematical atomic models on said visual display unit, and wherein said atomic data display means includes a periodic table means for displaying a plurality of said atomic select buttons to form element buttons labeled with said atomic information to form a periodic table of chemical elements on said visual display unit, and an element means for displaying on said visual display unit, in response to selection of one of said element buttons, a plurality of said atomic select buttons to form isotope buttons labeled with isotope information from said atomic information, said isotope information corresponding to the isotopes of said one of said chemical elements. | 1. A computer apparatus for exhibiting the properties and structure of matter comprising: a visual display unit; a data entry device; and a data processing system connected to said visual display unit and said data entry device, said data processing system having atomic structure program means for constructing mathematical atomic models, and a text/graphic interactive user interface having program selection means for permitting a user to interact with and perform operations on said atomic structure program means via said data entry device and said visual display unit, an atomic data base containing atomic information for use by said atomic structure program means for constructing said mathematical atomic models, an atomic data display means for displaying on said visual display unit atomic select buttons and said atomic information in response to selections made by said user via said atomic select buttons and said data entry device, and a graphic display means for displaying graphical representations of said mathematical atomic models on said visual display unit, and wherein said atomic data display means includes a periodic table means for displaying a plurality of said atomic select buttons to form element buttons labeled with said atomic information to form a periodic table of chemical elements on said visual display unit, and an element means for displaying on said visual display unit, in response to selection of one of said element buttons, a plurality of said atomic select buttons to form isotope buttons labeled with isotope information from said atomic information, said isotope information corresponding to the isotopes of said one of said chemical elements. 3. The computer apparatus of claim 1 wherein said element means includes a program selection means button for permitting a user to activate said program selection means via said data entry device. | 0.589874 |
7. A computer system for securing search queries, comprising: at least one processing unit; memory operably associated with the at least one processing unit; and a utility stored in the memory and executable by the at least one processing unit, the utility comprising: a module for receiving a search query; a module for analyzing the search query to determine a subject matter of the search query; a module for generating a set of securing search queries that have the subject matter of the search query; a module for submitting the search query and the set of securing search queries to a search engine; and a module for filtering results received from the search engine to remove any hits that resulted from the set of securing search queries. | 7. A computer system for securing search queries, comprising: at least one processing unit; memory operably associated with the at least one processing unit; and a utility stored in the memory and executable by the at least one processing unit, the utility comprising: a module for receiving a search query; a module for analyzing the search query to determine a subject matter of the search query; a module for generating a set of securing search queries that have the subject matter of the search query; a module for submitting the search query and the set of securing search queries to a search engine; and a module for filtering results received from the search engine to remove any hits that resulted from the set of securing search queries. 12. The computer system of claim 7 , further comprising a module for making a requestor of the search query and the set of securing search queries anonymous. | 0.523154 |
12. A digital home communication terminal (DHCT) comprising: a receiver configured to receive from a remote server a video presentation and supplementary information corresponding to and synchronized with the video presentation, the supplementary information comprising on-screen comments; memory configure to store program code; and a processing device configured to execute the program code stored in memory to enable the DHCT to: provide a selectable option to receive the supplementary information; responsive to receiving an input to select the option, receive the supplementary information; provide the video presentation and providing the supplementary information at a plurality of respective active times corresponding to respective portions of the video presentation, and a screen position relative to the video presentation, wherein the active time intervals are determined based on an internal clock and a timer located on the DHCT; receive a second input from the viewer; and provide a video screen in response to the second input, wherein the video screen comprises a first reduced video area for the video presentation, a second reduced area for displaying information related to the video presentation, and a third reduced area for displaying control options for the video presentation, the control options comprising an option to stop the receipt of sequential data supplements. | 12. A digital home communication terminal (DHCT) comprising: a receiver configured to receive from a remote server a video presentation and supplementary information corresponding to and synchronized with the video presentation, the supplementary information comprising on-screen comments; memory configure to store program code; and a processing device configured to execute the program code stored in memory to enable the DHCT to: provide a selectable option to receive the supplementary information; responsive to receiving an input to select the option, receive the supplementary information; provide the video presentation and providing the supplementary information at a plurality of respective active times corresponding to respective portions of the video presentation, and a screen position relative to the video presentation, wherein the active time intervals are determined based on an internal clock and a timer located on the DHCT; receive a second input from the viewer; and provide a video screen in response to the second input, wherein the video screen comprises a first reduced video area for the video presentation, a second reduced area for displaying information related to the video presentation, and a third reduced area for displaying control options for the video presentation, the control options comprising an option to stop the receipt of sequential data supplements. 13. The DHCT of claim 12 , wherein the supplementary information comprises at least one type of data selected from the group consisting of graphical data, textual data, video data, and audio data. | 0.663256 |
2. A voice recognition device controller according to claim 1 , further comprising a learning level storage unit configured to updatably store the user's temporary learning level in speech, wherein the reference input item count setting unit sets the reference value for the number of items identified from the speech based on the user's temporary learning level in speech stored by the learning level storage unit. | 2. A voice recognition device controller according to claim 1 , further comprising a learning level storage unit configured to updatably store the user's temporary learning level in speech, wherein the reference input item count setting unit sets the reference value for the number of items identified from the speech based on the user's temporary learning level in speech stored by the learning level storage unit. 10. A voice recognition device controller according to claim 2 , wherein the learning level storage unit updates the user's temporary learning level in speech stored in the learning level storage unit, based on a determination result of the learning level determination unit. | 0.915102 |
8. A media processing device comprising: a memory to store computer instructions; and a processor coupled to the memory, wherein the processor, responsive to executing the computer instructions, performs operations comprising: receiving, during an active telephone call between a first party and a second party, a textual interpretation of an audio signal associated with the active telephone call and that is generated by equipment of the second party, wherein the textual interpretation of the audio signal is received from an application server; rendering a graphical image of the textual interpretation of the audio signal generated during the active telephone call by the equipment of the second party; accessing a user preference associated with a feature of the graphical image of the textual interpretation of the audio signal; presenting, at a television display, media content that is received from a content source; and presenting at the television display that is associated with a caller identification of the first party, the graphical image of the textual interpretation of the audio signal while the active telephone call by the equipment of the second party is occurring, wherein the graphical image of the textual interpretation of the audio signal is presented as an overlay of the media content that is being presented, and wherein the graphical image is presented according to the user preference. | 8. A media processing device comprising: a memory to store computer instructions; and a processor coupled to the memory, wherein the processor, responsive to executing the computer instructions, performs operations comprising: receiving, during an active telephone call between a first party and a second party, a textual interpretation of an audio signal associated with the active telephone call and that is generated by equipment of the second party, wherein the textual interpretation of the audio signal is received from an application server; rendering a graphical image of the textual interpretation of the audio signal generated during the active telephone call by the equipment of the second party; accessing a user preference associated with a feature of the graphical image of the textual interpretation of the audio signal; presenting, at a television display, media content that is received from a content source; and presenting at the television display that is associated with a caller identification of the first party, the graphical image of the textual interpretation of the audio signal while the active telephone call by the equipment of the second party is occurring, wherein the graphical image of the textual interpretation of the audio signal is presented as an overlay of the media content that is being presented, and wherein the graphical image is presented according to the user preference. 9. The media processing device of claim 8 , wherein the processor, responsive to executing the computer instructions, performs operations further comprising presenting to the television display an offer for presenting the textual interpretation of an audio signal generated during the active telephone call, wherein the rendering of the graphical image of the textual interpretation of the audio signal and the presenting to the television display the graphical image of the textual interpretation are responsive to an acceptance of the offer. | 0.5 |
1. A method of providing a confidence-estimation-based inference, the method comprising: receiving a query concerning a patient from a user; accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient; querying the user, using a conversational interface, for a second component regarding the patient, the second component being in a natural language information form; receiving the second component regarding the patient in response to the query; calculating a first probability density function using the first component, and a second probability density function using the second component; combining the first and second probability density functions using a Gaussian mixture model; calculating at least one conditional probability table using the Gaussian mixture model; and providing the confidence-estimation-based inference based on the at least one conditional probability table. | 1. A method of providing a confidence-estimation-based inference, the method comprising: receiving a query concerning a patient from a user; accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient; querying the user, using a conversational interface, for a second component regarding the patient, the second component being in a natural language information form; receiving the second component regarding the patient in response to the query; calculating a first probability density function using the first component, and a second probability density function using the second component; combining the first and second probability density functions using a Gaussian mixture model; calculating at least one conditional probability table using the Gaussian mixture model; and providing the confidence-estimation-based inference based on the at least one conditional probability table. 7. The method of claim 1 , wherein the user is one of a health care professional, the patient, or a non-human system. | 0.950628 |
15. A system for translating user input into at least one word having multiple characters, the system comprising: a display configured to display a keyboard, wherein the keyboard comprises multiple character indicators; an input device configured to receive a sequence of user inputs; one or more processors; and a memory; wherein the processor and the memory are configured to: encode the sequence of user inputs into a sequence of discrete input directions by selecting, from a set of predetermined primary directions, a discrete direction most closely matching, or exactly matching, each user input; and identify, using the sequence of user inputs, at least one word in a stored dictionary, by matching the sequence of discrete input directions to one or more patterns corresponding to words stored in the dictionary; wherein each of the one or more patterns corresponding to a word specifies a relative directional relationship between; A) a position or area of the keyboard associated with a first character of a pair of sequential characters in the word corresponding to that pattern, and a position or area of the keyboard associated with a second character of the pair of sequential characters; and wherein matching the sequence of discrete input directions to the one or more patterns comprises finding matches between: items in the sequence of discrete input directions, and items in the sequence of discrete directions corresponding to each of the one or more patterns. | 15. A system for translating user input into at least one word having multiple characters, the system comprising: a display configured to display a keyboard, wherein the keyboard comprises multiple character indicators; an input device configured to receive a sequence of user inputs; one or more processors; and a memory; wherein the processor and the memory are configured to: encode the sequence of user inputs into a sequence of discrete input directions by selecting, from a set of predetermined primary directions, a discrete direction most closely matching, or exactly matching, each user input; and identify, using the sequence of user inputs, at least one word in a stored dictionary, by matching the sequence of discrete input directions to one or more patterns corresponding to words stored in the dictionary; wherein each of the one or more patterns corresponding to a word specifies a relative directional relationship between; A) a position or area of the keyboard associated with a first character of a pair of sequential characters in the word corresponding to that pattern, and a position or area of the keyboard associated with a second character of the pair of sequential characters; and wherein matching the sequence of discrete input directions to the one or more patterns comprises finding matches between: items in the sequence of discrete input directions, and items in the sequence of discrete directions corresponding to each of the one or more patterns. 21. The system of claim 15 , wherein the input device comprises at least one of: a set of push-buttons, a joystick, or a multi-directional input button having eight or fewer distinctly selectable directions. | 0.87822 |
16. A system for tracking usage of business data elements, the system comprising: a) means for identifying instances of business data elements in a first plurality of electronic documents being communicated between business entities during a first time duration, each electronic document in the first plurality having a format corresponding to a business communication schema, wherein the business communication schema includes a set of predefined business data elements for use in electronically communicating business data from a first business entity to a second business entity; b) means for tracking usage of the business data elements across the first plurality of electronic documents in the set of predefined business data elements in response to identifying instances of the business data elements in the set of predefined business data elements in each electronic document; c) means for comparing a quantity of instances of the business data elements with threshold values, each threshold value corresponding to a particular business data element; d) means for removing the business data elements from the business communication schema when the quantity of instances of the business data elements is less than their corresponding threshold values during the first time duration; e) means for presenting a user with at least one of the quantity of instances and the business data elements prior to removing the business data elements from the business communication schema based on the quantity of instances being less than their corresponding threshold values; f) means for receiving an instruction from the user to remove the business data elements from the business communication schema; g) means for resetting the quantity of instance based on the quantity being at least equal to the corresponding threshold values; h) means for initiating a second time duration upon resetting of the Quantity; and i) means for repeating the functions of b) through d) for a second plurality of electronic documents being communicated between business entities during the second time duration. | 16. A system for tracking usage of business data elements, the system comprising: a) means for identifying instances of business data elements in a first plurality of electronic documents being communicated between business entities during a first time duration, each electronic document in the first plurality having a format corresponding to a business communication schema, wherein the business communication schema includes a set of predefined business data elements for use in electronically communicating business data from a first business entity to a second business entity; b) means for tracking usage of the business data elements across the first plurality of electronic documents in the set of predefined business data elements in response to identifying instances of the business data elements in the set of predefined business data elements in each electronic document; c) means for comparing a quantity of instances of the business data elements with threshold values, each threshold value corresponding to a particular business data element; d) means for removing the business data elements from the business communication schema when the quantity of instances of the business data elements is less than their corresponding threshold values during the first time duration; e) means for presenting a user with at least one of the quantity of instances and the business data elements prior to removing the business data elements from the business communication schema based on the quantity of instances being less than their corresponding threshold values; f) means for receiving an instruction from the user to remove the business data elements from the business communication schema; g) means for resetting the quantity of instance based on the quantity being at least equal to the corresponding threshold values; h) means for initiating a second time duration upon resetting of the Quantity; and i) means for repeating the functions of b) through d) for a second plurality of electronic documents being communicated between business entities during the second time duration. 20. The system of claim 16 wherein the tracked usage of the business data elements is used in selecting among business data elements in the set of predefined business data elements during a translation of an electronic document from a first one of a plurality of available business communication schemas to a second one of the plurality of available business communication schemas. | 0.616824 |
1. A document processing method comprising: receiving an input document which includes an abstract and a main body within the input document; storing the input document in memory of a computer system; identifying the abstract and the main body of the input document; for each sentence of the abstract of the input document, comparing the sentence with sentences of the main body of the input document using textual entailment techniques to identify whether the sentence of the abstract entails a sentence in the main body of the input document, the textual entailment techniques including identifying one-directional paraphrasing, wherein the entailed sentence in the main body need not entail the sentence of the abstract; generating links between the entailing sentences of the abstract and the corresponding entailed sentences of the input document; and outputting the generated links; wherein at least one of the comparing and link generation is performed with a computer processor. | 1. A document processing method comprising: receiving an input document which includes an abstract and a main body within the input document; storing the input document in memory of a computer system; identifying the abstract and the main body of the input document; for each sentence of the abstract of the input document, comparing the sentence with sentences of the main body of the input document using textual entailment techniques to identify whether the sentence of the abstract entails a sentence in the main body of the input document, the textual entailment techniques including identifying one-directional paraphrasing, wherein the entailed sentence in the main body need not entail the sentence of the abstract; generating links between the entailing sentences of the abstract and the corresponding entailed sentences of the input document; and outputting the generated links; wherein at least one of the comparing and link generation is performed with a computer processor. 14. The method of claim 1 further comprising natural language processing of the abstract and main body of the input document prior to comparing the abstract sentences with sentences of a main body of the input document. | 0.5672 |
1. A computer-implemented data mining system for use in rating endorsers, comprising: a server computer having a tangible computing processor, the processor in data communication with a non-transitory computer memory that stores instructions which, when executed on the processor, cause the computer to implement: a search engine that searches a plurality of RSS feeds for mentions of an identified endorser in conjunction with keywords; a ratings engine that rates the mentions in at least a portion of the RSS feeds based on an identified subset of a categorical hierarchy of the keywords and a number of words in the RSS feeds between the endorser and the corresponding keywords, wherein positive mentions and negative mentions are separately tracked and combined into an overall rating; an information engine that obtains information regarding a number of viewings of the rated mentions in the RSS feeds; a repository that stores each of the plurality of RSS feeds; and a data miner communicatively connected to the search engine, the ratings engine, and the repository, the data miner operative to generate a consumer opinion index of the endorser based on a correlation of the rating of the mentions and the number of viewings, wherein the RSS feeds stored in the repository, the mentions of the subject in conjunction with the keywords, and the consumer opinion index are searchable, wherein the mentions are permanently available from the repository; and wherein the endorser is one of an affinity brand, a marketing partner, and a sponsor. | 1. A computer-implemented data mining system for use in rating endorsers, comprising: a server computer having a tangible computing processor, the processor in data communication with a non-transitory computer memory that stores instructions which, when executed on the processor, cause the computer to implement: a search engine that searches a plurality of RSS feeds for mentions of an identified endorser in conjunction with keywords; a ratings engine that rates the mentions in at least a portion of the RSS feeds based on an identified subset of a categorical hierarchy of the keywords and a number of words in the RSS feeds between the endorser and the corresponding keywords, wherein positive mentions and negative mentions are separately tracked and combined into an overall rating; an information engine that obtains information regarding a number of viewings of the rated mentions in the RSS feeds; a repository that stores each of the plurality of RSS feeds; and a data miner communicatively connected to the search engine, the ratings engine, and the repository, the data miner operative to generate a consumer opinion index of the endorser based on a correlation of the rating of the mentions and the number of viewings, wherein the RSS feeds stored in the repository, the mentions of the subject in conjunction with the keywords, and the consumer opinion index are searchable, wherein the mentions are permanently available from the repository; and wherein the endorser is one of an affinity brand, a marketing partner, and a sponsor. 10. The system of claim 1 , wherein the RRS feeds include any web accessible content. | 0.707483 |
15. A computer-implemented method, comprising: receiving event data from an event stream; receiving, by a computing system, a continuous query language query statement for processing the event data of the event stream; generating a first logical plan comprising one or more logical operators of the continuous language query; generating, based at least in part on the one or more logical operators of the continuous query language query statement in the first logical plan, a query graph for enabling evaluation of less than all of the one or more logical operators of the continuous query language query statement; generating, based at least in part on the query graph, a second logical plan for implementing the continuous query language query statement to process the event data of the event stream, the second logical plan comprising at least one conditional instruction for skipping evaluation of at least one or more expressions associated with the one or more logical operators after a first expression comprising the one or more expressions has been evaluated; compiling, by the computing system, the second logical plan into machine-readable instructions for implementing the one or more logical operators of the continuous query language query statement in the first logical plan; and executing the machine-readable instructions, the machine-readable instructions comprising the conditional instruction for skipping evaluation, at a runtime, of the one or more expressions associated with the subset of the logical operators of the continuous query language query, the conditional instruction identifying, at the runtime, a function comprising a list of input arguments, and the list of input arguments comprising at least one of an input operand indicating a result of execution of a previous instruction in the second logical plan, a storage parameter indicating a storage location to jump to if an expression represented by the input operand satisfies a condition, or a result parameter indicating a result location of execution of the conditional instruction. | 15. A computer-implemented method, comprising: receiving event data from an event stream; receiving, by a computing system, a continuous query language query statement for processing the event data of the event stream; generating a first logical plan comprising one or more logical operators of the continuous language query; generating, based at least in part on the one or more logical operators of the continuous query language query statement in the first logical plan, a query graph for enabling evaluation of less than all of the one or more logical operators of the continuous query language query statement; generating, based at least in part on the query graph, a second logical plan for implementing the continuous query language query statement to process the event data of the event stream, the second logical plan comprising at least one conditional instruction for skipping evaluation of at least one or more expressions associated with the one or more logical operators after a first expression comprising the one or more expressions has been evaluated; compiling, by the computing system, the second logical plan into machine-readable instructions for implementing the one or more logical operators of the continuous query language query statement in the first logical plan; and executing the machine-readable instructions, the machine-readable instructions comprising the conditional instruction for skipping evaluation, at a runtime, of the one or more expressions associated with the subset of the logical operators of the continuous query language query, the conditional instruction identifying, at the runtime, a function comprising a list of input arguments, and the list of input arguments comprising at least one of an input operand indicating a result of execution of a previous instruction in the second logical plan, a storage parameter indicating a storage location to jump to if an expression represented by the input operand satisfies a condition, or a result parameter indicating a result location of execution of the conditional instruction. 19. The computer-implemented method of claim 15 , wherein the instructions include at least a jump_if_true or a jump_if_false instruction. | 0.582609 |
18. The non-transitory computer readable medium of claim 17 , wherein the application further comprises a user interface for enabling user input. | 18. The non-transitory computer readable medium of claim 17 , wherein the application further comprises a user interface for enabling user input. 21. The non-transitory computer readable medium of claim 18 , wherein the user input comprises a user definition of the context of the key word sets. | 0.957386 |
17. The computer-readable hardware storage medium as in claim 16 , wherein mapping each set includes: mapping the first set of words to a first candidate intent value; and mapping the second of words to a second candidate intent value. | 17. The computer-readable hardware storage medium as in claim 16 , wherein mapping each set includes: mapping the first set of words to a first candidate intent value; and mapping the second of words to a second candidate intent value. 18. The computer-readable hardware storage medium as in claim 17 , wherein selecting the candidate intent value includes: identifying a frequency of occurrence that utterances in a pool of previously received utterances were of a same intent type as that of the first candidate intent value; identifying a frequency of occurrence that utterances in the pool of previously received utterances were of a same intent type as that of the second candidate intent value; and selecting the candidate intent value for the utterance depending on which of the first candidate intent value and second candidate intent value occurred more often in the pool for the previously received utterances, the selected candidate value indicating a dominant subject matter of the utterance. | 0.761961 |
15. A method implemented by a computing device, the method comprising: receiving, with a web browser, user input in the form of text; based upon a format of the user input, selecting, by the web browser, from among at least two different URLs, a first of the URLs being configured to enable a search provider to cause a redirection of the web browser to a web address associated with the user input based at least in part on an indication that the text is the subject of an attempted navigation to the web address, a second of the URLs being configured to enable the search provider to return, to the web browser a search results page associated with the user input based at least in part on an indication that the text is the subject of an attempted search; automatically navigating, by the web browser, to the web address responsive to selecting the first of the URLs: and presenting, with the web browser, a web page associated with the selected URL. | 15. A method implemented by a computing device, the method comprising: receiving, with a web browser, user input in the form of text; based upon a format of the user input, selecting, by the web browser, from among at least two different URLs, a first of the URLs being configured to enable a search provider to cause a redirection of the web browser to a web address associated with the user input based at least in part on an indication that the text is the subject of an attempted navigation to the web address, a second of the URLs being configured to enable the search provider to return, to the web browser a search results page associated with the user input based at least in part on an indication that the text is the subject of an attempted search; automatically navigating, by the web browser, to the web address responsive to selecting the first of the URLs: and presenting, with the web browser, a web page associated with the selected URL. 18. The method of claim 15 , wherein the web browser is configured to enable the search provider to cause redirection of the web browser without further user action. | 0.877219 |
11. A multi-modal dialog system presenting a map-based application comprising: a multi-modal interface module that receives multi-modal input from a user received in a combination of a first mode and a second mode and provides multi-modal information to the user; a module that maintains a current dialog screen context by only presenting additional data on a display in response to the multimodal input until further user input is received via user interaction with the additional data that clarifies the multimodal input; and a widget control module that dynamically presents the slider widget on the display screen to facilitate a multi-modal dialog between the user and the multi-modal dialog system, the slider widget receiving further user input in a third mode, the further user input clarifying the first user input and providing distance range data that is shown on the display screen as the slider widget is adjusted by the further user input. | 11. A multi-modal dialog system presenting a map-based application comprising: a multi-modal interface module that receives multi-modal input from a user received in a combination of a first mode and a second mode and provides multi-modal information to the user; a module that maintains a current dialog screen context by only presenting additional data on a display in response to the multimodal input until further user input is received via user interaction with the additional data that clarifies the multimodal input; and a widget control module that dynamically presents the slider widget on the display screen to facilitate a multi-modal dialog between the user and the multi-modal dialog system, the slider widget receiving further user input in a third mode, the further user input clarifying the first user input and providing distance range data that is shown on the display screen as the slider widget is adjusted by the further user input. 16. The multi-modal dialog system of claim 11 , wherein the user can provide user input in response to the slider widget via speech rather than interacting with the widget via a non-speech mode. | 0.616376 |
12. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU for extracting a human readable list from a document, said apparatus comprising: a display device in operative communication with said CPU for displaying information to a user of said apparatus; a file access mechanism configured to access a file, said file containing data that represents a portion of said document, said data formatted in accordance with a document formatting description (DFD); a parser configured for parsing said data, the parsing including: making corrections to said data when said data is formed incorrectly with respect to the DFD; identifying a plurality of tags in said data; generating a plurality of container tokens, each of said plurality of container tokens corresponding to one of said plurality of tags; and generating a plurality of textual tokens for said data not identified as one of said plurality of tags; a tag path set detection mechanism configured to determine a set of tag paths, each of the tag paths being associated with at least one of the plurality of textual tokens; a tag path of interest detection mechanism configured to determine tag paths of interest, the tag path of interest detection mechanism further configured to: collect all of the tag paths of the set of tag paths; remove duplicate tag paths from the collected tag paths to generate a full tag path set for the document; determine the number of textual tokens for each tag path of the full tag path set; and find tag paths of interest in the full tag path set, each of the tag paths of interest satisfying a predetermined criteria; a semantic analysis mechanism configured to determine a context for each tag path of interest, said context defined by the tag path of interest and a matching pair of said container tokens within the tag path of interest; a contiguous list detection mechanism configured to determine contiguous lists, by performing the steps of: iterating through tokens of the tag oaths of interest to find at least one locatable list; and for each locatable list, perform accumulation of text tokens, the accumulation of text tokens comprising: identifying a first textual token in the respective tag path of interest; accumulating the first textual token into a contiguous list; identifying a second textual token having the same context as the first textual token; accumulating the second textual token into the contiguous list; creating a separator pattern based on tokens between the first textual token and the second textual token, the creating a separator pattern including: discarding white space in the tokens between the first textual token and the second textual token; and discarding tag attributes in the tokens between the first textual token and the second textual token; and checking for another occurrence of the separator pattern following the second textual token, and for each occurrence of the separator pattern: extracting a subsequent text token associated with the occurrence of the separator pattern and accumulating the subsequent textual token into the contiguous list if the subsequent textual token is separated from the previous textual token by only the occurrence of the separator pattern; and terminating the accumulating text tokens for the current locatable list if the subsequent textual token is not separated from the previous textual token by only the occurrence of the separator pattern; the contiguous list detection mechanism including: an interval detection mechanism configured to determine the separator pattern between one of said plurality of textual tokens and an adjacent textual token where both said one of said plurality of textual tokens and said adjacent textual token have said context; and an extraction mechanism configured to extract one or more of said plurality of textual tokens, wherein each of the extracted one or more of said plurality of textual tokens have said context; and a presentation mechanism configured to present one or more of said plurality of textual tokens to said user on said display device as said human readable list, the presentation mechanism including: an audio mechanism to present said human readable list to the user using audio; and a retrievable storage mechanism to store said human readable list in a retrievable electronic file. | 12. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU for extracting a human readable list from a document, said apparatus comprising: a display device in operative communication with said CPU for displaying information to a user of said apparatus; a file access mechanism configured to access a file, said file containing data that represents a portion of said document, said data formatted in accordance with a document formatting description (DFD); a parser configured for parsing said data, the parsing including: making corrections to said data when said data is formed incorrectly with respect to the DFD; identifying a plurality of tags in said data; generating a plurality of container tokens, each of said plurality of container tokens corresponding to one of said plurality of tags; and generating a plurality of textual tokens for said data not identified as one of said plurality of tags; a tag path set detection mechanism configured to determine a set of tag paths, each of the tag paths being associated with at least one of the plurality of textual tokens; a tag path of interest detection mechanism configured to determine tag paths of interest, the tag path of interest detection mechanism further configured to: collect all of the tag paths of the set of tag paths; remove duplicate tag paths from the collected tag paths to generate a full tag path set for the document; determine the number of textual tokens for each tag path of the full tag path set; and find tag paths of interest in the full tag path set, each of the tag paths of interest satisfying a predetermined criteria; a semantic analysis mechanism configured to determine a context for each tag path of interest, said context defined by the tag path of interest and a matching pair of said container tokens within the tag path of interest; a contiguous list detection mechanism configured to determine contiguous lists, by performing the steps of: iterating through tokens of the tag oaths of interest to find at least one locatable list; and for each locatable list, perform accumulation of text tokens, the accumulation of text tokens comprising: identifying a first textual token in the respective tag path of interest; accumulating the first textual token into a contiguous list; identifying a second textual token having the same context as the first textual token; accumulating the second textual token into the contiguous list; creating a separator pattern based on tokens between the first textual token and the second textual token, the creating a separator pattern including: discarding white space in the tokens between the first textual token and the second textual token; and discarding tag attributes in the tokens between the first textual token and the second textual token; and checking for another occurrence of the separator pattern following the second textual token, and for each occurrence of the separator pattern: extracting a subsequent text token associated with the occurrence of the separator pattern and accumulating the subsequent textual token into the contiguous list if the subsequent textual token is separated from the previous textual token by only the occurrence of the separator pattern; and terminating the accumulating text tokens for the current locatable list if the subsequent textual token is not separated from the previous textual token by only the occurrence of the separator pattern; the contiguous list detection mechanism including: an interval detection mechanism configured to determine the separator pattern between one of said plurality of textual tokens and an adjacent textual token where both said one of said plurality of textual tokens and said adjacent textual token have said context; and an extraction mechanism configured to extract one or more of said plurality of textual tokens, wherein each of the extracted one or more of said plurality of textual tokens have said context; and a presentation mechanism configured to present one or more of said plurality of textual tokens to said user on said display device as said human readable list, the presentation mechanism including: an audio mechanism to present said human readable list to the user using audio; and a retrievable storage mechanism to store said human readable list in a retrievable electronic file. 13. The apparatus of claim 12 , wherein said document formatting description is selected from the group consisting of HTML, SGML, XML, PCL, POSTSCRIPT and ASCII text. | 0.536444 |
23. A computer-implemented method of associating dependency structures from two different languages stored on a tangible computer readable medium, wherein the dependency structures comprise nodes organized in a parent/child structure, the computer-implemented method comprising: aligning nodes of the dependency structures with correspondences on the tangible medium with a computer as a function of a set of rules comprising at least three different rules, wherein the dependency structures comprise a set of unaligned nodes and wherein after each of the rules are applied any aligned nodes are removed from the set of unaligned nodes before applying another rule, and wherein aligning does not require beginning with either a top or bottom node of the hierarchical parent/child structure of the dependency structures, and wherein aligning is not based on top-down processing or bottom-up processing of nodes; and providing an output from the computer indicative of the alignment of the dependency structures. | 23. A computer-implemented method of associating dependency structures from two different languages stored on a tangible computer readable medium, wherein the dependency structures comprise nodes organized in a parent/child structure, the computer-implemented method comprising: aligning nodes of the dependency structures with correspondences on the tangible medium with a computer as a function of a set of rules comprising at least three different rules, wherein the dependency structures comprise a set of unaligned nodes and wherein after each of the rules are applied any aligned nodes are removed from the set of unaligned nodes before applying another rule, and wherein aligning does not require beginning with either a top or bottom node of the hierarchical parent/child structure of the dependency structures, and wherein aligning is not based on top-down processing or bottom-up processing of nodes; and providing an output from the computer indicative of the alignment of the dependency structures. 26. The computer-implemented method of claim 23 wherein later rule applications use an alignment created by an earlier rule application as a reference point that is used to disambiguate between competing alignments. | 0.612075 |
9. A program product stored on a computer recordable medium for analyzing table access in a database system, comprising: program code configured for defining an incorrect rule set and a related correct rule set from a database model associated with the database system; program code configured for retrieving index definitions for the database system; program code configured for comparing the index definitions with the incorrect rule set to identify improper indexes independent of SQL processing; program code configured for generating a list of index definitions that match a rule in the incorrect rule set; program code configured for retrieving application programs for the database system; program code configured for comparing application programs with the index definitions that match a rule in the incorrect rule set; program code configured for generating a list of application programs which match a rule in the incorrect rule set; program code configured for merging the list of index definitions with the list of application programs; program code configured for reporting the merged list of index definitions and application programs; program code configured for identifying and outputting to memory application program statements that utilize the improper indexes; and program code configured for using the related correct rule set to propose changes to the improper indexes and any application programs that depend on the improper indexes. | 9. A program product stored on a computer recordable medium for analyzing table access in a database system, comprising: program code configured for defining an incorrect rule set and a related correct rule set from a database model associated with the database system; program code configured for retrieving index definitions for the database system; program code configured for comparing the index definitions with the incorrect rule set to identify improper indexes independent of SQL processing; program code configured for generating a list of index definitions that match a rule in the incorrect rule set; program code configured for retrieving application programs for the database system; program code configured for comparing application programs with the index definitions that match a rule in the incorrect rule set; program code configured for generating a list of application programs which match a rule in the incorrect rule set; program code configured for merging the list of index definitions with the list of application programs; program code configured for reporting the merged list of index definitions and application programs; program code configured for identifying and outputting to memory application program statements that utilize the improper indexes; and program code configured for using the related correct rule set to propose changes to the improper indexes and any application programs that depend on the improper indexes. 10. The program product of claim 9 , wherein each incorrect rule in the incorrect rule set includes a table name, a name of a column in the table containing redundantly stored data that is properly indexed in another table, and a link to a correct rule. | 0.5 |
1. A computer-implemented method, comprising: receiving, at a server from a mobile computing device, the server having one or more processors, an image including a text; obtaining, at the server, optical character recognition (OCR) text corresponding to the text, the OCR text having been obtained by performing OCR on the image; identifying, at the server, non-textual context information from the image, the non-textual context information (i) representing context information other than the text itself, (ii) being indicative of a context of the image, and (iii) including at least a color of an object in the image; based on the color of the object, determining, at the server, whether the image was captured indoors or outdoors; based on (i) the non-textual context information and (ii) whether the image was captured indoors or outdoors, obtaining, at the server, a translation of the OCR text to a target language to obtain a translated OCR text; and outputting, from the server to the mobile computing device, the translated OCR text. | 1. A computer-implemented method, comprising: receiving, at a server from a mobile computing device, the server having one or more processors, an image including a text; obtaining, at the server, optical character recognition (OCR) text corresponding to the text, the OCR text having been obtained by performing OCR on the image; identifying, at the server, non-textual context information from the image, the non-textual context information (i) representing context information other than the text itself, (ii) being indicative of a context of the image, and (iii) including at least a color of an object in the image; based on the color of the object, determining, at the server, whether the image was captured indoors or outdoors; based on (i) the non-textual context information and (ii) whether the image was captured indoors or outdoors, obtaining, at the server, a translation of the OCR text to a target language to obtain a translated OCR text; and outputting, from the server to the mobile computing device, the translated OCR text. 4. The computer-implemented method of claim 1 , further comprising determining, at the server, a type of location at which the image was captured based on the non-textual context information, wherein the translated OCR text is further based on the type of location. | 0.528796 |
12. The method of claim 10 , wherein punctuation marks are parsed in the same manner as words. | 12. The method of claim 10 , wherein punctuation marks are parsed in the same manner as words. 13. The method of claim 12 , wherein concept symbols are generated for punctuation marks in the same manner that concept symbols are generated for words. | 0.974822 |
9. A method for contact centers to identify contact center agents based upon voice characteristics of the human agents comprising: a human agent logging onto a contact center and providing authentication information that includes a user name unique to that human agent and a corresponding password for the user name; the contact center authenticating the agent using the authentication information; the call center transferring a caller to the human agent to initiate a contact center communication session between the human agent and the caller; receiving speech content associated with the contact center communication session; extracting biometric characteristics contained within the speech content of the contact center communication session; comparing the extracted biometric characteristics against previously stored biometric characteristics associated with the human agent; determining an identity of a speaker of the content based upon results of the comparing step; comparing the identity of the speaker with an identity of a human associated with the user name, wherein the comparison is performed to verify that a human logged in as the human agent via the user name is in fact the speaker; a contact center performing at least one programmatic action based upon results of the determined identity, wherein the programmatic action is determining whether inappropriate phrases spoken during the communication session were attributable to the human agent or to the caller and taking corrective or punishment actions against the human agent when the human agent is determined to have spoken the inappropriate phrases. | 9. A method for contact centers to identify contact center agents based upon voice characteristics of the human agents comprising: a human agent logging onto a contact center and providing authentication information that includes a user name unique to that human agent and a corresponding password for the user name; the contact center authenticating the agent using the authentication information; the call center transferring a caller to the human agent to initiate a contact center communication session between the human agent and the caller; receiving speech content associated with the contact center communication session; extracting biometric characteristics contained within the speech content of the contact center communication session; comparing the extracted biometric characteristics against previously stored biometric characteristics associated with the human agent; determining an identity of a speaker of the content based upon results of the comparing step; comparing the identity of the speaker with an identity of a human associated with the user name, wherein the comparison is performed to verify that a human logged in as the human agent via the user name is in fact the speaker; a contact center performing at least one programmatic action based upon results of the determined identity, wherein the programmatic action is determining whether inappropriate phrases spoken during the communication session were attributable to the human agent or to the caller and taking corrective or punishment actions against the human agent when the human agent is determined to have spoken the inappropriate phrases. 14. The method of claim 9 , further comprising: automatically converting the speech content to text; and adding speaker identifying text to the converted text that indicates which of the contact center agent and a caller provided the associated converted text, wherein the added speaker identifying text is based on results of the determining step. | 0.570833 |
8. A system comprising: a processor; one or more memory devices; a data store held in at least one of the memory devices, the data store comprising: rule definitions, each rule including one or more rule components, each rule component including a reference to one or more values from which an inference is made when the rule is applied; tag definitions which when associated with a rule component limit how the rule component may be modified, the limiting of one or more rule component modifications with the one or more tag definitions including a tag definition specifying a subset of available rule component values from the one or more values defined in the rule definition, the tag definitions each including at least one verb that identifies how the tag modifies data of the available rule component values to form the subset of available rule component values; associations of tag definitions to rule components of the rule definitions; and rule administrator records, each rule administrator record including a rule administrator identifier; a rule administration program in at least one of the memory devices and operable on the processor to: provide one or more rule administration user interfaces, the rule administration user interfaces operable to receive input to define and modify the rule definitions and the associations of the tag definitions to the rule components; and implementing the limits of tag definitions associated with rule components by limiting how rule components may be modified within the one or more rule administration user interfaces as a function of a rule administrator identifier. | 8. A system comprising: a processor; one or more memory devices; a data store held in at least one of the memory devices, the data store comprising: rule definitions, each rule including one or more rule components, each rule component including a reference to one or more values from which an inference is made when the rule is applied; tag definitions which when associated with a rule component limit how the rule component may be modified, the limiting of one or more rule component modifications with the one or more tag definitions including a tag definition specifying a subset of available rule component values from the one or more values defined in the rule definition, the tag definitions each including at least one verb that identifies how the tag modifies data of the available rule component values to form the subset of available rule component values; associations of tag definitions to rule components of the rule definitions; and rule administrator records, each rule administrator record including a rule administrator identifier; a rule administration program in at least one of the memory devices and operable on the processor to: provide one or more rule administration user interfaces, the rule administration user interfaces operable to receive input to define and modify the rule definitions and the associations of the tag definitions to the rule components; and implementing the limits of tag definitions associated with rule components by limiting how rule components may be modified within the one or more rule administration user interfaces as a function of a rule administrator identifier. 13. The system of claim 8 , wherein the rule administration program is further operable to: allow a first user to generate the rule definition and associate tag definitions to the rule components to limit how a second user is allowed to modify the rule definition. | 0.5 |
8. A non-transitory computer-readable storage medium storing instructions that, when executed by a mobile client device executing a social media messaging program, cause the mobile client device to perform the operations of: receiving, in the social media messaging program, a search request including one or more search terms; in accordance with a predefined search type hierarchy, searching content of a first set of content types of a plurality of content types to produce first search results, wherein: the search is based on the search request; and the predefined search type hierarchy specifies an order with which content types in the plurality of content types are to be searched; determining a count of the first search results; when the count of first search results is greater than or equal to a predefined number, displaying the first search results and affordances for searching content of one or more other content types in the plurality of content types; when the count of first search results is less than the predefined number: in accordance with the predefined search type hierarchy, searching content of a second set of content types of the plurality of content types to produce second search results; and displaying the second search results. | 8. A non-transitory computer-readable storage medium storing instructions that, when executed by a mobile client device executing a social media messaging program, cause the mobile client device to perform the operations of: receiving, in the social media messaging program, a search request including one or more search terms; in accordance with a predefined search type hierarchy, searching content of a first set of content types of a plurality of content types to produce first search results, wherein: the search is based on the search request; and the predefined search type hierarchy specifies an order with which content types in the plurality of content types are to be searched; determining a count of the first search results; when the count of first search results is greater than or equal to a predefined number, displaying the first search results and affordances for searching content of one or more other content types in the plurality of content types; when the count of first search results is less than the predefined number: in accordance with the predefined search type hierarchy, searching content of a second set of content types of the plurality of content types to produce second search results; and displaying the second search results. 11. The non-transitory computer-readable storage medium of claim 8 , wherein: the displayed first search results each includes a first affordance to perform a first operation in accordance with the first set of content types; and the displayed second search results each includes a second affordance to perform a second operation in accordance with the second set of content types. | 0.592869 |
1. A computer system, comprising: at least one audio input device, at least one computer storage medium and at least one processor, wherein the at least one audio input device and the computer storage medium are configured to receive and store live audio data for processing by the computer system; wherein the computer system is further configured by a computer program in the computer storage medium to: access, using the processor, data in the computer storage medium defining computer operating context of the computer system; detect, using the processor, starting conditions by processing the computer operating context accessed from the computer storage medium; after detecting starting conditions: process, using the processor, the live audio data to extract at least text and store the text in the at least one computer storage medium; process, using the processor, the extracted text to generate information in the at least one computer storage medium identifying salient patterns in the extracted text; and provide the extracted text and the information identifying salient patterns in the computer storage medium for access by a notetaking application running on the computer system, wherein the notetaking application running on the computer system is configured to receive user input to edit an electronic document in the at least one computer storage medium incorporating the extracted text and the information identifying salient patterns. | 1. A computer system, comprising: at least one audio input device, at least one computer storage medium and at least one processor, wherein the at least one audio input device and the computer storage medium are configured to receive and store live audio data for processing by the computer system; wherein the computer system is further configured by a computer program in the computer storage medium to: access, using the processor, data in the computer storage medium defining computer operating context of the computer system; detect, using the processor, starting conditions by processing the computer operating context accessed from the computer storage medium; after detecting starting conditions: process, using the processor, the live audio data to extract at least text and store the text in the at least one computer storage medium; process, using the processor, the extracted text to generate information in the at least one computer storage medium identifying salient patterns in the extracted text; and provide the extracted text and the information identifying salient patterns in the computer storage medium for access by a notetaking application running on the computer system, wherein the notetaking application running on the computer system is configured to receive user input to edit an electronic document in the at least one computer storage medium incorporating the extracted text and the information identifying salient patterns. 2. The computer system of claim 1 , wherein the data defining computer operating context includes environmental data from a sensor. | 0.602557 |
1. A method comprising: for each of a plurality of application (app) records each specifying an app and including an app download address (ADA) for downloading the app, determining, by an analysis system in a server, one or more connections associated with the app, and determining, by the analysis system, one or more terms associated with one or more resources connected with the app by the one or more connections; receiving, by a search system in the server, a search query from a user device; identifying, by the search system, one or more of the plurality of app records based on the search query and based on the one or more terms associated with the one or more resources connected with the app specified by the each of the plurality of app records; selecting, by the search system, one or more ADAs from the identified one or more of the plurality of app records; and transmitting, by the search system, the one or more ADAs to the user device. | 1. A method comprising: for each of a plurality of application (app) records each specifying an app and including an app download address (ADA) for downloading the app, determining, by an analysis system in a server, one or more connections associated with the app, and determining, by the analysis system, one or more terms associated with one or more resources connected with the app by the one or more connections; receiving, by a search system in the server, a search query from a user device; identifying, by the search system, one or more of the plurality of app records based on the search query and based on the one or more terms associated with the one or more resources connected with the app specified by the each of the plurality of app records; selecting, by the search system, one or more ADAs from the identified one or more of the plurality of app records; and transmitting, by the search system, the one or more ADAs to the user device. 6. The method of claim 1 , wherein identifying the one or more of the plurality of app records based on the search query and based on the one or more terms associated with the at least one resource connected with the app specified by the each of the plurality of app records comprises identifying the each of the plurality of app records based on one or more matches between one or more terms of the search query and the one or more terms associated with the one or more resources connected with the app specified by the each of the plurality of app records. | 0.759673 |
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. | 0.503808 |
1. A polyaxial bone screw assembly for fixation to a bone, the assembly including a shank with a threaded body and an upwardly extending head portion, a retainer structure sized and shaped to join and polyaxially rotate with the shank, and a receiver that operably receives the head portion and retainer, the assembly further wherein: a) the head portion comprising a retainer engagement portion including a partially circumferential curvate groove with contoured upper and lower mating surfaces and a pair of spaced recesses; b) the retainer structure being sized and shaped to matingly engage the retainer engagement portion so as to form a substantially spherical ball-shaped pivoting surface with the head portion, the retainer structure comprising i) top and bottom mating surfaces complementary contoured for mating with the head portion upper and lower mating surfaces; and ii) a pair of spaced prongs sized and shaped to matingly engage the head portion recesses; c) the receiver defining an open channel and having a base with a lower seating surface partially defining a cavity, the seating surface being sized and shaped to engage at least a portion of upper head portion, the open channel communicating with the cavity, the cavity communicating with an exterior of the base through an opening sized and shaped to receive the shank upper head portion by uploading the upper head portion through the opening, where the upper head portion mates with the retainer within the cavity. | 1. A polyaxial bone screw assembly for fixation to a bone, the assembly including a shank with a threaded body and an upwardly extending head portion, a retainer structure sized and shaped to join and polyaxially rotate with the shank, and a receiver that operably receives the head portion and retainer, the assembly further wherein: a) the head portion comprising a retainer engagement portion including a partially circumferential curvate groove with contoured upper and lower mating surfaces and a pair of spaced recesses; b) the retainer structure being sized and shaped to matingly engage the retainer engagement portion so as to form a substantially spherical ball-shaped pivoting surface with the head portion, the retainer structure comprising i) top and bottom mating surfaces complementary contoured for mating with the head portion upper and lower mating surfaces; and ii) a pair of spaced prongs sized and shaped to matingly engage the head portion recesses; c) the receiver defining an open channel and having a base with a lower seating surface partially defining a cavity, the seating surface being sized and shaped to engage at least a portion of upper head portion, the open channel communicating with the cavity, the cavity communicating with an exterior of the base through an opening sized and shaped to receive the shank upper head portion by uploading the upper head portion through the opening, where the upper head portion mates with the retainer within the cavity. 2. The assembly according to claim 1 including a pressure insert that pivotably engages the shank head portion comprising: i) a lower body with a pair of spaced opposed partially cylindrical surfaces and a pair of spaced vertical faces; and ii) a pair of opposed upwardly extending arm structures, each arm structure having a radially extending protrusion with a centrally located locking slot, the cavity of the receiver having an interior wall having a protrusion that mates with locking slot. | 0.600906 |
17. The computer program product as described in claim 16 wherein the method further includes taking a given action with respect to the one or more pieces of information that have been highlighted. | 17. The computer program product as described in claim 16 wherein the method further includes taking a given action with respect to the one or more pieces of information that have been highlighted. 19. The computer program product as described in claim 17 wherein the method further includes outputting the data item without the one or more pieces of information. | 0.894563 |
1. A method for enabling a search against an information source deemed to be an expert in a category of interest, comprising: accessing results of searches performed by at least one search engine; determining, among the accessed results, a set of results provided by a particular information source; identifying a category of interest; determining a set of results that are related to the identified category of interest and that also are provided by the particular information source; determining a first ratio of the accessed results provided by the particular information source to the accessed results provided by other information sources; determining a second ratio of search results that are related to the identified category and provided by the particular information source to search results that are related to the identified category and provided by other information sources; identifying the particular information source as an expert information source for the category of interest by comparing the first ratio and the second ratio; receiving a query; determining that the query is associated with the category of interest; and selecting the particular information source for satisfaction of the query based on the identification of the particular information source as an expert information source for the category of interest and based on the determination that the query is associated with the category of interest. | 1. A method for enabling a search against an information source deemed to be an expert in a category of interest, comprising: accessing results of searches performed by at least one search engine; determining, among the accessed results, a set of results provided by a particular information source; identifying a category of interest; determining a set of results that are related to the identified category of interest and that also are provided by the particular information source; determining a first ratio of the accessed results provided by the particular information source to the accessed results provided by other information sources; determining a second ratio of search results that are related to the identified category and provided by the particular information source to search results that are related to the identified category and provided by other information sources; identifying the particular information source as an expert information source for the category of interest by comparing the first ratio and the second ratio; receiving a query; determining that the query is associated with the category of interest; and selecting the particular information source for satisfaction of the query based on the identification of the particular information source as an expert information source for the category of interest and based on the determination that the query is associated with the category of interest. 6. The method of claim 1 wherein determining that the query is associated with the category of interest includes: determining a category associated with the received query; and identifying that the category associated with the received query is the category of interest. | 0.852397 |
12. An apparatus comprising: a processor; a memory; and a comparison module stored on the memory, the comparison module being configured to execute computer readable instructions using the processor to: determine a length of a first string, determine a first end segment of the first string, select a second string from a plurality of strings, determine a second end segment of the second string based on the length of the first string, determine that the first end segment matches the second end segment, determine that the first string matches the second string in response to the first end segment matching the second end segment, and link a table reference by the second string to an application in response to the first string matching the second string. | 12. An apparatus comprising: a processor; a memory; and a comparison module stored on the memory, the comparison module being configured to execute computer readable instructions using the processor to: determine a length of a first string, determine a first end segment of the first string, select a second string from a plurality of strings, determine a second end segment of the second string based on the length of the first string, determine that the first end segment matches the second end segment, determine that the first string matches the second string in response to the first end segment matching the second end segment, and link a table reference by the second string to an application in response to the first string matching the second string. 15. The apparatus of claim 12 , wherein a last word of each string of the plurality of strings comprises a null terminated character. | 0.572641 |
76. The computer system for presenting an electronic document of claim 70 wherein the computer program product further comprises program instructions that generate a cognitively parsed file. | 76. The computer system for presenting an electronic document of claim 70 wherein the computer program product further comprises program instructions that generate a cognitively parsed file. 79. The computer system for presenting an electronic document of claim 76 wherein the computer program product further comprises program instructions that assign a color property that is indicative of a part of speech to each word and cognitive cluster. | 0.916667 |
11. An article, comprising: a computer-readable medium having stored thereon instructions executable by a processor of a computing platform to: predict one or more future hot terms according to a classification process, is based, at least in part, on frequency change rates associated with an array of query terms; rank the one or more predicted future hot terms based, at least in part, on probability values determined by the classification process; and create one or more contextual shortcuts associated with the respective one or more predicted future hot terms based, at least in part, on the ranking of the one or more predicted future hot terms, wherein the one or more contextual shortcuts comprise one or more selectable links in an online document to additional online content related to the respective one or more predicted future hot terms. | 11. An article, comprising: a computer-readable medium having stored thereon instructions executable by a processor of a computing platform to: predict one or more future hot terms according to a classification process, is based, at least in part, on frequency change rates associated with an array of query terms; rank the one or more predicted future hot terms based, at least in part, on probability values determined by the classification process; and create one or more contextual shortcuts associated with the respective one or more predicted future hot terms based, at least in part, on the ranking of the one or more predicted future hot terms, wherein the one or more contextual shortcuts comprise one or more selectable links in an online document to additional online content related to the respective one or more predicted future hot terms. 12. The article of claim 11 , wherein the classification process comprises a machine learning process. | 0.575397 |
3. A method, performed by a computing system, for displaying information from one or more linked web pages and without requiring user commitment to downloading the one or more linked web pages, the method comprising: accessing and displaying a current web page that includes a displayed and selectable link to a corresponding linked web page; determining the displayed link is referenced within a stored link list that is accessible to the computing system, wherein the stored link list includes, for each link referenced within the link list, a web page address and summary information corresponding to a web page associated with each link, respectively; accessing the summary information associated with the corresponding linked web page, wherein the summary information is configured to be displayed in response to a cursor hovering over the displayed link; receiving user input that causes the cursor to hover over the displayed link; and in response to receiving the user input that causes the cursor to hover over the displayed link, displaying the summary information within an informational region that is displayed simultaneously with the display of the current web page, wherein the displayed summary information includes paragraph headings extracted from the linked reference corresponding to the displayed link and prior to receipt of the user input causing the cursor to hover over the displayed link, and which paragraph headings are stored in the summary information for the displayed link, wherein displaying the summary information includes displaying up to a predefined maximum number of paragraph headings from the summary data. | 3. A method, performed by a computing system, for displaying information from one or more linked web pages and without requiring user commitment to downloading the one or more linked web pages, the method comprising: accessing and displaying a current web page that includes a displayed and selectable link to a corresponding linked web page; determining the displayed link is referenced within a stored link list that is accessible to the computing system, wherein the stored link list includes, for each link referenced within the link list, a web page address and summary information corresponding to a web page associated with each link, respectively; accessing the summary information associated with the corresponding linked web page, wherein the summary information is configured to be displayed in response to a cursor hovering over the displayed link; receiving user input that causes the cursor to hover over the displayed link; and in response to receiving the user input that causes the cursor to hover over the displayed link, displaying the summary information within an informational region that is displayed simultaneously with the display of the current web page, wherein the displayed summary information includes paragraph headings extracted from the linked reference corresponding to the displayed link and prior to receipt of the user input causing the cursor to hover over the displayed link, and which paragraph headings are stored in the summary information for the displayed link, wherein displaying the summary information includes displaying up to a predefined maximum number of paragraph headings from the summary data. 17. A method as recited in claim 3 , wherein determining the displayed link is referenced within a stored link list includes first determining that the displayed link is not referenced within a stored link list and then referencing the displayed link within the stored link list with the web page address and web page summary information corresponding to the web page associated the displayed link. | 0.662504 |
12. A system comprising: a policy generator adapted to generate a security policy defining at least one protected element contained within a portion of a file, said protected element comprising at least one of a group composed of a keyword; a file name extension; a link to a protected object, a filename and a metadata element, and a disposition action for the file containing said protected element, said protected element containing sensitive information; a file scanner operable and executed on a processor of a remote device and adapted to: scan a portion of file system that is not currently subjected to the security policy for said at least one protected element in a portion of a file to find a first file, said first file comprising both said at least one protected element and at least one unprotected element said protected element within the file having been previously subjected to the security policy, but due to actions performed by a user no longer subjected to the security policy; apply said security policy to said first file, and perform said disposition action on said first file. | 12. A system comprising: a policy generator adapted to generate a security policy defining at least one protected element contained within a portion of a file, said protected element comprising at least one of a group composed of a keyword; a file name extension; a link to a protected object, a filename and a metadata element, and a disposition action for the file containing said protected element, said protected element containing sensitive information; a file scanner operable and executed on a processor of a remote device and adapted to: scan a portion of file system that is not currently subjected to the security policy for said at least one protected element in a portion of a file to find a first file, said first file comprising both said at least one protected element and at least one unprotected element said protected element within the file having been previously subjected to the security policy, but due to actions performed by a user no longer subjected to the security policy; apply said security policy to said first file, and perform said disposition action on said first file. 14. The system of claim 12 , said disposition action comprising at least one of a group composed of: encrypting said file; deleting said file; applying rights management to said file; modifying metadata for said file; and applying security descriptors to said file. | 0.553824 |
9. A non-transitory computer readable medium having stored thereon instructions managing client defined response requirements in a domain name system query comprising machine executable code which when executed by at least one processor, causes the processor to: determine when a DNS request to resolve a hostname comprises a domain name with a value indicating a type of internet protocol version; truncate the internet protocol version value from the DNS request when the domain name and the internet protocol version value is present and prior to querying at least one of a plurality of servers for an internet protocol address associated with the DNS request; receive the internet protocol address from the at least one of a plurality of servers; determine when a format of the received internet protocol address conforms to one or more policies; and perform one or more actions based on the determination of the conformance of the received internet protocol address. | 9. A non-transitory computer readable medium having stored thereon instructions managing client defined response requirements in a domain name system query comprising machine executable code which when executed by at least one processor, causes the processor to: determine when a DNS request to resolve a hostname comprises a domain name with a value indicating a type of internet protocol version; truncate the internet protocol version value from the DNS request when the domain name and the internet protocol version value is present and prior to querying at least one of a plurality of servers for an internet protocol address associated with the DNS request; receive the internet protocol address from the at least one of a plurality of servers; determine when a format of the received internet protocol address conforms to one or more policies; and perform one or more actions based on the determination of the conformance of the received internet protocol address. 11. The medium as set forth in claim 9 wherein the determining the received query to resolve the hostname further comprises: determine when a querying client is present within a pre-defined list when the domain name with the value indicating the type of internet protocol version is determined to be absent in the received query; and append a pre-defined value indicating a type of internet protocol version when the querying client computing device is determined to be present in the pre-defined list. | 0.582808 |
9. The apparatus according to claim 8 , further comprising: a storage unit for storing the transmitted and received first and second instant messages with semantic tags in a message log; the input unit further for selecting a semantic tag in a visual topic structural diagram; and a filter unit for filtering from the message log the instant message(s) associated with the selected semantic tag. | 9. The apparatus according to claim 8 , further comprising: a storage unit for storing the transmitted and received first and second instant messages with semantic tags in a message log; the input unit further for selecting a semantic tag in a visual topic structural diagram; and a filter unit for filtering from the message log the instant message(s) associated with the selected semantic tag. 10. The apparatus according to claim 9 , said display unit further displays said filtered instant messages in a separate display region. | 0.894643 |
12. A method for operating a memory device, the memory device including an array of memory cells arranged in rows and columns, each row of memory cells configured to store a memory word, each memory word including at least one first word and at least one second word, comprising: providing to a configurable port of the memory device a memory word to be written to a selected row of memory cells; and selectively configuring the configurable port, in response to a first configuration command, to disable writing of the at least one first word to the selected row and to enable writing of the at least one second word to the selected row. | 12. A method for operating a memory device, the memory device including an array of memory cells arranged in rows and columns, each row of memory cells configured to store a memory word, each memory word including at least one first word and at least one second word, comprising: providing to a configurable port of the memory device a memory word to be written to a selected row of memory cells; and selectively configuring the configurable port, in response to a first configuration command, to disable writing of the at least one first word to the selected row and to enable writing of the at least one second word to the selected row. 13. A method for operating a memory device as defined in claim 12 , further comprising selectively configuring the configurable port, in response to a second configuration command, to disable writing of the at least one second word to the selected row and to enable writing of the at least one first word to the selected row. | 0.828502 |
9. The method according to claim 1 , further comprising calculating a reliability grade based on quality of voice segment, significance of emotional arousal decision, and consistency of specific segment results with results of previous speech segments. | 9. The method according to claim 1 , further comprising calculating a reliability grade based on quality of voice segment, significance of emotional arousal decision, and consistency of specific segment results with results of previous speech segments. 10. The method according to claim 9 , wherein said quality of voice segment is determined, based on noise level, size of sampled data, and quality of sampled data. | 0.958313 |
20. The system of claim 12 , wherein the processor is further configured to provide an input interface to receive input from a user to manage the set of test operations. | 20. The system of claim 12 , wherein the processor is further configured to provide an input interface to receive input from a user to manage the set of test operations. 21. The system of claim 20 , wherein the input interface comprises at least one of a command line interface or a graphical user interface. | 0.946449 |
8. The method of claim 7 further comprising: for each of the plurality of RWEs, determining a relationship between that RWE and the second RWE based on the retrieved social data, spatial data, temporal data and logical data; and generating that RWE's probability based on the relationship between that RWE and the second RWE. | 8. The method of claim 7 further comprising: for each of the plurality of RWEs, determining a relationship between that RWE and the second RWE based on the retrieved social data, spatial data, temporal data and logical data; and generating that RWE's probability based on the relationship between that RWE and the second RWE. 9. The method of claim 8 , further comprising: assigning each relationship a relative weight; and generating each RWE's probability based at least in part on the relative weight assigned to the relationship between that RWE and the second RWE. | 0.850463 |
17. A computer storage medium encoding a computer program of instructions for executing a computer implemented method for creating a color template for a document, the method comprising: receiving at least one color for the document; constraining at least one document parameter to the at least one color, to generate at least one constrained color parameter; comparing the at least one constrained color parameter to one or more attributes of one or more example color templates in a template example library; automatically selecting one or more example color templates based on the comparison; receiving a selection of one of the one or more example color templates; automatically applying the selected example color template to the constrained color parameters to extrapolate one or more other colors for unset document parameters; and providing the selected example color template based on the received colors and the extrapolated colors. | 17. A computer storage medium encoding a computer program of instructions for executing a computer implemented method for creating a color template for a document, the method comprising: receiving at least one color for the document; constraining at least one document parameter to the at least one color, to generate at least one constrained color parameter; comparing the at least one constrained color parameter to one or more attributes of one or more example color templates in a template example library; automatically selecting one or more example color templates based on the comparison; receiving a selection of one of the one or more example color templates; automatically applying the selected example color template to the constrained color parameters to extrapolate one or more other colors for unset document parameters; and providing the selected example color template based on the received colors and the extrapolated colors. 18. A computer storage medium defined in claim 17 , wherein the constrained color parameter is one of a color setting or a relationship between two color settings. | 0.507071 |
23. A computer program product for managing data stored in an electronic device, the computer program product comprising: a computer readable storage medium having computer readable program code embodied in the medium, the computer readable program code comprising: computer readable program code configured to electronically identify a user input written on a display of the electronic device as a written user direction to transfer data displayed on the electronic device, the written user input defining at least one alphanumeric character; computer readable program code configured to determine a desired memory storage location for the data displayed on the electronic device responsive to the written user direction, wherein the desired memory storage location corresponds to the alphanumeric character defined by the written user input; and computer readable program code configured to transfer the data displayed on the electronic device to the desired memory storage location responsive to the determination. | 23. A computer program product for managing data stored in an electronic device, the computer program product comprising: a computer readable storage medium having computer readable program code embodied in the medium, the computer readable program code comprising: computer readable program code configured to electronically identify a user input written on a display of the electronic device as a written user direction to transfer data displayed on the electronic device, the written user input defining at least one alphanumeric character; computer readable program code configured to determine a desired memory storage location for the data displayed on the electronic device responsive to the written user direction, wherein the desired memory storage location corresponds to the alphanumeric character defined by the written user input; and computer readable program code configured to transfer the data displayed on the electronic device to the desired memory storage location responsive to the determination. 25. The computer program product of claim 23 , further comprising: computer readable program code configured to receive the at least one alphanumeric character and/or symbol that is defined by moving a cursor displayed on the electronic device using a mouse, trackball, and/or joystick. | 0.581738 |
15. A computer program product for determining and displaying relationships in a social network, the computer program product comprising: one or more computer-readable storage devices and program instructions, stored on at least one of the one or more storage devices, the program instructions comprising: program instructions to identify, based on a list of types of identified terms that are searchable within a social networking application, within content displayed to a user, one or more terms within displayed application window text areas of at least two different types of computer program applications; program instructions to visually distinguish the identified term in the displayed application window text areas; program instructions to transmit, for each identified term, the identified term to one or more servers executing a social networking application; program instructions to, for each identified term, receive from the one or more servers a list of people that correspond to the identified term; program instructions to direct a display device, for each identified term, to display the list of people that correspond to the identified term; program instructions to direct a display device to display a mapping clipboard program graphical user interface; program instructions to receive from the user a selection of a mapping clipboard from a plurality of mapping clipboards program instructions to add, for each identified term, in response to user input, an identification of a person from the list of people to the mapping clipboard; and program instructions to direct the display device to display a graph that indicates how the person and other people identified in the mapping clipboard are connected to each other in the social networking application, wherein a connection represents one of a friend, relative, colleague, present co-worker, former co-worker, or classmate. | 15. A computer program product for determining and displaying relationships in a social network, the computer program product comprising: one or more computer-readable storage devices and program instructions, stored on at least one of the one or more storage devices, the program instructions comprising: program instructions to identify, based on a list of types of identified terms that are searchable within a social networking application, within content displayed to a user, one or more terms within displayed application window text areas of at least two different types of computer program applications; program instructions to visually distinguish the identified term in the displayed application window text areas; program instructions to transmit, for each identified term, the identified term to one or more servers executing a social networking application; program instructions to, for each identified term, receive from the one or more servers a list of people that correspond to the identified term; program instructions to direct a display device, for each identified term, to display the list of people that correspond to the identified term; program instructions to direct a display device to display a mapping clipboard program graphical user interface; program instructions to receive from the user a selection of a mapping clipboard from a plurality of mapping clipboards program instructions to add, for each identified term, in response to user input, an identification of a person from the list of people to the mapping clipboard; and program instructions to direct the display device to display a graph that indicates how the person and other people identified in the mapping clipboard are connected to each other in the social networking application, wherein a connection represents one of a friend, relative, colleague, present co-worker, former co-worker, or classmate. 17. The computer program product of claim 15 further comprising program instructions to receive from the user a selection of the social networking application from a plurality of social networking applications. | 0.564268 |
19. A non-transitory computer storage medium comprising a browser component configured to execute a process on one or more computing devices, the process comprising: providing a first user interface option to access content associated with an opinion that differs in classification, as one of a positive opinion, a neutral opinion, or a negative opinion, from a classification of a first opinion, of a first content page displayed by the browser component, regarding a topic of the first content page, wherein the first opinion is classified as one of a positive opinion, a neutral opinion, or a negative opinion regarding the topic, wherein a network-accessible computer system stores opinion data classifying the topics of a plurality of content pages from a plurality content sources; in response to activation of the first user interface option, receiving, from the network-accessible computer system, response data comprising a second content page associated with a second opinion regarding the topic of the first content page, wherein the network-accessible computer system transmits the second content page upon identifying that the second opinion differs in classification from the first opinion as one of a positive opinion, a neutral opinion, or a negative opinion; and providing a second user interface option to submit feedback, to the network-accessible computer system, regarding at least one of the first opinion or the second opinion, wherein the network-accessible computer system uses the feedback to classify at least one of the first opinion or the second opinion. | 19. A non-transitory computer storage medium comprising a browser component configured to execute a process on one or more computing devices, the process comprising: providing a first user interface option to access content associated with an opinion that differs in classification, as one of a positive opinion, a neutral opinion, or a negative opinion, from a classification of a first opinion, of a first content page displayed by the browser component, regarding a topic of the first content page, wherein the first opinion is classified as one of a positive opinion, a neutral opinion, or a negative opinion regarding the topic, wherein a network-accessible computer system stores opinion data classifying the topics of a plurality of content pages from a plurality content sources; in response to activation of the first user interface option, receiving, from the network-accessible computer system, response data comprising a second content page associated with a second opinion regarding the topic of the first content page, wherein the network-accessible computer system transmits the second content page upon identifying that the second opinion differs in classification from the first opinion as one of a positive opinion, a neutral opinion, or a negative opinion; and providing a second user interface option to submit feedback, to the network-accessible computer system, regarding at least one of the first opinion or the second opinion, wherein the network-accessible computer system uses the feedback to classify at least one of the first opinion or the second opinion. 21. The non-transitory computer storage medium of claim 19 , the process further comprising: causing, in response to receipt of the response data, presentation of at least one of: at least a portion of the first content page, a summary of at least a portion of the first content page, or a user interface option to retrieve the first content page. | 0.624739 |
72. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for displaying at least one window in connection with a website; computer code for displaying, utilizing the at least one window, a stock-related field; computer code for receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; computer code for dynamically determining, after the user types each character in the received text, whether the characters typed so far match any of n text strings in one of a plurality of n-tuples including n>l text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; computer code for indicating to the user that a match has been found, utilizing the at least one window, if it is determined that the characters typed so far match any of the n text strings in the one of the plurality of n-tuples; computer code for displaying, utilizing the at least one window, a first set of representations of a first set of hyperlinks; computer code for receiving first input from the user indicating a selection of one of the first set of hyperlink representations; computer code for displaying a second set of representations of a second set of hyperlinks, utilizing the at least one window, in response to receiving the first input; computer code for receiving second input from the user indicating a selection of one of the second set of hyperlink representations; and computer code for navigating to a destination specified by the selected one of the second set of hyperlink representations, in response to receiving the second input. | 72. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for displaying at least one window in connection with a website; computer code for displaying, utilizing the at least one window, a stock-related field; computer code for receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; computer code for dynamically determining, after the user types each character in the received text, whether the characters typed so far match any of n text strings in one of a plurality of n-tuples including n>l text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; computer code for indicating to the user that a match has been found, utilizing the at least one window, if it is determined that the characters typed so far match any of the n text strings in the one of the plurality of n-tuples; computer code for displaying, utilizing the at least one window, a first set of representations of a first set of hyperlinks; computer code for receiving first input from the user indicating a selection of one of the first set of hyperlink representations; computer code for displaying a second set of representations of a second set of hyperlinks, utilizing the at least one window, in response to receiving the first input; computer code for receiving second input from the user indicating a selection of one of the second set of hyperlink representations; and computer code for navigating to a destination specified by the selected one of the second set of hyperlink representations, in response to receiving the second input. 129. The computer program product of claim 72 , wherein the computer program product is configured such that the dynamically determining comprises determining that the characters typed so far match a first one of the n text strings in the one of the plurality of n-tuples, and that the characters typed so far do not match a second one of the n text strings in the one of the plurality of n-tuples. | 0.531939 |
1. A system for custom-fitting a service solution to consumer requirements, comprising: a memory and a processor coupled to the memory; a service consumer module, executed on the processor, and including a conversational interface configured to interact with a consumer to acquire a request for the service solution, and a service specification mining module; a services marketplace module, executed on the processor, and including a service knowledge base having a collection of service knowledge representation items, wherein: the service specification mining module is configured to interact with the conversational interface and the service knowledge base; the service specification mining module is configure to issue a query to the service knowledge base, to obtain a set of the service knowledge representation items, to analyze each service knowledge representation item and to determine whether a custom-fit service solution can be developed; the conversational interface is configured to compute the query to be issued to the service knowledge base based on the request for the service solution, and configured to forward the query to the service specification mining module; and the service specification mining module is configured to synthesize the custom-fit service solution, to transmit the custom-fit service solution to the conversational interface, and to determine that the request cannot be fulfilled automatically by concluding that each parameter of every service knowledge representation item of the set of the service knowledge representation items is an unpluggable parameter; and a service provider module, executed on the processor, and including a service assetization module configured to assetize the custom-fit service solution, and to provide the custom-fit service solution to the service knowledge base. | 1. A system for custom-fitting a service solution to consumer requirements, comprising: a memory and a processor coupled to the memory; a service consumer module, executed on the processor, and including a conversational interface configured to interact with a consumer to acquire a request for the service solution, and a service specification mining module; a services marketplace module, executed on the processor, and including a service knowledge base having a collection of service knowledge representation items, wherein: the service specification mining module is configured to interact with the conversational interface and the service knowledge base; the service specification mining module is configure to issue a query to the service knowledge base, to obtain a set of the service knowledge representation items, to analyze each service knowledge representation item and to determine whether a custom-fit service solution can be developed; the conversational interface is configured to compute the query to be issued to the service knowledge base based on the request for the service solution, and configured to forward the query to the service specification mining module; and the service specification mining module is configured to synthesize the custom-fit service solution, to transmit the custom-fit service solution to the conversational interface, and to determine that the request cannot be fulfilled automatically by concluding that each parameter of every service knowledge representation item of the set of the service knowledge representation items is an unpluggable parameter; and a service provider module, executed on the processor, and including a service assetization module configured to assetize the custom-fit service solution, and to provide the custom-fit service solution to the service knowledge base. 14. The system of claim 1 , wherein the service specification mining module is configured to engage a human consultant based upon the request not being able to be filled automatically. | 0.553546 |
1. A method comprising: converting (i) a multi-way theta join query on MapReduce into a multi-way interval join query on MapReduce, and (ii) one or more items of data associated with the multi-way theta join query to one or more items of interval data; executing the multi-way interval join query on the one or more items of interval data via MapReduce to generate an output, wherein the output comprises a set of multiple responses to the multi-way interval join query; and processing the output to generate a solution to the multi-way theta join query, wherein said processing comprises discarding each response from the set that does not satisfy the multi-way theta join query; wherein said converting, said executing, and said processing are carried out by at least one computing device. | 1. A method comprising: converting (i) a multi-way theta join query on MapReduce into a multi-way interval join query on MapReduce, and (ii) one or more items of data associated with the multi-way theta join query to one or more items of interval data; executing the multi-way interval join query on the one or more items of interval data via MapReduce to generate an output, wherein the output comprises a set of multiple responses to the multi-way interval join query; and processing the output to generate a solution to the multi-way theta join query, wherein said processing comprises discarding each response from the set that does not satisfy the multi-way theta join query; wherein said converting, said executing, and said processing are carried out by at least one computing device. 6. The method of claim 1 , wherein said converting comprises converting the multi-way theta join query into multiple multi-way interval join queries. | 0.551778 |
1. A computer-implemented method, comprising: receiving, at a computing device executing a communication application, a received textual message from a sender user, the received textual message including text content; determining, at the computing device, an insertion point for the received textual message based on the text content, the insertion point corresponding to a particular location of a plurality of possible locations in a graphical user interface of the communication application, each of the plurality of possible locations corresponding to a position in the graphical user interface subsequent to a preceding textual message; and displaying, at the computing device, the received textual message in the graphical user interface of the communication application at the determined insertion point, wherein: the received textual message is received by the computing device at a first time; and when (i) the computing device is displaying the graphical user interface at the first time, and (ii) the determined insertion point corresponds to a re-ordered position other than a most recent textual message position, the displaying the received textual message in the graphical user interface at the determined insertion point comprises providing an active indication of the received textual message being inserted at the insertion point. | 1. A computer-implemented method, comprising: receiving, at a computing device executing a communication application, a received textual message from a sender user, the received textual message including text content; determining, at the computing device, an insertion point for the received textual message based on the text content, the insertion point corresponding to a particular location of a plurality of possible locations in a graphical user interface of the communication application, each of the plurality of possible locations corresponding to a position in the graphical user interface subsequent to a preceding textual message; and displaying, at the computing device, the received textual message in the graphical user interface of the communication application at the determined insertion point, wherein: the received textual message is received by the computing device at a first time; and when (i) the computing device is displaying the graphical user interface at the first time, and (ii) the determined insertion point corresponds to a re-ordered position other than a most recent textual message position, the displaying the received textual message in the graphical user interface at the determined insertion point comprises providing an active indication of the received textual message being inserted at the insertion point. 7. The computer-implemented method of claim 1 , wherein the active indication is a distinctive marking that that differentiates the received textual message from other textual messages in the graphical user interface. | 0.673475 |
28. A system comprising a processor and memory for generating and updating information of connections between and among nodes of social network, comprising: a node database maintaining a plurality of nodes of the social network or a social graph; a connection database maintaining a plurality of connections in the social network or the social graph, wherein each connection represents the connection between two or more nodes in the social network or the social graph, the connection database further maintaining information about the plurality of connections; a server providing an interface for users of the social network or social graph to share and post content items in one or more communication channels of the social network or social graph, wherein the server receives the content item from the user via the interface, wherein the content item comprises selected content and instructions for selecting a referenced node, wherein the instructions for selecting the referenced node comprise: determining which of the nodes of the social network or the social graph match the referenced node; providing the user with a list of referenced nodes that matched any of the nodes of the social network or social graph; receiving from the user a selected referenced node from the list of nodes, the selected referenced node being referenced in the content item; and, presenting in the content item a link to the selected referenced node of the social network or the social graph, wherein both node database and the connection database are partial components of a universal database, wherein updates to either the node database or the connection database are synchronized in the universal database. | 28. A system comprising a processor and memory for generating and updating information of connections between and among nodes of social network, comprising: a node database maintaining a plurality of nodes of the social network or a social graph; a connection database maintaining a plurality of connections in the social network or the social graph, wherein each connection represents the connection between two or more nodes in the social network or the social graph, the connection database further maintaining information about the plurality of connections; a server providing an interface for users of the social network or social graph to share and post content items in one or more communication channels of the social network or social graph, wherein the server receives the content item from the user via the interface, wherein the content item comprises selected content and instructions for selecting a referenced node, wherein the instructions for selecting the referenced node comprise: determining which of the nodes of the social network or the social graph match the referenced node; providing the user with a list of referenced nodes that matched any of the nodes of the social network or social graph; receiving from the user a selected referenced node from the list of nodes, the selected referenced node being referenced in the content item; and, presenting in the content item a link to the selected referenced node of the social network or the social graph, wherein both node database and the connection database are partial components of a universal database, wherein updates to either the node database or the connection database are synchronized in the universal database. 40. The system according to claim 28 , wherein the interface posts the content items to the communication channel comprising a message stream. | 0.670793 |
21. The method of claim 20 , wherein the setting mode comprises selection information about at least one of a prefix index of the consonant/vowel unit, a prefix index of the syllable unit, and a suffix index of the syllable unit, and wherein determining the at least one autocomplete recommended word comprises determining the at least one autocomplete recommended word from a recommended word index database using the selected index. | 21. The method of claim 20 , wherein the setting mode comprises selection information about at least one of a prefix index of the consonant/vowel unit, a prefix index of the syllable unit, and a suffix index of the syllable unit, and wherein determining the at least one autocomplete recommended word comprises determining the at least one autocomplete recommended word from a recommended word index database using the selected index. 23. The method of claim 21 , wherein indexing the at least one converted word comprises indexing the at least one converted word according to the prefix of the syllable unit, in response to a determination that the setting mode is the prefix index of the syllable unit. | 0.878453 |
1. A visualization system that generates a customized visualization in an industrial automation environment, comprising: a processor, communicatively coupled to a memory, and configured to execute computer-executable components, the computer-executable components comprising: a context component configured to capture context information regarding a first data visualization, wherein the first data visualization presents data received from at least one device of the industrial automation environment and the captured context information relates to interaction with the first data visualization during presentment of the received data by the first data visualization; and a visualization component configured to: determine, based upon the captured context information, an inability of the first data visualization to present the received data in accord with the captured context information; and a second data visualization, wherein the second data visualization facilitates presentation of the received data in accord with the captured context information; and dynamically replace, in response to the second data visualization being determined, the first visualization with the second visualization. | 1. A visualization system that generates a customized visualization in an industrial automation environment, comprising: a processor, communicatively coupled to a memory, and configured to execute computer-executable components, the computer-executable components comprising: a context component configured to capture context information regarding a first data visualization, wherein the first data visualization presents data received from at least one device of the industrial automation environment and the captured context information relates to interaction with the first data visualization during presentment of the received data by the first data visualization; and a visualization component configured to: determine, based upon the captured context information, an inability of the first data visualization to present the received data in accord with the captured context information; and a second data visualization, wherein the second data visualization facilitates presentation of the received data in accord with the captured context information; and dynamically replace, in response to the second data visualization being determined, the first visualization with the second visualization. 7. The visualization system of claim 1 , wherein the captured context information is a function of an identity of an entity, a role, a logical location, a physical location, a current activity, a similar interaction with an automation device, a previous interaction with an automation device, or context data pertaining to at least one automation device including at least one of a control system, a device or associated equipment. | 0.5 |
6. A computer-implemented method comprising: receiving a query prefix from a user device; determining a user identifier based on the user device; identifying an associated user category that is associated with the user identifier; locating a first node representing the query prefix in a query graph, wherein: the query graph is a directed graph that comprises a plurality of nodes, each node representing a query, a query prefix, or both, wherein each node representing a query prefix has a directed edge that directs to one or more child nodes; and each node has one or more user category specific frequency measures, each user category specific frequency measure being based on a number of times that the query that is represented by the node was received from users that belong to the associated user category; locating descendant nodes of the first node, each descendent node being a node that represents a query; ranking the queries represented by the located nodes based on the user category specific frequency measure associated with the identified user category; and sending the ranked queries to the user device. | 6. A computer-implemented method comprising: receiving a query prefix from a user device; determining a user identifier based on the user device; identifying an associated user category that is associated with the user identifier; locating a first node representing the query prefix in a query graph, wherein: the query graph is a directed graph that comprises a plurality of nodes, each node representing a query, a query prefix, or both, wherein each node representing a query prefix has a directed edge that directs to one or more child nodes; and each node has one or more user category specific frequency measures, each user category specific frequency measure being based on a number of times that the query that is represented by the node was received from users that belong to the associated user category; locating descendant nodes of the first node, each descendent node being a node that represents a query; ranking the queries represented by the located nodes based on the user category specific frequency measure associated with the identified user category; and sending the ranked queries to the user device. 9. The method of claim 6 , wherein the query prefix is received from a browser executing at the user device. | 0.76601 |
1. A method for establishing mapping rules for mapping user codes (MR payer IDs) to prescription transaction data records, wherein each data record comprises at least a first, a second and a third data fields, the method comprising: analyzing a set of previously mapped data records that have been assigned MR payer IDs based on at least the values of the third data fields; determining unique combinations of first and second data field values present in the set of data records; for each unique combination of the first and second data field values, determining a MR payer ID that is frequently assigned to the corresponding data records, wherein the frequency of assignment is above a cutoff limit value; establishing a mapping rule that assigns the frequently mapped MR payer ID to all data records having the unique combination of the first and second data field values; Wherein a mapping rule is assigned only for the unique combinations of the first and second data field values that occur with a frequency greater than a cutoff limit. | 1. A method for establishing mapping rules for mapping user codes (MR payer IDs) to prescription transaction data records, wherein each data record comprises at least a first, a second and a third data fields, the method comprising: analyzing a set of previously mapped data records that have been assigned MR payer IDs based on at least the values of the third data fields; determining unique combinations of first and second data field values present in the set of data records; for each unique combination of the first and second data field values, determining a MR payer ID that is frequently assigned to the corresponding data records, wherein the frequency of assignment is above a cutoff limit value; establishing a mapping rule that assigns the frequently mapped MR payer ID to all data records having the unique combination of the first and second data field values; Wherein a mapping rule is assigned only for the unique combinations of the first and second data field values that occur with a frequency greater than a cutoff limit. 3. A computer data processing arrangement comprising software applications for carrying out the steps of claim 1 . | 0.767583 |
1. A method performed by one or more processing devices comprising: receiving, from a member of a social network, an entry in a display field along with an indication that the entry is for a post; after receiving the entry and the indication, identifying content by performing a search using a search query comprising at least one keyword included in the entry and information about the member of the social network, the information comprising social connections of the member; determining relevance scores for the content identified, a relevance score comprising a measure of how closely content matches the search query; obtaining tags corresponding to identified content having relevance scores that indicate greater relevance to the search query than other content; ranking the tags to produce ranked tags based at least on some of the information about the member of the social network; outputting the ranked tags as suggestions to include with the display field upon selection; and augmenting the entry by associating, with the entry, a tag selected for display in the display field. | 1. A method performed by one or more processing devices comprising: receiving, from a member of a social network, an entry in a display field along with an indication that the entry is for a post; after receiving the entry and the indication, identifying content by performing a search using a search query comprising at least one keyword included in the entry and information about the member of the social network, the information comprising social connections of the member; determining relevance scores for the content identified, a relevance score comprising a measure of how closely content matches the search query; obtaining tags corresponding to identified content having relevance scores that indicate greater relevance to the search query than other content; ranking the tags to produce ranked tags based at least on some of the information about the member of the social network; outputting the ranked tags as suggestions to include with the display field upon selection; and augmenting the entry by associating, with the entry, a tag selected for display in the display field. 6. The method of claim 1 , wherein the information comprises a language of the member. | 0.556881 |
17. The method recited in claim 15 , further comprising: selecting, by the processor of the communication device, a plurality of voice pattern-to-emotion definitions based on a language for the voice communication, a dialect for the voice communication and a speaker for the voice communication; and selecting, by the processor of the communication device, a plurality of text-to-emotion definitions based on a language for the voice communication, a dialect for the voice communication and a speaker for the voice communication. | 17. The method recited in claim 15 , further comprising: selecting, by the processor of the communication device, a plurality of voice pattern-to-emotion definitions based on a language for the voice communication, a dialect for the voice communication and a speaker for the voice communication; and selecting, by the processor of the communication device, a plurality of text-to-emotion definitions based on a language for the voice communication, a dialect for the voice communication and a speaker for the voice communication. 18. The method recited in claim 17 , wherein the voice pattern-to-emotion definitions comprise voice patterns for one of pitch, tone, cadence and amplitude. | 0.729908 |
11. A system comprising: one or more processors; memory; and machine-readable instructions stored in the memory, that upon execution by the one or more processors cause the system to carry out operations comprising: training a neural network implemented by the system to map one or more training-time sequences of phonetic-context descriptors received by the neural network into training-time predicted feature vectors that correspond to acoustic properties of predefined speech waveforms, wherein the one or more training-time sequences of phonetic-context descriptors correspond to phonetic transcriptions of training-time text strings, and the training-time text strings correspond to written transcriptions of speech carried in the predefined speech waveforms, receiving, by a text analysis module implemented by the system, a run-time text string, processing the received run-time text string with the text analysis module to generate a run-time sequence of phonetic-context descriptors that corresponds to a phonetic transcription of the run-time text string, wherein each phonetic-context descriptor of the run-time sequence includes a respective label identifying a phonetic speech unit of a plurality of phonetic speech units, data indicating phonetic context of the identified phonetic speech unit, and data indicating time duration of the identified phonetic speech unit, processing the run-time sequence of the phonetic-context descriptors with the trained neural network in a corresponding sequence of neural network time steps to generate one or more run-time predicted feature vectors, and processing the one or more run-time predicted feature vectors with a signal generation module to produce and output a run-time speech waveform corresponding to a spoken rendering of the received run-time text string, wherein processing the received run-time text string with the text analysis module to generate the run-time sequence of phonetic-context descriptors comprises: generating a run-time transcription sequence of phonetic speech units that corresponds to the phonetic transcription of the run-time text string; and determining a respective number of consecutive phonetic-context descriptors to generate for each of the phonetic speech units of the run-time transcription sequence. | 11. A system comprising: one or more processors; memory; and machine-readable instructions stored in the memory, that upon execution by the one or more processors cause the system to carry out operations comprising: training a neural network implemented by the system to map one or more training-time sequences of phonetic-context descriptors received by the neural network into training-time predicted feature vectors that correspond to acoustic properties of predefined speech waveforms, wherein the one or more training-time sequences of phonetic-context descriptors correspond to phonetic transcriptions of training-time text strings, and the training-time text strings correspond to written transcriptions of speech carried in the predefined speech waveforms, receiving, by a text analysis module implemented by the system, a run-time text string, processing the received run-time text string with the text analysis module to generate a run-time sequence of phonetic-context descriptors that corresponds to a phonetic transcription of the run-time text string, wherein each phonetic-context descriptor of the run-time sequence includes a respective label identifying a phonetic speech unit of a plurality of phonetic speech units, data indicating phonetic context of the identified phonetic speech unit, and data indicating time duration of the identified phonetic speech unit, processing the run-time sequence of the phonetic-context descriptors with the trained neural network in a corresponding sequence of neural network time steps to generate one or more run-time predicted feature vectors, and processing the one or more run-time predicted feature vectors with a signal generation module to produce and output a run-time speech waveform corresponding to a spoken rendering of the received run-time text string, wherein processing the received run-time text string with the text analysis module to generate the run-time sequence of phonetic-context descriptors comprises: generating a run-time transcription sequence of phonetic speech units that corresponds to the phonetic transcription of the run-time text string; and determining a respective number of consecutive phonetic-context descriptors to generate for each of the phonetic speech units of the run-time transcription sequence. 17. The system of claim 11 , wherein each of the one or more run-time predicted feature vectors corresponds to a respective temporal frame of acoustic data in the run-time speech waveform, and wherein the data indicating time duration of the identified phonetic speech unit comprises a number that specifies how many consecutive temporal frames of acoustic data over which an acoustic rendering of the identified phonetic speech unit in the run-time speech waveform should last. | 0.646608 |
12. A computer readable medium having stored thereon a set of data operable to configure a computer to: a) identify a plurality of relevant phrases in a website, wherein said plurality of relevant phrases comprises a first phrase from a first page from said website and a second phrase from a second page from said website; b) determine a plurality of weights wherein each weight from said plurality of weights corresponds to a relevant phrase from said plurality of relevant phrases and is based at least in part on a relationship between the corresponding relevant phrase and a leaf page from the website; c) using a set of information comprising said plurality of weights and said plurality of relevant phrases, train a grammar to categorize an input according to a class corresponding to the leaf page from the website; and d) store said grammar in a computer memory in a format readable by an interactive voice response system; wherein at least one relevant phrase from the plurality of relevant phrases is a phrase in an ancestor page separated from the leaf page by a number of links, and wherein the relationship between the at least one relevant phrase from the ancestor page comprises the number of links separating the ancestor page from the leaf page. | 12. A computer readable medium having stored thereon a set of data operable to configure a computer to: a) identify a plurality of relevant phrases in a website, wherein said plurality of relevant phrases comprises a first phrase from a first page from said website and a second phrase from a second page from said website; b) determine a plurality of weights wherein each weight from said plurality of weights corresponds to a relevant phrase from said plurality of relevant phrases and is based at least in part on a relationship between the corresponding relevant phrase and a leaf page from the website; c) using a set of information comprising said plurality of weights and said plurality of relevant phrases, train a grammar to categorize an input according to a class corresponding to the leaf page from the website; and d) store said grammar in a computer memory in a format readable by an interactive voice response system; wherein at least one relevant phrase from the plurality of relevant phrases is a phrase in an ancestor page separated from the leaf page by a number of links, and wherein the relationship between the at least one relevant phrase from the ancestor page comprises the number of links separating the ancestor page from the leaf page. 13. The computer readable medium of claim 12 , wherein determining the plurality of weights comprises, for each weight from the plurality of weights, determining a value for that weight which is inversely related to the number of links separating the ancestor page from the home page. | 0.740592 |
21. A non-transitory computer-readable storage medium including instructions for identifying elements, the instructions when executed by a processor of a computing device causing the computing device to: identify a semantic meaning associated with one or more words in an electronic document being displayed on a display of the computing device, the one or more words being located at a specific location of the electronic document; identify an audio file associated with the semantic meaning; determine a gaze direction of a user relative to the display; determine an estimated location on the display corresponding to the gaze direction; determine that the estimated location is within a threshold distance from the specific location of the one or more words; and play the audio file with a volume based at least in part upon the semantic meaning of the one or more words and a determination that the estimated location is within the threshold distance from the specific location of the one or more words. | 21. A non-transitory computer-readable storage medium including instructions for identifying elements, the instructions when executed by a processor of a computing device causing the computing device to: identify a semantic meaning associated with one or more words in an electronic document being displayed on a display of the computing device, the one or more words being located at a specific location of the electronic document; identify an audio file associated with the semantic meaning; determine a gaze direction of a user relative to the display; determine an estimated location on the display corresponding to the gaze direction; determine that the estimated location is within a threshold distance from the specific location of the one or more words; and play the audio file with a volume based at least in part upon the semantic meaning of the one or more words and a determination that the estimated location is within the threshold distance from the specific location of the one or more words. 22. The non-transitory computer-readable storage medium of claim 21 , wherein the instructions when executed cause the computing device to further: receive a type of audio content for the audio file, wherein the audio file is identified from a plurality of audio files corresponding to the type of audio content. | 0.5 |
1. A method implemented by one or more computing devices, the method comprising: receiving input data, the input data comprising linguistic items including: a first set of linguistic items with known intent labels, the known intent labels representing known relations between entities provided by a knowledge resource; and a second set of linguistic items without known intent labels provided by the knowledge resource; determining intents for the linguistic items in the input data to produce intent output information, the determining comprising: when a respective linguistic item corresponds to a member of the first set, deterministically assigning a respective known intent to the respective linguistic item based at least on a respective known intent label associated with the respective linguistic item; and when the respective linguistic item corresponds to a member of the second set, inferring the intent associated with the respective linguistic item based at least on selection log data; and storing the intent output information in a data store, the determining including discovering a new intent for an individual linguistic item of the second set that identifies an individual entity represented in the knowledge resource, the new intent identifying a new relation for the individual entity that is not included in the known relations provided by the knowledge resource, the selection log data reflecting actions of users associated with using various linguistic items with the known intents and with the new intent. | 1. A method implemented by one or more computing devices, the method comprising: receiving input data, the input data comprising linguistic items including: a first set of linguistic items with known intent labels, the known intent labels representing known relations between entities provided by a knowledge resource; and a second set of linguistic items without known intent labels provided by the knowledge resource; determining intents for the linguistic items in the input data to produce intent output information, the determining comprising: when a respective linguistic item corresponds to a member of the first set, deterministically assigning a respective known intent to the respective linguistic item based at least on a respective known intent label associated with the respective linguistic item; and when the respective linguistic item corresponds to a member of the second set, inferring the intent associated with the respective linguistic item based at least on selection log data; and storing the intent output information in a data store, the determining including discovering a new intent for an individual linguistic item of the second set that identifies an individual entity represented in the knowledge resource, the new intent identifying a new relation for the individual entity that is not included in the known relations provided by the knowledge resource, the selection log data reflecting actions of users associated with using various linguistic items with the known intents and with the new intent. 11. The method of claim 1 , wherein said inferring uses a Bayesian hierarchical graphical model, and where the model represents user actions based on a process which involves: drawing an intent based on a distribution of intents, to provide a specified intent; generating one or more entity types, each entity type being drawn according to a distribution of entity types associated with the specified intent; generating one or more context words, each context word being drawn according to a distribution of context words associated with the specified intent; and generating one or more click components, each click component being drawn according to a distribution of click components associated with the specified intent. | 0.5 |
11. The system of claim 8 , wherein each data object is identified by a Uniform Resource Identifier (URI). | 11. The system of claim 8 , wherein each data object is identified by a Uniform Resource Identifier (URI). 12. The system of claim 11 , wherein the URI references a web page. | 0.978531 |
1. A traffic simulator, comprising: a setting portion that, when a vehicle model, which is a model of a vehicle, is virtually driven on a road and traffic conditions are simulated, sets ability information representing driving abilities of a driver of the vehicle model; a storage portion that stores space arrangement data representing an arrangement of the vehicle model in a virtual road space; a searching portion that searches the road space, which is represented by the space arrangement data stored in the storage portion, for cautionary objects that should be heeded by the driver when driving the vehicle model; a selection portion, using a processor, that selects a plurality of cautionary objects recognized by the driver from the cautionary objects found by the searching portion based on the ability information of the driver set by the setting portion, the selection portion selecting, as the cautionary objects recognized by the driver, the cautionary objects found by the searching portion whose required level of experience for driver recognition, represented by a level of experience information associated with each predetermined cautionary object, is less than or equal to a level of driving experience of the driver included in the ability information of the driver; and a determination portion that calculates a plurality of movement ranges of the vehicle mode, based on the plurality of cautionary objects selected by the selection portion, and determines a movement of the vehicle model based on the plurality of movement ranges, wherein: the ability information further includes at least one of information representing an eyesight ability of the driver or information representing a level of concentration ability of the driver; the storage portion further stores, for each predetermined cautionary object, recognition time information representing a time required for the driver to recognize the cautionary object according to at least one of eyesight ability or level of concentration ability; and the selection portion, based on the recognition time information stored in the storage portion, obtains the time required for the driver to recognize the cautionary object found by the searching portion according to at least one of the eyesight ability or the level of concentration ability of the driver set by the setting portion, adds together the obtained required times in a predetermined order of priority or in a random order, and selects as cautionary objects recognized by a driver those cautionary objects which are added within a movement determination time required for the driver to recognize cautionary objects and for the movement of the vehicle model to be determined. | 1. A traffic simulator, comprising: a setting portion that, when a vehicle model, which is a model of a vehicle, is virtually driven on a road and traffic conditions are simulated, sets ability information representing driving abilities of a driver of the vehicle model; a storage portion that stores space arrangement data representing an arrangement of the vehicle model in a virtual road space; a searching portion that searches the road space, which is represented by the space arrangement data stored in the storage portion, for cautionary objects that should be heeded by the driver when driving the vehicle model; a selection portion, using a processor, that selects a plurality of cautionary objects recognized by the driver from the cautionary objects found by the searching portion based on the ability information of the driver set by the setting portion, the selection portion selecting, as the cautionary objects recognized by the driver, the cautionary objects found by the searching portion whose required level of experience for driver recognition, represented by a level of experience information associated with each predetermined cautionary object, is less than or equal to a level of driving experience of the driver included in the ability information of the driver; and a determination portion that calculates a plurality of movement ranges of the vehicle mode, based on the plurality of cautionary objects selected by the selection portion, and determines a movement of the vehicle model based on the plurality of movement ranges, wherein: the ability information further includes at least one of information representing an eyesight ability of the driver or information representing a level of concentration ability of the driver; the storage portion further stores, for each predetermined cautionary object, recognition time information representing a time required for the driver to recognize the cautionary object according to at least one of eyesight ability or level of concentration ability; and the selection portion, based on the recognition time information stored in the storage portion, obtains the time required for the driver to recognize the cautionary object found by the searching portion according to at least one of the eyesight ability or the level of concentration ability of the driver set by the setting portion, adds together the obtained required times in a predetermined order of priority or in a random order, and selects as cautionary objects recognized by a driver those cautionary objects which are added within a movement determination time required for the driver to recognize cautionary objects and for the movement of the vehicle model to be determined. 5. The traffic simulator of claim 1 , wherein: the movement ranges include acceleration/deceleration speed ranges; and the determination portion aggregates the plural acceleration/deceleration speed ranges, and determines a highest acceleration/deceleration speed within the range of a superposed acceleration/deceleration speed range as the movement of the vehicle model. | 0.521813 |
16. The computer-readable medium of claim 12 , wherein sending the user query to the second location is performed only if a predetermined number of slots are filled by terms within the user query. | 16. The computer-readable medium of claim 12 , wherein sending the user query to the second location is performed only if a predetermined number of slots are filled by terms within the user query. 17. The computer-readable medium of claim 16 , further comprising determining a nomatch score, wherein the nomatch score is a percentage of the words in the user query that were not matched against the slot values, and wherein if the nomatch score is above a predetermined nomatch threshold the user query is not sent to the second location. | 0.801798 |
20. A method, performed by one or more server devices, the method comprising: storing, in a memory of the one or more server devices, a plurality of query-document associations, each query-document association including a one-to-one pairing of an issued search query and a stored search document that was retrieved based on the issued search query; receiving, by one or more processors of the one or more server devices, a search query from a client device; identifying, by one or more processors of the one or more server devices, a set of search result documents using the received search query; identifying, by one or more processors of the one or more server devices, search result documents in the identified set of search result documents that match stored search documents; forming, by one or more processors of the one or more server devices, a plurality of clusters of the search documents, of the stored plurality of query-document associations, that match the search result documents; selecting, by one or more processors of the one or more server devices, at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a centroid for each of the selected at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a score for each unique issued search query associated with a document in the selected at least one of a plurality of clusters based on the computed centroid; identifying, by one or more processors of the one or more server devices, for a stored search document of the selected at least one of the plurality of clusters, a query-document association in the plurality of query-document associations based on the computed scores; formulating, by one or more processors of the one or more server devices, a search query refinement suggestion for the received search query based on an issued search query of the identified query-document association; and sorting, by one or more processors of the one or more sever devices, the formulated search query refinement suggestion among a group of search query refinement suggestions. | 20. A method, performed by one or more server devices, the method comprising: storing, in a memory of the one or more server devices, a plurality of query-document associations, each query-document association including a one-to-one pairing of an issued search query and a stored search document that was retrieved based on the issued search query; receiving, by one or more processors of the one or more server devices, a search query from a client device; identifying, by one or more processors of the one or more server devices, a set of search result documents using the received search query; identifying, by one or more processors of the one or more server devices, search result documents in the identified set of search result documents that match stored search documents; forming, by one or more processors of the one or more server devices, a plurality of clusters of the search documents, of the stored plurality of query-document associations, that match the search result documents; selecting, by one or more processors of the one or more server devices, at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a centroid for each of the selected at least one of the plurality of clusters; computing, by one or more processors of the one or more server devices, a score for each unique issued search query associated with a document in the selected at least one of a plurality of clusters based on the computed centroid; identifying, by one or more processors of the one or more server devices, for a stored search document of the selected at least one of the plurality of clusters, a query-document association in the plurality of query-document associations based on the computed scores; formulating, by one or more processors of the one or more server devices, a search query refinement suggestion for the received search query based on an issued search query of the identified query-document association; and sorting, by one or more processors of the one or more sever devices, the formulated search query refinement suggestion among a group of search query refinement suggestions. 28. The method of claim 20 , where the formulating the search query refinement suggestion further comprises: designating a name to each of the selected clusters based on the computed scores of the unique search queries of the selected clusters. | 0.535655 |
16. The computer implemented method of claim 12 , wherein analyzing the content further comprises: determining at least one similar web page to the target web page; revising the content of the target web page by supplementing it with the content of the similar web page; and analyzing the revised content of the target web page to identify a set of one or more topics. | 16. The computer implemented method of claim 12 , wherein analyzing the content further comprises: determining at least one similar web page to the target web page; revising the content of the target web page by supplementing it with the content of the similar web page; and analyzing the revised content of the target web page to identify a set of one or more topics. 20. The computer implemented method of claim 16 , wherein the web page is contained in a host, and wherein determining at least one similar web page comprises determining that a web page is similar if it is contained within the same host as the target web page. | 0.813202 |
6. A machine-readable storage having stored thereon, a computer program having a plurality of code sections, said code sections executable by a machine for causing the machine to perform the steps of: determining at least two possible meanings for a language input; for each possible meaning, determining a probability that said possible meaning is a correct interpretation of said language input; computing at least one relative delta computation based at least in part upon said probabilities, wherein each value of a relative delta computation uniquely corresponds to a type of irregularity within said language input such that values of relative delta computations vary depending on the corresponding type of irregularity; detecting at least one irregularity within said language input and determining the corresponding type of the at least one irregularity based upon said relative delta computation; and performing at least one programmatic action responsive to detecting said irregularity. | 6. A machine-readable storage having stored thereon, a computer program having a plurality of code sections, said code sections executable by a machine for causing the machine to perform the steps of: determining at least two possible meanings for a language input; for each possible meaning, determining a probability that said possible meaning is a correct interpretation of said language input; computing at least one relative delta computation based at least in part upon said probabilities, wherein each value of a relative delta computation uniquely corresponds to a type of irregularity within said language input such that values of relative delta computations vary depending on the corresponding type of irregularity; detecting at least one irregularity within said language input and determining the corresponding type of the at least one irregularity based upon said relative delta computation; and performing at least one programmatic action responsive to detecting said irregularity. 16. The machine-readable storage of claim 6 , wherein said probability that each possible meaning is a correct interpretation is a confidence value; said method further comprising the steps of: receiving a plurality of language inputs; for each language input, determining at least two possible meanings and associated confidence values; plotting at least a portion of said confidence values on a graph; and determining at least one threshold from said graph, wherein said relative delta computation is compared against said threshold when detecting said irregularity. | 0.534044 |
1. A method for updating an existing document using natural language processing (NLP), the method comprising: receiving information about a subject-matter domain; identifying a portion of the existing document, wherein the portion corresponds to the subject-matter domain by including at least a threshold number of references to a category identified in the subject matter domain; lemmatizing, using a processor and a memory, a group of words from the portion to use in a search query, wherein the search query returns a result set, the result set including current information corresponding to the subject-matter domain, the current information being recent as compared to an age of the portion; forming, using the processor and the memory, natural language (NL) update content by processing the current information through an NLP application; associating with the NL update content a confidence rating, the confidence rating being indicative of a provenance of a data source that supplied the current information; and updating, by changing the portion of the existing document in a document repository, the existing document using the NL update content and the confidence rating. | 1. A method for updating an existing document using natural language processing (NLP), the method comprising: receiving information about a subject-matter domain; identifying a portion of the existing document, wherein the portion corresponds to the subject-matter domain by including at least a threshold number of references to a category identified in the subject matter domain; lemmatizing, using a processor and a memory, a group of words from the portion to use in a search query, wherein the search query returns a result set, the result set including current information corresponding to the subject-matter domain, the current information being recent as compared to an age of the portion; forming, using the processor and the memory, natural language (NL) update content by processing the current information through an NLP application; associating with the NL update content a confidence rating, the confidence rating being indicative of a provenance of a data source that supplied the current information; and updating, by changing the portion of the existing document in a document repository, the existing document using the NL update content and the confidence rating. 5. The method of claim 1 , where the updating further comprises: modifying a content of the portion in the existing document, wherein the modifying adds to the portion a first reference, wherein the first reference is usable to access a first data source that provided information responsive to the search query. | 0.833688 |
12. The computer-implemented method of claim 9 further comprising: under direction of the one or more hardware processors configured with specific software instructions, further in response to receiving the command and the node identifier: deleting the first portion of the textual record. | 12. The computer-implemented method of claim 9 further comprising: under direction of the one or more hardware processors configured with specific software instructions, further in response to receiving the command and the node identifier: deleting the first portion of the textual record. 13. The computer-implemented method of claim 12 , wherein a cursor is placed at a previous location of the deleted first portion of the textual record after the first portion of the textual record is deleted. | 0.919027 |
25. A non-transitory computer-readable storage medium storing executable program code comprised of computer program instructions for creating a linked list for executing a plurality of portions of script on a device, the computer program instructions, when executed by at least one processor, causes the processor to: receive a set of nodes, each node comprising a portion of script defining functionality of the device; couple the nodes in a nodal structure based on a desired order of execution of the portions of script; determine a first execution path through a first subset of nodes in the nodal structure based at least in part on one or more input values of defined input properties for one or more portions of script; compile the first subset of nodes into a first linked list of operations for execution by the device, the first linked list following the first determined execution path through the first subset of nodes; receive a new node comprising a new portion of script defining additional functionality of the device; couple the new node to at least one other node in the nodal structure based on a desired location of execution of the new portion of script in the order of execution of the portions of script; determine a second execution path through a second subset of nodes in the nodal structure based at least in part on the one or more input values of defined input properties and the new portion of script, the second subset of nodes including the new node; and compile the second subset of nodes into a second linked list of operations for execution by the device, the second linked list following the second determined execution path through the second subset of nodes. | 25. A non-transitory computer-readable storage medium storing executable program code comprised of computer program instructions for creating a linked list for executing a plurality of portions of script on a device, the computer program instructions, when executed by at least one processor, causes the processor to: receive a set of nodes, each node comprising a portion of script defining functionality of the device; couple the nodes in a nodal structure based on a desired order of execution of the portions of script; determine a first execution path through a first subset of nodes in the nodal structure based at least in part on one or more input values of defined input properties for one or more portions of script; compile the first subset of nodes into a first linked list of operations for execution by the device, the first linked list following the first determined execution path through the first subset of nodes; receive a new node comprising a new portion of script defining additional functionality of the device; couple the new node to at least one other node in the nodal structure based on a desired location of execution of the new portion of script in the order of execution of the portions of script; determine a second execution path through a second subset of nodes in the nodal structure based at least in part on the one or more input values of defined input properties and the new portion of script, the second subset of nodes including the new node; and compile the second subset of nodes into a second linked list of operations for execution by the device, the second linked list following the second determined execution path through the second subset of nodes. 30. The non-transitory computer-readable storage medium of claim 25 , wherein an input value of the one or more defined input properties is at least one of: a number, a string, a Boolean value, and a null. | 0.520977 |
3. The platen of claim 1 further comprising a pair of bearing surfaces attached to the substrate for engagement with a bearing member for at least partial rotation of the platen about an axis through the bearing surfaces. | 3. The platen of claim 1 further comprising a pair of bearing surfaces attached to the substrate for engagement with a bearing member for at least partial rotation of the platen about an axis through the bearing surfaces. 4. The platen of claim 3 where the bearing surfaces are attached to the upper portion. | 0.946097 |
26. The computer program of claim 25 , further comprising: program code for generating, using an entity builder, an entity key required to publish the block of text, wherein the entity builder is linked to the publishing entity table. | 26. The computer program of claim 25 , further comprising: program code for generating, using an entity builder, an entity key required to publish the block of text, wherein the entity builder is linked to the publishing entity table. 27. The computer program of claim 26 , wherein generating an entity key comprises: program code for providing a choice list for each business entity to which the block of text pertains, wherein each choice list comprises at least one specific instance of the corresponding business entity; program code for selecting an instance of each business entity from each choice list; program code for building the entity key based on the selected instance of each business entity; and program code for storing the entity key in a published standard text table. | 0.829299 |
3. The method according to claim 2 , further comprising a step of generating a set of first binary vectors based on the second individual collection of biometric data, the step for providing a statistical sampling for each vector likelihood vector comprising: replacing the likelihood values higher than a first threshold value determined by a bit equal to 1 and replacing the others by a bit equal to 0, or replacing a number N of highest likelihood values by a bit equal to 1 and replacing the others by a bit equal to 0, such that each biometric data corresponds to a first binary vector. | 3. The method according to claim 2 , further comprising a step of generating a set of first binary vectors based on the second individual collection of biometric data, the step for providing a statistical sampling for each vector likelihood vector comprising: replacing the likelihood values higher than a first threshold value determined by a bit equal to 1 and replacing the others by a bit equal to 0, or replacing a number N of highest likelihood values by a bit equal to 1 and replacing the others by a bit equal to 0, such that each biometric data corresponds to a first binary vector. 5. The method according to claim 3 , wherein each first or second binary vector comprises a number of bits equal to 1 determined among others according to one of the first, second and third threshold values, this number being lower by at least an order of magnitude with respect to the number of bits equal to 0. | 0.939127 |
33. A hardware computer readable storage media including instructions readable by a computing device comprising: a language model comprising a combination of an N-gram language model and a context-free grammar language model and storing information related to words and semantic information to be recognized; a module receiving input including commands executable by an application from a user and capturing the input for processing, the module performing recognition on the input by accessing the language model and ascertaining semantic information pertaining to a first portion of the input and outputting a semantic object comprising data including data for executing commands in a format to be processed by a computer application and being in accordance with the input that has been recognized and semantic information for the first portion, wherein performing recognition and outputting the semantic object are performed while capturing continues for subsequent portions of the input; and a second module performing a selected task, the second module receiving semantic objects synchronously in accordance with the user's input, each semantic object comprising data including commands in a format to be processed by a computer application and in accordance with a portion of input from the user and semantic information pertaining to the portion of input from the user, the module taking action as a function of processing the semantic objects synchronously including providing information or utilizing other applications based on at least the data for executing the commands. | 33. A hardware computer readable storage media including instructions readable by a computing device comprising: a language model comprising a combination of an N-gram language model and a context-free grammar language model and storing information related to words and semantic information to be recognized; a module receiving input including commands executable by an application from a user and capturing the input for processing, the module performing recognition on the input by accessing the language model and ascertaining semantic information pertaining to a first portion of the input and outputting a semantic object comprising data including data for executing commands in a format to be processed by a computer application and being in accordance with the input that has been recognized and semantic information for the first portion, wherein performing recognition and outputting the semantic object are performed while capturing continues for subsequent portions of the input; and a second module performing a selected task, the second module receiving semantic objects synchronously in accordance with the user's input, each semantic object comprising data including commands in a format to be processed by a computer application and in accordance with a portion of input from the user and semantic information pertaining to the portion of input from the user, the module taking action as a function of processing the semantic objects synchronously including providing information or utilizing other applications based on at least the data for executing the commands. 42. The hardware computer readable storage media of claim 33 wherein the second module takes action comprising rendering information to the user while semantic objects related to subsequent portions of the user's input are further received. | 0.5 |
1. A computer-implemented method of merging text analysis results, comprising: processing, by a computer system, a plurality of text information according to a first text processing service to generate a first plurality of instances annotated according to a first taxonomy having a first set of elements; processing, by the computer system, the plurality of text information according to a second text processing service to generate a second plurality of instances annotated according to a second taxonomy having a second set of elements; calculating, by the computer system, a first coefficient between a first set of instances and a second set of instances according to a first corrected, weakened Jaccard factor, wherein the first set of instances corresponds to a first element of the first set of elements and wherein the second set of instances corresponds to a second element of the second set of elements; calculating, by the computer system, a second coefficient between the first set of instances and the second set of instances according to a second corrected, weakened Jaccard factor; calculating, by the computer system, a third coefficient between the first set of instances and the second set of instances according to a third corrected, weakened Jaccard factor; determining, by the computer system, that the first element is a subtype of the second element, that the second element is a subtype of the first element, or that the first element is associated with the second element, according to the first coefficient, the second coefficient and the third coefficient; and merging, by the computer system, the first taxonomy and the second taxonomy according to the first element and the second element being associated, the first element being the subtype of the second element, or the second element being the subtype of the first element, wherein the first corrected, weakened Jaccard factor corresponds to a Jaccard factor having a numerator and a denominator, wherein the Jaccard factor is corrected in the numerator with a first correction factor and weakened in the denominator with a first weakening factor, wherein the second corrected, weakened Jaccard factor corresponds to a ratio between a first corrected intersection size and a first corrected instance set size, wherein the first corrected intersection size is a size of an intersection of the first set of instances and the second set of instances corrected with a second correction factor, and wherein the first corrected instance set size is a size of the first set of instances deducted by a number of instances only found by the first text processing service multiplied with a second weakening factor, and wherein the third corrected, weakened Jaccard factor corresponds to a ratio between a second corrected intersection size and a second corrected instance set size, wherein the second corrected intersection size is a size of an intersection of the first set of instances and the second set of instances corrected with a third correction factor, and wherein the second corrected instance set size is a size of the second set of instances deducted by a number of instances only found by the second text processing service multiplied with a third weakening factor. | 1. A computer-implemented method of merging text analysis results, comprising: processing, by a computer system, a plurality of text information according to a first text processing service to generate a first plurality of instances annotated according to a first taxonomy having a first set of elements; processing, by the computer system, the plurality of text information according to a second text processing service to generate a second plurality of instances annotated according to a second taxonomy having a second set of elements; calculating, by the computer system, a first coefficient between a first set of instances and a second set of instances according to a first corrected, weakened Jaccard factor, wherein the first set of instances corresponds to a first element of the first set of elements and wherein the second set of instances corresponds to a second element of the second set of elements; calculating, by the computer system, a second coefficient between the first set of instances and the second set of instances according to a second corrected, weakened Jaccard factor; calculating, by the computer system, a third coefficient between the first set of instances and the second set of instances according to a third corrected, weakened Jaccard factor; determining, by the computer system, that the first element is a subtype of the second element, that the second element is a subtype of the first element, or that the first element is associated with the second element, according to the first coefficient, the second coefficient and the third coefficient; and merging, by the computer system, the first taxonomy and the second taxonomy according to the first element and the second element being associated, the first element being the subtype of the second element, or the second element being the subtype of the first element, wherein the first corrected, weakened Jaccard factor corresponds to a Jaccard factor having a numerator and a denominator, wherein the Jaccard factor is corrected in the numerator with a first correction factor and weakened in the denominator with a first weakening factor, wherein the second corrected, weakened Jaccard factor corresponds to a ratio between a first corrected intersection size and a first corrected instance set size, wherein the first corrected intersection size is a size of an intersection of the first set of instances and the second set of instances corrected with a second correction factor, and wherein the first corrected instance set size is a size of the first set of instances deducted by a number of instances only found by the first text processing service multiplied with a second weakening factor, and wherein the third corrected, weakened Jaccard factor corresponds to a ratio between a second corrected intersection size and a second corrected instance set size, wherein the second corrected intersection size is a size of an intersection of the first set of instances and the second set of instances corrected with a third correction factor, and wherein the second corrected instance set size is a size of the second set of instances deducted by a number of instances only found by the second text processing service multiplied with a third weakening factor. 5. The computer-implemented method of claim 1 , further comprising: determining, by the computer system, that the first element is associated with the second element when the first element is not equal to the second element, the first element is not the subtype of the second element, the second element is not the subtype of the first element, and at least one of the first coefficient, the second coefficient and the third coefficient is greater than 0.2. | 0.815768 |
1. A computer Chinese character input method comprising: Selecting 10 elements corresponding to the 10 simplified Chinese character simplified strokes which are and Selecting 46 elements corresponding to the 46 stroke combination sets whose representative visual representations are: ; Assigning said 46 elements, and 8 elements, excluding and from said 10 elements, to the keyboard in the following way: TABLE 4 in the table above, elements in the same line are assigned to the same keys, while those in different lines are assigned to different keys; and Determining desired input characters based on the keystrokes typed by a user on this keyboard. | 1. A computer Chinese character input method comprising: Selecting 10 elements corresponding to the 10 simplified Chinese character simplified strokes which are and Selecting 46 elements corresponding to the 46 stroke combination sets whose representative visual representations are: ; Assigning said 46 elements, and 8 elements, excluding and from said 10 elements, to the keyboard in the following way: TABLE 4 in the table above, elements in the same line are assigned to the same keys, while those in different lines are assigned to different keys; and Determining desired input characters based on the keystrokes typed by a user on this keyboard. 3. The invention of claim 1 , further comprising the step of selecting 25 elements that are respectively corresponding to the 25 stroke combination sets whose representative visual representations are: ; Assigning these 25 elements to keys of the keyboard. | 0.731648 |
28. The method of claim 27 further comprising: executing a query to the federated schema; and returning query results. | 28. The method of claim 27 further comprising: executing a query to the federated schema; and returning query results. 29. The method of claim 28 wherein said executing is performed by a software application. | 0.956121 |
26. A computer-implemented method for use in a computer programming environment, comprising: automatically generating a background script from a workflow; automatically detecting a data type incompatibility in the script incompatibility between an output a first action and an input of a second action in the workflow; and automatically scripting a data type conversion between the first and second actions in the background script, such that the first action output is converted to become compatible with the second action input, wherein the conversion is perform in the background and wherein automatically scripting a data type conversion comprises converting a data type based at least upon a relevance hierarchy of compatible data types. | 26. A computer-implemented method for use in a computer programming environment, comprising: automatically generating a background script from a workflow; automatically detecting a data type incompatibility in the script incompatibility between an output a first action and an input of a second action in the workflow; and automatically scripting a data type conversion between the first and second actions in the background script, such that the first action output is converted to become compatible with the second action input, wherein the conversion is perform in the background and wherein automatically scripting a data type conversion comprises converting a data type based at least upon a relevance hierarchy of compatible data types. 50. The computer-implemented method of claim 26 , further comprising receiving a plurality of user inputs defining the workflow, including: determining a context and a data requirement for a potential user input, the potential user input including selecting a graphical element specifying an action in a workflow, from a preceding user input; filtering candidates for the potential user input for relevance in light of the context and the data requirement; and presenting the filtered candidates to the user ordered by their relevance. | 0.608803 |
1. A method comprising: performing an analysis of a history of communication sessions over two communication modalities, wherein the analysis considers a semantic meaning of the communication sessions, a temporal relationship among the communication sessions, and a user activity that transitions from a first communication session to a second communication session, wherein the first communication session and the second communication session are part of the communication sessions; identifying a relationship among the communication sessions based on the analysis; prioritizing the communication sessions based on the relationship to yield prioritized communication sessions; generating a unified communication log based on the prioritized communication sessions; outputting the unified communication log to a user; processing feedback from the user to yield processed feedback, wherein the feedback from the user comprises an observation of how the user interacts with the unified communication log; and based on the processed feedback, adaptively adjusting how the communication sessions are prioritized. | 1. A method comprising: performing an analysis of a history of communication sessions over two communication modalities, wherein the analysis considers a semantic meaning of the communication sessions, a temporal relationship among the communication sessions, and a user activity that transitions from a first communication session to a second communication session, wherein the first communication session and the second communication session are part of the communication sessions; identifying a relationship among the communication sessions based on the analysis; prioritizing the communication sessions based on the relationship to yield prioritized communication sessions; generating a unified communication log based on the prioritized communication sessions; outputting the unified communication log to a user; processing feedback from the user to yield processed feedback, wherein the feedback from the user comprises an observation of how the user interacts with the unified communication log; and based on the processed feedback, adaptively adjusting how the communication sessions are prioritized. 3. The method of claim 1 , wherein the unified communication log is used as part of one of a predictive contacts application, a topic analyzer, a conferencing application, and a personal communication assistant. | 0.813051 |
1. A non-transitory computer readable medium storing a program causing a computer to execute a process for classifying multilingual documents, the process comprising: extracting, concerning first document information including a plurality of supervised texts of a first language, a word sense associated with a word included in each of the plurality of supervised texts in the first document information from predetermined word-sense information; setting an extracted word sense to be a teacher signal for each of the plurality of supervised texts included in the first document information; creating a first topic model by executing supervised topic modeling on the first document information by using the set teacher signal for each of the plurality of supervised texts included in the first document information; estimating a topic of each of the plurality of supervised texts included in the first document information by using the created first topic model; generating a learning model by executing supervised machine learning by using, as a feature, the estimated topic of each of the plurality of supervised texts included in the first document information and by using, as a category, the teacher signal for each of the plurality of supervised texts in the first document information; extracting, concerning second document information including a plurality of supervised texts of a second language and concerning a field identical to a field of the first document information, a word sense associated with a word included in each of the plurality of supervised texts in the second document information from the predetermined word-sense information; setting an extracted word sense to be a teacher signal for each of the plurality of supervised texts included in the second document information; creating a second topic model by executing supervised topic modeling on the second document information by using the set teacher signal for each of the plurality of supervised texts included in the second document information; estimating a topic of each of the plurality of supervised texts included in the second document information by using the created second topic model; and estimating a category of each of the plurality of supervised texts included in the second document information by using, as a feature, the estimated topic of an associated supervised text and by using the generated learning model. | 1. A non-transitory computer readable medium storing a program causing a computer to execute a process for classifying multilingual documents, the process comprising: extracting, concerning first document information including a plurality of supervised texts of a first language, a word sense associated with a word included in each of the plurality of supervised texts in the first document information from predetermined word-sense information; setting an extracted word sense to be a teacher signal for each of the plurality of supervised texts included in the first document information; creating a first topic model by executing supervised topic modeling on the first document information by using the set teacher signal for each of the plurality of supervised texts included in the first document information; estimating a topic of each of the plurality of supervised texts included in the first document information by using the created first topic model; generating a learning model by executing supervised machine learning by using, as a feature, the estimated topic of each of the plurality of supervised texts included in the first document information and by using, as a category, the teacher signal for each of the plurality of supervised texts in the first document information; extracting, concerning second document information including a plurality of supervised texts of a second language and concerning a field identical to a field of the first document information, a word sense associated with a word included in each of the plurality of supervised texts in the second document information from the predetermined word-sense information; setting an extracted word sense to be a teacher signal for each of the plurality of supervised texts included in the second document information; creating a second topic model by executing supervised topic modeling on the second document information by using the set teacher signal for each of the plurality of supervised texts included in the second document information; estimating a topic of each of the plurality of supervised texts included in the second document information by using the created second topic model; and estimating a category of each of the plurality of supervised texts included in the second document information by using, as a feature, the estimated topic of an associated supervised text and by using the generated learning model. 2. The non-transitory computer readable medium according to claim 1 , wherein the process further comprises performing word-sense disambiguation, if there are a plurality of word senses associated with a word in a supervised text of the second language, by determining one of the plurality of word senses on the basis of a co-occurrence probability of another word in the supervised text. | 0.5 |
1. A computer-implemented method for determining organizational agility of an organization across multiple computing domains, comprising: extracting, from one or more mail servers of the organization, a set of relevant historical organizational e-mail documents associated with an organization in a computer memory medium; fetching a set of electronic documents from an intranet of the organization via a web crawler; analyzing, by a computer system, the set of relevant historical organizational e-mail documents and the set of electronic documents by parsing the set of relevant historical organizational e-mail documents and the set of electronic documents for a set of keywords that is indicative of the organizational agility of the organization, each of the set of keywords having an associated score, the organizational agility based on an amount of governance within the organization; determining trends across disparate documents in the set of relevant historical organizational e-mail documents and the set of electronic documents combined with customer and enterprise insights mined from social media content using deep text and data analytics; calculating, by the computer system, a set of agility scores based on the trends and the analyzing of scores associated with the set of keywords using a set of agility computation rules, wherein a higher agility score is calculated in the case that the set of keywords indicate a lower amount of governance; weighting, by the computer system, the set of agility scores based on a geographic region associated with the organization; providing output based on the calculating and the weighting; and altering work tasks in a workload to an ordering that is optimal for the organization based on the weighted agility scores. | 1. A computer-implemented method for determining organizational agility of an organization across multiple computing domains, comprising: extracting, from one or more mail servers of the organization, a set of relevant historical organizational e-mail documents associated with an organization in a computer memory medium; fetching a set of electronic documents from an intranet of the organization via a web crawler; analyzing, by a computer system, the set of relevant historical organizational e-mail documents and the set of electronic documents by parsing the set of relevant historical organizational e-mail documents and the set of electronic documents for a set of keywords that is indicative of the organizational agility of the organization, each of the set of keywords having an associated score, the organizational agility based on an amount of governance within the organization; determining trends across disparate documents in the set of relevant historical organizational e-mail documents and the set of electronic documents combined with customer and enterprise insights mined from social media content using deep text and data analytics; calculating, by the computer system, a set of agility scores based on the trends and the analyzing of scores associated with the set of keywords using a set of agility computation rules, wherein a higher agility score is calculated in the case that the set of keywords indicate a lower amount of governance; weighting, by the computer system, the set of agility scores based on a geographic region associated with the organization; providing output based on the calculating and the weighting; and altering work tasks in a workload to an ordering that is optimal for the organization based on the weighted agility scores. 2. The computer-implemented method of claim 1 , further comprising determining, by the computer system, a set of actions to be taken based on the output. | 0.879688 |
23. The computing device of claim 19 wherein said calculating comprises breaking said portion of said username into letter pairs or letter triplets and determining a frequency of occurrence of said letter pairs or letter triplets in a spoken language. | 23. The computing device of claim 19 wherein said calculating comprises breaking said portion of said username into letter pairs or letter triplets and determining a frequency of occurrence of said letter pairs or letter triplets in a spoken language. 24. The computing device of claim 23 wherein said calculating calculates a high likelihood of pronounceability when said frequency of occurrence of said letter pairs or letter triplets in said spoken language exceeds a threshold. | 0.870216 |
11. A computer-implemented method comprising: receiving a query for information from the document collection, wherein the query includes a first phrase; accessing a plurality of index servers to retrieve identifiers of documents on a phrase posting list associated with the first phrase, wherein the phrase posting list identifies documents of the document collection associated with the first phrase, and is divided into a plurality of shards, each shard identifying a subset of the plurality of the documents identified by the posting list, and each different shard being stored on a corresponding different index server of the plurality of index servers; serving a response to the query, wherein the response is based on information in the phrase posting list associated with the first phrase; and storing a plurality of shards of different phrase posting lists on a first index server; storing plurality of shards of different phrase posting lists on a second index server; and within each of the first and second index servers, for each shard of a phrase posting list, ordering the shard according to document identifiers of the documents included in the shard. | 11. A computer-implemented method comprising: receiving a query for information from the document collection, wherein the query includes a first phrase; accessing a plurality of index servers to retrieve identifiers of documents on a phrase posting list associated with the first phrase, wherein the phrase posting list identifies documents of the document collection associated with the first phrase, and is divided into a plurality of shards, each shard identifying a subset of the plurality of the documents identified by the posting list, and each different shard being stored on a corresponding different index server of the plurality of index servers; serving a response to the query, wherein the response is based on information in the phrase posting list associated with the first phrase; and storing a plurality of shards of different phrase posting lists on a first index server; storing plurality of shards of different phrase posting lists on a second index server; and within each of the first and second index servers, for each shard of a phrase posting list, ordering the shard according to document identifiers of the documents included in the shard. 15. The method of claim 11 , further comprising: associating a first set of index servers with a first tier of index servers; associating a second set of index servers with a second tier of index servers; and determining whether to store shards of the phrase posting list for the first phrase on the first tier or the second tier based on a query processing cost for the phrase posting list. | 0.663868 |
6. The system set forth in claim 5 wherein each said symbol generating means comprises a symbol memory means containing data corresponding to said output signals for said symbols. | 6. The system set forth in claim 5 wherein each said symbol generating means comprises a symbol memory means containing data corresponding to said output signals for said symbols. 7. The system set forth in claim 6 wherein said directory memory means contains data representative of address locations for said symbol memory means. | 0.939317 |
33. A development system, comprising: means for editing a documentation object in a software development tool according to a current language context by employing an edit window; and means for presenting a translation of the documentation object in an alternative language received from a storage medium, near or above the edit window, in response to an initiation of modification of the documentation object in a current language by the means for editing, wherein the means for presenting provides an alert indicative of an existence of the translation of the documentation object and provides a reminder indicating that the translation of the documentation object is to be updated in view of a change made to the documentation object via the means for editing. | 33. A development system, comprising: means for editing a documentation object in a software development tool according to a current language context by employing an edit window; and means for presenting a translation of the documentation object in an alternative language received from a storage medium, near or above the edit window, in response to an initiation of modification of the documentation object in a current language by the means for editing, wherein the means for presenting provides an alert indicative of an existence of the translation of the documentation object and provides a reminder indicating that the translation of the documentation object is to be updated in view of a change made to the documentation object via the means for editing. 34. The development system of claim 33 , further comprising means for switching between a current language context and an alternative language context. | 0.762344 |
10. A method of analyzing feedback data of an electronic learning system comprising: receiving a plurality of feedback data from one or more client devices, the received feedback data corresponding to user feedback of one or more users relating to electronic learning content of the electronic learning system; determining an associated user and a sentiment score for each of the received plurality of feedback data; grouping the plurality of feedback data into one or more feedback aggregations associated with the one or more users; calculating a sentiment score for each of the one or more first feedback aggregations associated with the one or more users; receiving user records associated with each of the one or more users, the received user records relating to interactions of the one or more users with the electronic learning system occurring after receipt of the feedback data; storing the user records and associated sentiment scores for each of the one or more user within a data store of the electronic learning system; training a machine learning algorithm based on the stored user records and associated sentiment scores, for each of the one or more users within the data store of the electronic learning system; receiving additional feedback data from the one or more client devices, the additional feedback data including user feedback from a first user relating to electronic learning content; calculating a sentiment score for the first user, based on the received additional feedback data; using the stored user records and associated sentiment scores in the data store of the electronic learning system, determining a user record prediction for the first user using the trained machine learning algorithm, based on the calculated sentiment score for the first user; determining an output and one or more output devices, based on the determined user record prediction for the first user; and transmitting the determined output to the determined one or more output devices. | 10. A method of analyzing feedback data of an electronic learning system comprising: receiving a plurality of feedback data from one or more client devices, the received feedback data corresponding to user feedback of one or more users relating to electronic learning content of the electronic learning system; determining an associated user and a sentiment score for each of the received plurality of feedback data; grouping the plurality of feedback data into one or more feedback aggregations associated with the one or more users; calculating a sentiment score for each of the one or more first feedback aggregations associated with the one or more users; receiving user records associated with each of the one or more users, the received user records relating to interactions of the one or more users with the electronic learning system occurring after receipt of the feedback data; storing the user records and associated sentiment scores for each of the one or more user within a data store of the electronic learning system; training a machine learning algorithm based on the stored user records and associated sentiment scores, for each of the one or more users within the data store of the electronic learning system; receiving additional feedback data from the one or more client devices, the additional feedback data including user feedback from a first user relating to electronic learning content; calculating a sentiment score for the first user, based on the received additional feedback data; using the stored user records and associated sentiment scores in the data store of the electronic learning system, determining a user record prediction for the first user using the trained machine learning algorithm, based on the calculated sentiment score for the first user; determining an output and one or more output devices, based on the determined user record prediction for the first user; and transmitting the determined output to the determined one or more output devices. 14. The method of claim 10 , wherein receiving the plurality of feedback data from the one or more client devices comprises: receiving the plurality of feedback data via an event streaming service executing on a data store server separate from the one or more client devices. | 0.943558 |
12. The method as set forth in claim 11 , further comprising: conditional upon the identifying initially not identifying any caption signatures, repeating the assigning and identifying wherein the repeated assigning employs a different text fragment representation. | 12. The method as set forth in claim 11 , further comprising: conditional upon the identifying initially not identifying any caption signatures, repeating the assigning and identifying wherein the repeated assigning employs a different text fragment representation. 13. The method as set forth in claim 12 , wherein the different text fragment representation comprises the initial text fragment representation with at least one additional text fragment attribute. | 0.919159 |
15. The system of claim 10 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising updating the website visitation policy for the crawling once a specified number of pages is crawled. | 15. The system of claim 10 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising updating the website visitation policy for the crawling once a specified number of pages is crawled. 16. The system of claim 15 , wherein updating the website visitation policy is according to an expected perplexity value of novelty regions. | 0.843812 |
9. An appliance according to claim 1, wherein the operating cycle is further adjusted as a function of the rate of change of liquid turbidity. | 9. An appliance according to claim 1, wherein the operating cycle is further adjusted as a function of the rate of change of liquid turbidity. 10. An appliance according to claim 9, wherein an operating cycle comprises at least one pre-wash fill cycle, a main wash fill cycle, a rinse fill cycle, and a final rinse fill cycle. | 0.914069 |
12. The computer program product of claim 8 wherein the computer readable program code configured to identify the original language is further configured to: calculate a confidence score based on the given pair vector and the threshold vector distance; and identifying the original language based on the confidence score. | 12. The computer program product of claim 8 wherein the computer readable program code configured to identify the original language is further configured to: calculate a confidence score based on the given pair vector and the threshold vector distance; and identifying the original language based on the confidence score. 13. The computer program product of claim 12 wherein the computer readable program code configured to calculate a confidence score is further configured to: determine a language probability of the original language corresponding to each pair vector; and incorporate the language probability into the confidence score. | 0.840708 |
10. A communications apparatus, comprising: a speech input for receiving conversational speech information from a first user; a speech to text process for converting the received speech information to a text representation thereof; a communications interface for communicating the text representation and the speech input remotely from the user as part of a real time conversation with a second user; and an audio interface configured to reproduce a second speech input and a visual interface displaying the text representation from the second user to the first user. | 10. A communications apparatus, comprising: a speech input for receiving conversational speech information from a first user; a speech to text process for converting the received speech information to a text representation thereof; a communications interface for communicating the text representation and the speech input remotely from the user as part of a real time conversation with a second user; and an audio interface configured to reproduce a second speech input and a visual interface displaying the text representation from the second user to the first user. 12. The apparatus according to claim 10 , wherein the text representation is converted into speech remotely from the first user. | 0.820971 |
19. The method of claim 14 wherein the hierarchical data structure is a binary trie. | 19. The method of claim 14 wherein the hierarchical data structure is a binary trie. 20. The method of claim 19 wherein the hierarchical data structure provides a minimal perfect hash function. | 0.973919 |
73. A non-transitory computer-readable medium comprising instructions for recognizing an input environmental sound at a server, the instructions causing a processor to perform operations comprising: if a confidence level determined by a client device and associated with a first label associated with an input environmental sound received at the client device is less than a first confidence threshold: accessing a server database including a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; receiving, from the client device, an input sound model representing the input environmental sound; determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; selecting a second label from one or more labels, of the plurality of labels, associated with the one or more sound models; associating the second label with the input environmental sound based on a confidence level of the second label; and sending the second label or an indication of a failure in recognizing the input environmental sound to the client device based on the confidence level of the second label. | 73. A non-transitory computer-readable medium comprising instructions for recognizing an input environmental sound at a server, the instructions causing a processor to perform operations comprising: if a confidence level determined by a client device and associated with a first label associated with an input environmental sound received at the client device is less than a first confidence threshold: accessing a server database including a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; receiving, from the client device, an input sound model representing the input environmental sound; determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; selecting a second label from one or more labels, of the plurality of labels, associated with the one or more sound models; associating the second label with the input environmental sound based on a confidence level of the second label; and sending the second label or an indication of a failure in recognizing the input environmental sound to the client device based on the confidence level of the second label. 84. The non-transitory computer-readable medium of claim 73 , wherein selecting the second label comprises: grouping the one or more sound models into one or more sets of sound models based on the one or more labels; calculating a sum of the similarity values of sound models in each of the one or more sets to determine a largest sum; and selecting a particular label associated with a set of the one or more sets having the largest sum. | 0.502115 |
1. A computer-implemented method for proactive customer experience management in a communication network, comprising: a) obtaining a performance-indicating alert (PA) from at least one probe; b) identifying relevant alerts from an alert database in absence of possible fault condition from the PA; c) determining a possible problem condition from the PA and the identified relevant alerts; d) raising trace trigger for gathering relevant trace data; e) determining specific problem condition and relevant cause, based on gathered trace data and relevant data from PM/FM, CDR and OSS systems; f) determining appropriate recommendation for resolution of the determined specific problem condition; g) recalculating a probe alert threshold value for triggering the performance-indicating probe alert; h) providing the recalculated probe alert threshold value for modifying a configuration of a performance-indicating probe; i) updating a user interface dashboard using the determination of a root cause of the possible problem and the recommendation for resolution of the possible problem; and j) updating new knowledge into a knowledge base with problem-context, resolution, relevant adjustments to alerts, thresholds and rules. | 1. A computer-implemented method for proactive customer experience management in a communication network, comprising: a) obtaining a performance-indicating alert (PA) from at least one probe; b) identifying relevant alerts from an alert database in absence of possible fault condition from the PA; c) determining a possible problem condition from the PA and the identified relevant alerts; d) raising trace trigger for gathering relevant trace data; e) determining specific problem condition and relevant cause, based on gathered trace data and relevant data from PM/FM, CDR and OSS systems; f) determining appropriate recommendation for resolution of the determined specific problem condition; g) recalculating a probe alert threshold value for triggering the performance-indicating probe alert; h) providing the recalculated probe alert threshold value for modifying a configuration of a performance-indicating probe; i) updating a user interface dashboard using the determination of a root cause of the possible problem and the recommendation for resolution of the possible problem; and j) updating new knowledge into a knowledge base with problem-context, resolution, relevant adjustments to alerts, thresholds and rules. 2. The method of claim 1 , wherein the relevant alerts are identified from the alert database using a rules engine applying pre-defined rules. | 0.546452 |
13. A non-transitory computer-readable medium having embodied thereon a computer program for executing a method comprising: identifying, a business rule from a text document, wherein the business rule comprises one or more rule intents, wherein one or more rule intent comprise at least one of keywords, parts of speech (POS) tags, and wildcards and said one or more rule intents are utilized to automatically identify the business rule from the text document; creating, via the one or more hardware processors, a rule repository based on an identified business rule and the one or more rule intents, wherein the rule intents are atomic constraints stored in an ontology form; comparing, the one or more rule intents in the business rule with the one or more clusters associated with a plurality of rule types in the rule repository to compute a match score, wherein a match score is indicative of number of rule intents and based on the match score, the business rule is annotated with one or more rule types in the rule repository, and wherein the rule repository is periodically updated with a plurality of new rule intents, said rule intent patterns and new rule types; classifying, the business rule under at least one rule type, amongst the plurality of rule types, to further classify the business rule into at least one of formatted and unformatted text documents for referring and tracing the text document by annotating the business rule with one or more corresponding rule intents and one or more rule types in the rule repository; clustering, said plurality of new rule intents in an agglomerative manner to identify one or more clustering rule intents that co-occur frequently in the rule repository; assembling, the one or more clusters into a plurality of clustering techniques, wherein the rule repository is periodically updated with the corresponding rule intent and the rule type to classify sentences obtained from a training dataset; and automatically associating, via the one or more hardware processors, the business rules extracted from the text document with a plurality of corresponding knowledge element types and system components to reference, trace and re-use at least one of requirement artifacts and system documentation. | 13. A non-transitory computer-readable medium having embodied thereon a computer program for executing a method comprising: identifying, a business rule from a text document, wherein the business rule comprises one or more rule intents, wherein one or more rule intent comprise at least one of keywords, parts of speech (POS) tags, and wildcards and said one or more rule intents are utilized to automatically identify the business rule from the text document; creating, via the one or more hardware processors, a rule repository based on an identified business rule and the one or more rule intents, wherein the rule intents are atomic constraints stored in an ontology form; comparing, the one or more rule intents in the business rule with the one or more clusters associated with a plurality of rule types in the rule repository to compute a match score, wherein a match score is indicative of number of rule intents and based on the match score, the business rule is annotated with one or more rule types in the rule repository, and wherein the rule repository is periodically updated with a plurality of new rule intents, said rule intent patterns and new rule types; classifying, the business rule under at least one rule type, amongst the plurality of rule types, to further classify the business rule into at least one of formatted and unformatted text documents for referring and tracing the text document by annotating the business rule with one or more corresponding rule intents and one or more rule types in the rule repository; clustering, said plurality of new rule intents in an agglomerative manner to identify one or more clustering rule intents that co-occur frequently in the rule repository; assembling, the one or more clusters into a plurality of clustering techniques, wherein the rule repository is periodically updated with the corresponding rule intent and the rule type to classify sentences obtained from a training dataset; and automatically associating, via the one or more hardware processors, the business rules extracted from the text document with a plurality of corresponding knowledge element types and system components to reference, trace and re-use at least one of requirement artifacts and system documentation. 14. The non-transitory computer-readable medium as claimed in claim 13 , wherein the identifying comprises: extracting a sentence from a text document; classifying the extracted sentence as one of a candidate rule and a non-rule based on a Bayesian classification technique; and comparing a syntactic structure of the candidate rule with a plurality of rule intent patterns in the rule repository to identify the candidate rule as the business rule. | 0.546626 |
17. The system of claim 16 , wherein a high saliency weight indicates a high predicted importance to the user. | 17. The system of claim 16 , wherein a high saliency weight indicates a high predicted importance to the user. 18. The system of claim 17 , wherein the processor spends additional effort converting high saliency words. | 0.94686 |
1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix. | 1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix. 7. The method of claim 1 , wherein the objective function is expressed using a convex envelope of a non-convex rank function subject to a row constraint on the matrix. | 0.838462 |
2. The method of claim 1 , further comprising informing the user of the selected command. | 2. The method of claim 1 , further comprising informing the user of the selected command. 4. The method of claim 2 , wherein the user is audibly informed of the selected command. | 0.968032 |
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