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1. One or more computer-storage memory devices having computer-executable instructions embodied thereon that when executed by a computing device, perform a method of featuring recently published documents within search results, the method comprising: receiving a search query from a user; identifying a first plurality of documents that are responsive to the search query because a portion of the search query matches one or more portions of the documents; determining that an intent of the user to receive recently published documents is ambiguous by calculating a freshness score for the search query, wherein the freshness score is based on how many recently published documents are responsive to the search query, and by determining that the freshness score for the search query falls into a designated range bounded by a low-threshold score and a high-threshold score; displaying, on a search results page, the first plurality of search results; and upon said determining, that the freshness score for the search query falls into a designated range bounded by the low-threshold score and the high-threshold score, displaying, on the search results page with the first plurality of search results, a second plurality of search results that describe documents published less than a designated period of time from the present. | 1. One or more computer-storage memory devices having computer-executable instructions embodied thereon that when executed by a computing device, perform a method of featuring recently published documents within search results, the method comprising: receiving a search query from a user; identifying a first plurality of documents that are responsive to the search query because a portion of the search query matches one or more portions of the documents; determining that an intent of the user to receive recently published documents is ambiguous by calculating a freshness score for the search query, wherein the freshness score is based on how many recently published documents are responsive to the search query, and by determining that the freshness score for the search query falls into a designated range bounded by a low-threshold score and a high-threshold score; displaying, on a search results page, the first plurality of search results; and upon said determining, that the freshness score for the search query falls into a designated range bounded by the low-threshold score and the high-threshold score, displaying, on the search results page with the first plurality of search results, a second plurality of search results that describe documents published less than a designated period of time from the present. 6. The memory device of claim 1 , wherein the method further comprises displaying a publication time with one or more of the search results within the second plurality of search results, and wherein the publication time indicates when a document described by a search result was published. | 0.69093 |
1. A method for generating an aggregated social feed, the method comprising: receiving a plurality of feeds, each feed including a plurality of content items and received from a social networking service; determining a relevance score for each of the plurality of content items based on one or more relevance factors; adjusting the relevance scores for each of one or more of the content items based on the social networking service from which the content item was received, where the adjusting comprises reducing or increasing the relevance score of the content item based on a number of other content items received from the same social networking service; ranking the content items based on the relevance scores thereof; selecting a plurality of the ranked content items based on ranking; and sending for display to a client device the selected content items in the aggregated social feed. | 1. A method for generating an aggregated social feed, the method comprising: receiving a plurality of feeds, each feed including a plurality of content items and received from a social networking service; determining a relevance score for each of the plurality of content items based on one or more relevance factors; adjusting the relevance scores for each of one or more of the content items based on the social networking service from which the content item was received, where the adjusting comprises reducing or increasing the relevance score of the content item based on a number of other content items received from the same social networking service; ranking the content items based on the relevance scores thereof; selecting a plurality of the ranked content items based on ranking; and sending for display to a client device the selected content items in the aggregated social feed. 14. The method of claim 1 , wherein the adjusting comprises reducing or increasing the relevance score of the content item based on a number of other content items received from the same social networking service, wherein the reducing or increasing the relevance score of the content item comprises weighting the one or more relevance factors to achieve a target velocity of the aggregated social feed, the target velocity representing a predetermined number of content items received from the plurality of feeds to be included in the aggregated social feed. | 0.5 |
11. At least one computer readable storage device encoded with a plurality of instructions that, when executed, cause at least one processor to perform a method for determining an intended action of a user of a computing system environment, the computing system environment comprising a voice system, the intended action being specified via a spoken utterance input of the user, wherein the method comprises acts of: obtaining a decoding of the spoken input of the user, wherein the voice system has a precise machine-based grammar to allow the user to invoke the intended action by speaking one or more predetermined voice commands and wherein the spoken input is a free form voice instruction that is different than the precise machine-based grammar; and extracting the intended action from the decoding of the spoken input using an iterative hierarchical extraction process comprising analyzing the decoding of the spoken input in multiple hierarchically dependent semantic stages, comprising: determining a first level of classification of the intended action from the decoding of the spoken input during a first semantic stage of the iterative hierarchical extraction process, the first level of classification having a plurality of sub-classifications associated with the first level of classification; and determining, from among the plurality of sub-classifications associated with the first level of classification, a second level of classification of the intended action from the same decoding of the spoken input during a second semantic stage of the iterative hierarchical extraction process. | 11. At least one computer readable storage device encoded with a plurality of instructions that, when executed, cause at least one processor to perform a method for determining an intended action of a user of a computing system environment, the computing system environment comprising a voice system, the intended action being specified via a spoken utterance input of the user, wherein the method comprises acts of: obtaining a decoding of the spoken input of the user, wherein the voice system has a precise machine-based grammar to allow the user to invoke the intended action by speaking one or more predetermined voice commands and wherein the spoken input is a free form voice instruction that is different than the precise machine-based grammar; and extracting the intended action from the decoding of the spoken input using an iterative hierarchical extraction process comprising analyzing the decoding of the spoken input in multiple hierarchically dependent semantic stages, comprising: determining a first level of classification of the intended action from the decoding of the spoken input during a first semantic stage of the iterative hierarchical extraction process, the first level of classification having a plurality of sub-classifications associated with the first level of classification; and determining, from among the plurality of sub-classifications associated with the first level of classification, a second level of classification of the intended action from the same decoding of the spoken input during a second semantic stage of the iterative hierarchical extraction process. 16. The at least one computer readable storage device of claim 11 , wherein the method further comprises providing one or more commands to the voice system based, at least in part, on the determination of the first level of classification and the second level of classification. | 0.605637 |
4. The method according to claim 3, wherein said English letters and said phonetic alphabets are processed separately. | 4. The method according to claim 3, wherein said English letters and said phonetic alphabets are processed separately. 5. The method according to claim 4, wherein said processing English letters comprises the steps of: when all of the English letters are consonants, stopping said phonetic spelling check; deleting all non-English letters and symbols excepts `-`; providing a mapping representing the relationship between the English letters and corresponding symbols, wherein each of said English letters maps to at least one of said symbols; generating a plurality of letter strings comprising said symbols according to replaceability of said symbols; filtering out all same vowels in succession until one thereof is left; changing n to .eta. if n is followed by k or g; changing s.intg. to .intg. if .intg. is preceded by s, and changing k.intg. to t.intg. if .intg. is preceded by k; replacing ed by t if the ed locates at the end of the letter string, and is preceded by p, k, S, .intg., t.intg., .theta., and f, otherwise, replacing the ed by d if is not preceded by d or t; replacing the ed by Id if none of the conditions in the previous step exists; deleting all null characters in the letter strings; finding the corresponding English letters for each of the letter strings; and generating additional letter strings by deleting consonants in succession one at a time starting from the second of said symbols of each of the letter strings. | 0.732907 |
1. A computer-implemented method of translating user input into at least one word having multiple characters, the method comprising: displaying a keyboard on a display, wherein the keyboard comprises multiple keys, and wherein each key in the keyboard has a relative position with respect to every other key in the keyboard, receiving a sequence of user inputs; translating the sequence of user inputs into a pattern of one or more relative directions, wherein each relative direction in the pattern corresponds to the relative position of a key in the keyboard with respect to a previous key; and using the pattern of one or more relative directions to identify the at least one word in a stored dictionary, wherein the stored dictionary associates the word with a pattern of relative directions that reflects relative positions of the keys associated with the multiple characters that form the word. | 1. A computer-implemented method of translating user input into at least one word having multiple characters, the method comprising: displaying a keyboard on a display, wherein the keyboard comprises multiple keys, and wherein each key in the keyboard has a relative position with respect to every other key in the keyboard, receiving a sequence of user inputs; translating the sequence of user inputs into a pattern of one or more relative directions, wherein each relative direction in the pattern corresponds to the relative position of a key in the keyboard with respect to a previous key; and using the pattern of one or more relative directions to identify the at least one word in a stored dictionary, wherein the stored dictionary associates the word with a pattern of relative directions that reflects relative positions of the keys associated with the multiple characters that form the word. 6. The computer-implemented method of claim 1 , wherein the sequence of user inputs is received via a push-button keyboard. | 0.953593 |
1. A file search system for searching for a file stored in a storage device, comprising: reception means for receiving a search request made by a user; search means for obtaining search result files by searching the storage device on the basis of notification from the reception means; monitor means for monitoring a file operation by the user; creation means for creating a reference relation of the search result files on the basis of the file operation by the user monitored by the monitor means, the reference relation being defined as a relation between a reference file and a reference source file in which information included in the reference file is introduced into the reference source file by the file operation of the user, wherein the reference file is a file to be referenced and the reference source file is a file referencing the reference file, and the introduction of information from the reference file to the reference source file is performed by copying information from the reference file and pasting the copied information into the reference source file; storage means for storing the reference relation; importance calculation means for calculating an importance of the reference file on the basis of one or more items selected from among reference relation items each obtained by monitoring a file operation of the user regarding introduction of information from the reference file to the reference source file; and search result sort means for arranging the search result files obtained by the search means on the basis of the importance of the reference file; and a control section for displaying a screen for allowing the user to select arrangement of the search result files obtained by the search means on the basis of the importance or a condition other than the importance, the control section judging whether or not the user selects the arrangement of the search result files on the basis of the importance; wherein the search result sort means arranges the search result files on the basis of the importance when the arrangement of the search result files on the basis of the importance is selected, and arranges the search result files on the basis of the condition other than the importance when the arrangement of the search result files on the basis of the importance is not selected. | 1. A file search system for searching for a file stored in a storage device, comprising: reception means for receiving a search request made by a user; search means for obtaining search result files by searching the storage device on the basis of notification from the reception means; monitor means for monitoring a file operation by the user; creation means for creating a reference relation of the search result files on the basis of the file operation by the user monitored by the monitor means, the reference relation being defined as a relation between a reference file and a reference source file in which information included in the reference file is introduced into the reference source file by the file operation of the user, wherein the reference file is a file to be referenced and the reference source file is a file referencing the reference file, and the introduction of information from the reference file to the reference source file is performed by copying information from the reference file and pasting the copied information into the reference source file; storage means for storing the reference relation; importance calculation means for calculating an importance of the reference file on the basis of one or more items selected from among reference relation items each obtained by monitoring a file operation of the user regarding introduction of information from the reference file to the reference source file; and search result sort means for arranging the search result files obtained by the search means on the basis of the importance of the reference file; and a control section for displaying a screen for allowing the user to select arrangement of the search result files obtained by the search means on the basis of the importance or a condition other than the importance, the control section judging whether or not the user selects the arrangement of the search result files on the basis of the importance; wherein the search result sort means arranges the search result files on the basis of the importance when the arrangement of the search result files on the basis of the importance is selected, and arranges the search result files on the basis of the condition other than the importance when the arrangement of the search result files on the basis of the importance is not selected. 2. The file search system according to claim 1 , further comprising weight setting means for setting a weight of the reference relation, to one or more items selected from among the reference relation items, wherein the importance calculation means calculates the importance of the file on the basis of the weight set by the weight setting means. | 0.587623 |
11. An apparatus for rendering a video program, comprising: a computer-readable storage medium; and a processor responsive to the computer-readable storage medium and to a software program, the software program, when loaded into the processor, operative to: render the video content on a display device; receive a segment of speech from a user such that the speech segment annotates a portion of the video content currently being rendered; convert the speech segment to a text-segment; associate the text-segment with the portion of the video content; and store in a selectively retrievable manner the text-segment so that it is associated with the rendered portion of the video content. | 11. An apparatus for rendering a video program, comprising: a computer-readable storage medium; and a processor responsive to the computer-readable storage medium and to a software program, the software program, when loaded into the processor, operative to: render the video content on a display device; receive a segment of speech from a user such that the speech segment annotates a portion of the video content currently being rendered; convert the speech segment to a text-segment; associate the text-segment with the portion of the video content; and store in a selectively retrievable manner the text-segment so that it is associated with the rendered portion of the video content. 15. The apparatus of claim 11 wherein the processor is further configured to receive the video content from a video camera. | 0.559829 |
1. A method of synchronizing bookmarks comprising: receiving a request to save a first bookmark identifying a first web document in a first mode, the first bookmark received from a first browser executing in the first mode, the first mode being one of a visual mode and a voice mode; receiving, from the first browser, the first bookmark comprising data indicative of the first web document; storing the first bookmark in a bookmark repository on a multimodal platform, the bookmark repository operable for storing one or more bookmarks in a multimodal format and accessible to a plurality of browsers regardless of whether the browsers are executing in the visual or voice mode; receiving, from a second browser executing in a second mode, the second mode being one of the visual or voice mode, a request to access the first bookmark; linking the first bookmark with a second web document in the second mode containing substantially equivalent content of the first web document, the second web document compatible with the second browser based on a relationship between the first web document and the second web document; and sending a second bookmark identifying the second web document to the second browser, wherein the second browser executing in the second mode is operable to navigate to the second web document using the second bookmark. | 1. A method of synchronizing bookmarks comprising: receiving a request to save a first bookmark identifying a first web document in a first mode, the first bookmark received from a first browser executing in the first mode, the first mode being one of a visual mode and a voice mode; receiving, from the first browser, the first bookmark comprising data indicative of the first web document; storing the first bookmark in a bookmark repository on a multimodal platform, the bookmark repository operable for storing one or more bookmarks in a multimodal format and accessible to a plurality of browsers regardless of whether the browsers are executing in the visual or voice mode; receiving, from a second browser executing in a second mode, the second mode being one of the visual or voice mode, a request to access the first bookmark; linking the first bookmark with a second web document in the second mode containing substantially equivalent content of the first web document, the second web document compatible with the second browser based on a relationship between the first web document and the second web document; and sending a second bookmark identifying the second web document to the second browser, wherein the second browser executing in the second mode is operable to navigate to the second web document using the second bookmark. 11. The method of claim 1 , wherein the bookmark repository further stores annotative data descriptive of the first web document. | 0.555556 |
27. The speech recognition method of claim 22 wherein the step of determining the preferred mix of the preclassification output data comprises the steps of: selecting a mix of the preclassification output data to obtain a predetermined satisfactory recognition accuracy in the least amount of time. | 27. The speech recognition method of claim 22 wherein the step of determining the preferred mix of the preclassification output data comprises the steps of: selecting a mix of the preclassification output data to obtain a predetermined satisfactory recognition accuracy in the least amount of time. 28. The speech recognition method of claim 27 wherein the preferred mix is selected from the group comprising (i) the first speech input signal preclassifying output data alone, (ii) the second speech input signal preclassifying output data alone, (iii) a combination of the first and second speech input signal preclassifying output data, (iv) the first speech input signal preclassifying output data and the second speech input signal preclassifying output data, (v) the first speech input signal preclassifying output data and the combination of the first and second speech input signal preclassifying output data, (vi) the second speech input signal preclassifying output data and the combination of the first and second speech input signal preclassifying output data, and (vii) the first speech input signal preclassifying output data, the combination of the first and second speech input signal preclassifying output data, and the second speech input signal preclassifying output data. | 0.77037 |
17. A computer-implemented method comprising: receiving audio data and a textual transcript of the audio data to be aligned with the audio data; generating, from the textual transcript, a language model that represents a set of particular substrings of the textual transcript, the language model comprising allowed states of the language model and one or more transitions that link the allowed states; generating a speech hypothesis of one or more language elements included in the audio using a speech recognizer, wherein the speech hypothesis includes time stamps associated with an occurrence of each of the one or more language elements; comparing the one or more language elements of the speech hypothesis to the substrings generated by the language model the language model to identify times at which particular ones of the substrings occur in the audio data; and associating at least a portion of the textual transcript with the time stamps based on the comparison. | 17. A computer-implemented method comprising: receiving audio data and a textual transcript of the audio data to be aligned with the audio data; generating, from the textual transcript, a language model that represents a set of particular substrings of the textual transcript, the language model comprising allowed states of the language model and one or more transitions that link the allowed states; generating a speech hypothesis of one or more language elements included in the audio using a speech recognizer, wherein the speech hypothesis includes time stamps associated with an occurrence of each of the one or more language elements; comparing the one or more language elements of the speech hypothesis to the substrings generated by the language model the language model to identify times at which particular ones of the substrings occur in the audio data; and associating at least a portion of the textual transcript with the time stamps based on the comparison. 22. The method of claim 17 , wherein comparing comprises transitioning to a subsequent substring when a language element from the speech hypothesis is successfully matched with a substring. | 0.541108 |
11. The method according to claim 9 , further including transcribing audio into the other text. | 11. The method according to claim 9 , further including transcribing audio into the other text. 12. The method according to claim 11 , wherein the transcribing is done using a speech recognition software. | 0.956951 |
13. A computer-implemented system, comprising: a relational model that includes a plurality of atoms and a plurality of relationships between atoms; and a modifier component receives an identity of a user and automatically modifies the relational model based at least in part upon an identity of a user to generate a modified relational model. | 13. A computer-implemented system, comprising: a relational model that includes a plurality of atoms and a plurality of relationships between atoms; and a modifier component receives an identity of a user and automatically modifies the relational model based at least in part upon an identity of a user to generate a modified relational model. 18. The system of claim 13 , further comprising an output component that performs inference over the modified relational model and outputs an indication of a query that is believed to be of interest to the user upon performing the inference. | 0.775327 |
3. The method of claim 1 where the extracting the second information includes: extracting, from a feed, at least one of a title of the blog, an author of the blog, or a profile of the author of the blog. | 3. The method of claim 1 where the extracting the second information includes: extracting, from a feed, at least one of a title of the blog, an author of the blog, or a profile of the author of the blog. 4. The method of claim 3 where the extracting the second information further includes: extracting, from the blog, at least one of a profile of the author of the blog or a blogroll. | 0.869636 |
11. The method of claim 10, further including the step of adjusting the belief network when the at least one decision graph indicates that a relationship between the nodes of the belief network exists that is not reflected by the belief network. | 11. The method of claim 10, further including the step of adjusting the belief network when the at least one decision graph indicates that a relationship between the nodes of the belief network exists that is not reflected by the belief network. 12. The method of claim 11 wherein the step of adjusting the belief network includes adding an arc that introduces a cycle into the belief network to create a cyclic directed graph. | 0.960214 |
33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. | 33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. 34. The non-transitory computer readable storage medium of claim 33 , wherein the one or more causal features comprise at least one of a lexical feature, a grammatical feature, and a semantic feature. | 0.660252 |
1. Apparatus for use in managing a service level associated with resources in a distributed information technology (IT) system based on financial terms, the apparatus comprising: at least one processor operative to: (i) construct and maintain an electronic contract that contains information pertaining to descriptions of one or more business transactions in IT terms, financial implications of one or more business transaction service levels, and reporting to be performed in one or more financial terms; (ii) measure at least one service level of at least one distributed element of the IT system in terms of one or more business metrics based on the electronic contract and based at least in part on input received from at least one agent module located in the at least one distributed element; (iii) determine at least one financial optimization based at least in part on the measured at least one service level of at least one element of the IT system and based at least in part on the electronic contract, the financial optimization being specified in the electronic contract at the time of construction such that, at the time the financial optimization is to be determined, the electronic contract is accessed to identify a particular financial metric of the financial optimization that is to be computed and to identify an operation for computing the particular financial metric, the one or more business metrics are converted to one or more financial equivalents wherein the one or more financial equivalents comprise a cost of a lost connection, a cost of down time, and a relationship between revenue and network latency; and (iv) issue at least one control command based on the at least one financial optimization, the command to be executed on the at least one distributed element by the at least one agent module located in the at least one distributed element; and memory, operatively coupled to the at least one processor, for storing at least one of the electronic contract and results of the measurement operation. | 1. Apparatus for use in managing a service level associated with resources in a distributed information technology (IT) system based on financial terms, the apparatus comprising: at least one processor operative to: (i) construct and maintain an electronic contract that contains information pertaining to descriptions of one or more business transactions in IT terms, financial implications of one or more business transaction service levels, and reporting to be performed in one or more financial terms; (ii) measure at least one service level of at least one distributed element of the IT system in terms of one or more business metrics based on the electronic contract and based at least in part on input received from at least one agent module located in the at least one distributed element; (iii) determine at least one financial optimization based at least in part on the measured at least one service level of at least one element of the IT system and based at least in part on the electronic contract, the financial optimization being specified in the electronic contract at the time of construction such that, at the time the financial optimization is to be determined, the electronic contract is accessed to identify a particular financial metric of the financial optimization that is to be computed and to identify an operation for computing the particular financial metric, the one or more business metrics are converted to one or more financial equivalents wherein the one or more financial equivalents comprise a cost of a lost connection, a cost of down time, and a relationship between revenue and network latency; and (iv) issue at least one control command based on the at least one financial optimization, the command to be executed on the at least one distributed element by the at least one agent module located in the at least one distributed element; and memory, operatively coupled to the at least one processor, for storing at least one of the electronic contract and results of the measurement operation. 10. The apparatus of claim 1 , wherein the IT system comprises a collection of hardware and software intended to store or deliver data in a digital form. | 0.561355 |
1. A word information storage and retrieval apparatus comprising: a plurality of character keys for entering first word information representing a desired word in original form; search means responsive to said plurality of character keys for searching second word information representing said desired word in a variant form, said search means including; an original form memory for containing original forms of a plurality of words; at least one variant form memory for containing variant forms corresponding to said plurality of words; a counter for producing an incremental count upon the initiation of searching; a coincidence detector for sequentially comparing said desired word with the original forms of said plurality of words stored in said original form memory; said coincidence detector comparing said desired word with the original form of a new one of said plurality of words with each increment of said counter, a detected coincidence stopping the incremental count of said counter to thereby allow said counter to produce a signal representative of the original form of the word corresponding to said desired word; said signal generated by said counter being used to address and recall the variant form of said desired word from one of said at least one variant form memories; and a display responsive to said variant form of said desired word for indicating said second word information. | 1. A word information storage and retrieval apparatus comprising: a plurality of character keys for entering first word information representing a desired word in original form; search means responsive to said plurality of character keys for searching second word information representing said desired word in a variant form, said search means including; an original form memory for containing original forms of a plurality of words; at least one variant form memory for containing variant forms corresponding to said plurality of words; a counter for producing an incremental count upon the initiation of searching; a coincidence detector for sequentially comparing said desired word with the original forms of said plurality of words stored in said original form memory; said coincidence detector comparing said desired word with the original form of a new one of said plurality of words with each increment of said counter, a detected coincidence stopping the incremental count of said counter to thereby allow said counter to produce a signal representative of the original form of the word corresponding to said desired word; said signal generated by said counter being used to address and recall the variant form of said desired word from one of said at least one variant form memories; and a display responsive to said variant form of said desired word for indicating said second word information. 3. The apparatus as specified in claim 1, which further comprises a driver for controlling the transfer of either the original form from the original form memory or a variant form form said at least one variant form memory to the display. | 0.548043 |
11. An apparatus comprising: at least one processor; and at least one memory including computer program code, at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: at least: identify a time period to be described linguistically in an output text; identify a communicative context for the output text; determine one or more temporal reference frames that are applicable to the time period and a domain defined by the communicative context; and generate a phrase specification that linguistically describes the time period based on a descriptor that is defined by a temporal reference frame of the one or more temporal reference frames, wherein the descriptor specifies a time window that is inclusive of at least a portion of the time period to be described linguistically. | 11. An apparatus comprising: at least one processor; and at least one memory including computer program code, at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: at least: identify a time period to be described linguistically in an output text; identify a communicative context for the output text; determine one or more temporal reference frames that are applicable to the time period and a domain defined by the communicative context; and generate a phrase specification that linguistically describes the time period based on a descriptor that is defined by a temporal reference frame of the one or more temporal reference frames, wherein the descriptor specifies a time window that is inclusive of at least a portion of the time period to be described linguistically. 12. An apparatus according to claim 11 , wherein the at least one memory including the computer program code is further configured to, with the at least one processor, cause the apparatus to: align the one or more temporal reference frames to the communicative context; and select the descriptor defined by the temporal reference frame of the one or more temporal reference frames based on the time period and one or more previously generated phrase specifications. | 0.545379 |
5. A non-transitory computer readable storage medium storing a program which allows a computer to realize: an import function for obtaining a connection relationship of ruled lines and character strings from first data which is data of an Fault Tree (FT) diagram expressing a tree structure by the ruled lines and the character strings on a sheet of a spreadsheet program, acquiring an event included in the FT diagram and a connection relationship between events from an obtained connection relationship of the ruled lines and the character strings, and generating second data describing the tree structure of the FT diagram in markup language based on the event included in the FT diagram and the connection relationship between events; and an editing function for editing the second data to generate third data describing the tree structure of the FT diagram in the markup language, wherein the import function generates the second data by making a computer: repeatedly execute first processing of setting a specific cell surrounded by a ruled line as a cell to be analyzed, discovering a lower event of the cell to be analyzed by following a ruled line extending on a right side of the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the lower event between a start tag and an end tag of the cell to be analyzed in the second data, and setting a cell of the lower event as a new cell to be analyzed until no additional new lower event is discovered after a cell of a top event is set as a first cell to be analyzed; repeatedly execute second processing of, when no additional new lower event is discovered, discovering a same-rank event of the cell to be analyzed by following a ruled line branching downward from a ruled line extending to a left side from the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the same-rank event in parallel with the element of the cell to be analyzed in the second data, setting the cell of the same-rank event as a new cell to be analyzed, and repeating the first processing until no additional new lower event is discovered, until no additional new same-rank event is discovered; and repeatedly execute third processing of, when no additional new same-rank event is discovered, setting a higher event of the same-rank event discovered immediately before as a new cell to be analyzed, and repeating the second processing until no additional new same-rank event is discovered, until the cell to be analyzed becomes the cell of the top event. | 5. A non-transitory computer readable storage medium storing a program which allows a computer to realize: an import function for obtaining a connection relationship of ruled lines and character strings from first data which is data of an Fault Tree (FT) diagram expressing a tree structure by the ruled lines and the character strings on a sheet of a spreadsheet program, acquiring an event included in the FT diagram and a connection relationship between events from an obtained connection relationship of the ruled lines and the character strings, and generating second data describing the tree structure of the FT diagram in markup language based on the event included in the FT diagram and the connection relationship between events; and an editing function for editing the second data to generate third data describing the tree structure of the FT diagram in the markup language, wherein the import function generates the second data by making a computer: repeatedly execute first processing of setting a specific cell surrounded by a ruled line as a cell to be analyzed, discovering a lower event of the cell to be analyzed by following a ruled line extending on a right side of the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the lower event between a start tag and an end tag of the cell to be analyzed in the second data, and setting a cell of the lower event as a new cell to be analyzed until no additional new lower event is discovered after a cell of a top event is set as a first cell to be analyzed; repeatedly execute second processing of, when no additional new lower event is discovered, discovering a same-rank event of the cell to be analyzed by following a ruled line branching downward from a ruled line extending to a left side from the cell to be analyzed and by searching a cell surrounded by a ruled line beyond the same, arranging an element of the same-rank event in parallel with the element of the cell to be analyzed in the second data, setting the cell of the same-rank event as a new cell to be analyzed, and repeating the first processing until no additional new lower event is discovered, until no additional new same-rank event is discovered; and repeatedly execute third processing of, when no additional new same-rank event is discovered, setting a higher event of the same-rank event discovered immediately before as a new cell to be analyzed, and repeating the second processing until no additional new same-rank event is discovered, until the cell to be analyzed becomes the cell of the top event. 7. The non-transitory computer readable storage medium storing the program according to claim 5 , wherein the program allows the computer to further realize a consistency verification function for obtaining a physical quantity of each event from the second or third data and if the physical quantity of a specific event and the physical quantity of a lower event thereof do not share the same unit and the physical quantity of the specific event cannot be expressed by multiplication, division or exponentiation of the unit of the physical quantity of the lower event, for determining that consistency of the second or third data is not obtained and for verifying consistency of the second or third data. | 0.5 |
13. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving unconstrained input speech from a user; converting, via a processor, only the unconstrained input speech corresponding to single digits into a string of words, wherein each word in the string of words is modeled using a three segment structure comprising a plurality of heads and a plurality of tails; converting the string of words into a sequence of digits using classes of rules and according to an acoustic model database in which Markov models characterize acoustic features of numeric words; comparing the sequence of digits to a plurality of valid sequences of digits, to yield validity information; and providing the validity information to a device associated with the user. | 13. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving unconstrained input speech from a user; converting, via a processor, only the unconstrained input speech corresponding to single digits into a string of words, wherein each word in the string of words is modeled using a three segment structure comprising a plurality of heads and a plurality of tails; converting the string of words into a sequence of digits using classes of rules and according to an acoustic model database in which Markov models characterize acoustic features of numeric words; comparing the sequence of digits to a plurality of valid sequences of digits, to yield validity information; and providing the validity information to a device associated with the user. 16. The computer-readable storage device of claim 13 , the computer-readable storage device having additional instructions stored which, when executed by the computing device, result in the operations further comprising: using a language model database that stores data describing a structure and a sequence of words and phrases. | 0.5 |
1. A computer-implemented method for performing a location search, comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a location search query; identifying geographical feature documents that satisfy the location search query, wherein each of the geographical feature documents correspond to a geographical feature; and ranking the identified geographical feature documents in accordance with a score that is based, at least in part, on proximity of the geographical features corresponding to the identified geographical feature documents to a geographical viewport region of a client system, to produce a set of ranked geographical feature documents; and providing results, in accordance with the ranked geographical feature documents, that identify at least one geographic feature corresponding to the at least one of the ranked geographical feature documents. | 1. A computer-implemented method for performing a location search, comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a location search query; identifying geographical feature documents that satisfy the location search query, wherein each of the geographical feature documents correspond to a geographical feature; and ranking the identified geographical feature documents in accordance with a score that is based, at least in part, on proximity of the geographical features corresponding to the identified geographical feature documents to a geographical viewport region of a client system, to produce a set of ranked geographical feature documents; and providing results, in accordance with the ranked geographical feature documents, that identify at least one geographic feature corresponding to the at least one of the ranked geographical feature documents. 2. The method of claim 1 , wherein the geographical viewport region corresponds to a geographical region displayed on the client system. | 0.584034 |
11. A client system, for processing query information, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors; the one or more programs comprising instructions for: receiving a partial search query from a user; prior to receiving a search request from the user on a complete search query that includes the partial search query, sending the partial search query to a server system; receiving from the server system, a set of historical complete search queries, the set of historical complete search queries corresponding to the partial search query and ordered in accordance with a ranking criterion; receiving from the server system, prior to receiving a user selection of one of the set of historical complete search queries, predicted search results corresponding to one or more search queries of the set of historical complete search queries; and displaying at least a subset of the set of historical complete search queries and at least a subset of the predicted search results. | 11. A client system, for processing query information, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors; the one or more programs comprising instructions for: receiving a partial search query from a user; prior to receiving a search request from the user on a complete search query that includes the partial search query, sending the partial search query to a server system; receiving from the server system, a set of historical complete search queries, the set of historical complete search queries corresponding to the partial search query and ordered in accordance with a ranking criterion; receiving from the server system, prior to receiving a user selection of one of the set of historical complete search queries, predicted search results corresponding to one or more search queries of the set of historical complete search queries; and displaying at least a subset of the set of historical complete search queries and at least a subset of the predicted search results. 15. The system of claim 11 , wherein the predicted search results are received prior to receiving from the user the search request on the complete search query that includes the partial search query. | 0.531421 |
5. The avatar facial expression representation apparatus of claim 4 , wherein the short-term change of the parameter is identified by detecting a change of the parameter or a changing speed of the parameter during a predetermined second reference time which is set shorter than the predetermined first reference time. | 5. The avatar facial expression representation apparatus of claim 4 , wherein the short-term change of the parameter is identified by detecting a change of the parameter or a changing speed of the parameter during a predetermined second reference time which is set shorter than the predetermined first reference time. 6. The avatar facial expression representation apparatus of claim 5 , wherein the point of emphasis estimating portion estimates a point of emphasis as a vocal point where a sound is changed. | 0.922455 |
13. A computer system with a processor and a computer-readable storage memory the computer system comprising: means for presenting a graphical user interface at a client computer, the graphical user interface enabling a user to add a new annotation corresponding to media content; means for receiving a user request to add the new annotation; means for presenting, to the user via the graphical user interface, a plurality of likely temporal locations of the media content to associate the new annotation with; and means for receiving a user selection of one of the plurality of likely temporal locations to be the temporal location of the media content to associate the new annotation with. | 13. A computer system with a processor and a computer-readable storage memory the computer system comprising: means for presenting a graphical user interface at a client computer, the graphical user interface enabling a user to add a new annotation corresponding to media content; means for receiving a user request to add the new annotation; means for presenting, to the user via the graphical user interface, a plurality of likely temporal locations of the media content to associate the new annotation with; and means for receiving a user selection of one of the plurality of likely temporal locations to be the temporal location of the media content to associate the new annotation with. 15. A system as recited in claim 13 , wherein the means for presenting comprises means for displaying a visual indication of the likely temporal location for each of the plurality of likely temporal locations. | 0.665053 |
15. The system of claim 11 , further comprising a user identification device configured to communicate the user identification to the input device of the user interface. | 15. The system of claim 11 , further comprising a user identification device configured to communicate the user identification to the input device of the user interface. 16. The system of claim 15 , wherein the user identification device includes at least one of a wireless transmitter, a magnetic stripe card, and biometric data. | 0.933175 |
1. A method for reconciling detailed user transaction feedback with a numerical seller rating that rates a seller of a product, comprising: detecting, by one or more computer processors, that the numerical seller rating indicates a negative experience; mining a sentiment of words in the feedback and detecting that the words in the feedback indicate positive sentiment; responsive to detecting that the words in the feedback indicate positive sentiment, mining the sentiment of words in the feedback and detecting that the words in the feedback do not indicate any negative sentiment; and responsive to detecting that the words in the feedback do not indicate any negative sentiment, transforming a state of the numerical seller rating from a state that is inconsistent with the words in the feedback to a state that is reconciled with the words in the feedback. | 1. A method for reconciling detailed user transaction feedback with a numerical seller rating that rates a seller of a product, comprising: detecting, by one or more computer processors, that the numerical seller rating indicates a negative experience; mining a sentiment of words in the feedback and detecting that the words in the feedback indicate positive sentiment; responsive to detecting that the words in the feedback indicate positive sentiment, mining the sentiment of words in the feedback and detecting that the words in the feedback do not indicate any negative sentiment; and responsive to detecting that the words in the feedback do not indicate any negative sentiment, transforming a state of the numerical seller rating from a state that is inconsistent with the words in the feedback to a state that is reconciled with the words in the feedback. 4. The method of claim 1 wherein transforming a state of the numerical seller rating from a state that is inconsistent with the words in the feedback to a state that is reconciled with the words in the feedback is done by weighting the numerical seller rating. | 0.608696 |
29. A method comprising: establishing, using computing instructions comprised in at least one memory of a computing apparatus defining a first location in a network, a web browsing session with the network; selecting, using a traffic routing software unit comprised in at least one computing processor of the computing apparatus, a secure web container through which web content is to be accessed during the web browsing session, wherein the network comprises two or more secure web containers, and wherein a first secure web container, of the two or more secure web containers, is located in a first secure web container location of the network and a second secure web container, of the two or more secure web containers, is located in a second secure web container location of the network; selecting, using the traffic routing software unit, an egress node through which the web content is to be routed during the web browsing session, wherein the network comprises two or more egress nodes, and wherein a first egress node, of the two or more egress nodes, is located in a first egress node location of the network and a second egress node, of the two or more egress nodes, is located in a second egress node location of the network; and providing, via a communication connection between at least one of the two or more secure web containers and a user device defining a second location in the network, a user of the user device with secure access to the web content, wherein the web content is rendered or accessed at the secure web container, and wherein providing the user of the user device with the secure access to the web content comprises manipulating, at the secure web container, one or more elements of a browser fingerprint presented to or accessed by a web server associated with the web content such that a characteristic of the user device comprised in the manipulated browser fingerprint and a third location presented to or accessed by the web server is different from an actual characteristic of the user device and the second location, respectively. | 29. A method comprising: establishing, using computing instructions comprised in at least one memory of a computing apparatus defining a first location in a network, a web browsing session with the network; selecting, using a traffic routing software unit comprised in at least one computing processor of the computing apparatus, a secure web container through which web content is to be accessed during the web browsing session, wherein the network comprises two or more secure web containers, and wherein a first secure web container, of the two or more secure web containers, is located in a first secure web container location of the network and a second secure web container, of the two or more secure web containers, is located in a second secure web container location of the network; selecting, using the traffic routing software unit, an egress node through which the web content is to be routed during the web browsing session, wherein the network comprises two or more egress nodes, and wherein a first egress node, of the two or more egress nodes, is located in a first egress node location of the network and a second egress node, of the two or more egress nodes, is located in a second egress node location of the network; and providing, via a communication connection between at least one of the two or more secure web containers and a user device defining a second location in the network, a user of the user device with secure access to the web content, wherein the web content is rendered or accessed at the secure web container, and wherein providing the user of the user device with the secure access to the web content comprises manipulating, at the secure web container, one or more elements of a browser fingerprint presented to or accessed by a web server associated with the web content such that a characteristic of the user device comprised in the manipulated browser fingerprint and a third location presented to or accessed by the web server is different from an actual characteristic of the user device and the second location, respectively. 39. The method of claim 29 , wherein at least one of: the characteristic comprised in the manipulated browser fingerprint comprises the third location presented to or accessed by the web server, or the actual characteristic of the user device comprises the second location. | 0.613876 |
31. The method of claim 25 , wherein each process in the plurality of processes further generates a relevancy score for each candidate identity attribute, the relevancy score representing a degree of correctness that the particular entity identified by the candidate identity attribute is the entity. | 31. The method of claim 25 , wherein each process in the plurality of processes further generates a relevancy score for each candidate identity attribute, the relevancy score representing a degree of correctness that the particular entity identified by the candidate identity attribute is the entity. 33. The method of claim 31 , wherein calculating the score for the particular candidate identity attribute further comprises calculating the score based on a normalization factor for converting the relevancy score to a particular range of values. | 0.908321 |
46. A physical memory device including instructions for execution by one or more processors, the physical memory device including: instructions for receiving a plurality of search query/search result document pairings, where each search query/search result document pairing, of the pairings, includes a search query and a search result document associated with the search query; instructions for generating, for each of the pairings, a objective data derived from each of the pairings, where the objective data, for a particular one of the pairings that comprises a particular search result document and a particular search query, includes: first data based on a time between when search result documents, associated with the particular search query, are presented, and when the particular search result document, is selected, and second data based on a value indicating a portion of users that select another search result document, of the search result documents associated with the particular search query, before selecting the particular search result document; instructions for obtaining information associated with a relevance evaluation, from a human evaluator, for each of the pairings, each of the relevance evaluations measuring a relevance of a search query to a corresponding search result document, of a search query/search result document pairing; and instructions for training an evaluation model, based on the obtained information associated with the relevance evaluations and the objective data, to predict a human relevance evaluation that is used to rank additional search query/search result document pairings, where each search query/search result document pairing, of the additional search query/search result document pairings, includes a search query and a search result document. | 46. A physical memory device including instructions for execution by one or more processors, the physical memory device including: instructions for receiving a plurality of search query/search result document pairings, where each search query/search result document pairing, of the pairings, includes a search query and a search result document associated with the search query; instructions for generating, for each of the pairings, a objective data derived from each of the pairings, where the objective data, for a particular one of the pairings that comprises a particular search result document and a particular search query, includes: first data based on a time between when search result documents, associated with the particular search query, are presented, and when the particular search result document, is selected, and second data based on a value indicating a portion of users that select another search result document, of the search result documents associated with the particular search query, before selecting the particular search result document; instructions for obtaining information associated with a relevance evaluation, from a human evaluator, for each of the pairings, each of the relevance evaluations measuring a relevance of a search query to a corresponding search result document, of a search query/search result document pairing; and instructions for training an evaluation model, based on the obtained information associated with the relevance evaluations and the objective data, to predict a human relevance evaluation that is used to rank additional search query/search result document pairings, where each search query/search result document pairing, of the additional search query/search result document pairings, includes a search query and a search result document. 47. The physical memory device of claim 46 , where the objective data further includes: data obtained from historical logs of search activity. | 0.649531 |
27. The computer program product of claim 26 , wherein the code for identifying the set of quota cells further comprises code for determining an incomplete match to a quota cell in response to an edge of a quota cell vertex for the quota cell encountering a profile parameter value vertex representing a value of a profile parameter that is not determined for the panelist. | 27. The computer program product of claim 26 , wherein the code for identifying the set of quota cells further comprises code for determining an incomplete match to a quota cell in response to an edge of a quota cell vertex for the quota cell encountering a profile parameter value vertex representing a value of a profile parameter that is not determined for the panelist. 29. The computer program product of claim 27 , wherein the non-transitory computer-readable medium further comprises: code for determining whether matches are complete for each quota cell of the set associated with the project and, if not, obtaining additional information from the panelist with respect to each of the incompletely matched quota cells and determining whether a fit exists based on the additional information; and code for responding to a determination that a fit does not exist by eliminating all quota cells from the set that are associated with the incompletely matched project, and selecting another one of the quota cells of the set. | 0.77581 |
1. A non-transitory computer-readable storage medium having stored contents including instructions that, when executed, configure a computer system to perform a method, the method comprising: determining, by the configured computer system, one or more categories associated with a user-defined group of multiple items that is defined by a first user to be treated as a group, the first user being one of multiple customers of an item ordering service that makes the multiple items available to the multiple customers; providing, by the configured computer system, information for display to a second user that identifies the user-defined group of multiple items based on at least one of the associated categories for the user-defined group, wherein the second user is one of the multiple customers and is distinct from the first user, and wherein the provided information, when displayed, identifies the user-defined group of multiple items as a single item to be ordered and includes a visual indication of an action that is to be performed to order the user-defined group of multiple items from the item ordering service as the single item; in response to the indicated action being performed by the second user, initiating an order of the user-defined group of multiple items for the second user; and based at least in part on the defining of the user-defined group of multiple items by the first user, compensating the first user. | 1. A non-transitory computer-readable storage medium having stored contents including instructions that, when executed, configure a computer system to perform a method, the method comprising: determining, by the configured computer system, one or more categories associated with a user-defined group of multiple items that is defined by a first user to be treated as a group, the first user being one of multiple customers of an item ordering service that makes the multiple items available to the multiple customers; providing, by the configured computer system, information for display to a second user that identifies the user-defined group of multiple items based on at least one of the associated categories for the user-defined group, wherein the second user is one of the multiple customers and is distinct from the first user, and wherein the provided information, when displayed, identifies the user-defined group of multiple items as a single item to be ordered and includes a visual indication of an action that is to be performed to order the user-defined group of multiple items from the item ordering service as the single item; in response to the indicated action being performed by the second user, initiating an order of the user-defined group of multiple items for the second user; and based at least in part on the defining of the user-defined group of multiple items by the first user, compensating the first user. 17. The non-transitory computer-readable storage medium of claim 1 wherein the computer-readable storage medium is a memory of the computer system that stores the contents. | 0.569372 |
4. The method of claim 1 , further comprising: identifying an ambiguous concept within the unstructured data source; and resolving the ambiguous concept using the second set of potential contexts, wherein the second set of potential contexts comprises at least a first potential context associated with a highest confidence value. | 4. The method of claim 1 , further comprising: identifying an ambiguous concept within the unstructured data source; and resolving the ambiguous concept using the second set of potential contexts, wherein the second set of potential contexts comprises at least a first potential context associated with a highest confidence value. 5. The method of claim 4 , wherein the ambiguous concept is a formatted number. | 0.878493 |
6. A computer-implemented system for communicating between an application and a database, the system comprising: a code generator to generate a code of databinding files to bind data of the database to a program of the application wherein said code identifies tables to persist the data in the database, wherein said code generates a table of metadata from the identified tables, wherein said code generates stored procedures from the metadata table, generates value objects (VO) from the metadata table and generates at least one XML binding definition from the metadata table; and at least one run-time component coupled to the code generator to integrate the generated code of the stored procedures to the VOs via the XML binding definitions into the application when the application is run. | 6. A computer-implemented system for communicating between an application and a database, the system comprising: a code generator to generate a code of databinding files to bind data of the database to a program of the application wherein said code identifies tables to persist the data in the database, wherein said code generates a table of metadata from the identified tables, wherein said code generates stored procedures from the metadata table, generates value objects (VO) from the metadata table and generates at least one XML binding definition from the metadata table; and at least one run-time component coupled to the code generator to integrate the generated code of the stored procedures to the VOs via the XML binding definitions into the application when the application is run. 15. The system of claim 6 wherein the application comprises an application written in C++ programming language. | 0.601112 |
1. A computer-implemented method for improving text annotation comprising: configuring a grammar and an ontology used for natural language understanding (NLU) processing by: obtaining, by a computing device, a plurality of annotations using the ontology and the grammar, each of the plurality of annotations corresponding to one of a plurality of text samples; performing, by the computing device, one or more quality assurance checks for at least one of the plurality of annotations, the ontology, or the grammar; generating, by the computing device, a list of one or more flagged annotations, each of the one or more flagged annotations corresponding to one of the plurality of annotations flagged during one of the one or more quality assurance checks; presenting, at a display device of the computing device, the list of flagged annotations; receiving, via a user input device of the computing device, user input modifying one of the one or more flagged annotations to obtain a modified annotation; and updating at least one of the grammar or the ontology based on the modified annotation; and wherein performance of the first one of the quality assurance checks comprises: comparing a first arrangement of a set of hypernyms in a first annotation of the plurality of annotations to a second arrangement of the set of hypernyms in a second annotation of the plurality of annotations; and configuring the list of flagged annotations to include the first annotation and the second annotation responsive to determine that the first arrangement of the set of hypernyms does not match the second arrangement of the set of hypernyms. | 1. A computer-implemented method for improving text annotation comprising: configuring a grammar and an ontology used for natural language understanding (NLU) processing by: obtaining, by a computing device, a plurality of annotations using the ontology and the grammar, each of the plurality of annotations corresponding to one of a plurality of text samples; performing, by the computing device, one or more quality assurance checks for at least one of the plurality of annotations, the ontology, or the grammar; generating, by the computing device, a list of one or more flagged annotations, each of the one or more flagged annotations corresponding to one of the plurality of annotations flagged during one of the one or more quality assurance checks; presenting, at a display device of the computing device, the list of flagged annotations; receiving, via a user input device of the computing device, user input modifying one of the one or more flagged annotations to obtain a modified annotation; and updating at least one of the grammar or the ontology based on the modified annotation; and wherein performance of the first one of the quality assurance checks comprises: comparing a first arrangement of a set of hypernyms in a first annotation of the plurality of annotations to a second arrangement of the set of hypernyms in a second annotation of the plurality of annotations; and configuring the list of flagged annotations to include the first annotation and the second annotation responsive to determine that the first arrangement of the set of hypernyms does not match the second arrangement of the set of hypernyms. 6. The method of claim 1 wherein performance of a second one of the quality assurance checks comprises: determining whether multiple grammar rules of the grammar parse an n-gram; and configuring the list of flagged annotations to include an annotation of the plurality of annotations corresponding to a text sample that includes the n-gram. | 0.624426 |
1. A computer-implemented method comprising: causing display of a set of events that are search results of a search query that specifies a plurality of commands, each event corresponding to a portion of raw machine data associated with a timestamp extracted from the portion of raw machine data, the display of the set of events being in a table format that includes: one or more columns, each column comprising data items of an event attribute, the data items being of the set of events; and a plurality of rows forming cells with the one or more columns, each cell displaying a textual representation of at least one of the data items of the event attribute of a corresponding column, the textual representation being selectable by a user, the textual representation including at least some of the portion of raw machine data of a corresponding event; based on a user selection of a text portion of the textual representation in a corresponding cell: causing display of a list of options corresponding to the selected text portion of the textual representation in the corresponding cell; and causing one or more commands to be added to the plurality of commands specified in the search query, wherein the one or more commands are based on an option that is selected from the list of options and the selected text portion of the textual representation in the corresponding cell. | 1. A computer-implemented method comprising: causing display of a set of events that are search results of a search query that specifies a plurality of commands, each event corresponding to a portion of raw machine data associated with a timestamp extracted from the portion of raw machine data, the display of the set of events being in a table format that includes: one or more columns, each column comprising data items of an event attribute, the data items being of the set of events; and a plurality of rows forming cells with the one or more columns, each cell displaying a textual representation of at least one of the data items of the event attribute of a corresponding column, the textual representation being selectable by a user, the textual representation including at least some of the portion of raw machine data of a corresponding event; based on a user selection of a text portion of the textual representation in a corresponding cell: causing display of a list of options corresponding to the selected text portion of the textual representation in the corresponding cell; and causing one or more commands to be added to the plurality of commands specified in the search query, wherein the one or more commands are based on an option that is selected from the list of options and the selected text portion of the textual representation in the corresponding cell. 21. The computer-implemented method of claim 1 , wherein the one or more commands are of a pipelined search language. | 0.912072 |
1. A computer program product for generating an appendix from document content comprising: a non-transitory computer readable storage medium, the document analytics system including program instructions executable by a processor, the program instructions comprising: program instructions to execute a zoning and structural analysis phase, wherein the zoning and structural analysis phase comprises program instructions to identify a document structure, and program instructions to store the identified document structure; in response to completing the zoning and structural analysis phase, program instructions to execute a semantic relationship extraction phase, wherein the semantic relationship extraction phase comprises program instructions to extract semantic relationships from the stored identified document structure, and program instructions to store the extracted semantic relationships, and wherein the semantic relationship extraction phase further comprises: program instructions to extract a semantic relationship from each stored identified sentence, wherein the semantic relationship comprises a subject, a predicate, and an object; responsive to extracting and identifying the semantic relationship, program instructions to apply statistical distribution analysis to record a position where the subject and the object appear in the document; program instructions to identify and eliminate a trivial relation, wherein the trivial relation does not relate to a main topic of the document and based on the trivial relation having at least one of: the subject being evenly distributed within a section of the document, wherein a section is selected from a group consisting of a sentence, a paragraph, a page, a chapter, and the document as a whole; and the object being evenly distributed within the section of the document; and program instructions to store a non-trivial relation in persistent storage; in response to completing the semantic relationship extraction phase, program instructions to execute an analytics and relevance determination phase wherein the analytics and relevance determination phase comprises program instructions to identify candidate appendix topics in the stored extracted semantic relationships based on a degree of interdependency between the semantic relationships and program instructions to store the identified candidate appendix topics; in response to completing the analytics and relevance determination phase, program instructions to execute a web mining phase wherein the web mining phase comprises program instructions to calculate a measure of relevance of the mined web page to the stored candidate appendix topics and eliminate non-relevant intermediate results; and based on the web mining phase returning results relevant to a topic of the document, program instructions to generate the appendix. | 1. A computer program product for generating an appendix from document content comprising: a non-transitory computer readable storage medium, the document analytics system including program instructions executable by a processor, the program instructions comprising: program instructions to execute a zoning and structural analysis phase, wherein the zoning and structural analysis phase comprises program instructions to identify a document structure, and program instructions to store the identified document structure; in response to completing the zoning and structural analysis phase, program instructions to execute a semantic relationship extraction phase, wherein the semantic relationship extraction phase comprises program instructions to extract semantic relationships from the stored identified document structure, and program instructions to store the extracted semantic relationships, and wherein the semantic relationship extraction phase further comprises: program instructions to extract a semantic relationship from each stored identified sentence, wherein the semantic relationship comprises a subject, a predicate, and an object; responsive to extracting and identifying the semantic relationship, program instructions to apply statistical distribution analysis to record a position where the subject and the object appear in the document; program instructions to identify and eliminate a trivial relation, wherein the trivial relation does not relate to a main topic of the document and based on the trivial relation having at least one of: the subject being evenly distributed within a section of the document, wherein a section is selected from a group consisting of a sentence, a paragraph, a page, a chapter, and the document as a whole; and the object being evenly distributed within the section of the document; and program instructions to store a non-trivial relation in persistent storage; in response to completing the semantic relationship extraction phase, program instructions to execute an analytics and relevance determination phase wherein the analytics and relevance determination phase comprises program instructions to identify candidate appendix topics in the stored extracted semantic relationships based on a degree of interdependency between the semantic relationships and program instructions to store the identified candidate appendix topics; in response to completing the analytics and relevance determination phase, program instructions to execute a web mining phase wherein the web mining phase comprises program instructions to calculate a measure of relevance of the mined web page to the stored candidate appendix topics and eliminate non-relevant intermediate results; and based on the web mining phase returning results relevant to a topic of the document, program instructions to generate the appendix. 4. The computer program product of claim 1 , wherein the analytics and relevance determination phase further comprises: program instructions to detect at least one interdependency between two or more non-trivial relations in the stored extracted semantic relationships; program instructions to graph the at least one interdependency between the two or more non-trivial relations, wherein the two or more non-trivial relations comprise nodes of a graph, and the at least one interdependency comprise an edge of the graph; and program instructions to identify candidate appendix topics, based on a degree of relatedness between the nodes of the graph, centrality, between-ness, and connected-ness; and program instructions to store the identified candidate appendix topics in persistent storage. | 0.5 |
1. A method for the automatic composition of music, the method comprising: receiving a plurality of input sound sequences containing sound frequencies with corresponding time duration; converting the plurality of input sound sequences to a finite state automaton using a system that allows over-generation; receiving exploration rules that constrain how the finite state automaton is to be traversed; creating a path marker data structure indexing a plurality of path markers, where each path marker contains a path marker history and a path marker registry; traversing the finite state automaton with a graph exploration procedure that uses the exploration rules and the plurality of path markers to determine path across the finite state automaton, such that the path marker history and the path marker registry of particular path markers are updated when traversing the finite state automaton; and storing the paths across the finite state automaton to the path marker data structure to define recorded path markers; wherein the recorded path markers that are not found in the plurality of input sound sequences define a new music composition. | 1. A method for the automatic composition of music, the method comprising: receiving a plurality of input sound sequences containing sound frequencies with corresponding time duration; converting the plurality of input sound sequences to a finite state automaton using a system that allows over-generation; receiving exploration rules that constrain how the finite state automaton is to be traversed; creating a path marker data structure indexing a plurality of path markers, where each path marker contains a path marker history and a path marker registry; traversing the finite state automaton with a graph exploration procedure that uses the exploration rules and the plurality of path markers to determine path across the finite state automaton, such that the path marker history and the path marker registry of particular path markers are updated when traversing the finite state automaton; and storing the paths across the finite state automaton to the path marker data structure to define recorded path markers; wherein the recorded path markers that are not found in the plurality of input sound sequences define a new music composition. 4. A method for automatic music composition as recited in claim 1 wherein the path marker registry is used to record links that are blocked. | 0.719693 |
1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user. | 1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user. 7. The method of claim 1 wherein the received supplemental information includes a document rendering characteristic observed in a previous text capture operation by said user and a corresponding document rendering characteristic observed in the distinguished text capture operation, and wherein the determined action is identifying different electronic documents as corresponding to the rendered documents in which the distinguished text capture operation and the previous text capture operation were performed based upon a difference between the document rendering characteristic observed in the previous text capture operation and the corresponding document rendering characteristic observed in the distinguished text capture operation. | 0.5 |
17. The system recited in claim 11 , wherein the editing action includes altering the first computer programming code portion associated with the first active tag indicator, wherein altering the first computer programming code portion associated with the first active tag indicator includes selection of one or more of the following: altering an event name that triggers execution of the first computer programming code portion when the associated webpage is rendered, altering a variable or selector from which to collect data during execution of such first computer programming code portion when the associated webpage is rendered, and/or altering a post-processing procedure for the collected data during execution of such first computer programming code portion when the associated webpage is rendered. | 17. The system recited in claim 11 , wherein the editing action includes altering the first computer programming code portion associated with the first active tag indicator, wherein altering the first computer programming code portion associated with the first active tag indicator includes selection of one or more of the following: altering an event name that triggers execution of the first computer programming code portion when the associated webpage is rendered, altering a variable or selector from which to collect data during execution of such first computer programming code portion when the associated webpage is rendered, and/or altering a post-processing procedure for the collected data during execution of such first computer programming code portion when the associated webpage is rendered. 18. The system of claim 17 , wherein the editing action includes the post-processing procedure, which includes analyzing the collected data for such first computer programming code portion, and wherein such analyzing includes protecting the privacy of users of the associated webpage, reducing an amount of the collected data, and/or categorizing the collected data. | 0.835165 |
1. A voice controlled wireless communication device system comprising: a wireless communication device that records a voice command, recited by a user, and that executes a software based application resident on the wireless communication device; one or more server computers that communicate with the wireless communication device, comprising at least one server based module for creation of a command to be executed on the wireless communication device; wherein said software based application communicates the voice command to said server computer; wherein the server computer initiates at least one speech recognition process to identify the voice command, constructs an application command based on the voice command and communicates the application command to the wireless communication device; wherein said software based application directs the application command communicated from the server computer to a corresponding application on the wireless communication device for execution; an additional server computer, wherein based on a type of voice command, the server computer directs the voice command to the additional server computer for processing; wherein the wireless communication device maintains a contact list, and the contact list is periodically transmitted and stored on the server computer; wherein the contact list stored in the server is accessible to the speech recognition process to assist in automatic translation of a given voice command that requires input from the contact list; and the contact list stored on the server is also provided to an interface for presenting the given voice command for manual review and identification, wherein the contact list stored on the server is automatically displayed via the interface in response to presenting the voice command for manual review. | 1. A voice controlled wireless communication device system comprising: a wireless communication device that records a voice command, recited by a user, and that executes a software based application resident on the wireless communication device; one or more server computers that communicate with the wireless communication device, comprising at least one server based module for creation of a command to be executed on the wireless communication device; wherein said software based application communicates the voice command to said server computer; wherein the server computer initiates at least one speech recognition process to identify the voice command, constructs an application command based on the voice command and communicates the application command to the wireless communication device; wherein said software based application directs the application command communicated from the server computer to a corresponding application on the wireless communication device for execution; an additional server computer, wherein based on a type of voice command, the server computer directs the voice command to the additional server computer for processing; wherein the wireless communication device maintains a contact list, and the contact list is periodically transmitted and stored on the server computer; wherein the contact list stored in the server is accessible to the speech recognition process to assist in automatic translation of a given voice command that requires input from the contact list; and the contact list stored on the server is also provided to an interface for presenting the given voice command for manual review and identification, wherein the contact list stored on the server is automatically displayed via the interface in response to presenting the voice command for manual review. 10. The system of claim 1 , wherein the software based application presents a list of potential commands to be recorded. | 0.658276 |
11. A computer program product, encoded on a computer-readable medium, operable to cause data processing apparatus to perform operations comprising: receiving a plurality of images each including a corresponding version of an identified candidate text region; aligning each candidate text region from the plurality of images to a high resolution grid; compositing the aligned candidate text regions to create a single superresolution image; and performing character recognition on the superresolution image to identify text. | 11. A computer program product, encoded on a computer-readable medium, operable to cause data processing apparatus to perform operations comprising: receiving a plurality of images each including a corresponding version of an identified candidate text region; aligning each candidate text region from the plurality of images to a high resolution grid; compositing the aligned candidate text regions to create a single superresolution image; and performing character recognition on the superresolution image to identify text. 18. The computer program product of claim 11 , where aligning the candidate text regions comprises aligning pixels of the candidate text regions using block matching. | 0.633508 |
1. A method for determining a class associated with an image, the method comprising: generating at least one image segment based on a segmentation of the image; determining a segmentation score for an image segment included in the at least one image segment based on a comparison of the image segment and a region of the image, the region of the image associated with the image segment; determining a confidence score for the image segment based on the segmentation score and a classification score, the classification score indicative of a similarity between the image segment and at least one class; determining a class associated with the image based on the confidence score; and outputting the class associated with the image. | 1. A method for determining a class associated with an image, the method comprising: generating at least one image segment based on a segmentation of the image; determining a segmentation score for an image segment included in the at least one image segment based on a comparison of the image segment and a region of the image, the region of the image associated with the image segment; determining a confidence score for the image segment based on the segmentation score and a classification score, the classification score indicative of a similarity between the image segment and at least one class; determining a class associated with the image based on the confidence score; and outputting the class associated with the image. 8. The method of claim 1 , further comprising determining the at least one class based on a comparison of the image segment with a plurality of classes, each of the plurality of classes associated with a character. | 0.924508 |
8. A system comprising: a processor; and a computer-readable storage medium having instruction stored which, when executed by the processor, result in the processor performing operations comprising: receiving, from a speech recognition system, recognized speech; identifying information about a speaker of the recognized speech from the recognized speech; and submitting the recognized speech and the information to a question-answering engine which selects and outputs a response associated with the recognized speech based on the recognized speech and the information. | 8. A system comprising: a processor; and a computer-readable storage medium having instruction stored which, when executed by the processor, result in the processor performing operations comprising: receiving, from a speech recognition system, recognized speech; identifying information about a speaker of the recognized speech from the recognized speech; and submitting the recognized speech and the information to a question-answering engine which selects and outputs a response associated with the recognized speech based on the recognized speech and the information. 9. The system of claim 8 , wherein the information comprises demographic features. | 0.595609 |
1. A method comprising: initiating a connection with a remote system upon detection by a speech recognition operation of a local system of a keyword in a speech input; storing a portion of the speech input into a local memory at the local system; transmitting the stored portion of the speech input from the local system to the remote system; and updating or modifying a set of recognizable keywords stored by the local system based on updates or modifications received from the remote system responsive to analysis of the stored portion of the speech input performed by a speech recognition operation of the remote system. | 1. A method comprising: initiating a connection with a remote system upon detection by a speech recognition operation of a local system of a keyword in a speech input; storing a portion of the speech input into a local memory at the local system; transmitting the stored portion of the speech input from the local system to the remote system; and updating or modifying a set of recognizable keywords stored by the local system based on updates or modifications received from the remote system responsive to analysis of the stored portion of the speech input performed by a speech recognition operation of the remote system. 9. The method of claim 1 , wherein analysis of the stored portion of the speech input by the remote system comprises analysis of language usage or acoustic properties of a voice. | 0.635463 |
9. A network-based computing system for in context localization permitting an end-user to view the appearance of textual language translations of an application in real-time, comprising: a. a translation system computer comprising a processor and a memory device operably connected to one another, and a plurality of computer-executable instructions stored on said memory device and executed by said processor, comprising: i. computer-executable instructions to convert application text that is selected by an end-user for translation from a first language to a second language with pseudo-language identifiers, wherein the pseudo-language identifiers comprise a sequence of characters indicating a string identifier at the translator server or in a resource file on an end user electronic computing device that the application text was imported from; ii. a database storing one or more end-user records comprising user data input, data input from third parties and/or external data sources, pseudo-language identifiers, and one or more textual language translations performed by the system; b. an application system computer comprising a processor and a memory device operably connected to one another, and a plurality of computer-executable instructions stored on said memory device and executed by said processor, comprising: i. computer-executable instructions for; substituting the pseudo-language identifiers for application text that is to be translated from a first language to a second language; replacing in response to the translator's running of the application, the pseudo-language identifiers with the text in the first language and making the text user selectable; launching, a localization editor in response to the translator selecting the translated text, the editor comprising a graphical user interface simultaneously displaying in real-time inputted textual translations or machine translations and the appearance of the translation in the application; storing the translated text within a memory of the application computer and/or the end-user electronic computing device; ii. a database storing one or more end-user records comprising user data input, pseudo-language identifiers, integration libraries, and application libraries; c. one or more end-user electronic computing devices in communication with the application and translation system computer over a network; d. a wired or wireless network connection between the application and translation system computer and the one or more end-user electronic computing devices; e. wherein in context localization is performable in web based applications, content websites, and non-web based applications comprising Android and iOS applications; and f. wherein the pseudo-language identifier comprises the format of: {reserved-word|string-identifier-at-the-server|:plural-form-of-the-source-string}. | 9. A network-based computing system for in context localization permitting an end-user to view the appearance of textual language translations of an application in real-time, comprising: a. a translation system computer comprising a processor and a memory device operably connected to one another, and a plurality of computer-executable instructions stored on said memory device and executed by said processor, comprising: i. computer-executable instructions to convert application text that is selected by an end-user for translation from a first language to a second language with pseudo-language identifiers, wherein the pseudo-language identifiers comprise a sequence of characters indicating a string identifier at the translator server or in a resource file on an end user electronic computing device that the application text was imported from; ii. a database storing one or more end-user records comprising user data input, data input from third parties and/or external data sources, pseudo-language identifiers, and one or more textual language translations performed by the system; b. an application system computer comprising a processor and a memory device operably connected to one another, and a plurality of computer-executable instructions stored on said memory device and executed by said processor, comprising: i. computer-executable instructions for; substituting the pseudo-language identifiers for application text that is to be translated from a first language to a second language; replacing in response to the translator's running of the application, the pseudo-language identifiers with the text in the first language and making the text user selectable; launching, a localization editor in response to the translator selecting the translated text, the editor comprising a graphical user interface simultaneously displaying in real-time inputted textual translations or machine translations and the appearance of the translation in the application; storing the translated text within a memory of the application computer and/or the end-user electronic computing device; ii. a database storing one or more end-user records comprising user data input, pseudo-language identifiers, integration libraries, and application libraries; c. one or more end-user electronic computing devices in communication with the application and translation system computer over a network; d. a wired or wireless network connection between the application and translation system computer and the one or more end-user electronic computing devices; e. wherein in context localization is performable in web based applications, content websites, and non-web based applications comprising Android and iOS applications; and f. wherein the pseudo-language identifier comprises the format of: {reserved-word|string-identifier-at-the-server|:plural-form-of-the-source-string}. 11. The computer system of claim 9 , further comprising on the applications server computer-executable instructions for: a. displaying on a graphical user interface the machine translation of the text; b. receiving input from the translator to accept it, or reject it and receiving a translator's manual input of the translated text in the second language; and, c. displaying the appearance of the translated text within the application co-located on the graphical user interface with the translator's input in step (b), and in response to the translator's selection of a link. | 0.5 |
21. The method of claim 18 wherein the authentication process comprises receiving identifying information from each of the plurality of student wireless communication devices, the method further comprising using the received identifying information from each of the plurality of student wireless communication devices to retrieve data associating a student identification with the identifying information from respective student wireless communication devices to thereby permit identification of students. | 21. The method of claim 18 wherein the authentication process comprises receiving identifying information from each of the plurality of student wireless communication devices, the method further comprising using the received identifying information from each of the plurality of student wireless communication devices to retrieve data associating a student identification with the identifying information from respective student wireless communication devices to thereby permit identification of students. 22. The method of claim 21 , further comprising providing an attendance list to the instructor wireless communication device using the student identification information associated with each of the plurality of student wireless communication devices that have been authenticated. | 0.899392 |
16. The method of claim 1 further comprising: providing at least one phonetic search criterion in association with a search query wherein the phonetic search criterion corresponds to phonetic content; identifying a matching portion of the phonetic index that meets the at least one phonetic search criterion; and taking an action in response to identifying the matching portion of the phonetic index. | 16. The method of claim 1 further comprising: providing at least one phonetic search criterion in association with a search query wherein the phonetic search criterion corresponds to phonetic content; identifying a matching portion of the phonetic index that meets the at least one phonetic search criterion; and taking an action in response to identifying the matching portion of the phonetic index. 17. The method of claim 16 further comprising providing source criteria identifying at least one source of the plurality of sources in association with the search query, and wherein identifying the matching portion of the phonetic index comprises identifying the matching portion of the phonetic index that meets the at least one phonetic search criterion and the source criteria in light of the association of the corresponding one of the plurality of sources with the phonemes in the sequence of phonemes, such that the matching portion of the phonetic index corresponds to a source identified by the source criteria. | 0.661593 |
3. The system of claim 1 , the computer readable medium further storing instructions that, when executed by the processor, further causes the processor to: receive a search query, wherein the search query includes at least one search phrase; receive, for the at least one search phrase, an indication from a user specifying to perform one of a noisy phrase search or a noiseless phrase search; process a search using the at least one search phrase, wherein the search can be performed as a noisy phrase search or as a noiseless phrase search; and output a search result. | 3. The system of claim 1 , the computer readable medium further storing instructions that, when executed by the processor, further causes the processor to: receive a search query, wherein the search query includes at least one search phrase; receive, for the at least one search phrase, an indication from a user specifying to perform one of a noisy phrase search or a noiseless phrase search; process a search using the at least one search phrase, wherein the search can be performed as a noisy phrase search or as a noiseless phrase search; and output a search result. 8. The system of claim 3 , wherein the search query includes both noisy search phrases and noiseless search phrases. | 0.922 |
1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. | 1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. 5. The system of claim 1 , wherein the one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message comprise: a functional magnetic resonance imaging (fMRI) device. | 0.653762 |
1. A method comprising: providing, by one or more processors and for presentation, an excerpt page of a document; providing, by the one or more processors and for presentation in the excerpt page, a plurality of links, each of the plurality of links being associated with a respective page of the document; receiving, by the one or more processors, a selection of a first link of the plurality of links presented in the excerpt page; providing, by the one or more processors and for presentation in the excerpt page, the respective page of the document associated with the first link based on the selection of the first link; modifying, by the one or more processors, the first link presented in the excerpt page, by replacing a portion of the first link with corresponding first link text, and including a first element next to the first link text and a second element next to the first link text, to create a modified first link based on the selection of the first link, the first element, when selected, causing a previous sequential page, with respect to the respective page associated with the first link, of the document to be presented in the excerpt page, and the second element, when selected, causing a next sequential page, with respect to the respective page associated with the first link, of the document to be presented in the excerpt page; receiving, by the one or more processors, a selection of a second link of the plurality of links presented in the excerpt page, the second link being different than the first link; replacing, by the one or more processors and based on receiving the selection of the second link, the modified first link presented in the excerpt page with the first link by removing the first element and the second element and replacing the first link text with the portion of the first link; providing, by the one or more processors and for presentation in the excerpt page, the respective page of the document associated with the second link based on the selection of the second link; and modifying, by the one or more processors, the second link presented in the excerpt page, by replacing a portion of the second link with corresponding second link text, and including a third element next to the second link text and a fourth element next to the second link text, to create a modified second link based on the selection of the second link. | 1. A method comprising: providing, by one or more processors and for presentation, an excerpt page of a document; providing, by the one or more processors and for presentation in the excerpt page, a plurality of links, each of the plurality of links being associated with a respective page of the document; receiving, by the one or more processors, a selection of a first link of the plurality of links presented in the excerpt page; providing, by the one or more processors and for presentation in the excerpt page, the respective page of the document associated with the first link based on the selection of the first link; modifying, by the one or more processors, the first link presented in the excerpt page, by replacing a portion of the first link with corresponding first link text, and including a first element next to the first link text and a second element next to the first link text, to create a modified first link based on the selection of the first link, the first element, when selected, causing a previous sequential page, with respect to the respective page associated with the first link, of the document to be presented in the excerpt page, and the second element, when selected, causing a next sequential page, with respect to the respective page associated with the first link, of the document to be presented in the excerpt page; receiving, by the one or more processors, a selection of a second link of the plurality of links presented in the excerpt page, the second link being different than the first link; replacing, by the one or more processors and based on receiving the selection of the second link, the modified first link presented in the excerpt page with the first link by removing the first element and the second element and replacing the first link text with the portion of the first link; providing, by the one or more processors and for presentation in the excerpt page, the respective page of the document associated with the second link based on the selection of the second link; and modifying, by the one or more processors, the second link presented in the excerpt page, by replacing a portion of the second link with corresponding second link text, and including a third element next to the second link text and a fourth element next to the second link text, to create a modified second link based on the selection of the second link. 7. The method of claim 1 , further comprising: providing, for presentation in the excerpt page, one or more advertisements associated with a business that sells the document, other documents associated with an author of the document, or other documents associated with a same topic as the document. | 0.678959 |
1. A method comprising: receiving, over a network, a data object that is associated with a user who is engaged in a search for employment, wherein the data object includes a résumé of the user and a requirement that is associated with the search; calculating, based on the data object, a score that indicates a likelihood of receiving an offer for an employment position that satisfies the requirement, wherein the score includes an estimated duration until the user receives the offer; generating a suggestion that identifies how the score may be increased; and sending the suggestion over the network to a computing device of the user; wherein the method is performed by one or more computing devices. | 1. A method comprising: receiving, over a network, a data object that is associated with a user who is engaged in a search for employment, wherein the data object includes a résumé of the user and a requirement that is associated with the search; calculating, based on the data object, a score that indicates a likelihood of receiving an offer for an employment position that satisfies the requirement, wherein the score includes an estimated duration until the user receives the offer; generating a suggestion that identifies how the score may be increased; and sending the suggestion over the network to a computing device of the user; wherein the method is performed by one or more computing devices. 4. The method of claim 1 wherein the suggestion includes an estimated increase of the score if the suggestion is fulfilled. | 0.621414 |
1. A method for routing a confirmation of receipt of a facsimile or portion thereof, comprising: analyzing, using a processor, text of a facsimile for at least one of a meaning and a context of the text; and routing one or more confirmations to one or more destinations based on the analysis, wherein routing the one or more confirmations comprises routing the one or more confirmations to one or more destinations other than a sender of the facsimile for communicating information to a human other than the sender of the facsimile, wherein the analysis does not include utilizing any optical character recognition (OCR) techniques, and wherein the analysis comprises using one or more techniques selected from the group consisting of: naïve Bayes classification; tf-idf weighting; latent semantic analysis; support vector machine analysis; k-nearest neighbor algorithmic analysis; and decision tree analysis. | 1. A method for routing a confirmation of receipt of a facsimile or portion thereof, comprising: analyzing, using a processor, text of a facsimile for at least one of a meaning and a context of the text; and routing one or more confirmations to one or more destinations based on the analysis, wherein routing the one or more confirmations comprises routing the one or more confirmations to one or more destinations other than a sender of the facsimile for communicating information to a human other than the sender of the facsimile, wherein the analysis does not include utilizing any optical character recognition (OCR) techniques, and wherein the analysis comprises using one or more techniques selected from the group consisting of: naïve Bayes classification; tf-idf weighting; latent semantic analysis; support vector machine analysis; k-nearest neighbor algorithmic analysis; and decision tree analysis. 20. A method as recited in claim 1 , wherein the facsimile text does not contain confirmation destination information, wherein the analysis includes classifying the text as a specific document type. | 0.825333 |
1. A method comprising: determining a target geographic feature that has insufficient targeting information associated therewith, wherein the insufficient targeting information is insufficient to provide targeted content associated with the target geographic feature, the target geographic feature defining a location; determining one or more similar geographic features to the target geographic feature, each similar geographic feature including targeting information and defining a different non-overlapping location from the target geographic location, wherein the one or more similar geographic features are determined based at least in part by identifying a geographic feature having one or more excess queries in common with the target geographic feature, wherein each excess query is a query associated with and exceeds an expected query count for each of the one or more similar geographic features and the target geographic feature; attributing targeting information associated with at least one of the one or more similar geographic features to the target geographic feature; and serving content responsive to queries that relate to the target geographic feature based at least in part on the attributed targeting information; wherein for each of the target geographic feature and the one or more similar geographic features, the expected query count associated with the query is computed as a function of a total number of queries received over a time period for the target geographic feature or the one or more similar geographic features and a query share associated with the query; wherein the query share is computed as a ratio of the number of times that the query was received from user devices in a baseline geographic region relative to a total number of queries that have been received from user devices in the baseline geographic region. | 1. A method comprising: determining a target geographic feature that has insufficient targeting information associated therewith, wherein the insufficient targeting information is insufficient to provide targeted content associated with the target geographic feature, the target geographic feature defining a location; determining one or more similar geographic features to the target geographic feature, each similar geographic feature including targeting information and defining a different non-overlapping location from the target geographic location, wherein the one or more similar geographic features are determined based at least in part by identifying a geographic feature having one or more excess queries in common with the target geographic feature, wherein each excess query is a query associated with and exceeds an expected query count for each of the one or more similar geographic features and the target geographic feature; attributing targeting information associated with at least one of the one or more similar geographic features to the target geographic feature; and serving content responsive to queries that relate to the target geographic feature based at least in part on the attributed targeting information; wherein for each of the target geographic feature and the one or more similar geographic features, the expected query count associated with the query is computed as a function of a total number of queries received over a time period for the target geographic feature or the one or more similar geographic features and a query share associated with the query; wherein the query share is computed as a ratio of the number of times that the query was received from user devices in a baseline geographic region relative to a total number of queries that have been received from user devices in the baseline geographic region. 2. The method of claim 1 where determining one or more similar geographic features includes determining one or more geographic features within a predetermined proximity of the target geographic feature. | 0.62382 |
19. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a web page that includes text and images; selecting a first subset of the images that are not excluded content-type images, wherein an excluded content-type image is an image that is boilerplate content or that is advertising content; determining, for each of the images in the first subset, (I) whether the image has a size ratio that is within a predetermined size ratio range, (II) whether the image has greater than a redetermined quantity of pixels or (III) whether the image is located between a defined minimum altitude and a defined maximum altitude on the web page; selecting a second subset of the images in the first subset based on the determinations for the images in the first subset; determining (i) a quantity of images in the second subset, and (ii) a ratio of the area of the web page that is covered by the images of the second subset to the total area of the web page; generating a score for the web page based at least on (i) the quantity of the images in the second subset, and (ii) the ratio of the area of the web page that is covered by the images to the total area of the web page; classifying the web page as a gallery web page based on the score for the web page meeting a predefined threshold; and based on classifying the web page as a gallery web page, formatting a search result that references the web page, among a set of search results that each reference a different web page, using a search result format that is designated for web pages that are classified as gallery web pages. | 19. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a web page that includes text and images; selecting a first subset of the images that are not excluded content-type images, wherein an excluded content-type image is an image that is boilerplate content or that is advertising content; determining, for each of the images in the first subset, (I) whether the image has a size ratio that is within a predetermined size ratio range, (II) whether the image has greater than a redetermined quantity of pixels or (III) whether the image is located between a defined minimum altitude and a defined maximum altitude on the web page; selecting a second subset of the images in the first subset based on the determinations for the images in the first subset; determining (i) a quantity of images in the second subset, and (ii) a ratio of the area of the web page that is covered by the images of the second subset to the total area of the web page; generating a score for the web page based at least on (i) the quantity of the images in the second subset, and (ii) the ratio of the area of the web page that is covered by the images to the total area of the web page; classifying the web page as a gallery web page based on the score for the web page meeting a predefined threshold; and based on classifying the web page as a gallery web page, formatting a search result that references the web page, among a set of search results that each reference a different web page, using a search result format that is designated for web pages that are classified as gallery web pages. 22. The medium of claim 19 , wherein generating a score for the web page comprises generating a score for the web page based on evaluating the quantity of images in the second subset against a minimum value. | 0.530495 |
22. A method for aggregating user interactions into a user profile, comprising: logging a plurality of user interactions at a plurality of websites in a network of affiliated websites; associating each of the plurality of user interactions logged at each of the plurality of websites with a respective user identifier; combining the plurality of logged user interactions from the plurality of websites in the network of affiliated websites; correlating the combined user interactions logged by the plurality of websites in the network of affiliated websites with respective users using the user identifiers associated with each of the logged user interactions; and generating a plurality of user profiles using the plurality of correlated user interactions. | 22. A method for aggregating user interactions into a user profile, comprising: logging a plurality of user interactions at a plurality of websites in a network of affiliated websites; associating each of the plurality of user interactions logged at each of the plurality of websites with a respective user identifier; combining the plurality of logged user interactions from the plurality of websites in the network of affiliated websites; correlating the combined user interactions logged by the plurality of websites in the network of affiliated websites with respective users using the user identifiers associated with each of the logged user interactions; and generating a plurality of user profiles using the plurality of correlated user interactions. 27. The method of claim 22 , wherein the user profile of the particular user comprises an interface type preference of the particular user. | 0.712635 |
1. A method for defining a service monitor for a web service, the method comprising: accepting by a processor a functional web service that operates as one of a plurality of functional web services all operating on a single server; including in the functional web service at least one monitor data collection function that records at least one monitor data element, the at least one monitor data element characterizing at least one operation of the functional web service, and the at least one monitor data element being made available to the monitoring service; defining at least one functional web service description language (WSDL) document for the functional web service; defining a monitor web service, separate from the functional web service, the monitor web service providing access to the at least one monitor data element recorded by the at least one data collection function included within the functional web service; and including, in the at least one functional web service description language (WSDL) document, a reference to a monitoring web service description language (WSDL) document defining the monitoring service, wherein the monitoring web service description language (WSDL) document is separate from the functional web service description language (WSDL) document. | 1. A method for defining a service monitor for a web service, the method comprising: accepting by a processor a functional web service that operates as one of a plurality of functional web services all operating on a single server; including in the functional web service at least one monitor data collection function that records at least one monitor data element, the at least one monitor data element characterizing at least one operation of the functional web service, and the at least one monitor data element being made available to the monitoring service; defining at least one functional web service description language (WSDL) document for the functional web service; defining a monitor web service, separate from the functional web service, the monitor web service providing access to the at least one monitor data element recorded by the at least one data collection function included within the functional web service; and including, in the at least one functional web service description language (WSDL) document, a reference to a monitoring web service description language (WSDL) document defining the monitoring service, wherein the monitoring web service description language (WSDL) document is separate from the functional web service description language (WSDL) document. 6. The method according to claim 1 , wherein the including a reference is automatically performed by a web service development tool. | 0.652832 |
14. A method comprising: on an Internet-enabled portable electronic device, obtaining digital image information, wherein the digital image information corresponds to a digital image, and wherein the digital image relates to a digital photograph; using one or more computers or computerized devices, utilizing one or more character recognition techniques, determining a URI or URL included within the digital image; and on the Internet-enabled portable electronic device, utilizing the URI or URL, accessing a Web page corresponding to the URI or URL. | 14. A method comprising: on an Internet-enabled portable electronic device, obtaining digital image information, wherein the digital image information corresponds to a digital image, and wherein the digital image relates to a digital photograph; using one or more computers or computerized devices, utilizing one or more character recognition techniques, determining a URI or URL included within the digital image; and on the Internet-enabled portable electronic device, utilizing the URI or URL, accessing a Web page corresponding to the URI or URL. 17. The method of claim 14 , comprising obtaining the digital image, wherein the URI or URL is contained within a visible rectangular box or other frame, and wherein the visible rectangular box or other frame facilitates recognition of the URI or URL. | 0.5 |
1. A method comprising: determining an original receiver operating characteristic (ROC) curve describing performance of a speech recognition system with respect to an original rate of false acceptance (FA) of the speech recognition system versus an original rate of correct acceptance (CA) of the speech recognition system; changing an algorithm used by the speech recognition system for sentence confidence scores, wherein changing the algorithm results in a new ROC curve with respect to a new rate of FA of the speech recognition system versus a new rate of CA of the speech recognition system; receiving a user specification of relative importance of the new rate of FA versus the new rate of CA; and based on the relative importance of the new rate of FA versus the new rate of CA, adjusting a confidence scoring functionality related to recognition reliability for a given input utterance, wherein at or above a given operating point of the speech recognition system, the new ROC curve reflects a double gain constraint relative to the original ROC curve, such that the new rate of FA is equal to or less than the original rate of FA, and the new rate of CA is equal to or greater than the original rate of CA. | 1. A method comprising: determining an original receiver operating characteristic (ROC) curve describing performance of a speech recognition system with respect to an original rate of false acceptance (FA) of the speech recognition system versus an original rate of correct acceptance (CA) of the speech recognition system; changing an algorithm used by the speech recognition system for sentence confidence scores, wherein changing the algorithm results in a new ROC curve with respect to a new rate of FA of the speech recognition system versus a new rate of CA of the speech recognition system; receiving a user specification of relative importance of the new rate of FA versus the new rate of CA; and based on the relative importance of the new rate of FA versus the new rate of CA, adjusting a confidence scoring functionality related to recognition reliability for a given input utterance, wherein at or above a given operating point of the speech recognition system, the new ROC curve reflects a double gain constraint relative to the original ROC curve, such that the new rate of FA is equal to or less than the original rate of FA, and the new rate of CA is equal to or greater than the original rate of CA. 8. The method of claim 1 , wherein the confidence scoring functionality includes confidence score thresholds that define for a given set of circumstances whether to accept, reject, or confirm a given input utterance. | 0.579747 |
2. A query generation system comprising: an element rank and inference engine in communication with a computing system and a user interface, the element rank and inference engine operable to: receive a plurality of terms from the user interface; derive, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not in the plurality of received terms; modify the plurality of terms according to a specified criteria; display the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generate a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmit the query to a web search engine. | 2. A query generation system comprising: an element rank and inference engine in communication with a computing system and a user interface, the element rank and inference engine operable to: receive a plurality of terms from the user interface; derive, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not in the plurality of received terms; modify the plurality of terms according to a specified criteria; display the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generate a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmit the query to a web search engine. 5. The query generation system of claim 2 , wherein the query generation system is further operable to receive, following display of the modified plurality of terms on the user interface, an additional term from the user interface. | 0.534355 |
10. A computer readable medium, said computer readable medium comprising a set of computer instructions implementing a system for ranking an electronic advertisement relative to target content, said set of computer instructions performing the steps of: extracting a title and keywords from said electronic advertisement and a landing page associated with said electronic advertisement for creating a first set of elements, and keywords from said target content on said web page for creating a second set of elements, said first and second sets of elements comprising a plurality of multi-word expressions; calculating, using a computer, a first content match feature using said first and second set of elements, the content match feature to evaluate how well said electronic advertisement matches said target content on said web page; calculating, using a computer, a second content match feature using said first and second set of elements, said second content match feature comprising a semantic association feature based on a degree of correlation between pairs of said plurality of words; and processing said first content match feature and said second content match features with a machine learning model to output a relevance score of said electronic advertisement relative to said target content. | 10. A computer readable medium, said computer readable medium comprising a set of computer instructions implementing a system for ranking an electronic advertisement relative to target content, said set of computer instructions performing the steps of: extracting a title and keywords from said electronic advertisement and a landing page associated with said electronic advertisement for creating a first set of elements, and keywords from said target content on said web page for creating a second set of elements, said first and second sets of elements comprising a plurality of multi-word expressions; calculating, using a computer, a first content match feature using said first and second set of elements, the content match feature to evaluate how well said electronic advertisement matches said target content on said web page; calculating, using a computer, a second content match feature using said first and second set of elements, said second content match feature comprising a semantic association feature based on a degree of correlation between pairs of said plurality of words; and processing said first content match feature and said second content match features with a machine learning model to output a relevance score of said electronic advertisement relative to said target content. 16. The computer readable medium as set forth in claim 10 wherein said second content match feature comprises feature comprises point-wise mutual information. | 0.507042 |
1. In a computing system comprising a microphone array and an image sensor, a method of operating a speech recognition input system, the method comprising: receiving speech recognition data as an output from a speech recognition stage of an audio processing pipeline, the speech recognition data comprising a recognized speech segment and confidence data comprising a recognition confidence value that represents a confidence in a certainty of a match of the recognized speech segment to a speech pattern; receiving acoustic locational data as an output from a digital audio processing stage of the audio processing pipeline, the acoustic locational data related to a location of origin of the recognized speech segment as determined via signals from the microphone array; receiving image data comprising visual locational information related to a location of each person located in a field of view of the image sensor; comparing the acoustic locational data to the visual locational information to determine whether the recognized speech segment originated from a person in the field of view of the image sensor; and adjusting the confidence data based upon whether the recognized speech segment is determined to have originated from a person in the field of view of the image sensor. | 1. In a computing system comprising a microphone array and an image sensor, a method of operating a speech recognition input system, the method comprising: receiving speech recognition data as an output from a speech recognition stage of an audio processing pipeline, the speech recognition data comprising a recognized speech segment and confidence data comprising a recognition confidence value that represents a confidence in a certainty of a match of the recognized speech segment to a speech pattern; receiving acoustic locational data as an output from a digital audio processing stage of the audio processing pipeline, the acoustic locational data related to a location of origin of the recognized speech segment as determined via signals from the microphone array; receiving image data comprising visual locational information related to a location of each person located in a field of view of the image sensor; comparing the acoustic locational data to the visual locational information to determine whether the recognized speech segment originated from a person in the field of view of the image sensor; and adjusting the confidence data based upon whether the recognized speech segment is determined to have originated from a person in the field of view of the image sensor. 7. The method of claim 1 , further comprising receiving a speech input of a keyword before receiving the recognized speech segment, and wherein adjusting the confidence data comprises adjusting the recognition confidence value based upon an amount of time that passed between receiving the speech input of the keyword and receiving the recognized speech segment. | 0.660154 |
12. The memory controller according to claim 11 , wherein the encoding circuitry is configured to individually encode the component code words in a first subset of the component code words, and to generate the component code words in a second subset of the component code words, which comprises the component code words not belonging to the first subset, using joint encoding. | 12. The memory controller according to claim 11 , wherein the encoding circuitry is configured to individually encode the component code words in a first subset of the component code words, and to generate the component code words in a second subset of the component code words, which comprises the component code words not belonging to the first subset, using joint encoding. 14. The memory controller according to claim 12 , wherein the encoding circuitry is configured to jointly encode the second subset of the component code words by multiplying a vector comprising at least part of the component code words of the first subset by a predefined matrix. | 0.708163 |
1. A method for providing data based on object relevance via at least one computing device, comprising: receiving one or more query terms from a user via a communications interface associated with the at least one computing device; and executing instructions stored in memory by a processor to: determine a preliminary relevance of one or more objects associated with an enterprise system based on the query terms, assign at least one rating to the one or more objects based on the preliminary relevance, propogate the preliminary relevance among the one or more objects; and establish an overall relevance of the one or more objects based on the at least one rating, utilizing the preliminary relevance and the propogation, rank the one or more objects according to the overall relevance, provide data as search results comprising the one or more objects according to the ranking to the user, filter the search results based on at least one selected, dynamically generated filter associated with the one or more objects; and transmit to display the search results to the at least one computing device via the communications interface. | 1. A method for providing data based on object relevance via at least one computing device, comprising: receiving one or more query terms from a user via a communications interface associated with the at least one computing device; and executing instructions stored in memory by a processor to: determine a preliminary relevance of one or more objects associated with an enterprise system based on the query terms, assign at least one rating to the one or more objects based on the preliminary relevance, propogate the preliminary relevance among the one or more objects; and establish an overall relevance of the one or more objects based on the at least one rating, utilizing the preliminary relevance and the propogation, rank the one or more objects according to the overall relevance, provide data as search results comprising the one or more objects according to the ranking to the user, filter the search results based on at least one selected, dynamically generated filter associated with the one or more objects; and transmit to display the search results to the at least one computing device via the communications interface. 7. The method recited in claim 1 , wherein filtering the search results comprises providing a dynamic search result display. | 0.620486 |
9. A computer system for customizing help content, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a request for help content, wherein the request for help content is received after an error is encountered while performing a task with a software product, the request for help content identifying a topic of interest based on the error; program instructions to identify an annotated help file that corresponds to the request for help content; program instructions to identify a plurality of variables in the identified annotated help file, wherein at least a first variable of the plurality of variables includes another variable of the plurality of variables within the first variable; program instructions to retrieve a value for each of the plurality of variables from the software product, wherein the software product queries resources to obtain the value for each of the plurality of variables, wherein the retrieved values include at least two distinct values each of which is a server level parameter value retrieved from a product configuration file, an application user-level parameter value retrieved from a product configuration file, a database level parameter value retrieved from a services file, or a database level parameter value retrieved from a database configuration file; and program instructions to replace each of the plurality of variables in the identified annotated help file with the retrieved value to generate a customized help content. | 9. A computer system for customizing help content, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a request for help content, wherein the request for help content is received after an error is encountered while performing a task with a software product, the request for help content identifying a topic of interest based on the error; program instructions to identify an annotated help file that corresponds to the request for help content; program instructions to identify a plurality of variables in the identified annotated help file, wherein at least a first variable of the plurality of variables includes another variable of the plurality of variables within the first variable; program instructions to retrieve a value for each of the plurality of variables from the software product, wherein the software product queries resources to obtain the value for each of the plurality of variables, wherein the retrieved values include at least two distinct values each of which is a server level parameter value retrieved from a product configuration file, an application user-level parameter value retrieved from a product configuration file, a database level parameter value retrieved from a services file, or a database level parameter value retrieved from a database configuration file; and program instructions to replace each of the plurality of variables in the identified annotated help file with the retrieved value to generate a customized help content. 14. The computer system of claim 9 , wherein the retrieved values include a port configuration. | 0.541223 |
8. A system, comprising, an underlying database; and a runtime component executing on a processor, configured to: receive a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in the underlying database; retrieve, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and perform the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation. | 8. A system, comprising, an underlying database; and a runtime component executing on a processor, configured to: receive a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in the underlying database; retrieve, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and perform the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation. 11. The system of claim 8 , wherein the at least one instance of the model entity represents an individual, and wherein the linking function identifies additional instances of the model entity that represent individuals sharing a consanguineous relationship with the individual represented by the at least one instance of the model entity. | 0.556555 |
1. A search system for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the search system comprising: a result pipeline extending through the search system; a number of pipelined search engines, each having an input to selectively receive the input string of characters from a data pipeline, and each to selectively output one of a number of tokens onto the result pipeline in response to a match between the input string of characters and a corresponding sub-expression, wherein each unique sub-expression is assigned to a corresponding one of the tokens; and a token stitcher, having an input to receive the tokens from the result pipeline, to combine the tokens to generate an output match signal indicating whether the input string of characters matches the regular expression, wherein the regular expression comprises an unbounded sub-expression, and the unbounded sub-expression is delegated to the token stitcher for processing without utilizing sources of the pipelined search engines and wherein the pipelined search engines and the token stitcher are implemented by at least one processor-based computing device. | 1. A search system for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the search system comprising: a result pipeline extending through the search system; a number of pipelined search engines, each having an input to selectively receive the input string of characters from a data pipeline, and each to selectively output one of a number of tokens onto the result pipeline in response to a match between the input string of characters and a corresponding sub-expression, wherein each unique sub-expression is assigned to a corresponding one of the tokens; and a token stitcher, having an input to receive the tokens from the result pipeline, to combine the tokens to generate an output match signal indicating whether the input string of characters matches the regular expression, wherein the regular expression comprises an unbounded sub-expression, and the unbounded sub-expression is delegated to the token stitcher for processing without utilizing sources of the pipelined search engines and wherein the pipelined search engines and the token stitcher are implemented by at least one processor-based computing device. 3. The search system of claim 1 , wherein none of the pipelined search engines process tokens generated by the pipelined search engines. | 0.693765 |
1. A method of facilitating interaction between users of an electronic community, comprising: reviewing a user activity log for each user in the electronic community, each user having an associated user profile stored in a user profile and relationship database; executing a natural language parser to extract noun phrases from the each user activity log; updating the user profiles from the extracted noun phrases, a keyword being associated with each extracted noun phrase, said updating based on a usage frequency of the extracted noun phrases and an importance value of the keywords; storing the updated user profiles in the user profile and relationship database; executing a similarity based clustering algorithm to generate clusters of the updated user profiles, each cluster consisting of a group of users of the users in the electronic community, each cluster representing a relationship between the users in each group; and storing each cluster in the user profile and relationship database, wherein a digital hierarchical dictionary comprises synsets, each synset being a set of cognitive synonyms consisting of noun phrases, said synsets being interlinked into a semantic hierarchical tree within the digital hierarchical dictionary, wherein the keyword associated with each extracted noun phrase is in a synset within the semantic hierarchical tree, wherein the similarity based clustering algorithm comprises a member importance function and a member similarity function, wherein the member importance function ascertains an importance value of keywords as a depth of said keywords in the semantic hierarchical tree, wherein the member similarity function ascertains a similarity distance between keywords as a path distance between said keywords in the semantic hierarchical tree, and wherein said executing the similarity based clustering algorithm comprises: using the member importance function and the member similarity function to ascertain the clusters. | 1. A method of facilitating interaction between users of an electronic community, comprising: reviewing a user activity log for each user in the electronic community, each user having an associated user profile stored in a user profile and relationship database; executing a natural language parser to extract noun phrases from the each user activity log; updating the user profiles from the extracted noun phrases, a keyword being associated with each extracted noun phrase, said updating based on a usage frequency of the extracted noun phrases and an importance value of the keywords; storing the updated user profiles in the user profile and relationship database; executing a similarity based clustering algorithm to generate clusters of the updated user profiles, each cluster consisting of a group of users of the users in the electronic community, each cluster representing a relationship between the users in each group; and storing each cluster in the user profile and relationship database, wherein a digital hierarchical dictionary comprises synsets, each synset being a set of cognitive synonyms consisting of noun phrases, said synsets being interlinked into a semantic hierarchical tree within the digital hierarchical dictionary, wherein the keyword associated with each extracted noun phrase is in a synset within the semantic hierarchical tree, wherein the similarity based clustering algorithm comprises a member importance function and a member similarity function, wherein the member importance function ascertains an importance value of keywords as a depth of said keywords in the semantic hierarchical tree, wherein the member similarity function ascertains a similarity distance between keywords as a path distance between said keywords in the semantic hierarchical tree, and wherein said executing the similarity based clustering algorithm comprises: using the member importance function and the member similarity function to ascertain the clusters. 3. The method of claim 1 , wherein the similarity based clustering algorithm uses a similarity threshold to constrain a total number of clusters returned from said executing the similarity based clustering algorithm, and wherein said executing the similarity based clustering algorithm comprises: increasing the similarity threshold to decrease the total number of clusters returned from said executing the similarity based clustering algorithm; or decreasing the similarity threshold to increase the total number of clusters returned from said executing the similarity based clustering algorithm. | 0.72417 |
1. A system for teaching phonemic awareness, the system comprising: a plurality of phonemes, each phoneme comprising a unique sound and an indivisible unit of sound in a spoken language; a plurality of graphemes, each grapheme comprising a written representation of one of the plurality of phonemes; a plurality of distinct graphical images; a plurality of unique names: each unique name associated with only one of the graphical images; each graphical image associated with only one of the unique names: and each unique name comprising a unique grouping of multiple graphemes selected from the plurality of graphemes; a plurality of sets of display pieces, each set of display pieces comprising: one of the graphical images and the unique name associated with that graphical image; and a plurality of individual display pieces and each individual display piece comprising; at least a portion of the graphical image associated with the set of display pieces; and one or more graphemes from the unique grouping of multiple graphemes constituting the unique name associated with that graphical image; wherein each grapheme and its associated phoneme is separately represented within any given individual display piece; and a predefined instructional environment, the instructional environment comprising a predefined spatial context and predefined rules governing acquisition, dispersement and utilization of individual display pieces within the predefined spatial context. | 1. A system for teaching phonemic awareness, the system comprising: a plurality of phonemes, each phoneme comprising a unique sound and an indivisible unit of sound in a spoken language; a plurality of graphemes, each grapheme comprising a written representation of one of the plurality of phonemes; a plurality of distinct graphical images; a plurality of unique names: each unique name associated with only one of the graphical images; each graphical image associated with only one of the unique names: and each unique name comprising a unique grouping of multiple graphemes selected from the plurality of graphemes; a plurality of sets of display pieces, each set of display pieces comprising: one of the graphical images and the unique name associated with that graphical image; and a plurality of individual display pieces and each individual display piece comprising; at least a portion of the graphical image associated with the set of display pieces; and one or more graphemes from the unique grouping of multiple graphemes constituting the unique name associated with that graphical image; wherein each grapheme and its associated phoneme is separately represented within any given individual display piece; and a predefined instructional environment, the instructional environment comprising a predefined spatial context and predefined rules governing acquisition, dispersement and utilization of individual display pieces within the predefined spatial context. 7. The system of claim 1 , wherein each unique name comprises a single syllable word. | 0.611325 |
2. An apparatus for determining age categories of people, comprising: a) means for annotating a facial image database according to the demographics classes of the individual face, b) means for training a plurality of learning machines so that each learning machine outputs auxiliary demographics class information and age information of any given facial image, c) means for detecting and tracking a facial image from the input image frame, d) means for processing said facial image to extract image features, and e) means for processing said image features obtained from said facial image using classification techniques for determining age or age categories, whereby the age classes can be any partition based on age in multiple groups, wherein the apparatus further comprises means for determining the target outputs of the plurality of learning machines so that each learning machine maps a first input data, whose facial images belong to a first auxiliary demographics class, to first vector-valued points on a manifold in the space of facial images, whereas each learning machine maps a second input data, whose facial images do not belong to a first auxiliary demographics class, to second vector-valued points away from the manifold. | 2. An apparatus for determining age categories of people, comprising: a) means for annotating a facial image database according to the demographics classes of the individual face, b) means for training a plurality of learning machines so that each learning machine outputs auxiliary demographics class information and age information of any given facial image, c) means for detecting and tracking a facial image from the input image frame, d) means for processing said facial image to extract image features, and e) means for processing said image features obtained from said facial image using classification techniques for determining age or age categories, whereby the age classes can be any partition based on age in multiple groups, wherein the apparatus further comprises means for determining the target outputs of the plurality of learning machines so that each learning machine maps a first input data, whose facial images belong to a first auxiliary demographics class, to first vector-valued points on a manifold in the space of facial images, whereas each learning machine maps a second input data, whose facial images do not belong to a first auxiliary demographics class, to second vector-valued points away from the manifold. 15. The apparatus according to claim 2 , wherein the apparatus further comprises means for setting up a plurality of learning machines so that each learning machine represents an auxiliary demographics class, whereby the auxiliary demographics class comprises facial images having the same gender and ethnicity classes. | 0.635817 |
7. A system, comprising: one or more processors; and one or more memories having stored therein instructions that, upon execution by the one or more processors, cause the one or more processors to perform operations comprising: identifying a plurality of user devices associated with a user of a document management and collaboration system on which the user has had a user session; determining that one or more documents associated with the user that were downloaded to the plurality of user devices from the document management and collaboration system should be deleted from the plurality of user devices; causing a targeted deletion of the one or more documents from the plurality of user devices; and receiving, from the plurality of user devices, indications of successful deletion of the one or more documents. | 7. A system, comprising: one or more processors; and one or more memories having stored therein instructions that, upon execution by the one or more processors, cause the one or more processors to perform operations comprising: identifying a plurality of user devices associated with a user of a document management and collaboration system on which the user has had a user session; determining that one or more documents associated with the user that were downloaded to the plurality of user devices from the document management and collaboration system should be deleted from the plurality of user devices; causing a targeted deletion of the one or more documents from the plurality of user devices; and receiving, from the plurality of user devices, indications of successful deletion of the one or more documents. 8. The system of claim 7 , wherein the plurality of user devices are identified based on hardware or software configuration information for the plurality of user devices. | 0.70284 |
15. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform: sending a call prompt message to a user after the user has answered a call, the call prompt message soliciting a user response; receiving a spoken call greeting from the user in response to the call prompt message, the spoken call greeting comprising at least one initial utterance; performing an initial determination as to whether the at least one initial utterance of the spoken call greeting is indicative of a language preference via a first language preference characterization operation; assigning an initial numerical confidence level value to the at least one initial utterance by retrieving and matching at least one pre-stored word or phrase to the at least one initial utterance, wherein the initial numerical confidence level is based on a relative strength of the at least one initial utterance being indicative of the language preference; and confirming the initial determination based on at least one additional utterance spoken after the at least one initial utterance by performing at least one additional language preference characterization operation to the at least one additional utterance spoken. | 15. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform: sending a call prompt message to a user after the user has answered a call, the call prompt message soliciting a user response; receiving a spoken call greeting from the user in response to the call prompt message, the spoken call greeting comprising at least one initial utterance; performing an initial determination as to whether the at least one initial utterance of the spoken call greeting is indicative of a language preference via a first language preference characterization operation; assigning an initial numerical confidence level value to the at least one initial utterance by retrieving and matching at least one pre-stored word or phrase to the at least one initial utterance, wherein the initial numerical confidence level is based on a relative strength of the at least one initial utterance being indicative of the language preference; and confirming the initial determination based on at least one additional utterance spoken after the at least one initial utterance by performing at least one additional language preference characterization operation to the at least one additional utterance spoken. 16. The non-transitory computer readable storage medium of claim 15 , wherein the processor is further configured to perform calling the user via the call processing device. | 0.575286 |
9. A non-transitory computer-readable medium comprising computer program code that, when executed by a communications system including a communications server in communication with one or more communications devices, enables the communications system to perform the following method for optimizing a message text: receiving on a communications server a message text comprising a plurality of words or word phrases that combine together as non-overlapping parts of the message text; treating the non-overlapping words or word phrases of the message text as multiple independent variables that are reduced to a message vector having each of the multiple independent variables as components of the message vector; automatically creating on the communications server a plurality of lexical variants of the message text, wherein the lexical variants are created by replacing a word or word phrase for each of the multiple independent variables with one or more alternate words or word phrases based on one or more value-changing rules being applied to the received word or word phrase in the message text, the lexical variants for each of the multiple independent variables being reduced to a lexical vector such that the message vector is made up of variable-sized lexical vectors; sending each of the plurality of created lexical variants of the message text to the one or more communications devices; measuring a response rate for each sent lexical variant of the message text; identifying one or more lexical variants having the best performing measured response rates for each of the lexical vectors; automatically creating on the communications server syntactical variants of the identified best performing lexical variants by rearranging the lexical vectors within the message vector based on one or more position-changing rules; sending a plurality of the syntactical variants of the identified best performing lexical variants to the one or more communications devices, wherein only grammatically-correct syntactical variants are sent; measuring a response rate for each of the sent syntactical variants; and identifying a message text having the highest measured response rate for the sent syntactical variants. | 9. A non-transitory computer-readable medium comprising computer program code that, when executed by a communications system including a communications server in communication with one or more communications devices, enables the communications system to perform the following method for optimizing a message text: receiving on a communications server a message text comprising a plurality of words or word phrases that combine together as non-overlapping parts of the message text; treating the non-overlapping words or word phrases of the message text as multiple independent variables that are reduced to a message vector having each of the multiple independent variables as components of the message vector; automatically creating on the communications server a plurality of lexical variants of the message text, wherein the lexical variants are created by replacing a word or word phrase for each of the multiple independent variables with one or more alternate words or word phrases based on one or more value-changing rules being applied to the received word or word phrase in the message text, the lexical variants for each of the multiple independent variables being reduced to a lexical vector such that the message vector is made up of variable-sized lexical vectors; sending each of the plurality of created lexical variants of the message text to the one or more communications devices; measuring a response rate for each sent lexical variant of the message text; identifying one or more lexical variants having the best performing measured response rates for each of the lexical vectors; automatically creating on the communications server syntactical variants of the identified best performing lexical variants by rearranging the lexical vectors within the message vector based on one or more position-changing rules; sending a plurality of the syntactical variants of the identified best performing lexical variants to the one or more communications devices, wherein only grammatically-correct syntactical variants are sent; measuring a response rate for each of the sent syntactical variants; and identifying a message text having the highest measured response rate for the sent syntactical variants. 10. The non-transitory computer-readable medium of claim 9 , wherein only a subset of the created lexical variants of the message text is sent to the one or more communications devices and a D-optimal design is used to determine the subset. | 0.521937 |
7. A computer-implemented method, comprising: under control of one or more processors configured with executable instructions, receiving, from a device of an author and via a content ingestion service associated with a network, an electronic book having first body text and first metadata; normalizing the electronic book by at least one of removing illustrations from the electronic book, removing extraneous characters from the electronic book, or converting characters of the electronic book to a single case; comparing the first metadata of the electronic book with second metadata corresponding to other books to identify one or more candidate title sets of which the electronic book may be a member; determining that a number of the one or more candidate title sets meets or exceeds a pre-determined number of candidate title sets; and based at least partly on the determining that the number of the one or more candidate title sets meets or exceeds the pre-determined number of candidate title sets, comparing the first body text of the electronic book with second body text of the one or more candidate title sets to determine that the electronic book is a member of the one or more candidate title sets. | 7. A computer-implemented method, comprising: under control of one or more processors configured with executable instructions, receiving, from a device of an author and via a content ingestion service associated with a network, an electronic book having first body text and first metadata; normalizing the electronic book by at least one of removing illustrations from the electronic book, removing extraneous characters from the electronic book, or converting characters of the electronic book to a single case; comparing the first metadata of the electronic book with second metadata corresponding to other books to identify one or more candidate title sets of which the electronic book may be a member; determining that a number of the one or more candidate title sets meets or exceeds a pre-determined number of candidate title sets; and based at least partly on the determining that the number of the one or more candidate title sets meets or exceeds the pre-determined number of candidate title sets, comparing the first body text of the electronic book with second body text of the one or more candidate title sets to determine that the electronic book is a member of the one or more candidate title sets. 10. The computer-implemented method of claim 7 , wherein the first metadata of the electronic book and the second metadata corresponding to the other books comprises multiple data fields. | 0.880478 |
13. A method of controlling a mobile device, the method comprising: recognizing a conversation between users through mobile devices; verifying an intent of at least one user among the users based on the recognition result; and executing an additional function corresponding to the verified user's intent in a mobile device of the user. | 13. A method of controlling a mobile device, the method comprising: recognizing a conversation between users through mobile devices; verifying an intent of at least one user among the users based on the recognition result; and executing an additional function corresponding to the verified user's intent in a mobile device of the user. 14. The method of claim 13 , wherein the executing of the additional function searches for predetermined information through the Internet and displays the search result when the verified user's intent is to search for the predetermined information. | 0.800448 |
17. A method for distributed data annotation, comprising: receiving source data using a distributed data annotation server system, where the source data comprises one or more pieces of source data; selecting one or more annotators for at least one piece of source data using the distributed data annotation server system; creating one or more annotation tasks for the selected annotators and at least one piece of source data using the distributed data annotation server system; requesting one or more annotations for at least one piece of source data using the created annotation tasks and the distributed data annotation server system; receiving annotations for at least one piece of source data using the distributed data annotation server system; determining source data metadata for at least one piece of source data using the received annotations and the distributed data annotation server system, where the source data metadata includes source data characteristics; generating annotator metadata for at least one annotator using the received annotations, at least one piece of source data, and the distributed data annotation server system, where the annotator metadata includes identified annotator characteristics; and estimating the ground truth for at least one piece of source data using the source data metadata, the annotator metadata, and the distributed data annotation server system. | 17. A method for distributed data annotation, comprising: receiving source data using a distributed data annotation server system, where the source data comprises one or more pieces of source data; selecting one or more annotators for at least one piece of source data using the distributed data annotation server system; creating one or more annotation tasks for the selected annotators and at least one piece of source data using the distributed data annotation server system; requesting one or more annotations for at least one piece of source data using the created annotation tasks and the distributed data annotation server system; receiving annotations for at least one piece of source data using the distributed data annotation server system; determining source data metadata for at least one piece of source data using the received annotations and the distributed data annotation server system, where the source data metadata includes source data characteristics; generating annotator metadata for at least one annotator using the received annotations, at least one piece of source data, and the distributed data annotation server system, where the annotator metadata includes identified annotator characteristics; and estimating the ground truth for at least one piece of source data using the source data metadata, the annotator metadata, and the distributed data annotation server system. 27. The method of claim 17 , further comprising determining a confidence threshold value regarding the ground truth of at least one piece of source data using the distributed data annotation server system. | 0.648279 |
12. The method of claim 1 , comprising generating the location-interest graph comprising: identifying a node for the location-interest graph comprising a geographical location; identifying an interest level for the node; identify a stay time for the node; and identifying an edge for the location-interest graph comprising a travel trajectory between the node and a second node in the location-interest graph. | 12. The method of claim 1 , comprising generating the location-interest graph comprising: identifying a node for the location-interest graph comprising a geographical location; identifying an interest level for the node; identify a stay time for the node; and identifying an edge for the location-interest graph comprising a travel trajectory between the node and a second node in the location-interest graph. 13. The method of claim 12 , identifying the stay time comprising identifying a median stay time using a plurality of stay times from the one or more historical travel sequences. | 0.974125 |
1. A method of generating annotation tags for a digital image characterized by: maintaining a library of human-meaningful words or phrases organized as category entries according to a number of defined image description categories; receiving context metadata for the digital image that is associated with capture of the digital image; selecting particular category entries as vocabulary metadata for the digital image by mapping the context metadata into the library; generating annotation tags for the digital image by logically combining the vocabulary metadata according to a defined set of deductive logic rules that are predicated on the defined image description categories, said defined set of deductive logic rules comprising a set of conditional tests predicated on variable entries for one or more of the defined image description categories, such that said generating annotation tags for the digital image comprises substituting the category entries making up the vocabulary metadata as values for corresponding ones of the variable entries, and then logically evaluating the set of conditional tests according to the substituted category entries; determining confidence or fuzzy logic weighting values from the context metadata, said confidence or fuzzy logic weighting values numerically expressing the extents to which given ones of the substituted category entries apply to the digital image; and ranking the generated annotation tags from most likely to least likely, in terms of applicability to the digital image, according to the confidence or fuzzy logic weighting values, or incorporating the confidence or fuzzy logic weighting values into said logical evaluation of the set of conditional tests, whereby the truthfulness of each conditional evaluation depends on the confidence or fuzzy logic weighting values, such that the generated annotation tags correspond to higher-weighted category entries or combinations thereof. | 1. A method of generating annotation tags for a digital image characterized by: maintaining a library of human-meaningful words or phrases organized as category entries according to a number of defined image description categories; receiving context metadata for the digital image that is associated with capture of the digital image; selecting particular category entries as vocabulary metadata for the digital image by mapping the context metadata into the library; generating annotation tags for the digital image by logically combining the vocabulary metadata according to a defined set of deductive logic rules that are predicated on the defined image description categories, said defined set of deductive logic rules comprising a set of conditional tests predicated on variable entries for one or more of the defined image description categories, such that said generating annotation tags for the digital image comprises substituting the category entries making up the vocabulary metadata as values for corresponding ones of the variable entries, and then logically evaluating the set of conditional tests according to the substituted category entries; determining confidence or fuzzy logic weighting values from the context metadata, said confidence or fuzzy logic weighting values numerically expressing the extents to which given ones of the substituted category entries apply to the digital image; and ranking the generated annotation tags from most likely to least likely, in terms of applicability to the digital image, according to the confidence or fuzzy logic weighting values, or incorporating the confidence or fuzzy logic weighting values into said logical evaluation of the set of conditional tests, whereby the truthfulness of each conditional evaluation depends on the confidence or fuzzy logic weighting values, such that the generated annotation tags correspond to higher-weighted category entries or combinations thereof. 6. The method of claim 1 , wherein said maintaining a library of human-meaningful words or phrases includes receiving or otherwise storing a default library, and dynamically updating or adding category entries to the default library responsive to user selections and modifications to annotation tags as generated for one or more digital images. | 0.588754 |
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. 8. The method of claim 1 , wherein each of the plurality of app records further includes one or more app attributes (AAs) that describe the app, the method further comprising, for each of the plurality of app records, augmenting the one or more AAs included in the each of the plurality of app records to include the one or more terms determined for the each of the plurality of app records, and 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 one or more resources 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 one or more terms of the augmented one or more AAs included in the each of the plurality of app records. | 0.616939 |
23. The method of claim 19 wherein the amount of remuneration is based on a policy. | 23. The method of claim 19 wherein the amount of remuneration is based on a policy. 24. The method of claim 23 wherein the policy is specified by the copyright holder. | 0.966589 |
15. The method of claim 11 further comprising generating a third metric value based on selections among a plurality of results generated by initiating the first search query. | 15. The method of claim 11 further comprising generating a third metric value based on selections among a plurality of results generated by initiating the first search query. 16. The method of claim 15 wherein the third metric value is generated based on the number of times a regional result was selected relative to the number of times a global result was selected from the plurality of results. | 0.91307 |
1. A method for operator selection, comprising: initiating, by a call handling system, a dialog between a contact and a call the call handling system; identifying, by the call handling system, a language variation spoken by the contact; determining, by the call handling system, a skill level with respect to the language variation for each operator within a set of operators following the initiation of the dialog between the contact and the call handling system, the skill level for each operator within the set of operators being determined on a real time basis while each operator is engaged in a dialog with a contact that has been transferred to that operator; selecting, by the call handling system, an operator whose skill level in the language variation is above a predetermined value; and transferring, by the call handling system, the dialog with the contact to the operator. | 1. A method for operator selection, comprising: initiating, by a call handling system, a dialog between a contact and a call the call handling system; identifying, by the call handling system, a language variation spoken by the contact; determining, by the call handling system, a skill level with respect to the language variation for each operator within a set of operators following the initiation of the dialog between the contact and the call handling system, the skill level for each operator within the set of operators being determined on a real time basis while each operator is engaged in a dialog with a contact that has been transferred to that operator; selecting, by the call handling system, an operator whose skill level in the language variation is above a predetermined value; and transferring, by the call handling system, the dialog with the contact to the operator. 9. The method of claim 1 , further comprising: generating a report on all language variations spoken by contacts calling the call handling system. | 0.736753 |
4. A method as claimed in claim 3 wherein the candidate indexes are ordered by request value of importance, the method further comprising, with identification of each candidate index, searching previously identified indexes for an existing index that is similar to the candidate index and choosing from the steps of a) creating a new index, b) reusing the best existing index and c) modifying the best existing index to satisfy the context of the candidate index, choice of steps a, b and c being dependent on match between the candidate index and the best existing index and the value of importance of the requests for which the indexes are identified. | 4. A method as claimed in claim 3 wherein the candidate indexes are ordered by request value of importance, the method further comprising, with identification of each candidate index, searching previously identified indexes for an existing index that is similar to the candidate index and choosing from the steps of a) creating a new index, b) reusing the best existing index and c) modifying the best existing index to satisfy the context of the candidate index, choice of steps a, b and c being dependent on match between the candidate index and the best existing index and the value of importance of the requests for which the indexes are identified. 15. A method as claimed in claim 4 wherein the best existing index is changed to the order and type of the candidate index if the best existing index is hash, the candidate index is either hash or sorted, the best existing index has more columns, all columns of the candidate index match in identity to columns of the best existing index and the importance of the candidate index is greater than a threshold relative to the importance of the best existing index. | 0.911006 |
15. A computer program product comprising: a tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving information about an expected use of a spectrum band in a radio frequency spectrum, the expected use by a primary user; classifying the expected use of the spectrum band into at least two working modes, the classifying responsive to the information about the expected use; sensing the spectrum band to determine a current access pattern of the primary user; selecting one of the working modes as a current working mode of the primary user, the selecting responsive to the classifying and to the current access pattern of the primary user; scheduling transmissions on the spectrum band using a current schedule that is responsive to the current working mode of the primary user, the scheduling as a secondary user of the spectrum band; determining whether the current working mode of the primary user has changed; if the current working mode of the primary user has changed, re-performing the sensing, selecting, scheduling, and determining; and if the current working mode of the primary user has not changed, re-performing the scheduling and determining. | 15. A computer program product comprising: a tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving information about an expected use of a spectrum band in a radio frequency spectrum, the expected use by a primary user; classifying the expected use of the spectrum band into at least two working modes, the classifying responsive to the information about the expected use; sensing the spectrum band to determine a current access pattern of the primary user; selecting one of the working modes as a current working mode of the primary user, the selecting responsive to the classifying and to the current access pattern of the primary user; scheduling transmissions on the spectrum band using a current schedule that is responsive to the current working mode of the primary user, the scheduling as a secondary user of the spectrum band; determining whether the current working mode of the primary user has changed; if the current working mode of the primary user has changed, re-performing the sensing, selecting, scheduling, and determining; and if the current working mode of the primary user has not changed, re-performing the scheduling and determining. 16. The computer program product of claim 15 , wherein the method further comprises probing the spectrum band for a data transmission drift associated with the current working mode of the primary user, wherein the scheduling transmissions on the spectrum band is further responsive to the data transmission drift associated with the current working mode of the primary user. | 0.5 |
13. A computerized system comprising: a processor configured to execute instruction; a memory containing instructions when executed on the processor, causes the processor to perform operations that: receive a user utterance with a context manager; communicate, with the context manager, a user text an context identifier to an extraction engine, wherein the user text is obtained from the user utterance; create, with the context manager, a context object associated with the user utterance; extract topics and attributes from the user text with the extraction engine, wherein the extraction engine assigns a probability to each extracted attribute based on a number of occurrences of the attribute, wherein the extraction engine calculates a confidence value to the attribute, wherein the confidence value is defined as f ( I ( v i ) ) = 1 log 2 ( I ( v i ) + I ) ∑ v ∈ I ( v i ) α ( v ) C ( v ) ; communicate the topics and attributes to the context manager; update, with the context manager, the context object context manager with topics and attributes; communicate the context object to a semantic engine; update the context object, with the semantic engine, based on at least one of an inference rule or a semantic model; communicate the context object to a discourse manager; use discourse states, and dialogs to determine a system utterance for the user, wherein a system utterance comprises an automatically generated response generated with at least one processor; generate a query plan; send the updated context object and user intent to execution engine; query a database for additional information relevant to the system utterance; convert the additional information from to additional sentence in a user-readable natural language state; add additional sentences to the system utterance; and communicate the system utterance to at least one of a user device or a user application. | 13. A computerized system comprising: a processor configured to execute instruction; a memory containing instructions when executed on the processor, causes the processor to perform operations that: receive a user utterance with a context manager; communicate, with the context manager, a user text an context identifier to an extraction engine, wherein the user text is obtained from the user utterance; create, with the context manager, a context object associated with the user utterance; extract topics and attributes from the user text with the extraction engine, wherein the extraction engine assigns a probability to each extracted attribute based on a number of occurrences of the attribute, wherein the extraction engine calculates a confidence value to the attribute, wherein the confidence value is defined as f ( I ( v i ) ) = 1 log 2 ( I ( v i ) + I ) ∑ v ∈ I ( v i ) α ( v ) C ( v ) ; communicate the topics and attributes to the context manager; update, with the context manager, the context object context manager with topics and attributes; communicate the context object to a semantic engine; update the context object, with the semantic engine, based on at least one of an inference rule or a semantic model; communicate the context object to a discourse manager; use discourse states, and dialogs to determine a system utterance for the user, wherein a system utterance comprises an automatically generated response generated with at least one processor; generate a query plan; send the updated context object and user intent to execution engine; query a database for additional information relevant to the system utterance; convert the additional information from to additional sentence in a user-readable natural language state; add additional sentences to the system utterance; and communicate the system utterance to at least one of a user device or a user application. 14. A computerized system of claim 13 , wherein C(v) comprises a confidence in the information-extraction rule that extracted the attribute-value pair from the user utterance, wherein a(v) comprises an indicator function for whether a particular value occurred within a negated context, and wherein I(vi) comprises a collection of occurrences of a value extracted from the user utterance. | 0.58989 |
1. In a computing environment, a processor-implemented method of analyzing dynamic source code, the method comprising: parsing source code to generate one or more syntax trees defining constructs in a body of dynamic language source code; from the one or more syntax trees, extracting identifier information for one or more of the defined constructs; augmenting knowledge about the constructs by at least one of explicit inspection of the body of source code or implied references related to the source code; producing a correlation between identifiers and augmented knowledge; using the identifier information and augmented knowledge, generating metadata about the body of the dynamic language source code, the generated metadata being represented as a symbol table; parsing symbol table to compute metrics about the one or more syntax trees; and providing the metrics about the one or more syntax trees to a user, wherein the metrics provide code correctness analysis, and wherein the correctness analysis indicates parameter count mismatches. | 1. In a computing environment, a processor-implemented method of analyzing dynamic source code, the method comprising: parsing source code to generate one or more syntax trees defining constructs in a body of dynamic language source code; from the one or more syntax trees, extracting identifier information for one or more of the defined constructs; augmenting knowledge about the constructs by at least one of explicit inspection of the body of source code or implied references related to the source code; producing a correlation between identifiers and augmented knowledge; using the identifier information and augmented knowledge, generating metadata about the body of the dynamic language source code, the generated metadata being represented as a symbol table; parsing symbol table to compute metrics about the one or more syntax trees; and providing the metrics about the one or more syntax trees to a user, wherein the metrics provide code correctness analysis, and wherein the correctness analysis indicates parameter count mismatches. 4. The method of claim 1 , wherein the correctness analysis indicates the existence of duplicate cases in a switch block. | 0.8475 |
88. An apparatus for recognizing an environmental sound, comprising: means for storing 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; means for capturing an input environmental sound; means for generating an input sound model from the input environmental sound; means for determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models from the means for storing that are similar to the input sound model; means for selecting a first label from one or more labels, of the plurality of labels, associated with the one or more sound models; means for associating the first label with the input environmental sound based on a confidence level of the first label; means for transmitting the input sound model to a server if the confidence level is less than a confidence threshold; and means for receiving a second label identifying the input environmental sound from the server. | 88. An apparatus for recognizing an environmental sound, comprising: means for storing 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; means for capturing an input environmental sound; means for generating an input sound model from the input environmental sound; means for determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models from the means for storing that are similar to the input sound model; means for selecting a first label from one or more labels, of the plurality of labels, associated with the one or more sound models; means for associating the first label with the input environmental sound based on a confidence level of the first label; means for transmitting the input sound model to a server if the confidence level is less than a confidence threshold; and means for receiving a second label identifying the input environmental sound from the server. 102. The apparatus of claim 88 , wherein the means for storing, the means for capturing, the means for generating, the means for determining, the means for selecting, and the means for associating are integrated into a base station. | 0.644411 |
1. A computer program product for transforming policy statements, wherein the initial policy provides rules for how a database can be manipulated, and wherein the computer program product comprises a computer readable storage medium having program doe embodied therewith, the program code readable and executable by a processor to perform a method comprising: providing a user interface (UI) to a computer, wherein the UI comprises a field containing a sample database query statement, wherein the sample database query statement performs an action on the data in the database; parsing the sample database query statement into one or more clauses, wherein each clause depicts a specific type of grammatical structure, and wherein the grammatical structure is from a group consisting of a verb, an object, and a condition; associating a different hyperlink to each of the clauses, wherein each different hyperlink is specific for a particular type of grammatical structure; in response to receiving a signal activating a particular hyperlink for a particular clause in the sample database query statement, presenting change options, for the particular clause, from a resource that presents change options for the specific type of grammatical structure; receiving, from the change options, a user-selected change, wherein said user-selected change is applied to a matching clause in another database query statement; incorporating, by one or more processors, each user-selected change into a new rule, wherein the new rule causes a clause, of the particular type of grammatical structure, in the sample database query statement to be changed according to a change option that was selected; incorporating the new rule into the initial policy to create a revised policy; and modifying the sample database query statement according to the revised policy. | 1. A computer program product for transforming policy statements, wherein the initial policy provides rules for how a database can be manipulated, and wherein the computer program product comprises a computer readable storage medium having program doe embodied therewith, the program code readable and executable by a processor to perform a method comprising: providing a user interface (UI) to a computer, wherein the UI comprises a field containing a sample database query statement, wherein the sample database query statement performs an action on the data in the database; parsing the sample database query statement into one or more clauses, wherein each clause depicts a specific type of grammatical structure, and wherein the grammatical structure is from a group consisting of a verb, an object, and a condition; associating a different hyperlink to each of the clauses, wherein each different hyperlink is specific for a particular type of grammatical structure; in response to receiving a signal activating a particular hyperlink for a particular clause in the sample database query statement, presenting change options, for the particular clause, from a resource that presents change options for the specific type of grammatical structure; receiving, from the change options, a user-selected change, wherein said user-selected change is applied to a matching clause in another database query statement; incorporating, by one or more processors, each user-selected change into a new rule, wherein the new rule causes a clause, of the particular type of grammatical structure, in the sample database query statement to be changed according to a change option that was selected; incorporating the new rule into the initial policy to create a revised policy; and modifying the sample database query statement according to the revised policy. 7. The computer program product of claim 1 , wherein the sample database query statement is from a group of executable statements consisting of a request for data from the database, a request to change a format of data in the database, and a request to alter data in the database. | 0.578748 |
3. The method of claim 1 , wherein the documents from which the set of headline, sentence pairs is determined are news story documents. | 3. The method of claim 1 , wherein the documents from which the set of headline, sentence pairs is determined are news story documents. 4. The method of claim 3 , wherein for each of the headline, sentence pairs the sentence is a first sentence of the respective document. | 0.971995 |
6. The method of claim 1 wherein the plurality of electronic questioners include a plurality of internal and external dimension factors. | 6. The method of claim 1 wherein the plurality of electronic questioners include a plurality of internal and external dimension factors. 8. The method of claim 6 wherein the external dimension factors include salary, location, type of practice, type of professional encounters and employment benefits. | 0.980688 |
11. A system comprising: control circuitry configured to: send voice input data received by a media device to a speech-to-text service; receive, by the media device from the speech-to-text service, a textual representation of at least a portion of the voice input data; generate a signature based on at least a portion of the textual representation, wherein the signature is a hash value; locate a particular data entry among a set of data entries by performing a search of the set of data entries for a data entry matching the signature generated based on the at least a portion of the textual representation, each data entry of the set of data entries specifying a mapping between a given signature and one or more media device actions; update the set of data entries by storing the mapping between the signature and the at least a portion of the textual representation; in response to locating the particular data entry among the set of data entries based on the generated signature, perform one or more particular media device actions associated with the particular data entry, the one or more particular media device actions including sending a media content query to a media search service; receive, by the media device, one or more content item listings based on the media content query; and generate for display at least a portion of the one or more content item listings. | 11. A system comprising: control circuitry configured to: send voice input data received by a media device to a speech-to-text service; receive, by the media device from the speech-to-text service, a textual representation of at least a portion of the voice input data; generate a signature based on at least a portion of the textual representation, wherein the signature is a hash value; locate a particular data entry among a set of data entries by performing a search of the set of data entries for a data entry matching the signature generated based on the at least a portion of the textual representation, each data entry of the set of data entries specifying a mapping between a given signature and one or more media device actions; update the set of data entries by storing the mapping between the signature and the at least a portion of the textual representation; in response to locating the particular data entry among the set of data entries based on the generated signature, perform one or more particular media device actions associated with the particular data entry, the one or more particular media device actions including sending a media content query to a media search service; receive, by the media device, one or more content item listings based on the media content query; and generate for display at least a portion of the one or more content item listings. 19. The system of claim 11 , wherein the control circuitry is further configured, when receiving the one or more content item listings based on the media content query, to receive the one or more content item listings from the media search service. | 0.782271 |
8. The non-transitory computer readable medium of claim 6 , wherein the instructions comprise instructions for evaluating the performance of a system. | 8. The non-transitory computer readable medium of claim 6 , wherein the instructions comprise instructions for evaluating the performance of a system. 9. The non-transitory computer readable medium of claim 8 , wherein applying a runtime engine comprises running an automatic performance testing application. | 0.905258 |
15. A method of providing a database record retrieval service, comprising the steps of: establishing a communication link between a requestor and a service provider, and the communication link originating from the requestor; receiving requested database record information from the requestor; formulating a search query based on the requested database record information that includes non-sequential first and last elements of a plurality of different terms in a single search field, wherein first and last elements are each a single alphanumeric character, and the search query omits a plurality of elements of the search field positioned between the first and last elements; executing the search query: selecting at least one database record that matches the search query; and supplying the requestor with information from the selected database record. | 15. A method of providing a database record retrieval service, comprising the steps of: establishing a communication link between a requestor and a service provider, and the communication link originating from the requestor; receiving requested database record information from the requestor; formulating a search query based on the requested database record information that includes non-sequential first and last elements of a plurality of different terms in a single search field, wherein first and last elements are each a single alphanumeric character, and the search query omits a plurality of elements of the search field positioned between the first and last elements; executing the search query: selecting at least one database record that matches the search query; and supplying the requestor with information from the selected database record. 19. The method of claim 15 wherein the selecting step includes selecting a subset of the database that includes a plurality of database records that match the search query, which is a first search query; identifying an aspect of each of the database records of the subset that is unique to the respective database records; formulating a second search query at least in part by requesting additional information regarding the aspect from the requestor; executing the second search query on the subset; and retrieving, from the subset, at least one database record that matches the second search query. | 0.5 |
10. The method of claim 1 further comprises identifying root cause candidates for a performance problem in the distributed computing environment, where the root cause candidates are identified from the plurality of event records and a plurality of event causality records forming an event graph in the repository. | 10. The method of claim 1 further comprises identifying root cause candidates for a performance problem in the distributed computing environment, where the root cause candidates are identified from the plurality of event records and a plurality of event causality records forming an event graph in the repository. 12. The method of claim 10 wherein the event graph is defined as a weakly connected graph, where the nodes of the weakly connected graph are formed by event records and the edges of the graph are formed by event causality records. | 0.945673 |
1. In an apparatus, a method of extracting, merging, and systematizing organization names from text, comprising: at a computer-readable medium having one or more microprocessors configured to host and execute one or more programs, extracting organization-related text from a database; identifying one or more phrases contained in said text; associating organization entities with at least one country, email address, URL, street address, city, or state of a portion of said phrases based upon the content of said phrases; assigning at least a portion of the remaining phrases as organization entities, based upon the content of said phrases and whether nearby phrases have been assigned as organization entities; performing a first unsupervised clustering wherein said organization entities are grouped into a first plurality of clusters based upon geopolitical entity and a modified edit distance metric, wherein each of the first clusters includes a list of all organization entities in the cluster; wherein each new organization entity under consideration is compared to the centroids of all clusters having the same geopolitical entity, wherein if the modified edit distance metric indicates that the described organization entity, under consideration, matches above a predetermined threshold to the centroid of a cluster, then the described organization entity under consideration is added to that cluster, wherein if the described organization entity does not match above a predetermined threshold to the centroid of any existing cluster, then that described organization entity becomes the centroid of a new cluster; performing a second unsupervised clustering wherein said first plurality of clusters are clustered into one or more second clusters based upon geopolitical entity and at least one similarity metric based on centroids of said first plurality of clusters, wherein the second unsupervised clustering includes connected components clustering, wherein the second unsupervised clustering groups organization entities which represent the same organization despite being having substantially different words; and designating a normalized organization name for each second cluster based upon predetermined criteria. | 1. In an apparatus, a method of extracting, merging, and systematizing organization names from text, comprising: at a computer-readable medium having one or more microprocessors configured to host and execute one or more programs, extracting organization-related text from a database; identifying one or more phrases contained in said text; associating organization entities with at least one country, email address, URL, street address, city, or state of a portion of said phrases based upon the content of said phrases; assigning at least a portion of the remaining phrases as organization entities, based upon the content of said phrases and whether nearby phrases have been assigned as organization entities; performing a first unsupervised clustering wherein said organization entities are grouped into a first plurality of clusters based upon geopolitical entity and a modified edit distance metric, wherein each of the first clusters includes a list of all organization entities in the cluster; wherein each new organization entity under consideration is compared to the centroids of all clusters having the same geopolitical entity, wherein if the modified edit distance metric indicates that the described organization entity, under consideration, matches above a predetermined threshold to the centroid of a cluster, then the described organization entity under consideration is added to that cluster, wherein if the described organization entity does not match above a predetermined threshold to the centroid of any existing cluster, then that described organization entity becomes the centroid of a new cluster; performing a second unsupervised clustering wherein said first plurality of clusters are clustered into one or more second clusters based upon geopolitical entity and at least one similarity metric based on centroids of said first plurality of clusters, wherein the second unsupervised clustering includes connected components clustering, wherein the second unsupervised clustering groups organization entities which represent the same organization despite being having substantially different words; and designating a normalized organization name for each second cluster based upon predetermined criteria. 6. The method of claim 1 , wherein the modified edit distance metric is a Levenshtein distance calculated at a word level, after stop words have been removed; where the threshold for word matching (WS) is approximately 0.85; where WS =(Smith-Waterman Score of word a and word b) /(Average length of word a and word b); and where the Levenshtein score threshold is approximately four. | 0.526904 |
1. A method in a computing device for specifying context attributes for logging, comprising: employing a processor executing computer-executable instructions stored on a computer-reasonable storage medium to implement the following acts: displaying a list of context attributes available in the computing device, each context attribute in the list of context attributes having values supplied by one or more data sources; caching the values supplied by the one or more data sources as the values are obtained from the data sources; receiving a first set of user inputs identifying a subset of context attributes from the list of context attributes for logging; receiving a second set of user inputs specifying a logging frequency for each context attribute in the identified subset of context attributes; receiving a third set of user inputs specifying a maximum value age for each context attribute in the identified subset of context attributes; selecting the identified subset of context attributes for logging; for each context attribute in the identified subset of attributes: determining an age of a cached value associated with the context attribute at periodic intervals determined by the logging frequency specified for the context attribute; determining whether the age of the cached value associated with the context attribute is less than the maximum value age specified for the context attribute; logging the cached value associated with the context attribute when it is determined that the age of the cached value associated with the context attribute is less than the maximum value age specified for the context attribute; and obtaining a new value from a data source corresponding to the context attribute when it is determined that the age of the cached value associated with the context attribute is greater than the maximum value age specified for the context attribute; for each context attribute of the identified subset of selected context attributes, receiving user input identifying a log in which values of the context attribute are to be logged; and for each context attribute of the identified subset of context attributes, at periodic times as a function of the logging frequency associated with the context attribute, storing values of the selected context attribute in the log identified for the context attribute. | 1. A method in a computing device for specifying context attributes for logging, comprising: employing a processor executing computer-executable instructions stored on a computer-reasonable storage medium to implement the following acts: displaying a list of context attributes available in the computing device, each context attribute in the list of context attributes having values supplied by one or more data sources; caching the values supplied by the one or more data sources as the values are obtained from the data sources; receiving a first set of user inputs identifying a subset of context attributes from the list of context attributes for logging; receiving a second set of user inputs specifying a logging frequency for each context attribute in the identified subset of context attributes; receiving a third set of user inputs specifying a maximum value age for each context attribute in the identified subset of context attributes; selecting the identified subset of context attributes for logging; for each context attribute in the identified subset of attributes: determining an age of a cached value associated with the context attribute at periodic intervals determined by the logging frequency specified for the context attribute; determining whether the age of the cached value associated with the context attribute is less than the maximum value age specified for the context attribute; logging the cached value associated with the context attribute when it is determined that the age of the cached value associated with the context attribute is less than the maximum value age specified for the context attribute; and obtaining a new value from a data source corresponding to the context attribute when it is determined that the age of the cached value associated with the context attribute is greater than the maximum value age specified for the context attribute; for each context attribute of the identified subset of selected context attributes, receiving user input identifying a log in which values of the context attribute are to be logged; and for each context attribute of the identified subset of context attributes, at periodic times as a function of the logging frequency associated with the context attribute, storing values of the selected context attribute in the log identified for the context attribute. 8. The method of claim 1 , further comprising determining for a distinguished one of the selected context attributes a processing technique to which the distinguished context attribute is to be subjected before logging. | 0.531 |
8. The network device of claim 6 , where the processor is further to: transmit the modified set of policy rules to another network device. | 8. The network device of claim 6 , where the processor is further to: transmit the modified set of policy rules to another network device. 10. The network device of claim 8 , where the processor is further to: determine whether a document violates the modified set of policy rules, selectively permit transmission of the document when the document violates the modified set of policy rules, and permit transmission of the document when the document does not violate the modified set of policy rules. | 0.917655 |
12. A method for enabling a user to create his or her own custom search engine, said method comprising the following steps: hosting a first submission form on a first computer, said first computer being under the control of a first entity and connected to a computer network, said first submission form comprising at least a first data entry field suitable for user entry of data; receiving a first submission from a first user, said first user being different from said first entity, said first submission comprising at least a first user-specified piece of data, said first user-specified piece of data being selected from the group consisting of (i) a second user-specified piece of data, said second user-specified piece of data pertaining to weight, (ii) a third user-specified piece of data, said third user-specified piece of data pertaining to freshness, and (iii) a fourth user-specified piece of data, said fourth user-specified piece of data pertaining to tolerance; providing markup language text to said first user, said markup language text being suitable for embedding in a second submission form, said second submission form comprising a second data entry field and being hosted on a second computer, said second data entry field being suitable for user entry of a first term, said second computer being different from said first computer and being connected to said computer network; receiving a second submission, said second submission comprising said first term and being submitted by a second user from a third computer through said computer network by way of said second submission form, said second user being different from said first user and different from said first entity, said third computer being different from said first computer and different from said second computer; ranking a first set of items in response to said second submission, said step of ranking said first set of items being performed according to a ranking algorithm, said ranking algorithm being determined at least in part by said first user through said first submission, said first set of items comprising at least a first item and a second item; providing a search engine results document to said second user, said search engine results document comprising at least some results of said step of ranking and being selected from the group consisting of a first search engine results page and a first search engine results email; receiving a first URL at said first computer via said first computer network; receiving a first label, said first label comprising at least a first word; associating said first label with said first URL; receiving a first query via a first query submission form; comparing said first query to said first label; ranking a second set of items, said second set of items comprising a third item and a fourth item, said third item being associated with said first URL, said step of ranking said second set of items being performed according to an outcome of said step of comparing said first query to said first label; establishing a first vendor account, a second vendor account, and first shopper account; indicating that said first vendor account has been established; providing an electronic shopping cart mechanism; receiving by way of said electronic shopping cart mechanism information pertaining to a plurality of different purchases; charging said first shopper account for said plurality of different purchases; paying a plurality of different vendors for said plurality of different purchases; and instructing said plurality of different vendors to ship said purchases to a first shopper, said plurality of different vendors comprising a first vendor and a second vendor, said first vendor being associated with said first vendor account, said second vendor being associated with said second vendor account, and said first shopper being associated with said first shopper account, said first vendor being different from said second vendor and from said first shopper. | 12. A method for enabling a user to create his or her own custom search engine, said method comprising the following steps: hosting a first submission form on a first computer, said first computer being under the control of a first entity and connected to a computer network, said first submission form comprising at least a first data entry field suitable for user entry of data; receiving a first submission from a first user, said first user being different from said first entity, said first submission comprising at least a first user-specified piece of data, said first user-specified piece of data being selected from the group consisting of (i) a second user-specified piece of data, said second user-specified piece of data pertaining to weight, (ii) a third user-specified piece of data, said third user-specified piece of data pertaining to freshness, and (iii) a fourth user-specified piece of data, said fourth user-specified piece of data pertaining to tolerance; providing markup language text to said first user, said markup language text being suitable for embedding in a second submission form, said second submission form comprising a second data entry field and being hosted on a second computer, said second data entry field being suitable for user entry of a first term, said second computer being different from said first computer and being connected to said computer network; receiving a second submission, said second submission comprising said first term and being submitted by a second user from a third computer through said computer network by way of said second submission form, said second user being different from said first user and different from said first entity, said third computer being different from said first computer and different from said second computer; ranking a first set of items in response to said second submission, said step of ranking said first set of items being performed according to a ranking algorithm, said ranking algorithm being determined at least in part by said first user through said first submission, said first set of items comprising at least a first item and a second item; providing a search engine results document to said second user, said search engine results document comprising at least some results of said step of ranking and being selected from the group consisting of a first search engine results page and a first search engine results email; receiving a first URL at said first computer via said first computer network; receiving a first label, said first label comprising at least a first word; associating said first label with said first URL; receiving a first query via a first query submission form; comparing said first query to said first label; ranking a second set of items, said second set of items comprising a third item and a fourth item, said third item being associated with said first URL, said step of ranking said second set of items being performed according to an outcome of said step of comparing said first query to said first label; establishing a first vendor account, a second vendor account, and first shopper account; indicating that said first vendor account has been established; providing an electronic shopping cart mechanism; receiving by way of said electronic shopping cart mechanism information pertaining to a plurality of different purchases; charging said first shopper account for said plurality of different purchases; paying a plurality of different vendors for said plurality of different purchases; and instructing said plurality of different vendors to ship said purchases to a first shopper, said plurality of different vendors comprising a first vendor and a second vendor, said first vendor being associated with said first vendor account, said second vendor being associated with said second vendor account, and said first shopper being associated with said first shopper account, said first vendor being different from said second vendor and from said first shopper. 16. The method in claim 12 additionally comprising the following steps: providing a first markup language standard; determining whether a first text submission conforms to said first markup language standard; and providing a first custom search engine or algorithm according to said first text submission. | 0.830377 |
14. The method of claim 1 , wherein labeling the text entry as spam based on the score further comprises: determining that the text entry came from a particular website or portion of a website; selecting a threshold based on the particular website or portion of the website; and determining that the score exceeds the threshold. | 14. The method of claim 1 , wherein labeling the text entry as spam based on the score further comprises: determining that the text entry came from a particular website or portion of a website; selecting a threshold based on the particular website or portion of the website; and determining that the score exceeds the threshold. 15. The method of claim 14 , wherein a threshold for text entries corresponding to a portion of a website containing business listings is lower than a threshold for text entries corresponding to a portion of a website corresponding to user reviews. | 0.808994 |
5. A method in accordance with claim 1 , further comprising: computing a two-dimensional vector containing a frequency of occurrence of all unique n-grams in the candidate character string and a frequency of occurrence of all unique n-grams in the reference character string; computing a similarity metric for the candidate character string, with respect to the reference character string, based on the two-dimensional vector; determining a magnitude of the vector associated with the candidate character string as magnitude A; determining a magnitude of the vector associated with the reference character string as magnitude B; computing a dot product between the two vectors; computing the similarity metric according to (dot product/(magnitude A×magnitude B)). | 5. A method in accordance with claim 1 , further comprising: computing a two-dimensional vector containing a frequency of occurrence of all unique n-grams in the candidate character string and a frequency of occurrence of all unique n-grams in the reference character string; computing a similarity metric for the candidate character string, with respect to the reference character string, based on the two-dimensional vector; determining a magnitude of the vector associated with the candidate character string as magnitude A; determining a magnitude of the vector associated with the reference character string as magnitude B; computing a dot product between the two vectors; computing the similarity metric according to (dot product/(magnitude A×magnitude B)). 6. A method in accordance with claim 5 , wherein computing a similarity metric for the candidate character string comprises using a structured query language calculation to compare contents of the two-dimensional vector. | 0.85333 |
1. A computer-implemented method of adding a hotspot definition to an imaged document to create a mixed media document, the method executed by a computer and comprising: converting a source document into the imaged document from which a feature representation can be extracted; extracting features from the imaged document to create the feature representation; receiving a first user input for the hotspot definition that comprises a first coordinate location of a first bounding box for a hotspot in the imaged document and at least one of a media or an action that is associated with the first coordinate location, wherein the hotspot comprises a portion of the imaged document that is included in the first bounding box; determining whether the portion of the imaged document that is included in the first bounding box uniquely identifies the hotspot is in a database based on an amount of information included in the first bounding box; in response to determining that the portion of the imaged document that is included in the first bounding box does not uniquely identify the hotspot in the database, receiving a second user input to change the hotspot definition to a second coordinate location of a second bounding box, the second bounding box comprising the first bounding box and containing a larger amount of information than the first bounding box, wherein the larger amount of information contained in the second bounding box uniquely identifies the hotspot in the database; and storing, as the mixed media document, the imaged document, the hotspot definition, and the feature representation. | 1. A computer-implemented method of adding a hotspot definition to an imaged document to create a mixed media document, the method executed by a computer and comprising: converting a source document into the imaged document from which a feature representation can be extracted; extracting features from the imaged document to create the feature representation; receiving a first user input for the hotspot definition that comprises a first coordinate location of a first bounding box for a hotspot in the imaged document and at least one of a media or an action that is associated with the first coordinate location, wherein the hotspot comprises a portion of the imaged document that is included in the first bounding box; determining whether the portion of the imaged document that is included in the first bounding box uniquely identifies the hotspot is in a database based on an amount of information included in the first bounding box; in response to determining that the portion of the imaged document that is included in the first bounding box does not uniquely identify the hotspot in the database, receiving a second user input to change the hotspot definition to a second coordinate location of a second bounding box, the second bounding box comprising the first bounding box and containing a larger amount of information than the first bounding box, wherein the larger amount of information contained in the second bounding box uniquely identifies the hotspot in the database; and storing, as the mixed media document, the imaged document, the hotspot definition, and the feature representation. 4. The method of claim 1 , wherein extracting the features further comprises, in response to a print command, capturing coordinates corresponding to a printed representation of the imaged document. | 0.608504 |
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