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1. A method for automatically classifying a markup language text that is accessible at an Internet domain comprising: (a) retrieving from one or more data repositories, data associated with the Internet domain; (b) computing a first identifier for the Internet domain based on at least the data associated with the Internet domain and the markup language text; (c) computing a measure of similarity of content of the computed first identifier and content of each of a first plurality of previously classified identifiers; (d) assigning the markup language text a classification based on the computed measure of similarity between the computed first identifier and each of the first plurality of previously classified identifiers; (e) computing a second identifier for the markup language text based on the layout of the markup language text; (f) computing a measure of similarity between the second identifier and each of a second plurality of previously classified identifiers; and (g) assigning the markup language text a classification based on both the first identifier and the second identifier.
1. A method for automatically classifying a markup language text that is accessible at an Internet domain comprising: (a) retrieving from one or more data repositories, data associated with the Internet domain; (b) computing a first identifier for the Internet domain based on at least the data associated with the Internet domain and the markup language text; (c) computing a measure of similarity of content of the computed first identifier and content of each of a first plurality of previously classified identifiers; (d) assigning the markup language text a classification based on the computed measure of similarity between the computed first identifier and each of the first plurality of previously classified identifiers; (e) computing a second identifier for the markup language text based on the layout of the markup language text; (f) computing a measure of similarity between the second identifier and each of a second plurality of previously classified identifiers; and (g) assigning the markup language text a classification based on both the first identifier and the second identifier. 5. The method of claim 1 , wherein computing the first identifier comprises computing, for each of a plurality of words in a predetermined set of words, a frequency of each word in the markup language text and the search result.
0.508043
13. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to implement a community selection system for content analysis based automatic selection of user communities or groups of users, wherein the instructions cause the processor to: receive, by the community selection system from a client data processing system of a user, content authored by the user to be published; perform, by a content analysis engine executing within the community selection system, content analysis on the content to identify a context of the content; identify, by the community selection system, one or more social collaboration communities to which the user belongs using a user registry data structure; select, by the community selection system, a social collaboration community based on the identified one or more social collaboration communities to which the user belongs, the context of the content, and a community registry data structure of social collaboration communities; publish, by the community selection system, the content to a community server data processing system in the selected social collaboration community; receive, by the community selection system, feedback from the selected social collaboration community regarding the content; analyze, by a feedback analysis engine executing within the community selection system, the feedback; and determine, by the community selection system, whether to republish the content to a second social collaboration community within the community registry data structure based on results of analyzing the feedback.
13. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to implement a community selection system for content analysis based automatic selection of user communities or groups of users, wherein the instructions cause the processor to: receive, by the community selection system from a client data processing system of a user, content authored by the user to be published; perform, by a content analysis engine executing within the community selection system, content analysis on the content to identify a context of the content; identify, by the community selection system, one or more social collaboration communities to which the user belongs using a user registry data structure; select, by the community selection system, a social collaboration community based on the identified one or more social collaboration communities to which the user belongs, the context of the content, and a community registry data structure of social collaboration communities; publish, by the community selection system, the content to a community server data processing system in the selected social collaboration community; receive, by the community selection system, feedback from the selected social collaboration community regarding the content; analyze, by a feedback analysis engine executing within the community selection system, the feedback; and determine, by the community selection system, whether to republish the content to a second social collaboration community within the community registry data structure based on results of analyzing the feedback. 16. The apparatus of claim 13 , wherein the instructions further cause the processor to: determine whether to return the content to the user to edit based on results of analyzing the feedback.
0.531915
1. A method for managing interactive dialog between a machine and a user comprising: providing audio output comprising speech to the user from the machine, said audio output comprising a sequence of one or more phrases, wherein each phrase is followed by a yield zone, said yield zone characterized by an absence of speech provided from the machine; receiving digitized audio data comprising speech audio input at the machine wherein said speech audio input is generated from the user or from an environment of the user; determining said audio input comprises speech audio input generated from the user; determining a time at which said speech audio input begins; determining an onset likelihood value based on the time wherein the onset likelihood has a first value if the time occurs during a given phrase associated with the one or more phrases and a second value if the time occurs during a given yield zone associated with the one or more yield zones; determining a confidence value from the audio input, wherein the confidence value is dependent upon the onset likelihood value and a recognition result from a speech recognition module; and providing an audio response from the machine to the user based on the confidence value.
1. A method for managing interactive dialog between a machine and a user comprising: providing audio output comprising speech to the user from the machine, said audio output comprising a sequence of one or more phrases, wherein each phrase is followed by a yield zone, said yield zone characterized by an absence of speech provided from the machine; receiving digitized audio data comprising speech audio input at the machine wherein said speech audio input is generated from the user or from an environment of the user; determining said audio input comprises speech audio input generated from the user; determining a time at which said speech audio input begins; determining an onset likelihood value based on the time wherein the onset likelihood has a first value if the time occurs during a given phrase associated with the one or more phrases and a second value if the time occurs during a given yield zone associated with the one or more yield zones; determining a confidence value from the audio input, wherein the confidence value is dependent upon the onset likelihood value and a recognition result from a speech recognition module; and providing an audio response from the machine to the user based on the confidence value. 4. The method of claim 1 , wherein the given yield zone comprises a first portion and a second portion, and wherein the corresponding onset likelihood value is lower when said time occurs in said second portion than when said time occurs in said first portion.
0.674564
6. A method comprising: receiving first speech input from a user; determining a first recognized text corresponding to the first speech input; storing, in a dialog concept database and based on the first speech input, a first dialog concept item and an associated first indicator of a first application; displaying a user interface for the first application, the user interface for the first application comprising the first recognized text with the first indicator; receiving second speech input from the user; determining a second recognized text corresponding to the second speech input; storing, in the dialog concept database and based on the second speech input, a second dialog concept item and a second indicator of a second application corresponding to the second dialog concept item; receiving third speech input from the user; determining a third recognized text corresponding to the third speech input; storing, in the dialog concept database and based on the third speech input, a third dialog concept item and a third indicator of a third application corresponding to the third dialog concept item; and modifying the user interface for the first application to further comprise the second recognized text with the second indicator and the third recognized text with the third indicator.
6. A method comprising: receiving first speech input from a user; determining a first recognized text corresponding to the first speech input; storing, in a dialog concept database and based on the first speech input, a first dialog concept item and an associated first indicator of a first application; displaying a user interface for the first application, the user interface for the first application comprising the first recognized text with the first indicator; receiving second speech input from the user; determining a second recognized text corresponding to the second speech input; storing, in the dialog concept database and based on the second speech input, a second dialog concept item and a second indicator of a second application corresponding to the second dialog concept item; receiving third speech input from the user; determining a third recognized text corresponding to the third speech input; storing, in the dialog concept database and based on the third speech input, a third dialog concept item and a third indicator of a third application corresponding to the third dialog concept item; and modifying the user interface for the first application to further comprise the second recognized text with the second indicator and the third recognized text with the third indicator. 7. The method of claim 6 , wherein the first application is a text messaging application, the second application is an email application, a social media application, a weather application, or a map application, and the third application is an email application, a social media application, a weather application, or a map application.
0.5
9. A non-transitory computer readable medium encoded with a computer program comprising instructions that when executed operate to cause a computer to perform operations comprising: segmenting textual content for each of a plurality of distinct book content items into word strings, each word string including a predefined number of contiguous words in the textual content of a distinct book content item; classifying word strings having a frequency of occurrence that is less than a threshold frequency of occurrence as uncommon word strings, the frequency of occurrence for each word string being a number of occurrences of the word string relative to the total number of word strings in the plurality of distinct book content items; representing a weighted graph in computer memory, the weighted graph including a plurality of distinct nodes, each distinct node representing a corresponding distinct book content item in the plurality of distinct book content items, and where an edge exists in the weighted graph between each pair of distinct nodes that represent distinct book content items that both include a matching uncommon word string, each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching word strings in the textual content of other distinct book content items that are represented by other distinct nodes, each matching word string being a word string that matches an uncommon word string in the textual content of the distinct book content item corresponding to the distinct node; and generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of an uncommon word string to one or more matching word strings in the textual content of another distinct book content item; and determining a rank score for each distinct book content item based on the edges between the distinct nodes representing the distinct book content items, the rank score being a score indicative of the importance of each distinct book content item relative to other distinct book content items.
9. A non-transitory computer readable medium encoded with a computer program comprising instructions that when executed operate to cause a computer to perform operations comprising: segmenting textual content for each of a plurality of distinct book content items into word strings, each word string including a predefined number of contiguous words in the textual content of a distinct book content item; classifying word strings having a frequency of occurrence that is less than a threshold frequency of occurrence as uncommon word strings, the frequency of occurrence for each word string being a number of occurrences of the word string relative to the total number of word strings in the plurality of distinct book content items; representing a weighted graph in computer memory, the weighted graph including a plurality of distinct nodes, each distinct node representing a corresponding distinct book content item in the plurality of distinct book content items, and where an edge exists in the weighted graph between each pair of distinct nodes that represent distinct book content items that both include a matching uncommon word string, each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching word strings in the textual content of other distinct book content items that are represented by other distinct nodes, each matching word string being a word string that matches an uncommon word string in the textual content of the distinct book content item corresponding to the distinct node; and generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of an uncommon word string to one or more matching word strings in the textual content of another distinct book content item; and determining a rank score for each distinct book content item based on the edges between the distinct nodes representing the distinct book content items, the rank score being a score indicative of the importance of each distinct book content item relative to other distinct book content items. 13. The computer readable media of claim 9 , wherein identifying matching word strings in the textual content of other distinct book content items comprises identifying an exact match of each word in the uncommon word string in the textual content of the distinct book content item corresponding to the distinct node.
0.569104
5. A machine translation apparatus in which, a plurality of text files are browsed, and a desired one of the text is selected and translated, said apparatus comprising: a dividing means for dividing a text of a first language subject to translation into a plurality of component units; a generating means for generating a plurality of component units of a second language by translating said plurality of component units of the first language text; and a link information adding means for adding link information for component units of the second language text to each of the component units of said first language text and adding link information for component units of the first language text to each of the component units of said second language text.
5. A machine translation apparatus in which, a plurality of text files are browsed, and a desired one of the text is selected and translated, said apparatus comprising: a dividing means for dividing a text of a first language subject to translation into a plurality of component units; a generating means for generating a plurality of component units of a second language by translating said plurality of component units of the first language text; and a link information adding means for adding link information for component units of the second language text to each of the component units of said first language text and adding link information for component units of the first language text to each of the component units of said second language text. 8. A machine translation apparatus according to claim 5, wherein the first language text and the second language text to which said link information is added is hyper text.
0.872821
1. A computer-implemented method for extending content based on the semantic meaning of content, comprising the steps of: a) dividing the content into at least one of a plurality of content regions; b) calculating a vector for each of the content regions wherein the vector for each of the content regions is composited based on a term vector table, wherein the term vector table is obtained based on the latent semantic indexing using the dimension reduction operation with a sufficient number of available documents; c) calculating a relevance score between each of the vector of the content regions and each term vector in the term vector table, wherein the relevance score is the cosine value of the angle between each of the vector of the content regions and each term vector in the term vector table; d) for each of the content regions, selecting a group of extending terms from a group of terms in which the term vectors have the largest relevance scores with the vector of the content region; e) rendering the group of extending terms around each of the content regions.
1. A computer-implemented method for extending content based on the semantic meaning of content, comprising the steps of: a) dividing the content into at least one of a plurality of content regions; b) calculating a vector for each of the content regions wherein the vector for each of the content regions is composited based on a term vector table, wherein the term vector table is obtained based on the latent semantic indexing using the dimension reduction operation with a sufficient number of available documents; c) calculating a relevance score between each of the vector of the content regions and each term vector in the term vector table, wherein the relevance score is the cosine value of the angle between each of the vector of the content regions and each term vector in the term vector table; d) for each of the content regions, selecting a group of extending terms from a group of terms in which the term vectors have the largest relevance scores with the vector of the content region; e) rendering the group of extending terms around each of the content regions. 4. The method of claim 1 , wherein the step d) further comprising: selecting at least one of extending terms, wherein the extending term is not appeared in the content.
0.660479
1. A method for translation between source and target natural languages using a programmable digital computer system, the steps comprising: (a) storing in a main memory of the computer system a source text to be translated; (b) scanning and comparing such stored source words with dictionaries of source language words stored in a memory and for each source text word for which a match is found, storing in a file in main memory each word and in assocation with each such word, coded information derived from such dictionary for use in translation of such word, the coded information including memory offset address linkages to a memory in the computer system where grammar and target language translations for the word are stored; (c) analyzing the source text words in its file of words, a complete sentence at a time, and converting the same into a sentence in the target language utilizing the coded information and including the steps of (1) utilizing the memory offset address linkages for obtaining the target language translations of words from a memory; and (2) reordering the target language translation into the proper target language sequence; the step of analyzing additionally comprising the steps of analyzing each source word in multiple passes through each sentence of the source text assigning codes thereto, considering all the codes which previous passes have attached to a word and assigning target language synthesis codes attached to the meaning with which the code functions in the sentence, placing the word into a form corresponding to the target language dependent upon the analysis and consideration of all relevant codes assigned to the words.
1. A method for translation between source and target natural languages using a programmable digital computer system, the steps comprising: (a) storing in a main memory of the computer system a source text to be translated; (b) scanning and comparing such stored source words with dictionaries of source language words stored in a memory and for each source text word for which a match is found, storing in a file in main memory each word and in assocation with each such word, coded information derived from such dictionary for use in translation of such word, the coded information including memory offset address linkages to a memory in the computer system where grammar and target language translations for the word are stored; (c) analyzing the source text words in its file of words, a complete sentence at a time, and converting the same into a sentence in the target language utilizing the coded information and including the steps of (1) utilizing the memory offset address linkages for obtaining the target language translations of words from a memory; and (2) reordering the target language translation into the proper target language sequence; the step of analyzing additionally comprising the steps of analyzing each source word in multiple passes through each sentence of the source text assigning codes thereto, considering all the codes which previous passes have attached to a word and assigning target language synthesis codes attached to the meaning with which the code functions in the sentence, placing the word into a form corresponding to the target language dependent upon the analysis and consideration of all relevant codes assigned to the words. 14. A method, according to claim 1, wherein during the steps of scanning, comparing and storing, there is included the step of attaching part of speech codes to source text words and wherein during the step of analyzing there is included the step of attaching parts of speech codes used to branch into a required routine including the step of adding the value of part of speech to a fixed address.
0.583122
1. A method of analyzing text, the method comprising: providing a system capable of electronically receiving and manipulating text data associated with the text; providing a database that is comprised of data relative to one or more reference texts; said system being enabled to electronically access said database; using said system to recognize the text data as one or more scenes and a plurality of boundaries; using said system to analyze said one or more scenes and identify one or more elements of the text within said one or more scenes; and compiling the identified one or more elements of text within said one or more scenes to provide a bookmark that is a measured representation of the text, wherein said bookmark is a perspective bookmark complied by counting a number of first person indicators within dialog containing sentences within said one or more scenes.
1. A method of analyzing text, the method comprising: providing a system capable of electronically receiving and manipulating text data associated with the text; providing a database that is comprised of data relative to one or more reference texts; said system being enabled to electronically access said database; using said system to recognize the text data as one or more scenes and a plurality of boundaries; using said system to analyze said one or more scenes and identify one or more elements of the text within said one or more scenes; and compiling the identified one or more elements of text within said one or more scenes to provide a bookmark that is a measured representation of the text, wherein said bookmark is a perspective bookmark complied by counting a number of first person indicators within dialog containing sentences within said one or more scenes. 19. The method of claim 1 wherein said bookmark is a cumulative bookmark that is representative of a plurality of scenes within the text.
0.718421
1. A system for gesture recognition by a computing device, the system comprising: one or more processors; a memory coupled to the one or more processors; a touch-sensitive display coupled to the one or more processors; a virtual keyboard module configured to display a virtual keyboard on the touch-sensitive display and to receive a continuous stroke input by a user on the virtual keyboard, wherein the continuous stroke comprises a start-point and an end-point; a recognition module configured to obtain a most probable candidate word corresponding to the continuous stroke input by a user on the virtual keyboard; and a candidate display module configured to display, over the virtual keyboard, one or more characters representing the most probable candidate word, wherein a representation of the most probable candidate word is displayed at a particular location selected based at least in part on the continuous stroke end-point.
1. A system for gesture recognition by a computing device, the system comprising: one or more processors; a memory coupled to the one or more processors; a touch-sensitive display coupled to the one or more processors; a virtual keyboard module configured to display a virtual keyboard on the touch-sensitive display and to receive a continuous stroke input by a user on the virtual keyboard, wherein the continuous stroke comprises a start-point and an end-point; a recognition module configured to obtain a most probable candidate word corresponding to the continuous stroke input by a user on the virtual keyboard; and a candidate display module configured to display, over the virtual keyboard, one or more characters representing the most probable candidate word, wherein a representation of the most probable candidate word is displayed at a particular location selected based at least in part on the continuous stroke end-point. 2. The system of claim 1 wherein the continuous stroke is entered by the user on the touch-sensitive display using a stylus, and wherein the most probable candidate word includes a suffix for a word matching the continuous stroke.
0.783395
1. A computer-based method for generation of a graph representation of a rule set, the method comprising: setting a first rule list equal to the rule set; and performing a recursive process on the first rule list, wherein the recursive process comprises: setting a second rule list equal to the first rule list; when the second rule list includes more than one rule, for each rule in the second rule list: selecting the rule for processing; determining at least one verification set for said selected rule, wherein said at least one verification set is composed of individual offsets or data fields that define said selected rule, and data ranges for each individual offset or data field; creating a third rule list for the at least one verification set, wherein the third rule list represents a subgraph that is a portion of the graph representation; updating the individual offsets or data fields of the at least one verification set; adding the at least one verification set to the second rule list; and performing the recursive process on the third rule set to generate a new subgraph.
1. A computer-based method for generation of a graph representation of a rule set, the method comprising: setting a first rule list equal to the rule set; and performing a recursive process on the first rule list, wherein the recursive process comprises: setting a second rule list equal to the first rule list; when the second rule list includes more than one rule, for each rule in the second rule list: selecting the rule for processing; determining at least one verification set for said selected rule, wherein said at least one verification set is composed of individual offsets or data fields that define said selected rule, and data ranges for each individual offset or data field; creating a third rule list for the at least one verification set, wherein the third rule list represents a subgraph that is a portion of the graph representation; updating the individual offsets or data fields of the at least one verification set; adding the at least one verification set to the second rule list; and performing the recursive process on the third rule set to generate a new subgraph. 7. The method of claim 1 , comprising multiple verification sets, wherein each of said multiple verification sets is unique and does not overlap with any other verification set.
0.5
8. A server connected to a distribution terminal distributing a recognition model and a user terminal recognizing input speech and a translation terminal translating a speech recognition result of said user terminal through a network, said server comprising: a conferencing database; a model selection unit which selects a recognition model for each user of a plurality of users based on subject information and language information of each user that are stored in said conferencing database as part of characteristic information, and which selects translation dictionary information based on said language information of each user and language information for translation that are stored in said conferencing database as part of said characteristic information; and an indication unit which indicates said selected recognition model to said user terminal and indicates said selected translation dictionary information to said translation terminal.
8. A server connected to a distribution terminal distributing a recognition model and a user terminal recognizing input speech and a translation terminal translating a speech recognition result of said user terminal through a network, said server comprising: a conferencing database; a model selection unit which selects a recognition model for each user of a plurality of users based on subject information and language information of each user that are stored in said conferencing database as part of characteristic information, and which selects translation dictionary information based on said language information of each user and language information for translation that are stored in said conferencing database as part of said characteristic information; and an indication unit which indicates said selected recognition model to said user terminal and indicates said selected translation dictionary information to said translation terminal. 12. The server according to claim 8 , wherein said recognition model includes acoustic models and language models; and wherein said model selection unit selects an acoustic model among said acoustic models based on said language information of each user and selects a language model among said language models based on said subject information of input speech and selects translation dictionary information among said translation dictionaries based on said language information for translation.
0.524335
1. A method comprising: obtaining, by one or more computers, acoustic data for an utterance; determining, by the one or more computers, speech recognition candidates for the utterance based on the acoustic data; obtaining, by the one or more computers, a ranking of the speech recognition candidates determined by a speech recognizer; selecting, by the one or more computers, a transcription for the acoustic data from among the speech recognition candidates; determining, by the one or more computers, feature scores from the ranking of the speech recognition candidates; generating, by the one or more computers, a classifier output for each of at least some of the speech recognition candidates, wherein each of the classifier outputs is an output that a trained machine learning classifier provided in response to receiving at least one of the feature scores as input; selecting, by the one or more computers, a subset of the speech recognition candidates based on the classifier outputs of the trained machine learning classifier; and providing, by the one or more computers and for display at a client device, data indicating (i) the transcription for the utterance and (ii) the subset of the speech recognition candidates as a set of alternative transcriptions for the utterance, wherein the one or more computers are configured to provide different quantities of alternative transcriptions for different utterances.
1. A method comprising: obtaining, by one or more computers, acoustic data for an utterance; determining, by the one or more computers, speech recognition candidates for the utterance based on the acoustic data; obtaining, by the one or more computers, a ranking of the speech recognition candidates determined by a speech recognizer; selecting, by the one or more computers, a transcription for the acoustic data from among the speech recognition candidates; determining, by the one or more computers, feature scores from the ranking of the speech recognition candidates; generating, by the one or more computers, a classifier output for each of at least some of the speech recognition candidates, wherein each of the classifier outputs is an output that a trained machine learning classifier provided in response to receiving at least one of the feature scores as input; selecting, by the one or more computers, a subset of the speech recognition candidates based on the classifier outputs of the trained machine learning classifier; and providing, by the one or more computers and for display at a client device, data indicating (i) the transcription for the utterance and (ii) the subset of the speech recognition candidates as a set of alternative transcriptions for the utterance, wherein the one or more computers are configured to provide different quantities of alternative transcriptions for different utterances. 4. The method of claim 1 , wherein at least one of the alternative transcriptions includes a different number of words than the transcription.
0.706191
11. The non-transitory computer-readable storage medium of claim 10 , wherein the XML index contains a row for each node in a set of XML documents, and wherein said row contains the value of the node.
11. The non-transitory computer-readable storage medium of claim 10 , wherein the XML index contains a row for each node in a set of XML documents, and wherein said row contains the value of the node. 12. The non-transitory computer-readable storage medium of claim 11 , wherein performing said XML rewrite of said certain query includes rewriting the query to refer to a database object of the XML index.
0.902745
1. A computer-implemented method for query optimization, the computer-implemented method comprising executing instructions in a computer system to perform the operations of: receiving a request for a fact regarding a product offered for purchase in a product catalog from a client, wherein receiving the request for a fact includes receiving a product identifier associated with the product offered for purchase; in response to receiving the request for the fact regarding the product offered for purchase in the product catalog from the client, generating the fact regarding the product offered for purchase in the product catalog and returning the fact regarding the product offered for purchase in the product catalog to the client in response to the request; determining a probability that the client will request one or more additional facts regarding the product offered for purchase in the product catalog, wherein the probability that the client will request the one or more additional facts is determined at least in part on historical requests data describing a probability that the one or more additional facts will be requested following a request for the fact; determining an estimated cost of generating the one or more additional facts regarding the product offered for purchase in the product catalog, wherein the estimated cost is determined at least in part based upon historical cost data describing an actual historical cost to generate the one or more additional facts, the estimated cost comprising one or more of an estimated time, memory usage, processing capacity, or network bandwidth required to generate the one or more additional facts; speculatively generating the one or more additional facts regarding the product offered for purchase in the product catalog based upon the determined probability and the estimated cost of generating the one or more additional facts regarding the product offered for purchase in the product catalog; storing the speculatively generated one or more additional facts regarding the product offered for purchase in the product catalog for use in responding to a future fact request regarding the product offered for purchase in the product catalog from the client; updating the historical cost data with an actual cost to generate the one or more additional facts; receiving a request from the client for the one or more additional facts; and responding to the request for the one or more additional facts with the one or more additional facts.
1. A computer-implemented method for query optimization, the computer-implemented method comprising executing instructions in a computer system to perform the operations of: receiving a request for a fact regarding a product offered for purchase in a product catalog from a client, wherein receiving the request for a fact includes receiving a product identifier associated with the product offered for purchase; in response to receiving the request for the fact regarding the product offered for purchase in the product catalog from the client, generating the fact regarding the product offered for purchase in the product catalog and returning the fact regarding the product offered for purchase in the product catalog to the client in response to the request; determining a probability that the client will request one or more additional facts regarding the product offered for purchase in the product catalog, wherein the probability that the client will request the one or more additional facts is determined at least in part on historical requests data describing a probability that the one or more additional facts will be requested following a request for the fact; determining an estimated cost of generating the one or more additional facts regarding the product offered for purchase in the product catalog, wherein the estimated cost is determined at least in part based upon historical cost data describing an actual historical cost to generate the one or more additional facts, the estimated cost comprising one or more of an estimated time, memory usage, processing capacity, or network bandwidth required to generate the one or more additional facts; speculatively generating the one or more additional facts regarding the product offered for purchase in the product catalog based upon the determined probability and the estimated cost of generating the one or more additional facts regarding the product offered for purchase in the product catalog; storing the speculatively generated one or more additional facts regarding the product offered for purchase in the product catalog for use in responding to a future fact request regarding the product offered for purchase in the product catalog from the client; updating the historical cost data with an actual cost to generate the one or more additional facts; receiving a request from the client for the one or more additional facts; and responding to the request for the one or more additional facts with the one or more additional facts. 13. The computer-implemented method as in claim 1 , wherein the request for the one or more additional facts comprises a no execute flag.
0.532183
10. The method of claim 2 , wherein when the first customer query is a structured query, the method comprising: automatically identifying the first language; and automatically identifying an appropriate template from the structured query.
10. The method of claim 2 , wherein when the first customer query is a structured query, the method comprising: automatically identifying the first language; and automatically identifying an appropriate template from the structured query. 11. The method of claim 10 , which the first customer query is received via the Internet using a structured web form.
0.928117
18. A speech recognition system implemented on a computing device, comprising: a) a language model module for implementing a coding scheme; b) an acoustic model module associated with the coding scheme, the coding scheme associates a desired character with the desired character along with at least one subsequent character, the subsequent character being a consecutive character in a sequence of characters that define an alphabet for an alpha-numeric language; c) a receiving module that interacts with a microphone on the computing device for receiving a spoken character and at least one subsequent spoken character; and d) a processing module that interacts with the computing device for decoding the spoken character and the subsequent spoken character into the desired character based on the coding scheme.
18. A speech recognition system implemented on a computing device, comprising: a) a language model module for implementing a coding scheme; b) an acoustic model module associated with the coding scheme, the coding scheme associates a desired character with the desired character along with at least one subsequent character, the subsequent character being a consecutive character in a sequence of characters that define an alphabet for an alpha-numeric language; c) a receiving module that interacts with a microphone on the computing device for receiving a spoken character and at least one subsequent spoken character; and d) a processing module that interacts with the computing device for decoding the spoken character and the subsequent spoken character into the desired character based on the coding scheme. 20. The speech recognition system of claim 18 , further comprising a display for displaying text corresponding to a string of desired characters.
0.524096
1. A system to complete a code snippet to define an object literal, the system comprising: memory; and one or more processors coupled to the memory, the one or more processors configured to: provide a proxy object to a function that is included in code; perform global dynamic analysis by using a getter trap that is included in the proxy object to extract information regarding one or more properties of the object literal from the code, which includes the function; and generate a recommendation that recommends content for completion of the code snippet to define the object literal based at least in part on the information, the content identifying the one or more properties of the object literal.
1. A system to complete a code snippet to define an object literal, the system comprising: memory; and one or more processors coupled to the memory, the one or more processors configured to: provide a proxy object to a function that is included in code; perform global dynamic analysis by using a getter trap that is included in the proxy object to extract information regarding one or more properties of the object literal from the code, which includes the function; and generate a recommendation that recommends content for completion of the code snippet to define the object literal based at least in part on the information, the content identifying the one or more properties of the object literal. 2. The system of claim 1 , wherein the one or more processors are configured to: provide the proxy object as an argument to the function; and perform the global dynamic analysis by using the getter trap, which is included in the proxy object, to extract the information regarding the one or more properties that are requested with respect to the object literal from the code.
0.589623
1. A computer system for identifying one or more electronic documents within a collection of electronic documents, the system comprising: one or more processors programmed at least to (1) store, in a memory operatively coupled to at least one of the processors, a search level that is a whole number that is at least two, (2) accept a search query through an interface operatively coupled to at least one of the processors, the search query comprising one or more criteria that a user has explicitly entered, and the search query having an association with a topical area for a search, (3) define a subset of a collection of electronic documents, the subset comprising a plurality of electronic documents, (4) execute the search query against all documents in the subset, thereby identifying as responsive documents all documents in the subset that satisfy the entire query such that each responsive document includes each of the one or more criteria of the search query, (5) retrieving a definition of a search space, the definition of the search space comprising one or more normalized citations to every document within the search space, and the search space having an association with the topical area for the search; (6) filtering the responsive documents resulting from the execution of the search query by checking each responsive document against the definition of the search space and removing from further consideration an responsive document not found in the definition of the search space; and (7) provide information that identifies one or more of the remaining responsive documents through an interface operatively coupled to at least one of the processors; wherein the subset comprises one or more source documents within the collection and one or more additional documents within the collection, the one or more additional documents being identifiable by a process carried out for a number of iterations equal to the search level and comprising: (1) a first iteration that comprises finding one or more references in one or more of the electronic source documents, each of the references identifying a respective document in the collection, and adding to the subset each document in the collection that is identified by any of the found references but is not already in the subset, and (2) one or more subsequent iterations, each of which comprises finding one or more references in one or more of the documents added to the subset in the immediately previous iteration, each of the references identifying a respective document in the collection, and adding to the subset each document in the collection that is identified by any of the found references but is not already in the subset.
1. A computer system for identifying one or more electronic documents within a collection of electronic documents, the system comprising: one or more processors programmed at least to (1) store, in a memory operatively coupled to at least one of the processors, a search level that is a whole number that is at least two, (2) accept a search query through an interface operatively coupled to at least one of the processors, the search query comprising one or more criteria that a user has explicitly entered, and the search query having an association with a topical area for a search, (3) define a subset of a collection of electronic documents, the subset comprising a plurality of electronic documents, (4) execute the search query against all documents in the subset, thereby identifying as responsive documents all documents in the subset that satisfy the entire query such that each responsive document includes each of the one or more criteria of the search query, (5) retrieving a definition of a search space, the definition of the search space comprising one or more normalized citations to every document within the search space, and the search space having an association with the topical area for the search; (6) filtering the responsive documents resulting from the execution of the search query by checking each responsive document against the definition of the search space and removing from further consideration an responsive document not found in the definition of the search space; and (7) provide information that identifies one or more of the remaining responsive documents through an interface operatively coupled to at least one of the processors; wherein the subset comprises one or more source documents within the collection and one or more additional documents within the collection, the one or more additional documents being identifiable by a process carried out for a number of iterations equal to the search level and comprising: (1) a first iteration that comprises finding one or more references in one or more of the electronic source documents, each of the references identifying a respective document in the collection, and adding to the subset each document in the collection that is identified by any of the found references but is not already in the subset, and (2) one or more subsequent iterations, each of which comprises finding one or more references in one or more of the documents added to the subset in the immediately previous iteration, each of the references identifying a respective document in the collection, and adding to the subset each document in the collection that is identified by any of the found references but is not already in the subset. 2. The computer system of claim 1 , wherein: the one or more processors are programmed at least to compute rankings of the identified responsive documents, the computed ranking of each respective identified responsive document depending at least upon the iteration in which that document would first be added to the subset, and provide information that identifies a plurality of the responsive documents through an interface operatively coupled to at least one of the processors; and the provided information that identifies a plurality of the responsive documents comprises information about the ranking of the identified documents.
0.725987
12. The system as recited in claim 8 , wherein the server is further configured to plug a differencing module into the framework, wherein the differencing module is configured to determine differences between modified versions of documents in the server format and corresponding original versions of the documents in the server format.
12. The system as recited in claim 8 , wherein the server is further configured to plug a differencing module into the framework, wherein the differencing module is configured to determine differences between modified versions of documents in the server format and corresponding original versions of the documents in the server format. 14. The system as recited in claim 12 , wherein the server comprises a converter factory configured to generate the converter module, the merger module and the differencing module for plugging into the framework.
0.914393
1. An authoring tool, embedded in a non-transitory tangible computer readable medium, the authoring tool configured to: enable authoring of a gallery card among a plurality of cards of a wrap package, the gallery card having a fixed layout of content authored into the card, the authoring tool enabling an author to: (a) select a gallery card for authoring; (b) select a gallery item template; (c) author content into a new gallery item derived from the selected gallery item template; (d) author a plurality of gallery items for the gallery card by authoring content into each of a plurality of gallery items respectively; and (e) define a sequence order for rendering the plurality of gallery items of the gallery card; the authoring tool further including a behavior tool for declaring a transitional behavior that is associated with the plurality of gallery items when the gallery card is navigated; the authoring tool further configured to: (1) generate a plurality of gallery item descriptors for the plurality of gallery items respectively, each of the gallery item descriptors defining a fixed aspect ratio and a fixed layout for the content authored into the associated gallery item respectively; (2) generate a JSON gallery card descriptor including the plurality of gallery item descriptors; and (3) generate a JSON wrap descriptor that represents the wrap package of cards, the wrap descriptor including a plurality of card descriptors for the plurality of cards of the wrap package including the JSON gallery card descriptor for the gallery card, wherein the gallery card has a fixed presentation that is defined by: (i) the defined sequence order for rendering the plurality of gallery items; (ii) the fixed layout of the content authored into each of the plurality of gallery items respectively; and (iii) the fixed aspect ratio of the gallery card, wherein the fixed presentation of the gallery card is maintained as authored when the wrap package is rendered on a consuming device regardless of the type or class of the consuming device or the size or orientation of the rendering environment provided by the consuming device, wherein the gallery card is imbued with a behavior corresponding to the declared transitional behavior by a runtime viewer located at the consuming device when the wrap package is rendered, wherein the behavior is selected from a library of behavior definitions maintained by the runtime viewer.
1. An authoring tool, embedded in a non-transitory tangible computer readable medium, the authoring tool configured to: enable authoring of a gallery card among a plurality of cards of a wrap package, the gallery card having a fixed layout of content authored into the card, the authoring tool enabling an author to: (a) select a gallery card for authoring; (b) select a gallery item template; (c) author content into a new gallery item derived from the selected gallery item template; (d) author a plurality of gallery items for the gallery card by authoring content into each of a plurality of gallery items respectively; and (e) define a sequence order for rendering the plurality of gallery items of the gallery card; the authoring tool further including a behavior tool for declaring a transitional behavior that is associated with the plurality of gallery items when the gallery card is navigated; the authoring tool further configured to: (1) generate a plurality of gallery item descriptors for the plurality of gallery items respectively, each of the gallery item descriptors defining a fixed aspect ratio and a fixed layout for the content authored into the associated gallery item respectively; (2) generate a JSON gallery card descriptor including the plurality of gallery item descriptors; and (3) generate a JSON wrap descriptor that represents the wrap package of cards, the wrap descriptor including a plurality of card descriptors for the plurality of cards of the wrap package including the JSON gallery card descriptor for the gallery card, wherein the gallery card has a fixed presentation that is defined by: (i) the defined sequence order for rendering the plurality of gallery items; (ii) the fixed layout of the content authored into each of the plurality of gallery items respectively; and (iii) the fixed aspect ratio of the gallery card, wherein the fixed presentation of the gallery card is maintained as authored when the wrap package is rendered on a consuming device regardless of the type or class of the consuming device or the size or orientation of the rendering environment provided by the consuming device, wherein the gallery card is imbued with a behavior corresponding to the declared transitional behavior by a runtime viewer located at the consuming device when the wrap package is rendered, wherein the behavior is selected from a library of behavior definitions maintained by the runtime viewer. 2. The authoring tool of claim 1 , further configured to generate the plurality of gallery item descriptors from one or more data objects generated for each of the plurality of gallery items respectively.
0.582365
1. A system, comprising: a computer including: a non-transitory memory device storing instructions and a similarity matrix, the similarity matrix combining: a first categorization matrix defining a similarity between computer applications in a plurality of computer applications according to a first categorization of computer program calls, a second categorization matrix defining a similarity between the computer applications according to a second categorization of the computer program calls, and wherein the computer program calls are defined hierarchically and the first categorization corresponds to a first level of a hierarchy and the second categorization corresponds to a second level of the hierarchy; and a processor that executes the instructions, causing the computer to: receive a selection of one of the plurality of computer applications, and indicate at least one of the plurality of computer applications using the stored similarity matrix and based on the selected one of the plurality of computer applications.
1. A system, comprising: a computer including: a non-transitory memory device storing instructions and a similarity matrix, the similarity matrix combining: a first categorization matrix defining a similarity between computer applications in a plurality of computer applications according to a first categorization of computer program calls, a second categorization matrix defining a similarity between the computer applications according to a second categorization of the computer program calls, and wherein the computer program calls are defined hierarchically and the first categorization corresponds to a first level of a hierarchy and the second categorization corresponds to a second level of the hierarchy; and a processor that executes the instructions, causing the computer to: receive a selection of one of the plurality of computer applications, and indicate at least one of the plurality of computer applications using the stored similarity matrix and based on the selected one of the plurality of computer applications. 8. The system of claim 1 , wherein the first level of the hierarchy includes Java packages and the second level of the hierarchy includes Java classes.
0.68922
11. A computer-readable medium that stores a set of computer instructions for selecting external corpora to integrate into primary internet search engine results in response to a query, said instructions for: receiving a query, at least one server computer, from a client computer over a network; storing an offline model probability in memory; processing said query by: computing a first probabilistic estimate of relevance of external corpora to said query from offline query-related data from said offline model probability; combining said offline query-related data with user feedback data to determine a second probabilistic estimate of relevance of said external corpora to said query; selecting said external corpora to integrate into a response to said query based on said second probabilistic estimate of relevance of said external corpora to said query; and transmitting over said network, for display on said client computer search results for said query that include said external corpora selected.
11. A computer-readable medium that stores a set of computer instructions for selecting external corpora to integrate into primary internet search engine results in response to a query, said instructions for: receiving a query, at least one server computer, from a client computer over a network; storing an offline model probability in memory; processing said query by: computing a first probabilistic estimate of relevance of external corpora to said query from offline query-related data from said offline model probability; combining said offline query-related data with user feedback data to determine a second probabilistic estimate of relevance of said external corpora to said query; selecting said external corpora to integrate into a response to said query based on said second probabilistic estimate of relevance of said external corpora to said query; and transmitting over said network, for display on said client computer search results for said query that include said external corpora selected. 16. The computer-readable medium of claim 11 , further comprising including data from similar queries to said query.
0.66473
39. The method of claim 28, wherein the evaluating step further comprises evaluating an operator effective to distill a multi-value operand, having one or more values corresponding thereto and arising from a single record, into a single result value.
39. The method of claim 28, wherein the evaluating step further comprises evaluating an operator effective to distill a multi-value operand, having one or more values corresponding thereto and arising from a single record, into a single result value. 42. The method of claim 39, wherein the operator is a selector operator.
0.882929
5. A method for selecting a motion expressing artificial feelings, the method comprising: a) setting a probability of each of feeling expression behaviors performed by each of expression elements of a machine with respect to each of predetermined feelings; b) generating an initial behavior combination by extracting the feeling expression behaviors closest to predetermined feeling values of the machine with respect to each of the expression elements; c) generating behavior combinations by randomly extracting the feeling expression behaviors from each of the expression elements one at a time, wherein the probability of each of the feeling expression behaviors includes at least one of probabilities of at least one of the predetermined feelings, and calculating each of averages of the probability of the feeling expression behaviors included in the behavior combinations according to each of the predetermined feelings of the machine; d) determining which of each of the averages of the probability of the feeling expression behaviors and an optimal behavior combination using the initial behavior combination as an initial value is closer to the predetermined feeling values of the machine; and e) when any of the averages of the probability of the feeling expression behaviors is closer than the optimal behavior combination to the predetermined feeling values of the machine, substituting the behavior combinations having one of the averages of the probability of the feeling expression behaviors closer than the optimal behavior combination to the predetermined feeling values of the machine for the optimal behavior combination, and subtracting a repeated value and when the repeated value is smaller than a predetermined value, selecting the optimal behavior combination as the motion of the machine and otherwise, returning to the step c).
5. A method for selecting a motion expressing artificial feelings, the method comprising: a) setting a probability of each of feeling expression behaviors performed by each of expression elements of a machine with respect to each of predetermined feelings; b) generating an initial behavior combination by extracting the feeling expression behaviors closest to predetermined feeling values of the machine with respect to each of the expression elements; c) generating behavior combinations by randomly extracting the feeling expression behaviors from each of the expression elements one at a time, wherein the probability of each of the feeling expression behaviors includes at least one of probabilities of at least one of the predetermined feelings, and calculating each of averages of the probability of the feeling expression behaviors included in the behavior combinations according to each of the predetermined feelings of the machine; d) determining which of each of the averages of the probability of the feeling expression behaviors and an optimal behavior combination using the initial behavior combination as an initial value is closer to the predetermined feeling values of the machine; and e) when any of the averages of the probability of the feeling expression behaviors is closer than the optimal behavior combination to the predetermined feeling values of the machine, substituting the behavior combinations having one of the averages of the probability of the feeling expression behaviors closer than the optimal behavior combination to the predetermined feeling values of the machine for the optimal behavior combination, and subtracting a repeated value and when the repeated value is smaller than a predetermined value, selecting the optimal behavior combination as the motion of the machine and otherwise, returning to the step c). 6. The method of claim 5 , further comprising: f) determining whether a difference between the behavior combinations having one of the averages of the probability of the feeling expression behaviors closer than the optimal behavior combination to the predetermined feeling values of the machine and the optimal behavior combination satisfies a randomness; g) when the randomness is satisfied, substituting the optimal behavior combination with the behavior combinations having one of the averages of the probability of the feeling expression behaviors closer than the optimal behavior combination to the predetermined feeling values of the machine, and subtracting the repeated value, and when the repeated value is smaller than the predetermined value, selecting the optimal behavior combination as the motion of the machine and otherwise, returning to the step c); and h) when the randomness is not satisfied, returning to the step c).
0.5
4. A media editing system comprising: a first digital audio workstation comprising a first automation system and first audio storage, the first digital audio station in data communication with a second digital audio workstation, the second digital audio workstation comprising a second automation system and second audio storage, wherein the first digital audio workstation is configured to: receive from the second digital audio workstation an audio track and time-based metadata pertaining to the audio track; enabling a user of the first digital audio workstation to: actuate a first single control of the first digital audio workstation to select whether the first digital audio workstation (i) monitors playback of the audio track and the time-based metadata received from the second digital audio workstation; or (ii) monitors playback of a corresponding audio track and time-based metadata pertaining to the audio track stored on the first digital audio workstation; and actuate a second single control of the first digital audio workstation to cause the first digital audio workstation to start recording both the audio track and the time-based metadata pertaining to the audio track received from the second digital audio workstation, wherein recording the received audio and time-based metadata overwrites a temporally corresponding portion of the audio track and time-based metadata stored on the first digital audio workstation.
4. A media editing system comprising: a first digital audio workstation comprising a first automation system and first audio storage, the first digital audio station in data communication with a second digital audio workstation, the second digital audio workstation comprising a second automation system and second audio storage, wherein the first digital audio workstation is configured to: receive from the second digital audio workstation an audio track and time-based metadata pertaining to the audio track; enabling a user of the first digital audio workstation to: actuate a first single control of the first digital audio workstation to select whether the first digital audio workstation (i) monitors playback of the audio track and the time-based metadata received from the second digital audio workstation; or (ii) monitors playback of a corresponding audio track and time-based metadata pertaining to the audio track stored on the first digital audio workstation; and actuate a second single control of the first digital audio workstation to cause the first digital audio workstation to start recording both the audio track and the time-based metadata pertaining to the audio track received from the second digital audio workstation, wherein recording the received audio and time-based metadata overwrites a temporally corresponding portion of the audio track and time-based metadata stored on the first digital audio workstation. 6. The media editing system of claim 4 , wherein the first digital audio workstation outputs audio data and time-based metadata that is being monitored by the first digital audio workstation to a rendering system, wherein the rendering system generates signals for a plurality of speakers to generate audio that appears to originate from a source location determined by the time-based metadata being monitored by the first digital audio workstation.
0.632986
1. A computing system that has access to a hierarchically-structured document having a plurality of elements that may each be associated with one or more namespaces, the computing system comprising: one or more computer-readable storage media having computer-executable instruction for implementing a method for establishing a plurality of abbreviated namespace identifiers for a hierarchically-structured document, wherein the method comprises: an act of associating each of a plurality of associated abbreviated namespace identifiers with a hierarchical namespace; an act of accessing a hierarchically-structured document; an act of determining that at least one group identifier is associated with the hierarchically-structured document, the group identifier representing that when any of the abbreviated namespace identifiers are found associated with an element in the hierarchically-structured document, that the associated namespace is also associated with that element; and at least one of: an act of associating each of the plurality of associated abbreviated namespace identifiers with the hierarchical namespace before the act of accessing the hierarchically-structured document, and an act of reading a pre-processor directive that indicates that the at least one group identifier is associated with the hierarchically-structured document.
1. A computing system that has access to a hierarchically-structured document having a plurality of elements that may each be associated with one or more namespaces, the computing system comprising: one or more computer-readable storage media having computer-executable instruction for implementing a method for establishing a plurality of abbreviated namespace identifiers for a hierarchically-structured document, wherein the method comprises: an act of associating each of a plurality of associated abbreviated namespace identifiers with a hierarchical namespace; an act of accessing a hierarchically-structured document; an act of determining that at least one group identifier is associated with the hierarchically-structured document, the group identifier representing that when any of the abbreviated namespace identifiers are found associated with an element in the hierarchically-structured document, that the associated namespace is also associated with that element; and at least one of: an act of associating each of the plurality of associated abbreviated namespace identifiers with the hierarchical namespace before the act of accessing the hierarchically-structured document, and an act of reading a pre-processor directive that indicates that the at least one group identifier is associated with the hierarchically-structured document. 18. A computing system in accordance with claim 1 , wherein the computing system comprises a PDA.
0.602691
9. A computer system for messaging, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored therein for execution by at least one of the one or more computer processors, the program instructions comprising instructions to: receive proxy recipient information from a target recipient; detect that a message is being drafted to the target recipient determine whether the target recipient is currently available without receiving a message from the target recipient; and in response to determining that the target recipient is currently unavailable, suggest a proxy recipient for the target recipient to a user.
9. A computer system for messaging, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored therein for execution by at least one of the one or more computer processors, the program instructions comprising instructions to: receive proxy recipient information from a target recipient; detect that a message is being drafted to the target recipient determine whether the target recipient is currently available without receiving a message from the target recipient; and in response to determining that the target recipient is currently unavailable, suggest a proxy recipient for the target recipient to a user. 15. The computer system of claim 9 , wherein the proxy recipient information is provided by the user.
0.634703
7. Apparatus comprising: a processor; and a processor-readable medium storing processor-executable instructions that, when executed by the processor, perform a method comprising: identifying a plurality of alternative hypotheses for a medical billing code corresponding to a portion of text documenting a patient encounter; selecting at least two of the alternative hypotheses; and displaying the selected hypotheses to a user documenting the patient encounter; wherein the selecting comprises: scoring each hypothesis of the plurality of alternative hypotheses; and selecting hypotheses of the plurality of alternative hypotheses that exceed a threshold score.
7. Apparatus comprising: a processor; and a processor-readable medium storing processor-executable instructions that, when executed by the processor, perform a method comprising: identifying a plurality of alternative hypotheses for a medical billing code corresponding to a portion of text documenting a patient encounter; selecting at least two of the alternative hypotheses; and displaying the selected hypotheses to a user documenting the patient encounter; wherein the selecting comprises: scoring each hypothesis of the plurality of alternative hypotheses; and selecting hypotheses of the plurality of alternative hypotheses that exceed a threshold score. 9. The apparatus of claim 7 , wherein each of the plurality of alternative hypotheses represents a medical billing code selected from the group consisting of an ICD code, a CPT code, and an E&M code.
0.55287
38. The system of claim 37 further comprising second display interfacing means, in communication with the display device and the receiving means, for displaying at least one of the one or more instructions of the source program in the text-based language as text on the display device.
38. The system of claim 37 further comprising second display interfacing means, in communication with the display device and the receiving means, for displaying at least one of the one or more instructions of the source program in the text-based language as text on the display device. 39. The system of claim 38 wherein first display interfacing means and the second display interfacing means display the ladder diagram and the text on the display device simultaneously.
0.891784
3. A computer-readable medium having stored thereon computer-executable instructions for refining a search string on a mobile device, wherein the instructions, when executed by a computing system, cause the computing system to: display, on a user interface of the mobile device: a plurality of search results of a first search result dataset, wherein the first search result dataset is associated with a first search, and wherein the user interface is manipulable along a vertical axis to display additional search results of the first search results dataset; and one or more search filters, wherein the search filters are useable to refine the first search result dataset, and wherein the interface is manipulable along a horizontal axis to display other search filters; wherein the search results and the search filters are simultaneously displayed and independently selectable; and in response to receiving a selection of at least one of the one or more search filters, perform a second search of a data storage component of the mobile device based on; the first search or one or more of the plurality of search results of the first search result dataset, and the selected search filter; wherein one or more search results of the second search replace one or more search results of the first search result dataset displayed on the user interface.
3. A computer-readable medium having stored thereon computer-executable instructions for refining a search string on a mobile device, wherein the instructions, when executed by a computing system, cause the computing system to: display, on a user interface of the mobile device: a plurality of search results of a first search result dataset, wherein the first search result dataset is associated with a first search, and wherein the user interface is manipulable along a vertical axis to display additional search results of the first search results dataset; and one or more search filters, wherein the search filters are useable to refine the first search result dataset, and wherein the interface is manipulable along a horizontal axis to display other search filters; wherein the search results and the search filters are simultaneously displayed and independently selectable; and in response to receiving a selection of at least one of the one or more search filters, perform a second search of a data storage component of the mobile device based on; the first search or one or more of the plurality of search results of the first search result dataset, and the selected search filter; wherein one or more search results of the second search replace one or more search results of the first search result dataset displayed on the user interface. 18. The computer-readable medium of claim 3 , wherein the instructions further cause the computing system to: display a horizontal indicator on the user interface; and in response to receiving a user manipulation of the horizontal indicator, display a next filter.
0.585754
26. A computing system comprising: one or more processors; one or more computer-readable storage media storing computer-executable instructions; a wake word evaluation module maintained in the one or more computer-readable storage media and executed by the one or more processors to: receive an audio input including a candidate word for evaluation as a wake word that activates functionality of a computing device; determine a plurality of values from wake word metrics for the candidate word, wherein the plurality of values includes a word frequency value that is determined for the candidate word by determining a frequency of occurrence of the candidate word in a test set comprising one or more words; and determine an overall score for the candidate wake word based at least in part on the plurality of values.
26. A computing system comprising: one or more processors; one or more computer-readable storage media storing computer-executable instructions; a wake word evaluation module maintained in the one or more computer-readable storage media and executed by the one or more processors to: receive an audio input including a candidate word for evaluation as a wake word that activates functionality of a computing device; determine a plurality of values from wake word metrics for the candidate word, wherein the plurality of values includes a word frequency value that is determined for the candidate word by determining a frequency of occurrence of the candidate word in a test set comprising one or more words; and determine an overall score for the candidate wake word based at least in part on the plurality of values. 27. The computing system as recited in claim 26 , wherein the word frequency value is normalized to value between one and zero.
0.771785
47. A non-transitory computer-readable storage medium storing instructions for transmitting an electronic document, the instructions causing one or more computer processors at an intermediate computer that is remote from an electronic device sending a message to perform operations comprising: receiving the email message having a delivery address from the mobile electronic device; determining that the email message has an attached document; determining that the attached document is to be cleansed of metadata according to a cleansing policy; automatically removing metadata from the attached document; creating a cleansed version of the attached document at the intermediate computer; replacing in the email message the attached document with the cleansed version of the attached document; and sending the email message with the cleansed version of the attached document from the intermediate computer to the delivery address.
47. A non-transitory computer-readable storage medium storing instructions for transmitting an electronic document, the instructions causing one or more computer processors at an intermediate computer that is remote from an electronic device sending a message to perform operations comprising: receiving the email message having a delivery address from the mobile electronic device; determining that the email message has an attached document; determining that the attached document is to be cleansed of metadata according to a cleansing policy; automatically removing metadata from the attached document; creating a cleansed version of the attached document at the intermediate computer; replacing in the email message the attached document with the cleansed version of the attached document; and sending the email message with the cleansed version of the attached document from the intermediate computer to the delivery address. 50. The storage medium of claim 47 , wherein the cleansing policy allows a user to choose not to cleanse pre-specified types of metadata.
0.706009
3. The method of claim 1 , wherein the particular organization represents a class, wherein users internal to the particular organization are included in the class, and wherein users external to the organization are not included in the class.
3. The method of claim 1 , wherein the particular organization represents a class, wherein users internal to the particular organization are included in the class, and wherein users external to the organization are not included in the class. 4. The method of claim 3 , wherein the class of a user is indicated by associated information stored in an address book.
0.896241
8. An article of manufacture having machine-readable instructions executable by a digital processing apparatus to perform method steps for fitting a golf club, the method steps comprising: receiving machine readable input data from an input data source wherein said input data includes measurements of parameters for a plurality of swings of a single golf club; normalizing said input data to eliminate aberrant input data; choosing parameters; analyzing the interrelationship of at least two of said chosen parameters to determined inferences therefrom; prescribing a golf club chemistry based upon said inferences; said chosen parameters comprising: a SPEED parameter represented by a SPEED data block, wherein said SPEED data block contains measurements of the golf club head speed at the point of impact with a golf ball; a TEMPO parameter represented by a TEMPO data block, wherein said TEMPO data block contains measurements of the time required for the club head to travel from the address position to its impact point with the golf ball; a FACE ANGLE parameter represented by a FACE SINGLE data block, wherein said FACE ANGLE data block contains measurements of the club head face relative to the club head's swing path at the point of impact with the golf ball; a DYNAMIC LOFT parameter represented by a DYNAMIC LOFT data block, wherein said DYNAMIC LOFT data block contains measurements of the actual loft imparted on a golf ball by the club head face at the point of impact with the golf ball, wherein said measurement is taken relative to the ground plane upon which the golfer is standing; a TRAJECTORY parameter represented by a TRAJECTORY data block, wherein said TRAJECTORY data block contains measurements reflecting the club head's vector relative to the ground plane upon which the golfer is standing; a DYNAMIC LIE parameter represented by a DYNAMIC LIE data block, wherein said DYNAMIC LIE data block contains measurements reflecting the test club's indigenous lie angle and the test club's dynamic lie angle at the point of impact; a ROTATION parameter represented by a ROTATION data block, wherein said ROTATION data block contains measurements reflecting the delta from the test club head's static position and the test club head's dynamic position measured as a rotation of the club head about said club shaft's longitudinal axis; and a HEIGHT parameter represented by a HEIGHT data block, wherein said HEIGHT data block contains a measurement of the test golfer's physical height.
8. An article of manufacture having machine-readable instructions executable by a digital processing apparatus to perform method steps for fitting a golf club, the method steps comprising: receiving machine readable input data from an input data source wherein said input data includes measurements of parameters for a plurality of swings of a single golf club; normalizing said input data to eliminate aberrant input data; choosing parameters; analyzing the interrelationship of at least two of said chosen parameters to determined inferences therefrom; prescribing a golf club chemistry based upon said inferences; said chosen parameters comprising: a SPEED parameter represented by a SPEED data block, wherein said SPEED data block contains measurements of the golf club head speed at the point of impact with a golf ball; a TEMPO parameter represented by a TEMPO data block, wherein said TEMPO data block contains measurements of the time required for the club head to travel from the address position to its impact point with the golf ball; a FACE ANGLE parameter represented by a FACE SINGLE data block, wherein said FACE ANGLE data block contains measurements of the club head face relative to the club head's swing path at the point of impact with the golf ball; a DYNAMIC LOFT parameter represented by a DYNAMIC LOFT data block, wherein said DYNAMIC LOFT data block contains measurements of the actual loft imparted on a golf ball by the club head face at the point of impact with the golf ball, wherein said measurement is taken relative to the ground plane upon which the golfer is standing; a TRAJECTORY parameter represented by a TRAJECTORY data block, wherein said TRAJECTORY data block contains measurements reflecting the club head's vector relative to the ground plane upon which the golfer is standing; a DYNAMIC LIE parameter represented by a DYNAMIC LIE data block, wherein said DYNAMIC LIE data block contains measurements reflecting the test club's indigenous lie angle and the test club's dynamic lie angle at the point of impact; a ROTATION parameter represented by a ROTATION data block, wherein said ROTATION data block contains measurements reflecting the delta from the test club head's static position and the test club head's dynamic position measured as a rotation of the club head about said club shaft's longitudinal axis; and a HEIGHT parameter represented by a HEIGHT data block, wherein said HEIGHT data block contains a measurement of the test golfer's physical height. 10. The article of manufacture recited in claim 8, said inferences comprising: a shaft flex inference, where in said shaft flex inference comprises the union of a first shaft frequency and a second shaft frequency, wherein said first shaft frequency comprises the intersection of said SPEED parameter and said TEMPO parameter, and wherein said second shaft frequency comprise the intersection of said SPEED parameter and said FACE ANGLE parameter; a club head loft inference, wherein said club head loft inference comprises the union of a first loft parameter and a second loft parameter, wherein said first loft parameter comprises the intersection of said SPEED parameter and said DYNAMIC LOFT parameter, and wherein said second loft parameter comprises the intersection of said DYNAMIC LOFT parameter and said TRAJECTORY parameter; a lie angle inference, wherein said lie angle inference comprises the union of a club shaft length parameter and an effective lie angle parameter, said club shaft length parameter comprising the intersection of said DYNAMIC LIE parameter and said HEIGHT parameter plus the intersection of said SHOT CHOICE parameter and said SHAFT TYPE parameter, and wherein said effective lie angle comprises said DYNAMIC LIE parameter plus an effective lie angle parameter for a club used to gather said input data; an offset inference, wherein said offset inference comprises the union of said NET ROTATION parameter and said FACE ANGLE parameter, and wherein aid NET ROTATION parameter comprises the union of said HEIGHT parameter and said ROTATION parameter; a bounce angle inference, wherein said bounce angle inference comprises the intersection of said DYNAMIC LOFT parameter and said TRAJECTORY parameter; a swing weight inference, wherein said swing weight inference comprises the union of a first swing weight parameter and a second swing weight parameter, wherein said first swing weight parameter comprises the intersection of said HEIGHT parameter and said TEMPO parameter, and wherein said second swing weight parameter comprise the intersection of said SPEED parameter and said TEMPO parameter; a shaft weight inference, wherein said shaft weight inference comprises W', wherein W'=(((wt.sub.x .times.W1)+(wt.sub.y .times.W2)+(wt.sub.z .times.W3)).div.100), and wherein W1 comprises the intersection of said of said LENGTH parameter and said swing weight inference, and wherein W2 comprises the intersection of said SPEED parameter and said TEMPO parameter, and wherein W3 comprises the intersection of said SPEED parameter and said DYNAMIC LOFT parameter; a bend point inference, wherein said bend point inference comprises the intersection of said SPEED parameter and said DYNAMIC LOFT parameter; a shaft torque inference, wherein said shaft torque inference comprises the intersection of said SPEED date block with the union of said NET ROTATION parameter and said FACE ANGLE parameter; and a grip size inference, wherein said grip size inference comprises the union of a first grip size parameter and a second grip size parameter, wherein said first grips size parameter comprises the intersection of said HEIGHT parameter and said ROTATION parameter, and wherein said second grip size parameter comprises the intersection of said FACE ANGLE parameter and said ROTATION parameter.
0.614421
5. An XML-based preprocessor, stored in one or more computer-readable storage media, comprising: a source file parser configured to parse a programmed source file and generate an in-memory graph of a syntactic structure of the programmed source file, wherein the in-memory graph is a syntactic representation of the programmed source file; an XML (Extensible Markup Language) generator configured to generate an XML document from the syntactic representation of the programmed source file, the XML generator further configured to: validate the XML document with an XML schema; search for a first Extensible Stylesheet Language (XSL) transform, wherein the first XSL transform is designated in the programmed source file as a first module-level attribute, the first module-level attribute being user-defined such that the XML-based preprocessor recognizes the first module-level attribute and a source file compiler does not; apply the first XSL transform to the XML document to generate a modified XML document; validate the modified XML document with the XML schema; search for a second XSL transform, wherein the second XSL transform is designated in the programmed source file as a second module-level attribute, the second module-level attribute being user-defined such that the XML-based preprocessor recognizes the attribute and the source file compiler does not; and an output file generator configured to generate an output file from the modified XML document in a format of the programmed source file.
5. An XML-based preprocessor, stored in one or more computer-readable storage media, comprising: a source file parser configured to parse a programmed source file and generate an in-memory graph of a syntactic structure of the programmed source file, wherein the in-memory graph is a syntactic representation of the programmed source file; an XML (Extensible Markup Language) generator configured to generate an XML document from the syntactic representation of the programmed source file, the XML generator further configured to: validate the XML document with an XML schema; search for a first Extensible Stylesheet Language (XSL) transform, wherein the first XSL transform is designated in the programmed source file as a first module-level attribute, the first module-level attribute being user-defined such that the XML-based preprocessor recognizes the first module-level attribute and a source file compiler does not; apply the first XSL transform to the XML document to generate a modified XML document; validate the modified XML document with the XML schema; search for a second XSL transform, wherein the second XSL transform is designated in the programmed source file as a second module-level attribute, the second module-level attribute being user-defined such that the XML-based preprocessor recognizes the attribute and the source file compiler does not; and an output file generator configured to generate an output file from the modified XML document in a format of the programmed source file. 6. An XML-based preprocessor as recited in claim 5 , wherein: the programmed source file is a C# (C-Sharp) source file; and the output file generator is further configured to generate a C# output file from the modified XML document.
0.5
9. A computer program product, stored on a non-transitory computer readable medium, comprising instructions that when executed on one or more computers cause the one or more computers to perform operations implementing a speech recognition model training service, the operations comprising: receiving service requests comprising new model generation requests and model update requests, wherein each service request is associated with speech data; for each received service request, generating a speech recognition model corresponding to the service request in response to receiving the service request and associated speech data; maintaining a training database of speech samples, wherein maintaining the training database comprises augmenting the training database with speech data associated with each received service request; and maintaining a model store of generated speech recognition models, wherein maintaining the model store comprises storing generated speech recognition models.
9. A computer program product, stored on a non-transitory computer readable medium, comprising instructions that when executed on one or more computers cause the one or more computers to perform operations implementing a speech recognition model training service, the operations comprising: receiving service requests comprising new model generation requests and model update requests, wherein each service request is associated with speech data; for each received service request, generating a speech recognition model corresponding to the service request in response to receiving the service request and associated speech data; maintaining a training database of speech samples, wherein maintaining the training database comprises augmenting the training database with speech data associated with each received service request; and maintaining a model store of generated speech recognition models, wherein maintaining the model store comprises storing generated speech recognition models. 11. The computer program product of claim 9 wherein the operations further comprise: receiving additional data associated with a first new model service request, wherein the additional data comprises a text representation of a word or phrase to be modeled, a user identifier identifying a speaker, and a specification of a type of model to be generated; determining, from the specification of the type of model, that a particular type of model is to be generated; and generating the speech recognition model as a model of the particular type.
0.601106
1. A method executing on a processor of a computing device for collecting and analyzing contextual information relating to clients of a call center coupled to an aggregator agent, comprising: initializing a communication channel between the call center and at least one client; wherein the communication channel is used to transmit contextual data packets and conversational data packets; establishing between the call center and the at least one client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit the contextual information; receiving contextual information relating to at least one client; wherein the contextual information is packetized and arranged according to the predefined structured hierarchy; receiving other sets of contextual information relating to other clients, the other sets of contextual information sharing at least some common information with the received contextual information; identifying relevant contextual information from the received contextual information and the received other sets of contextual information; providing the identified contextual information to the aggregator agent that aggregates the relevant contextual information and the other sets of contextual information; determining when the aggregated contextual information meets a threshold and based on the determination determining when to receive and aggregate more contextual information in addition to previously collected contextual information; during the aggregating, identifying levels of relevancy of the received contextual information and the other sets of contextual information; receiving a set of events from the aggregator agent; executing actions corresponding to the set of events; and clearing the aggregated contextual information and the threshold for a new analysis.
1. A method executing on a processor of a computing device for collecting and analyzing contextual information relating to clients of a call center coupled to an aggregator agent, comprising: initializing a communication channel between the call center and at least one client; wherein the communication channel is used to transmit contextual data packets and conversational data packets; establishing between the call center and the at least one client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit the contextual information; receiving contextual information relating to at least one client; wherein the contextual information is packetized and arranged according to the predefined structured hierarchy; receiving other sets of contextual information relating to other clients, the other sets of contextual information sharing at least some common information with the received contextual information; identifying relevant contextual information from the received contextual information and the received other sets of contextual information; providing the identified contextual information to the aggregator agent that aggregates the relevant contextual information and the other sets of contextual information; determining when the aggregated contextual information meets a threshold and based on the determination determining when to receive and aggregate more contextual information in addition to previously collected contextual information; during the aggregating, identifying levels of relevancy of the received contextual information and the other sets of contextual information; receiving a set of events from the aggregator agent; executing actions corresponding to the set of events; and clearing the aggregated contextual information and the threshold for a new analysis. 4. The method of claim 1 further comprising: collecting additional contextual information relating to at least one client.
0.522081
1. A method for configuring an audio channel with a processor, the method comprising: generating a confidence metric indicative of at least one control cue in a telecommunication audio feed, wherein generating the confidence metric comprises: analyzing the at least one control cue to determine a cue type; assigning a confidence metric value for the at least one control cue based on the cue type, wherein the cue type comprises both explicit speech to perform an action and muffled voice having a lower amplitude than the average amplitude of other portions of the audio feed; comparing the confidence metric value to a predetermined threshold value associated with the cue type; updating a context history with the cue type and the confidence metric value; and configuring an input of the audio channel based on the confidence metric and the context history.
1. A method for configuring an audio channel with a processor, the method comprising: generating a confidence metric indicative of at least one control cue in a telecommunication audio feed, wherein generating the confidence metric comprises: analyzing the at least one control cue to determine a cue type; assigning a confidence metric value for the at least one control cue based on the cue type, wherein the cue type comprises both explicit speech to perform an action and muffled voice having a lower amplitude than the average amplitude of other portions of the audio feed; comparing the confidence metric value to a predetermined threshold value associated with the cue type; updating a context history with the cue type and the confidence metric value; and configuring an input of the audio channel based on the confidence metric and the context history. 13. The method of claim 1 , further comprising outputting an audio cue indicative that the processor has configured the input to the audio channel.
0.566633
9. A non-transitory computer readable storage medium storing instructions for searching a content collection, the instructions when executed by a processor causing the processor to: identify query descriptors for query content of a search request, the query descriptors characterizing the query content; for each content piece of at least a portion of a content collection: identify a subset of content descriptors of the content piece that corresponds to at least a portion of the query descriptors, the content descriptors characterizing the content piece, one or more of the subset of the content descriptors corresponding to one or more blur transforms; identify first candidate regions of the content piece, one or more of the first candidate regions overlapping with at least another one of the first candidate regions, each first candidate region corresponding to at east a portion of the subset of the content descriptors; and select the content piece for inclusion in a matching content subset of the content collection when at least one of the first candidate regions comprises a first proportionate size greater than a first proportion threshold; and provide the matching content subset in response to the search request.
9. A non-transitory computer readable storage medium storing instructions for searching a content collection, the instructions when executed by a processor causing the processor to: identify query descriptors for query content of a search request, the query descriptors characterizing the query content; for each content piece of at least a portion of a content collection: identify a subset of content descriptors of the content piece that corresponds to at least a portion of the query descriptors, the content descriptors characterizing the content piece, one or more of the subset of the content descriptors corresponding to one or more blur transforms; identify first candidate regions of the content piece, one or more of the first candidate regions overlapping with at least another one of the first candidate regions, each first candidate region corresponding to at east a portion of the subset of the content descriptors; and select the content piece for inclusion in a matching content subset of the content collection when at least one of the first candidate regions comprises a first proportionate size greater than a first proportion threshold; and provide the matching content subset in response to the search request. 11. The non-transitory computer readable storage medium of claim 9 , wherein each first candidate regions is contained within a whole region of the content piece.
0.638763
1. A method for determining a person's response to a retail element, based on the person's facial expression and shopping behavior, comprising the following steps of: a) detecting and tracking a face from first input images captured by at least a first means for capturing images, estimating two-dimensional and three-dimensional poses of the face, and localizing facial features, using at least a control and processing system, b) estimating gaze direction of the person using the two-dimensional and three-dimensional poses and positions of the facial features and changes in affective state of the person by extracting emotion-sensitive features, and recognizing a demographic category of the person, c) detecting and tracking the person from second input images captured by at least a second means for capturing images, producing a trajectory of the person, and estimating body orientation, using the control and processing system, d) identifying the shopping behaviors of the person toward the retail element, utilizing position and the body orientation of the person relative to the retail element, and e) determining intermediate responses and end response of the person to the retail element by analyzing the changes in affective states and interest, in the context of the shopping behavior and the demographics category of the person, wherein the first means for capturing images and the second means for capturing images are connected to the control and processing system via at least a means for video interface, and wherein the shopping behaviors include showing interest, engagement, interaction, or purchasing.
1. A method for determining a person's response to a retail element, based on the person's facial expression and shopping behavior, comprising the following steps of: a) detecting and tracking a face from first input images captured by at least a first means for capturing images, estimating two-dimensional and three-dimensional poses of the face, and localizing facial features, using at least a control and processing system, b) estimating gaze direction of the person using the two-dimensional and three-dimensional poses and positions of the facial features and changes in affective state of the person by extracting emotion-sensitive features, and recognizing a demographic category of the person, c) detecting and tracking the person from second input images captured by at least a second means for capturing images, producing a trajectory of the person, and estimating body orientation, using the control and processing system, d) identifying the shopping behaviors of the person toward the retail element, utilizing position and the body orientation of the person relative to the retail element, and e) determining intermediate responses and end response of the person to the retail element by analyzing the changes in affective states and interest, in the context of the shopping behavior and the demographics category of the person, wherein the first means for capturing images and the second means for capturing images are connected to the control and processing system via at least a means for video interface, and wherein the shopping behaviors include showing interest, engagement, interaction, or purchasing. 18. The method according to claim 1 , wherein the method further comprises a step of detecting an incident of purchase and identifying the retail element that is purchased based on a foreground image analysis performed on a shelf and on a shopping cart or basket.
0.526982
16. The system of claim 13 , wherein the first stage recognizer is located in a first device and the second stage recognizer is located in a second device.
16. The system of claim 13 , wherein the first stage recognizer is located in a first device and the second stage recognizer is located in a second device. 17. The system of claim 16 , wherein the first device receives the acoustic input signal and sends the acoustic input signal to the second device over a network.
0.940996
13. A computer-implemented structure for storing XML data in a relational database, the computer implemented structure comprising a first table structure, the first table structure comprising: a document identifier stored in a volatile or non-volatile computer usable storage medium corresponding to an XML document; and a path string for a node within the XML document stored in the volatile or non-volatile computer usable storage medium, wherein the path string comprises a full path for the node from a root node of the XML document.
13. A computer-implemented structure for storing XML data in a relational database, the computer implemented structure comprising a first table structure, the first table structure comprising: a document identifier stored in a volatile or non-volatile computer usable storage medium corresponding to an XML document; and a path string for a node within the XML document stored in the volatile or non-volatile computer usable storage medium, wherein the path string comprises a full path for the node from a root node of the XML document. 14. The computer-implemented structure of claim 13 in which the document identifier is a unique identifier for each different XML document.
0.764173
11. A computing device for performing large vocabulary speech recognition comprising: computer readable memory; one or more processors capable of executing program instructions read from said memory; a microphone or audio input for providing an electronic signal representing an utterance to be recognized; a speaker or audio output for enabling an electronic representation of sound produced in said device to be transduced into a corresponding sound; and programming recorded in the memory including instructions for: performing large vocabulary speech recognition that responds to the electronic representations of each of a sequence of one or more utterances received from the microphone or audio input by: selecting as a best scoring recognition candidate the one or more words recognized by the speech recognition as corresponding to the utterance; detecting the end of the utterance; and then responding to the detection of the end of utterance by providing TTS output to said speaker or audio output saying the one or more words of said best scoring recognition candidate for the utterance whereby the device can generate audio feedback on the one or more words recognized for each of a succession of large vocabulary speech utterances at the end of each such utterance.
11. A computing device for performing large vocabulary speech recognition comprising: computer readable memory; one or more processors capable of executing program instructions read from said memory; a microphone or audio input for providing an electronic signal representing an utterance to be recognized; a speaker or audio output for enabling an electronic representation of sound produced in said device to be transduced into a corresponding sound; and programming recorded in the memory including instructions for: performing large vocabulary speech recognition that responds to the electronic representations of each of a sequence of one or more utterances received from the microphone or audio input by: selecting as a best scoring recognition candidate the one or more words recognized by the speech recognition as corresponding to the utterance; detecting the end of the utterance; and then responding to the detection of the end of utterance by providing TTS output to said speaker or audio output saying the one or more words of said best scoring recognition candidate for the utterance whereby the device can generate audio feedback on the one or more words recognized for each of a succession of large vocabulary speech utterances at the end of each such utterance. 16. A computing device as in claim 11 wherein: said device has a display; said recorded programming instructions include instructions for: causing said best scoring recognition candidates to be shown on said display as said utterances are recognized; and enabling a user to select whether or not to have said audio feedback generated at the end of each such utterance.
0.563369
5. The method according to claim 1 , wherein selecting the parameters comprises selecting performance-oriented parameters to monitor during the execution of the query workload.
5. The method according to claim 1 , wherein selecting the parameters comprises selecting performance-oriented parameters to monitor during the execution of the query workload. 6. The method according to claim 5 , wherein the performance-oriented parameters comprise any one or more of: response time, average processor (CPU) utilization, sequential Input/Output (I/O) throughput rate, random I/O operations rate, size of the largest n-way table join, memory utilization, and network utilization.
0.85859
1. A computer implemented method for manipulating a graphical representation of a real-world object in a computer drawing application comprising: (a) defining, using a computer, a semantic behavior for the real-world object, wherein: (i) the semantic behavior comprises a collision rule, an orientation rule, an affinity rule, and an attachment rule; (ii) the collision rule defines an intersection between geometries or bounding boxes of a subject object and a host object; (iii) the orientation rule defines an alignment of the subject object with a geometry of the host object; (iv) the affinity rule defines placement rules that determine where the subject object can be legally placed in a drawing; (v) the attachment rule defines an attachment between the subject object and the host object wherein both the subject object and the host object move if either the host object or subject object is moved; (vi) the affinity rule has procedural priority over the orientation rule; (vii) the attachment rule has procedural priority over the affinity rule and the orientation rule; and (viii) the collision rule has procedural priority over the attachment rule, the affinity rule, and the orientation rule; (b) obtaining, using a computer, a graphical representation of the real-world object, wherein the graphical representation is referred to as the subject object; (c) assigning, using a computer, the semantic behavior to the subject object, wherein: (i) the semantic behavior defines a behavioral rule for placement of the subject object into the drawing; (ii) the behavioral rule specifies a host object type that specifies a type of object that the behavioral rule applies to; (iii) the behavioral rule specifies an exclusion host identifier that identifies a particular host object for which an application of the behavioral rule will be excluded; and (d) placing, using a computer, the subject object into the drawing using the computer-drawing application, wherein the subject object automatically, without additional user input, places itself into the drawing based on the semantic behavior.
1. A computer implemented method for manipulating a graphical representation of a real-world object in a computer drawing application comprising: (a) defining, using a computer, a semantic behavior for the real-world object, wherein: (i) the semantic behavior comprises a collision rule, an orientation rule, an affinity rule, and an attachment rule; (ii) the collision rule defines an intersection between geometries or bounding boxes of a subject object and a host object; (iii) the orientation rule defines an alignment of the subject object with a geometry of the host object; (iv) the affinity rule defines placement rules that determine where the subject object can be legally placed in a drawing; (v) the attachment rule defines an attachment between the subject object and the host object wherein both the subject object and the host object move if either the host object or subject object is moved; (vi) the affinity rule has procedural priority over the orientation rule; (vii) the attachment rule has procedural priority over the affinity rule and the orientation rule; and (viii) the collision rule has procedural priority over the attachment rule, the affinity rule, and the orientation rule; (b) obtaining, using a computer, a graphical representation of the real-world object, wherein the graphical representation is referred to as the subject object; (c) assigning, using a computer, the semantic behavior to the subject object, wherein: (i) the semantic behavior defines a behavioral rule for placement of the subject object into the drawing; (ii) the behavioral rule specifies a host object type that specifies a type of object that the behavioral rule applies to; (iii) the behavioral rule specifies an exclusion host identifier that identifies a particular host object for which an application of the behavioral rule will be excluded; and (d) placing, using a computer, the subject object into the drawing using the computer-drawing application, wherein the subject object automatically, without additional user input, places itself into the drawing based on the semantic behavior. 9. The method of claim 1 , further comprising: identifying behavior patterns and styles based on usage of the subject object; and utilizing the behavior patterns and styles to define the semantic behavior.
0.516282
20. A conferencing method, comprising: obtaining audio of a conference for an endpoint; detecting speech in the obtained audio; determining that the detected speech constitutes a speech fragment; generating an indicium indicative of the determined speech fragment by generating an audible cue; and including the generated indicium in data of the conference by including the audible cue in audio data of the endpoint.
20. A conferencing method, comprising: obtaining audio of a conference for an endpoint; detecting speech in the obtained audio; determining that the detected speech constitutes a speech fragment; generating an indicium indicative of the determined speech fragment by generating an audible cue; and including the generated indicium in data of the conference by including the audible cue in audio data of the endpoint. 23. The method of claim 20 , wherein determining that the detected speech constitutes the speech fragment comprises determining that a character of the detected speech meets at least one criterion, wherein the at least one criterion is selected from the group consisting of an intonation, a pitch, an inflection, an emotion, a duration, and a quantified speech recognition detail.
0.537634
7. A system comprising: a processor; and a computer-readable storage device having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving a search query, wherein the search query is: formatted according to a standard language for containing and annotating interpretations of user input, the standard language being different than a language the search query was recorded in; and based on a natural language spoken query from a user; retrieving an N-best list of recognition results based on the search query; transmitting the N-best list of recognition results to a plurality of user devices comprising a first user device and a second user device; after presenting the N-best list on the plurality of user devices, receiving disambiguation input from the first user device, the disambiguation input comprising a vocal disambiguation input and a gesture disambiguation input, the disambiguation input indicating an entry in the N-best list; and transmitting to the second user device additional information associated with the entry based on the disambiguation input; wherein the additional information is a map indicating an address for the entry.
7. A system comprising: a processor; and a computer-readable storage device having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving a search query, wherein the search query is: formatted according to a standard language for containing and annotating interpretations of user input, the standard language being different than a language the search query was recorded in; and based on a natural language spoken query from a user; retrieving an N-best list of recognition results based on the search query; transmitting the N-best list of recognition results to a plurality of user devices comprising a first user device and a second user device; after presenting the N-best list on the plurality of user devices, receiving disambiguation input from the first user device, the disambiguation input comprising a vocal disambiguation input and a gesture disambiguation input, the disambiguation input indicating an entry in the N-best list; and transmitting to the second user device additional information associated with the entry based on the disambiguation input; wherein the additional information is a map indicating an address for the entry. 10. The system of claim 7 , wherein the additional information is retrieved from a corporate personnel directory.
0.592593
1. A method, implemented by a computing device, for filtering content based on acquiring data associated with language identification, comprising: providing an interactive program guide via a computing device to present content to a customer on a display; acquiring data associated with language identification from a plurality of sources associated with the content of the interactive program guide; performing an analysis of the acquired data associated with language identification to determine which source of the plurality of sources associated with the content of the interactive program guide has a highest priority; in response to performing the analysis of the acquired data, utilizing the source with the highest priority to determine a preferred language of the interactive program guide and filtering the content from the interactive program guide based on the preferred language identified using the acquired data, wherein filtering content based on a preferred language identified using acquired data comprises the computing device filtering data based on a parameter associated with and obtained from a user device or based on the user's use of the user device; and displaying the interactive program guide comprising the filtered content in the preferred language on the display.
1. A method, implemented by a computing device, for filtering content based on acquiring data associated with language identification, comprising: providing an interactive program guide via a computing device to present content to a customer on a display; acquiring data associated with language identification from a plurality of sources associated with the content of the interactive program guide; performing an analysis of the acquired data associated with language identification to determine which source of the plurality of sources associated with the content of the interactive program guide has a highest priority; in response to performing the analysis of the acquired data, utilizing the source with the highest priority to determine a preferred language of the interactive program guide and filtering the content from the interactive program guide based on the preferred language identified using the acquired data, wherein filtering content based on a preferred language identified using acquired data comprises the computing device filtering data based on a parameter associated with and obtained from a user device or based on the user's use of the user device; and displaying the interactive program guide comprising the filtered content in the preferred language on the display. 7. The method of claim 1 wherein the filtering content based on a preferred language identified using the acquired data further comprises filtering data based on an identified preferred language of the user device or filtering data based on the user's behavior derived from use of the user device.
0.647516
34. The method of claim 33 , wherein the operational policies and procedures under which the presentation authority operates each has a policy identifier.
34. The method of claim 33 , wherein the operational policies and procedures under which the presentation authority operates each has a policy identifier. 37. The method of claim 34 , wherein the policy identifier of the presentation authority is included in a Reason entry of the signature field.
0.966788
31. The method of claim 15 in which said step for applying a recursive reduction procedure includes the step of applying an off-by-one reduction procedure which comprises the steps of: determining whether the rule R of said acquired grammar element is an OR rule; providing an add rules list; providing a remove rules list; when said rule R is determined to be an OR rule, then acquiring each subrule B thereof which is an AND rule and acquiring each other subrule C thereof, comparing each acquired subrule B with each acquired subrule C and determining from said comparison whether they differ by one subrule M of subrule B; identifying said differing one base component when said acquired subrule B and said acquired subrule C differ by one base component; generating a new rule formed of acquired subrule B with said differing one subrule M having a zero-based repetition symbol; adding said new rule to said add rules list; adding said acquired said rule B and said acquired subrule C to said remove rules list; when all said subrules B have been compared with all said subrules C, removing said subrules of said remove rules list and adding said rules of said add rules list as subrules of said rule R; then emptying said remove rules list and said add rules list; and repeating the above steps until said step for adding said new rule to said add rules list does not occur.
31. The method of claim 15 in which said step for applying a recursive reduction procedure includes the step of applying an off-by-one reduction procedure which comprises the steps of: determining whether the rule R of said acquired grammar element is an OR rule; providing an add rules list; providing a remove rules list; when said rule R is determined to be an OR rule, then acquiring each subrule B thereof which is an AND rule and acquiring each other subrule C thereof, comparing each acquired subrule B with each acquired subrule C and determining from said comparison whether they differ by one subrule M of subrule B; identifying said differing one base component when said acquired subrule B and said acquired subrule C differ by one base component; generating a new rule formed of acquired subrule B with said differing one subrule M having a zero-based repetition symbol; adding said new rule to said add rules list; adding said acquired said rule B and said acquired subrule C to said remove rules list; when all said subrules B have been compared with all said subrules C, removing said subrules of said remove rules list and adding said rules of said add rules list as subrules of said rule R; then emptying said remove rules list and said add rules list; and repeating the above steps until said step for adding said new rule to said add rules list does not occur. 32. The method of claim 31 in which said step of comparing each acquired subrule B with each acquired subrule C includes the steps of: determining whether subrule M of subrule B subsumes said subrule C when said subrule C is not an AND rule; when a said subrule M does not subsume said subrule C, then determining whether said subrule M has a zero-based repetition symbol; when said subrule M does not have a zero-based repetition symbol, then identifying said subrule M; then, carrying out said step for generating a new rule.
0.738206
1. A method for selectively obtaining information stored in a business warehouse, the method comprising: requesting, by a client from a server, a list of available data access services, the list of data access services being part of a library containing at least one data access service for each of a plurality of on-line analytical processing data access queries, the data access service being a service offered by the server to the client to provide access to an on-line analytical processing query performed at the server system through a service call to the data access service, the data access service having a predefined selection of input parameters to define a selection of data from the query and a predefined selection of a single output parameter to define output data to be provided as a result of the selection of the data from the query based on the input parameters, at least one of the data access services being built using a data access service designer, the data access service designer including an object tagger to attach semantic information to a service and its input and output parameters; invoking, by the client, a selected data access service from the list; and presenting, at the client, data within the business warehouse using the selected data access service via a data access service provider wrapping an existing business warehouse object type to expose its data as the data access service.
1. A method for selectively obtaining information stored in a business warehouse, the method comprising: requesting, by a client from a server, a list of available data access services, the list of data access services being part of a library containing at least one data access service for each of a plurality of on-line analytical processing data access queries, the data access service being a service offered by the server to the client to provide access to an on-line analytical processing query performed at the server system through a service call to the data access service, the data access service having a predefined selection of input parameters to define a selection of data from the query and a predefined selection of a single output parameter to define output data to be provided as a result of the selection of the data from the query based on the input parameters, at least one of the data access services being built using a data access service designer, the data access service designer including an object tagger to attach semantic information to a service and its input and output parameters; invoking, by the client, a selected data access service from the list; and presenting, at the client, data within the business warehouse using the selected data access service via a data access service provider wrapping an existing business warehouse object type to expose its data as the data access service. 17. A method as in claim 1 , wherein the data access service designer allows semantic enrichment of parameters of the data access service.
0.591317
1. A method to generate a human-friendly test context in a test proxy for a function under test, the method comprising: generating an initial test context of the function under test; enhancing a current test context with a new context enhancement; adding a hint to the current test context; and performing extended symbolic execution of the function under test using the current test context to identify the new context enhancement, the extended symbolic execution including: determining whether a concrete variable included in a portion of the function under test is a dependent concrete variable based on whether an ability to execute a branch of the function under test depends on the concrete variable; further determining the branch is not executable; in response to determining that the concrete variable is the dependent concrete variable and to determining that the branch of the function under test is not executable, marking the concrete variable as a symbolic variable; determining whether the marked symbolic variable is accessible to the function under test; and in response to determining that the symbolic variable is accessible to the function under test, identifying the symbolic variable as the new context enhancement, wherein the current test context includes or is derived from the initial test context.
1. A method to generate a human-friendly test context in a test proxy for a function under test, the method comprising: generating an initial test context of the function under test; enhancing a current test context with a new context enhancement; adding a hint to the current test context; and performing extended symbolic execution of the function under test using the current test context to identify the new context enhancement, the extended symbolic execution including: determining whether a concrete variable included in a portion of the function under test is a dependent concrete variable based on whether an ability to execute a branch of the function under test depends on the concrete variable; further determining the branch is not executable; in response to determining that the concrete variable is the dependent concrete variable and to determining that the branch of the function under test is not executable, marking the concrete variable as a symbolic variable; determining whether the marked symbolic variable is accessible to the function under test; and in response to determining that the symbolic variable is accessible to the function under test, identifying the symbolic variable as the new context enhancement, wherein the current test context includes or is derived from the initial test context. 8. The method of claim 1 , wherein the hint comprises a suggestion for a user to modify the current test context, the method further comprising: receiving user input effective to enhance the current test context by specification of a user-specified variable in the current test context; identifying the user-specified variable in the current test context; and prioritizing the user-specified variable such that it is not overwritten by subsequent automatic enhancements to the current test context.
0.671705
6. The method of claim 1 , wherein generating query language statements comprises generating SQL statements.
6. The method of claim 1 , wherein generating query language statements comprises generating SQL statements. 12. A computer readable storage medium having computer-executable instructions stored thereon, wherein the computer executable instructions are executable by a computer for performing the steps of claim 6 .
0.901709
10. A system comprising: at least one computing device comprising one or more processors to execute and memory to store instructions to: receive an item recommendation request, the request identifying a user; responsive to a determination made using web page interaction data that the user is a frequent user, use item scoring in a model trained using the web page interaction data for a plurality of users, the item scoring identifying a plurality of scored items and the corresponding scores; responsive to a determination made using the web page interaction data that the user is an infrequent user; identify, using a current item identified from behavior of the user and the trained model, a probability for each cluster identified in the trained model that the user belongs to the cluster; and generate the plurality of scored items, each item of the plurality of scored items having an item score determined using the item's cluster score and the probability that the user belongs to the cluster; select items from the plurality of scored items based on the item scoring; and provide the selected items as item recommendations in response to the request.
10. A system comprising: at least one computing device comprising one or more processors to execute and memory to store instructions to: receive an item recommendation request, the request identifying a user; responsive to a determination made using web page interaction data that the user is a frequent user, use item scoring in a model trained using the web page interaction data for a plurality of users, the item scoring identifying a plurality of scored items and the corresponding scores; responsive to a determination made using the web page interaction data that the user is an infrequent user; identify, using a current item identified from behavior of the user and the trained model, a probability for each cluster identified in the trained model that the user belongs to the cluster; and generate the plurality of scored items, each item of the plurality of scored items having an item score determined using the item's cluster score and the probability that the user belongs to the cluster; select items from the plurality of scored items based on the item scoring; and provide the selected items as item recommendations in response to the request. 12. The system of claim 10 , the instructions further comprising instructions to: generate a short-term cluster membership vector using the current item identified from the behavior of the user and the trained model, the short-term membership vector being used to identify the probability for each cluster identified in the trained model that the user belongs to the cluster.
0.548601
1. A method of determining interaction analytics for user interactions with audio and video content items, the method comprising: retrieving, from a first database, a collection of content identifiers for identifying a plurality of content items based on characteristics of the plurality of content items; retrieving, from a second database, a catalog of the plurality of content items, each content item of the plurality of the content items of the catalog being associated with metacontent describing the respective content item; cross-referencing metacontent associated with a first content item of the plurality of content items of the catalog retrieved from the second database with the collection of the content identifiers retrieved from the first database; associating, based on the cross-referencing, a content identifier with the first content item based on the metacontent associated with the first content item; providing, to a third database, monitored user interactions with the plurality of content items of the catalog and historical records of the user interactions, the historical records including the content identifier associated with the first content item and the user interactions including media navigation associated with the plurality of content items of the catalog at a specified period of time; determining, using the third database, interaction analytics for a second content item of the plurality of content items of the catalog and a set of users having interacted with the second content item based on the monitored user interactions and the historical records; determining whether the set of users will perform a specified interaction with the second content item during a future period of time based on the interaction analytics, wherein the specified interaction is one of a pause operation, a rewind operation, and a fast-forward operation; and identifying an advertisement associated with the second content item of the plurality of content items of the catalog based on the determination whether the set of users will perform the specified interaction.
1. A method of determining interaction analytics for user interactions with audio and video content items, the method comprising: retrieving, from a first database, a collection of content identifiers for identifying a plurality of content items based on characteristics of the plurality of content items; retrieving, from a second database, a catalog of the plurality of content items, each content item of the plurality of the content items of the catalog being associated with metacontent describing the respective content item; cross-referencing metacontent associated with a first content item of the plurality of content items of the catalog retrieved from the second database with the collection of the content identifiers retrieved from the first database; associating, based on the cross-referencing, a content identifier with the first content item based on the metacontent associated with the first content item; providing, to a third database, monitored user interactions with the plurality of content items of the catalog and historical records of the user interactions, the historical records including the content identifier associated with the first content item and the user interactions including media navigation associated with the plurality of content items of the catalog at a specified period of time; determining, using the third database, interaction analytics for a second content item of the plurality of content items of the catalog and a set of users having interacted with the second content item based on the monitored user interactions and the historical records; determining whether the set of users will perform a specified interaction with the second content item during a future period of time based on the interaction analytics, wherein the specified interaction is one of a pause operation, a rewind operation, and a fast-forward operation; and identifying an advertisement associated with the second content item of the plurality of content items of the catalog based on the determination whether the set of users will perform the specified interaction. 16. The method of claim 1 , further comprising monitoring user interactions for a particular population.
0.609331
54. A display apparatus comprising: a display unit which displays a first display item; a text determination unit which determines a first text corresponding to the first display item; a voice recognition unit which recognizes a voice input from a user; and a controller which: couples the first text to the first display item, displays the first display item so as to distinguish the first display item from a second display item, determines if the recognized voice input corresponds to the first text, and selects the first display item in response to a determination that the recognized voice input corresponds to the first text, wherein the voice input comprises a voice of the user speaking at least a word from the first text, and wherein the determining the first text comprises extracting the first text comprising at least one word from the first display item such that the first text does not share common words with a second text coupled to the second display item.
54. A display apparatus comprising: a display unit which displays a first display item; a text determination unit which determines a first text corresponding to the first display item; a voice recognition unit which recognizes a voice input from a user; and a controller which: couples the first text to the first display item, displays the first display item so as to distinguish the first display item from a second display item, determines if the recognized voice input corresponds to the first text, and selects the first display item in response to a determination that the recognized voice input corresponds to the first text, wherein the voice input comprises a voice of the user speaking at least a word from the first text, and wherein the determining the first text comprises extracting the first text comprising at least one word from the first display item such that the first text does not share common words with a second text coupled to the second display item. 59. The display apparatus of claim 54 , wherein the first display item comprises a link, and the selecting the first display item comprises displaying a web page linked to the first display item.
0.574058
13. A method for testing input device attributes, the method comprising: receiving first input on an input surface via an input device; determining if the received first input is associated with a scribble input for determining attributes of the input device based on a location corresponding to a margin of an electronic document of the received first input on the input surface; in response to determining that the received first input is associated with the scribble input, making a determination whether to erase the scribble input, wherein making the determination to erase the scribble input comprises: receiving a second input via the input device; evaluating a location of the second input to the scribble input; determining that the location of the second input to the scribble input is not in the margin of the electronic document; and determining, based on the location of the second input, that the second input is not a continuation of the scribble input; and based on the received first input being associated with the scribble input, erasing the scribble input, but not the second input, after a predetermined amount of time after receiving the scribble input.
13. A method for testing input device attributes, the method comprising: receiving first input on an input surface via an input device; determining if the received first input is associated with a scribble input for determining attributes of the input device based on a location corresponding to a margin of an electronic document of the received first input on the input surface; in response to determining that the received first input is associated with the scribble input, making a determination whether to erase the scribble input, wherein making the determination to erase the scribble input comprises: receiving a second input via the input device; evaluating a location of the second input to the scribble input; determining that the location of the second input to the scribble input is not in the margin of the electronic document; and determining, based on the location of the second input, that the second input is not a continuation of the scribble input; and based on the received first input being associated with the scribble input, erasing the scribble input, but not the second input, after a predetermined amount of time after receiving the scribble input. 18. The method of claim 13 , wherein providing feedback via the input device comprises providing one or more of: a haptic feedback; a visual feedback; or an audible feedback.
0.572397
1. A method implemented by one or more computing devices, the method comprising: checking compatibility of a second collection of dynamically-typed executable machine-readable code with a first collection of statically-typed executable machine-readable code, the checking comprising: parsing the first collection of statically-typed executable machine-readable code to locate descriptions of one or more application programming interfaces (APIs) included in the first collection of statically-typed executable machine-readable code; projecting the descriptions of the one or more application programming interfaces of the first collection of statically-typed executable machine-readable code into an alternate form; and employing the projected descriptions of the first collection of statically-typed executable machine-readable code to check for the compatibility of the second collection of dynamically-typed executable machine-readable code with the first collection of statically-typed executable machine-readable code.
1. A method implemented by one or more computing devices, the method comprising: checking compatibility of a second collection of dynamically-typed executable machine-readable code with a first collection of statically-typed executable machine-readable code, the checking comprising: parsing the first collection of statically-typed executable machine-readable code to locate descriptions of one or more application programming interfaces (APIs) included in the first collection of statically-typed executable machine-readable code; projecting the descriptions of the one or more application programming interfaces of the first collection of statically-typed executable machine-readable code into an alternate form; and employing the projected descriptions of the first collection of statically-typed executable machine-readable code to check for the compatibility of the second collection of dynamically-typed executable machine-readable code with the first collection of statically-typed executable machine-readable code. 6. A method as described in claim 1 , wherein the alternate form is an abstract syntax tree or executable code in compliance with a dynamically-typed language.
0.831661
19. A system comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: analyzing, using a time series engine, a distribution of unstructured time-stamped data to identify a plurality of potential time series data hierarchies for structuring the unstructured time-stamped data, wherein a potential time series data hierarchy is a framework for structuring the data through use of multiple time series, and wherein the time series engine is at a server layer of a time series computing system; performing, using the time series engine, an analysis of the plurality of potential time series data hierarchies, wherein performing the analysis of the plurality of potential time series data hierarchies includes determining an optimal time series frequency and a data sufficiency metric for each of the plurality of potential time series data hierarchies; comparing data sufficiency metrics for the plurality of potential time series data hierarchies; selecting a hierarchy of the plurality of potential time series data hierarchies based on the comparison of the data sufficiency metrics; structuring the unstructured time-stamped data into structured time-stamped data according to the hierarchy and the optimal time series frequency, wherein structuring the transformed time-stamped data into the structured time-stamped data is performed using a single pass of the unstructured time-stamped data through the time series engine; computing a plurality of transformations of the structured time-stamped data using the single pass of the structured time-stamped data through the time series engine; transforming the structured time-stamped data into transformed time-stamped data according to the plurality of transformations; and providing, using an application programming interface, the transformed time-stamped data for visual presentation.
19. A system comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: analyzing, using a time series engine, a distribution of unstructured time-stamped data to identify a plurality of potential time series data hierarchies for structuring the unstructured time-stamped data, wherein a potential time series data hierarchy is a framework for structuring the data through use of multiple time series, and wherein the time series engine is at a server layer of a time series computing system; performing, using the time series engine, an analysis of the plurality of potential time series data hierarchies, wherein performing the analysis of the plurality of potential time series data hierarchies includes determining an optimal time series frequency and a data sufficiency metric for each of the plurality of potential time series data hierarchies; comparing data sufficiency metrics for the plurality of potential time series data hierarchies; selecting a hierarchy of the plurality of potential time series data hierarchies based on the comparison of the data sufficiency metrics; structuring the unstructured time-stamped data into structured time-stamped data according to the hierarchy and the optimal time series frequency, wherein structuring the transformed time-stamped data into the structured time-stamped data is performed using a single pass of the unstructured time-stamped data through the time series engine; computing a plurality of transformations of the structured time-stamped data using the single pass of the structured time-stamped data through the time series engine; transforming the structured time-stamped data into transformed time-stamped data according to the plurality of transformations; and providing, using an application programming interface, the transformed time-stamped data for visual presentation. 30. The system of claim 19 , further comprising instructions, which when executed by the one or more processors, cause the computing device to perform operations including: generating, using the time series engine, an electronic representation of the structured data using the single pass of the time stamped unstructured data.
0.564076
11. A method comprising: identifying a first term in a document structure instance matching a first permissible term in a glossary; identifying an attribute requirement assignable to the first permissible term, the attribute requirement identified by an attribute phrase; analyzing, with a processor, the document structure instance to find a target phrase in the document structure instance that matches the attribute phrase; determining that the document structure instance satisfies the attribute requirement in response to identifying the matching target phrase in said document structure instance; and generating an attribute report identifying whether the attribute requirement for the first permissible term has been satisfied.
11. A method comprising: identifying a first term in a document structure instance matching a first permissible term in a glossary; identifying an attribute requirement assignable to the first permissible term, the attribute requirement identified by an attribute phrase; analyzing, with a processor, the document structure instance to find a target phrase in the document structure instance that matches the attribute phrase; determining that the document structure instance satisfies the attribute requirement in response to identifying the matching target phrase in said document structure instance; and generating an attribute report identifying whether the attribute requirement for the first permissible term has been satisfied. 14. The method of claim 11 , where the attribute report comprises: a row corresponding to the first term; a column corresponding to the attribute requirement; and an intersection cell representing an intersection between the row and the column, the intersection cell identifying whether the document structure instance satisfies the attribute requirement.
0.5
1. A system for supporting targeted sharing and early curation of information, comprising: a content module to identify a personal digital data item selection by a user within a personal information management client and data set that is unique to the user; a recommendation module to recommend from a shared information repository separate from the personal information management client, shared documents that are similar to the digital data item from the personal information management client and dataset, comprising: a criteria module to select recommendation criteria, to compare the personal digital data item from the personal information management client and dataset with a set of shared documents from the separate shared information repository, and to apply the recommendation criteria to the comparison of the personal digital data item and the set of documents; and a satisfaction module to identify one or more of the shared documents from the shared information repository that satisfy the recommendation criteria as the similar shared documents; a display module to display the similar shared documents visually proximate to the personal digital data item in the personal information client; an incorporation module to receive a selection of one of the similar shared documents and to incorporate the personal digital data item into the selected similar shared document in the shared information repository.
1. A system for supporting targeted sharing and early curation of information, comprising: a content module to identify a personal digital data item selection by a user within a personal information management client and data set that is unique to the user; a recommendation module to recommend from a shared information repository separate from the personal information management client, shared documents that are similar to the digital data item from the personal information management client and dataset, comprising: a criteria module to select recommendation criteria, to compare the personal digital data item from the personal information management client and dataset with a set of shared documents from the separate shared information repository, and to apply the recommendation criteria to the comparison of the personal digital data item and the set of documents; and a satisfaction module to identify one or more of the shared documents from the shared information repository that satisfy the recommendation criteria as the similar shared documents; a display module to display the similar shared documents visually proximate to the personal digital data item in the personal information client; an incorporation module to receive a selection of one of the similar shared documents and to incorporate the personal digital data item into the selected similar shared document in the shared information repository. 4. A system according to claim 1 , further comprising: a criteria adjustment module to identify user selections of recommended documents and to adjust the recommendation criteria from the identified user selections, wherein the criteria module further applies the adjusted recommendation criteria to later recommendations of shared documents.
0.531269
9. A system embodied on a computer readable storage medium, that employs distributional analysis on a query log to facilitate improving search engine query results, comprising: a component that obtains a set of queries by mining queries from a query log based on at least one of a distributional algorithm, a substring, a string, or a user identification, wherein the set of queries comprises a saved search query or a null set; a profiling component that generates probability distributional profiles for the set of queries based at least on one of a substring distribution algorithm that represents a distribution characteristic for a substring as a probability distribution over strings from the query log that include the substring or a string sequence distribution algorithm that represents a distribution characteristic for a query as a probability distribution of queries that a user queries subsequent the query, wherein the obtained set of queries is dependent upon the distribution algorithm; and a similarity component that employs the distributional profiles to output query terms with similar profiles by generating a distributional similarity between the distributional profiles.
9. A system embodied on a computer readable storage medium, that employs distributional analysis on a query log to facilitate improving search engine query results, comprising: a component that obtains a set of queries by mining queries from a query log based on at least one of a distributional algorithm, a substring, a string, or a user identification, wherein the set of queries comprises a saved search query or a null set; a profiling component that generates probability distributional profiles for the set of queries based at least on one of a substring distribution algorithm that represents a distribution characteristic for a substring as a probability distribution over strings from the query log that include the substring or a string sequence distribution algorithm that represents a distribution characteristic for a query as a probability distribution of queries that a user queries subsequent the query, wherein the obtained set of queries is dependent upon the distribution algorithm; and a similarity component that employs the distributional profiles to output query terms with similar profiles by generating a distributional similarity between the distributional profiles. 14. The system of claim 9 , the distributional similarity employed to facilitate collaborative filtering.
0.566901
1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal.
1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal. 8. The method for an electronic communications dialog of claim 1 further comprising sending an alert message to at least one user that is not logged on to the web portal.
0.621547
1. An apparatus for converting a sequence of digital words representative of speech in a time division multiplexed format into an acoustic signal, each word having a plurality of magnitude bit locations comprising: a. means for converting the magnitude bits into a plurality of voltages, each of which represents the occurrence of a bit in one of the magnitude bit locations, b. a beam made of a piezoelectric material and having a free and fixed end, c. means for applying each of the plurality of voltages across each of a plurality of elements of the beam to create a deflection of the free end of the beam related to the magnitude of the digital word, the deflection being in a direction substantially perpendicular to the length of the beam, and d. means responsive to the deflection of the free end for generating an acoustic signal related to the sequence of digital words.
1. An apparatus for converting a sequence of digital words representative of speech in a time division multiplexed format into an acoustic signal, each word having a plurality of magnitude bit locations comprising: a. means for converting the magnitude bits into a plurality of voltages, each of which represents the occurrence of a bit in one of the magnitude bit locations, b. a beam made of a piezoelectric material and having a free and fixed end, c. means for applying each of the plurality of voltages across each of a plurality of elements of the beam to create a deflection of the free end of the beam related to the magnitude of the digital word, the deflection being in a direction substantially perpendicular to the length of the beam, and d. means responsive to the deflection of the free end for generating an acoustic signal related to the sequence of digital words. 3. The apparatus according to claim 1, wherein the voltage representative of the most significant bit is applied across the element of the beam closest to the fixed end and the voltage representative of the least significant bit is applied across the element of the beam closest to the free end, the beam elements having substantially equal surface areas.
0.792954
6. An apparatus for optimized generation of facts, the apparatus comprising: at least one processor; and a computer-readable storage medium having computer-executable instructions stored thereon which, when executed on the at least one processor, cause the apparatus to: receive a request for one or more facts regarding an item identified in a product catalog, the request including a product identifier associated with the item identified in the product catalog, determine, based at least in part upon historical request data, a probability that one or more additional facts regarding the item identified in the product catalog will be requested following the request for the one or more facts; determine, based at least in part upon historical cost data, an estimated cost for generating the one or more additional facts, the estimated cost comprising one or more of an estimated time, memory usage, processing capacity, or network bandwidth required to generate the one or more additional facts; speculatively generate the one or more additional facts regarding the item identified in the product catalog based upon the probability that the one or more additional facts regarding the item identified in the product catalog will be requested; and update the historical cost data with an actual cost to generate the one or more additional facts.
6. An apparatus for optimized generation of facts, the apparatus comprising: at least one processor; and a computer-readable storage medium having computer-executable instructions stored thereon which, when executed on the at least one processor, cause the apparatus to: receive a request for one or more facts regarding an item identified in a product catalog, the request including a product identifier associated with the item identified in the product catalog, determine, based at least in part upon historical request data, a probability that one or more additional facts regarding the item identified in the product catalog will be requested following the request for the one or more facts; determine, based at least in part upon historical cost data, an estimated cost for generating the one or more additional facts, the estimated cost comprising one or more of an estimated time, memory usage, processing capacity, or network bandwidth required to generate the one or more additional facts; speculatively generate the one or more additional facts regarding the item identified in the product catalog based upon the probability that the one or more additional facts regarding the item identified in the product catalog will be requested; and update the historical cost data with an actual cost to generate the one or more additional facts. 8. The apparatus of claim 6 , wherein the computer-readable storage medium has further computer-executable instructions stored thereon which, when executed on the at least one processor, cause the apparatus to: store the speculatively generated one or more additional facts regarding the item identified in the product catalog in a fact cache; receive a request for the one or more additional facts regarding the item identified in the product catalog subsequent to the request for the one or more facts regarding the item identified in the product catalog; and respond to the request for the one or more additional facts regarding the item identified in the product catalog with the one or more additional facts regarding the item identified in the product catalog stored in the fact cache.
0.64972
1. An article of manufacture comprising a program storage medium having a non-transitory computer readable code embodied therein, the computer readable code being configured for handling at least a target document, said target document having been transmitted electronically and involving an encoding scheme, the article of manufacture comprising: code for ascertaining, using identification rules, whether a charset employed to encode said target document belongs to an excluded charset group, said excluded charset group having at least two charsets, each charset in said excluded charset group selected based on charset inherent characteristics; code for performing, if said charset employed to encode said target document does not belong to said excluded charset group, further processing of said target document, wherein said code for performing including at least: code for training, using a plurality of text document samples that have been encoded with different encoding schemes and selected for training purposes said different encoding schemes pertaining to charset encoding, to obtain a set of machine learning models, said training including using a SVM (Support Vector Machine) technique to generate said set of machine learning models from feature vectors converted from said plurality of text document samples, said feature vectors are grouped by charsets, wherein said training including generating fundamental units from said plurality of text document samples and extracting a subset of said fundamental units to form a set of feature lists, said feature vectors are converted from said set of feature lists and said plurality of text document samples, said extracting said subset of said fundamental units includes filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences among said different encoding schemes; code for applying said set of machine learning models against a set of target document feature vectors converted from said target document, said applying including analyzing said set of target document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of target document feature vectors; and code for decoding said target document to obtain decoded content of said target document based on at least said first encoding scheme.
1. An article of manufacture comprising a program storage medium having a non-transitory computer readable code embodied therein, the computer readable code being configured for handling at least a target document, said target document having been transmitted electronically and involving an encoding scheme, the article of manufacture comprising: code for ascertaining, using identification rules, whether a charset employed to encode said target document belongs to an excluded charset group, said excluded charset group having at least two charsets, each charset in said excluded charset group selected based on charset inherent characteristics; code for performing, if said charset employed to encode said target document does not belong to said excluded charset group, further processing of said target document, wherein said code for performing including at least: code for training, using a plurality of text document samples that have been encoded with different encoding schemes and selected for training purposes said different encoding schemes pertaining to charset encoding, to obtain a set of machine learning models, said training including using a SVM (Support Vector Machine) technique to generate said set of machine learning models from feature vectors converted from said plurality of text document samples, said feature vectors are grouped by charsets, wherein said training including generating fundamental units from said plurality of text document samples and extracting a subset of said fundamental units to form a set of feature lists, said feature vectors are converted from said set of feature lists and said plurality of text document samples, said extracting said subset of said fundamental units includes filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences among said different encoding schemes; code for applying said set of machine learning models against a set of target document feature vectors converted from said target document, said applying including analyzing said set of target document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of target document feature vectors; and code for decoding said target document to obtain decoded content of said target document based on at least said first encoding scheme. 5. The article of manufacture of claim 1 wherein said target document represents an email message.
0.536179
42. The system of claim 35 , further comprising an intermediate collection platform disposed between the context manager and the centralized storage location.
42. The system of claim 35 , further comprising an intermediate collection platform disposed between the context manager and the centralized storage location. 43. The system of claim 42 , wherein the intermediate collection platform comprises a message queue.
0.933683
1. A method comprising: using one or more computer systems, accessing a modeling language representation of a system under test, the representation comprising one or more Message Sequence Charts (MSCs), one or more of the MSCs comprising one or more conditional constructs including at least one or more guards or one or more loops; using the computer systems, generating one or more use scenarios based on the modeling language representation, wherein generating the one or more use scenarios comprises identifying and generating one or more use scenarios for each combination of two MSCs in the order indicated in a directed graph; and using the computer systems, generating one or more validation test suites based on the one or more use scenarios.
1. A method comprising: using one or more computer systems, accessing a modeling language representation of a system under test, the representation comprising one or more Message Sequence Charts (MSCs), one or more of the MSCs comprising one or more conditional constructs including at least one or more guards or one or more loops; using the computer systems, generating one or more use scenarios based on the modeling language representation, wherein generating the one or more use scenarios comprises identifying and generating one or more use scenarios for each combination of two MSCs in the order indicated in a directed graph; and using the computer systems, generating one or more validation test suites based on the one or more use scenarios. 6. The method of claim 1 , wherein generating one or more use scenarios comprises identifying and generating one or more use scenarios for every MSC in a directed graph.
0.568828
1. A computing device comprising: one or more processors; one or more computer-readable hardware storage memories comprising computer readable instructions which, when executed by the one or more processors, implement: a security module configured to enable secure information transfer between a web content scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine.
1. A computing device comprising: one or more processors; one or more computer-readable hardware storage memories comprising computer readable instructions which, when executed by the one or more processors, implement: a security module configured to enable secure information transfer between a web content scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 5. The system of claim 1 , the security module further comprising: a module configured to enable bypassing security checks based, at least in part, on a determination of the information transfer occurring in a same domain.
0.567941
20. The non-transitory computer-accessible memory medium of claim 1 , wherein the specifications or constraints further comprise: input count (IC), comprising a number of tokens consumed at an input terminal of the at least one functional block by one firing of the at least one functional block; output count (OC), comprising a number of tokens produced at an output terminal of the at least one functional block by one firing of the at least one functional block; and execution time (ET), comprising a number of cycles needed by the at least one functional block to complete firing.
20. The non-transitory computer-accessible memory medium of claim 1 , wherein the specifications or constraints further comprise: input count (IC), comprising a number of tokens consumed at an input terminal of the at least one functional block by one firing of the at least one functional block; output count (OC), comprising a number of tokens produced at an output terminal of the at least one functional block by one firing of the at least one functional block; and execution time (ET), comprising a number of cycles needed by the at least one functional block to complete firing. 24. The non-transitory computer-accessible memory medium of claim 20 , wherein the at least one functional block has multiple possible configurations of IC, OC, ET, II, IP, and OP, and wherein the program instructions are further executable to determine a configuration from the possible configurations based on the specifications or constraints of the at least one functional block, of another functional block, or of the graphical program.
0.825852
9. A method for data federation query suggestions, the method comprising: receiving a query to search a federated database comprising a plurality of non-integrated databases using a federated database search engine with a client identity of the user submitting the query, wherein the lurality of non-integrated databases are selected by a data architect for search using the query and stored to disparate memory storages connected over a network, wherein the data architect sets the at least one query constraint on views of result sets from the query of the plurality of non-integrated databases with query suggestions for non-compliant queries based on the client identity, wherein each of the plurality of non-integrated databases comprise a separate query rule list, and wherein the federated database search engine transforms the query for the each of the plurality of non-integrated databases using the separate query rule list for the each of the plurality of non-integrated databases on receipt of the query; determining, using one or more hardware processor of a query constraint system, if the query satisfies at least one query constraints for querying the plurality of non-integrated databases without submission of the query to the each of the plurality of non-integrated databases; determining a query suggestion if the query does not satisfy at least one query constraints; communicating, to the data architect, search results comprising at least one view for the query from the each of the plurality of non-integrated databases, wherein the at least one view comprises secure data; receiving an update for re-optimization of the at least on query constraints from the data architect, wherein the update limits access to the secure data based on the client identity; and updating the at least one query constraints in the query constraint database based on the update for re-optimization received from the data architect.
9. A method for data federation query suggestions, the method comprising: receiving a query to search a federated database comprising a plurality of non-integrated databases using a federated database search engine with a client identity of the user submitting the query, wherein the lurality of non-integrated databases are selected by a data architect for search using the query and stored to disparate memory storages connected over a network, wherein the data architect sets the at least one query constraint on views of result sets from the query of the plurality of non-integrated databases with query suggestions for non-compliant queries based on the client identity, wherein each of the plurality of non-integrated databases comprise a separate query rule list, and wherein the federated database search engine transforms the query for the each of the plurality of non-integrated databases using the separate query rule list for the each of the plurality of non-integrated databases on receipt of the query; determining, using one or more hardware processor of a query constraint system, if the query satisfies at least one query constraints for querying the plurality of non-integrated databases without submission of the query to the each of the plurality of non-integrated databases; determining a query suggestion if the query does not satisfy at least one query constraints; communicating, to the data architect, search results comprising at least one view for the query from the each of the plurality of non-integrated databases, wherein the at least one view comprises secure data; receiving an update for re-optimization of the at least on query constraints from the data architect, wherein the update limits access to the secure data based on the client identity; and updating the at least one query constraints in the query constraint database based on the update for re-optimization received from the data architect. 10. The method of claim 9 , wherein each of the at least one query constraints include a set of column query patterns having a two component tuple.
0.579629
1. A prosody editing apparatus comprising: a storage configured to store attribute information items of phrases and one or more first prosodic patterns corresponding to each of the attribute information items of the phrases; a search unit configured to search the storage for one or more second prosodic patterns corresponding to an attribute information item that matches an attribute information item of a predetermined phrase, the second prosodic patterns being included in the first prosodic patterns; a mapping unit configured to map each of the second prosodic patterns on a low dimensional space to generate mapping coordinates, the mapping coordinates being used to suppress a first prosodic pattern which is not assumed normally, wherein a first distance between coordinates of the first prosodic pattern and coordinates of a target prosodic pattern is not within a first threshold; a selection unit configured to obtain coordinates selected from the mapping coordinates as selected coordinates; a restoring unit configured to restore a second prosodic pattern according to the selected coordinates to obtain a restored prosodic pattern; and a replacing unit configured to replace prosody of synthetic speech generated based on the predetermined phrase by the restored prosodic pattern.
1. A prosody editing apparatus comprising: a storage configured to store attribute information items of phrases and one or more first prosodic patterns corresponding to each of the attribute information items of the phrases; a search unit configured to search the storage for one or more second prosodic patterns corresponding to an attribute information item that matches an attribute information item of a predetermined phrase, the second prosodic patterns being included in the first prosodic patterns; a mapping unit configured to map each of the second prosodic patterns on a low dimensional space to generate mapping coordinates, the mapping coordinates being used to suppress a first prosodic pattern which is not assumed normally, wherein a first distance between coordinates of the first prosodic pattern and coordinates of a target prosodic pattern is not within a first threshold; a selection unit configured to obtain coordinates selected from the mapping coordinates as selected coordinates; a restoring unit configured to restore a second prosodic pattern according to the selected coordinates to obtain a restored prosodic pattern; and a replacing unit configured to replace prosody of synthetic speech generated based on the predetermined phrase by the restored prosodic pattern. 4. The apparatus of claim 1 , wherein the attribute information items each includes a surface expression which indicates a character string of the phrase, and the search unit searches for whether or not a surface expression of the predetermined phrase matches a surface expression of the phrase.
0.516916
11. The method of claim 10 wherein said step of deactivating comprises the steps of: generating a deactivation signal; finding by said computer system's execution of said finite state machine program routine a fourth table within said present state's set of the tables associated with said deactivation signal; determining a fifth group of program instructions to be executed by said computer system from said fourth table; executing a fourth operation in said process by said computer system's execution of said first program instructions of said fifth group of program instructions; allowing the continuation of processing said deactivation signal by said computer system's execution of a second program instruction of said fifth group of program instructions; and purging said first script of program instructions by said computer system's execution of said finite state machine program routine upon the allowance of said continuation of processing of said deactivation signal.
11. The method of claim 10 wherein said step of deactivating comprises the steps of: generating a deactivation signal; finding by said computer system's execution of said finite state machine program routine a fourth table within said present state's set of the tables associated with said deactivation signal; determining a fifth group of program instructions to be executed by said computer system from said fourth table; executing a fourth operation in said process by said computer system's execution of said first program instructions of said fifth group of program instructions; allowing the continuation of processing said deactivation signal by said computer system's execution of a second program instruction of said fifth group of program instructions; and purging said first script of program instructions by said computer system's execution of said finite state machine program routine upon the allowance of said continuation of processing of said deactivation signal. 12. The method of claim 11 wherein said step of purging comprises the steps of: identifiying each set of said identification tables by said computer system's execution of said finite state machine program routine; checking by said computer system's execution of said finite state machine program routine each table within the identified set of identification tables for the occurrence of a reference to a group of instructions of said first set of program scripts; and removing by said computer system's execution of said finite state machine program routine the reference of the identified group of instructions of said first set of program scripts from each of said identified set of tables.
0.84375
9. The system of claim 8 , wherein determining that the first responsive resource is associated with enrichment information comprises: identifying responsive enrichment information, responsive enrichment information being enrichment information that is responsive to the query; and determining that the first responsive resource is associated with the responsive enrichment information.
9. The system of claim 8 , wherein determining that the first responsive resource is associated with enrichment information comprises: identifying responsive enrichment information, responsive enrichment information being enrichment information that is responsive to the query; and determining that the first responsive resource is associated with the responsive enrichment information. 10. The system of claim 9 , wherein identifying the responsive enrichment information is performed in parallel with identifying the responsive resources.
0.947938
17. A system, comprising: a memory; and one or more processors coupled to the memory, wherein the memory comprises program instructions executable by the one or more processors to implement a gesture module configured to: display a digital image on an electronic device, wherein the electronic device is configured to receive sets of gestural inputs; receive, via the electronic device, a gestural input set, wherein the gestural input set comprises a plurality of gestures, and wherein each given gesture of the received plurality of gestures: corresponds to one of multiple different regions within the digital image; and specifies a respective type of image processing constraint for processing the corresponding one of the multiple different regions within the digital image, wherein the respective type of image processing constraint depends on the gesture type of the given gesture; wherein the plurality of gestures in the received gestural input set include multiple different types of gestures such that the received gestural input set collectively specifies multiple types of image processing constraints; analyze the received gestural input set to determine, for each region of the multiple different regions, the respective type of image processing constraint for processing the region, as specified by the given gesture of the received plurality of gestures that corresponds to the region; and subsequent to receipt of the plurality of gestures including multiple different types of gestures, perform a particular image processing operation on the multiple different regions within the digital image according to each region's respective specified image processing constraint as specified by the type of gesture applied to that region.
17. A system, comprising: a memory; and one or more processors coupled to the memory, wherein the memory comprises program instructions executable by the one or more processors to implement a gesture module configured to: display a digital image on an electronic device, wherein the electronic device is configured to receive sets of gestural inputs; receive, via the electronic device, a gestural input set, wherein the gestural input set comprises a plurality of gestures, and wherein each given gesture of the received plurality of gestures: corresponds to one of multiple different regions within the digital image; and specifies a respective type of image processing constraint for processing the corresponding one of the multiple different regions within the digital image, wherein the respective type of image processing constraint depends on the gesture type of the given gesture; wherein the plurality of gestures in the received gestural input set include multiple different types of gestures such that the received gestural input set collectively specifies multiple types of image processing constraints; analyze the received gestural input set to determine, for each region of the multiple different regions, the respective type of image processing constraint for processing the region, as specified by the given gesture of the received plurality of gestures that corresponds to the region; and subsequent to receipt of the plurality of gestures including multiple different types of gestures, perform a particular image processing operation on the multiple different regions within the digital image according to each region's respective specified image processing constraint as specified by the type of gesture applied to that region. 20. The system of claim 17 , wherein one of the plurality of gestures is a stationary gesture and another one of the plurality of gestures is a mobile gesture, wherein the stationary gesture corresponds to a region of the digital image that is not subject to modification and wherein the mobile gesture corresponds to a region of the digital image that is subject to modification.
0.518182
2. The apparatus according to claim 1 , wherein said calculation means further calculates the confidence score on the basis of a size of the region.
2. The apparatus according to claim 1 , wherein said calculation means further calculates the confidence score on the basis of a size of the region. 3. The apparatus according to claim 2 , wherein said calculation means further calculates the confidence score on the basis of a size of a smallest region among the plurality of regions.
0.944246
3. An apparatus for processing information from a set of archive files, the apparatus comprising a processor, a data bus coupled to the processor, and a memory coupled to the processor through the data bus for storing computer readable code to be processed by the processor for: receiving a request to obtain information derived from a set of archive files; identifying a container with which the set of archive files are associated in response to receiving the request; determining an information operation specified by the request; performing the specified information operation with respect to each archive file in the set of archive files, wherein the specified information operation is selected from the group consisting of searching, indexing, and comparing; and generating a response to the request comprising information derived from the set of archive files and an identifier for an archive file and a constituent file therein which is associated with each information entry in the response to indicate an origin for the information entry.
3. An apparatus for processing information from a set of archive files, the apparatus comprising a processor, a data bus coupled to the processor, and a memory coupled to the processor through the data bus for storing computer readable code to be processed by the processor for: receiving a request to obtain information derived from a set of archive files; identifying a container with which the set of archive files are associated in response to receiving the request; determining an information operation specified by the request; performing the specified information operation with respect to each archive file in the set of archive files, wherein the specified information operation is selected from the group consisting of searching, indexing, and comparing; and generating a response to the request comprising information derived from the set of archive files and an identifier for an archive file and a constituent file therein which is associated with each information entry in the response to indicate an origin for the information entry. 4. The apparatus of claim 3 further comprising computer readable code to be processed by the processor for: determining a list of constituent files in each archive file in the set of archive files; and performing the specified information operation with respect to each constituent file in each archive file in the set of archive files.
0.5
10. A system comprising: one or more computers configured to perform operations comprising: receiving a collection of documents; for each document of the collection of documents: breaking the document into pieces of text, and extracting n+k-grams from each piece of text separately such that each n+k-gram does not overlap; using the extracted n+k-grams for each document as a collection of candidate phrases for a given topic; assigning weights to the candidate phrases; and generating a linear classifier using the weighted candidate phrases, wherein the linear classifier varies the weights for each phrase candidate depending on the length of a document being classified.
10. A system comprising: one or more computers configured to perform operations comprising: receiving a collection of documents; for each document of the collection of documents: breaking the document into pieces of text, and extracting n+k-grams from each piece of text separately such that each n+k-gram does not overlap; using the extracted n+k-grams for each document as a collection of candidate phrases for a given topic; assigning weights to the candidate phrases; and generating a linear classifier using the weighted candidate phrases, wherein the linear classifier varies the weights for each phrase candidate depending on the length of a document being classified. 12. The system of claim 10 , wherein extracting the n+k-grams includes defining a base order n and a list of skip words.
0.697591
9. The process of claim 1 , wherein said navigational entities are displayed on said mobile communication device as underlined link text.
9. The process of claim 1 , wherein said navigational entities are displayed on said mobile communication device as underlined link text. 10. The process of claim 9 , wherein said underlined link text is a selectable client control to allow invocation of said further request.
0.969442
3. The method of claim 1 , wherein each PPAN element comprises attribute name and value pairs associated with the current node.
3. The method of claim 1 , wherein each PPAN element comprises attribute name and value pairs associated with the current node. 5. The method of claim 3 , wherein a current attribute name of at least one of the PPAN elements is a wildcard.
0.952768
11. An apparatus for managing localization workflow for video game development, the apparatus comprising: one or more processors configured to execute computer program modules, the computer program modules comprising: a module configured to analyze a an executable asset of a video game under development to determine whether a string in the executable asset has been added to or modified; a module configured to analyze an executable asset of a video game under development to determine whether the string in the executable asset has been translated; and a module configured to automatically generate, responsive to a determination that the string has been translated, an electronic message for a reviewer, wherein the electronic message notifies the reviewer of a review and approval task associated with at least the translated string; wherein the electronic message is included a metadata that have data types and content types, and limits the length of the translated string such that the program automatically rejects a translation that exceeds the length requirement and display a message indicating the reason for the rejection; when an exact match for the string is found, the corresponding translated phrase is reused into the corresponding dictionary file(s), and the translated phrase is linked into the executable code by the linker.
11. An apparatus for managing localization workflow for video game development, the apparatus comprising: one or more processors configured to execute computer program modules, the computer program modules comprising: a module configured to analyze a an executable asset of a video game under development to determine whether a string in the executable asset has been added to or modified; a module configured to analyze an executable asset of a video game under development to determine whether the string in the executable asset has been translated; and a module configured to automatically generate, responsive to a determination that the string has been translated, an electronic message for a reviewer, wherein the electronic message notifies the reviewer of a review and approval task associated with at least the translated string; wherein the electronic message is included a metadata that have data types and content types, and limits the length of the translated string such that the program automatically rejects a translation that exceeds the length requirement and display a message indicating the reason for the rejection; when an exact match for the string is found, the corresponding translated phrase is reused into the corresponding dictionary file(s), and the translated phrase is linked into the executable code by the linker. 12. The apparatus of claim 11 , wherein the computer program modules further comprise a module configured to store the translated string.
0.547619
1. A system for delivering a page including a plurality of widgets comprising: a processor configured to: receive a query; determine one or more subject type concepts associated with the query by computing an expected cooccurrence between the query and each selected one of the one or more subject type concepts and determining if the expected cooccurrence exceeds, by a threshold amount, an observed cooccurrence between the query and the selected one of the one or more subject type concepts, wherein a subject type concept is a concept included in a concept hierarchy; find candidate widgets that correspond to the one or more associated subject type concepts, wherein at least one candidate widget comprises an atomic unit of content; select a template that is mapped to the one or more associated subject type concepts; select a plurality of widgets based at least in part on the template; rank the plurality of widgets by determining a module to concept affinity score for each of the plurality of widgets; and generate a page to be delivered in response to the received query, wherein generating the page comprises placing the selected plurality of widgets in the generated page according to the template and the module to concept affinity score for each of the plurality of widgets; and a memory coupled to the processor and configured to provide the processor with instructions.
1. A system for delivering a page including a plurality of widgets comprising: a processor configured to: receive a query; determine one or more subject type concepts associated with the query by computing an expected cooccurrence between the query and each selected one of the one or more subject type concepts and determining if the expected cooccurrence exceeds, by a threshold amount, an observed cooccurrence between the query and the selected one of the one or more subject type concepts, wherein a subject type concept is a concept included in a concept hierarchy; find candidate widgets that correspond to the one or more associated subject type concepts, wherein at least one candidate widget comprises an atomic unit of content; select a template that is mapped to the one or more associated subject type concepts; select a plurality of widgets based at least in part on the template; rank the plurality of widgets by determining a module to concept affinity score for each of the plurality of widgets; and generate a page to be delivered in response to the received query, wherein generating the page comprises placing the selected plurality of widgets in the generated page according to the template and the module to concept affinity score for each of the plurality of widgets; and a memory coupled to the processor and configured to provide the processor with instructions. 4. The system of claim 1 wherein at least one widget is selected based at least in part on the location of a user.
0.703608
31. A computer program product with instructions recorded on a non-transitory computer readable storage medium, which, when executed by a processor, carry out a method for building a user profile for a user, the instructions comprising: instructions for labeling and storing, with a computing device, user registration information in a database as a set of demographic nouns; instructions for analyzing, with a computing device, author-generated classification information regarding at least one document of a set of documents and assigning a set of first taxonomic nouns to characterize the user based upon the author-generated classification information; instructions for examining, with a computing device, a user-generated tag from a client computer and characterizing the user of at least one document of the set of documents and assigning a set of second taxonomic nouns to characterize the user based upon the user-generated tag characterization; instructions for identifying, with a computing device, a method by which the user accessed at least one document of the set of documents from a content provider and assigning at set of third taxonomic nouns to characterize the user based upon the method of access; instructions for evaluating, with a computing device, attributes that are related to the method of access and assigning a set of fourth taxonomic nouns to characterize the user based upon the attributes related to the method of access; instructions for processing, with a computing device, at least one document of the set of documents to extract a set of fifth taxonomic nouns to characterize the user; instructions for aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; instructions for building, with a computing device, a user profile based upon the composite set of taxonomic nouns, the author-generated classification information, and at least one of the demographic nouns; instructions for comparing, with a computing device, the composite set of taxonomic nouns with taxonomic nouns associated with a plurality of other user profiles corresponding to a plurality of other users; and instructions for modifying, with a computing device, the user profile based on the comparison.
31. A computer program product with instructions recorded on a non-transitory computer readable storage medium, which, when executed by a processor, carry out a method for building a user profile for a user, the instructions comprising: instructions for labeling and storing, with a computing device, user registration information in a database as a set of demographic nouns; instructions for analyzing, with a computing device, author-generated classification information regarding at least one document of a set of documents and assigning a set of first taxonomic nouns to characterize the user based upon the author-generated classification information; instructions for examining, with a computing device, a user-generated tag from a client computer and characterizing the user of at least one document of the set of documents and assigning a set of second taxonomic nouns to characterize the user based upon the user-generated tag characterization; instructions for identifying, with a computing device, a method by which the user accessed at least one document of the set of documents from a content provider and assigning at set of third taxonomic nouns to characterize the user based upon the method of access; instructions for evaluating, with a computing device, attributes that are related to the method of access and assigning a set of fourth taxonomic nouns to characterize the user based upon the attributes related to the method of access; instructions for processing, with a computing device, at least one document of the set of documents to extract a set of fifth taxonomic nouns to characterize the user; instructions for aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; instructions for building, with a computing device, a user profile based upon the composite set of taxonomic nouns, the author-generated classification information, and at least one of the demographic nouns; instructions for comparing, with a computing device, the composite set of taxonomic nouns with taxonomic nouns associated with a plurality of other user profiles corresponding to a plurality of other users; and instructions for modifying, with a computing device, the user profile based on the comparison. 39. The computer program product for building a user profile of claim 31 , wherein the attributes related to the method of access include at least one of sharing the user's interests, clicking on a newsletter, participating in a discussion, reading or writing a blog, downloading a white paper, purchasing a product or a service, reviewing a product or service, sharing a document, posting to a social network, sending an email, and disclosing information about the user.
0.502724
3. The method in accordance with claim 2 , wherein highlighting further includes receiving a user selection of the highlighted portion to convert said synthesized speech to a SSML representation.
3. The method in accordance with claim 2 , wherein highlighting further includes receiving a user selection of the highlighted portion to convert said synthesized speech to a SSML representation. 6. The method in accordance with claim 3 , further comprising: adding a speaking style as SSML codes to said user supplied text.
0.934492
5. A system for language learning, comprising: a memory that stores text; a computing device that retrieves the text from the memory, and replaces each of at least two portions of the text with a corresponding key word or phrase; a display device that displays the text having the at least two key words or phrases in a graphical user interface to a learner using the computing device, wherein the text includes a plurality of active regions, each active region corresponding to a different one of the at least two key words or phrases, each active region being associated with a corresponding menu of linguistic choices, each key word or phrase representing a type of answer selection in the associating menu, the linguistic choices for each menu comprising at least two correct choices and at least one incorrect choice; an input device that enables a language learner to select a first active region of the active regions by selecting the corresponding key word or phrase of the first active region; an output device that displays a first menu of linguistic choices of the menus in response to the selection of the first active region, the first menu corresponding to the first active regions, displays an error message when a linguistically incorrect choice is selected, the error message comprising an explanation as to why the selection is incorrect; wherein the computing device replaces the key word or phrase associated with the first active region with the selected linguistic choice when a correct linguistic choice is selected; wherein selection of a linguistically correct choice in the first menu of linguistic choices corresponding to the first active region causes linguistic choices in a second menu of linguistic choices corresponding to another of the active regions to change; wherein the input device enables a language learner to select a second active region of the active regions by selecting the corresponding key word or phrase of the second active region; wherein the output device displays a second menu of linguistic choices of the menus in response to the selection of the second active region, the second menu corresponding to the second active region; wherein the computing device determines when a linguistic choice selected from the second menu is linguistically incompatible with the linguistic choice selected from the first menu; wherein each active region corresponds to a choice of content of the text that needs to be made by the language learner; wherein the output device displays another error message when the linguistic choice selected from each of the remaining active regions is linguistically incompatible with the linguistic choice selected from the menu of previously selected menu choices.
5. A system for language learning, comprising: a memory that stores text; a computing device that retrieves the text from the memory, and replaces each of at least two portions of the text with a corresponding key word or phrase; a display device that displays the text having the at least two key words or phrases in a graphical user interface to a learner using the computing device, wherein the text includes a plurality of active regions, each active region corresponding to a different one of the at least two key words or phrases, each active region being associated with a corresponding menu of linguistic choices, each key word or phrase representing a type of answer selection in the associating menu, the linguistic choices for each menu comprising at least two correct choices and at least one incorrect choice; an input device that enables a language learner to select a first active region of the active regions by selecting the corresponding key word or phrase of the first active region; an output device that displays a first menu of linguistic choices of the menus in response to the selection of the first active region, the first menu corresponding to the first active regions, displays an error message when a linguistically incorrect choice is selected, the error message comprising an explanation as to why the selection is incorrect; wherein the computing device replaces the key word or phrase associated with the first active region with the selected linguistic choice when a correct linguistic choice is selected; wherein selection of a linguistically correct choice in the first menu of linguistic choices corresponding to the first active region causes linguistic choices in a second menu of linguistic choices corresponding to another of the active regions to change; wherein the input device enables a language learner to select a second active region of the active regions by selecting the corresponding key word or phrase of the second active region; wherein the output device displays a second menu of linguistic choices of the menus in response to the selection of the second active region, the second menu corresponding to the second active region; wherein the computing device determines when a linguistic choice selected from the second menu is linguistically incompatible with the linguistic choice selected from the first menu; wherein each active region corresponds to a choice of content of the text that needs to be made by the language learner; wherein the output device displays another error message when the linguistic choice selected from each of the remaining active regions is linguistically incompatible with the linguistic choice selected from the menu of previously selected menu choices. 8. The system of claim 5 , wherein the text is a single literary unit.
0.926531
40. The method of claim 1 , further comprising: receiving input from the user selecting one of the n-tuples; and using text from the selected one of the n-tuples to complete input of the text to the system.
40. The method of claim 1 , further comprising: receiving input from the user selecting one of the n-tuples; and using text from the selected one of the n-tuples to complete input of the text to the system. 41. The method of claim 40 , wherein the using comprises replacing the characters typed so far by the user with text from the selected one of the n-tuples.
0.944095
1. A multifunctional document processing system comprising: a host computer including a control module disposed therein; a multifunctional local peripheral device physically separate from but electrically connected to said host computer, said multifunctional local peripheral device including scanning means for optically scanning document information and for converting the scanned document information into first document signals, transmitting means for transmitting the first document signals to the host computer, receiving means for receiving second document signals from the control module, and recording means for producing a recorded form of document information based on the received second document signals; the control module being interfaced between the host computer and the multifunctional local peripheral device, the control module for receiving the first document signals from the multifunctional local peripheral device and third document signals from a remote device and for sending the received first and third document signals to the host computer, the control module also for receiving the second document signals and fourth document signals from the host computer, for sending the received second document signals to the multifunctional local peripheral device and for sending the received fourth document signals to the remote device, the control module functioning to require that the first document signals from the multifunctional local peripheral device and the third document signals from the remote device be transmitted to the host computer, that the second document signals from the host computer be transmitted to the multifunctional local peripheral device, and that the fourth document signals from the host computer be transmitted to the remote device, the control module further functioning to generate and transmit control signals to the multifunctional local peripheral device, storing means for storing the first document signals received from said multifunctional local peripheral device and the third document signals received from said remote device in a memory within said host computer; determining means within the host computer for determining a destination for the stored first and third document signals based on the first and third document signals; and retrieving means for retrieving stored first and third document signals from the memory and transmitting the retrieved first and third document signals as the second document signals to the multifunctional local peripheral device or the fourth document signals to the remote device, according to the determining means.
1. A multifunctional document processing system comprising: a host computer including a control module disposed therein; a multifunctional local peripheral device physically separate from but electrically connected to said host computer, said multifunctional local peripheral device including scanning means for optically scanning document information and for converting the scanned document information into first document signals, transmitting means for transmitting the first document signals to the host computer, receiving means for receiving second document signals from the control module, and recording means for producing a recorded form of document information based on the received second document signals; the control module being interfaced between the host computer and the multifunctional local peripheral device, the control module for receiving the first document signals from the multifunctional local peripheral device and third document signals from a remote device and for sending the received first and third document signals to the host computer, the control module also for receiving the second document signals and fourth document signals from the host computer, for sending the received second document signals to the multifunctional local peripheral device and for sending the received fourth document signals to the remote device, the control module functioning to require that the first document signals from the multifunctional local peripheral device and the third document signals from the remote device be transmitted to the host computer, that the second document signals from the host computer be transmitted to the multifunctional local peripheral device, and that the fourth document signals from the host computer be transmitted to the remote device, the control module further functioning to generate and transmit control signals to the multifunctional local peripheral device, storing means for storing the first document signals received from said multifunctional local peripheral device and the third document signals received from said remote device in a memory within said host computer; determining means within the host computer for determining a destination for the stored first and third document signals based on the first and third document signals; and retrieving means for retrieving stored first and third document signals from the memory and transmitting the retrieved first and third document signals as the second document signals to the multifunctional local peripheral device or the fourth document signals to the remote device, according to the determining means. 2. The system according to claim 1, wherein the recording means is a printer which produces printed documents.
0.508985
1. A search engine comprising: a computer implemented database for storing a plurality of enhanced documents; a computer for retrieving documents from said computer implemented database; a semantic document editor executing on the computer that is operable to allow a user to edit an existing document by creating at least one searchable compound word that contains information contextually relevant to the contents of the document and associate the at least one created compound word with the document to produce an enhanced document having the compounds word associated therewith; a semantic rule engine executing on the computer that is operable to generate and store rules, each of which includes at least one compound word derived from at least one of the enhanced documents; a semantic searching means executing on the computer that uses a selected enhanced document to generate at least one searchable compound word associated with the selected enhanced document; a rule search module executing on the computer for searching the rules to find at least one rule specifying the at least one searchable compound word and at least one additional compound word to generate a set of candidate rules as rules which are possibly relevant to the selected enhanced document; a module executing on the computer for processing the set of candidate rules and adding to the selected enhanced document additional compound words specified in at least one of the rules in the set of candidate rules where the respective rule is satisfied for the selected enhanced document; a semantic query editor executing on the computer operable to enable a searcher to address the database of enhanced documents with a query, said query editor being operable to receive the query and convert it into at least one query searchable compound word that contains contextually relevant information; a search module executing on the computer operable to receive the at least one query searchable compound word and to locate the relevant enhanced documents that have compound words associated with the document matching the at least one query searchable compound word; and an output module executing on the computer for presenting any located documents to the searcher.
1. A search engine comprising: a computer implemented database for storing a plurality of enhanced documents; a computer for retrieving documents from said computer implemented database; a semantic document editor executing on the computer that is operable to allow a user to edit an existing document by creating at least one searchable compound word that contains information contextually relevant to the contents of the document and associate the at least one created compound word with the document to produce an enhanced document having the compounds word associated therewith; a semantic rule engine executing on the computer that is operable to generate and store rules, each of which includes at least one compound word derived from at least one of the enhanced documents; a semantic searching means executing on the computer that uses a selected enhanced document to generate at least one searchable compound word associated with the selected enhanced document; a rule search module executing on the computer for searching the rules to find at least one rule specifying the at least one searchable compound word and at least one additional compound word to generate a set of candidate rules as rules which are possibly relevant to the selected enhanced document; a module executing on the computer for processing the set of candidate rules and adding to the selected enhanced document additional compound words specified in at least one of the rules in the set of candidate rules where the respective rule is satisfied for the selected enhanced document; a semantic query editor executing on the computer operable to enable a searcher to address the database of enhanced documents with a query, said query editor being operable to receive the query and convert it into at least one query searchable compound word that contains contextually relevant information; a search module executing on the computer operable to receive the at least one query searchable compound word and to locate the relevant enhanced documents that have compound words associated with the document matching the at least one query searchable compound word; and an output module executing on the computer for presenting any located documents to the searcher. 8. The search engine according to claim 1 in which the rules stored by the semantic rule engine are stored in a ripple down rule tree.
0.649051
1. A method for installing a language in a mobile communication terminal, the method comprising: determining at least two installable languages from a multi language image file comprising language packages of the at least two languages; selecting and installing one of the at least two installable languages; storing the multi language image file; when changing a language, determining at least two changeable languages from the multi language image file; changing the installed language by selecting one of the at least two changeable languages; and storing language packages associated with the changed language, wherein the multi language image file comprises a header field comprising configuration information of the multi language image file, a bootloader field comprising control information for a hardware initialization process required for driving an Operating System (OS), an OS image field comprising drive information of the OS, and a language package file field comprising a language package for at least one language.
1. A method for installing a language in a mobile communication terminal, the method comprising: determining at least two installable languages from a multi language image file comprising language packages of the at least two languages; selecting and installing one of the at least two installable languages; storing the multi language image file; when changing a language, determining at least two changeable languages from the multi language image file; changing the installed language by selecting one of the at least two changeable languages; and storing language packages associated with the changed language, wherein the multi language image file comprises a header field comprising configuration information of the multi language image file, a bootloader field comprising control information for a hardware initialization process required for driving an Operating System (OS), an OS image field comprising drive information of the OS, and a language package file field comprising a language package for at least one language. 12. The method of claim 1 , further comprising, after at least one of the installing of the language and the changing of the installed language, performing rebooting.
0.6669
71. The memory medium of claim 70, wherein said matching includes determining matches between one or more of said first plurality of objects of said first graphical program with one or more of said second plurality of objects of said second graphical program.
71. The memory medium of claim 70, wherein said matching includes determining matches between one or more of said first plurality of objects of said first graphical program with one or more of said second plurality of objects of said second graphical program. 72. The memory medium of claim 71, wherein said matching comprises determining objects of said first graphical program which have a same type as objects of said second graphical program.
0.937206
1. A method of mapping reference data, comprising: mapping a first reference value from a first set of reference data to a first ontology value in an ontology, wherein the first reference value characterizes one or more data values in a first database; mapping a second reference value from a second set of reference data to a second ontology value in the ontology, wherein the second reference value characterizes one or more data values in a second database; determining a first association between the first ontology value and the second ontology value; and based on the determined first association, and by use of one or more computer processors, determining a second association between the first value from the first set of reference data and the second value from the second set of reference data.
1. A method of mapping reference data, comprising: mapping a first reference value from a first set of reference data to a first ontology value in an ontology, wherein the first reference value characterizes one or more data values in a first database; mapping a second reference value from a second set of reference data to a second ontology value in the ontology, wherein the second reference value characterizes one or more data values in a second database; determining a first association between the first ontology value and the second ontology value; and based on the determined first association, and by use of one or more computer processors, determining a second association between the first value from the first set of reference data and the second value from the second set of reference data. 5. The method of claim 1 , wherein mapping the first reference value from the first set of reference data to the first ontology value in the ontology, further comprises: identifying a first domain of the ontology corresponding to the one or more reference values from the first set of reference data; and mapping the one or more reference values from the first set of reference data to an ontology value in the first domain of the ontology.
0.571881
3. A system, comprising: at least one computing device; and at least one application executable in the at least one computing device, wherein, when executed, the at least one application causes the at least one computing device to at least: obtain a plurality of customer review search queries from a plurality of users, the plurality of customer review search queries being obtained to search a collection of customer reviews for a specific item; extract a set of relevant topics for the specific item by analyzing the plurality of customer review search queries; and generate a user interface based at least in part on at least some of the set of relevant topics for the specific item.
3. A system, comprising: at least one computing device; and at least one application executable in the at least one computing device, wherein, when executed, the at least one application causes the at least one computing device to at least: obtain a plurality of customer review search queries from a plurality of users, the plurality of customer review search queries being obtained to search a collection of customer reviews for a specific item; extract a set of relevant topics for the specific item by analyzing the plurality of customer review search queries; and generate a user interface based at least in part on at least some of the set of relevant topics for the specific item. 20. The system of claim 3 , wherein the user interface is configured to present a group of items that are selected based at least in part on the at least some of the set of relevant topics.
0.87622
1. A method, comprising: receiving, with a text entry device, text input comprising one or more words, wherein at least a portion of the text input is displayed on a touch screen; receiving first touch screen input from the touch screen to select at least one of the words; based on the first touch screen input, selecting at least one of the words and displaying one or more suggestion candidates related to the at least one selected word, at least one of the suggestion candidates including the at least one selected word, the displaying including: displaying the at least one selected word within a shape designating an area of the touch screen as a button, and displaying an add-to-dictionary indicator within the button shape; receiving a second single touch screen input from the touch screen over a selected one of the suggestion candidates that includes the at least one selected word; and based on the receiving the second touch screen input, adding the at least one selected word associated with the selected suggestion candidate to a candidate source.
1. A method, comprising: receiving, with a text entry device, text input comprising one or more words, wherein at least a portion of the text input is displayed on a touch screen; receiving first touch screen input from the touch screen to select at least one of the words; based on the first touch screen input, selecting at least one of the words and displaying one or more suggestion candidates related to the at least one selected word, at least one of the suggestion candidates including the at least one selected word, the displaying including: displaying the at least one selected word within a shape designating an area of the touch screen as a button, and displaying an add-to-dictionary indicator within the button shape; receiving a second single touch screen input from the touch screen over a selected one of the suggestion candidates that includes the at least one selected word; and based on the receiving the second touch screen input, adding the at least one selected word associated with the selected suggestion candidate to a candidate source. 5. The method of claim 1 , wherein the text input is received using a hardware keyboard.
0.802299
6. The method of claim 5 further comprising the step of concealing errors in the information signal.
6. The method of claim 5 further comprising the step of concealing errors in the information signal. 7. The method of claim 6 in which the step of concealing errors includes detecting and correcting the errors in the information words.
0.951051
7. An apparatus, comprising: a first processor; a network adapter; and storage bearing instructions executable by a second processor for: storing a first phrase derived from a sent message for presentation during a subsequent composition of a second message, wherein the first phrase as stored comprises a variable that will be replaced with at least one character for a particular recipient during composition of the second message; during composition of the second message, identifying the first phrase for presentation; and during composition of the second message, presenting, on a display, at least a portion of the first phrase; wherein the first processor transfers the instructions to the second processor over a network via the network adapter.
7. An apparatus, comprising: a first processor; a network adapter; and storage bearing instructions executable by a second processor for: storing a first phrase derived from a sent message for presentation during a subsequent composition of a second message, wherein the first phrase as stored comprises a variable that will be replaced with at least one character for a particular recipient during composition of the second message; during composition of the second message, identifying the first phrase for presentation; and during composition of the second message, presenting, on a display, at least a portion of the first phrase; wherein the first processor transfers the instructions to the second processor over a network via the network adapter. 14. The apparatus of claim 7 , wherein the first phrase is identified during composition of the second message based on a context associated with the second message.
0.598029
17. A computer program product for performing association rule based data mining in an electronic data processing system, comprising: a non-transitory computer readable medium; computer program instructions, recorded on the computer readable medium, executable by a processor, for performing the steps of providing a dataset comprising a plurality of data entries, each data entry comprising information relating to an item or event; counting each occurrence of each item or event in each data entry in the dataset; generating, for each item or event, a compilation of data entries that include each item or event; determining frequent itemsets, each itemset including a plurality of items or events in the dataset; generating a support count for each frequent itemset by determining support counts for a plurality of itemsets in a range of sizes of itemsets in one pass, wherein the support counts of candidates within a particular size range are determined by generating the candidates and arranging them in a lattice; and generating and compressing a vertical representation during the one pass.
17. A computer program product for performing association rule based data mining in an electronic data processing system, comprising: a non-transitory computer readable medium; computer program instructions, recorded on the computer readable medium, executable by a processor, for performing the steps of providing a dataset comprising a plurality of data entries, each data entry comprising information relating to an item or event; counting each occurrence of each item or event in each data entry in the dataset; generating, for each item or event, a compilation of data entries that include each item or event; determining frequent itemsets, each itemset including a plurality of items or events in the dataset; generating a support count for each frequent itemset by determining support counts for a plurality of itemsets in a range of sizes of itemsets in one pass, wherein the support counts of candidates within a particular size range are determined by generating the candidates and arranging them in a lattice; and generating and compressing a vertical representation during the one pass. 18. The computer program product of claim 17 , wherein the step of counting each occurrence of each item or event in each data entry in the dataset comprises the step of: generating a count array comprising a first column including a plurality of identifiers, each identifier identifying an item or event in the dataset, and a second column comprising a plurality of counts, each count indicating a number of occurrences of an item or event identified by a corresponding identifier.
0.5
1. A computer implemented method comprising: receiving, from a user of a social networking system, a content item to be posted on the social networking system by the user; receiving, at the social networking system from the user, a location query for a location associated with the content item to include by the user in the post with the content item, the location queried for being different from a current location of the user, the location query having one or more attributes; accessing a user profile associated with the user in the social networking system, the user profile describing characteristics of the user and other users of the social networking system connected to the user; accessing location data stored by the social networking system, the location data identifying a plurality of locations; comparing the one or more attributes of the location query to one or more attributes of each of the plurality of locations; selecting candidate locations from the plurality of locations, each candidate location having at least one attribute matching an attribute of the location query; ranking the selected candidate locations based on data from the user profile associated with the user; selecting a subset of the selected candidate locations for presentation to the user based on the ranking from which the user can select a location to include in the post with the content item, the subset including different types of locations such that the user is presented with a diversity of locations; and presenting the subset of the selected candidate locations to the user for selection of the location to include in the post with the content item.
1. A computer implemented method comprising: receiving, from a user of a social networking system, a content item to be posted on the social networking system by the user; receiving, at the social networking system from the user, a location query for a location associated with the content item to include by the user in the post with the content item, the location queried for being different from a current location of the user, the location query having one or more attributes; accessing a user profile associated with the user in the social networking system, the user profile describing characteristics of the user and other users of the social networking system connected to the user; accessing location data stored by the social networking system, the location data identifying a plurality of locations; comparing the one or more attributes of the location query to one or more attributes of each of the plurality of locations; selecting candidate locations from the plurality of locations, each candidate location having at least one attribute matching an attribute of the location query; ranking the selected candidate locations based on data from the user profile associated with the user; selecting a subset of the selected candidate locations for presentation to the user based on the ranking from which the user can select a location to include in the post with the content item, the subset including different types of locations such that the user is presented with a diversity of locations; and presenting the subset of the selected candidate locations to the user for selection of the location to include in the post with the content item. 6. The method of claim 1 , wherein selecting candidate locations comprises: determining, from the user profile, a location associated with the user; determining a set of distances from the location associated with the user; associating a group with each in the set of distances from the location associated with the user; determining a distance between each candidate location and the location associated with the user; including a candidate location in a group based on a distance between the candidate location and the location associated with the user; and selecting a plurality of candidate locations, the plurality of candidate locations including locations associated with a plurality of groups.
0.51007
22. A prosody generation apparatus that receives phonological information and linguistic information so as to generate prosody, the prosody generation apparatus being operable to refer to (a) a representative prosodic pattern storage unit for accumulating beforehand representative prosodic patterns of portions of speech data, the portions including prosody changing points; (b) a selection rule storage unit that stores a selection rule predetermined according to attributes concerning phonology or attributes concerning linguistic information of the portions of the speech data including the prosody changing points; and (c) a transformation rule storage unit that stores a transformation rule predetermined according to attributes concerning the phonology or the linguistic information of the portions of the speech data including the prosody changing points; the prosody generation apparatus comprising a computer processing unit and a memory storing a program that are configured to implement: a prosody changing point setting unit that sets a prosody changing point according to at least any one of the received phonological information and the linguistic information; a pattern selection unit that selects a representative prosodic pattern from the representative prosodic pattern storage unit according to the selection rule, based on the received phonological information and the linguistic information; and a prosody generation unit that transforms the representative prosodic pattern selected by the pattern selection unit according to the transformation rule and interpolates the transformed prosodic pattern for a portion between the prosodic patterns corresponding to the prosody changing points, wherein the transformation rule is obtained by clustering prosodic patterns of the speech data into clusters corresponding to the representative patterns so as to produce a representative pattern for each cluster and by formulating a relationship between (i) a distance between each of the prosodic patterns and a representative pattern of a cluster to which the prosodic pattern belongs and (ii) attributes concerning phonology or attributes concerning linguistic information of the prosodic pattern, by means of a statistical technique or a learning technique so as to estimate an amount of transformation of the selected prosodic pattern, using at least one of the attributes concerning phonology and the attributes concerning linguistic information.
22. A prosody generation apparatus that receives phonological information and linguistic information so as to generate prosody, the prosody generation apparatus being operable to refer to (a) a representative prosodic pattern storage unit for accumulating beforehand representative prosodic patterns of portions of speech data, the portions including prosody changing points; (b) a selection rule storage unit that stores a selection rule predetermined according to attributes concerning phonology or attributes concerning linguistic information of the portions of the speech data including the prosody changing points; and (c) a transformation rule storage unit that stores a transformation rule predetermined according to attributes concerning the phonology or the linguistic information of the portions of the speech data including the prosody changing points; the prosody generation apparatus comprising a computer processing unit and a memory storing a program that are configured to implement: a prosody changing point setting unit that sets a prosody changing point according to at least any one of the received phonological information and the linguistic information; a pattern selection unit that selects a representative prosodic pattern from the representative prosodic pattern storage unit according to the selection rule, based on the received phonological information and the linguistic information; and a prosody generation unit that transforms the representative prosodic pattern selected by the pattern selection unit according to the transformation rule and interpolates the transformed prosodic pattern for a portion between the prosodic patterns corresponding to the prosody changing points, wherein the transformation rule is obtained by clustering prosodic patterns of the speech data into clusters corresponding to the representative patterns so as to produce a representative pattern for each cluster and by formulating a relationship between (i) a distance between each of the prosodic patterns and a representative pattern of a cluster to which the prosodic pattern belongs and (ii) attributes concerning phonology or attributes concerning linguistic information of the prosodic pattern, by means of a statistical technique or a learning technique so as to estimate an amount of transformation of the selected prosodic pattern, using at least one of the attributes concerning phonology and the attributes concerning linguistic information. 25. The prosody generation apparatus according to claim 22 , wherein the statistical technique is the Quantification Theory Type I where a compression rate or an extension rate in a dynamic range of a representative prosodic pattern of a cluster is designated as a criterion variable.
0.593084
1. A computer-implemented method for protecting data residing in a repository of an electronic product code information service against undesired data disclosure, the method comprising: defining one or more disclosure policies for an entity representing a set of items sharing a common master data attribute, each item being tagged with an electronic product code and having associated data stored in a relational database in the repository, each disclosure policy including a rule defining what attributes of the entity can be disclosed to a querying party, by creating a security view on one or more relational database objects in the database; and enforcing the one or more disclosure policies in response to receiving a query pertaining to an entity, by: transforming the received query to use the created security view for the one or more relational database objects pertaining to the entity, and returning data defined by the security view to the querying party, thereby only disclosing a subset of the data from the repository, the subset being determined in accordance with the defined one or more disclosure policies.
1. A computer-implemented method for protecting data residing in a repository of an electronic product code information service against undesired data disclosure, the method comprising: defining one or more disclosure policies for an entity representing a set of items sharing a common master data attribute, each item being tagged with an electronic product code and having associated data stored in a relational database in the repository, each disclosure policy including a rule defining what attributes of the entity can be disclosed to a querying party, by creating a security view on one or more relational database objects in the database; and enforcing the one or more disclosure policies in response to receiving a query pertaining to an entity, by: transforming the received query to use the created security view for the one or more relational database objects pertaining to the entity, and returning data defined by the security view to the querying party, thereby only disclosing a subset of the data from the repository, the subset being determined in accordance with the defined one or more disclosure policies. 3. The method of claim 1 , wherein enforcing the one or more disclosure policies includes responding to the received query with less information than specified in the query.
0.897285