sentence1
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4. The keyboard of claim 1 , further comprising at least one vowel key, the vowel key being associated with vowels, wherein the at least one vowel key is positioned in a row other than the rows of the first set of keys. | 4. The keyboard of claim 1 , further comprising at least one vowel key, the vowel key being associated with vowels, wherein the at least one vowel key is positioned in a row other than the rows of the first set of keys. 9. The keyboard of claim 4 , wherein the at least one vowel key comprises a first and a second vowel key, said first and second vowel keys being positioned in a row other than the rows of the first set of keys. | 0.930983 |
5. A processing system for prepending nonce labels to DNS queries, the system comprising: at least one processor; a nonce label analyzer module associated with the at least one processor, the nonce label analyzer module being configured: to evaluate whether a log stored in memory contains at least one past entry of a domain name resolution query to a name server for a full domain name that resulted in a positive reply indicating that the full domain name did exist, to determine whether the log contains at least one recent entry of the domain name resolution query to the name server for the full domain name that resulted in a negative reply indicating that the full domain name did not exist, if it is determined that the log contains the at least one past entry of the domain name resolution query, to determine whether querying the name server with a nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that the log contains the at least one recent entry of the domain name resolution query, to determine whether querying the name server with a nonce label prepended query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that querying the name server with the nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, and to flag the full domain name as inappropriate for nonce label prepending, if it is determined that querying the name server with a nonce label prepended query for the full domain name currently results in the negative reply indicating that the full domain name does not exist. | 5. A processing system for prepending nonce labels to DNS queries, the system comprising: at least one processor; a nonce label analyzer module associated with the at least one processor, the nonce label analyzer module being configured: to evaluate whether a log stored in memory contains at least one past entry of a domain name resolution query to a name server for a full domain name that resulted in a positive reply indicating that the full domain name did exist, to determine whether the log contains at least one recent entry of the domain name resolution query to the name server for the full domain name that resulted in a negative reply indicating that the full domain name did not exist, if it is determined that the log contains the at least one past entry of the domain name resolution query, to determine whether querying the name server with a nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that the log contains the at least one recent entry of the domain name resolution query, to determine whether querying the name server with a nonce label prepended query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that querying the name server with the nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, and to flag the full domain name as inappropriate for nonce label prepending, if it is determined that querying the name server with a nonce label prepended query for the full domain name currently results in the negative reply indicating that the full domain name does not exist. 7. The processing system of claim 5 , wherein the log is a DNS resolver log. | 0.527584 |
1. A communication system including: a first communication device specifically configured for use by a call assistant of a remote captioning service providing captioning assistance for a hearing-impaired user during a real-time communication session; and a second communication device specifically configured for use by the hearing-impaired user to provide captions displayed to the hearing-impaired user during the real-time communication session; wherein the first communication device comprises: a first memory device having a speech recognition program stored therein; a first input device configured to receive inputs from the captioning assistant; a first processor operably coupled with the first memory device and the first input device, the first processor configured to: receive a voice signal during a real-time communication session between at least two parties, the voice signal including at least audio from a far end user for the real-time communication session; generate a text transcription for the audio for the far-end user from the voice signal during the real-time communication session using the speech recognition program; transmit a first block of text of the text transcription to the second communication device for display by the second communication device during the real-time communication session; receive the inputs from the call assistant as edits to the text transcription; and transmit a replacement block of text with the edits to the second communication device after transmission of the first block to the second communication device has already occurred, the replacement block of text being an inline correction for the first block of text that was already received and displayed by the second communication device; and wherein the second communication device comprises: second electronic display; and second processor operably coupled with the second electronic display, the second processor configured to: receive the voice signal and during the real-time communication session; receive the first block of text of the text transcription from the remote captioning service; cause the first block of text of the text transcription to be displayed by the second electronic display as captions for the hearing-impaired user during the real-time communication session; receive the replacement block of text from the remote captioning service after the first block of text has been received and displayed by the second electronic display; and cause the replacement block of text to be displayed by the second electronic as an inline correction for the first block of text previously displayed by the second communication device. | 1. A communication system including: a first communication device specifically configured for use by a call assistant of a remote captioning service providing captioning assistance for a hearing-impaired user during a real-time communication session; and a second communication device specifically configured for use by the hearing-impaired user to provide captions displayed to the hearing-impaired user during the real-time communication session; wherein the first communication device comprises: a first memory device having a speech recognition program stored therein; a first input device configured to receive inputs from the captioning assistant; a first processor operably coupled with the first memory device and the first input device, the first processor configured to: receive a voice signal during a real-time communication session between at least two parties, the voice signal including at least audio from a far end user for the real-time communication session; generate a text transcription for the audio for the far-end user from the voice signal during the real-time communication session using the speech recognition program; transmit a first block of text of the text transcription to the second communication device for display by the second communication device during the real-time communication session; receive the inputs from the call assistant as edits to the text transcription; and transmit a replacement block of text with the edits to the second communication device after transmission of the first block to the second communication device has already occurred, the replacement block of text being an inline correction for the first block of text that was already received and displayed by the second communication device; and wherein the second communication device comprises: second electronic display; and second processor operably coupled with the second electronic display, the second processor configured to: receive the voice signal and during the real-time communication session; receive the first block of text of the text transcription from the remote captioning service; cause the first block of text of the text transcription to be displayed by the second electronic display as captions for the hearing-impaired user during the real-time communication session; receive the replacement block of text from the remote captioning service after the first block of text has been received and displayed by the second electronic display; and cause the replacement block of text to be displayed by the second electronic as an inline correction for the first block of text previously displayed by the second communication device. 3. The communication system of claim 1 , wherein the replacement block of text is selected from the group consisting of at least one word, at least one sentence, and at least one line of text. | 0.554822 |
3. The method according to claim 1 , wherein the items to be clustered comprise a collection of documents. | 3. The method according to claim 1 , wherein the items to be clustered comprise a collection of documents. 4. The method according to claim 3 , wherein the initial set of phrases comprise unigrams. | 0.966111 |
8. The method of claim 3, wherein the match patterns correspond to a plurality of match-set nodes, the match-set nodes being formed into a match-set node graph of connected match-set nodes based on the query, starting with an empty accessibility graph, the generating accessibility graphs step comprising: matching match patterns corresponding to first match-set nodes of the match-set node graph with patterns of edges of each of the separated portions; adding to the accessibility graph a first matched match-set node if corresponding match patterns of the first match-set node is found and adding one first match node for each match connected below the first matched match-set node; matching match patterns corresponding to second match-set nodes that appear below the first matched match-set node in the match-set node graph, if a match is found for any of the second match-set nodes, then adding to the accessibility graph second matched match-set nodes connected below the first matched match-set node and for each match, adding one second match node connected below the second matched match-set node; and generating at least a data edge emanating from each of the match nodes labeled by at least one of a variable of a respective corresponding match pattern and an identification of a part of each of the separated portions identified by the respective corresponding match pattern. | 8. The method of claim 3, wherein the match patterns correspond to a plurality of match-set nodes, the match-set nodes being formed into a match-set node graph of connected match-set nodes based on the query, starting with an empty accessibility graph, the generating accessibility graphs step comprising: matching match patterns corresponding to first match-set nodes of the match-set node graph with patterns of edges of each of the separated portions; adding to the accessibility graph a first matched match-set node if corresponding match patterns of the first match-set node is found and adding one first match node for each match connected below the first matched match-set node; matching match patterns corresponding to second match-set nodes that appear below the first matched match-set node in the match-set node graph, if a match is found for any of the second match-set nodes, then adding to the accessibility graph second matched match-set nodes connected below the first matched match-set node and for each match, adding one second match node connected below the second matched match-set node; and generating at least a data edge emanating from each of the match nodes labeled by at least one of a variable of a respective corresponding match pattern and an identification of a part of each of the separated portions identified by the respective corresponding match pattern. 9. The method of claim 8, further comprising: adding to the accessibility graph local existence nodes corresponding to each of the match-set nodes and match nodes and connecting the local existence nodes in a similar manner as the match-set nodes and the match nodes are connected; setting the values of each of the local existence nodes corresponding to leaf match nodes to ACC; setting values of each of the local existence nodes corresponding to other match nodes to ACC if values of the local existence nodes below each of the local existence nodes are all ACC; and setting values of each of the local existence nodes corresponding to match-set nodes to ACC if any values of local existence nodes below each of the local existence nodes is ACC. | 0.5 |
1. A computer-implemented method for segregating data and code implemented in a dynamic language, wherein the segregated data and code operate in an environment, wherein the environment and the segregated data and code are controlled using a common dynamic language, the method comprising: implementing the environment in the common dynamic language, the environment including a framework, the framework including a plurality of properties; identify in a visible framework property that is visible to applications; identifying an invisible framework property that is not visible to the applications; and implementing a first application in a first sandbox within the environment, wherein the first application is implemented in the common dynamic language, wherein the first application is unable to access the invisible framework property, and wherein the first application is able to access the visible framework property. | 1. A computer-implemented method for segregating data and code implemented in a dynamic language, wherein the segregated data and code operate in an environment, wherein the environment and the segregated data and code are controlled using a common dynamic language, the method comprising: implementing the environment in the common dynamic language, the environment including a framework, the framework including a plurality of properties; identify in a visible framework property that is visible to applications; identifying an invisible framework property that is not visible to the applications; and implementing a first application in a first sandbox within the environment, wherein the first application is implemented in the common dynamic language, wherein the first application is unable to access the invisible framework property, and wherein the first application is able to access the visible framework property. 9. The method of claim 1 , further comprising: implementing a second application in a second sandbox within the environment, the second application being implemented in the common dynamic language, the second application including a second application property; and preventing the first application from accessing the second application Property of the second application operating in the second sandbox. | 0.59444 |
12. A system for generating representations of information, the system comprising: a computer readable storage medium having instructions encoded thereon; and a processor that supports at least reading the instructions, and running a program to perform operations for generating a tree based on the instructions; and wherein the operations comprise at least receiving data of a specified type from a database using a smart tree generated based on a tree specification in response to accessing the tree specification from a database, the smart tree being a virtual tree stored in the computer-readable storage medium that tracks configuration of the tree defined by the tree specification and specifies names associated with nodes of the visual representation of the tree, a hierarchy of the nodes and leaves of the tree, and information used to find the specified type of content in the database, the tree specification defining: a type of content stored in the database to be to be displayed in a visual representation of a tree, and where the type of content can be found in the database; updating, based on accessing a display information tree in response to receiving the data of the specified type from the database using the smart tree, the display information tree stored in the computer-readable storage medium to modify with the data of the specified type information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree, information specifying how one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree in the display information tree, and information specifying how coding for a tree image that generates the visual representation of the tree is created using the information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree and the information specifying how the one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree, the display information tree being a virtual tree that tracks the contents of the tree and provides: the information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree, and the information specifying how the one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree, and the information specifying how coding for a tree image that generates the visual representation of the tree is created using the information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree and the information specifying how the one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree; and update, based on accessing a display language tree in response to updating the display information tree, the display language tree stored in the computer-readable storage medium to modify coding for a tree image that generates the visual representation of the tree defined by the tree specification according to the modified display information tree, the display language tree being a virtual tree that contains the coding for a tree image that generates the visual representation of the tree defined by the tree specification, the tree image supporting at least being pasted into a window of another application and being run from the window; the tree including at least nodes having parent/child relationships that appear when displayed in a tree; the tree supporting at least storing relational information that is independent from the parent/child relationships. | 12. A system for generating representations of information, the system comprising: a computer readable storage medium having instructions encoded thereon; and a processor that supports at least reading the instructions, and running a program to perform operations for generating a tree based on the instructions; and wherein the operations comprise at least receiving data of a specified type from a database using a smart tree generated based on a tree specification in response to accessing the tree specification from a database, the smart tree being a virtual tree stored in the computer-readable storage medium that tracks configuration of the tree defined by the tree specification and specifies names associated with nodes of the visual representation of the tree, a hierarchy of the nodes and leaves of the tree, and information used to find the specified type of content in the database, the tree specification defining: a type of content stored in the database to be to be displayed in a visual representation of a tree, and where the type of content can be found in the database; updating, based on accessing a display information tree in response to receiving the data of the specified type from the database using the smart tree, the display information tree stored in the computer-readable storage medium to modify with the data of the specified type information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree, information specifying how one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree in the display information tree, and information specifying how coding for a tree image that generates the visual representation of the tree is created using the information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree and the information specifying how the one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree, the display information tree being a virtual tree that tracks the contents of the tree and provides: the information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree, and the information specifying how the one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree, and the information specifying how coding for a tree image that generates the visual representation of the tree is created using the information specifying how the type of content defined in the tree specification is arranged in the visual representation of the tree and the information specifying how the one or more interactions that manipulate the type of content defined in the tree specification are arranged in the visual representation of the tree; and update, based on accessing a display language tree in response to updating the display information tree, the display language tree stored in the computer-readable storage medium to modify coding for a tree image that generates the visual representation of the tree defined by the tree specification according to the modified display information tree, the display language tree being a virtual tree that contains the coding for a tree image that generates the visual representation of the tree defined by the tree specification, the tree image supporting at least being pasted into a window of another application and being run from the window; the tree including at least nodes having parent/child relationships that appear when displayed in a tree; the tree supporting at least storing relational information that is independent from the parent/child relationships. 15. The system of claim 12 , wherein the relational information includes at least an association relationship having two or more associatively related nodes. | 0.581016 |
1. A method of generating linear models for an aircraft engine system, the method comprising: determining, offline, a set of linear models for the aircraft engine system by linearization of a nonlinear model of the aircraft engine system at selected operating points or from desired data; analyzing, offline, accuracy of each linear model and eliminating inaccurate linear models therefrom to provide a residual set of the linear engine models; generating, offline, linear models corresponding to grid points of one or more rectangular lookup tables based on the residual set of the linear engine models; associating, offline, lookup table grid points or the residual set of the linear engine models with selected scheduling variables; and generating, offline, algorithmic software for the aircraft engine system therefrom such that the linear models for the aircraft engine system generated offline form a basis for online scheduling of linear models. | 1. A method of generating linear models for an aircraft engine system, the method comprising: determining, offline, a set of linear models for the aircraft engine system by linearization of a nonlinear model of the aircraft engine system at selected operating points or from desired data; analyzing, offline, accuracy of each linear model and eliminating inaccurate linear models therefrom to provide a residual set of the linear engine models; generating, offline, linear models corresponding to grid points of one or more rectangular lookup tables based on the residual set of the linear engine models; associating, offline, lookup table grid points or the residual set of the linear engine models with selected scheduling variables; and generating, offline, algorithmic software for the aircraft engine system therefrom such that the linear models for the aircraft engine system generated offline form a basis for online scheduling of linear models. 25. The method according to claim 1 , wherein the basis for online scheduling of linear models comprises a polytopic method that uses offline grid point linear models to generate online scheduled linear models. | 0.580286 |
2. Apparatus for formatting text with justified margins comprising: first means responsive to said text for storing suffixes whch are characters to be prevented from appearing at the ends of lines of justified text, second means for building a formatted line of characters in accordance with said text, and third means for comparing the last character of said formatted line with the stored characters that are to be prevented from being at the end of a line and for placing that character at the beginning of the next line if it is one of the stored characters. | 2. Apparatus for formatting text with justified margins comprising: first means responsive to said text for storing suffixes whch are characters to be prevented from appearing at the ends of lines of justified text, second means for building a formatted line of characters in accordance with said text, and third means for comparing the last character of said formatted line with the stored characters that are to be prevented from being at the end of a line and for placing that character at the beginning of the next line if it is one of the stored characters. 3. The apparatus as set forth in claim 2, wherein said first means is further responsive to said text for storing characters to be prevented from appearing at the beginning of lines of justified text, and fourth means for comparing the character at the beginning of said next line with the stored characters that are to be prevented from being at the beginning of a line and for replacing a character at the beginning of said next line if it is one of the stored characters with a character from the previous line. | 0.5 |
10. A method comprising: decoding at least one syntax data element related to at least two partitions of at least a portion of a picture, wherein the at least one syntax element is decoded from a plurality of successive decoding loops including a first loop that decodes macroblock and sub-macroblock coding modes as a first data class, the at least one syntax element belonging to a given class of data, and said wherein the decoding of the at least one syntax data element uses already decoded data from surrounding macroblocks for a given class of data prior to decoding a next class of data, wherein later decoded data classes, wherein a later decoding loop decodes a syntax data element of a second data class based on the coding modes, wherein reference picture information is decoded in a decoding loop after the later decoding loop based on the coding modes and the syntax data element of the second data class, and wherein a use of the plurality of successive decoding loops is enabled or disabled using at least one syntax data field in a high level syntax element. | 10. A method comprising: decoding at least one syntax data element related to at least two partitions of at least a portion of a picture, wherein the at least one syntax element is decoded from a plurality of successive decoding loops including a first loop that decodes macroblock and sub-macroblock coding modes as a first data class, the at least one syntax element belonging to a given class of data, and said wherein the decoding of the at least one syntax data element uses already decoded data from surrounding macroblocks for a given class of data prior to decoding a next class of data, wherein later decoded data classes, wherein a later decoding loop decodes a syntax data element of a second data class based on the coding modes, wherein reference picture information is decoded in a decoding loop after the later decoding loop based on the coding modes and the syntax data element of the second data class, and wherein a use of the plurality of successive decoding loops is enabled or disabled using at least one syntax data field in a high level syntax element. 11. The method of claim 10 , wherein the decoder is an extended version of an existing decoder of an existing video coding standard or video coding recommendation. | 0.5 |
13. A system, comprising: hardware logic performing operations, the operations comprising: receiving a search request including one or more search terms; capturing each of the one or more search terms; providing a list of topics to a user as search results; receiving user selection of a topic in the list of topics, wherein the user adds one or more folksonomy tags to the topic after reviewing the topic; capturing the one or more folksonomy tags added by the user to the topic; and mapping each of the one or more search terms and each of the one or more folksonomy tags to the topic; for each of the search terms: counting a first number of times the search term has been used for both searching and adding folksonomy tags to the topic; and based on the first number of times, adding the search term to retrievability aids by adding the search term to metadata for the topic, to an index, to a controlled vocabulary, and to a taxonomy , and wherein the adding is based on a search term threshold; and for each of the one or more folksonomy tags: counting a second number of times the folksonomy tag has been added to the topic; and based on the second number of times, adding the folksonomy tag to retrievability aids by adding the folksonomy tag to the metadata for the topic, to the index, to the controlled vocabulary, and to the taxonomy , and wherein the adding is based on a folksonomy tag threshold. | 13. A system, comprising: hardware logic performing operations, the operations comprising: receiving a search request including one or more search terms; capturing each of the one or more search terms; providing a list of topics to a user as search results; receiving user selection of a topic in the list of topics, wherein the user adds one or more folksonomy tags to the topic after reviewing the topic; capturing the one or more folksonomy tags added by the user to the topic; and mapping each of the one or more search terms and each of the one or more folksonomy tags to the topic; for each of the search terms: counting a first number of times the search term has been used for both searching and adding folksonomy tags to the topic; and based on the first number of times, adding the search term to retrievability aids by adding the search term to metadata for the topic, to an index, to a controlled vocabulary, and to a taxonomy , and wherein the adding is based on a search term threshold; and for each of the one or more folksonomy tags: counting a second number of times the folksonomy tag has been added to the topic; and based on the second number of times, adding the folksonomy tag to retrievability aids by adding the folksonomy tag to the metadata for the topic, to the index, to the controlled vocabulary, and to the taxonomy , and wherein the adding is based on a folksonomy tag threshold. 15. The system of claim 13 , wherein the operations further comprise: determining whether the first number of times meets the search term threshold; and in response to determining that the first number of times meets the search term threshold, adding the search term to the retrievability aids. | 0.614965 |
23. The method of claim 19 , wherein automatically causing the controls area to contain the context block comprises displaying, by the computer, the context block within a context pane, the context pane having a title bar and a controls area, the title bar of the context pane labeling the context pane, the controls area of the context pane including the set of commands. | 23. The method of claim 19 , wherein automatically causing the controls area to contain the context block comprises displaying, by the computer, the context block within a context pane, the context pane having a title bar and a controls area, the title bar of the context pane labeling the context pane, the controls area of the context pane including the set of commands. 31. The method of claim 23 , wherein multiple context panes are stackable in a queue. | 0.964447 |
1. A computer-implemented method comprising: obtaining and storing one or more annotations that annotate one or more attribute declarations of a base object of an object-oriented programming environment, wherein the one or more annotations denote one or more JavaScript Object Notation (JSON) attributes; at runtime of an executable computer program that has been created using the base object: generating a JSON object based upon the base object; retrieving the annotations; creating a JSON header that comprises the annotations in a format compatible with a function library that expects name-value pair declarations; attaching the JSON header to the JSON object; renaming an attribute of the JSON object to an items attribute; wherein at least the generating, creating and renaming are performed by one or more processors. | 1. A computer-implemented method comprising: obtaining and storing one or more annotations that annotate one or more attribute declarations of a base object of an object-oriented programming environment, wherein the one or more annotations denote one or more JavaScript Object Notation (JSON) attributes; at runtime of an executable computer program that has been created using the base object: generating a JSON object based upon the base object; retrieving the annotations; creating a JSON header that comprises the annotations in a format compatible with a function library that expects name-value pair declarations; attaching the JSON header to the JSON object; renaming an attribute of the JSON object to an items attribute; wherein at least the generating, creating and renaming are performed by one or more processors. 5. The method of claim 1 , wherein obtaining the annotations comprises reading a plurality of base objects according to a recursive search order that iteratively reads all fields of a current class, a superclass of the current class when the superclass is present, and one or more non-primitive fields of the current class. | 0.714789 |
1. A multimodal system for receiving inputs via more than one mode from a user and for interpretation and display of text based upon the inputs received via the more than one modes, the system comprising: a) a user input device having a plurality of modes, one mode accepting speech input and the remaining modes accepting entry of non-speech input; b) a memory containing a plurality of acoustic networks, each of the plurality of acoustic networks being associated with at least one mode; and c) a processor to: i) process the speech input and at least one non-speech input accepted by at least one of the remaining modes; ii) dynamically adapting an acoustic network based on the speech input and the at least one non-speech input; iii) perform automatic speech recognition using the dynamically adapted acoustic network; iv) determine an output based on the automatic speech recognition; and v) return the output to aid in a determination of a subsequent user-action. | 1. A multimodal system for receiving inputs via more than one mode from a user and for interpretation and display of text based upon the inputs received via the more than one modes, the system comprising: a) a user input device having a plurality of modes, one mode accepting speech input and the remaining modes accepting entry of non-speech input; b) a memory containing a plurality of acoustic networks, each of the plurality of acoustic networks being associated with at least one mode; and c) a processor to: i) process the speech input and at least one non-speech input accepted by at least one of the remaining modes; ii) dynamically adapting an acoustic network based on the speech input and the at least one non-speech input; iii) perform automatic speech recognition using the dynamically adapted acoustic network; iv) determine an output based on the automatic speech recognition; and v) return the output to aid in a determination of a subsequent user-action. 7. The system of claim 1 wherein the system automatically defaults to a pure text prediction system in the event that the speech input from the user is unusable. | 0.510753 |
15. The computer program product of claim 3 wherein the angle set data structure further comprises data for a plurality of story angles, the story angle data comprising, for each story angle (1) an identifier for that story angle, and (2) data representative of at least one applicability condition for that story angle. | 15. The computer program product of claim 3 wherein the angle set data structure further comprises data for a plurality of story angles, the story angle data comprising, for each story angle (1) an identifier for that story angle, and (2) data representative of at least one applicability condition for that story angle. 28. The computer program product of claim 15 wherein the plurality of instructions are further configured for (1) creating an archive of data, the data being indicative of at least one member of the group consisting of a plurality of previously generated evaluation indicators, a plurality of previously generated story generation requests, a plurality of story angles previously found to be applicable to previously evaluated data, and a plurality of previously generated narrative stories, and (2) adjusting at least one of the applicability conditions in the angle set data structure based on the content of the archive. | 0.717647 |
1. A method for populating one or more search indexes with atoms identified in a plurality of documents, the method comprising: identifying a set of documents to be indexed in a search index; for each document in the set of documents, identifying a plurality of atoms, the plurality of atoms comprising one or more unigrams, one or more n-grams, and one or more n-tuples; based on the identified set of documents and the plurality of atoms, generating a list of atom/document pairs; computing an information metric for each atom/document pair, wherein the information metric represents a pre-computed ranking of the atom used during a search query in relation to the particular document; based on the information metric for each atom/document pair, selecting a subset of the atom/document pairs that are most relevant to the particular document from which the atoms were identified; populating the search index using the subset of the atom/document pairs for the particular document, wherein identifying relevant documents for the search query from the search index is based on a pruning algorithm that computes a preliminary score for each of the documents to select a subset of the set of documents based on the preliminary score, wherein the preliminary score is computed using the information metric pre-computed for each atom/document pair and a simplified scoring function that approximates a final ranking algorithm utilized in identifying the relevant documents. | 1. A method for populating one or more search indexes with atoms identified in a plurality of documents, the method comprising: identifying a set of documents to be indexed in a search index; for each document in the set of documents, identifying a plurality of atoms, the plurality of atoms comprising one or more unigrams, one or more n-grams, and one or more n-tuples; based on the identified set of documents and the plurality of atoms, generating a list of atom/document pairs; computing an information metric for each atom/document pair, wherein the information metric represents a pre-computed ranking of the atom used during a search query in relation to the particular document; based on the information metric for each atom/document pair, selecting a subset of the atom/document pairs that are most relevant to the particular document from which the atoms were identified; populating the search index using the subset of the atom/document pairs for the particular document, wherein identifying relevant documents for the search query from the search index is based on a pruning algorithm that computes a preliminary score for each of the documents to select a subset of the set of documents based on the preliminary score, wherein the preliminary score is computed using the information metric pre-computed for each atom/document pair and a simplified scoring function that approximates a final ranking algorithm utilized in identifying the relevant documents. 6. The method of claim 1 , wherein selecting a subset of the atom/document pairs that are most relevant to the particular document further comprises utilizing the pruning algorithm to prune a quantity of the atom/document pairs to a smaller quantity such that the atom/document pairs that are less relevant than other atom/document pairs are not indexed. | 0.728984 |
10. The computer program product of claim 8 further configured wherein the language model pairs are each built from a corpus of at least one of: i) non-translated documents in the language of the retrieved document; and ii) documents translated to the language of the retrieved document. | 10. The computer program product of claim 8 further configured wherein the language model pairs are each built from a corpus of at least one of: i) non-translated documents in the language of the retrieved document; and ii) documents translated to the language of the retrieved document. 11. The computer program product of claim 10 further configured wherein each pair vector of a given language model pair is associated with statistical probabilities of a likelihood of occurrence of one or more vocabulary entries in at least one of non-translated and translated documents. | 0.86605 |
13. A non-transitory computer-readable storage medium storing one or more instructions which, when executed by one or more processors, causes the one or more processors to perform steps comprising: causing displaying a first user interface at a first computer; receiving at a production manager computer, from the first computer via the first user interface, scene metadata defining a plurality of scenes of a media production; causing displaying a second user interface at a second computer that is different from the first computer; receiving at the production manager computer, via the second user interface, at a time after the scene metadata was received and before closing the media production, item metadata for a particular item appearing in the media production, wherein the item metadata specifies a scene, from among the plurality of scenes, in which the particular item appears; using the production manager computer: based on the scene metadata and the item metadata, creating a record in an item database that associates the particular item with the specified scene; determining one or more time values representing a time period during which the particular item appears in the media production based on the scene metadata; generating data specifying when the particular item and each of a plurality of other items appears in the media production based on the time period, wherein the data includes the one or more time values. | 13. A non-transitory computer-readable storage medium storing one or more instructions which, when executed by one or more processors, causes the one or more processors to perform steps comprising: causing displaying a first user interface at a first computer; receiving at a production manager computer, from the first computer via the first user interface, scene metadata defining a plurality of scenes of a media production; causing displaying a second user interface at a second computer that is different from the first computer; receiving at the production manager computer, via the second user interface, at a time after the scene metadata was received and before closing the media production, item metadata for a particular item appearing in the media production, wherein the item metadata specifies a scene, from among the plurality of scenes, in which the particular item appears; using the production manager computer: based on the scene metadata and the item metadata, creating a record in an item database that associates the particular item with the specified scene; determining one or more time values representing a time period during which the particular item appears in the media production based on the scene metadata; generating data specifying when the particular item and each of a plurality of other items appears in the media production based on the time period, wherein the data includes the one or more time values. 18. The non-transitory computer-readable storage medium of claim 13 , wherein the scene metadata defines each scene in the plurality of scenes by one of more of: start timecode, end timecode, or scene number. | 0.674501 |
63. The method of claim 57 wherein the user selection comprises an activation of a menu. | 63. The method of claim 57 wherein the user selection comprises an activation of a menu. 64. The method of claim 63 , wherein the step of performing the operation further comprises the steps of: initializing the second application program; searching, using the second application program, for the second information associated with the first information; and retrieving the second information. | 0.814403 |
8. A computer program product comprising a computer readable medium having computer readable program code for batch-updating multiple distinct structured query language (SQL) statements in a database, said computer program product including: computer readable program code for identifying a set of one or more data types, wherein the set comprises one or more columns that are each updated, respectively, by one of the multiple distinct SQL statements; computer readable program code for identifying multiple tables, wherein each of the multiple tables is updated, respectively, by one of the multiple distinct SQL statements; computer readable program code for identifying a set of one or more columns used in a WHERE clause of each of the multiple distinct SQL statements; computer readable program code for configuring a UNION ALL view for updating the multiple distinct SQL statements; and computer readable program code for batch-updating the multiple distinct SQL statements, wherein the multiple distinct SQL statements comprise two or more distinct SQL statements, wherein each distinct SQL statement updates a unique table with a unique combination of SET and WHERE clauses and includes a WHERE clause that specifies a record that is unique from each record specified by each WHERE clause in the one or more other distinct SQL statements, wherein batch-updating comprises using the UNION ALL view comprising the set of one or more data types, the set of one or more tables and the set of one or more columns used in a WHERE clause, and wherein each distinct SQL statement is mapped to each set of the UNION ALL view. | 8. A computer program product comprising a computer readable medium having computer readable program code for batch-updating multiple distinct structured query language (SQL) statements in a database, said computer program product including: computer readable program code for identifying a set of one or more data types, wherein the set comprises one or more columns that are each updated, respectively, by one of the multiple distinct SQL statements; computer readable program code for identifying multiple tables, wherein each of the multiple tables is updated, respectively, by one of the multiple distinct SQL statements; computer readable program code for identifying a set of one or more columns used in a WHERE clause of each of the multiple distinct SQL statements; computer readable program code for configuring a UNION ALL view for updating the multiple distinct SQL statements; and computer readable program code for batch-updating the multiple distinct SQL statements, wherein the multiple distinct SQL statements comprise two or more distinct SQL statements, wherein each distinct SQL statement updates a unique table with a unique combination of SET and WHERE clauses and includes a WHERE clause that specifies a record that is unique from each record specified by each WHERE clause in the one or more other distinct SQL statements, wherein batch-updating comprises using the UNION ALL view comprising the set of one or more data types, the set of one or more tables and the set of one or more columns used in a WHERE clause, and wherein each distinct SQL statement is mapped to each set of the UNION ALL view. 12. The computer program product of claim 8 , wherein each of the one or more tables is different. | 0.631478 |
1. A method for ingesting and delivering video comprising: crawling, by a crawler component executed by a processor, one or more predetermined video reference sources and selectively ingesting, by an ingest component executed by a processor, one or more videos and their metadata based on predetermined ingest criteria, the ingested metadata including a title for each video and a description for each video, the title and description being maintained by a third party location from which the video and its metadata are ingested; analyzing, by an analysis component executed by a processor, the ingested videos to identify moments in the video by parsing comments relating to the video, identifying a moment if a comment includes a reference to a time in the video and storing the time and a text of the comment in a record of the moment; recording user activity data related to a user's activity with respect to one or more ingested videos, the user activity data including at least data indicating previous search parameters received from the user; rating, by a rating component executed by a processor, the video according to predetermined rating factors, including at least comparing metadata of the video to previous search parameters received from the user; searching, by a search component executed by a processor, at least the text of moment records and the titles and keywords associated with ingested videos based on search parameters received from the user; selectively delivering videos, by a delivery component executed by a processor, based on the results of the searching step in order of their rating as determined by the results of the rating step; displaying moments together with the delivered videos by displaying text of a particular moment at the time of the particular moment as the video is delivered; storing the search parameters received from the user as a channel; and in response to the receipt of a selection of a channel from a user, searching at least the text of moment records based on search parameters stored in association with the channel. | 1. A method for ingesting and delivering video comprising: crawling, by a crawler component executed by a processor, one or more predetermined video reference sources and selectively ingesting, by an ingest component executed by a processor, one or more videos and their metadata based on predetermined ingest criteria, the ingested metadata including a title for each video and a description for each video, the title and description being maintained by a third party location from which the video and its metadata are ingested; analyzing, by an analysis component executed by a processor, the ingested videos to identify moments in the video by parsing comments relating to the video, identifying a moment if a comment includes a reference to a time in the video and storing the time and a text of the comment in a record of the moment; recording user activity data related to a user's activity with respect to one or more ingested videos, the user activity data including at least data indicating previous search parameters received from the user; rating, by a rating component executed by a processor, the video according to predetermined rating factors, including at least comparing metadata of the video to previous search parameters received from the user; searching, by a search component executed by a processor, at least the text of moment records and the titles and keywords associated with ingested videos based on search parameters received from the user; selectively delivering videos, by a delivery component executed by a processor, based on the results of the searching step in order of their rating as determined by the results of the rating step; displaying moments together with the delivered videos by displaying text of a particular moment at the time of the particular moment as the video is delivered; storing the search parameters received from the user as a channel; and in response to the receipt of a selection of a channel from a user, searching at least the text of moment records based on search parameters stored in association with the channel. 3. The method of claim 1 , wherein the predetermined rating factors include at least the total number of comments for the video. | 0.522073 |
1. A computer-implemented method of processing documents, comprising: receiving a document in a search engine crawler, the document having a first link tag embedded in the document, the first link tag including a location value and one or more information pairs that are distinct from the location value, wherein a respective information pair has a respective parameter and a corresponding parameter value; selecting a method of processing content, wherein the content is specified by the location value of the first link tag and the selected method of processing is in accordance with one or more of the one or more information pairs of the first link tag; retrieving the content specified by the location value of the first link tag; and processing the retrieved content specified by the first link tag in accordance with the selected method to add information to one or more databases used by a search engine. | 1. A computer-implemented method of processing documents, comprising: receiving a document in a search engine crawler, the document having a first link tag embedded in the document, the first link tag including a location value and one or more information pairs that are distinct from the location value, wherein a respective information pair has a respective parameter and a corresponding parameter value; selecting a method of processing content, wherein the content is specified by the location value of the first link tag and the selected method of processing is in accordance with one or more of the one or more information pairs of the first link tag; retrieving the content specified by the location value of the first link tag; and processing the retrieved content specified by the first link tag in accordance with the selected method to add information to one or more databases used by a search engine. 10. The method of claim 1 , wherein the first link tag is XML compatible. | 0.700347 |
2. A computer-based method according to claim 1 wherein determining a similarity between the n-gram representations comprises: computing a two-dimensional vector containing a frequency of occurrence of all unique n-grams in the candidate character string and a frequency of occurrence of all unique n-grams in the reference character string; and computing a similarity metric for the candidate character string, with respect to the reference character string, based on the two-dimensional vector. | 2. A computer-based method according to claim 1 wherein determining a similarity between the n-gram representations comprises: computing a two-dimensional vector containing a frequency of occurrence of all unique n-grams in the candidate character string and a frequency of occurrence of all unique n-grams in the reference character string; and computing a similarity metric for the candidate character string, with respect to the reference character string, based on the two-dimensional vector. 3. A computer-based method according to claim 2 wherein computing a similarity metric for the candidate character string comprises using a structured query language calculation to compare contents of the two-dimensional vector. | 0.868318 |
27. The system of claim 17 , further comprising: storing the one or more referring search terms used to locate the web site from the referring web page; using a search term validation program configured to group a plurality of session logs according to the one or more referring search terms; and processing the plurality of session logs to calculate probability information relating to the one or more referring search terms and the one or more web pages within each session log. | 27. The system of claim 17 , further comprising: storing the one or more referring search terms used to locate the web site from the referring web page; using a search term validation program configured to group a plurality of session logs according to the one or more referring search terms; and processing the plurality of session logs to calculate probability information relating to the one or more referring search terms and the one or more web pages within each session log. 30. The system of claim 27 , wherein the search term validation program calculates statistics for a candidate search term based upon the paths taken by the candidate search term to the web site. | 0.861922 |
1. A computer implemented method for improving access to search results, the method comprising: prerendering, using a processor, a search engine page in a hidden browser instance, such that at least some portion of content of the search engine page other than search results responsive to a search query is rendered; receiving the search query via a text entry field; passing the search query to the search engine page to perform a search using the search query; and merging the prerendered content of the search engine page with display content loaded in an active browser instance to facilitate display of one or more search results responsive to the search query as the one or more search results are received via the search engine. | 1. A computer implemented method for improving access to search results, the method comprising: prerendering, using a processor, a search engine page in a hidden browser instance, such that at least some portion of content of the search engine page other than search results responsive to a search query is rendered; receiving the search query via a text entry field; passing the search query to the search engine page to perform a search using the search query; and merging the prerendered content of the search engine page with display content loaded in an active browser instance to facilitate display of one or more search results responsive to the search query as the one or more search results are received via the search engine. 3. The method of claim 1 , wherein the text entry field determines whether the text entry is a search query or a website address. | 0.677966 |
1. A method for translating natural languages using a statistical translation system, the method comprising: parsing a first string in a first language into a parse tree using a statistical parser included in the statistical machine translation system, the parse tree including a plurality of nodes, one or more of said nodes including one or more leafs, each leaf including a first word in the first language, the nodes including child nodes having labels; determining a plurality of possible reorderings of one or more of said child nodes including one or more of the leafs using the statistical translation system, the reordering performed in response to a probability corresponding to a sequence of the child node labels; determining a probability between 0.0000% and 100.0000%, non-inclusive, of the possible reorderings by the statistical translation system; determining a plurality of possible insertions of one or more words at one or more of said nodes using the statistical translation system; determining a probability between 0.0000% and 100.0000%, non-inclusive, of the possible insertions of one or more words at one or more of said nodes by the statistical translation system; translating the first word at each leaf into a second word corresponding to a possible translation in a second language using the statistical translation system; and determining a total probability between 0.0000% and 100.0000%, non-inclusive, based on the reordering, the inserting, and the translating by the statistical translation system. | 1. A method for translating natural languages using a statistical translation system, the method comprising: parsing a first string in a first language into a parse tree using a statistical parser included in the statistical machine translation system, the parse tree including a plurality of nodes, one or more of said nodes including one or more leafs, each leaf including a first word in the first language, the nodes including child nodes having labels; determining a plurality of possible reorderings of one or more of said child nodes including one or more of the leafs using the statistical translation system, the reordering performed in response to a probability corresponding to a sequence of the child node labels; determining a probability between 0.0000% and 100.0000%, non-inclusive, of the possible reorderings by the statistical translation system; determining a plurality of possible insertions of one or more words at one or more of said nodes using the statistical translation system; determining a probability between 0.0000% and 100.0000%, non-inclusive, of the possible insertions of one or more words at one or more of said nodes by the statistical translation system; translating the first word at each leaf into a second word corresponding to a possible translation in a second language using the statistical translation system; and determining a total probability between 0.0000% and 100.0000%, non-inclusive, based on the reordering, the inserting, and the translating by the statistical translation system. 6. The method of claim 1 , wherein the parse tree includes one or more parent nodes and a plurality of child nodes associated with the one or more parent nodes, the parent nodes having parent node labels and the child nodes having child node labels. | 0.509395 |
3. The method of claim 2 , further comprising: for each of the selected plurality of tokens, holding a pointer pointing to the respective token of the selected plurality of tokens, wherein the scanner is configured to hold the pointer; and receiving each token into the scanner from the reader based on processing the pointer to that token. | 3. The method of claim 2 , further comprising: for each of the selected plurality of tokens, holding a pointer pointing to the respective token of the selected plurality of tokens, wherein the scanner is configured to hold the pointer; and receiving each token into the scanner from the reader based on processing the pointer to that token. 7. The method of claim 3 , further comprising: receiving a token into the scanner from the reader including the scanner being configured to receive the token in the scanner from the reader and the scanner being configured to receive the token into the scanner buffer; and the scanner is configured to receive a token into the scanner from the reader buffer based on an indication of a need by the application for a string object, based on the token. | 0.833582 |
10. A system for identifying characters in a handwritten input on an input device, the system comprising: at least one processor; at least one data storage device coupled to the at least one processor; at least one input device, coupled to the at least one processor, to receive a single-character manually input by a user; means for establishing an anchor point on the touch-sensitive device; means for establishing distances from the anchor point to one or more reference support lines; means for receiving a handwritten user input via the touch-sensitive device; means for identifying a set of candidate characters based on the handwritten user input; means for estimating support lines for each of the candidate characters; means for associating temporary reference support lines for each candidate character based on: an angle of the estimated support lines for the candidate character and the established anchor point, and the established distances from the anchor point to the one or more reference support lines; means, for each candidate character, for measuring a deviation between the estimated support lines and temporary reference support lines to determine a scale and position deviation from an expectation for each candidate character, and for combining the measured deviation with candidate expectation deviation measurements for properties other than scale and position; means for ranking each candidate character based on a total deviation measurement for each candidate character; and, means for identifying a best-ranked candidate based at least in part on a smallest total deviation measurement. | 10. A system for identifying characters in a handwritten input on an input device, the system comprising: at least one processor; at least one data storage device coupled to the at least one processor; at least one input device, coupled to the at least one processor, to receive a single-character manually input by a user; means for establishing an anchor point on the touch-sensitive device; means for establishing distances from the anchor point to one or more reference support lines; means for receiving a handwritten user input via the touch-sensitive device; means for identifying a set of candidate characters based on the handwritten user input; means for estimating support lines for each of the candidate characters; means for associating temporary reference support lines for each candidate character based on: an angle of the estimated support lines for the candidate character and the established anchor point, and the established distances from the anchor point to the one or more reference support lines; means, for each candidate character, for measuring a deviation between the estimated support lines and temporary reference support lines to determine a scale and position deviation from an expectation for each candidate character, and for combining the measured deviation with candidate expectation deviation measurements for properties other than scale and position; means for ranking each candidate character based on a total deviation measurement for each candidate character; and, means for identifying a best-ranked candidate based at least in part on a smallest total deviation measurement. 12. The system of claim 10 , further comprising means for establishing new reference support lines based on the temporary reference support lines associated with the best-ranked candidate character, and wherein the total deviation measurement for each candidate character is further based at least in part on a deviation between an estimated candidate writing angle and an angle of an orthogonal projection point of a mass center of the curve to the baseline of the estimated support lines around the anchor point. | 0.630354 |
1. A system for predicting data, comprising: a processor configured to: obtain a name or title from a taste profile; index into a data set based on the name or the title, and retrieve a set of descriptive terms and corresponding term weights associated with the name or the title; construct a sparse vector based on the set of descriptive terms and term weights; identify a target brand or segment of interest; generate a first list of accounts who follow the brand or segment of interest by examining social media data, and a second list of additional entities followed by accounts in the first list; filter the second list through a space mapping that maps entities to names or titles from taste profiles, to generate a subset of test data having a correspondence to the target brand or segment of interest; input the sparse vector to a training model including target data, wherein the target data includes the subset of test data having a correspondence to the target brand or segment of interest and the training model is based on a machine learning from ground truths from a selection of the target data, and output a respective binary value and confidence level for each descriptive term above a threshold, corresponding to an association between the descriptive term and the target brand or segment of interest. | 1. A system for predicting data, comprising: a processor configured to: obtain a name or title from a taste profile; index into a data set based on the name or the title, and retrieve a set of descriptive terms and corresponding term weights associated with the name or the title; construct a sparse vector based on the set of descriptive terms and term weights; identify a target brand or segment of interest; generate a first list of accounts who follow the brand or segment of interest by examining social media data, and a second list of additional entities followed by accounts in the first list; filter the second list through a space mapping that maps entities to names or titles from taste profiles, to generate a subset of test data having a correspondence to the target brand or segment of interest; input the sparse vector to a training model including target data, wherein the target data includes the subset of test data having a correspondence to the target brand or segment of interest and the training model is based on a machine learning from ground truths from a selection of the target data, and output a respective binary value and confidence level for each descriptive term above a threshold, corresponding to an association between the descriptive term and the target brand or segment of interest. 2. The system according to claim 1 , wherein the first list of accounts is generated by selecting accounts who follow the target brand or segment of interest in a random sampling fashion. | 0.580171 |
4. The object recognition system of claim 1 , wherein the step of applying the set of rules to the set of responses to determine an output comprises the steps of: determining if a set of responses matches at least one rule, wherein a set of responses matches a rule if each response token identifier and associated response probability of recognition of the set of responses are all found among the predicates of the rule and the rule probabilities of recognition overlap the response probabilities of recognition for each of the response token identifiers; if a set of responses matches at least one rule, then determining the most-specific matched rule; and applying the most-specific matched rule to determine an output. | 4. The object recognition system of claim 1 , wherein the step of applying the set of rules to the set of responses to determine an output comprises the steps of: determining if a set of responses matches at least one rule, wherein a set of responses matches a rule if each response token identifier and associated response probability of recognition of the set of responses are all found among the predicates of the rule and the rule probabilities of recognition overlap the response probabilities of recognition for each of the response token identifiers; if a set of responses matches at least one rule, then determining the most-specific matched rule; and applying the most-specific matched rule to determine an output. 5. The object recognition system of claim 4 , wherein if a set of responses does not match at least one rule, the method further comprises the step of determining if all of the response token identifiers of the set of responses are all found among the predicates of the rule. | 0.817642 |
2. The method of claim 1 , wherein said generating a code behavior model comprises: initiating a static code analysis upon a current subject feature-related code scope method to generate a control flow graph (CFG) information for that method; and integrating said CFG information generated for each method and a signature information of a method's callees in said code behavior model, said generated control flow information resulting in an increased fine-grained code behavior model. | 2. The method of claim 1 , wherein said generating a code behavior model comprises: initiating a static code analysis upon a current subject feature-related code scope method to generate a control flow graph (CFG) information for that method; and integrating said CFG information generated for each method and a signature information of a method's callees in said code behavior model, said generated control flow information resulting in an increased fine-grained code behavior model. 3. The method of claim 2 , wherein said generating a feature behavior model comprises extracting an internal behavior of the specified feature based on one of: Natural Language Processing techniques or writing rules of the feature specification. | 0.877339 |
2. The voice recognition device of claim 1 , wherein the domain determiner is further configured to determine the current domain to provide response information regarding the voice utterance based on a main action and parameters corresponding to the first and the second utterance elements extracted by the extractor. | 2. The voice recognition device of claim 1 , wherein the domain determiner is further configured to determine the current domain to provide response information regarding the voice utterance based on a main action and parameters corresponding to the first and the second utterance elements extracted by the extractor. 3. The voice recognition device of claim 2 , wherein the controller is further configured to determine whether or not the current domain and the previous domain are the same and whether the conversation context is converted from the current conversation frame and the previous conversation frame generated regarding the previous domain, and determine a candidate conversation frame to provide response information regarding the voice utterance on at least one of the current domain and the previous domain. | 0.862414 |
12. A method comprising: presenting a plurality of prompts requesting information items associated with data describing characteristics of a user of a social networking system; logging, in a database, a plurality of responses from the user to the plurality of prompts; maintaining a profile for the user, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; obtaining a plurality of prompts associated with one or more information items from the set of unknown information items; determining, for each of the plurality of prompts associated with the one or more information items from the set of unknown information items, a response probability based at least in part on one or a combination of prompts previously presented to the user and the logged plurality of responses from the user, the response probability indicating a likelihood of receiving a response to a prompt when presented; determining a data acquisition value for each of a plurality of the unknown information items in the set of unknown information items, the data acquisition value of an unknown information item based at least in part on a value to the social networking system of associating data with the unknown information item and the determined response probability; selecting an unknown information item from the set of unknown information items based at least in part on the data acquisition values; and selecting a prompt associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more prompts associated with the selected unknown information item. | 12. A method comprising: presenting a plurality of prompts requesting information items associated with data describing characteristics of a user of a social networking system; logging, in a database, a plurality of responses from the user to the plurality of prompts; maintaining a profile for the user, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; obtaining a plurality of prompts associated with one or more information items from the set of unknown information items; determining, for each of the plurality of prompts associated with the one or more information items from the set of unknown information items, a response probability based at least in part on one or a combination of prompts previously presented to the user and the logged plurality of responses from the user, the response probability indicating a likelihood of receiving a response to a prompt when presented; determining a data acquisition value for each of a plurality of the unknown information items in the set of unknown information items, the data acquisition value of an unknown information item based at least in part on a value to the social networking system of associating data with the unknown information item and the determined response probability; selecting an unknown information item from the set of unknown information items based at least in part on the data acquisition values; and selecting a prompt associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more prompts associated with the selected unknown information item. 18. The method of claim 12 , wherein the value to the social networking system of associating data with the unknown information item is based at least in part on user engagement with the social networking system based on content selected using the data associated with the unknown information item. | 0.832587 |
16. The mobile device of claim 14 wherein the conversational narrative comprises at least one implied navigation oriented conversational element wherein the at least one implied navigation oriented conversational element is one of omitted, ambiguous, inaccurate, incomplete, grammatically miss-specified, irrelevant, incorrect, contradictory, misleading or a combination thereof. | 16. The mobile device of claim 14 wherein the conversational narrative comprises at least one implied navigation oriented conversational element wherein the at least one implied navigation oriented conversational element is one of omitted, ambiguous, inaccurate, incomplete, grammatically miss-specified, irrelevant, incorrect, contradictory, misleading or a combination thereof. 17. The mobile device of claim 16 wherein the navigation processor is further operative to derive an associated navigation data element associated with the at least one implied navigation oriented element based on a contextual profile of the provider of the conversational narrative, a contextual profile of the receiver of the conversional narrative, or a combination thereof. | 0.884958 |
19. A non-transitory computer readable medium having stored thereon computer executable instructions that, when executed by a processor, cause a computer system to perform computer application code automation, by performing the steps of: displaying a first electronic user interface screen presented by a code automation computer server for accepting user input for generating a Structured Query Language (SQL) query, the user input comprising a plurality of SQL tokens; receiving, via an electronic user interface presented by the code automation computer server, a first partial portion of the user input for generating the SQL query; executing, via a processor associated with the code automation computer server, computer executable instructions for: performing a check to identify a possible error or a query performance problem based on the first partial portion of the user input, displaying a warning screen when the first partial portion of the user input is associated with a possible error or a query performance problem, and displaying a second electronic user interface screen for accepting a second partial portion of the user input comprising the plurality of SQL tokens, wherein the second electronic user interface screen is displayed after displaying the warning screen; and automatically incorporating the generated SQL query into the computer application code. | 19. A non-transitory computer readable medium having stored thereon computer executable instructions that, when executed by a processor, cause a computer system to perform computer application code automation, by performing the steps of: displaying a first electronic user interface screen presented by a code automation computer server for accepting user input for generating a Structured Query Language (SQL) query, the user input comprising a plurality of SQL tokens; receiving, via an electronic user interface presented by the code automation computer server, a first partial portion of the user input for generating the SQL query; executing, via a processor associated with the code automation computer server, computer executable instructions for: performing a check to identify a possible error or a query performance problem based on the first partial portion of the user input, displaying a warning screen when the first partial portion of the user input is associated with a possible error or a query performance problem, and displaying a second electronic user interface screen for accepting a second partial portion of the user input comprising the plurality of SQL tokens, wherein the second electronic user interface screen is displayed after displaying the warning screen; and automatically incorporating the generated SQL query into the computer application code. 24. The non-transitory computer readable medium of claim 19 wherein the instructions further comprise accepting user input for modifying an input parameter value corresponding to at least one SQL token supplied by the user. | 0.617647 |
8. A speech processing system customizing speech parameters across a networked environment, comprising: at least one of a first speech recognizer and a first speaker recognizer residing on a first computing device, the at least one first speech recognizer and first speaker recognizer capturing customized speech parameters for a given speaker and communicate the customized speech parameters across a network; and an intermediary speech processor residing on a second computing device, the second computing device being interconnected by the network to the first computing device; said intermediary speech processor receiving customized speech parameters, said intermediary speech processor retrieving one or more device parameters for a third computing device from a device parameter data store and transform the customized speech parameters for use on the third computing device based on the one or more device parameters for the third computing device, the device parameters selected from either available memory space on the third computing device or the available processing resources of the third computing device. | 8. A speech processing system customizing speech parameters across a networked environment, comprising: at least one of a first speech recognizer and a first speaker recognizer residing on a first computing device, the at least one first speech recognizer and first speaker recognizer capturing customized speech parameters for a given speaker and communicate the customized speech parameters across a network; and an intermediary speech processor residing on a second computing device, the second computing device being interconnected by the network to the first computing device; said intermediary speech processor receiving customized speech parameters, said intermediary speech processor retrieving one or more device parameters for a third computing device from a device parameter data store and transform the customized speech parameters for use on the third computing device based on the one or more device parameters for the third computing device, the device parameters selected from either available memory space on the third computing device or the available processing resources of the third computing device. 10. The speech processing system of claim 8 further comprises at least one of a second speech recognizer and a second speaker recognizer residing on the third computing device, the intermediary speech processor transmitting the transformed customized speech parameters to the at least one second speech recognizer and second speaker recognizer residing on the third computing device. | 0.600062 |
3. The method of claim 1 , further comprising: receiving a second communication of the unique information from a second input device in association with a machine read of the unique information by the second input device during a second presentation of the document for use; verifying the second communicated unique information by determining that the unique information is valid; checking the database to determine that the second communicated unique information has been previously read in association with a previous presentation for use; and in response to determining that the second communicated unique information has been previously read, providing a second signal at the location of the second input device at the time the document is second presented. | 3. The method of claim 1 , further comprising: receiving a second communication of the unique information from a second input device in association with a machine read of the unique information by the second input device during a second presentation of the document for use; verifying the second communicated unique information by determining that the unique information is valid; checking the database to determine that the second communicated unique information has been previously read in association with a previous presentation for use; and in response to determining that the second communicated unique information has been previously read, providing a second signal at the location of the second input device at the time the document is second presented. 17. The method of claim 3 , wherein the second input device is the first input device. | 0.819034 |
13. A system comprising: a display; a user interface, including a control device and a microphone; and processor electronics configured to perform operations comprising: displaying a text script on a display; receiving input from the control device positioning a plurality of visual images associated with a plurality of media events adjacent to the text script in a scrollable portion of the display to establish a spatial relationship between the plurality of visual images and the text script, such that the position of each visual image corresponds to one or more words in the text script with which the associated media event is to begin during a presentation; scrolling the text script on the display while maintaining the spatial relationship between the text script and the visual images; causing the media events associated with the visual images to begin approximately upon the corresponding one or more words of the text script scrolling through a predetermined region of the display during the presentation; and generating the presentation, including audio information corresponding to the user speaking at least a portion of the text script. | 13. A system comprising: a display; a user interface, including a control device and a microphone; and processor electronics configured to perform operations comprising: displaying a text script on a display; receiving input from the control device positioning a plurality of visual images associated with a plurality of media events adjacent to the text script in a scrollable portion of the display to establish a spatial relationship between the plurality of visual images and the text script, such that the position of each visual image corresponds to one or more words in the text script with which the associated media event is to begin during a presentation; scrolling the text script on the display while maintaining the spatial relationship between the text script and the visual images; causing the media events associated with the visual images to begin approximately upon the corresponding one or more words of the text script scrolling through a predetermined region of the display during the presentation; and generating the presentation, including audio information corresponding to the user speaking at least a portion of the text script. 15. The system of claim 13 , wherein the processor electronics are further configured to perform operations comprising: loading the text script from a location within a storage device. | 0.56053 |
8. A method for performing a search, the method comprising the computer-implemented steps of: receiving, from a client, at a server, via a contextual search interface displayed on a content presentation application executing on the client, a user query that includes query data entered by the user in a first field of the contextual search interface; receiving from said client, at said server, with said query data, context data entered by the user in a second field of the contextual search interface; deriving a context vector from said context data, said context vector representing said context data and further being not identical to said context data; generating a search result comprising a ranked list of hits using at least the query data, the context vector, and a plurality of hits obtained from searching a search corpus; wherein the step of generating the search result includes at least one of: searching the search corpus based on search criteria that are based, at least in part, on the context vector; or ranking the plurality of hits based, at least in part, on the context vector; transmitting the search result for presentation to the user. | 8. A method for performing a search, the method comprising the computer-implemented steps of: receiving, from a client, at a server, via a contextual search interface displayed on a content presentation application executing on the client, a user query that includes query data entered by the user in a first field of the contextual search interface; receiving from said client, at said server, with said query data, context data entered by the user in a second field of the contextual search interface; deriving a context vector from said context data, said context vector representing said context data and further being not identical to said context data; generating a search result comprising a ranked list of hits using at least the query data, the context vector, and a plurality of hits obtained from searching a search corpus; wherein the step of generating the search result includes at least one of: searching the search corpus based on search criteria that are based, at least in part, on the context vector; or ranking the plurality of hits based, at least in part, on the context vector; transmitting the search result for presentation to the user. 9. The method of claim 8 , further comprising: with said search result, transmitting to the user a user-editable list of context terms from the context vector. | 0.73298 |
1. A method comprising: comparing at least one aspect of a query to access a data store to one or more rule sets associated with the data store to determine at least one potential access path within the data store for responding to the query, wherein said comparing the at least one aspect is carried out prior to executing said query on the data store; comparing information pertaining to an entity responsible for submission of the query to risk information pertaining to one or more entities to determine a level of risk associated with the entity, wherein said risk information comprises an established risk level attributed to (i) one or more internet protocol addresses pertaining to the one or more entities and (ii) one or more account identifiers pertaining to the one or more entities, wherein said comparing comprises comparing the one or more internet protocol addresses pertaining to the one or more entities to (a) a white list of internet protocol addresses and (b) a list of internet protocol addresses linked to fraudulent activity, and wherein said comparing the information is carried out prior to executing said query on the data store; generating a modified version of the query based on information derived from the at least one potential access path within the data store for responding to the query, wherein said generating comprises re-formatting one or more Rete-based rules to reduce response data resulting from the query, and wherein said generating the modified version of the query is carried out prior to executing said query on the data store; calculating a risk score associated with the modified version of the query based on (i) the level of risk associated with the entity responsible for submission of the query, (ii) one or more aspects of the modified version of the query, and (iii) a correlation between the level of risk associated with the entity and at least one of one or more historical use cases and one or more policy parameters, wherein said calculating is carried out prior to executing said modified version of the query on the data store; determining, based on the risk score, one or more of multiple authentication operations to be implemented prior to executing the modified version of the query on the data store; and implementing the one or more authentication operations prior to executing the modified version of the query on the data store. | 1. A method comprising: comparing at least one aspect of a query to access a data store to one or more rule sets associated with the data store to determine at least one potential access path within the data store for responding to the query, wherein said comparing the at least one aspect is carried out prior to executing said query on the data store; comparing information pertaining to an entity responsible for submission of the query to risk information pertaining to one or more entities to determine a level of risk associated with the entity, wherein said risk information comprises an established risk level attributed to (i) one or more internet protocol addresses pertaining to the one or more entities and (ii) one or more account identifiers pertaining to the one or more entities, wherein said comparing comprises comparing the one or more internet protocol addresses pertaining to the one or more entities to (a) a white list of internet protocol addresses and (b) a list of internet protocol addresses linked to fraudulent activity, and wherein said comparing the information is carried out prior to executing said query on the data store; generating a modified version of the query based on information derived from the at least one potential access path within the data store for responding to the query, wherein said generating comprises re-formatting one or more Rete-based rules to reduce response data resulting from the query, and wherein said generating the modified version of the query is carried out prior to executing said query on the data store; calculating a risk score associated with the modified version of the query based on (i) the level of risk associated with the entity responsible for submission of the query, (ii) one or more aspects of the modified version of the query, and (iii) a correlation between the level of risk associated with the entity and at least one of one or more historical use cases and one or more policy parameters, wherein said calculating is carried out prior to executing said modified version of the query on the data store; determining, based on the risk score, one or more of multiple authentication operations to be implemented prior to executing the modified version of the query on the data store; and implementing the one or more authentication operations prior to executing the modified version of the query on the data store. 11. The method of claim 1 , further comprising: outputting the risk score associated with the modified version of the query to a policy engine associated with the data store. | 0.841486 |
1. An apparatus for controlling subscriptions, the apparatus comprising: a processor; a non-transitory computer-readable storage having stored thereon a computer program configured for controlling the processor to perform the steps of: assigning one of a PASSTHROUGH value and a BLOCK value to a first attribute of each topic node of a topic tree based on at least one assignment rule; responsive to a wildcard topic string, determining a highest level topic node of the topic tree matching the wildcard topic string to define a root node; traversing each topic node of the topic tree starting the root node, the traversing comprising: analyzing the first attribute of the topic node to determine whether the first attribute specifies the PASSTHROUGH value or the BLOCK value, if the first attribute specifies the PASSTHROUGH value, determining a subscriber associated with the subscription should receive a message associated with the topic string of the topic node, and if the first attribute specifies the BLOCK value, determining that the subscriber should not receive a message associated with the topic string of the topic node or a message associated with other topic strings more specific than the topic string of the topic node when the wildcard topic string is less specific than the topic string of the topic node; detecting a generation of a new topic node; and performing the traversing for the new topic node. | 1. An apparatus for controlling subscriptions, the apparatus comprising: a processor; a non-transitory computer-readable storage having stored thereon a computer program configured for controlling the processor to perform the steps of: assigning one of a PASSTHROUGH value and a BLOCK value to a first attribute of each topic node of a topic tree based on at least one assignment rule; responsive to a wildcard topic string, determining a highest level topic node of the topic tree matching the wildcard topic string to define a root node; traversing each topic node of the topic tree starting the root node, the traversing comprising: analyzing the first attribute of the topic node to determine whether the first attribute specifies the PASSTHROUGH value or the BLOCK value, if the first attribute specifies the PASSTHROUGH value, determining a subscriber associated with the subscription should receive a message associated with the topic string of the topic node, and if the first attribute specifies the BLOCK value, determining that the subscriber should not receive a message associated with the topic string of the topic node or a message associated with other topic strings more specific than the topic string of the topic node when the wildcard topic string is less specific than the topic string of the topic node; detecting a generation of a new topic node; and performing the traversing for the new topic node. 2. The apparatus of claim 1 , the traversing further comprising that when the first attribute specifies the BLOCK value and the wildcard topic string directly matches the topic string of the topic node, determining that the subscriber should receive a message associated with the topic string. | 0.5 |
7. A method, comprising: providing, by a computing device, user input from a query form to a server; providing, by the computing device, a number of a plurality of speculative search queries to the server, individual ones of the plurality of speculative search queries including at least one of a plurality of suggested keywords obtained from the server, wherein at least one of the plurality of suggested keywords comprises at least one enhanced suggested keyword, the at least one enhanced suggested keyword including at least one spelling correction to the user input, wherein the number of the plurality of speculative search queries is based at least in part on a length of time that a user account has been associated with an electronic commerce application and wherein some of the plurality of suggested keywords are based at least in part on a shopping history associated with the user account corresponding to the electronic commerce application or a popularity of an item offered for sale through the electronic commerce application, and wherein individual ones of the plurality of speculative search queries that include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword are weighted higher than individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword, wherein the weights of the suggested keywords are used to prefer the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword over individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword when determining suggested keywords to include in the speculative search queries; processing a plurality of responses in the computing device, individual ones of the plurality of responses corresponding to at least one of the plurality of speculative search queries, the individual ones of the plurality of responses including a corresponding plurality of speculative search results; rendering, in a hidden portion of a browser window in the computing device, at least a portion of the plurality of speculative search results from more than one of the plurality of responses; in response to receiving a user input to execute a committed search query that includes a suggested keyword in at least one of the plurality of speculative search queries, rendering the portion of the plurality of speculative search results in a visible portion of the browser window in the computing device, wherein the visible portion of the browser window is separate from the hidden portion of the browser window; and rendering, in the visible portion of the browser window, a remaining portion of results from at least one of the speculative search queries, in response to receiving the remaining portion of results from the server. | 7. A method, comprising: providing, by a computing device, user input from a query form to a server; providing, by the computing device, a number of a plurality of speculative search queries to the server, individual ones of the plurality of speculative search queries including at least one of a plurality of suggested keywords obtained from the server, wherein at least one of the plurality of suggested keywords comprises at least one enhanced suggested keyword, the at least one enhanced suggested keyword including at least one spelling correction to the user input, wherein the number of the plurality of speculative search queries is based at least in part on a length of time that a user account has been associated with an electronic commerce application and wherein some of the plurality of suggested keywords are based at least in part on a shopping history associated with the user account corresponding to the electronic commerce application or a popularity of an item offered for sale through the electronic commerce application, and wherein individual ones of the plurality of speculative search queries that include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword are weighted higher than individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword, wherein the weights of the suggested keywords are used to prefer the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword over individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword when determining suggested keywords to include in the speculative search queries; processing a plurality of responses in the computing device, individual ones of the plurality of responses corresponding to at least one of the plurality of speculative search queries, the individual ones of the plurality of responses including a corresponding plurality of speculative search results; rendering, in a hidden portion of a browser window in the computing device, at least a portion of the plurality of speculative search results from more than one of the plurality of responses; in response to receiving a user input to execute a committed search query that includes a suggested keyword in at least one of the plurality of speculative search queries, rendering the portion of the plurality of speculative search results in a visible portion of the browser window in the computing device, wherein the visible portion of the browser window is separate from the hidden portion of the browser window; and rendering, in the visible portion of the browser window, a remaining portion of results from at least one of the speculative search queries, in response to receiving the remaining portion of results from the server. 8. The method of claim 7 , wherein the number of the plurality of speculative search queries also varies in accordance with a number of characters in a user input provided to the server. | 0.889087 |
16. The computer system of claim 11 , wherein merging a base language of the added language to the List if the added language is a partially localized language includes: (a) adding the valid base language of the added language to the List, after the added language, if no base language of the added language is in the List; and (b) adding the base language of the valid base language if the valid base language is a partially localized language; and (c) removing the added language from the List if no valid base language is found for the added language. | 16. The computer system of claim 11 , wherein merging a base language of the added language to the List if the added language is a partially localized language includes: (a) adding the valid base language of the added language to the List, after the added language, if no base language of the added language is in the List; and (b) adding the base language of the valid base language if the valid base language is a partially localized language; and (c) removing the added language from the List if no valid base language is found for the added language. 17. The computer system of claim 16 , wherein a valid base language of the added language is a language supported by the computer system. | 0.879697 |
9. A system for image recognition analysis of a digital image comprising: a memory having program instructions and data storage space; a processor configured to use the program instructions to perform the steps of: generating a plurality of characterized pixels from a digitized pathology image; determining in a first layer feature analysis a plurality of first layer confidence scores based on the plurality of characterized pixels, wherein the confidence scores represent a first likelihood of each pixel belonging to a specific classification; determining in a second layer feature analysis a plurality of final recognition scores based on the plurality of characterized pixels and the plurality of first layer confidence scores by applying a second layer model to the plurality of first layer confidence scores, wherein the second layer model is selected from a plurality of second layer models each of which is targeted to perform a specific classification task, wherein the recognition scores represent a final likelihood of each pixel belonging to a specific classification; and classifying part or all of the digitized pathology image based on the final recognition scores, wherein each pixel of the plurality of pixels is labeled with a ground truth; each first layer model from among a plurality of first layer models is generated by machine-learning algorithms based on a correspondence between the ground truth of each pixel of the plurality of pixels and feature descriptor values of a feature of each pixel of the plurality of pixels corresponding to a designated feature type from among a plurality of feature types; and a different first layer model is generated to correspond to each feature type from among the plurality of feature types. | 9. A system for image recognition analysis of a digital image comprising: a memory having program instructions and data storage space; a processor configured to use the program instructions to perform the steps of: generating a plurality of characterized pixels from a digitized pathology image; determining in a first layer feature analysis a plurality of first layer confidence scores based on the plurality of characterized pixels, wherein the confidence scores represent a first likelihood of each pixel belonging to a specific classification; determining in a second layer feature analysis a plurality of final recognition scores based on the plurality of characterized pixels and the plurality of first layer confidence scores by applying a second layer model to the plurality of first layer confidence scores, wherein the second layer model is selected from a plurality of second layer models each of which is targeted to perform a specific classification task, wherein the recognition scores represent a final likelihood of each pixel belonging to a specific classification; and classifying part or all of the digitized pathology image based on the final recognition scores, wherein each pixel of the plurality of pixels is labeled with a ground truth; each first layer model from among a plurality of first layer models is generated by machine-learning algorithms based on a correspondence between the ground truth of each pixel of the plurality of pixels and feature descriptor values of a feature of each pixel of the plurality of pixels corresponding to a designated feature type from among a plurality of feature types; and a different first layer model is generated to correspond to each feature type from among the plurality of feature types. 10. The system of claim 9 , wherein the processor configured for characterizing each pixel of a plurality of the pixels is further configured for: generating an image classification confidence map representing the final image classification likelihood based on the plurality of final recognition scores; and classifying part or all of the digitized pathology image based on the image classification confidence map. | 0.5407 |
2. The method of claim 1 , wherein propagating the at least one knowledge value comprises iteratively applying, by the data processing system, one or more knowledge reasoners to the logical parse hierarchical representation to propagate the at least one knowledge value of at least a subset of the nodes in the logical parse hierarchical representation to one or more other nodes in the logical parse hierarchical representation based on propagation rules, wherein each application of a knowledge reasoner generates a transaction record in the transaction knowledgebase data structure identifying nodes affected by the application of the knowledge reasoner. | 2. The method of claim 1 , wherein propagating the at least one knowledge value comprises iteratively applying, by the data processing system, one or more knowledge reasoners to the logical parse hierarchical representation to propagate the at least one knowledge value of at least a subset of the nodes in the logical parse hierarchical representation to one or more other nodes in the logical parse hierarchical representation based on propagation rules, wherein each application of a knowledge reasoner generates a transaction record in the transaction knowledgebase data structure identifying nodes affected by the application of the knowledge reasoner. 3. The method of claim 2 , wherein the one or more knowledge reasoners comprises at least one of an evidential support reasoner, a relevance reasoner, or a co-reference knowledge reasoner. | 0.834726 |
6. The system of claim 5 , wherein the predictive module generates at least one second background query of the database based on the second set of query results and prior to the user interface receiving the second user query, the at least one second background query querying the database for the different set of query results for each of the query results in the second set of query results. | 6. The system of claim 5 , wherein the predictive module generates at least one second background query of the database based on the second set of query results and prior to the user interface receiving the second user query, the at least one second background query querying the database for the different set of query results for each of the query results in the second set of query results. 7. The system of claim 6 , wherein the predictive module compares the second user query to the at least one second background query prior to sending the second user query to the database such that if the second user query corresponds to the at least one second background query the user interface displays the different set of query results acquired from the at least one second background query that correspond to the second user query. | 0.891331 |
1. A method comprising: receiving a first speech signal and a second speech signal; generating, via a processor, feature coefficients based at least in part on the first speech signal and the second speech signal; comparing the feature coefficients to a codebook to yield an utterance similarity value, wherein the codebook is associated with a database of reference speech signals; if the utterance similarity value is above a threshold, providing access to a service and adding at least one of the first speech signal and the second speech signal to the database of reference signals. | 1. A method comprising: receiving a first speech signal and a second speech signal; generating, via a processor, feature coefficients based at least in part on the first speech signal and the second speech signal; comparing the feature coefficients to a codebook to yield an utterance similarity value, wherein the codebook is associated with a database of reference speech signals; if the utterance similarity value is above a threshold, providing access to a service and adding at least one of the first speech signal and the second speech signal to the database of reference signals. 7. The method of claim 1 , further comprising verifying a user based on the first speech signal using a speaker verification system when the user has used the service previously. | 0.833952 |
15. The apparatus of claim 14 , wherein the received input comprises gesture input. | 15. The apparatus of claim 14 , wherein the received input comprises gesture input. 17. The apparatus of claim 15 further comprising a storage device in communication with the programmable control device, and wherein the operations further comprise: storing the first filtered image within the storage device; and storing, separate from the image, metadata corresponding to the first filtered image, the meta data including the first filter and the first imput parameter used to generate the first filtered image. | 0.846319 |
17. A system according to claim 15 , wherein determination of whether the first semantic representation is similar to the second semantic representation comprises: determination of a number of shared instances between the one or more instances of each of the plurality of entity types of the first semantic digest and one or more instances of each of a second plurality of entity types which are within the second data content; and determination of whether the number of shared instances is greater than a threshold number. | 17. A system according to claim 15 , wherein determination of whether the first semantic representation is similar to the second semantic representation comprises: determination of a number of shared instances between the one or more instances of each of the plurality of entity types of the first semantic digest and one or more instances of each of a second plurality of entity types which are within the second data content; and determination of whether the number of shared instances is greater than a threshold number. 18. A system according to claim 17 , wherein determination of whether the first semantic representation is similar to the second semantic representation comprises: determination of a ratio of the number of shared instances to the smaller of the one or more instances of each of the plurality of entity types and the one or more instances of each of the second plurality of entity types; and determination of whether the ratio is greater than a threshold ratio. | 0.931064 |
12. A method of identifying in one or more images captured by a second camera a target platoon of n objects corresponding to a reference platoon of n objects generated using images captured by a first camera, the method implemented by a processor and comprising: storing in a non-transitory computer readable memory operatively coupled to the processor a first set of trained classifiers and a second set of trained classifiers, wherein the 1 st set specifies values corresponding to a first plurality of attributes usable for identifying objects captured by the first camera, and the 2 nd set differs from the first set and specifies values corresponding to a second plurality of attributes usable for identifying objects captured by the 2 nd camera, wherein the first set of trained classifiers and second set of trained classifiers are trained independently, and wherein the first plurality of attributes and second plurality of attributes have at least one attribute in common; generating, by the processor, a reference group by running the first set of trained classifiers over the reference platoon, the reference group being indicative of values of attributes specified by the 1 st set of trained classifiers and characterizing the objects in the reference platoon; generating, by the processor, using one or more images captured by the 2 nd camera, a plurality of candidate platoons, each candidate platoon comprising n objects, wherein the one or more images are captured by the 2 nd camera in a time window corresponding to the time of capturing by the 1 st camera the one or more images used for generating the reference platoon; generating, by the processor, a plurality of candidate groups, each candidate group obtained by running the 2 nd set of trained classifiers over a respective candidate platoon, each candidate group being indicative of values of attributes specified by the 2 nd set of trained classifiers and characterizing the objects in the corresponding candidate platoon; selecting, by the processor, a candidate platoon corresponding to a candidate group best matching the reference group; identifying, by the processor, the selected candidate platoon as the target platoon. | 12. A method of identifying in one or more images captured by a second camera a target platoon of n objects corresponding to a reference platoon of n objects generated using images captured by a first camera, the method implemented by a processor and comprising: storing in a non-transitory computer readable memory operatively coupled to the processor a first set of trained classifiers and a second set of trained classifiers, wherein the 1 st set specifies values corresponding to a first plurality of attributes usable for identifying objects captured by the first camera, and the 2 nd set differs from the first set and specifies values corresponding to a second plurality of attributes usable for identifying objects captured by the 2 nd camera, wherein the first set of trained classifiers and second set of trained classifiers are trained independently, and wherein the first plurality of attributes and second plurality of attributes have at least one attribute in common; generating, by the processor, a reference group by running the first set of trained classifiers over the reference platoon, the reference group being indicative of values of attributes specified by the 1 st set of trained classifiers and characterizing the objects in the reference platoon; generating, by the processor, using one or more images captured by the 2 nd camera, a plurality of candidate platoons, each candidate platoon comprising n objects, wherein the one or more images are captured by the 2 nd camera in a time window corresponding to the time of capturing by the 1 st camera the one or more images used for generating the reference platoon; generating, by the processor, a plurality of candidate groups, each candidate group obtained by running the 2 nd set of trained classifiers over a respective candidate platoon, each candidate group being indicative of values of attributes specified by the 2 nd set of trained classifiers and characterizing the objects in the corresponding candidate platoon; selecting, by the processor, a candidate platoon corresponding to a candidate group best matching the reference group; identifying, by the processor, the selected candidate platoon as the target platoon. 14. The method of claim 12 further comprising identifying the m th object in the target platoon as the same object as the m th object in the reference platoon, wherein m is less than or equal to n. | 0.566284 |
1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: based on an analysis of conversation data transmitted within an audio communication session between a first communication device of a network and a second communication device of the network, determining, during the audio communication session, goal data indicative of a goal associated with the first communication device and the second communication device; based on data received from a network data store coupled to the first communication device and the second communication device, determining solution data indicative of solutions to accomplish the goal; and in response to the determining the solution data and determining that first speech data associated with the conversation data is not being transmitted between the first communication device and the second communication device during the audio communication session, generating second speech data based on the solution data and adding a network device that is coupled to the first communication device and the second communication device via the network as an additional participant in the audio communication session, and simultaneously transmitting the second speech data from the network device to the first communication device and the second communication device, wherein, in addition to the conversation data transmitted between the first communication device and the second communication device during the audio communication session, the second speech data is transmitted to the first communication device and the second communication device during the audio communication session, and third speech data is transmitted between the first communication device and the second communication device after receiving the second speech data associated with the solution data. | 1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: based on an analysis of conversation data transmitted within an audio communication session between a first communication device of a network and a second communication device of the network, determining, during the audio communication session, goal data indicative of a goal associated with the first communication device and the second communication device; based on data received from a network data store coupled to the first communication device and the second communication device, determining solution data indicative of solutions to accomplish the goal; and in response to the determining the solution data and determining that first speech data associated with the conversation data is not being transmitted between the first communication device and the second communication device during the audio communication session, generating second speech data based on the solution data and adding a network device that is coupled to the first communication device and the second communication device via the network as an additional participant in the audio communication session, and simultaneously transmitting the second speech data from the network device to the first communication device and the second communication device, wherein, in addition to the conversation data transmitted between the first communication device and the second communication device during the audio communication session, the second speech data is transmitted to the first communication device and the second communication device during the audio communication session, and third speech data is transmitted between the first communication device and the second communication device after receiving the second speech data associated with the solution data. 10. The system of claim 1 , wherein the transmission is a first transmission and the operations further comprise: determining conflict data indicative of a conflict of the goal with an action associated with the first communication device, wherein the action is determined based on the analysis, and wherein the adding comprises adding the network device as the additional participant to facilitate a second transmission of the conflict data from the network device to the first communication device. | 0.528041 |
4. The system of claim 1 in which the type of the at least one portion is determined at least in part by detecting a boundary between portions of the message corresponding to the greeting portion, the message body portion and/or the tail portion. | 4. The system of claim 1 in which the type of the at least one portion is determined at least in part by detecting a boundary between portions of the message corresponding to the greeting portion, the message body portion and/or the tail portion. 6. The system of claim 4 in which the boundary between the greeting portion, the message body portion and/or the tail portion of the audio voice message are detected or inferred at a pause in the message. | 0.902288 |
22. The method of claim 17 , wherein said metadata database is populated with metadata corresponding to a plurality of digital images. | 22. The method of claim 17 , wherein said metadata database is populated with metadata corresponding to a plurality of digital images. 24. The method of claim 22 , further comprising: extracting said metadata for each corresponding digital image from a header of a digital image file of said digital image. | 0.941057 |
1. A system comprising: one or more processors; and a computer-readable storage device storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting a first split from the one or more splits according to the overall score for each split; and augmenting the query with a first synonym phrase, wherein the first synonym phrase is a synonym of a first subterm of the first split. | 1. A system comprising: one or more processors; and a computer-readable storage device storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting a first split from the one or more splits according to the overall score for each split; and augmenting the query with a first synonym phrase, wherein the first synonym phrase is a synonym of a first subterm of the first split. 3. The system of claim 1 , wherein generating one or more splits of the first compound term comprises incrementally analyzing prefixes of increasing length of the first compound term to identify subterms of the prefixes that appear in the dictionary. | 0.513575 |
2. The method of claim 1 , wherein obtaining candidate replacement words for one of the input words comprises: matching the input word to subject words of a candidate table; and obtaining one or more candidate replacement words from the candidate table corresponding to the matched subject word. | 2. The method of claim 1 , wherein obtaining candidate replacement words for one of the input words comprises: matching the input word to subject words of a candidate table; and obtaining one or more candidate replacement words from the candidate table corresponding to the matched subject word. 7. The method of claim 2 , wherein the candidate replacement words of the candidate table include words that have a phonetic match to their corresponding subject words. | 0.951071 |
13. A system comprising: a processor; and a computer-readable medium having stored therein instructions which, when executed by the processor, cause the processor to perform operations comprising: receiving text, wherein a portion of the text comprises an abbreviation; associating a sender of the text with one of a plurality of groups, to yield a sender group; associating a recipient of the text with one of the plurality of groups, to yield a recipient group; and upon determining a difference in the sender group and the recipient group, wherein the difference indicates distinct cultures of the sender and the recipient: expanding, the abbreviation based on the distinct cultures, to yield expanded text; transmitting a message to the recipient which comprises the abbreviation and the expanded text; modifying, via the processor, a display presented to the sender in which the expanded text is added to the text having the abbreviation; and presenting a first advertisement to the sender based on the text and the sender group, wherein the first advertisement is distinct from a second advertisement presented to the recipient. | 13. A system comprising: a processor; and a computer-readable medium having stored therein instructions which, when executed by the processor, cause the processor to perform operations comprising: receiving text, wherein a portion of the text comprises an abbreviation; associating a sender of the text with one of a plurality of groups, to yield a sender group; associating a recipient of the text with one of the plurality of groups, to yield a recipient group; and upon determining a difference in the sender group and the recipient group, wherein the difference indicates distinct cultures of the sender and the recipient: expanding, the abbreviation based on the distinct cultures, to yield expanded text; transmitting a message to the recipient which comprises the abbreviation and the expanded text; modifying, via the processor, a display presented to the sender in which the expanded text is added to the text having the abbreviation; and presenting a first advertisement to the sender based on the text and the sender group, wherein the first advertisement is distinct from a second advertisement presented to the recipient. 15. The system of claim 13 , wherein the expanded text is a group-specific term related to the selected group. | 0.514932 |
1. A speech recognition system, comprising: a host computer operative to communicate at least one graphical user interface (GUI) display file to a mobile terminal, wherein the GUI files have attached thereto a dictionary file having phonemes and syntax file having allowable patterns of words being content specific to the graphical user interface (GUI) display file and associated with a particular context state; and the mobile terminal that displays one or more GUI pages associated with the received GUI files and receives speech input to assign a correct meaning to received input speech by determining a current context state of the received input speech, assigning one meaning to received input speech by utilizing the dictionary file and syntax file when the current context state is determined to be a first context state, and assigning a different meaning to the same received input speech by utilizing the dictionary file and syntax file when the current context state is determined to be a second context. | 1. A speech recognition system, comprising: a host computer operative to communicate at least one graphical user interface (GUI) display file to a mobile terminal, wherein the GUI files have attached thereto a dictionary file having phonemes and syntax file having allowable patterns of words being content specific to the graphical user interface (GUI) display file and associated with a particular context state; and the mobile terminal that displays one or more GUI pages associated with the received GUI files and receives speech input to assign a correct meaning to received input speech by determining a current context state of the received input speech, assigning one meaning to received input speech by utilizing the dictionary file and syntax file when the current context state is determined to be a first context state, and assigning a different meaning to the same received input speech by utilizing the dictionary file and syntax file when the current context state is determined to be a second context. 4. The system of claim 1 , wherein at least one of the dictionary file or the syntax file are stored in a memory of the host computer. | 0.622627 |
10. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. | 10. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. 16. The system of claim 10 , wherein: the interactive field is selectable to cause display of the one or more query terms and additional interactive field query terms; identifying user interaction with the interactive field includes identifying user selection of the interactive field and identifying the selection of the one or more query terms within the interactive field; and wherein updating the display of the query completion template comprises providing for display the selected one or more query terms within the interactive field in response to the user selection. | 0.504444 |
1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; responsive to detecting a first portion of a gesture at a presence-sensitive input device, generating a word prefix comprising a plurality of characters; responsive to detecting, by the computing device and during the gesture, a second portion of the gesture at the presence-sensitive input device: updating, based on a word in a dictionary, the word prefix to include an additional character; responsive to determining that an alignment score of the gesture matching the word prefix with the additional character does not satisfy a threshold, determining, using correction data that indicates at least one alternative word prefix that is based at least in part on a misspelling of the word in the dictionary, an alternative alignment score, wherein the alternative word prefix comprises at least a portion of the word prefix; determining, by the computing device and based on the alternative alignment score for the alternative word prefix, a candidate word; and outputting, by the computing device and for display, the candidate word. | 1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; responsive to detecting a first portion of a gesture at a presence-sensitive input device, generating a word prefix comprising a plurality of characters; responsive to detecting, by the computing device and during the gesture, a second portion of the gesture at the presence-sensitive input device: updating, based on a word in a dictionary, the word prefix to include an additional character; responsive to determining that an alignment score of the gesture matching the word prefix with the additional character does not satisfy a threshold, determining, using correction data that indicates at least one alternative word prefix that is based at least in part on a misspelling of the word in the dictionary, an alternative alignment score, wherein the alternative word prefix comprises at least a portion of the word prefix; determining, by the computing device and based on the alternative alignment score for the alternative word prefix, a candidate word; and outputting, by the computing device and for display, the candidate word. 8. The method of claim 1 , further comprising: responsive to receiving a third portion of the gesture, determining, by the computing device, a quantity of error correction operations applied to the word prefix; and responsive to determining that the quantity of error correction operations satisfies a threshold, refraining, by the computing device, from applying a subsequent error correction operation to the word prefix. | 0.541032 |
1. A method programmed for execution in a computing environment for consulting and providing localized response information from a radiological domain ontology in reference to a subject, the method comprising: defining one or more aspects of radiology functions as concept properties represented by a vocabulary of one or more instances of the radiological domain ontology, the radiological domain ontology declaring and fulfilling a model of radiological domain knowledge; wherein said model of radiological domain knowledge comprises: one or more findings; one or more finding characteristics; and object properties, wherein said object properties represent relationships among said findings and finding characteristics; employing a context that defines a set of said radiological domain knowledge and the relationships among said set of said radiological domain knowledge, to describe said subject; providing an informational item of interest that relates to said subject in a localized representation; and providing a localization ontology, said localization ontology comprising: localization language references; localization labels for said findings, finding characteristics and object properties; and references to said radiological domain ontology; wherein a localized representation of said informational item of interest is identified in said localization language reference and the corresponding localization labels are identified and utilized to consult said radiological domain ontology to validate that said localized informational item of interest is radiological and resides in said radiological domain knowledge, wherein a definitive concept of said localized informational item of interest is identified from within said radiological domain knowledge, and wherein said localized informational item of interest is classified to provide said localized response regarding the subject. | 1. A method programmed for execution in a computing environment for consulting and providing localized response information from a radiological domain ontology in reference to a subject, the method comprising: defining one or more aspects of radiology functions as concept properties represented by a vocabulary of one or more instances of the radiological domain ontology, the radiological domain ontology declaring and fulfilling a model of radiological domain knowledge; wherein said model of radiological domain knowledge comprises: one or more findings; one or more finding characteristics; and object properties, wherein said object properties represent relationships among said findings and finding characteristics; employing a context that defines a set of said radiological domain knowledge and the relationships among said set of said radiological domain knowledge, to describe said subject; providing an informational item of interest that relates to said subject in a localized representation; and providing a localization ontology, said localization ontology comprising: localization language references; localization labels for said findings, finding characteristics and object properties; and references to said radiological domain ontology; wherein a localized representation of said informational item of interest is identified in said localization language reference and the corresponding localization labels are identified and utilized to consult said radiological domain ontology to validate that said localized informational item of interest is radiological and resides in said radiological domain knowledge, wherein a definitive concept of said localized informational item of interest is identified from within said radiological domain knowledge, and wherein said localized informational item of interest is classified to provide said localized response regarding the subject. 5. The method of claim 1 wherein the provided response information from said radiological domain ontology is a list of all of said localization labels for all of said finding characteristics for said model of radiological domain knowledge. | 0.51271 |
1. A method comprising: receiving, at a computing device, a request from a mobile device over a network; determining, via the computing device, whether the request includes one or more of a search query and geo-location information; when it is determined that the request includes the search query and excludes the geo-location information: generating a search result based on the search query; parsing the search results to determine a first geo-location; and determining the at least one virtual billboard in proximity with the first geo-location derived from the search result; and communicating the at least one virtual billboard to the mobile device; and when it is determined that the request includes the geo-location information identifying a second geo-location and excludes the search query: determining at least one further virtual billboard in proximity with the second geo-location identified by the geo-location information; and communicating the at least one further virtual billboard to the mobile device. | 1. A method comprising: receiving, at a computing device, a request from a mobile device over a network; determining, via the computing device, whether the request includes one or more of a search query and geo-location information; when it is determined that the request includes the search query and excludes the geo-location information: generating a search result based on the search query; parsing the search results to determine a first geo-location; and determining the at least one virtual billboard in proximity with the first geo-location derived from the search result; and communicating the at least one virtual billboard to the mobile device; and when it is determined that the request includes the geo-location information identifying a second geo-location and excludes the search query: determining at least one further virtual billboard in proximity with the second geo-location identified by the geo-location information; and communicating the at least one further virtual billboard to the mobile device. 5. The method of claim 1 , further comprising: receiving traffic information for the first geo-location; generating a price for the at least one virtual billboard based on the received traffic information; providing the at least one virtual billboard for purchase based on the price; and receiving a purchase of a right to associate an advertisement with the at least one virtual billboard, before providing the at least one virtual billboard to the mobile device. | 0.852568 |
8. A tangible computer readable storage medium having instructions for causing a computer to execute a method, comprising: identifying documents that include a name of an individual; comparing the documents with articles in an encyclopedia; summarizing the documents with content from the articles in the encyclopedia to build a user profile of the individual; and using the user profile to respond to search queries. | 8. A tangible computer readable storage medium having instructions for causing a computer to execute a method, comprising: identifying documents that include a name of an individual; comparing the documents with articles in an encyclopedia; summarizing the documents with content from the articles in the encyclopedia to build a user profile of the individual; and using the user profile to respond to search queries. 10. The tangible computer readable storage medium of claim 8 , wherein the instructions are for causing the computer to further perform: receiving a search query with search terms; comparing the search terms with the content from the articles in the user profile to determine a similarity between the search terms and the content; using the similarity to determine whether the user profile matches the search terms. | 0.5 |
21. A tangible computer program product comprising a computer readable storage medium having control logic stored therein for causing a computer to process text, the control logic comprising: computer readable first program code that causes the computer to provide a first abstract mathematical vector space and a second abstract mathematical vector space, wherein the first abstract mathematical vector space is based on a first collection of documents and the second abstract mathematical vector space is based on a second collection of documents; and computer readable second program code that causes the computer to merge the first abstract mathematical vector space with the second abstract mathematical vector space to produce a merged abstract mathematical vector space that is stored in an electronic format accessible to a user, wherein merging is based on a vector averaging of vectors in the first abstract mathematical vector space with vectors in the second abstract mathematical vector space. | 21. A tangible computer program product comprising a computer readable storage medium having control logic stored therein for causing a computer to process text, the control logic comprising: computer readable first program code that causes the computer to provide a first abstract mathematical vector space and a second abstract mathematical vector space, wherein the first abstract mathematical vector space is based on a first collection of documents and the second abstract mathematical vector space is based on a second collection of documents; and computer readable second program code that causes the computer to merge the first abstract mathematical vector space with the second abstract mathematical vector space to produce a merged abstract mathematical vector space that is stored in an electronic format accessible to a user, wherein merging is based on a vector averaging of vectors in the first abstract mathematical vector space with vectors in the second abstract mathematical vector space. 25. The computer program product of claim 21 , wherein the computer readable second program code comprises: code that causes the computer to merge the first abstract mathematical vector space with the second abstract mathematical vector space to produce a merged abstract mathematical vector space that is stored in an electronic format accessible to a user, wherein merging is based on at least one of (i) a vector averaging of document vectors in the first abstract mathematical vector space with document vectors in the second abstract mathematical vector space, and (ii) a vector averaging of term vectors in the first abstract mathematical vector space with term vectors in the second abstract mathematical vector space. | 0.535674 |
9. An automatic speech recognition system comprising: an input interface configured to receive input speech; a pre-processor configured to determine a language of the input speech and, based on the language of the input speech, select from among a plurality of automatic speech recognition engines configured to recognize speech of different languages, only those automatic speech recognition engines configured to recognize the language of the input speech including: a first automatic speech recognition (ASR) engine configured to translate the input speech of the language into text according to a first acoustic model, and output first translated text that is translated from the input speech according to the first acoustic model and a first confidence score indicating a degree of accuracy of translating the input speech into the first translated text according to the first acoustic model; a second ASR engine configured to translate the input speech of the language into text according to a second acoustic model, and output second translated text that is translated from the input speech according to the second acoustic model and a second confidence score indicating a degree of accuracy of translating the input speech into the second translated text according to the second acoustic model; and a comparator configured to compare the first confidence score and the second confidence score, and output a most accurate representation of the input speech from among the first translated text and the second translated text based on a result of the comparison, wherein the first acoustic model is different from the second acoustic model. | 9. An automatic speech recognition system comprising: an input interface configured to receive input speech; a pre-processor configured to determine a language of the input speech and, based on the language of the input speech, select from among a plurality of automatic speech recognition engines configured to recognize speech of different languages, only those automatic speech recognition engines configured to recognize the language of the input speech including: a first automatic speech recognition (ASR) engine configured to translate the input speech of the language into text according to a first acoustic model, and output first translated text that is translated from the input speech according to the first acoustic model and a first confidence score indicating a degree of accuracy of translating the input speech into the first translated text according to the first acoustic model; a second ASR engine configured to translate the input speech of the language into text according to a second acoustic model, and output second translated text that is translated from the input speech according to the second acoustic model and a second confidence score indicating a degree of accuracy of translating the input speech into the second translated text according to the second acoustic model; and a comparator configured to compare the first confidence score and the second confidence score, and output a most accurate representation of the input speech from among the first translated text and the second translated text based on a result of the comparison, wherein the first acoustic model is different from the second acoustic model. 10. The automatic speech recognition system of claim 9 , wherein the first ASR engine is further configured to translate the input speech of the language into the first translated text according to the first acoustic model and a first language model, wherein the second ASR engine is further configured to translate the input speech of the language into the second translated text according to the second acoustic model and a second language model, and wherein the first language model is different from the second language model. | 0.5 |
20. A method for processing voice recognition in a client/server system comprising: transmitting information from a web server a markup language page having extensions configured to obtain input data from a user a first client device and a user of a second client device, wherein the first client device and the second client device are remote from each other and communicate with the web server over a wide area network, the first client device having a visual interface browser to access information from the web server and a visual rendering device, and the second client device comprising a telephone and a voice browser to access information from the web server; rendering the markup language page on each of the client devices; obtaining input data as a function of input from each of the users of the corresponding client devices; transmitting the input data and an indication of an associated grammar over the wide area network to a single recognition server remote from each of the client devices, the recognition server being connected to the wide area network; processing the input data with the associated grammar using the single recognition server; transmitting a recognition result from the single recognition server indicative of what was inputted from each client device over the wide area network to at least one of the corresponding client device providing the input and the web server; receiving over the wide area network and at the single recognition server data indicative of a prompt for the user to be used when the recognition results are indicative of no recognition of the input from one of the client devices; converting at the single recognition server the data indicative of the prompt to audible speech data when the recognition results are indicative of no recognition of the input from said one of the client devices; and sending the audible speech data to said one of the client devices over the wide area network. | 20. A method for processing voice recognition in a client/server system comprising: transmitting information from a web server a markup language page having extensions configured to obtain input data from a user a first client device and a user of a second client device, wherein the first client device and the second client device are remote from each other and communicate with the web server over a wide area network, the first client device having a visual interface browser to access information from the web server and a visual rendering device, and the second client device comprising a telephone and a voice browser to access information from the web server; rendering the markup language page on each of the client devices; obtaining input data as a function of input from each of the users of the corresponding client devices; transmitting the input data and an indication of an associated grammar over the wide area network to a single recognition server remote from each of the client devices, the recognition server being connected to the wide area network; processing the input data with the associated grammar using the single recognition server; transmitting a recognition result from the single recognition server indicative of what was inputted from each client device over the wide area network to at least one of the corresponding client device providing the input and the web server; receiving over the wide area network and at the single recognition server data indicative of a prompt for the user to be used when the recognition results are indicative of no recognition of the input from one of the client devices; converting at the single recognition server the data indicative of the prompt to audible speech data when the recognition results are indicative of no recognition of the input from said one of the client devices; and sending the audible speech data to said one of the client devices over the wide area network. 24. The method of claim 20 wherein transmitting the indication of the grammar comprises transmitting a reference to the recognition server as to where the grammar is located. | 0.567947 |
1. A machine translation apparatus comprising: a document receiving unit configured to receive an input of a source language document described in a source language; a first translating unit configured to translate the source language document into a translated document described in a target language in a first translation process, and to identify a document ambiguous portion that is a word or a sentence, for which a plurality of candidate translations occurs during the first translation process; a storing unit configured to store the translated document and the document ambiguous portion; a speech receiving unit configured to receive a speech in the source language; a recognition unit configured to recognize the speech received by the speech receiving unit and to create text of a source language speech sentence as a recognition result; a second translating unit configured to translate the text of the source language speech sentence into the target language; an extracting unit configured to extract a source language document sentence relating to the source language speech sentence from the source language document; an updating unit configured to: select, when the extracted source language document sentence includes the document ambiguous portion, a translated portion of the source language speech sentence corresponding to the document ambiguous portion of the extracted source language document sentence, the translated portion of the source language speech sentence being obtained by a type of ambiguity identification that is the same type of ambiguity identification as was used in the first translation process that identified the document ambiguous portion; retranslate the source language document using the selected translated portion of the source language speech sentence, and the extracted source language document sentence relating to the source language speech sentence; and update the translated document stored in the storing unit using the retranslated source language document; and a display control unit configured to display the updated translated document on a display unit. | 1. A machine translation apparatus comprising: a document receiving unit configured to receive an input of a source language document described in a source language; a first translating unit configured to translate the source language document into a translated document described in a target language in a first translation process, and to identify a document ambiguous portion that is a word or a sentence, for which a plurality of candidate translations occurs during the first translation process; a storing unit configured to store the translated document and the document ambiguous portion; a speech receiving unit configured to receive a speech in the source language; a recognition unit configured to recognize the speech received by the speech receiving unit and to create text of a source language speech sentence as a recognition result; a second translating unit configured to translate the text of the source language speech sentence into the target language; an extracting unit configured to extract a source language document sentence relating to the source language speech sentence from the source language document; an updating unit configured to: select, when the extracted source language document sentence includes the document ambiguous portion, a translated portion of the source language speech sentence corresponding to the document ambiguous portion of the extracted source language document sentence, the translated portion of the source language speech sentence being obtained by a type of ambiguity identification that is the same type of ambiguity identification as was used in the first translation process that identified the document ambiguous portion; retranslate the source language document using the selected translated portion of the source language speech sentence, and the extracted source language document sentence relating to the source language speech sentence; and update the translated document stored in the storing unit using the retranslated source language document; and a display control unit configured to display the updated translated document on a display unit. 6. The apparatus according to claim 1 , wherein the first translating unit creates the document ambiguous portion for which a plurality of candidate translations occur during selecting a dependency of a word in the first translation process, and the updating unit, when the extracted source language document sentence includes the document an ambiguous portion selects a dependency between words of the source language speech sentence corresponding to the document ambiguous portion of the extracted source language sentence as a dependency of the document ambiguous portion, the updating unit retranslating the source language document and updating the translated document stored in the storing unit using the retranslated source language document. | 0.5 |
4. The method of claim 1 , wherein the regular expressions are to be placed in the group. | 4. The method of claim 1 , wherein the regular expressions are to be placed in the group. 5. The method of claim 4 , wherein if any of the regular expressions appear in a group of documents, then a presence of the concept associated with the expressions is marked in those documents. | 0.939375 |
3. The method of claim 2 wherein identifying a plurality of deep senones comprises: identifying a pair of parameters to be merged corresponding to the plurality of deep senones. | 3. The method of claim 2 wherein identifying a plurality of deep senones comprises: identifying a pair of parameters to be merged corresponding to the plurality of deep senones. 6. The method of claim 3 wherein each deep senone is represented by at least one continuous density function, wherein the parameters comprise characteristics of the continuous density function, and wherein identifying a pair of parameters to be merged comprises: identifying a pair of characteristics to be merged based on a reduction in likelihood of generating a set of data corresponding to the pair of characteristics which results from merging the pair of characteristics. | 0.82148 |
19. The computer-readable non-transitory medium of claim 14 , wherein the instructions further cause the microprocessor to: update an agent compliance score based on failure to receive the second event notification prior to expiry of the timer. | 19. The computer-readable non-transitory medium of claim 14 , wherein the instructions further cause the microprocessor to: update an agent compliance score based on failure to receive the second event notification prior to expiry of the timer. 20. The computer-readable non-transitory medium of claim 19 , wherein the instructions further cause the microprocessor to: display the agent compliance score on the screen of the computer used by the agent. | 0.853992 |
1. An apparatus for natural language processing (‘NLP’), the apparatus comprising a computer processor, a computer memory operatively coupled to the computer processor and the computer memory having disposed within it computer program instructions that, when executed by the processor, cause the apparatus to carry out the steps of: receiving, by an NLP module, the NLP module including automated computing machinery configured for NLP, text specifying predetermined evidence; receiving, by the NLP module, a text passage to process, the text passage including conditions and logical operators, the text passage comprising criteria for evidence; decomposing, by the NLP module, the text passage into coarse grained text fragments, including grouping text segments as coarse grained text fragments in dependence upon the logical operators; analyzing, by the NLP module, each coarse grained text fragment to identify conditions within the coarse grained text fragment; evaluating, by the NLP module, each identified condition in accordance with the predetermined evidence and predefined condition evaluation rules; evaluating, by the NLP module, each coarse grained text fragment in dependence upon the identified condition evaluations and the logical operators of the coarse grained text fragment including: evaluating each OR logical operator as the higher value of each evaluated condition of the OR logical operator; evaluating each AND logical operator as the lower value of each evaluated condition of the AND logical operator; and calculating a fragment score for each coarse grained text fragment as the average of the evaluations of the OR logical operators and the AND logical operators of the coarse grained text fragment; and calculating, by the NLP module in dependence upon the evaluations of each coarse grained text fragment, a truth value indicating a degree to which the evidence meets the criteria of the text passage. | 1. An apparatus for natural language processing (‘NLP’), the apparatus comprising a computer processor, a computer memory operatively coupled to the computer processor and the computer memory having disposed within it computer program instructions that, when executed by the processor, cause the apparatus to carry out the steps of: receiving, by an NLP module, the NLP module including automated computing machinery configured for NLP, text specifying predetermined evidence; receiving, by the NLP module, a text passage to process, the text passage including conditions and logical operators, the text passage comprising criteria for evidence; decomposing, by the NLP module, the text passage into coarse grained text fragments, including grouping text segments as coarse grained text fragments in dependence upon the logical operators; analyzing, by the NLP module, each coarse grained text fragment to identify conditions within the coarse grained text fragment; evaluating, by the NLP module, each identified condition in accordance with the predetermined evidence and predefined condition evaluation rules; evaluating, by the NLP module, each coarse grained text fragment in dependence upon the identified condition evaluations and the logical operators of the coarse grained text fragment including: evaluating each OR logical operator as the higher value of each evaluated condition of the OR logical operator; evaluating each AND logical operator as the lower value of each evaluated condition of the AND logical operator; and calculating a fragment score for each coarse grained text fragment as the average of the evaluations of the OR logical operators and the AND logical operators of the coarse grained text fragment; and calculating, by the NLP module in dependence upon the evaluations of each coarse grained text fragment, a truth value indicating a degree to which the evidence meets the criteria of the text passage. 4. The apparatus of claim 1 wherein evaluating the identified condition in accordance with the predetermined evidence and predefined evaluation criteria further comprises assigning to the condition a value between 0 and 1, where a value of 1 represents evidence satisfying the condition and a value of 0 represents evidence not satisfying the condition. | 0.539063 |
15. A method comprising: under control of one or more processors configured with executable instructions, recognizing textual strings within a written work, each of the textual strings corresponding to one of a plurality of named entities and having a position within the written work; grouping the textual strings by named entity; for each of the named entities: determining a significance value for the named entity based on a quantity of textual strings corresponding to the named entity; and associating the named entity with the written work; determining an ordered list of the named entities based at least in part on the determined significance values; storing the ordered list of the named entities in a memory for association with the written work; identifying a motion picture corresponding to the written work; identifying one or more motion picture character names from the identified motion picture; and associating each selected motion picture character name with a named identity. | 15. A method comprising: under control of one or more processors configured with executable instructions, recognizing textual strings within a written work, each of the textual strings corresponding to one of a plurality of named entities and having a position within the written work; grouping the textual strings by named entity; for each of the named entities: determining a significance value for the named entity based on a quantity of textual strings corresponding to the named entity; and associating the named entity with the written work; determining an ordered list of the named entities based at least in part on the determined significance values; storing the ordered list of the named entities in a memory for association with the written work; identifying a motion picture corresponding to the written work; identifying one or more motion picture character names from the identified motion picture; and associating each selected motion picture character name with a named identity. 16. The method of claim 15 , further comprising: for each of the named entities: comparing the textual strings with the identified one or more motion picture character names; and selecting a motion picture character name from the identified one or more motion picture character names which most closely matches the textual strings for the named identity. | 0.746496 |
1. A computerized system for generating user-configured designs of integrated circuits, comprising: a user interface adapted to provide and receive information to and from a user, respectively; and an object-oriented design environment operatively coupled to said user interface and having a plurality of associated design tools, wherein a plurality of components associated with said designs of integrated circuits are represented as objects, at least a portion of said objects being encapsulated and containing information relating to both the interface and build hierarchy associated with its respective design component, said design tools using said information within said objects to build said design, said objects being user-configurable and selectable within said environment via said user interface; wherein said objects being user configurable comprises adding an extension instruction to said designs of integrated circuits, said extension instruction comprising a mixed length instruction set architecture that utilizes instructions of at least two lengths without a mode switch. | 1. A computerized system for generating user-configured designs of integrated circuits, comprising: a user interface adapted to provide and receive information to and from a user, respectively; and an object-oriented design environment operatively coupled to said user interface and having a plurality of associated design tools, wherein a plurality of components associated with said designs of integrated circuits are represented as objects, at least a portion of said objects being encapsulated and containing information relating to both the interface and build hierarchy associated with its respective design component, said design tools using said information within said objects to build said design, said objects being user-configurable and selectable within said environment via said user interface; wherein said objects being user configurable comprises adding an extension instruction to said designs of integrated circuits, said extension instruction comprising a mixed length instruction set architecture that utilizes instructions of at least two lengths without a mode switch. 3. The system of claim 1 , wherein said information comprises at least one Java script. | 0.803571 |
15. The apparatus of claim 10 , wherein the at least one processor is further operative with the set of instructions to: obtain the road information associated with the maneuver, the road information comprising at least one of a road type, a road name, a road number, a road direction, or an orientation of the road. | 15. The apparatus of claim 10 , wherein the at least one processor is further operative with the set of instructions to: obtain the road information associated with the maneuver, the road information comprising at least one of a road type, a road name, a road number, a road direction, or an orientation of the road. 16. The apparatus of claim 15 , wherein the at least one processor is further operative with the set of instructions to: identify a plurality of candidate road symbols and candidate action symbols; and select the road symbol from the candidate road symbols based on at least the road information. | 0.856322 |
14. The medium of claim 12 , wherein: the data repository comprises a plurality of data sources; and the data is retrieved from the data repository by: identifying a first data source according to a source key, identifying a record in the first data source containing the data according to a record key, and retrieving the data from the record. | 14. The medium of claim 12 , wherein: the data repository comprises a plurality of data sources; and the data is retrieved from the data repository by: identifying a first data source according to a source key, identifying a record in the first data source containing the data according to a record key, and retrieving the data from the record. 15. The medium of claim 14 , wherein the first data source is a table, the source key identifying the table among the plurality of data sources. | 0.957164 |
1. A method, comprising: reading, via a processor from a displaced-read memory offset address adjusted relative to word-aligned memory operations of a memory access system that utilizes word-aligned address boundaries within a memory, a split data word from the memory comprising a portion of each of two word-aligned data words stored by the memory access system within the memory using the word-aligned memory operations at two of the word-aligned address boundaries within the memory, where reading the split data word from the displaced-read memory offset address comprises a first level of a two-level memory search; comparing the portions of each of the two word-aligned data words within the split data word with corresponding portions of a word-aligned search pattern; determining that a potential complete match for the word-aligned search pattern exists within at least one of the two word-aligned data words based upon an identified match of at least one of the portions of the two word-aligned data words within the split data word with a corresponding at least one portion of the word-aligned search pattern; iterating processing of the first level of the two-level memory search through the memory; performing a second level of the two-level memory search in response to each determined potential complete match for the word-aligned search pattern, comprising: reading, in response to determining that the potential complete match for the word-aligned search pattern exists within the at least one of the two word-aligned data words, at least one complete data word from a word-aligned address boundary at which the at least one of the two word-aligned data words is stored within the memory, where reading the at least one complete data word from the word-aligned address boundary at which the at least one of the two word-aligned data words is stored within the memory comprises the second level of the two-level memory search of the two word-aligned data words: comparing the at least one complete data word with the word-aligned search pattern; and determining whether a complete data word match for the word-aligned search pattern exists within the at least one of the two word-aligned data words based upon the comparison of the at least one complete data word with the word-aligned search pattern; where the two-level memory search comprises a specified memory search address range, and further comprising: determining whether an odd number of word-aligned data words within the specified memory search address range results in a single word-aligned data word at an end of the specified memory search address range that has not been processed; reading, in response to determining that the odd number of word-aligned data words within the specified memory search address range results in the single word-aligned data word at the end of the specified memory search address range that has not been processed, a complete data word from a word-aligned address at which the single word-aligned data word is stored within the memory; comparing the complete data word with the word-aligned search pattern; and determining whether the complete data word match for the word-aligned search pattern exists within the single word-aligned data word based upon the comparison of the complete data word with the word-aligned search pattern. | 1. A method, comprising: reading, via a processor from a displaced-read memory offset address adjusted relative to word-aligned memory operations of a memory access system that utilizes word-aligned address boundaries within a memory, a split data word from the memory comprising a portion of each of two word-aligned data words stored by the memory access system within the memory using the word-aligned memory operations at two of the word-aligned address boundaries within the memory, where reading the split data word from the displaced-read memory offset address comprises a first level of a two-level memory search; comparing the portions of each of the two word-aligned data words within the split data word with corresponding portions of a word-aligned search pattern; determining that a potential complete match for the word-aligned search pattern exists within at least one of the two word-aligned data words based upon an identified match of at least one of the portions of the two word-aligned data words within the split data word with a corresponding at least one portion of the word-aligned search pattern; iterating processing of the first level of the two-level memory search through the memory; performing a second level of the two-level memory search in response to each determined potential complete match for the word-aligned search pattern, comprising: reading, in response to determining that the potential complete match for the word-aligned search pattern exists within the at least one of the two word-aligned data words, at least one complete data word from a word-aligned address boundary at which the at least one of the two word-aligned data words is stored within the memory, where reading the at least one complete data word from the word-aligned address boundary at which the at least one of the two word-aligned data words is stored within the memory comprises the second level of the two-level memory search of the two word-aligned data words: comparing the at least one complete data word with the word-aligned search pattern; and determining whether a complete data word match for the word-aligned search pattern exists within the at least one of the two word-aligned data words based upon the comparison of the at least one complete data word with the word-aligned search pattern; where the two-level memory search comprises a specified memory search address range, and further comprising: determining whether an odd number of word-aligned data words within the specified memory search address range results in a single word-aligned data word at an end of the specified memory search address range that has not been processed; reading, in response to determining that the odd number of word-aligned data words within the specified memory search address range results in the single word-aligned data word at the end of the specified memory search address range that has not been processed, a complete data word from a word-aligned address at which the single word-aligned data word is stored within the memory; comparing the complete data word with the word-aligned search pattern; and determining whether the complete data word match for the word-aligned search pattern exists within the single word-aligned data word based upon the comparison of the complete data word with the word-aligned search pattern. 2. The method of claim 1 , further comprising logging all positive determinations of complete data word matches. | 0.965102 |
7. The control device according to claim 1 , wherein the question selector calculates data indicative of user reply simplicity to each question and selects the question corresponding to the control content that maximizes a sum of the data indicative of the degree of comfort and the data indicative of the reply simplicity. | 7. The control device according to claim 1 , wherein the question selector calculates data indicative of user reply simplicity to each question and selects the question corresponding to the control content that maximizes a sum of the data indicative of the degree of comfort and the data indicative of the reply simplicity. 9. The control device according to claim 7 , wherein the data indicative of the reply simplicity is calculated based on the dialog model. | 0.943853 |
27. A method for media-independent advertisement management by a host company over a network, comprising: a. forming an inventory based information network having at least two tiers of access with at least one host server and at least one remote company user I/O device; b. configuring the at least one host server with an interactive system for generating and managing advertisement inventory listings; c. configuring the at least one host server to manage remote company user access to the advertising inventory listings; and d. enabling remote access to the at least one host server for the remote company user to create and manage advertising inventory listings. | 27. A method for media-independent advertisement management by a host company over a network, comprising: a. forming an inventory based information network having at least two tiers of access with at least one host server and at least one remote company user I/O device; b. configuring the at least one host server with an interactive system for generating and managing advertisement inventory listings; c. configuring the at least one host server to manage remote company user access to the advertising inventory listings; and d. enabling remote access to the at least one host server for the remote company user to create and manage advertising inventory listings. 40. The method of claim 27 , wherein: a. the interactive advertisement inventory item builder comprises b. creating a new advertisement inventory item; c. generating a unique listing code and associating the unique listing code with the advertisement inventory item; d. adding at least one photo file associated with the new advertisement inventory item; and e. adding text data associated with the new advertisement inventory item. | 0.524332 |
1. A method of designing an integrated circuit employing a hierarchical design flow, comprising: (a) creating a functional circuit for a functional block of an IC design; (b) verifying said functional circuit satisfies a rule-set for said IC design, wherein said rule-set is context-based with respect to said hierarchical design flow; (c) synthesizing a logical circuit based on said functional circuit; (d) verifying said logical circuit satisfies said rule-set; (e) implementing a physical layout of said logical circuit; and (f) verifying said physical layout satisfies said rule-set, wherein each step of said method is carried out by at least one EDA tool. | 1. A method of designing an integrated circuit employing a hierarchical design flow, comprising: (a) creating a functional circuit for a functional block of an IC design; (b) verifying said functional circuit satisfies a rule-set for said IC design, wherein said rule-set is context-based with respect to said hierarchical design flow; (c) synthesizing a logical circuit based on said functional circuit; (d) verifying said logical circuit satisfies said rule-set; (e) implementing a physical layout of said logical circuit; and (f) verifying said physical layout satisfies said rule-set, wherein each step of said method is carried out by at least one EDA tool. 2. The method as recited in claim 1 wherein said steps a-f are performed for multiple functional blocks of said IC design. | 0.537011 |
1. A computer-based method for processing one or more citations within a document, the method comprising: identifying in an electronic document an unformatted citation; parsing the identified unformatted citation and determining one or more citation terms; querying one or more citation libraries to find possible matching citations, each possible matching citation comprising at least a portion of the one or more citation terms; presenting for selecting a set of possible matching citations; and inserting a formatted citation based on a selected one of the set of possible matching citations into the document. | 1. A computer-based method for processing one or more citations within a document, the method comprising: identifying in an electronic document an unformatted citation; parsing the identified unformatted citation and determining one or more citation terms; querying one or more citation libraries to find possible matching citations, each possible matching citation comprising at least a portion of the one or more citation terms; presenting for selecting a set of possible matching citations; and inserting a formatted citation based on a selected one of the set of possible matching citations into the document. 2. The method of claim 1 , further comprising: providing a hyperlink between an in-text citation within the document and a corresponding citation in a bibliography of citations. | 0.686237 |
5. The method as recited in claim 1 , wherein generating the one or more annotated alternative versions of the input annotated phrase includes applying one or more transformation rules to nodes of the syntactic tree. | 5. The method as recited in claim 1 , wherein generating the one or more annotated alternative versions of the input annotated phrase includes applying one or more transformation rules to nodes of the syntactic tree. 6. The method as recited in claim 5 , wherein applying one or more transformation rules to nodes of the syntactic tree includes reordering expressions of the input annotated phrase within an alternative version of the one or more annotated alternative versions generated, the expressions associated with nodes of the syntactic tree generated. | 0.802281 |
9. A system for facilitating a real-time virtual interaction between two or more users, comprising: a memory; and at least one processor coupled to said memory and operative to: extract a dynamically changing context from two or more users, wherein the context comprises at least one of user-provided information and one or more items related to at least one of current activity and past activity of the two or more users; analyze the context from each user to create a distinct classification for each user; compare the distinct classification for each user with a distinct classification for each additional user, wherein comparing comprises ordering each user in terms of closeness to each additional user; and use the ordering of each user in terms of closeness to each additional user to facilitate a real-time virtual interaction between two or more users. | 9. A system for facilitating a real-time virtual interaction between two or more users, comprising: a memory; and at least one processor coupled to said memory and operative to: extract a dynamically changing context from two or more users, wherein the context comprises at least one of user-provided information and one or more items related to at least one of current activity and past activity of the two or more users; analyze the context from each user to create a distinct classification for each user; compare the distinct classification for each user with a distinct classification for each additional user, wherein comparing comprises ordering each user in terms of closeness to each additional user; and use the ordering of each user in terms of closeness to each additional user to facilitate a real-time virtual interaction between two or more users. 13. The system of claim 9 , wherein the at least one processor coupled to said memory operative to extract context is further operative to: parse a document object model (DOM) for the current user activity; use the parsed DOM to obtain one or more words of text from the activity; remove each word that conveys no context information; remove each set of equivalent words; compute a count of one or more unique words from the activity; and compute a content vector and normalized term-frequency vector of one or more frequently occurring terms. | 0.716961 |
13. A system for transmitting at least one real-time customized notification alert to at least one user, the system comprising: at least one electronic communication device; a sensor network comprising one or more sensor devices; a smart public alert system communicatively coupled with the at least one electronic communication device and the sensor network through a communication network; the at least one electronic communication device further comprising a user interface unit configured for retrieving relevant alerts and updating the user profile data; the smart public alert system further comprising: at least one processor electronically coupled with a memory, the memory comprising a plurality of modules executed by the at least one processor, the modules comprising: a profile database storing profile data related to plurality of users, wherein the profile data comprises user specific contextual information, demographic profile and a list of event types for which a notification alert in a specific format is desired; a reasoning module configured for reasoning a background knowledge module to pre-process, filter and extend a background knowledge stored in the background knowledge module to derive a refined structured background knowledge; a sensing module configured to sense at least one raw event feed from the at least one sensor device in the sensor network or the at least one electronic communication device; a monitoring module adapted to monitor the raw event feed sensed and to determine a raw event data and a raw context data from the received raw event feed, wherein the raw event feed is of at least one data format selected from a group comprising of text, image, video, audio, multimedia and combinations thereof, and wherein the raw event data is selected from a group comprising of traffic jams, robbery, flood, climate updates, traffic accident, road blockage, criminal activity, mutually affecting event among multiple users and combinations thereof; a context extractor module configured for extracting context from the electronic communication device and the monitoring module using a context mapping database storing the user specific contextual information; a knowledge converter module configured to convert the raw event data and the raw context data into a structured knowledge format; loading a combined structured knowledge comprising the refined structured background knowledge, the structured raw event data and the structured raw context data into a stream reasoning module; applying stream reasoning by querying the combined structured knowledge to determine if the sensed raw event feed is relevant to the profile data and the user-specific contextual information for the user; an application program module configured for processing alerts output from the stream reasoning module, transmitting the alerts to the electronic communication device and registering rules and queries received through the user interface unit to obtain the relevant alerts; and the stream reasoning module in response to the queries and rules registered adapted to stream reasoned the refined structured background knowledge, the structured raw event data and the structured raw context data to determine if the raw event feed is relevant to the profile data and the user-specific contextual information of the user and accordingly transmit the notification alert to the user interface unit through the application program module if the raw event feed is determined as relevant. | 13. A system for transmitting at least one real-time customized notification alert to at least one user, the system comprising: at least one electronic communication device; a sensor network comprising one or more sensor devices; a smart public alert system communicatively coupled with the at least one electronic communication device and the sensor network through a communication network; the at least one electronic communication device further comprising a user interface unit configured for retrieving relevant alerts and updating the user profile data; the smart public alert system further comprising: at least one processor electronically coupled with a memory, the memory comprising a plurality of modules executed by the at least one processor, the modules comprising: a profile database storing profile data related to plurality of users, wherein the profile data comprises user specific contextual information, demographic profile and a list of event types for which a notification alert in a specific format is desired; a reasoning module configured for reasoning a background knowledge module to pre-process, filter and extend a background knowledge stored in the background knowledge module to derive a refined structured background knowledge; a sensing module configured to sense at least one raw event feed from the at least one sensor device in the sensor network or the at least one electronic communication device; a monitoring module adapted to monitor the raw event feed sensed and to determine a raw event data and a raw context data from the received raw event feed, wherein the raw event feed is of at least one data format selected from a group comprising of text, image, video, audio, multimedia and combinations thereof, and wherein the raw event data is selected from a group comprising of traffic jams, robbery, flood, climate updates, traffic accident, road blockage, criminal activity, mutually affecting event among multiple users and combinations thereof; a context extractor module configured for extracting context from the electronic communication device and the monitoring module using a context mapping database storing the user specific contextual information; a knowledge converter module configured to convert the raw event data and the raw context data into a structured knowledge format; loading a combined structured knowledge comprising the refined structured background knowledge, the structured raw event data and the structured raw context data into a stream reasoning module; applying stream reasoning by querying the combined structured knowledge to determine if the sensed raw event feed is relevant to the profile data and the user-specific contextual information for the user; an application program module configured for processing alerts output from the stream reasoning module, transmitting the alerts to the electronic communication device and registering rules and queries received through the user interface unit to obtain the relevant alerts; and the stream reasoning module in response to the queries and rules registered adapted to stream reasoned the refined structured background knowledge, the structured raw event data and the structured raw context data to determine if the raw event feed is relevant to the profile data and the user-specific contextual information of the user and accordingly transmit the notification alert to the user interface unit through the application program module if the raw event feed is determined as relevant. 15. The system of claim 13 , wherein the application program module further comprises: a profile updater configured for updating the profile data including the user-specific contextual information and the demographic profile mined through the profile database; a query listener adapted to monitor query results coming from the stream reasoning module; an alert processor adapted to transmit the notification alert generated based on processing of results of query execution and an alert translator configured for translating the generated notification alert in to user-specified format before transmitting the alert to the electronic communication device. | 0.5 |
12. A computer-implemented method for operation of a mixed media reality brokerage network, the method comprising: identifying electronic data from a customer; associating and optimizing the identified electronic data with a hot spot; securing a hot spot license; transferring a revenue model and content to a service bureau; interacting with users via service bureau; and collecting and distributing revenue generated by the interacting. | 12. A computer-implemented method for operation of a mixed media reality brokerage network, the method comprising: identifying electronic data from a customer; associating and optimizing the identified electronic data with a hot spot; securing a hot spot license; transferring a revenue model and content to a service bureau; interacting with users via service bureau; and collecting and distributing revenue generated by the interacting. 22. The method of claim 12 , wherein interacting with the users further comprises collecting information about whether a transaction was completed and the terms of the transaction. | 0.722506 |
3. The method of claim 2 , wherein the feature score is computed by determining a count of words appearing in a text of the first case and a text of the first candidate answer, wherein the similarity score is based on each of: (i) the classification of the first case and the classification of the second case, and (ii) a context of the first case and a context of the second case. | 3. The method of claim 2 , wherein the feature score is computed by determining a count of words appearing in a text of the first case and a text of the first candidate answer, wherein the similarity score is based on each of: (i) the classification of the first case and the classification of the second case, and (ii) a context of the first case and a context of the second case. 4. The method of claim 3 , wherein the first case and the second case are further classified based on each of: (i) metadata describing an attribute of a user presenting the respective case to the question answering system, (ii) a content of a question in the respective case, and (iii) a type of the question in the respective case, wherein the metadata is received with the first case. | 0.929688 |
1. A text-to-speech synthesis apparatus comprising: storage means for storing phoneme data of a plurality of speaker voices; selecting means for selecting at least two speaker voices from said plurality of speaker voices; searching means for searching said storage means for phoneme data of the speaker voices selected by said selecting means; and text-to-speech synthesis processing means for linking said phoneme data of said speaker voices retrieved by said searching means to convert input data into a synthetic speech; wherein said text-to-speech synthesis processing means can convert said input data into a synthetic speech including at least two speaker voices. | 1. A text-to-speech synthesis apparatus comprising: storage means for storing phoneme data of a plurality of speaker voices; selecting means for selecting at least two speaker voices from said plurality of speaker voices; searching means for searching said storage means for phoneme data of the speaker voices selected by said selecting means; and text-to-speech synthesis processing means for linking said phoneme data of said speaker voices retrieved by said searching means to convert input data into a synthetic speech; wherein said text-to-speech synthesis processing means can convert said input data into a synthetic speech including at least two speaker voices. 8. The text-to-speech synthesis apparatus according to claim 1 , further comprising input means for directly inputting said input data. | 0.829023 |
10. A method of organising and storing documents in a computer system for subsequent retrieval, the documents having associated metadata terms, the method comprising: providing access to a store of existing metadata in the computer system; analysing the existing metadata to generate statistical data as to co-occurrence of pairs of terms in the metadata of a single document; analysing a fresh document to assign to the fresh document a set of terms and determine for each term of the set a measure of a strength of association of the term with the document; determining for each term of the set a score that is a monotonically increasing function of (a) the strength of association with the document and of (b) a relative frequency of co-ocurrence, in the existing metadata, of the term and another term that occurs in the set; and selecting, as metadata for the fresh document, a subset of the terms in the set having highest scores. | 10. A method of organising and storing documents in a computer system for subsequent retrieval, the documents having associated metadata terms, the method comprising: providing access to a store of existing metadata in the computer system; analysing the existing metadata to generate statistical data as to co-occurrence of pairs of terms in the metadata of a single document; analysing a fresh document to assign to the fresh document a set of terms and determine for each term of the set a measure of a strength of association of the term with the document; determining for each term of the set a score that is a monotonically increasing function of (a) the strength of association with the document and of (b) a relative frequency of co-ocurrence, in the existing metadata, of the term and another term that occurs in the set; and selecting, as metadata for the fresh document, a subset of the terms in the set having highest scores. 15. The method according to claim 10 , in which the score for a term is proportional to the strength of association. | 0.626634 |
14. A system comprising: at least one processor and at least one memory device; a network interface device; a page description language document, stored in the at least one memory device, the page description language document including one or more files packaged therein, wherein when packaged in the page description language document, the one or more files are compressed in a compressed archive interleaved within the page description language document, and wherein the page description language is Portable Document Format; a page description language reader application in the at least one memory device, the page description language reader application executable by the at least one processor to: identify platform, application, and web services capable of opening each of the one or more files packaged in the page description language document; receive, within a first user interface of the page description language reader application, a command to open a selected file of the files packaged within the page description language document; and issue a command, via the network interface device, to a web service identified as capable of converting the selected file from a first format to a second format compatible for opening, within a second user interface of the page description language reader application, the selected file with a reference to a location from which the platform or application service is to open the selected file from. | 14. A system comprising: at least one processor and at least one memory device; a network interface device; a page description language document, stored in the at least one memory device, the page description language document including one or more files packaged therein, wherein when packaged in the page description language document, the one or more files are compressed in a compressed archive interleaved within the page description language document, and wherein the page description language is Portable Document Format; a page description language reader application in the at least one memory device, the page description language reader application executable by the at least one processor to: identify platform, application, and web services capable of opening each of the one or more files packaged in the page description language document; receive, within a first user interface of the page description language reader application, a command to open a selected file of the files packaged within the page description language document; and issue a command, via the network interface device, to a web service identified as capable of converting the selected file from a first format to a second format compatible for opening, within a second user interface of the page description language reader application, the selected file with a reference to a location from which the platform or application service is to open the selected file from. 17. The system of claim 14 , wherein when the one or more files are compressed, the compression performed by the page description language reader application. | 0.571262 |
8. A mobile device providing HyperText Markup Language (HTML) directed adaptive features for a mobile application, the mobile device comprising: a memory including a mobile application, the mobile application including a local file manifest and a native binary; a processor configured to: downloading the mobile application from an application marketplace, the mobile application including a local file manifest and a native binary including all of executable binary code of the mobile application; execute the native binary of the mobile application, the native binary implementing a plurality of Uniform Resource Locator (URL) handlers each registered to a function of the mobile application; determine the local file manifest of the mobile application needs to be updated, the local file manifest referencing a HTML document including a plurality of URLs associated with a subset of the plurality of URL handlers; update the local file manifest of the mobile application from a remote server without updating any of the executable binary code of the mobile application, the updating modifying the plurality of URLs in the HTML document; render the HTML document from the updated local file manifest on a display. | 8. A mobile device providing HyperText Markup Language (HTML) directed adaptive features for a mobile application, the mobile device comprising: a memory including a mobile application, the mobile application including a local file manifest and a native binary; a processor configured to: downloading the mobile application from an application marketplace, the mobile application including a local file manifest and a native binary including all of executable binary code of the mobile application; execute the native binary of the mobile application, the native binary implementing a plurality of Uniform Resource Locator (URL) handlers each registered to a function of the mobile application; determine the local file manifest of the mobile application needs to be updated, the local file manifest referencing a HTML document including a plurality of URLs associated with a subset of the plurality of URL handlers; update the local file manifest of the mobile application from a remote server without updating any of the executable binary code of the mobile application, the updating modifying the plurality of URLs in the HTML document; render the HTML document from the updated local file manifest on a display. 13. The mobile device of claim 8 , the processor further configured to: store a remote asset referenced by the local file manifest as a local asset, the remote asset retrieved from the remote server. | 0.665049 |
5. A computer program product stored in a computer readable storage medium, comprising computer program code that, when executed by an information handling system, causes the information handling system to perform actions comprising: correlating a first document to a first set of domain discernible attributes selected from a plurality of sets of domain discernible attributes, wherein the first set of domain discernible attributes corresponds to a first domain corpus subset selected from a plurality of domain corpus subsets; including the first document in the first domain corpus subset in response to the correlating; in response to determining that each of a plurality of second documents do not correlate to any of the plurality of sets of domain discernible attributes, analyzing the plurality of second documents as a cluster of documents, wherein the analyzing results in a set of cluster attributes corresponding to the plurality of second documents; correlating the set of cluster attributes with a second set of domain discernible attributes selected from the plurality of sets of domain discernible attributes, wherein the second set of domain discernible attributes corresponds to a second domain corpus subset selected from the plurality of domain corpus subsets; including the plurality of second documents in the second domain corpus subset; and utilizing at least one of the plurality of domain corpus subsets in a question-answer system to process an input question. | 5. A computer program product stored in a computer readable storage medium, comprising computer program code that, when executed by an information handling system, causes the information handling system to perform actions comprising: correlating a first document to a first set of domain discernible attributes selected from a plurality of sets of domain discernible attributes, wherein the first set of domain discernible attributes corresponds to a first domain corpus subset selected from a plurality of domain corpus subsets; including the first document in the first domain corpus subset in response to the correlating; in response to determining that each of a plurality of second documents do not correlate to any of the plurality of sets of domain discernible attributes, analyzing the plurality of second documents as a cluster of documents, wherein the analyzing results in a set of cluster attributes corresponding to the plurality of second documents; correlating the set of cluster attributes with a second set of domain discernible attributes selected from the plurality of sets of domain discernible attributes, wherein the second set of domain discernible attributes corresponds to a second domain corpus subset selected from the plurality of domain corpus subsets; including the plurality of second documents in the second domain corpus subset; and utilizing at least one of the plurality of domain corpus subsets in a question-answer system to process an input question. 7. The computer program product of claim 5 wherein the computer program code, when executed by an information handling system, causes the information handling system to perform further actions comprising: parsing the document into a plurality of document attributes; matching one or more of the plurality of document attributes to one or more domain discernible attributes included in the first set of domain discernible attributes; computing a correlation value based upon one or more attribute correlation values corresponding to the matched domain discernible attributes; and determining that the computed correlation value reaches a domain correlation threshold corresponding to the first domain corpus subset. | 0.5 |
19. An article comprising: a non-transitory storage medium comprising processor-readable instructions stored thereon which are executable by a special purpose computing apparatus to: determine a response completion model (RCM) via a linear combination of a generic response language model (LM) and a stimulus model with a mixing parameter for a mixing model, the mixing model to be based, at least in part, on a topic probability, the topic probability to be assigned a value to be based, at least in part, on a likelihood that a candidate topic is to be associated with a received stimulus message; receive a stimulus message (SM); if an incomplete response message is to include at least one preceding word, to determine at least one candidate next word for the incomplete response message to be based, at least in part, on the RCM, the SM, and the at least one preceding word, and to be based, at least in part, on estimated word frequencies in stimulus messages from a plurality of stimulus-response message pairs; select at least one word from the at least one determined candidate next word; include the selected at least one word within the incomplete response message; and generate a complete response message to be based, at least in part on the incomplete response message to include the selected at least one word. | 19. An article comprising: a non-transitory storage medium comprising processor-readable instructions stored thereon which are executable by a special purpose computing apparatus to: determine a response completion model (RCM) via a linear combination of a generic response language model (LM) and a stimulus model with a mixing parameter for a mixing model, the mixing model to be based, at least in part, on a topic probability, the topic probability to be assigned a value to be based, at least in part, on a likelihood that a candidate topic is to be associated with a received stimulus message; receive a stimulus message (SM); if an incomplete response message is to include at least one preceding word, to determine at least one candidate next word for the incomplete response message to be based, at least in part, on the RCM, the SM, and the at least one preceding word, and to be based, at least in part, on estimated word frequencies in stimulus messages from a plurality of stimulus-response message pairs; select at least one word from the at least one determined candidate next word; include the selected at least one word within the incomplete response message; and generate a complete response message to be based, at least in part on the incomplete response message to include the selected at least one word. 23. The article of claim 19 , wherein the non-transitory storage medium additionally comprises processor-readable instructions stored thereon which are executable by the special purpose computing apparatus to: determine the topic model to be based, at least in part on received stimulus-response parameters; determine the mixing parameter to be based, at least in part, on the determined topic model; and determine the RCM to be based, at least in part, on the determined topic model, LM, and the mixing parameter. | 0.748821 |
1. A system for an enterprise having multiple business units to communicate with a user over multiple channels, the system comprising: channel interfaces respectively coupled to the multiple channels; a knowledge management system coupled to the channel interfaces, the knowledge management system comprising: an offer database, the offer database storing potential offers to the user, the potential offers being supplied from the multiple business units within the enterprise; a user profile database, the user profile database storing a user profile with respect to the user; and a decision engine coupled to the offer database and the user profile database, the decision engine implementing computer processing components for making a decision as to which of the potential offers to present to the user and which of the multiple channels over which to make the presentation. | 1. A system for an enterprise having multiple business units to communicate with a user over multiple channels, the system comprising: channel interfaces respectively coupled to the multiple channels; a knowledge management system coupled to the channel interfaces, the knowledge management system comprising: an offer database, the offer database storing potential offers to the user, the potential offers being supplied from the multiple business units within the enterprise; a user profile database, the user profile database storing a user profile with respect to the user; and a decision engine coupled to the offer database and the user profile database, the decision engine implementing computer processing components for making a decision as to which of the potential offers to present to the user and which of the multiple channels over which to make the presentation. 24. The system of claim 1 , further comprising a personalization engine, wherein the personalization engine personalizes information presented to the user by at least one of click stream analysis from a user communication device, collaborative filtering based on past and/or present interaction, explicit information provided by one of the user and another input device, rules based on interaction with the user and explicit information and events including transactional and service related events. | 0.5 |
7. At least one computer readable medium encoded with instructions that, when executed on a computer system, perform a method for automatically generating text, the method comprising acts of: accessing human-language text automatically generated using at least one template that includes at least some fixed text and at least one tag that serves as a placeholder to be filled in with automatically generated text; identifying instances of at least one portion of the human-language text appearing multiple times in the human language text; and automatically generating output text in a human-readable language at least in part by substituting one or more synonyms of the at least one portion for one or more of the identified instances of the at least one portion in the human-language text; wherein the one or more synonyms comprises a first synonym; wherein identifying instances of the at least one portion comprises identifying two instances of the at least one portion that appear in close proximity to each other in the human-language text; wherein substituting the one or more synonyms comprises substituting the first synonym for one of the two identified instances of the at least one portion in the human-language text; and wherein identifying the two instances of the at least one portion comprises identifying two instances that appear within a threshold number of characters or words of one another in the human-language text. | 7. At least one computer readable medium encoded with instructions that, when executed on a computer system, perform a method for automatically generating text, the method comprising acts of: accessing human-language text automatically generated using at least one template that includes at least some fixed text and at least one tag that serves as a placeholder to be filled in with automatically generated text; identifying instances of at least one portion of the human-language text appearing multiple times in the human language text; and automatically generating output text in a human-readable language at least in part by substituting one or more synonyms of the at least one portion for one or more of the identified instances of the at least one portion in the human-language text; wherein the one or more synonyms comprises a first synonym; wherein identifying instances of the at least one portion comprises identifying two instances of the at least one portion that appear in close proximity to each other in the human-language text; wherein substituting the one or more synonyms comprises substituting the first synonym for one of the two identified instances of the at least one portion in the human-language text; and wherein identifying the two instances of the at least one portion comprises identifying two instances that appear within a threshold number of characters or words of one another in the human-language text. 10. The at least one computer readable medium of claim 7 , wherein identifying the two instances of the at least one portion comprises identifying two instances in a same sentence or paragraph of the human-language text. | 0.529183 |
7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment. | 7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment. 17. The method of claim 7 , wherein the collective qualitative analysis is based on a plurality of different categories of interactions for the impressions in the subset. | 0.949137 |
8. The method of claim 6 , further comprising: the computer-implemented tool automatically analyzing the first network resource to identify the one or more keywords. | 8. The method of claim 6 , further comprising: the computer-implemented tool automatically analyzing the first network resource to identify the one or more keywords. 17. One or more non-transitory storage media storing instructions which, when executed by one or more processors cause performance of the method recited in claim 8 . | 0.941511 |
22. A system comprising: a memory and a processor; a search index construction unit stored in the memory and executable by the processor, for receiving, via a network, data relating to at least one input document associated with a new item available for purchase, and for generating search index information for the at least one input document, the data received including a threshold parameter indicating a predetermined threshold similarity of subject matter, wherein a structure of the at least one input document includes at least two fields, the at least two fields each containing content, and the predetermined threshold similarity of subject matter exists at least when a percentage of fields in the structure of the at least one input document correspond to fields in a structure of at least one existing document; and a synonym recognition unit stored in the memory and executable by the processor, in communication with the search index construction unit for: receiving the data relating to the at least one input document, comparing a subject matter of the data relating to the at least one input document to a subject matter of at least further data received from the at least one existing document that relates to an item available for purchase, determining, based at least on the comparison, that the at least one input document and the at least one existing document meet the predetermined threshold similarity of subject matter; responsive to determining that the at least one input document and the at least one existing document meet the predetermined threshold similarity of subject matter, comparing words in the at least one input document to words in the at least one existing document; and designating any dissimilar words or phrases between the at least one input document and the at least one existing document as candidate synonyms; and the search index construction unit being further configured to: merge the candidate synonyms into a search index file, wherein the merging associates the dissimilar words or phrases as synonyms in the search index file, and index the at least one input document into the search index file. | 22. A system comprising: a memory and a processor; a search index construction unit stored in the memory and executable by the processor, for receiving, via a network, data relating to at least one input document associated with a new item available for purchase, and for generating search index information for the at least one input document, the data received including a threshold parameter indicating a predetermined threshold similarity of subject matter, wherein a structure of the at least one input document includes at least two fields, the at least two fields each containing content, and the predetermined threshold similarity of subject matter exists at least when a percentage of fields in the structure of the at least one input document correspond to fields in a structure of at least one existing document; and a synonym recognition unit stored in the memory and executable by the processor, in communication with the search index construction unit for: receiving the data relating to the at least one input document, comparing a subject matter of the data relating to the at least one input document to a subject matter of at least further data received from the at least one existing document that relates to an item available for purchase, determining, based at least on the comparison, that the at least one input document and the at least one existing document meet the predetermined threshold similarity of subject matter; responsive to determining that the at least one input document and the at least one existing document meet the predetermined threshold similarity of subject matter, comparing words in the at least one input document to words in the at least one existing document; and designating any dissimilar words or phrases between the at least one input document and the at least one existing document as candidate synonyms; and the search index construction unit being further configured to: merge the candidate synonyms into a search index file, wherein the merging associates the dissimilar words or phrases as synonyms in the search index file, and index the at least one input document into the search index file. 24. The system of claim 22 , wherein the search index construction unit is for receiving data relating to an input document that is accessible through a network resource. | 0.573722 |
20. The information retrieval system according to claim 16 , further comprising: a buffer unit for holding a speech recognition result obtained by said speech recognition unit; and a feature selection unit for selecting a speech recognition result from said buffer unit according to a prescribed feature selection rule, to be inputted to said degree of similarity computation unit; wherein said degree of similarity computation unit uses a speech recognition result selected by said feature selection unit to compute said respective degree of similarity. | 20. The information retrieval system according to claim 16 , further comprising: a buffer unit for holding a speech recognition result obtained by said speech recognition unit; and a feature selection unit for selecting a speech recognition result from said buffer unit according to a prescribed feature selection rule, to be inputted to said degree of similarity computation unit; wherein said degree of similarity computation unit uses a speech recognition result selected by said feature selection unit to compute said respective degree of similarity. 21. The information retrieval system according to claim 20 , wherein said feature selection unit or said feature vector selection unit changes said prescribed feature selection rule, based on feedback from said information selection unit. | 0.935549 |
1. An activity recognition system comprising: an activity database configured to store similarity scoring techniques for known activity graphs, each of the similarity scoring techniques being associated with activity ingestion metadata; and an activity recognition device coupled with the activity database and configured to: generate a plurality of temporal features from a digital representation of an observed activity using a feature detection algorithm; establish an observed activity graph comprising one or more clusters of temporal features generated from the digital representation, wherein each one of the one or more clusters of temporal features defines a node of the observed activity graph; select at least one contextually relevant scoring technique from the similarity scoring techniques for known activity graphs, the at least one contextually relevant scoring technique being associated with activity ingestion metadata that satisfies device context criteria defined based on device contextual attributes of the digital representation; and calculate a similarity activity score for the observed activity graph as a function of the at least one contextually relevant scoring technique, the similarity activity score being relative to at least one known activity graph. | 1. An activity recognition system comprising: an activity database configured to store similarity scoring techniques for known activity graphs, each of the similarity scoring techniques being associated with activity ingestion metadata; and an activity recognition device coupled with the activity database and configured to: generate a plurality of temporal features from a digital representation of an observed activity using a feature detection algorithm; establish an observed activity graph comprising one or more clusters of temporal features generated from the digital representation, wherein each one of the one or more clusters of temporal features defines a node of the observed activity graph; select at least one contextually relevant scoring technique from the similarity scoring techniques for known activity graphs, the at least one contextually relevant scoring technique being associated with activity ingestion metadata that satisfies device context criteria defined based on device contextual attributes of the digital representation; and calculate a similarity activity score for the observed activity graph as a function of the at least one contextually relevant scoring technique, the similarity activity score being relative to at least one known activity graph. 22. The system of claim 1 , wherein the activity recognition device is further configured to establish a mapping of a static image from the digital representation into a graph space of at least one of the known activity graphs by mapping image features to nodes of the at least one of the known activity graphs. | 0.592834 |
1. A method for use with a first classification model that classifies an input into one of a plurality of classes, wherein the first classification model was built using labeled training data, wherein the labeled training data comprises a plurality of items of labeled training data, wherein each of the plurality of items of labeled training data is labeled with one of the plurality of classes, the method comprising acts of: obtaining unlabeled input for the first classification model; building a similarity model that represents similarities between the unlabeled input and the labeled training data; and using a programmed processor and the similarity model to evaluate the labeled training data to identify a subset of the plurality of items of labeled training data that is more similar to the unlabeled input than a remainder of the labeled training data. | 1. A method for use with a first classification model that classifies an input into one of a plurality of classes, wherein the first classification model was built using labeled training data, wherein the labeled training data comprises a plurality of items of labeled training data, wherein each of the plurality of items of labeled training data is labeled with one of the plurality of classes, the method comprising acts of: obtaining unlabeled input for the first classification model; building a similarity model that represents similarities between the unlabeled input and the labeled training data; and using a programmed processor and the similarity model to evaluate the labeled training data to identify a subset of the plurality of items of labeled training data that is more similar to the unlabeled input than a remainder of the labeled training data. 3. The method of claim 1 , wherein using the programmed processor and the similarity model to evaluate the labeled training data further comprises: using the similarity model to perform a transformation of a feature space of the labeled training data to create transformed labeled training data; and processing the transformed labeled training data using the first classification model. | 0.65035 |
1. A computer-implemented method comprising: accessing in memory a set of events, each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data; receiving data indicating selection of a first event from among a first plurality of events and data indicating a selection of one or more portions of text within the raw data of the first event to be extracted as one or more fields; automatically determining an initial extraction rule that extracts the selected portions of text within the first event; causing display of a first interface providing tools that implement user modification of the extraction rule, including selecting a field from the one or more fields and: selecting one or more non-adjoining strings to concatenate with the selected field; selecting a portion of the selected field to be trimmed from the beginning or end of the selected field; or selecting sub-portions of text to extract from within the selected field. | 1. A computer-implemented method comprising: accessing in memory a set of events, each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data; receiving data indicating selection of a first event from among a first plurality of events and data indicating a selection of one or more portions of text within the raw data of the first event to be extracted as one or more fields; automatically determining an initial extraction rule that extracts the selected portions of text within the first event; causing display of a first interface providing tools that implement user modification of the extraction rule, including selecting a field from the one or more fields and: selecting one or more non-adjoining strings to concatenate with the selected field; selecting a portion of the selected field to be trimmed from the beginning or end of the selected field; or selecting sub-portions of text to extract from within the selected field. 6. The method of claim 1 , further including: causing display of a second user interface providing tools that implement user selection of only events that match the field extraction rule the field extraction rule; receiving further data indicating a selection of only the events that match; and sampling according to the match selection; and causing display of a third user interface including the plurality of events according to the match selection, wherein the annotated version indicates the portions of text within the plurality of events extracted by the initial extraction rule. | 0.674444 |
1. A method for time aligned identification of video content playing on an electronic client device, the method comprising: receiving by the electronic client device, a video stream for presentation by the electronic client device, the video stream containing a first video content followed by a second video content; generating by the electronic client device, a first set of signatures for the first video content; identifying by the electronic client device, the first video content based on an analysis of the first set of signatures compared to reference signatures stored in a database; detecting by the electronic client device, a scale ratio mapping between video frames of the identified first video content playing on the electronic client device and reference frames stored in the database by calculating a scale ratio along an x axis (Sx) and a difference scale ratio along a y axis (Sy) for a query signature in the first set of signatures and a reliable matching reference signature in the database, wherein the calculated scale ratios Sx and Sy indicate that the video frames of the identified first video content and the reference frames are not in alignment; responsive to calculating the scale ratios, using the detected scale ratio mapping to generate subsequent signatures for subsequent incoming video frames; and monitoring the subsequent incoming video frames for the second video content by the electronic client device to determine that the video stream has made a scene change from the first video content to the second video content. | 1. A method for time aligned identification of video content playing on an electronic client device, the method comprising: receiving by the electronic client device, a video stream for presentation by the electronic client device, the video stream containing a first video content followed by a second video content; generating by the electronic client device, a first set of signatures for the first video content; identifying by the electronic client device, the first video content based on an analysis of the first set of signatures compared to reference signatures stored in a database; detecting by the electronic client device, a scale ratio mapping between video frames of the identified first video content playing on the electronic client device and reference frames stored in the database by calculating a scale ratio along an x axis (Sx) and a difference scale ratio along a y axis (Sy) for a query signature in the first set of signatures and a reliable matching reference signature in the database, wherein the calculated scale ratios Sx and Sy indicate that the video frames of the identified first video content and the reference frames are not in alignment; responsive to calculating the scale ratios, using the detected scale ratio mapping to generate subsequent signatures for subsequent incoming video frames; and monitoring the subsequent incoming video frames for the second video content by the electronic client device to determine that the video stream has made a scene change from the first video content to the second video content. 4. The method of claim 1 further comprising: displaying synchronous information on a selected device. | 0.59681 |
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