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AIPD_nlp_sentence_dataset

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11. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receive from the first user a text query comprising one or more character strings; identify one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identify one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generate one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges.

11. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receive from the first user a text query comprising one or more character strings; identify one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identify one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generate one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges. 16. The system of claim 11 , wherein the threshold degree of separation is one degree of separation.

10. A method for extending a voice server to add text exchange capabilities, the method comprising acts of: during an interactive dialogue between a text exchange client and a speech enabled application executing on a VoiceXML server, dynamically translating output text that is automatically generated in response to text received from the text exchange client and is grammatically part of a conversational language into corresponding text that is grammatically part of a text exchange specific language, wherein the corresponding text comprises at least one letter and/or at least one emoticon; and sending the translated output text to the text exchange client.

10. A method for extending a voice server to add text exchange capabilities, the method comprising acts of: during an interactive dialogue between a text exchange client and a speech enabled application executing on a VoiceXML server, dynamically translating output text that is automatically generated in response to text received from the text exchange client and is grammatically part of a conversational language into corresponding text that is grammatically part of a text exchange specific language, wherein the corresponding text comprises at least one letter and/or at least one emoticon; and sending the translated output text to the text exchange client. 15. The method of claim 10 , wherein the act of dynamically translating occurs in a manner transparent to the text exchange client and to the speech application.

5. An information display method for an information display apparatus comprising a display, the method comprising: displaying text in a content area on the display in response to a user selection operation, and displaying a temporarily registered character string list and a searched entry word list in another area on the display other than the content area; temporarily registering a character string which is included in the text displayed on the display in response to receiving a selection operation from the user that comprises selecting the character string in the text displayed on the display; updating the displayed temporarily registered character string list to include the temporarily registered character string selected by the user; searching an entry word corresponding to the temporarily registered character string from a dictionary in which each of a plurality of entry words is stored with corresponding explanatory information, in response to receiving a selection operation from the user that comprises selecting the temporarily registered character string in the displayed temporarily registered character string list; displaying on the display a first part of the explanatory information corresponding to the searched entry word as first explanatory information in the content area; changing the display to display a second part of the explanatory information that is different from the first explanatory information in the content area, as second explanatory information, upon receiving a user operation; registering the searched entry word in correspondence with a position of the second explanatory information of the searched entry word as a last displayed position, in accordance with receiving a user operation, and updating the displayed searched entry word list to include the searched entry word; changing the display from a state displaying the explanatory information in the content area to a state displaying the text in the content area, in accordance with receiving a user operation; and displaying, in the content area on the display, the explanatory information at the last displayed position of the second explanatory information of the registered searched entry word in response to receiving from the user an operation comprising selecting the registered searched entry word in the updated displayed searched entry word list.

5. An information display method for an information display apparatus comprising a display, the method comprising: displaying text in a content area on the display in response to a user selection operation, and displaying a temporarily registered character string list and a searched entry word list in another area on the display other than the content area; temporarily registering a character string which is included in the text displayed on the display in response to receiving a selection operation from the user that comprises selecting the character string in the text displayed on the display; updating the displayed temporarily registered character string list to include the temporarily registered character string selected by the user; searching an entry word corresponding to the temporarily registered character string from a dictionary in which each of a plurality of entry words is stored with corresponding explanatory information, in response to receiving a selection operation from the user that comprises selecting the temporarily registered character string in the displayed temporarily registered character string list; displaying on the display a first part of the explanatory information corresponding to the searched entry word as first explanatory information in the content area; changing the display to display a second part of the explanatory information that is different from the first explanatory information in the content area, as second explanatory information, upon receiving a user operation; registering the searched entry word in correspondence with a position of the second explanatory information of the searched entry word as a last displayed position, in accordance with receiving a user operation, and updating the displayed searched entry word list to include the searched entry word; changing the display from a state displaying the explanatory information in the content area to a state displaying the text in the content area, in accordance with receiving a user operation; and displaying, in the content area on the display, the explanatory information at the last displayed position of the second explanatory information of the registered searched entry word in response to receiving from the user an operation comprising selecting the registered searched entry word in the updated displayed searched entry word list. 7. The information display method of claim 5 , further comprising: displaying a text portion including the temporarily registered character string in a position in the text according to position information based on the position information of the temporarily registered character string corresponding to the selected searched entry word.

9. The CAM of claim 8 wherein the scheduler is further to: stop scheduling comparisons for dictionary words that have been determined to not match the input word.

9. The CAM of claim 8 wherein the scheduler is further to: stop scheduling comparisons for dictionary words that have been determined to not match the input word. 10. The CAM of claim 9 wherein the plurality of dictionary words divided into the plurality of banks further comprises: a match line for each bank of each dictionary word, the match line indicating the result of the comparison of the segment of the input word to the bank, wherein the match line is not pre-charged for dictionary words that have already been determined to not match the input word.

10. A computer program product for capturing and managing knowledge from social networking interactions comprising: a non-transitory computer readable storage medium, said computer readable storage medium comprising computer readable program code embodied therewith, said computer readable program code comprising program instructions that, when executed, causes a processor to: present a marking element in a social networking interaction, wherein said marking element allows a user to specify whether a corresponding message corresponds to at least one member of the group consisting of a question and an answer; receive a first user selection indicating a portion of the social network interaction as a question; receive a second user selection indicating a portion of the social networking interaction as an answer; create a knowledge element in response to a user activating said marking element in said social networking interaction; store said knowledge element in a catalog of knowledge elements; present an evaluation element for evaluating said knowledge element in said social networking interaction; present an editing element for editing said knowledge element; present knowledge element indicators to accompany the corresponding messages, which knowledge element indicators indicate whether corresponding messages correspond to at least one of the group consisting of a question and an answer; alter said knowledge element in response to a user evaluating or editing said knowledge element; and recommend said knowledge element for use in response to a user composing a message relevant to said knowledge element in said social networking interaction before said user shares said message within said social networking interaction.

10. A computer program product for capturing and managing knowledge from social networking interactions comprising: a non-transitory computer readable storage medium, said computer readable storage medium comprising computer readable program code embodied therewith, said computer readable program code comprising program instructions that, when executed, causes a processor to: present a marking element in a social networking interaction, wherein said marking element allows a user to specify whether a corresponding message corresponds to at least one member of the group consisting of a question and an answer; receive a first user selection indicating a portion of the social network interaction as a question; receive a second user selection indicating a portion of the social networking interaction as an answer; create a knowledge element in response to a user activating said marking element in said social networking interaction; store said knowledge element in a catalog of knowledge elements; present an evaluation element for evaluating said knowledge element in said social networking interaction; present an editing element for editing said knowledge element; present knowledge element indicators to accompany the corresponding messages, which knowledge element indicators indicate whether corresponding messages correspond to at least one of the group consisting of a question and an answer; alter said knowledge element in response to a user evaluating or editing said knowledge element; and recommend said knowledge element for use in response to a user composing a message relevant to said knowledge element in said social networking interaction before said user shares said message within said social networking interaction. 15. The computer program product of claim 10 , further comprising program instructions that, when executed, cause said processor to categorize the knowledge element.

1. A computer-readable medium having stored thereon a set of instructions which when executed perform a method for recommending an item to a user, the method, comprising: defining an ontology as nodes in a graph, the nodes including a scored node and an unscored node, the nodes in the graph representing concepts; wherein, the scored node has an associated score based on a preference of the user for a concept represented by the scored node; using a propagating function and the associated score of the scored node, to determine, for the user, a personalized score of the unscored node in the ontology; wherein, the propagation function determines the personalized score of the unscored node based on a relationship of the unscored node and the scored node in the graph representing the ontology; identifying, for the user, a qualifying concept from the concepts in the ontology for which the personalized scores have been computed, wherein, the qualifying concept that is identified from the concepts, is one that is associated a qualifying score among the personalized scores that have been computed for the concepts at the nodes of the ontology; and selecting the item which is an instance of the qualifying concept to be recommended to the user.

1. A computer-readable medium having stored thereon a set of instructions which when executed perform a method for recommending an item to a user, the method, comprising: defining an ontology as nodes in a graph, the nodes including a scored node and an unscored node, the nodes in the graph representing concepts; wherein, the scored node has an associated score based on a preference of the user for a concept represented by the scored node; using a propagating function and the associated score of the scored node, to determine, for the user, a personalized score of the unscored node in the ontology; wherein, the propagation function determines the personalized score of the unscored node based on a relationship of the unscored node and the scored node in the graph representing the ontology; identifying, for the user, a qualifying concept from the concepts in the ontology for which the personalized scores have been computed, wherein, the qualifying concept that is identified from the concepts, is one that is associated a qualifying score among the personalized scores that have been computed for the concepts at the nodes of the ontology; and selecting the item which is an instance of the qualifying concept to be recommended to the user. 31. The method of claim 1 further comprising, determining the preference of the user for the concept represented by the scored node using one or more user-specified ratings for instances of the concept.

1. A system for creating a personal ranking of specific to a user information, the system comprising: an interface for interfacing with online data, stored user data, and user device data; a processor executing an application to configured for analyzing information derived or inferred at least in part from the online data, the stored user data, and the user device data, wherein the analysis incorporates criteria derived or inferred from both the stored user data and the user device data; a database, the database configured for storing data relating to inputs and/or outputs of the relevance engine or the application, wherein the relevance engine is further configured for generating a series of personalised attention rankings outputs accessible by the user device by applying both a user-specific attention profile and a user-specific psychometric profile in producing machine readable, user-specific attention ranking of the online data; and further wherein the personalised attention rankings outputs are generated at least partially in response to changes in the personalised attention profile outputs or changes in the personalised the psychometric profile outputs specific to the user.

1. A system for creating a personal ranking of specific to a user information, the system comprising: an interface for interfacing with online data, stored user data, and user device data; a processor executing an application to configured for analyzing information derived or inferred at least in part from the online data, the stored user data, and the user device data, wherein the analysis incorporates criteria derived or inferred from both the stored user data and the user device data; a database, the database configured for storing data relating to inputs and/or outputs of the relevance engine or the application, wherein the relevance engine is further configured for generating a series of personalised attention rankings outputs accessible by the user device by applying both a user-specific attention profile and a user-specific psychometric profile in producing machine readable, user-specific attention ranking of the online data; and further wherein the personalised attention rankings outputs are generated at least partially in response to changes in the personalised attention profile outputs or changes in the personalised the psychometric profile outputs specific to the user. 3. The system according to claim 1 , wherein the application further comprises an ontology repository containing a list of ontologies.

1. An information repository system for managing, storing and retrieving a computer data file comprising: a content server for storing said file; content model means for defining a three-tiered content model which comprises nested tiers including component classes, physical object classes, and relations classes, and wherein a logical object contains a reference to said file and describes said file in generic terms and with reference to at least one attribute, and further wherein said logical object contains a reference to at least one physical object associated with said logical object, and contains a reference to at least one component associated with said at least one physical object, and wherein relations from said relations classes are used to connect logical objects and physical objects with other logical objects or physical objects; an administration data table which contains administration data associated with physical objects; logical hyperlink means for resolving, in context-based indirect runtime resolution, the logical object, to a physical destination of the file associated with the at least one physical object associated with the logical object; context resolution means, enabled by said logical hyperlink means, for context-based resolution of a particular physical object associated with the logical object on the basis of the context attributes of a request as determined by correlating requested context attributes against attributes of physical objects associated with the logical object and attributes of a front-end client application; and a management agent for managing said logical objects and physical objects using said content model means in conformance with said administration data and for identifying and retrieving the physical object resolved via said logical hyperlink means and said context resolution means.

1. An information repository system for managing, storing and retrieving a computer data file comprising: a content server for storing said file; content model means for defining a three-tiered content model which comprises nested tiers including component classes, physical object classes, and relations classes, and wherein a logical object contains a reference to said file and describes said file in generic terms and with reference to at least one attribute, and further wherein said logical object contains a reference to at least one physical object associated with said logical object, and contains a reference to at least one component associated with said at least one physical object, and wherein relations from said relations classes are used to connect logical objects and physical objects with other logical objects or physical objects; an administration data table which contains administration data associated with physical objects; logical hyperlink means for resolving, in context-based indirect runtime resolution, the logical object, to a physical destination of the file associated with the at least one physical object associated with the logical object; context resolution means, enabled by said logical hyperlink means, for context-based resolution of a particular physical object associated with the logical object on the basis of the context attributes of a request as determined by correlating requested context attributes against attributes of physical objects associated with the logical object and attributes of a front-end client application; and a management agent for managing said logical objects and physical objects using said content model means in conformance with said administration data and for identifying and retrieving the physical object resolved via said logical hyperlink means and said context resolution means. 20. The system of claim 1 further comprising content access means to maintain inter-physical object relations and to prevent the simultaneous editing of a physical object by multiple users.

1. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors using features learned during training; integrating verb of interest and word of interest position relative to the word to be labeled by employing a linear layer that is adapted to the input sentence; and applying linear transformations and squashing functions to the vectors to predict semantic role labels.

1. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors using features learned during training; integrating verb of interest and word of interest position relative to the word to be labeled by employing a linear layer that is adapted to the input sentence; and applying linear transformations and squashing functions to the vectors to predict semantic role labels. 8. The method as recited in claim 1 , wherein converting words into vectors includes outputting vectors of different dimensions for each word, each word of interest position and each verb position.

1. A computer-implemented system for populating clusters of documents, comprising: a presentation module to place a set of clusters in a display in relation to a common origin; a document selection module to select one of a plurality of unclustered documents in the display and to determine an angle θ of the document from the common origin; a cluster placement module to compute for each cluster, an angle σ of the cluster relative to the common origin; a placement calculation module to determine a difference between the document angle θ and one such cluster angle σ; a predetermined variance applied to the difference; and a clustering module to place the document into the cluster when the difference is less than the variance.

1. A computer-implemented system for populating clusters of documents, comprising: a presentation module to place a set of clusters in a display in relation to a common origin; a document selection module to select one of a plurality of unclustered documents in the display and to determine an angle θ of the document from the common origin; a cluster placement module to compute for each cluster, an angle σ of the cluster relative to the common origin; a placement calculation module to determine a difference between the document angle θ and one such cluster angle σ; a predetermined variance applied to the difference; and a clustering module to place the document into the cluster when the difference is less than the variance. 3. A system according to claim 1 , further comprising: a theme generator to generate the themes, comprising: a frequency determination module to determine a frequency of each term within each unclustered document; a theme mapping module to map the frequencies of the terms across all the unclustered documents; and a theme determination module to apply a predetermined range of frequencies to the mapped frequencies and to designate those terms that fall within the threshold as the themes for the unclustered documents.

13. A SQL Visualizer as claimed in claim 1 , which also allows a user to create textual SQL statements and SQL procedures from graphical SQL Rules and SQL Procedures.

13. A SQL Visualizer as claimed in claim 1 , which also allows a user to create textual SQL statements and SQL procedures from graphical SQL Rules and SQL Procedures. 14. A SQL Visualizer as claimed in claim 13 , which allows a user to switch between textual and graphical representations of the same SQL statement or SQL procedure.

13. A method of object tracking within image frames, the method comprising: using a processing system, performing a first level of association between detection responses in image frames, wherein the detection responses include a vector having position, size, and frame index components, the first level of association including forming one or more tracklets between pairs of detection responses having suitable link probabilities, wherein the first level of association produces a tracklet set, and the second level of association comprises, for each tracklet in the in the tracklet set, obtaining a motion model and an appearance model; using the processing system, receiving the one or more tracklets formed as a result of the first level of association, performing a second level of association, including producing a tracklet association between tracklets, wherein the second level of association comprises obtaining an optimal tracklet association set and a corresponding tracklet set; using the processing system, performing a third level of association, wherein performing a third level of association includes estimating a scene structure model from the second level of association; and provide as an output a trajectory set of the tracklets.

13. A method of object tracking within image frames, the method comprising: using a processing system, performing a first level of association between detection responses in image frames, wherein the detection responses include a vector having position, size, and frame index components, the first level of association including forming one or more tracklets between pairs of detection responses having suitable link probabilities, wherein the first level of association produces a tracklet set, and the second level of association comprises, for each tracklet in the in the tracklet set, obtaining a motion model and an appearance model; using the processing system, receiving the one or more tracklets formed as a result of the first level of association, performing a second level of association, including producing a tracklet association between tracklets, wherein the second level of association comprises obtaining an optimal tracklet association set and a corresponding tracklet set; using the processing system, performing a third level of association, wherein performing a third level of association includes estimating a scene structure model from the second level of association; and provide as an output a trajectory set of the tracklets. 20. The method of claim 13 , wherein for the third level of association, an entry map and an exit map are produced from the second level of association and used to specify the initialization and termination of each tracklet in an image scene, and a scene occluder map is produced from the second level of association and used to revise the link probabilities.

12. A modulus encoder according to claim 8, further comprising means for adaptively determining the value of b in response to the values of said moduli.

12. A modulus encoder according to claim 8, further comprising means for adaptively determining the value of b in response to the values of said moduli. 13. A modulus encoder according to claim 12, wherein said means for adaptively determining is configured to determine the value of b in response to the largest one of said moduli.

6. A computer program product for providing a data translation, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising: program code instructions for selecting a transform by receiving a data set comprising a plurality of input strings entered at a particular organization, processing the data set using at least two different transforms each of which defines a corresponding transform rule for transforming free text into a corresponding translated value, comparing results of the processing for each of the at least two different transforms to the rational range, discounting values in the results that are outside the rational range, and selecting, as the selected transform, one of the at least two different transforms that produced more results within the rational range than other transforms; program code instructions for receiving an input string comprising a free text response indicative of a physiologic condition, wherein the free text response is entered by personnel at the organization; and program code instructions for applying the selected transform to the input string to transform the input string into a translated value indicative of a value associated with the physiologic condition for storage in a fact repository, wherein the program code instructions for applying the selected transform comprise program code instructions for transforming an initial representation of the input string to the translated value in a standard form of representation, wherein the selected transform is selected from a library of potential transforms by applying the at least two different transforms from the library to the data set and selecting the selected transform from among the library of potential transforms based on results of the selected transform applied to the data set encountered at the respective organization relative to the rational range defined by physiologic limits associated with the physiologic condition and in comparison to results obtained by application of other transforms from the library to the data set.

6. A computer program product for providing a data translation, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising: program code instructions for selecting a transform by receiving a data set comprising a plurality of input strings entered at a particular organization, processing the data set using at least two different transforms each of which defines a corresponding transform rule for transforming free text into a corresponding translated value, comparing results of the processing for each of the at least two different transforms to the rational range, discounting values in the results that are outside the rational range, and selecting, as the selected transform, one of the at least two different transforms that produced more results within the rational range than other transforms; program code instructions for receiving an input string comprising a free text response indicative of a physiologic condition, wherein the free text response is entered by personnel at the organization; and program code instructions for applying the selected transform to the input string to transform the input string into a translated value indicative of a value associated with the physiologic condition for storage in a fact repository, wherein the program code instructions for applying the selected transform comprise program code instructions for transforming an initial representation of the input string to the translated value in a standard form of representation, wherein the selected transform is selected from a library of potential transforms by applying the at least two different transforms from the library to the data set and selecting the selected transform from among the library of potential transforms based on results of the selected transform applied to the data set encountered at the respective organization relative to the rational range defined by physiologic limits associated with the physiologic condition and in comparison to results obtained by application of other transforms from the library to the data set. 8. The computer program product of claim 6 , further comprising program code instructions for applying a different transform to a data set to compare results generated by the different transform to results generated using the selected transform to evaluate the selected transform.

1. A method of determining an annotation for a particular image, the method comprising: determining a plurality of images related to the particular image, the plurality of images stored in one or more computer systems; identifying a plurality of annotations associated with the plurality of images; generating an ontology for the particular image wherein the ontology comprises: a plurality of terms, the plurality of annotations, and the plurality of images arranged in a hierarchy with the plurality of annotations being downstream from the plurality of terms associated with a highest level of the hierarchy, and the plurality of images being downstream from the plurality of annotations, and a plurality of links defining relationships between respective terms, annotations, or images, wherein each link is associated with a respective relevance value indicating a measure of relevance between two respective terms, annotations, or images connected by a respective link; determining a total relevance value for each term associated with the highest level, wherein for each term associated with the highest level, the total relevance value is a sum of relevance values of links downstream from the term; and associating one of the plurality of terms having a highest total relevance value with the particular image as an image annotation.

1. A method of determining an annotation for a particular image, the method comprising: determining a plurality of images related to the particular image, the plurality of images stored in one or more computer systems; identifying a plurality of annotations associated with the plurality of images; generating an ontology for the particular image wherein the ontology comprises: a plurality of terms, the plurality of annotations, and the plurality of images arranged in a hierarchy with the plurality of annotations being downstream from the plurality of terms associated with a highest level of the hierarchy, and the plurality of images being downstream from the plurality of annotations, and a plurality of links defining relationships between respective terms, annotations, or images, wherein each link is associated with a respective relevance value indicating a measure of relevance between two respective terms, annotations, or images connected by a respective link; determining a total relevance value for each term associated with the highest level, wherein for each term associated with the highest level, the total relevance value is a sum of relevance values of links downstream from the term; and associating one of the plurality of terms having a highest total relevance value with the particular image as an image annotation. 3. The method of claim 1 , further comprising receiving the particular image and a request for annotation of the particular image, wherein generating an ontology for the particular image is in response to receiving the particular image and a request for annotation of the particular image.

8. A host computing device for obtaining at least one virus signature, the host computing device comprising: a plurality of computer files stored in one or more memory locations of the host computing device; and at least a processor with circuitry operating in conjunction with a memory storing codes of an anti-virus program, wherein the processor, when executing the code, is configured to: obtain at least one text string of characters sequence contained in program code lines of virus samples of a virus sample set; select a virus signatures candidate from the at least one text string of characters sequence according to a first frequency at which each of the at least one text string of characters sequence occurs in program code lines of non-virus samples of a non-virus sample set, and a second frequency at which each of the at least one text string of characters sequence occurs in the program code lines of virus samples of the virus sample set; calculate an information entropy of the virus signatures candidate, the information entropy consisting of a value calculated according to: a number of virus samples among the virus sample set containing the virus signatures candidate, a number of virus samples among the virus sample set not containing the virus signatures candidate, a number of non-virus samples among the non-virus sample set containing the virus signatures candidate, and a number of non-virus samples among the non-virus sample set not containing the virus signatures candidate; and determine whether the virus signatures candidate qualifies as a virus signature according to the calculated information entropy.

8. A host computing device for obtaining at least one virus signature, the host computing device comprising: a plurality of computer files stored in one or more memory locations of the host computing device; and at least a processor with circuitry operating in conjunction with a memory storing codes of an anti-virus program, wherein the processor, when executing the code, is configured to: obtain at least one text string of characters sequence contained in program code lines of virus samples of a virus sample set; select a virus signatures candidate from the at least one text string of characters sequence according to a first frequency at which each of the at least one text string of characters sequence occurs in program code lines of non-virus samples of a non-virus sample set, and a second frequency at which each of the at least one text string of characters sequence occurs in the program code lines of virus samples of the virus sample set; calculate an information entropy of the virus signatures candidate, the information entropy consisting of a value calculated according to: a number of virus samples among the virus sample set containing the virus signatures candidate, a number of virus samples among the virus sample set not containing the virus signatures candidate, a number of non-virus samples among the non-virus sample set containing the virus signatures candidate, and a number of non-virus samples among the non-virus sample set not containing the virus signatures candidate; and determine whether the virus signatures candidate qualifies as a virus signature according to the calculated information entropy. 12. The host computing device according to claim 8 , wherein the processor, when executing the codes to calculate the information entropy of the virus signatures candidate according to the number of virus samples containing the virus signatures candidate and the number of non-virus samples containing the virus signatures candidate, is configured to: calculate a number of virus samples among the virus sample set not containing the virus signatures candidate according to the number of virus samples containing the virus signatures candidate; calculate the number of non-virus samples among the non-virus sample set not containing the virus signatures candidate according to the number of non-virus samples containing the virus signatures candidate; and calculate the information entropy of the virus signatures candidate according to the number of virus samples containing the virus signatures candidate, the number of virus samples not containing the virus signatures candidate, the number of non-virus samples containing the virus signatures candidate, and the number of non-virus samples not containing the virus signatures candidate.

8. A non-transitory computer-readable storage medium coupled to at least one processor and having instructions stored thereon which, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving a set of words for use in monitoring network traffic, each word having at least one metric associated therewith; transmitting respective requests to a plurality of computer-implemented social networks through respective application program interfaces (APIs) over a network, the respective requests each including a set of search words, the set of search words comprising a subset of words of the set of words; receiving a set of messages comprising at least one message from each of the plurality of computer-implemented social networks, each message in the set of messages comprising a message distributed through a respective computer-implemented social network and at least one search word in the set of search words; scoring each message in the set of messages based on metrics of respective score words in a set of score words to provide respective scores, the set of score words comprising a subset of words of the set of words, and at least one score word in the set of score words being absent from the set of search words; and providing the messages for display in a rank order by score in a user interface.

8. A non-transitory computer-readable storage medium coupled to at least one processor and having instructions stored thereon which, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving a set of words for use in monitoring network traffic, each word having at least one metric associated therewith; transmitting respective requests to a plurality of computer-implemented social networks through respective application program interfaces (APIs) over a network, the respective requests each including a set of search words, the set of search words comprising a subset of words of the set of words; receiving a set of messages comprising at least one message from each of the plurality of computer-implemented social networks, each message in the set of messages comprising a message distributed through a respective computer-implemented social network and at least one search word in the set of search words; scoring each message in the set of messages based on metrics of respective score words in a set of score words to provide respective scores, the set of score words comprising a subset of words of the set of words, and at least one score word in the set of score words being absent from the set of search words; and providing the messages for display in a rank order by score in a user interface. 14. The computer-readable storage medium of claim 8 , wherein at least one word in the set of score words is also included in the set of search words.

1. A system for recommending sales activities to individual workers based on worker specific information and overall company-level sales strategy, the system comprising: one or more physical processors configured to execute computer program instructions, comprising: a strategy management component configured to: determine a first configurable strategy based on a plurality of configurable market segments, wherein the first configurable strategy is related to promoting the first product; determine a first plurality of configurable workflows related to the first configurable strategy, the first plurality of configurable workflows comprising a first configurable workflow, wherein determining the first configurable workflow comprises determining a first set of activities related to promoting a first product to a first customer and a second configurable workflow, wherein determining the second configurable workflow comprises determining a second set of activities related to promoting the first product to a second customer; determine a first configurable market segment of the plurality of market segments, wherein determining the first configurable market segment comprises: receiving information related to the first customer to be targeted by the first configurable strategy; receiving information related to the first product to be targeted by the first configurable strategy; receiving abstraction information related to one or more of: a territory, a worker type, or a company goal, wherein the company goal comprises a sales goal for the first product; and defining the first configurable market segment based on the first customer, the first product, and the abstraction information; associate the first configurable workflow with the defined first configurable market segment to target the first product to the first customer to pursue the sales goal for the first product; determine a second configurable strategy based on a second plurality of market segments different from the first plurality of market segments, wherein the second configurable strategy is related to promoting a second product; and determine a second plurality of configurable workflows related to the second configurable strategy, the second plurality of configurable workflows comprising a third configurable workflow related to promoting a second product to the first customer; a suggestion management component configured to: determine a first suggested activity for a first worker based on the first set of activities of the first configurable workflow, the second set of activities of the second configurable workflow, a first time period during which the first suggested activity is to be performed, a location associated with the first suggested activity, and a frequency of occurrence associated with the first suggested activity; and determine a second suggested activity for the first worker responsive to a determination that the first worker is associated with the third workflow, wherein the second suggested activity is determined based on the first set of activities of the first configurable workflow, the second set of activities of the second configurable workflow, a third set of activities from the third configurable workflow, a second time period during which the second suggested activity is to be performed, a second location associated with the second suggested activity, and a second frequency of occurrence associated with the second suggested activity; and an activity management component configured to: output, to the first worker, a schedule for the first time period and the first suggested activity, wherein the schedule comprises a plurality of scheduled activities associated with the first worker within the first time period; and output, to the first worker, the second suggested activity with the schedule for the first time period and the first suggested activity.

1. A system for recommending sales activities to individual workers based on worker specific information and overall company-level sales strategy, the system comprising: one or more physical processors configured to execute computer program instructions, comprising: a strategy management component configured to: determine a first configurable strategy based on a plurality of configurable market segments, wherein the first configurable strategy is related to promoting the first product; determine a first plurality of configurable workflows related to the first configurable strategy, the first plurality of configurable workflows comprising a first configurable workflow, wherein determining the first configurable workflow comprises determining a first set of activities related to promoting a first product to a first customer and a second configurable workflow, wherein determining the second configurable workflow comprises determining a second set of activities related to promoting the first product to a second customer; determine a first configurable market segment of the plurality of market segments, wherein determining the first configurable market segment comprises: receiving information related to the first customer to be targeted by the first configurable strategy; receiving information related to the first product to be targeted by the first configurable strategy; receiving abstraction information related to one or more of: a territory, a worker type, or a company goal, wherein the company goal comprises a sales goal for the first product; and defining the first configurable market segment based on the first customer, the first product, and the abstraction information; associate the first configurable workflow with the defined first configurable market segment to target the first product to the first customer to pursue the sales goal for the first product; determine a second configurable strategy based on a second plurality of market segments different from the first plurality of market segments, wherein the second configurable strategy is related to promoting a second product; and determine a second plurality of configurable workflows related to the second configurable strategy, the second plurality of configurable workflows comprising a third configurable workflow related to promoting a second product to the first customer; a suggestion management component configured to: determine a first suggested activity for a first worker based on the first set of activities of the first configurable workflow, the second set of activities of the second configurable workflow, a first time period during which the first suggested activity is to be performed, a location associated with the first suggested activity, and a frequency of occurrence associated with the first suggested activity; and determine a second suggested activity for the first worker responsive to a determination that the first worker is associated with the third workflow, wherein the second suggested activity is determined based on the first set of activities of the first configurable workflow, the second set of activities of the second configurable workflow, a third set of activities from the third configurable workflow, a second time period during which the second suggested activity is to be performed, a second location associated with the second suggested activity, and a second frequency of occurrence associated with the second suggested activity; and an activity management component configured to: output, to the first worker, a schedule for the first time period and the first suggested activity, wherein the schedule comprises a plurality of scheduled activities associated with the first worker within the first time period; and output, to the first worker, the second suggested activity with the schedule for the first time period and the first suggested activity. 9. The system of claim 1 , wherein the suggestion management component is configured to: determine, as a third suggested activity, an activity triggered by one or more of: receipt, from a second worker, of feedback related to the activity, a change in behavior of a customer of the company, or compliance with regulations related to the company, and wherein the activity management module is configured to: output, to the first worker, the third suggested activity with the schedule.

11. A method comprising: receiving from a user a search query for images from a database comprising the images and annotations describing each image, the search query comprising an annotation criterion, and a selection of a color scheme comprising a target hue bucket; conducting a search of the database to identify a set of images responsive to the annotation criterion; converting red-green-blue (RGB) data for each image in the set of images to luminance, chromaticity, and hue angle (LCH) data; associating each channel of the LCH data with a distribution measure; generating an image color spectrum histogram for each image in the set of images using the LCH data; and when a hue value of the image color spectrum histogram for an image in the set of images corresponds to a hue value of the target hue bucket of the color scheme, displaying the image to the user in response to the search query.

11. A method comprising: receiving from a user a search query for images from a database comprising the images and annotations describing each image, the search query comprising an annotation criterion, and a selection of a color scheme comprising a target hue bucket; conducting a search of the database to identify a set of images responsive to the annotation criterion; converting red-green-blue (RGB) data for each image in the set of images to luminance, chromaticity, and hue angle (LCH) data; associating each channel of the LCH data with a distribution measure; generating an image color spectrum histogram for each image in the set of images using the LCH data; and when a hue value of the image color spectrum histogram for an image in the set of images corresponds to a hue value of the target hue bucket of the color scheme, displaying the image to the user in response to the search query. 12. The method of claim 11 , wherein the annotation criterion is included in the set of annotations associated with the identified set of images.

13. The method as in claim 12 , wherein the plurality of pronunciation guessers comprise pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser.

13. The method as in claim 12 , wherein the plurality of pronunciation guessers comprise pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser. 15. The method as in claim 13 wherein the method is performed by a server that is coupled through a wireless network to the user's device which includes the contacts database and wherein the server obtains the words in the contacts database from the user's device through the wireless network and wherein the server receives the speech input from the user's device through the wireless network and wherein the server transmits the best match to the user's device through the wireless network.

2. A computer-readable medium encoded with instructions for controlling a computing device to rank web pages with hyperlinks to other web pages, by a method comprising: generating transition probabilities of transitioning between pairs of a source web page and a direct target web page based on information available through each target web page of the source web page based on information content of the target web pages; calculating importance of the web pages based on a stationary distribution of the generated transition probabilities, the stationary distribution including a stationary probability of visiting each web page; searching for web pages to be included in a search result for a search request; and ranking web pages of the search result based on the calculated importance.

2. A computer-readable medium encoded with instructions for controlling a computing device to rank web pages with hyperlinks to other web pages, by a method comprising: generating transition probabilities of transitioning between pairs of a source web page and a direct target web page based on information available through each target web page of the source web page based on information content of the target web pages; calculating importance of the web pages based on a stationary distribution of the generated transition probabilities, the stationary distribution including a stationary probability of visiting each web page; searching for web pages to be included in a search result for a search request; and ranking web pages of the search result based on the calculated importance. 15. The computer-readable medium of claim 2 wherein the calculating of importance is performed iteratively until the stationary probabilities of visiting the web pages converge on a solution.

9. A method for collecting and analyzing structured user feedback on websites, said method comprising: generating, using a computer, website user structured feedback forms for receiving website user feedback on website user interaction with a website-based process, said structured feedback forms comprising user selectable feedback messages provided in a categorized and nested structure; determining, based on a website action of a given user, that the given user intends to cancel a transaction associated with the website-based process or abandon the website-based process; upon making said determination, automatically presenting the given user with at least one of the generated website user structured feedback forms or an invitation to enter feedback using at least one of the generated website user structured feedback forms; interfacing with a web analytics service; receiving from the web analytics service web behavior analysis relating to behaviors of the multiplicity of website users; automatically collecting and analyzing, using said computer, said website user feedback entered in said structured feedback forms including factoring the received web behavior analysis in said automatic analysis; and providing, using said computer, at least one analysis report based on said website user feedback from a multiplicity of website users, said at least one analysis report comprising a structured analysis report based on said categorized and nested structure, wherein at least one analysis report includes an integration of the received web behavior analysis; and wherein said automatic analyzing includes analyzing website user feedback in relation to each of two or more stages in the website-based process separately for each stage, factoring into the stage specific analysis web behavior analysis relating to each of the two or more stages and reporting the results of the analysis in relation to the each of two or more stages separately for each stage.

9. A method for collecting and analyzing structured user feedback on websites, said method comprising: generating, using a computer, website user structured feedback forms for receiving website user feedback on website user interaction with a website-based process, said structured feedback forms comprising user selectable feedback messages provided in a categorized and nested structure; determining, based on a website action of a given user, that the given user intends to cancel a transaction associated with the website-based process or abandon the website-based process; upon making said determination, automatically presenting the given user with at least one of the generated website user structured feedback forms or an invitation to enter feedback using at least one of the generated website user structured feedback forms; interfacing with a web analytics service; receiving from the web analytics service web behavior analysis relating to behaviors of the multiplicity of website users; automatically collecting and analyzing, using said computer, said website user feedback entered in said structured feedback forms including factoring the received web behavior analysis in said automatic analysis; and providing, using said computer, at least one analysis report based on said website user feedback from a multiplicity of website users, said at least one analysis report comprising a structured analysis report based on said categorized and nested structure, wherein at least one analysis report includes an integration of the received web behavior analysis; and wherein said automatic analyzing includes analyzing website user feedback in relation to each of two or more stages in the website-based process separately for each stage, factoring into the stage specific analysis web behavior analysis relating to each of the two or more stages and reporting the results of the analysis in relation to the each of two or more stages separately for each stage. 16. The method according to claim 9 , wherein said providing at least one analysis report comprises automatically providing at least one analysis report which indicates proportions of website users who provide various pre-classified types of feedback.

1. A method comprising: receiving, at a social networking system, a template object from a third-party system external to the social networking system, the template object comprising formatting instructions for an advertisement and content instructions that when executed by a processor causes the social networking system to (1) retrieve user profile information of a user, (2) incorporate the user profile information in an advertisement generated based on the template object, and (3) specify an action to be performed by the advertiser system in response to the user selecting the advertisement; storing the received template object in a non-transitory computer readable storage medium; receiving a selection of the template object from an advertiser system external to the social networking system; receiving advertisement content from the advertiser system to generate an advertisement based on the selected template object; receiving, from a first computing device, a request for the advertisement, the first computing device being associated with a first user of the social networking system; retrieving, by the social networking system based on the content instructions, first user profile information from a first user profile of the first user to be incorporated into the advertisement by the template object; generating, using a computer processor of the social networking system, the advertisement based on the content instructions from the template object, the advertisement comprising the advertisement content and the first user profile information associated with the first user, the advertisement describing the action to the first user to be performed by the advertiser system in response to the first user selecting the advertisement; providing the advertisement for display to the first user on the first computing device; receiving, from the first computing device of the first user, a selection of the advertisement; responsive to receiving the selection, sending, to the advertiser system, a request to perform the action described to the first user in the advertisement; receiving a confirmation from the advertiser system that the action described in the advertisement has been performed, the confirmation comprising information associated with the action performed by the advertiser system; in response to receiving the confirmation, modifying the advertisement with the information associated with the action performed by the advertiser system; and providing the modified advertisement to the first computing device for display.

1. A method comprising: receiving, at a social networking system, a template object from a third-party system external to the social networking system, the template object comprising formatting instructions for an advertisement and content instructions that when executed by a processor causes the social networking system to (1) retrieve user profile information of a user, (2) incorporate the user profile information in an advertisement generated based on the template object, and (3) specify an action to be performed by the advertiser system in response to the user selecting the advertisement; storing the received template object in a non-transitory computer readable storage medium; receiving a selection of the template object from an advertiser system external to the social networking system; receiving advertisement content from the advertiser system to generate an advertisement based on the selected template object; receiving, from a first computing device, a request for the advertisement, the first computing device being associated with a first user of the social networking system; retrieving, by the social networking system based on the content instructions, first user profile information from a first user profile of the first user to be incorporated into the advertisement by the template object; generating, using a computer processor of the social networking system, the advertisement based on the content instructions from the template object, the advertisement comprising the advertisement content and the first user profile information associated with the first user, the advertisement describing the action to the first user to be performed by the advertiser system in response to the first user selecting the advertisement; providing the advertisement for display to the first user on the first computing device; receiving, from the first computing device of the first user, a selection of the advertisement; responsive to receiving the selection, sending, to the advertiser system, a request to perform the action described to the first user in the advertisement; receiving a confirmation from the advertiser system that the action described in the advertisement has been performed, the confirmation comprising information associated with the action performed by the advertiser system; in response to receiving the confirmation, modifying the advertisement with the information associated with the action performed by the advertiser system; and providing the modified advertisement to the first computing device for display. 4. The method of claim 1 , wherein providing the advertisement to the first computing device for display comprises: establishing communication with the first computing device associated with the first user via a server; and providing data comprising the advertisement to the computing device for display.

16. In a computer system capable of storing and processing data a method of positioning a plurality of Unicode textual character sequences of like directionality in storage sequence or externally defined image data onto a display line of limited size comprising the steps of: (a) setting an equal insertion point for all Unicode Bidirectional embedding depth levels at the start point of insertion for the start point of the line; (b) determining if the size of a sequence of like directionality Unicode characters or an externally defined image data object fit within the remaining space available on the line; (c) placing a sequence of like directionality Unicode characters or an externally defined image data object at the insertion point; (d) updating the end point of line insertion according to the dimensions of the sequence of like directionality Unicode characters or externally defined image object; (e) generating an insertion stack of insertion minimum and maximum positions for each Unicode Bidirectional embedding depth; and (f) updating entries in the insertion stack for each insertion of a sequence of like directionality Unicode characters or externally defined image object.

16. In a computer system capable of storing and processing data a method of positioning a plurality of Unicode textual character sequences of like directionality in storage sequence or externally defined image data onto a display line of limited size comprising the steps of: (a) setting an equal insertion point for all Unicode Bidirectional embedding depth levels at the start point of insertion for the start point of the line; (b) determining if the size of a sequence of like directionality Unicode characters or an externally defined image data object fit within the remaining space available on the line; (c) placing a sequence of like directionality Unicode characters or an externally defined image data object at the insertion point; (d) updating the end point of line insertion according to the dimensions of the sequence of like directionality Unicode characters or externally defined image object; (e) generating an insertion stack of insertion minimum and maximum positions for each Unicode Bidirectional embedding depth; and (f) updating entries in the insertion stack for each insertion of a sequence of like directionality Unicode characters or externally defined image object. 17. The method of claim 16 wherein subsequent insertion of sequences of like directionality Unicode characters or externally defined image objects use the insertion stack to choose placement position.

1. A computer implemented method for analyzing user performance data from multiple sources, and for providing evaluation and feedback regarding user performance, the method comprising: receiving performance data for evaluating the user with a computer, the performance data resulting from the user performing a first task for evaluating a cognitive ability of the user and a second, different task for evaluating a non-cognitive ability of the user; analyzing the performance data with the computer using mathematical models related to the first and second tasks; wherein the analyzing performance data comprises: identifying construct models as the mathematical models related to the first and second tasks; identifying model-specific evaluation functions for each of the construct models; transforming the performance data onto score scales using the model-specific evaluation functions, resulting in model-specific scaled score data; transforming the model-specific scored scaled data and previously stored model-specific scaled score data into construct-level scores; identifying score scale partition categories based on the construct-level scores; retrieving category-specific diagnostic feedback based on the identified score scale partition categories; generating an evaluation and diagnostic feedback with the computer based upon the analyzing; generating a report regarding user performance using the diagnostic feedback and the evaluation; and transmitting the report.

1. A computer implemented method for analyzing user performance data from multiple sources, and for providing evaluation and feedback regarding user performance, the method comprising: receiving performance data for evaluating the user with a computer, the performance data resulting from the user performing a first task for evaluating a cognitive ability of the user and a second, different task for evaluating a non-cognitive ability of the user; analyzing the performance data with the computer using mathematical models related to the first and second tasks; wherein the analyzing performance data comprises: identifying construct models as the mathematical models related to the first and second tasks; identifying model-specific evaluation functions for each of the construct models; transforming the performance data onto score scales using the model-specific evaluation functions, resulting in model-specific scaled score data; transforming the model-specific scored scaled data and previously stored model-specific scaled score data into construct-level scores; identifying score scale partition categories based on the construct-level scores; retrieving category-specific diagnostic feedback based on the identified score scale partition categories; generating an evaluation and diagnostic feedback with the computer based upon the analyzing; generating a report regarding user performance using the diagnostic feedback and the evaluation; and transmitting the report. 2. The method of claim 1 wherein each construct model corresponds to a construct representing at least one cognitive or non-cognitive ability.

1. A first computer system, comprising: at least one processing unit; and at least one system memory communicatively coupled to the at least one processing unit and comprising computer-readable instructions that when executed by the at least one processing unit perform a method of converting typed application data into a Simple Object Access Protocol (SOAP) format, the method comprising: an act of storing by the first computer system a typed data object, wherein the typed data object defines a method associated with a first portion of a distributed application, wherein the typed data object comprises: typed application data comprising at least one typed object parameter for invoking the method, wherein the at least one typed object parameter is in a format compatible with the first portion of the distributed application and with a second portion of the distributed application on a second computer system; and at least one message contract attribute of a message contract model, wherein the at least one message contract attribute annotates the typed data object such that the at least one message contract attribute is adjacent to the at least one typed object parameter, wherein the at least one message contract attribute defines a mapping between the at least one typed object parameter and a corresponding SOAP element, and wherein the at least one message contract attribute specifies a location within a SOAP envelope for inserting the corresponding SOAP element; an act of accessing the typed data object; an act of mapping the at least one typed object parameter to the corresponding SOAP element by referring to the at least one message contract attribute that annotates the accessed typed data object; an act of inserting the corresponding SOAP element into the location within the SOAP envelope in accordance with the at least one message contract attribute; and an act of transmitting the SOAP envelope to the second portion of the distributed application on the second computer system.

1. A first computer system, comprising: at least one processing unit; and at least one system memory communicatively coupled to the at least one processing unit and comprising computer-readable instructions that when executed by the at least one processing unit perform a method of converting typed application data into a Simple Object Access Protocol (SOAP) format, the method comprising: an act of storing by the first computer system a typed data object, wherein the typed data object defines a method associated with a first portion of a distributed application, wherein the typed data object comprises: typed application data comprising at least one typed object parameter for invoking the method, wherein the at least one typed object parameter is in a format compatible with the first portion of the distributed application and with a second portion of the distributed application on a second computer system; and at least one message contract attribute of a message contract model, wherein the at least one message contract attribute annotates the typed data object such that the at least one message contract attribute is adjacent to the at least one typed object parameter, wherein the at least one message contract attribute defines a mapping between the at least one typed object parameter and a corresponding SOAP element, and wherein the at least one message contract attribute specifies a location within a SOAP envelope for inserting the corresponding SOAP element; an act of accessing the typed data object; an act of mapping the at least one typed object parameter to the corresponding SOAP element by referring to the at least one message contract attribute that annotates the accessed typed data object; an act of inserting the corresponding SOAP element into the location within the SOAP envelope in accordance with the at least one message contract attribute; and an act of transmitting the SOAP envelope to the second portion of the distributed application on the second computer system. 9. The first computer system as recited in claim 1 , wherein the act of accessing the typed data object comprises an act of accessing the typed object parameter that is annotated with the at least one message contract attribute, wherein the at least one message contract attribute indicates that an XML representation of the typed object parameter is to be included in a SOAP envelope body.

7. The electronic device of claim 1 , wherein the processor is configured to: performs training based on the voice signal inputted during an operation preceding the voice recognition, and generates training data based on the training.

7. The electronic device of claim 1 , wherein the processor is configured to: performs training based on the voice signal inputted during an operation preceding the voice recognition, and generates training data based on the training. 8. The electronic device of claim 7 , wherein the training data is stored in one or more of the storage unit, another electronic device, or a server.

1. An information processor comprising: at least one processor; and at least one memory, the at least one memory storing instructions that when executed cause the at least one processor to function as: a specifying unit that specifies a candidate region in an image; a character recognizing unit that recognizes characters in the candidate region; a recognized character feature obtaining unit that obtains, as a recognized character feature, a quantity of predetermined characters contained in the characters recognized by the character recognizing unit; a translation deciding unit that decides whether or not the recognized characters are to be translated in accordance with the recognized character feature obtained by the recognized character feature obtaining unit, a translation unit that translates the recognized characters in accordance with a decision from the translation deciding unit; an outputting deciding unit that decides whether to output the translated result in accordance with a feature obtained from a translated result; and an outputting unit that outputs the translated result in accordance with the decision from the outputting deciding unit, wherein the predetermined characters are characters frequently appearing in characters obtained by performing character recognition in a region which does not include characters.

1. An information processor comprising: at least one processor; and at least one memory, the at least one memory storing instructions that when executed cause the at least one processor to function as: a specifying unit that specifies a candidate region in an image; a character recognizing unit that recognizes characters in the candidate region; a recognized character feature obtaining unit that obtains, as a recognized character feature, a quantity of predetermined characters contained in the characters recognized by the character recognizing unit; a translation deciding unit that decides whether or not the recognized characters are to be translated in accordance with the recognized character feature obtained by the recognized character feature obtaining unit, a translation unit that translates the recognized characters in accordance with a decision from the translation deciding unit; an outputting deciding unit that decides whether to output the translated result in accordance with a feature obtained from a translated result; and an outputting unit that outputs the translated result in accordance with the decision from the outputting deciding unit, wherein the predetermined characters are characters frequently appearing in characters obtained by performing character recognition in a region which does not include characters. 3. The information processor as claimed in claim 1 , wherein the recognized character feature obtaining unit obtains a fifth feature related to a predetermined number of letters of a character area included in the image.

7. The method of claim 1 wherein evaluating the submission further comprises: determining a reputation for the user based on previous submissions by the user for other objects stored in the social networking system; evaluating the submission based the reputation of the user.

7. The method of claim 1 wherein evaluating the submission further comprises: determining a reputation for the user based on previous submissions by the user for other objects stored in the social networking system; evaluating the submission based the reputation of the user. 8. The method of claim 7 wherein the user's reputation is based on a number of submissions by the user that have been evaluated and accepted as additional content for other objects.

1. A system for computer application code automation, the system comprising: a code automation computer server configured for presenting an electronic user interface for receiving user input for generating a Structured Query Language (SQL) query, the user input comprising a plurality of SQL tokens; a processor, associated with the code automation computer server, for receiving the plurality of SQL tokens, the processor retrieving from memory and executing computer executable instructions for: displaying a first electronic user interface screen for accepting a first partial portion of the user input comprising the plurality of SQL tokens, 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; wherein the processor is adapted for automatically incorporating the generated SQL query into the computer application code and storing the computer application code in a non-transitory computer readable medium.

1. A system for computer application code automation, the system comprising: a code automation computer server configured for presenting an electronic user interface for receiving user input for generating a Structured Query Language (SQL) query, the user input comprising a plurality of SQL tokens; a processor, associated with the code automation computer server, for receiving the plurality of SQL tokens, the processor retrieving from memory and executing computer executable instructions for: displaying a first electronic user interface screen for accepting a first partial portion of the user input comprising the plurality of SQL tokens, 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; wherein the processor is adapted for automatically incorporating the generated SQL query into the computer application code and storing the computer application code in a non-transitory computer readable medium. 4. The system of claim 1 wherein the computer executable instructions for error checking while receiving the user input further comprise generating a real-time prompt to supply missing information for at least one SQL token supplied by the user based on a predetermined syntax of the SQL token.

15. An information processing system comprising: an information processing apparatus and a computer connected to the information processing apparatus through a network, the information processing apparatus comprising a first Japanese-language converting portion that uses a first normal dictionary and first dictionary additional information to convert characters input through user operation and a controlling portion that performs control of transmitting the first normal dictionary to the computer through the network and control of externally receiving the first dictionary additional information as the response thereto, the computer comprising a second Japanese-language converting portion that uses a second normal dictionary and a second dictionary additional information to convert characters input through user operation, a dictionary additional information generating portion that uses the first normal dictionary and the second dictionary additional information to generate the first dictionary additional information for the first normal dictionary received from the information processing apparatus through the network, and a dictionary additional information output portion that outputs the first dictionary additional information generated by the dictionary additional information generating portion.

15. An information processing system comprising: an information processing apparatus and a computer connected to the information processing apparatus through a network, the information processing apparatus comprising a first Japanese-language converting portion that uses a first normal dictionary and first dictionary additional information to convert characters input through user operation and a controlling portion that performs control of transmitting the first normal dictionary to the computer through the network and control of externally receiving the first dictionary additional information as the response thereto, the computer comprising a second Japanese-language converting portion that uses a second normal dictionary and a second dictionary additional information to convert characters input through user operation, a dictionary additional information generating portion that uses the first normal dictionary and the second dictionary additional information to generate the first dictionary additional information for the first normal dictionary received from the information processing apparatus through the network, and a dictionary additional information output portion that outputs the first dictionary additional information generated by the dictionary additional information generating portion. 22. The information processing system as defined in claim 15 , wherein the computer comprises an erasing portion that erases the first normal dictionary received from the information processing apparatus after the dictionary additional information generating portion generates the first dictionary additional information for the first normal dictionary.

1. A method comprising, by a computing device: receiving, from a client device of a first user, a text string comprising one or more characters inputted by the first user; generating a set of suggested queries based on the text string, each suggested query in the set being based on a string generated by a grammar of a grammar model and comprising the text string of the query and one or more tokens inserted by the grammar model corresponding to one or more terms, respectively; calculating, for each suggested query in the set, a quality score based on an insertion cost of the one or more tokens of the suggested query inserted by the grammar model; filtering the set to remove one or more suggested queries from the set based on the respective quality scores of the suggested queries; and sending, to the client device, one or more of the suggested queries from the post-filtered set for presentation to the first user.

1. A method comprising, by a computing device: receiving, from a client device of a first user, a text string comprising one or more characters inputted by the first user; generating a set of suggested queries based on the text string, each suggested query in the set being based on a string generated by a grammar of a grammar model and comprising the text string of the query and one or more tokens inserted by the grammar model corresponding to one or more terms, respectively; calculating, for each suggested query in the set, a quality score based on an insertion cost of the one or more tokens of the suggested query inserted by the grammar model; filtering the set to remove one or more suggested queries from the set based on the respective quality scores of the suggested queries; and sending, to the client device, one or more of the suggested queries from the post-filtered set for presentation to the first user. 5. The method of claim 1 , wherein, for each suggested query, one or more of the tokens inserted by the grammar model corresponds to one or more objects associated with the online social network, respectively.

1. A mobile electronic device comprising: a touch sensitive screen; a detection component for detecting a change in physical orientation of the mobile electronic device; and a translator application operable in multiple physical orientations of the mobile electronic device, the translator application translating between natural languages and the translator application triggered by detecting a change in the physical orientation of the mobile electronic device, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from a first orientation to a second orientation, the translator application: causing a translation of a word or phrase from a first language entered via a first virtual keyboard, having characters or symbols from the first language, on the touch sensitive screen into a second language to obtain a first translation, and causing a display of the first translation and a second virtual keyboard with characters or symbols from the second language on the touch sensitive screen, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from the second orientation back to the first orientation, the translator application: causing a translation of a word or phrase entered via the second virtual keyboard from the second language on the touch sensitive screen into the first language to obtain a second translation, and causing a display of the second translation and the first virtual keyboard, wherein the first language is a default language or is selected by a first user, and wherein the second language is selected by the first user, selected by a second user, or determined by the mobile electronic device.

1. A mobile electronic device comprising: a touch sensitive screen; a detection component for detecting a change in physical orientation of the mobile electronic device; and a translator application operable in multiple physical orientations of the mobile electronic device, the translator application translating between natural languages and the translator application triggered by detecting a change in the physical orientation of the mobile electronic device, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from a first orientation to a second orientation, the translator application: causing a translation of a word or phrase from a first language entered via a first virtual keyboard, having characters or symbols from the first language, on the touch sensitive screen into a second language to obtain a first translation, and causing a display of the first translation and a second virtual keyboard with characters or symbols from the second language on the touch sensitive screen, wherein in response to the detection component detecting a change in the physical orientation of the mobile electronic device from the second orientation back to the first orientation, the translator application: causing a translation of a word or phrase entered via the second virtual keyboard from the second language on the touch sensitive screen into the first language to obtain a second translation, and causing a display of the second translation and the first virtual keyboard, wherein the first language is a default language or is selected by a first user, and wherein the second language is selected by the first user, selected by a second user, or determined by the mobile electronic device. 5. The device of claim 1 , wherein the mobile electronic device being in the first orientation is rotated by about ninety degrees in the plane of the touch sensitive screen to obtain the second orientation, and wherein the touch sensitive screen is to display right side up the word or phrase in the first language when the mobile electronic device is in the first orientation, and to display right side up the word or phrase in the second language when the mobile electronic device is in the second orientation.

1. A method implemented by a computer, the computer comprising in a computer readable storage medium including one or more computer readable instructions stored thereon that, when executed by a computer, cause the computer to perform the method to automatically generate a naturally reading narrative product summary including assertions about a specific product selected by a user, said method comprising: receiving the selection of the specific product from the user, the specific product associated with a plurality of attributes; determining at least one attribute of the plurality of attributes for comparison for the specific product selected by the user; selecting a comparable product based on the at least one attribute, the comparable product being the product having a high value rating for the at least one attribute; and generating the naturally reading narrative product summary including assertions about the specific product selected by the user and a recommendation of the comparable product.

1. A method implemented by a computer, the computer comprising in a computer readable storage medium including one or more computer readable instructions stored thereon that, when executed by a computer, cause the computer to perform the method to automatically generate a naturally reading narrative product summary including assertions about a specific product selected by a user, said method comprising: receiving the selection of the specific product from the user, the specific product associated with a plurality of attributes; determining at least one attribute of the plurality of attributes for comparison for the specific product selected by the user; selecting a comparable product based on the at least one attribute, the comparable product being the product having a high value rating for the at least one attribute; and generating the naturally reading narrative product summary including assertions about the specific product selected by the user and a recommendation of the comparable product. 6. The method of claim 1 , wherein said selected comparable product has a price within a predetermined near-price margin of said user selected product.

8. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at a search system from a user device associated with a user, user input comprising one or more characters of a partial search query; determining that the one or more characters of the partial search query correspond to a trigger query; in response to determining that the one or more characters of the partial search query correspond to a trigger query, determining a predicted query for the trigger query, the predicted query comprising the trigger query and additional information for refining the trigger query; and providing the predicted query to the user device for presentation to the user prior to the user submitting a search query to the search system.

8. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at a search system from a user device associated with a user, user input comprising one or more characters of a partial search query; determining that the one or more characters of the partial search query correspond to a trigger query; in response to determining that the one or more characters of the partial search query correspond to a trigger query, determining a predicted query for the trigger query, the predicted query comprising the trigger query and additional information for refining the trigger query; and providing the predicted query to the user device for presentation to the user prior to the user submitting a search query to the search system. 10. The computer program product of claim 8 , wherein providing the predicted query to the user device comprises providing the predicted query to the user device prior to providing search results in response to the user input.

6. A computer-implemented method of determining whether a business listing is legitimate, the method comprising: accessing, by a processor, a list of legitimate business titles, each legitimate business title including one or more words; generating a matrix of surprisingness values, where each surprisingness value indicates a likelihood of a word appearing in a legitimate business title, by: examining each legitimate business title to identify pairs of words occurring in that title, adding a count value to the matrix for each pair of words identified, such that the matrix includes a plurality of count values for different pairs of words occurring in the legitimate business titles, and normalizing the plurality of count values for the matrix to generate the matrix of surprisingness values, where each surprisingness value of the matrix of surprisingness values indicates how likely a pair of words are to appear in a legitimate business title; storing the matrix of surprisingness values in memory; accessing a first plurality of business listings each associated with title data including two or more words; identifying, from the first plurality of business listings, a second plurality of business listings all corresponding to one particular business; for each business listing of the identified second plurality of business listings, determining a surprisingness value indicative of the surprisingness of the title included in the particular business listing based on the stored matrix of surprisingness values; determining an average surprisingness value for the identified second plurality of business listings based on the stored matrix of surprisingness values; selecting a particular business listing of the identified second plurality of business listings; and determining whether the particular business listing is legitimate based on whether the surprisingness value for the particular business listing is greater than the average surprisingness value plus a threshold value.

6. A computer-implemented method of determining whether a business listing is legitimate, the method comprising: accessing, by a processor, a list of legitimate business titles, each legitimate business title including one or more words; generating a matrix of surprisingness values, where each surprisingness value indicates a likelihood of a word appearing in a legitimate business title, by: examining each legitimate business title to identify pairs of words occurring in that title, adding a count value to the matrix for each pair of words identified, such that the matrix includes a plurality of count values for different pairs of words occurring in the legitimate business titles, and normalizing the plurality of count values for the matrix to generate the matrix of surprisingness values, where each surprisingness value of the matrix of surprisingness values indicates how likely a pair of words are to appear in a legitimate business title; storing the matrix of surprisingness values in memory; accessing a first plurality of business listings each associated with title data including two or more words; identifying, from the first plurality of business listings, a second plurality of business listings all corresponding to one particular business; for each business listing of the identified second plurality of business listings, determining a surprisingness value indicative of the surprisingness of the title included in the particular business listing based on the stored matrix of surprisingness values; determining an average surprisingness value for the identified second plurality of business listings based on the stored matrix of surprisingness values; selecting a particular business listing of the identified second plurality of business listings; and determining whether the particular business listing is legitimate based on whether the surprisingness value for the particular business listing is greater than the average surprisingness value plus a threshold value. 10. The method of claim 6 , further comprising determining whether the particular business listing is legitimate when the surprisingness value for the particular business listing is greater than the average surprisingness value plus the threshold value.

1. A computer-implemented method comprising: identifying, in a plurality of digital videos, a plurality of candidate volumes representing spatio-temporal segments of the digital videos, wherein each of the candidate volumes corresponds to a contiguous sequence of spatial portions of video frames of one of the digital videos, has a starting time and an ending time, and potentially represents a discrete object or action within the video frames, wherein identifying the candidate volumes in the digital videos comprises: stabilizing the digital videos using a video stabilization algorithm and identifying, as a stable segment, a contiguous sequence of frames in one of the digital videos in which a degree of background motion is below a threshold, using a measure of background motion produced by the video stabilization algorithm; determining, for each of the identified candidate volumes, features characterizing the candidate volume, wherein the features are determined from visual properties of the spatial portions of the video frames contained in the candidate volumes; and assigning a verified label to each volume of a plurality of the identified candidate volumes using the determined features, the verified label indicating a particular object or action represented by the volume to which the verified label is assigned.

1. A computer-implemented method comprising: identifying, in a plurality of digital videos, a plurality of candidate volumes representing spatio-temporal segments of the digital videos, wherein each of the candidate volumes corresponds to a contiguous sequence of spatial portions of video frames of one of the digital videos, has a starting time and an ending time, and potentially represents a discrete object or action within the video frames, wherein identifying the candidate volumes in the digital videos comprises: stabilizing the digital videos using a video stabilization algorithm and identifying, as a stable segment, a contiguous sequence of frames in one of the digital videos in which a degree of background motion is below a threshold, using a measure of background motion produced by the video stabilization algorithm; determining, for each of the identified candidate volumes, features characterizing the candidate volume, wherein the features are determined from visual properties of the spatial portions of the video frames contained in the candidate volumes; and assigning a verified label to each volume of a plurality of the identified candidate volumes using the determined features, the verified label indicating a particular object or action represented by the volume to which the verified label is assigned. 6. The computer-implemented method of claim 1 , wherein ones of the plurality of digital videos are associated with labels, and wherein assigning a verified label to a volume comprises: associating, with each of the candidate volumes, preliminary labels associated with the digital video in which the candidate volume was identified; clustering the candidate volumes into a plurality of clusters according to their determined features; determining, for each of the clusters, a degree of label consistency of the preliminary labels associated with the candidate volumes in the cluster; and assigning, as a verified label, to a candidate volume in a cluster with at least a given threshold degree of label consistency, a label with a high degree of occurrence in the cluster.

1. A method performed by one or more server devices, the method comprising: receiving, using at least one processor of the one or more server devices, a comment associated with a first document, the comment corresponding to a first portion of the first document; determining, using the at least one processor of the one or more server devices, that a size of the first portion is greater than a threshold size; based on determining that the size of the first portion is greater than the threshold size, identifying, using the at least one processor of the one or more server devices, one or more second documents, each of the one or more second documents including a respective second portion that matches the first portion; storing, in a memory associated with the one or more server devices, the comment in association with the first document and the one or more second documents; and presenting, using the at least one processor of the one or more server devices, the comment and another comment in connection with a particular second document, of the one or more second documents, when the particular second document is accessed by a user, presenting the comment and the other comment in connection with the particular second document further including: generating a score for the comment based on a degree of match between the first portion and the respective second portion, generating another score for the other comment with respect to the particular second document based on a degree of match between the respective second portion and a third portion, of the first document, that differs from the first portion, the other comment being associated with the third portion, and presenting, in connection with the particular second document, the comment relative to the other comment, the comment and the other comment being ranked in an order that is based on the score and the other score.

1. A method performed by one or more server devices, the method comprising: receiving, using at least one processor of the one or more server devices, a comment associated with a first document, the comment corresponding to a first portion of the first document; determining, using the at least one processor of the one or more server devices, that a size of the first portion is greater than a threshold size; based on determining that the size of the first portion is greater than the threshold size, identifying, using the at least one processor of the one or more server devices, one or more second documents, each of the one or more second documents including a respective second portion that matches the first portion; storing, in a memory associated with the one or more server devices, the comment in association with the first document and the one or more second documents; and presenting, using the at least one processor of the one or more server devices, the comment and another comment in connection with a particular second document, of the one or more second documents, when the particular second document is accessed by a user, presenting the comment and the other comment in connection with the particular second document further including: generating a score for the comment based on a degree of match between the first portion and the respective second portion, generating another score for the other comment with respect to the particular second document based on a degree of match between the respective second portion and a third portion, of the first document, that differs from the first portion, the other comment being associated with the third portion, and presenting, in connection with the particular second document, the comment relative to the other comment, the comment and the other comment being ranked in an order that is based on the score and the other score. 3. The method of claim 1 , further comprising: storing the comment in association with only the first document when the size of the first portion is not greater than the threshold size.

13. An apparatus comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory are configured to provide operations comprising: receiving, at a service consumer implemented on a client computing system from a service provider implemented on a server computing system, a message comprising data values associated with a business object; transforming, at the service consumer, a portion of the message into first data values of a first data type, the first data values corresponding to a first business object instance, the first data type comprising character strings representing data elements of at least one business object node instance, the first data type being different than a second data type; storing the first data values in a table, the table being of a type associated with the business object, wherein each business object node instance corresponds to a row of the table and each column corresponds to the data elements; determining, at the service consumer, by type checking the first data values in response to a request for the first data values presented in the second data type, whether the first data values have already been transformed from the first data type to the second data type; transforming, at the service consumer, the first data values into the second data type based upon the determination that the first data values have not been previously transformed from the first data type to the second data type and based upon a plurality of rules; and replacing the first data values stored in the table in the first data type with the first data values transformed from the first data type to the second data type, wherein the computing resources utilized by the service consumer are reduced by transforming fewer than all of the data values from the first data type to the second data type.

13. An apparatus comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory are configured to provide operations comprising: receiving, at a service consumer implemented on a client computing system from a service provider implemented on a server computing system, a message comprising data values associated with a business object; transforming, at the service consumer, a portion of the message into first data values of a first data type, the first data values corresponding to a first business object instance, the first data type comprising character strings representing data elements of at least one business object node instance, the first data type being different than a second data type; storing the first data values in a table, the table being of a type associated with the business object, wherein each business object node instance corresponds to a row of the table and each column corresponds to the data elements; determining, at the service consumer, by type checking the first data values in response to a request for the first data values presented in the second data type, whether the first data values have already been transformed from the first data type to the second data type; transforming, at the service consumer, the first data values into the second data type based upon the determination that the first data values have not been previously transformed from the first data type to the second data type and based upon a plurality of rules; and replacing the first data values stored in the table in the first data type with the first data values transformed from the first data type to the second data type, wherein the computing resources utilized by the service consumer are reduced by transforming fewer than all of the data values from the first data type to the second data type. 14. An apparatus in accordance with claim 13 , wherein the second data type comprises a complex data type not being the character string data type.

15. A system for caller identification and authentication, the system comprising: a telephony recorder configured to record audio data for calls placed to at least one phone number; an authentication server comprising a processor and a non-transitory memory, the memory storing instructions that, when executed by the processor, cause the processor to perform processing comprising: receiving audio data including speech of a plurality of telephone calls; using audio data for at least a subset of the plurality of telephone calls to populate a plurality of word clusters, each word cluster being associated with a specific demographic, the populating of the plurality of word clusters comprising: for each of the subset of the plurality of telephone calls, determining demographic data for a telephone caller making the telephone call, and analyzing the audio data to identify at least one characteristic of the speech of the telephone caller, and populating at least one word cluster with the at least one characteristic of the speech of each telephone caller associated with the specific demographic based on the demographic data for the telephone caller; and using audio data for at least one of the plurality of telephone calls to identify the telephone caller making the telephone call, the identifying comprising: analyzing the audio data to identify at least one characteristic of the speech of the telephone caller, comparing the at least one characteristic of the speech of the telephone caller to the plurality of word clusters, determining a most similar word cluster of the plurality of word clusters to the audio data based on a similarity of the at least one characteristic of the speech of the telephone caller and the at least one associated characteristic of the most similar cluster, receiving a purported identity of the telephone caller, the purported identity including caller demographic data, determining whether the caller demographic data matches the demographic associated with the most similar word cluster, and identifying the telephone caller as: likely having the purported identity in response to determining that the caller demographic data matches the demographic associated with the most similar word cluster, or unlikely to have the purported identity in response to determining that the caller demographic data does not match the demographic associated with the most similar word cluster.

15. A system for caller identification and authentication, the system comprising: a telephony recorder configured to record audio data for calls placed to at least one phone number; an authentication server comprising a processor and a non-transitory memory, the memory storing instructions that, when executed by the processor, cause the processor to perform processing comprising: receiving audio data including speech of a plurality of telephone calls; using audio data for at least a subset of the plurality of telephone calls to populate a plurality of word clusters, each word cluster being associated with a specific demographic, the populating of the plurality of word clusters comprising: for each of the subset of the plurality of telephone calls, determining demographic data for a telephone caller making the telephone call, and analyzing the audio data to identify at least one characteristic of the speech of the telephone caller, and populating at least one word cluster with the at least one characteristic of the speech of each telephone caller associated with the specific demographic based on the demographic data for the telephone caller; and using audio data for at least one of the plurality of telephone calls to identify the telephone caller making the telephone call, the identifying comprising: analyzing the audio data to identify at least one characteristic of the speech of the telephone caller, comparing the at least one characteristic of the speech of the telephone caller to the plurality of word clusters, determining a most similar word cluster of the plurality of word clusters to the audio data based on a similarity of the at least one characteristic of the speech of the telephone caller and the at least one associated characteristic of the most similar cluster, receiving a purported identity of the telephone caller, the purported identity including caller demographic data, determining whether the caller demographic data matches the demographic associated with the most similar word cluster, and identifying the telephone caller as: likely having the purported identity in response to determining that the caller demographic data matches the demographic associated with the most similar word cluster, or unlikely to have the purported identity in response to determining that the caller demographic data does not match the demographic associated with the most similar word cluster. 16. The system of claim 15 , wherein: the at least one characteristic of the speech of the telephone caller comprises a plurality of words; the at least one associated characteristic of each word cluster comprises a plurality of associated words; and the determining whether the caller demographic data matches the demographic associated with the most similar word cluster comprises determining a similarity of the plurality of words and the plurality of associated words of the most similar cluster.

10. A method for indexing a document file comprising a plurality of characters arranged into an array of strings, the method comprising: identifying date strings within the array of strings that correspond to a date and selecting a date string that corresponds to the earliest date; comparing the date string that corresponds to the earliest date against a reference database, the reference database comprise a plurality of records and each record comprises at least one data field, to generate a comparison reference database comprising records from the reference database that possess at least one data field that matches the date string; responsive to the comparison reference database comprising a plurality of records, performing a matching operation to reduce the number of records that comprise the comparison reference database; responsive to the comparison reference database comprising one record, associating the document file with that record; and responsive to the comparison reference database comprising a second plurality of records following performance of the matching operation, providing at least a portion of the second plurality of records to a user to facilitate the user's selection of a record to associate with the document file.

10. A method for indexing a document file comprising a plurality of characters arranged into an array of strings, the method comprising: identifying date strings within the array of strings that correspond to a date and selecting a date string that corresponds to the earliest date; comparing the date string that corresponds to the earliest date against a reference database, the reference database comprise a plurality of records and each record comprises at least one data field, to generate a comparison reference database comprising records from the reference database that possess at least one data field that matches the date string; responsive to the comparison reference database comprising a plurality of records, performing a matching operation to reduce the number of records that comprise the comparison reference database; responsive to the comparison reference database comprising one record, associating the document file with that record; and responsive to the comparison reference database comprising a second plurality of records following performance of the matching operation, providing at least a portion of the second plurality of records to a user to facilitate the user's selection of a record to associate with the document file. 11. The method of claim 10 wherein the matching operation comprises performing one or more matching algorithms.

1. A system, comprising: a memory operable to store a search index associated with an ontology, wherein the ontology comprises at least one instance and the instance has a name; and a processor communicatively coupled to the memory and operable to: query the search index and the ontology in parallel, wherein the search index is generated based at least in part upon an unstructured data element by streaming and normalizing received data terms from a data source and the ontology is generated based at least in part upon an structured data element at least one data mitigation and classification rule; receive a first search request relating to information stored in an ontology; parse the first search request to determine if the first search request is an instance based search that comprises all or part of a name of at least a first instance in the ontology; perform a first query of the search index in response to determining that the first search request is an instance based search; receive a second search request relating to information stored in the ontology; parse the second search request to determine if the second search request is an instance based search that comprises all or part of a name of at least a second instance in the ontology; and perform a second query of at least the ontology in response to determining that the second search request is not an instance based search receive a third search request relating to information not stored in the ontology; parse the third search request to determine that the third search request is an instance based search that comprises all or part of a name of at least one instance in the ontology; perform a third query of the search index and retrieve metadata associated with the third instance from the search index, wherein the metadata comprises information about a data source associated with the third instance; and retrieve information from the data source that are not stored in the ontology.

1. A system, comprising: a memory operable to store a search index associated with an ontology, wherein the ontology comprises at least one instance and the instance has a name; and a processor communicatively coupled to the memory and operable to: query the search index and the ontology in parallel, wherein the search index is generated based at least in part upon an unstructured data element by streaming and normalizing received data terms from a data source and the ontology is generated based at least in part upon an structured data element at least one data mitigation and classification rule; receive a first search request relating to information stored in an ontology; parse the first search request to determine if the first search request is an instance based search that comprises all or part of a name of at least a first instance in the ontology; perform a first query of the search index in response to determining that the first search request is an instance based search; receive a second search request relating to information stored in the ontology; parse the second search request to determine if the second search request is an instance based search that comprises all or part of a name of at least a second instance in the ontology; and perform a second query of at least the ontology in response to determining that the second search request is not an instance based search receive a third search request relating to information not stored in the ontology; parse the third search request to determine that the third search request is an instance based search that comprises all or part of a name of at least one instance in the ontology; perform a third query of the search index and retrieve metadata associated with the third instance from the search index, wherein the metadata comprises information about a data source associated with the third instance; and retrieve information from the data source that are not stored in the ontology. 5. The system of claim 1 , wherein the processor is further operable to generate the search index at least in part by indexing data stored in the ontology.

1. A method, comprising: receiving, by a computing device, a request for a rank-specific search link corresponding to a particular search result within a first list of search results of a first search; identifying, by the computing device, one or more search parameters used by a search engine to generate the first list of search results, the first list of search results including search results of the first search in a ranked order; identifying, by the computing device, a search result rank position of the particular search result in the first list of search results; creating, by the computing device, the rank-specific search link associated with: the one or more search parameters used to generate the first list of search results, and the search result rank position of the particular search result in the first list of search results; and providing, by the computing device, the rank-specific search link in accordance with the request, where selection of the rank-specific search link causes a second search to be executed using the one or more search parameters and causes information, to be presented, relating to a document ranked at the search result rank position within a second list of search results of the second search.

1. A method, comprising: receiving, by a computing device, a request for a rank-specific search link corresponding to a particular search result within a first list of search results of a first search; identifying, by the computing device, one or more search parameters used by a search engine to generate the first list of search results, the first list of search results including search results of the first search in a ranked order; identifying, by the computing device, a search result rank position of the particular search result in the first list of search results; creating, by the computing device, the rank-specific search link associated with: the one or more search parameters used to generate the first list of search results, and the search result rank position of the particular search result in the first list of search results; and providing, by the computing device, the rank-specific search link in accordance with the request, where selection of the rank-specific search link causes a second search to be executed using the one or more search parameters and causes information, to be presented, relating to a document ranked at the search result rank position within a second list of search results of the second search. 6. The method of claim 1 , where the document is a first document, the method further comprising: receiving a search request corresponding to the rank-specific search link; identifying the one or more search parameters associated with the rank-specific search link; identifying the search result rank position associated with the rank-specific search link; identifying the second list of search results based on the one or more search parameters; identifying a search result, included in the second list of search results, that corresponds to the search result rank position within a search results document; and providing information regarding the search result, where: the particular search result is associated with a second document and the search result is associated with the first document, the first document and the second document being different documents, and the particular search result and the search result correspond to the same search result rank position.

1. A speech recognition dictionary creating support device comprising: a speech data storage section storing speech data; a prosodic information extracting section extracting prosodic information including at least a speech power value from the speech data; a speech data dividing section extracting an utterance section having a period with a power value equal to or larger than a predetermined threshold value lasting a preset time or longer from the speech data based on the prosodic information, and dividing the utterance section into sections, each of which has a power value equal to or lamer than a predetermined threshold value continuing for a given time or longer, to generate divided speech data; a phoneme sequence acquiring section executing a phoneme recognition process on the divided speech data to acquire phoneme sequence data for each divided speech data; a clustering section executing a clustering process on the phoneme sequence data to generate clusters each of which is a set of classified phoneme sequence data; an evaluation value calculating section calculating an evaluation value for each of the clusters based on the prosodic information for the divided speech data corresponding to the phoneme sequence data constituting the cluster; a candidate cluster selecting section selecting clusters for which the evaluation value is equal to or larger than a given value, as candidate clusters; and a listening target data selecting section determining one of the phoneme sequence data from the phoneme sequence data constituting the cluster for each of the candidate clusters to be a representative phoneme sequence and selecting the divided speech data corresponding to the representative phoneme sequence, as listening target speech data, and wherein the evaluation value calculating section includes dictionary data for a morpheme analysis process, and extracts a phrase classified as a predetermined word class from the dictionary data, calculates an appearance probability, in the extracted phrase, of a common phoneme subsequence constituting in the cluster, and calculates the evaluation value for the cluster based on the appearance probability.

1. A speech recognition dictionary creating support device comprising: a speech data storage section storing speech data; a prosodic information extracting section extracting prosodic information including at least a speech power value from the speech data; a speech data dividing section extracting an utterance section having a period with a power value equal to or larger than a predetermined threshold value lasting a preset time or longer from the speech data based on the prosodic information, and dividing the utterance section into sections, each of which has a power value equal to or lamer than a predetermined threshold value continuing for a given time or longer, to generate divided speech data; a phoneme sequence acquiring section executing a phoneme recognition process on the divided speech data to acquire phoneme sequence data for each divided speech data; a clustering section executing a clustering process on the phoneme sequence data to generate clusters each of which is a set of classified phoneme sequence data; an evaluation value calculating section calculating an evaluation value for each of the clusters based on the prosodic information for the divided speech data corresponding to the phoneme sequence data constituting the cluster; a candidate cluster selecting section selecting clusters for which the evaluation value is equal to or larger than a given value, as candidate clusters; and a listening target data selecting section determining one of the phoneme sequence data from the phoneme sequence data constituting the cluster for each of the candidate clusters to be a representative phoneme sequence and selecting the divided speech data corresponding to the representative phoneme sequence, as listening target speech data, and wherein the evaluation value calculating section includes dictionary data for a morpheme analysis process, and extracts a phrase classified as a predetermined word class from the dictionary data, calculates an appearance probability, in the extracted phrase, of a common phoneme subsequence constituting in the cluster, and calculates the evaluation value for the cluster based on the appearance probability. 3. The speech recognition dictionary creating support device according to claim 1 , wherein the prosodic information extracting section extracts prosodic information including a speech pitch value as the prosodic information, and the evaluation value calculating section calculates the evaluation value for the cluster based on the number of phoneme sequence data for which the pitch value in the prosodic information in the divided speech data corresponding to the phoneme sequence data has a range equal to or larger than a given value.

20. A method suitable for use in transition of one or more applications of an organization, the one or more applications being transitioned from a first set of users to a second set of users, the method comprising: a. generating one or more transition plans for the one or more applications, the one or more transition plans being generated based on information corresponding to the one or more applications, the one or more transition plans comprising one or more transition activities; b. capturing a plurality of knowledge elements corresponding to the one or more applications and the one or more transition activities, wherein the plurality of knowledge elements are captured using one or more knowledge capturing tools and one or more predefined knowledge reference components, and wherein the plurality of knowledge elements comprise a set of source code, a use case, and an incident resolution; c. associating each of the plurality of knowledge elements corresponding to a particular application with one or more other elements corresponding to said application, wherein the association between the plurality of knowledge elements is established by the first set of users and the second set of users; d. enabling the first set of users to assess and validate the knowledge of the plurality of knowledge elements and the association between the plurality of knowledge elements, wherein the validation is performed based on a predefined set of rules; and e. providing collaboration between the first set of users and the second set of users, wherein the collaboration enables communication between the first set of users and the second set of users during the transition of the one or more applications.

20. A method suitable for use in transition of one or more applications of an organization, the one or more applications being transitioned from a first set of users to a second set of users, the method comprising: a. generating one or more transition plans for the one or more applications, the one or more transition plans being generated based on information corresponding to the one or more applications, the one or more transition plans comprising one or more transition activities; b. capturing a plurality of knowledge elements corresponding to the one or more applications and the one or more transition activities, wherein the plurality of knowledge elements are captured using one or more knowledge capturing tools and one or more predefined knowledge reference components, and wherein the plurality of knowledge elements comprise a set of source code, a use case, and an incident resolution; c. associating each of the plurality of knowledge elements corresponding to a particular application with one or more other elements corresponding to said application, wherein the association between the plurality of knowledge elements is established by the first set of users and the second set of users; d. enabling the first set of users to assess and validate the knowledge of the plurality of knowledge elements and the association between the plurality of knowledge elements, wherein the validation is performed based on a predefined set of rules; and e. providing collaboration between the first set of users and the second set of users, wherein the collaboration enables communication between the first set of users and the second set of users during the transition of the one or more applications. 33. The method of claim 20 , wherein the one or more knowledge elements are captured based on a predefined knowledge reference component comprising a template for one or more of the second set of users to identify information required in connection with a knowledge element.

1. A system for indexing structured data, comprising: a communication interface configured receive first structured data; a processor configured to: determine a first plurality of subunits in the first structured data; for a first subunit included in the first structured data, determine a first mapping between the first subunit and a first dictionary entry; for a second subunit included in the first structured data, determine a second mapping between the second subunit and a second dictionary entry; aggregate at least the first and second dictionary entries into an aggregation, wherein the aggregation maintains a structure of the first plurality of subunits in the first structured data; cause the aggregation to be stored in an index along with other aggregations representing other structured data; receive a search query of second structured data; determine a search query aggregation based on a mapping between a second plurality of subunits of the second structured data of the search query and dictionary entries, wherein the search query aggregation maintains a structure of the second plurality of subunits in the second structured data; and determine a candidate set of aggregations in the index for the search query aggregation, wherein the candidate set of aggregations represent structured data that is determined to satisfy the search query of second structured data; and a memory configured to provide the processor with instructions.

1. A system for indexing structured data, comprising: a communication interface configured receive first structured data; a processor configured to: determine a first plurality of subunits in the first structured data; for a first subunit included in the first structured data, determine a first mapping between the first subunit and a first dictionary entry; for a second subunit included in the first structured data, determine a second mapping between the second subunit and a second dictionary entry; aggregate at least the first and second dictionary entries into an aggregation, wherein the aggregation maintains a structure of the first plurality of subunits in the first structured data; cause the aggregation to be stored in an index along with other aggregations representing other structured data; receive a search query of second structured data; determine a search query aggregation based on a mapping between a second plurality of subunits of the second structured data of the search query and dictionary entries, wherein the search query aggregation maintains a structure of the second plurality of subunits in the second structured data; and determine a candidate set of aggregations in the index for the search query aggregation, wherein the candidate set of aggregations represent structured data that is determined to satisfy the search query of second structured data; and a memory configured to provide the processor with instructions. 7. The system of claim 1 wherein the received structured data comprises log file data.

1. A method for sentence planning in a task classification system that interacts with a user, comprising: recognizing symbols in a user's single input communication to a task classification system; determining whether the user's input communication can be understood, wherein if the user's communication can be understood, understanding data is generated; generating a plurality of communicative goals based on the recognized symbols and understanding data, the generated plurality of communicative goals being related to information needed to be obtained from the user; in response to information from the user's single input communication: generating a plurality of sentence plans based on the plurality of generated communicative goals, each sentence plan in the plurality of sentence plans being a realization comprising elementary speech acts each corresponding to a respective communicative goal and combined into at least one complete sentence that accomplishes the plurality of communicative goals, and wherein each sentence plan of the plurality of sentence plans is a viable and potentially usable prompt in response to the user's single input communication; independent of the user, ranking the plurality of generated sentence plans; and outputting at least one of the ranked sentence plans to the user as a response to the user's single input communication such that one dialog turn occurs starting with the user's single input communication and ending with the outputted sentence plan.

1. A method for sentence planning in a task classification system that interacts with a user, comprising: recognizing symbols in a user's single input communication to a task classification system; determining whether the user's input communication can be understood, wherein if the user's communication can be understood, understanding data is generated; generating a plurality of communicative goals based on the recognized symbols and understanding data, the generated plurality of communicative goals being related to information needed to be obtained from the user; in response to information from the user's single input communication: generating a plurality of sentence plans based on the plurality of generated communicative goals, each sentence plan in the plurality of sentence plans being a realization comprising elementary speech acts each corresponding to a respective communicative goal and combined into at least one complete sentence that accomplishes the plurality of communicative goals, and wherein each sentence plan of the plurality of sentence plans is a viable and potentially usable prompt in response to the user's single input communication; independent of the user, ranking the plurality of generated sentence plans; and outputting at least one of the ranked sentence plans to the user as a response to the user's single input communication such that one dialog turn occurs starting with the user's single input communication and ending with the outputted sentence plan. 7. The method of claim 1 , wherein interactions between the user and the task classification system include nonverbal communications.

15. A machine-readable storage medium having instructions recorded therein for at least one processor, such that when the at least one processor executes the instructions, a method is performed comprising: detecting, by the at least one processor, an existence of a matrix structure or a multiline expression structure formed by a plurality of atoms of handwritten input; applying, by the at least one processor, a plurality of rewriting rules of an extended grammar parsing framework to atoms, included in a plurality of regions and a plurality of partitions, to produce a plurality of recognition results, the plurality of regions including a plurality of configuration regions and the plurality of partitions including a plurality of configuration partitions, the extended grammar parsing framework having been formed by adding a plurality of tabular structure productions to a grammar parsing framework, the applying a plurality of rewriting rules of an extended grammar parsing framework to atoms, included in a plurality of regions and a plurality of partitions, to produce a plurality of recognition results, further comprising: preventing an application of a unary production on a configuration region if the configuration region includes at least one configuration partition; and selecting and displaying, by the at least one processor, a best recognition result from among the plurality of recognition results.

15. A machine-readable storage medium having instructions recorded therein for at least one processor, such that when the at least one processor executes the instructions, a method is performed comprising: detecting, by the at least one processor, an existence of a matrix structure or a multiline expression structure formed by a plurality of atoms of handwritten input; applying, by the at least one processor, a plurality of rewriting rules of an extended grammar parsing framework to atoms, included in a plurality of regions and a plurality of partitions, to produce a plurality of recognition results, the plurality of regions including a plurality of configuration regions and the plurality of partitions including a plurality of configuration partitions, the extended grammar parsing framework having been formed by adding a plurality of tabular structure productions to a grammar parsing framework, the applying a plurality of rewriting rules of an extended grammar parsing framework to atoms, included in a plurality of regions and a plurality of partitions, to produce a plurality of recognition results, further comprising: preventing an application of a unary production on a configuration region if the configuration region includes at least one configuration partition; and selecting and displaying, by the at least one processor, a best recognition result from among the plurality of recognition results. 20. The machine-readable storage medium of claim 15 , wherein the applying a plurality of rewriting rules of an extended grammar parsing framework to atoms, included in a plurality of regions and a plurality of partitions, to produce a plurality of recognition results, further comprises: allowing a rewriting rule including a tabular structure production to be applied on a partition only if the partition is a configuration partition and the tabular structure production has a same tag as the configuration partition.

10. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, actions of the computer program instructions comprising: accessing a set of digital objects; determining degrees of similarity between pairs of the objects; and for each object of a plurality of the objects, training a classifier for the object, the training comprising: forming, for the object, a training set comprising other ones of the objects based at least in part on the degrees of similarity; and training the classifier for the object based at least in part on features extracted from the objects in the training set; applying the trained classifier for a first one of the objects to a second one of the objects to determine a degree of similarity between the second one of the objects and the first one of the objects; and responsive to the degree of similarity being above a threshold value: based on the degree of similarity, reducing cluster weights derived from user-supplied textual metadata of the first one of the objects, thereby obtaining first reduced cluster weight metadata; and associating the first reduced cluster weight metadata as metadata of the second one of the objects.

10. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, actions of the computer program instructions comprising: accessing a set of digital objects; determining degrees of similarity between pairs of the objects; and for each object of a plurality of the objects, training a classifier for the object, the training comprising: forming, for the object, a training set comprising other ones of the objects based at least in part on the degrees of similarity; and training the classifier for the object based at least in part on features extracted from the objects in the training set; applying the trained classifier for a first one of the objects to a second one of the objects to determine a degree of similarity between the second one of the objects and the first one of the objects; and responsive to the degree of similarity being above a threshold value: based on the degree of similarity, reducing cluster weights derived from user-supplied textual metadata of the first one of the objects, thereby obtaining first reduced cluster weight metadata; and associating the first reduced cluster weight metadata as metadata of the second one of the objects. 11. The non-transitory computer-readable storage medium of claim 10 , further comprising: applying the trained classifier for a third one of the objects to the second one of the objects to determine whether the third one of the objects is similar to the second one of the objects; and responsive to the third one of the objects being similar to the second one of the objects: based on a degree of similarity between the second and third objects, reducing cluster weights derived from user-supplied textual metadata of the third one of the objects, thereby obtaining second reduced cluster weight metadata; combining the second reduced cluster weight metadata with the first reduced cluster weight metadata values; and associating the combined reduced cluster weight metadata as metadata of the second one of the objects.

18. A system comprising: a processing device; and a storage device storing computer-executable instructions which, when executed by the processing device, cause the processing device to: obtain a data set; based at least on a diagnostic level selection, determine a magnitude of anomalies of an attribute of interest in the data set to be identified; identify the anomalies of the attribute of interest using an amount of computational resources specified by the diagnostic level selection; determine anomaly scores for the anomalies of the attribute of interest; generate a ranked list of predicates based at least in part on the anomaly scores; and cause at least one of the predicates of the ranked list to be presented.

18. A system comprising: a processing device; and a storage device storing computer-executable instructions which, when executed by the processing device, cause the processing device to: obtain a data set; based at least on a diagnostic level selection, determine a magnitude of anomalies of an attribute of interest in the data set to be identified; identify the anomalies of the attribute of interest using an amount of computational resources specified by the diagnostic level selection; determine anomaly scores for the anomalies of the attribute of interest; generate a ranked list of predicates based at least in part on the anomaly scores; and cause at least one of the predicates of the ranked list to be presented. 20. The system of claim 18 , wherein the computer-executable instructions further cause the processing device to: select the amount of the computational resources to use for identifying the anomalies based at least on the magnitude of the anomalies to be identified.

19. A computer readable storage medium tangibly embodying a program of instructions executable by a digital data processing machine to perform text input operations comprising: receiving machine-readable signals representing a series of user-submitted directional inputs entered via a directional input tool, the series having an order; where directional inputs of the directional input tool correspond to different linguistic object subcomponents according to a current mapping; for each user-submitted directional input, based upon that directional input alone, estimating multiple corresponding linguistic object subcomponents that the user might have intended by such directional input; assembling the different ones of the estimated linguistic object subcomponents to construct multiple different proposed linguistic objects that the user might have intended by the series of directional inputs, where each proposed object includes one estimated linguistic object subcomponent for each user-submitted directional input, the linguistic object subcomponents occurring in the proposed object in the same order as the series of user-submitted directional inputs; facilitating selection of a desired one of the proposed objects.

19. A computer readable storage medium tangibly embodying a program of instructions executable by a digital data processing machine to perform text input operations comprising: receiving machine-readable signals representing a series of user-submitted directional inputs entered via a directional input tool, the series having an order; where directional inputs of the directional input tool correspond to different linguistic object subcomponents according to a current mapping; for each user-submitted directional input, based upon that directional input alone, estimating multiple corresponding linguistic object subcomponents that the user might have intended by such directional input; assembling the different ones of the estimated linguistic object subcomponents to construct multiple different proposed linguistic objects that the user might have intended by the series of directional inputs, where each proposed object includes one estimated linguistic object subcomponent for each user-submitted directional input, the linguistic object subcomponents occurring in the proposed object in the same order as the series of user-submitted directional inputs; facilitating selection of a desired one of the proposed objects. 20. The medium of claim 19 , where each linguistic object subcomponent comprises at least one of the following: an alphabetic letter, accented letter, numeric digit, punctuation symbol; a sub-word component from a non-alphabetic language including one or more strokes, radicals, jamos, kana; a subcomponent or combination of one or more of the foregoing.

1. A computer implemented method for bidirectional matching between a plurality of parties belonging to a first group and a plurality of parties belonging to a second group, the method comprising: (a) operating a processor thereby to collect, from each party belonging to the first group, data indicative of first group criterion responses for a plurality of criterions, wherein each criterion has a pre-assigned baseline rating score; (b) operating the processor thereby to determine, in respect of at least a selection of the first group criterion responses, first group preferential rating scores; (c) operating the processor thereby to collect, from each party belonging to the second group, data indicative of second group criterion responses for the plurality of criterions; (d) operating the processor thereby to determine, in respect of at least a selection of the second group criterion responses, second group preferential rating scores; (e) on the basis of a criterion match determination protocol, operating the processor thereby to process the data indicative of criterion responses, thereby to identify criterion matches between parties belonging to the first group and parties belonging to the second group; (f) operating the processor thereby to determine, for each criterion match between a party belonging to the first group and a party belonging to the second group, a criterion match rating based on a function of the baseline rating score and, where determined, the first group preferential rating score, the second group preferential rating score, or the first group preferential rating score and the second group preferential rating score in combination; and (g) operating the processor thereby to calculate, in respect of a match between a given party belonging to the first group and a given party belonging to the second group, a total match rating, wherein the total match rating is calculated based on criterion match ratings determined for criterion matches between the given party belonging to the first group and the given party belonging to the second group, including at least one criterion match rating based on a first group preferential rating score and at least one criterion match rating based on a second group preferential rating score.

1. A computer implemented method for bidirectional matching between a plurality of parties belonging to a first group and a plurality of parties belonging to a second group, the method comprising: (a) operating a processor thereby to collect, from each party belonging to the first group, data indicative of first group criterion responses for a plurality of criterions, wherein each criterion has a pre-assigned baseline rating score; (b) operating the processor thereby to determine, in respect of at least a selection of the first group criterion responses, first group preferential rating scores; (c) operating the processor thereby to collect, from each party belonging to the second group, data indicative of second group criterion responses for the plurality of criterions; (d) operating the processor thereby to determine, in respect of at least a selection of the second group criterion responses, second group preferential rating scores; (e) on the basis of a criterion match determination protocol, operating the processor thereby to process the data indicative of criterion responses, thereby to identify criterion matches between parties belonging to the first group and parties belonging to the second group; (f) operating the processor thereby to determine, for each criterion match between a party belonging to the first group and a party belonging to the second group, a criterion match rating based on a function of the baseline rating score and, where determined, the first group preferential rating score, the second group preferential rating score, or the first group preferential rating score and the second group preferential rating score in combination; and (g) operating the processor thereby to calculate, in respect of a match between a given party belonging to the first group and a given party belonging to the second group, a total match rating, wherein the total match rating is calculated based on criterion match ratings determined for criterion matches between the given party belonging to the first group and the given party belonging to the second group, including at least one criterion match rating based on a first group preferential rating score and at least one criterion match rating based on a second group preferential rating score. 4. A method according to claim 1 wherein one or more of the criterions includes a plurality of sub-criterions, and wherein the match types include match types that define single/single, multiple/multiple and/or single/multiple matches between sub-criterions.

5. The method of claim 1 , wherein a tree edit distance between a query tree and a corresponding document tree is a combination of at least one from a set of: node insertion, deletion, and substitution operations.

5. The method of claim 1 , wherein a tree edit distance between a query tree and a corresponding document tree is a combination of at least one from a set of: node insertion, deletion, and substitution operations. 6. The method of claim 5 , wherein a cost associated with each of the operations is a function of the parsing parameters that created respective nodes associated with the node insertion, deletion, and substitution operations.

9. A vocabulary management server for processing text-to-speech and speech-to-text rendering associated with use of a voice application in progress between a user accessing a data source through a voice portal, the vocabulary management server comprising: a vocabulary set created specific to and associated with the data source, wherein the vocabulary set limits data rendered from the data source by the vocabulary management server, wherein the vocabulary management server further provides user-specific voice recognition options to each user, and wherein the user-specific voice recognition options limit voice recognition options to those options associated with both a particular user and a specific activity being requested by the particular user; and an interface for communicating with a text-to-speech or speech-to-text engine; wherein the server uses the vocabulary set specific to and associated with speech recognition generating dialog for the voice application in progress.

9. A vocabulary management server for processing text-to-speech and speech-to-text rendering associated with use of a voice application in progress between a user accessing a data source through a voice portal, the vocabulary management server comprising: a vocabulary set created specific to and associated with the data source, wherein the vocabulary set limits data rendered from the data source by the vocabulary management server, wherein the vocabulary management server further provides user-specific voice recognition options to each user, and wherein the user-specific voice recognition options limit voice recognition options to those options associated with both a particular user and a specific activity being requested by the particular user; and an interface for communicating with a text-to-speech or speech-to-text engine; wherein the server uses the vocabulary set specific to and associated with speech recognition generating dialog for the voice application in progress. 10. The vocabulary management server of claim 9 wherein the voice portal is an interactive voice response unit operating in a telephony environment.

1. A computer-implemented method, comprising: receiving an image on a device, the device comprising a display device; receiving a text segment on the device; determining a background contrast color; determining a background blend color based on the image; generating a mixed color gradient based on the background contrast color and the background blend color, the mixed color gradient providing a transition from the background contrast color to the background blend color, the transition being a gradient between the background contrast color and the background blend color; positioning the text segment in a text segment display area of the mixed color gradient; generating a combined text segment image display by overlaying the mixed color gradient on the image; and displaying the combined text segment image display on the display device.

1. A computer-implemented method, comprising: receiving an image on a device, the device comprising a display device; receiving a text segment on the device; determining a background contrast color; determining a background blend color based on the image; generating a mixed color gradient based on the background contrast color and the background blend color, the mixed color gradient providing a transition from the background contrast color to the background blend color, the transition being a gradient between the background contrast color and the background blend color; positioning the text segment in a text segment display area of the mixed color gradient; generating a combined text segment image display by overlaying the mixed color gradient on the image; and displaying the combined text segment image display on the display device. 3. The method of claim 1 , wherein the background blend color increases in mixing proportion with the background contrast color in the mixed color gradient with distance from the text segment display area.

13. A method according to claim 12 further comprising: processing the object of the first triple, including one or more of compressing, reformatting or encrypting the object, the representation of the object comprising the processed object or a representation thereof.

13. A method according to claim 12 further comprising: processing the object of the first triple, including one or more of compressing, reformatting or encrypting the object, the representation of the object comprising the processed object or a representation thereof. 14. A method according to claim 13 , wherein the processing the object of the first triple further includes archiving the processed object at a location in storage external to the triple store, the representation of the processed object comprising the storage location.

1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification.

1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification. 9. The method of claim 1 further comprising receiving an approval to allow the recipient of the topic notification to participate in the voice call from one of the first participant and the second participant before joining the recipient to the voice call.

1. A language learning system, for assessing a pronunciation in a learning sentence, the language learning system comprising: a storage module, configured for storing a plurality of training data and at least one assessment decision tree generated according to the training data, wherein the assessment decision tree has a plurality of decision paths, each of the decision paths comprises a plurality of decision nodes and is corresponding to at least one feedback information, and the decision paths and decision nodes on the assessment decision tree represent a specific type of pronunciations having a plurality of predefined types of tones; a feature extraction module, configured for extracting at least one pronunciation feature of the pronunciation, wherein the feature extraction module is further configured for extracting at least one pronunciation feature of each of the training data, wherein the training data has at least one grade mark, a decision tree generation module, configured for generating the assessment decision tree according to the pronunciation features and the grade marks of the training data, a feedback information generation module, configured for analyzing each of the decision paths of the assessment decision tree according to the pronunciation features corresponding to the decision nodes on the decision path to identify incorrect pronunciation types represented by the decision nodes and setting the feedback information corresponding to the decision path according to the incorrect pronunciation types represented by the decision nodes; and an assessment and diagnosis module, is configured for determining a diagnosis path corresponding to the pronunciation among the decision paths of the assessment decision tree according to the pronunciation feature of the pronunciation and outputting the feedback information corresponding to the diagnosis path to correct at least one incorrect pronunciation in the learning sentence.

1. A language learning system, for assessing a pronunciation in a learning sentence, the language learning system comprising: a storage module, configured for storing a plurality of training data and at least one assessment decision tree generated according to the training data, wherein the assessment decision tree has a plurality of decision paths, each of the decision paths comprises a plurality of decision nodes and is corresponding to at least one feedback information, and the decision paths and decision nodes on the assessment decision tree represent a specific type of pronunciations having a plurality of predefined types of tones; a feature extraction module, configured for extracting at least one pronunciation feature of the pronunciation, wherein the feature extraction module is further configured for extracting at least one pronunciation feature of each of the training data, wherein the training data has at least one grade mark, a decision tree generation module, configured for generating the assessment decision tree according to the pronunciation features and the grade marks of the training data, a feedback information generation module, configured for analyzing each of the decision paths of the assessment decision tree according to the pronunciation features corresponding to the decision nodes on the decision path to identify incorrect pronunciation types represented by the decision nodes and setting the feedback information corresponding to the decision path according to the incorrect pronunciation types represented by the decision nodes; and an assessment and diagnosis module, is configured for determining a diagnosis path corresponding to the pronunciation among the decision paths of the assessment decision tree according to the pronunciation feature of the pronunciation and outputting the feedback information corresponding to the diagnosis path to correct at least one incorrect pronunciation in the learning sentence. 2. The language learning system according to claim 1 , wherein the feature extraction module performs a phonetic segmentation operation on a plurality of training sentences to obtain a plurality of pronunciation units of the training sentences, and the feature extraction module obtains the training data from the pronunciation units of the training sentences, wherein the feature extraction module performs the phonetic segmentation operation on the learning sentence to obtain one or more pronunciation units of the learning sentence.

41. The computer program as recited in claim 32 , wherein the code segment for identifying candidate entries comprises a code segment for parsing the electronic document and extracting all possible n-grams that are also present in a controlled vocabulary.

41. The computer program as recited in claim 32 , wherein the code segment for identifying candidate entries comprises a code segment for parsing the electronic document and extracting all possible n-grams that are also present in a controlled vocabulary. 42. The computer program as recited in claim 41 , wherein the controlled vocabulary comprises a collection of at least article titles in an electronic encyclopedia.

48. A computer-readable memory medium according to claim 40 , wherein the computer-readable memory medium further stores a fact database, wherein the fact database includes at least the received factual input, wherein the rule engine accesses the rule library and the fact database to derive a conclusion, and wherein the conclusion derived by the rule engine is the sequence of function modules and sources of parameters used to build the color transformation workflow.

48. A computer-readable memory medium according to claim 40 , wherein the computer-readable memory medium further stores a fact database, wherein the fact database includes at least the received factual input, wherein the rule engine accesses the rule library and the fact database to derive a conclusion, and wherein the conclusion derived by the rule engine is the sequence of function modules and sources of parameters used to build the color transformation workflow. 49. A computer-readable memory medium according to claim 48 , wherein each external rule and each internal rule is at least one of a rule for performing an action and a rule for deducing a consequence of the factual input.

2. A method for data mapping acceleration, the method comprising: generating, by a processor, a syntactic profile of a data source to be mapped; generating a semantic classification of the data source by classifying values for a column of data from the data source by using an ontology that includes hierarchal classes, wherein a class of the hierarchal classes includes an attribute of including a lexical realization, and using classes from the ontology for which the lexical realization of the classes matches a column name of the column of the data; and evaluating the syntactic profile and semantic classification to determine an overall similarity between attributes of the data from the data source for mapping the data source.

2. A method for data mapping acceleration, the method comprising: generating, by a processor, a syntactic profile of a data source to be mapped; generating a semantic classification of the data source by classifying values for a column of data from the data source by using an ontology that includes hierarchal classes, wherein a class of the hierarchal classes includes an attribute of including a lexical realization, and using classes from the ontology for which the lexical realization of the classes matches a column name of the column of the data; and evaluating the syntactic profile and semantic classification to determine an overall similarity between attributes of the data from the data source for mapping the data source. 12. The method of claim 2 , further comprising generating a class vector for a column of the data from the data source to determine the semantic classification.

8. The system of claim 7 , wherein: the one or more computer processors execute the SAM to determine to provide a second indicator to the second ASM based on ascertaining the non-semantic speech characteristic, and determine not to provide the second indicator to the first ASM.

8. The system of claim 7 , wherein: the one or more computer processors execute the SAM to determine to provide a second indicator to the second ASM based on ascertaining the non-semantic speech characteristic, and determine not to provide the second indicator to the first ASM. 9. The system of claim 8 , wherein the one or more computer processors execute the first ASM to receive the first indicator, and perform the functionality for the first particular application in response to receiving the first indicator, and the one or more computer processors execute the second ASM to: receive the second indicator, and perform the functionality for the second particular application in response to receiving the second indicator.

28. A method comprising: receiving (a) information characterizing one or more of an appearance, a voice, or a behavior of a person and (b) information indicative of a relationship between the person and a recipient; inferring an identity of the recipient based on the received information indicative of the relationship between the person and the recipient; and providing a customized natural language response to an input received from the recipient, the providing of the response comprising using a digital representation of the person that is generated based on one or more of the appearance, the voice, or the behavior of the person, in which the person is not alive or not competent when the natural language interaction is conducted.

28. A method comprising: receiving (a) information characterizing one or more of an appearance, a voice, or a behavior of a person and (b) information indicative of a relationship between the person and a recipient; inferring an identity of the recipient based on the received information indicative of the relationship between the person and the recipient; and providing a customized natural language response to an input received from the recipient, the providing of the response comprising using a digital representation of the person that is generated based on one or more of the appearance, the voice, or the behavior of the person, in which the person is not alive or not competent when the natural language interaction is conducted. 30. The method of claim 28 , comprising determining a context of the natural language response based on one or more of (a) one or more of the appearance, the voice, or the behavior of the person, (b) information about a time period during which the person lived, or (c) autobiographical information about the person.

10. In computer-implemented apparatus, the apparatus having a processor and a memory, the memory having computer executable instructions stored therein, a method for recommending an item to a particular one of a plurality of users, the item not yet rated by the user, the method comprising steps, performed through the executable instructions, of: (a) generating, for the particular one user, a concept mask representing areas of interest of the one user; (b) storing, in the memory, a user profile in a memory for each of a plurality of users, wherein the user profile of the user includes a plurality of values, each of the plurality of values representing a rating given to one of a plurality of items by the user; (c) calculating, for each of the plurality of users, a plurality of similarity factor vectors representing the similarity between each user and another one of the plurality of users for at least one concept specified within the concept mask; (d) selecting, for each of the plurality of users, a plurality of neighboring users based on the similarity factor vectors; (e) assigning a weight to each of the neighboring users so as to define a plurality of weights assigned to the neighboring users; and (f) recommending at least one of the plurality of items to the particular one user based on the weights assigned to the neighboring users and the ratings given to the non-rated item by the neighboring users.

10. In computer-implemented apparatus, the apparatus having a processor and a memory, the memory having computer executable instructions stored therein, a method for recommending an item to a particular one of a plurality of users, the item not yet rated by the user, the method comprising steps, performed through the executable instructions, of: (a) generating, for the particular one user, a concept mask representing areas of interest of the one user; (b) storing, in the memory, a user profile in a memory for each of a plurality of users, wherein the user profile of the user includes a plurality of values, each of the plurality of values representing a rating given to one of a plurality of items by the user; (c) calculating, for each of the plurality of users, a plurality of similarity factor vectors representing the similarity between each user and another one of the plurality of users for at least one concept specified within the concept mask; (d) selecting, for each of the plurality of users, a plurality of neighboring users based on the similarity factor vectors; (e) assigning a weight to each of the neighboring users so as to define a plurality of weights assigned to the neighboring users; and (f) recommending at least one of the plurality of items to the particular one user based on the weights assigned to the neighboring users and the ratings given to the non-rated item by the neighboring users. 16. The method of claim 10 wherein the concept mask includes concepts which have a value which exceeds a predetermined threshold.

23. The computer-implemented method for building a user profile of claim 16 , further comprising assigning a value index to the user, wherein the value index is based on the user profile of the user and a user profile of at least one other user, and wherein the value index assigned to the user dynamically changes based upon subsequent user activity.

23. The computer-implemented method for building a user profile of claim 16 , further comprising assigning a value index to the user, wherein the value index is based on the user profile of the user and a user profile of at least one other user, and wherein the value index assigned to the user dynamically changes based upon subsequent user activity. 29. The computer-implemented method for building a user profile of claim 23 , wherein the subsequent user activity includes at least one of sharing the user's interests, clicking on a newsletter, participating in a discussion, reading or writing a blog, downloading a white paper, purchasing a product or a service, reviewing a product or service, sharing a document, posting to a social network, sending an email, and disclosing information about the user.

1. A system for saving digital content classified by person-based clustering, comprising: a database located on a non-transitory computer readable medium to save a plurality of digital content classified by person-based clustering; a data structure generation unit located on the non-transitory computer readable medium to generate a data structure including a plurality of nodes using the plurality of digital content; a face recognition unit located on the non-transitory computer readable medium to extract a face descriptor of new digital content to be saved in the database; a cluster classification unit located on the non-transitory computer readable medium to classify the new digital content and the plurality of digital content by the person-based clustering using the extracted face descriptor; and a data structure update unit located on the non-transitory computer readable medium to update the data structure according to the classification.

1. A system for saving digital content classified by person-based clustering, comprising: a database located on a non-transitory computer readable medium to save a plurality of digital content classified by person-based clustering; a data structure generation unit located on the non-transitory computer readable medium to generate a data structure including a plurality of nodes using the plurality of digital content; a face recognition unit located on the non-transitory computer readable medium to extract a face descriptor of new digital content to be saved in the database; a cluster classification unit located on the non-transitory computer readable medium to classify the new digital content and the plurality of digital content by the person-based clustering using the extracted face descriptor; and a data structure update unit located on the non-transitory computer readable medium to update the data structure according to the classification. 6. The system of claim 1 , wherein the data structure is a two-dimensional linked list data structure that comprises person nodes linked together by persons and face nodes linked to the person nodes to save face information of the digital content that is determined to be the same face.

7. The method of claim 1 , wherein the electronic document comprises a link to a legitimacy rating document, wherein the legitimacy rating document comprises additional legitimacy rating information.

7. The method of claim 1 , wherein the electronic document comprises a link to a legitimacy rating document, wherein the legitimacy rating document comprises additional legitimacy rating information. 9. The method of claim 7 , wherein the additional legitimacy rating information comprises a metric corresponding to a number of users who have provided negative feedback about the content source.

11. A system comprising: a processor of a machine; a template generation module configured to generate, using the processor of the machine, a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; a user interface module configured to receive a content item from a first user of a group of users designated as contributors to the publication the user interface module further configured to receive, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and a generation module configured to generate the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user.

11. A system comprising: a processor of a machine; a template generation module configured to generate, using the processor of the machine, a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; a user interface module configured to receive a content item from a first user of a group of users designated as contributors to the publication the user interface module further configured to receive, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and a generation module configured to generate the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user. 14. The system of claim 11 , wherein the group of users designated as contributors to the publication is defined by contribution privilege information associated with the template, the contribution privilege information specifying a manner in which each member of the group of users may contribute to each element of the publication.

14. The system of claim 13 , wherein the processor counts the number of N-grams that correspond to the one or more states in the string of bytes when collecting the statistical information.

14. The system of claim 13 , wherein the processor counts the number of N-grams that correspond to the one or more states in the string of bytes when collecting the statistical information. 15. The system of claim 14 , wherein another model is generated when the number of N-grams counted is equal to or greater than a predetermined number.

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.

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. 23. The system of claim 22 , wherein the activity recognition device is further configured to generate an action prediction based on the mapping and the nodes of the at least one of the known activity graphs.

12. A computer-implemented method of screening a database of molecules to identify leads for treating a disease, the method comprising: presenting on at least one computer display a first user interface configured to receive ASCII structural descriptions of a set of input ligands and to receive binding affinity data for the set of input ligands for a protein target known to be associated with the disease; receiving the ASCII structural descriptions of the set of input ligands and the binding affinity data via the first user interface; generating, from alignment data for the ASCII structural descriptions of a set of input ligands and from the binding affinity data for the set of input ligands for a target protein, a profile comprising ASCII descriptions of one or more patches in the set of input ligands; identifying, using a computer, a set of one or more leads for treating the disease from a database, the identifying based at least in part on the profile, wherein the database comprises ASCII structural descriptions of a plurality of molecules, the ASCII structural descriptions of the plurality of molecules comprising force field information for one or more atoms described in the ASCII structural descriptions of the plurality of molecules, the identifying comprising comparing the ASCII structural descriptions of the plurality of molecules with the ASCII structural descriptions of the one or more patches, the ASCII structural descriptions of the one or more leads for treating the disease comprising the ASCII structural description of at least one of the one or more patches; receiving a list of the set of one or more leads for treating the disease from the computer; displaying a second user interface on the at least one computer display; and displaying the list of the set of one or more leads for treating the disease in the second user interface.

12. A computer-implemented method of screening a database of molecules to identify leads for treating a disease, the method comprising: presenting on at least one computer display a first user interface configured to receive ASCII structural descriptions of a set of input ligands and to receive binding affinity data for the set of input ligands for a protein target known to be associated with the disease; receiving the ASCII structural descriptions of the set of input ligands and the binding affinity data via the first user interface; generating, from alignment data for the ASCII structural descriptions of a set of input ligands and from the binding affinity data for the set of input ligands for a target protein, a profile comprising ASCII descriptions of one or more patches in the set of input ligands; identifying, using a computer, a set of one or more leads for treating the disease from a database, the identifying based at least in part on the profile, wherein the database comprises ASCII structural descriptions of a plurality of molecules, the ASCII structural descriptions of the plurality of molecules comprising force field information for one or more atoms described in the ASCII structural descriptions of the plurality of molecules, the identifying comprising comparing the ASCII structural descriptions of the plurality of molecules with the ASCII structural descriptions of the one or more patches, the ASCII structural descriptions of the one or more leads for treating the disease comprising the ASCII structural description of at least one of the one or more patches; receiving a list of the set of one or more leads for treating the disease from the computer; displaying a second user interface on the at least one computer display; and displaying the list of the set of one or more leads for treating the disease in the second user interface. 17. The computer-implemented method of claim 12 , further comprising displaying a third user interface configured to receive a graphical description of one or more chemical compounds.

24. A device embedded in an apparatus for reporting a state of the apparatus to a remote computer, the device comprising circuitry configured to: detect the state of the apparatus; generate a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, the message using eXtensible Markup Language (XML) to report the state, and the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and send the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using XML; wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot communicate to the device to obtain the state of the apparatus; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus.

24. A device embedded in an apparatus for reporting a state of the apparatus to a remote computer, the device comprising circuitry configured to: detect the state of the apparatus; generate a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, the message using eXtensible Markup Language (XML) to report the state, and the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and send the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using XML; wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot communicate to the device to obtain the state of the apparatus; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus. 29. The device of claim 24 , further comprising queuing the message in the device prior to sending the message, the message being sent following a failure condition in a system comprising the device and/or the apparatus.

9. A method for triggering a sub-word unit recognition comprising: drawing one or more strokes of a desired sub-word unit using a stylus on a touch screen, wherein one of the drawn one or more strokes is a first head-line stroke and is a last drawn stroke in the drawn one or more strokes of the desired sub-word unit; inputting an associated data of the drawn one or more strokes via the touch screen into a handwriting recognition engine; computing stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope; determining a first trigger stroke in the drawn one or more strokes of the desired sub-word unit that can be used to trigger the sub-word unit recognition based as a function of the computed stroke recognition characteristics of each of the multiple drawn strokes, wherein the first trigger stroke is the first head-line stroke which is drawn substantially parallel to the horizontal reference line; and triggering sub-word unit recognition for the drawn one or more strokes by the handwriting recognition engine upon determining the first trigger stroke.

9. A method for triggering a sub-word unit recognition comprising: drawing one or more strokes of a desired sub-word unit using a stylus on a touch screen, wherein one of the drawn one or more strokes is a first head-line stroke and is a last drawn stroke in the drawn one or more strokes of the desired sub-word unit; inputting an associated data of the drawn one or more strokes via the touch screen into a handwriting recognition engine; computing stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope; determining a first trigger stroke in the drawn one or more strokes of the desired sub-word unit that can be used to trigger the sub-word unit recognition based as a function of the computed stroke recognition characteristics of each of the multiple drawn strokes, wherein the first trigger stroke is the first head-line stroke which is drawn substantially parallel to the horizontal reference line; and triggering sub-word unit recognition for the drawn one or more strokes by the handwriting recognition engine upon determining the first trigger stroke. 12. The method of claim 9 , further comprising: repeating the drawing, inputting, triggering, producing, and outputting steps to enter a next sub-word unit.

22. A non-transitory computer readable recording medium storing a similarity calculation program for obtaining similarity between media data and a query, the program causing a computer to execute: a function for calculating a single score a that shows similarity between the text query and second meta text of a second media data by comparing the text query with the second meta text, the second meta text including a plurality of words describing contents of the second media data; a function for calculating inter-media similarity that shows similarity between the first meta text of the first media data and the second meta text of the second media data by comparing the plurality of words of the first meta text of the first media data with the plurality of words of the second meta text of the second media data; a function for obtaining the similarity between the first media data and the text query by using the inter-media similarity and the single score, a function of creating meta text including the first meta text and the second meta text based on the first media data and the second media data, respectively, wherein the first meta text includes an error, and the second meta text includes fewer errors than the first meta text; a function of calculating a creating difficulty of a text that is same as the text query with the meta text creating device; a function of calculating the similarity between the first media data and the text query by using the inter-media similarity and the single scores of the second media data as well as the creating difficulty; a function of creating the meta text by using a dictionary; and a function of calculating the creating difficulty as large, when the text query is an unknown word that is not registered to the dictionary.

22. A non-transitory computer readable recording medium storing a similarity calculation program for obtaining similarity between media data and a query, the program causing a computer to execute: a function for calculating a single score a that shows similarity between the text query and second meta text of a second media data by comparing the text query with the second meta text, the second meta text including a plurality of words describing contents of the second media data; a function for calculating inter-media similarity that shows similarity between the first meta text of the first media data and the second meta text of the second media data by comparing the plurality of words of the first meta text of the first media data with the plurality of words of the second meta text of the second media data; a function for obtaining the similarity between the first media data and the text query by using the inter-media similarity and the single score, a function of creating meta text including the first meta text and the second meta text based on the first media data and the second media data, respectively, wherein the first meta text includes an error, and the second meta text includes fewer errors than the first meta text; a function of calculating a creating difficulty of a text that is same as the text query with the meta text creating device; a function of calculating the similarity between the first media data and the text query by using the inter-media similarity and the single scores of the second media data as well as the creating difficulty; a function of creating the meta text by using a dictionary; and a function of calculating the creating difficulty as large, when the text query is an unknown word that is not registered to the dictionary. 28. The non-transitory computer readable recording medium storing the similarity calculation program as claimed in claim 22 , which enables the computer to execute a function of creating the meta text by putting image data that is the media data into a text by image recognition or character recognition.

10. The system of claim 1 including: a second deflection rod connected to the mount of the first horizontal rod, the second deflection rod having a sixth end extending away from the mount substantially parallel to the first horizontal rod in the opposite direction than the fifth end of the first deflection rod.

10. The system of claim 1 including: a second deflection rod connected to the mount of the first horizontal rod, the second deflection rod having a sixth end extending away from the mount substantially parallel to the first horizontal rod in the opposite direction than the fifth end of the first deflection rod. 14. The system of claim 10 , wherein said first rod has a first diameter that decreases in a first direction away from said mount and said second rod has a second diameter that decreases in a second direction away from said mount and said first and second directions are opposite to each other.

7. The method of claim 5 and further comprising: defining a behavior for the mapped interface member.

7. The method of claim 5 and further comprising: defining a behavior for the mapped interface member. 8. The method of claim 7 wherein the skeleton source code is generated to represent an action that is applicable given the defined behavior and a known characteristic of the mapped interface member.

14. An apparatus for facilitating computer-assisted comprehension of texts, the apparatus comprising: a microprocessor; and machine-readable storage medium coupled with the microprocessor, the machine-readable storage medium encoded with instructions executable by the microprocessor, the instructions configured to; determine a plurality of expressions in a document presented in a document viewing application, wherein the document includes at least one occurrence of each of the plurality of expressions; calculate a difficulty index for each of the plurality of expressions based, at least in part, on frequency of occurrence of the expression in the document, wherein a lower frequency of occurrence estimates a greater comprehension difficulty; determine a set of the plurality of expressions that have difficulty indices that exceed a threshold value; associate each of the set of the plurality of expressions with a corresponding explanation; and supply for display an indication of the corresponding explanation of each of the set of the plurality of expressions in a part of the document being displayed; determine a frequency of occurrence of a second plurality of expressions in a plurality of sample documents, wherein each of the second plurality of expressions occurs at least once in the plurality of sample documents; calculate an initial difficulty index, for each of the second plurality of expressions, that estimates comprehension difficulty for each of the second plurality of expressions, wherein the initial difficult index is calculated based, at least in part, on the frequency of occurrence of the second plurality of expressions in the plurality of sample documents; and wherein the instructions to calculate the difficulty index for each of the plurality of expressions comprises instructions to update the initial difficulty index, for each of those of the plurality of expressions also in the second plurality of expressions, based on the frequency of occurrence of the expression in the document.

14. An apparatus for facilitating computer-assisted comprehension of texts, the apparatus comprising: a microprocessor; and machine-readable storage medium coupled with the microprocessor, the machine-readable storage medium encoded with instructions executable by the microprocessor, the instructions configured to; determine a plurality of expressions in a document presented in a document viewing application, wherein the document includes at least one occurrence of each of the plurality of expressions; calculate a difficulty index for each of the plurality of expressions based, at least in part, on frequency of occurrence of the expression in the document, wherein a lower frequency of occurrence estimates a greater comprehension difficulty; determine a set of the plurality of expressions that have difficulty indices that exceed a threshold value; associate each of the set of the plurality of expressions with a corresponding explanation; and supply for display an indication of the corresponding explanation of each of the set of the plurality of expressions in a part of the document being displayed; determine a frequency of occurrence of a second plurality of expressions in a plurality of sample documents, wherein each of the second plurality of expressions occurs at least once in the plurality of sample documents; calculate an initial difficulty index, for each of the second plurality of expressions, that estimates comprehension difficulty for each of the second plurality of expressions, wherein the initial difficult index is calculated based, at least in part, on the frequency of occurrence of the second plurality of expressions in the plurality of sample documents; and wherein the instructions to calculate the difficulty index for each of the plurality of expressions comprises instructions to update the initial difficulty index, for each of those of the plurality of expressions also in the second plurality of expressions, based on the frequency of occurrence of the expression in the document. 16. The apparatus of claim 14 , wherein the instructions to associate each of the set of the plurality of expressions with the corresponding explanation comprises instructions to access at least one of a dictionary and a translation service.

9. The system of claim 1 , further comprising a database of recorded audio pieces the speech synthesizer can use and concatenate together to synthesize speech, wherein the database of recorded audio pieces includes audio pieces of non-lexical cues.

9. The system of claim 1 , further comprising a database of recorded audio pieces the speech synthesizer can use and concatenate together to synthesize speech, wherein the database of recorded audio pieces includes audio pieces of non-lexical cues. 10. The system of claim 9 , wherein the audio pieces of non-lexical cues in the database include at least one audio piece of a parasitic lexical cue that is a varied form of another audio piece in the database, wherein the varied form comprises one or more of a phrasal stress, an intonation, or a lengthening of at least a portion of the another audio piece.

2. The method of claim 1 wherein determining the at least one concept related to the search query comprises: accessing a concept knowledge base having a plurality of concept data objects and a plurality of term data objects associated with at least one of the plurality of concept data objects; matching at least one of the at least one search term with at least one of the plurality of term data objects to generate a first term set containing term data objects from the concept knowledge base that match the at least one search term; and generating a concept set containing at least one concept data object associated with one or more of the term data objects in the first term set.

2. The method of claim 1 wherein determining the at least one concept related to the search query comprises: accessing a concept knowledge base having a plurality of concept data objects and a plurality of term data objects associated with at least one of the plurality of concept data objects; matching at least one of the at least one search term with at least one of the plurality of term data objects to generate a first term set containing term data objects from the concept knowledge base that match the at least one search term; and generating a concept set containing at least one concept data object associated with one or more of the term data objects in the first term set. 3. The method of claim 2 further comprising: generating a concept vector for each concept data object in the concept set, the concept vector comprising a dimension for each term data object associated with the concept data object, a magnitude of the dimension based on a weight of the association of the term data object with the concept data object; and generating a document vector for the at least one returned document, the document vector comprising a dimension for each of a plurality of terms in the document, a magnitude of the dimension based on a frequency of occurrence of each of the plurality of terms; wherein evaluating the similarity between the at least one returned document and the at least one concept is based on a fuzzy membership score determined by comparing the concept vector to the document vector.

14. A method as claimed in claim 1 , wherein said rules include a reference count representing the number of other rules that reference the rule.

14. A method as claimed in claim 1 , wherein said rules include a reference count representing the number of other rules that reference the rule. 15. A method as claimed in claim 14 , wherein said additional rules are determined on the basis of attribute constraints representing a correlation between slots of a rule and slots of said observations during said creating step.

13. The system of claim 12 , further comprising instructions for: identifying one or more web results relevant to the visual query and to the geographic location of the client system; and sending the web results to the client system.

13. The system of claim 12 , further comprising instructions for: identifying one or more web results relevant to the visual query and to the geographic location of the client system; and sending the web results to the client system. 14. The system of claim 13 , wherein the instructions for identifying one or more web results relevant to the visual query and to the geographic location of the client system comprises instructions for: identifying a geographic term within the one or more high quality textual strings; identifying one or more web results associated with both the geographic term and the geographic location of the client system.

14. The system of claim 13 , wherein the application is a web-browser application.

14. The system of claim 13 , wherein the application is a web-browser application. 16. The system of claim 14 , wherein the first dialog code is configured to cause the dialog to be displayed on the client when executed in the web browser.

9. A system for presenting facts, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions for: receiving responsive objects from a fact repository responsive to a search query submitted to the fact repository by a user, wherein a respective responsive object has associated facts, wherein a respective fact includes an attribute field indicating an attribute, a value field describing the indicated attribute; presenting the responsive objects to an end-user in a first user interface, wherein the first user interface displays each responsive object with one or more representative facts, the representative facts selected based on a metric that includes an importance score and a confidence score; saving a subset of the responsive objects as a user-identified collection responsive to selection of the objects in the subset by the user for inclusion in the user-identified collection; presenting the subset of the responsive objects to the end-user in a second user-interface, the second user interface including initial facts for the subset of the responsive objects, the initial facts being attributes most common among the subset of the responsive objects; receiving an end-user-selection of a first attribute of the initial facts displayed in the second user interface, the selection indicating an intent from the end-user to graph values of facts having the first attribute for responsive objects; automatically, without end-user interaction, determining a type of graph showing the values for the first attribute that best facilitates interpretation of the values by the end-user; automatically, without end-user interaction, generating the determined type of graph for objects in the user-identified collection; and presenting via the user interface the determined type of graph.

9. A system for presenting facts, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions for: receiving responsive objects from a fact repository responsive to a search query submitted to the fact repository by a user, wherein a respective responsive object has associated facts, wherein a respective fact includes an attribute field indicating an attribute, a value field describing the indicated attribute; presenting the responsive objects to an end-user in a first user interface, wherein the first user interface displays each responsive object with one or more representative facts, the representative facts selected based on a metric that includes an importance score and a confidence score; saving a subset of the responsive objects as a user-identified collection responsive to selection of the objects in the subset by the user for inclusion in the user-identified collection; presenting the subset of the responsive objects to the end-user in a second user-interface, the second user interface including initial facts for the subset of the responsive objects, the initial facts being attributes most common among the subset of the responsive objects; receiving an end-user-selection of a first attribute of the initial facts displayed in the second user interface, the selection indicating an intent from the end-user to graph values of facts having the first attribute for responsive objects; automatically, without end-user interaction, determining a type of graph showing the values for the first attribute that best facilitates interpretation of the values by the end-user; automatically, without end-user interaction, generating the determined type of graph for objects in the user-identified collection; and presenting via the user interface the determined type of graph. 11. The system of claim 9 , wherein a format of a value of a fact being graphed is one consideration in automatically determining of the type of graph that best facilitates interpretation of the facts by the end-user.

1. A computer-implemented method of determining a language intent of a user submitted query, the method comprising: receiving a user query comprising text and a user location; identifying at least one language usage signal based on the text of the user query, wherein the at least one language usage signal is associated with a first language; identifying a second language associated with the user location; generating a translation of the text of the user query from the first language to the second language; determining a strength of the at least one language usage signal based on an amount of variation between the text of the user query and the translation of the text of the user query, wherein the strength of the at least one language usage signal increases as the amount of variation between the text of the user query and the translation of the text of the user query increases; selecting, when the strength of the at least one language usage signal is greater than a predetermined threshold, the first language as the output language in which results of the user query are returned, based on the language usage signal; and returning the results for the query according to the output language.

1. A computer-implemented method of determining a language intent of a user submitted query, the method comprising: receiving a user query comprising text and a user location; identifying at least one language usage signal based on the text of the user query, wherein the at least one language usage signal is associated with a first language; identifying a second language associated with the user location; generating a translation of the text of the user query from the first language to the second language; determining a strength of the at least one language usage signal based on an amount of variation between the text of the user query and the translation of the text of the user query, wherein the strength of the at least one language usage signal increases as the amount of variation between the text of the user query and the translation of the text of the user query increases; selecting, when the strength of the at least one language usage signal is greater than a predetermined threshold, the first language as the output language in which results of the user query are returned, based on the language usage signal; and returning the results for the query according to the output language. 4. The method of claim 1 , wherein the identifying of the at least one language usage signal from the text of the user query is based on at least one of a usage of different languages for common terms or a usage of different geographically biased proper terms.

5. The computing system of claim 1 , wherein provide a notification of the message collection comprises provide a visual notification on a personal computing device, the visual notification indicating that the message collection is available for viewing and information about the message collection, including number of messages, a theme of the message collection, and the modalities associated with messages in the message collection.

5. The computing system of claim 1 , wherein provide a notification of the message collection comprises provide a visual notification on a personal computing device, the visual notification indicating that the message collection is available for viewing and information about the message collection, including number of messages, a theme of the message collection, and the modalities associated with messages in the message collection. 6. The computing system of claim 5 , wherein the visual notification is selectable using an input device, and wherein the message collection is displayed in response to selection of the visual notification by the user.

1. A computer-implemented method comprising: receiving, from a given user and by a microphone of a mobile device that includes (i) the microphone, (ii) an automated speech recognition system, and (iii) an end of utterance detector that is configured to identify an endpoint of an utterance spoken by a user in response to determining that a speaker has stopped speaking for a fixed duration, a first utterance; determining, by the end of utterance detector, that the given user has stopped speaking for the fixed duration after the first utterance; generating, by the automated speech recognition system, a first transcription of the first utterance; based on the first transcription of the first utterance, maintaining the microphone in an active state without endpointing the first utterance; after the given user has stopped speaking for at least the fixed duration after the first utterance, receiving, by the microphone and from the given user, a second utterance; generating, by the automated speech recognition system, a second transcription of the second utterance; based on both the first transcription and the second transcription, deactivating the microphone and endpointing the second utterance; in response to endpointing the second utterance, submitting, by the mobile device, a single search query that includes both the first transcription and the second transcription; receiving, by the mobile device, search results in response to the single search query that includes both the first transcription and the second transcription; and providing, for output by the mobile device, the search results.

1. A computer-implemented method comprising: receiving, from a given user and by a microphone of a mobile device that includes (i) the microphone, (ii) an automated speech recognition system, and (iii) an end of utterance detector that is configured to identify an endpoint of an utterance spoken by a user in response to determining that a speaker has stopped speaking for a fixed duration, a first utterance; determining, by the end of utterance detector, that the given user has stopped speaking for the fixed duration after the first utterance; generating, by the automated speech recognition system, a first transcription of the first utterance; based on the first transcription of the first utterance, maintaining the microphone in an active state without endpointing the first utterance; after the given user has stopped speaking for at least the fixed duration after the first utterance, receiving, by the microphone and from the given user, a second utterance; generating, by the automated speech recognition system, a second transcription of the second utterance; based on both the first transcription and the second transcription, deactivating the microphone and endpointing the second utterance; in response to endpointing the second utterance, submitting, by the mobile device, a single search query that includes both the first transcription and the second transcription; receiving, by the mobile device, search results in response to the single search query that includes both the first transcription and the second transcription; and providing, for output by the mobile device, the search results. 4. The method of claim 1 , comprising: after the given user has stopped speaking for longer than the fixed duration after the end of the first utterance and before the given user speaks the second utterance, updating a user interface to include the first transcription.

1. At a computer system comprising at least one processor operatively coupled to a system memory, a method for combining a mixture of semantic behaviors across a single computer program source code, the method comprising: an act of a computer system, which includes at least one processor, acquiring computer program source code; an act of the computer system receiving a first user interface gesture explicitly specifying a first region of the computer program source code that is to be statically bound; an act of the computer system visually and syntactically indicating that the first region of the computer program source code is to be statically bound by inserting a first syntactical identifier into the computer program source code that syntactically delimits the first region of the computer program source code; an act of the computer system receiving a second user interface gesture explicitly specifying a second region of the computer program source code that is hierarchically nested within the first region and that is to override a semantic behavior of the first region by being late bound; an act of the computer system visually and syntactically indicating that the second region of the computer program source code is to be late bound by inserting a second syntactical identifier into the computer program source code that syntactically delimits the second region of the computer program source code; an act of the computer system processing the computer program source code, including: the computer system identifying that at least a portion of the first region of the computer program source code is to be statically bound based on the first syntactical identifier; the computer system identifying that the second region of the computer program source code is to be late bound based on the second syntactical identifier; the computer system applying static binding to the portion of the first region of the computer program source code and applying late binding to the second region of the computer program source code; and the computer system transforming the computer program source code into a target language.

1. At a computer system comprising at least one processor operatively coupled to a system memory, a method for combining a mixture of semantic behaviors across a single computer program source code, the method comprising: an act of a computer system, which includes at least one processor, acquiring computer program source code; an act of the computer system receiving a first user interface gesture explicitly specifying a first region of the computer program source code that is to be statically bound; an act of the computer system visually and syntactically indicating that the first region of the computer program source code is to be statically bound by inserting a first syntactical identifier into the computer program source code that syntactically delimits the first region of the computer program source code; an act of the computer system receiving a second user interface gesture explicitly specifying a second region of the computer program source code that is hierarchically nested within the first region and that is to override a semantic behavior of the first region by being late bound; an act of the computer system visually and syntactically indicating that the second region of the computer program source code is to be late bound by inserting a second syntactical identifier into the computer program source code that syntactically delimits the second region of the computer program source code; an act of the computer system processing the computer program source code, including: the computer system identifying that at least a portion of the first region of the computer program source code is to be statically bound based on the first syntactical identifier; the computer system identifying that the second region of the computer program source code is to be late bound based on the second syntactical identifier; the computer system applying static binding to the portion of the first region of the computer program source code and applying late binding to the second region of the computer program source code; and the computer system transforming the computer program source code into a target language. 14. The computer system of claim 1 , wherein visually indicating that the first region of the computer program source code is to be statically bound comprises using a first combination of one or more colors, background highlighting, fonts, font sizes, italics, or bolding, and wherein visually indicating that the second region of the computer program source code is to be late bound comprises using a second combination of one or more colors, background highlighting, fonts, font sizes, italics, or bolding.

13. A system, comprising: at least one processor; a memory device including instructions operable to be executed by the at least one processor to configure the system to: receive audio data; identify a first representation of a first finite state transducer (FST) for automatic speech recognition (ASR), the FST configured to be traversed using input words and to output words, the first representation including: a first table representing states of the first FST, the first table including a first record representing a first state, the first record comprising: a first representation of a weight of the first state, and a reference to a second record in a second table, the second record representing a first arc; the second table representing arcs of the first FST, the second table including the second record, the second record comprising: a second representation of a weight of the first arc, a 12 bit representation of the weight of the first arc, a third representation of an input/output label pair, and an identifier of a destination state of the first arc; and identify a second representation of a second FST, wherein the second FST is an FST configured to be traversed using acoustic unit data and to output words; load the first representation of the first FST into a memory; load the second representation of the second FST into the memory; perform ASR on a first portion of the audio data using the first record and the second record; determine an output label using the third representation of the input/output label pair; and determine ASR output using the output label.

13. A system, comprising: at least one processor; a memory device including instructions operable to be executed by the at least one processor to configure the system to: receive audio data; identify a first representation of a first finite state transducer (FST) for automatic speech recognition (ASR), the FST configured to be traversed using input words and to output words, the first representation including: a first table representing states of the first FST, the first table including a first record representing a first state, the first record comprising: a first representation of a weight of the first state, and a reference to a second record in a second table, the second record representing a first arc; the second table representing arcs of the first FST, the second table including the second record, the second record comprising: a second representation of a weight of the first arc, a 12 bit representation of the weight of the first arc, a third representation of an input/output label pair, and an identifier of a destination state of the first arc; and identify a second representation of a second FST, wherein the second FST is an FST configured to be traversed using acoustic unit data and to output words; load the first representation of the first FST into a memory; load the second representation of the second FST into the memory; perform ASR on a first portion of the audio data using the first record and the second record; determine an output label using the third representation of the input/output label pair; and determine ASR output using the output label. 18. The system of claim 13 , wherein the memory device further comprises instructions that further configure the system to: configure the first table to further comprise a fourth record corresponding to a third state, the fourth record including a bit indicating that information about the third state is available outside the first table; and configure the representation to further include the information about the third state, the information comprising: a fourth representation of a weight of the third state, a second reference to a fifth record in the second table, the fifth record representing a second arc, the second arc outgoing from the second state in the FST, first data representing a number of arcs associated with the third state that have a blank input label, and second data representing a number of arcs associated with the third state that have a blank output label.

1. A method for natural language processing on a computing device, comprising: receiving a free text document; parsing, on a computing device, the free text document for gross structure, wherein the gross structure comprises sections, paragraphs and sentences; determining, on the computing device, an application of at least one knowledge base; parsing the free text document for fine structure on the computing device, wherein the fine structure comprises sub-sentences; applying, on the computing device, the parsed document and at least one likelihood vector to a Bayesian network, wherein applying the parsed document and the at least one likelihood vector to the Bayesian network comprises: identifying, on the computing device, possible sets of word-level network assignments for lowest-level phrases in a parse tree; identifying, on the computing device, assignments that have multiple different potential assignments; creating, on the computing device, likelihood vectors for all nodes of the Bayesian network, wherein the likelihood vectors cover all potential assignments; instantiating the likelihood vectors on the computing device; identifying, on the computing device, optimal null assignments for unassigned word-level nodes; and selecting, on the computing device, the highest probability state for each node to obtain an interpretation of the free text document; and outputting meanings and probabilities from the computing device.

1. A method for natural language processing on a computing device, comprising: receiving a free text document; parsing, on a computing device, the free text document for gross structure, wherein the gross structure comprises sections, paragraphs and sentences; determining, on the computing device, an application of at least one knowledge base; parsing the free text document for fine structure on the computing device, wherein the fine structure comprises sub-sentences; applying, on the computing device, the parsed document and at least one likelihood vector to a Bayesian network, wherein applying the parsed document and the at least one likelihood vector to the Bayesian network comprises: identifying, on the computing device, possible sets of word-level network assignments for lowest-level phrases in a parse tree; identifying, on the computing device, assignments that have multiple different potential assignments; creating, on the computing device, likelihood vectors for all nodes of the Bayesian network, wherein the likelihood vectors cover all potential assignments; instantiating the likelihood vectors on the computing device; identifying, on the computing device, optimal null assignments for unassigned word-level nodes; and selecting, on the computing device, the highest probability state for each node to obtain an interpretation of the free text document; and outputting meanings and probabilities from the computing device. 4. The method of claim 1 , further comprising encoding, on the computing device, at least one portion of the free text based on the meanings and probabilities.

2. The method of claim 1 wherein the unknown word repository is a sending client unknown word repository that corresponds to the sending client, the method further comprising: in response to determining that the unknown word is not included in the unknown word repository, retrieving a recipient client unknown word repository that corresponds to the recipient client; determining whether the unknown word is included in the recipient client unknown word repository, wherein each unknown word included in the recipient client unknown word repository corresponds to a plurality of recipient client definitions; in response to determining that the unknown word is included in the recipient client unknown word repository, selecting one of the plurality of recipient client definitions that corresponds to the unknown word, wherein the selection is based upon the identified common social networking group; and displaying the selected recipient client definition at the recipient client.

2. The method of claim 1 wherein the unknown word repository is a sending client unknown word repository that corresponds to the sending client, the method further comprising: in response to determining that the unknown word is not included in the unknown word repository, retrieving a recipient client unknown word repository that corresponds to the recipient client; determining whether the unknown word is included in the recipient client unknown word repository, wherein each unknown word included in the recipient client unknown word repository corresponds to a plurality of recipient client definitions; in response to determining that the unknown word is included in the recipient client unknown word repository, selecting one of the plurality of recipient client definitions that corresponds to the unknown word, wherein the selection is based upon the identified common social networking group; and displaying the selected recipient client definition at the recipient client. 4. The method of claim 2 further comprising: in response to determining that the unknown word is not included in the recipient client unknown word repository, identifying a mutual client that is included in the identified common social networking group; receiving a mutual client unknown word repository that corresponds to the mutual client; determining whether the unknown word is included in the mutual client unknown word repository, wherein each unknown word included in the mutual client unknown word repository corresponds to a plurality of mutual client definitions; in response to determining that the unknown word is included in the mutual client unknown word repository, selecting one of the plurality of mutual client definitions that corresponds to the unknown word, wherein the selection is based upon the identified common social networking group; and displaying the selected mutual client definition at the recipient client.

1. A system comprising: one or more computers including one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair.

1. A system comprising: one or more computers including one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair. 5. The system of claim 1 , wherein the context term of each name-context pair is identified from a window of text associated with the entity name of the name-context pair.

1. A method, comprising: storing first data representing a semantic network, the semantic network representing a plurality of nodes, and a plurality of links interconnecting the nodes such that, for each of the links, one of the nodes is a subject node of the link, another of the nodes is a target node of the link, and the respective link represents a verb between the corresponding subject and target nodes, at least some of the links each being conditioned by at least one variant; receiving second data representing one or more of the variants; determining, by a computer, a portion of the semantic network that contains fewer links than the semantic network depending upon which of the variants are included in the second data and which of the variants condition the at least some of the links; and generating third data based on the determined portion of the semantic network.

1. A method, comprising: storing first data representing a semantic network, the semantic network representing a plurality of nodes, and a plurality of links interconnecting the nodes such that, for each of the links, one of the nodes is a subject node of the link, another of the nodes is a target node of the link, and the respective link represents a verb between the corresponding subject and target nodes, at least some of the links each being conditioned by at least one variant; receiving second data representing one or more of the variants; determining, by a computer, a portion of the semantic network that contains fewer links than the semantic network depending upon which of the variants are included in the second data and which of the variants condition the at least some of the links; and generating third data based on the determined portion of the semantic network. 9. The method of claim 1 , wherein the semantic network represents an object model.

16. A non-transitory computer-readable storage medium including a first set of computer-executable instructions that, when executed by a script chunking service, cause the script chunking service to: identify a first script comprising instructions in a first format, wherein the instructions in the first format are not computer-executable; divide the first script into at least a first portion and a second portion; obtain, based at least in part on a first portion hash, a first chunk of computer-executable instructions corresponding to the first portion; and assemble at least the first chunk and a second chunk of computer-executable instructions corresponding to the second portion into a computer-executable script corresponding to the first script.

16. A non-transitory computer-readable storage medium including a first set of computer-executable instructions that, when executed by a script chunking service, cause the script chunking service to: identify a first script comprising instructions in a first format, wherein the instructions in the first format are not computer-executable; divide the first script into at least a first portion and a second portion; obtain, based at least in part on a first portion hash, a first chunk of computer-executable instructions corresponding to the first portion; and assemble at least the first chunk and a second chunk of computer-executable instructions corresponding to the second portion into a computer-executable script corresponding to the first script. 24. The non-transitory computer-readable storage medium of claim 16 , wherein the first set of computer-executable instructions further cause the script chunking service to: identify a second script comprising instructions in the first format; divide the second script into at least a third portion and a fourth portion; obtain, based at least in part on a third portion hash, a third chunk of computer-executable instructions corresponding to the third portion; and store the fourth portion in a pending compilation queue.

13. A system for labeling clusters of visual objects, comprising: a memory comprising a code; at least one processor adapted to execute said code in which said code comprising: code instructions for identifying a plurality of records each comprising at least one object image associated with at least one textual field; code instructions for applying a visual analysis of a visual similarity between respective said object images of said plurality of records to yield a plurality of sub clusters; code instructions for uniting said plurality of sub clusters into a plurality of clusters according to text similarity between said object images by applying a text similarity function on each said at least one textual field; code instructions for labeling each cluster of the plurality of clusters with a label reflecting a common semantic factor of respective said textual fields of members in each cluster; code instructions for displaying a catalog wherein the label of each cluster of the plurality of clusters is presented in association with the representative image thereof, the catalog is displayed as part of a user interface at a user terminal; wherein the visual similarity provides a measure of resemblances between two visual objects based on local descriptors in the visual objects.

13. A system for labeling clusters of visual objects, comprising: a memory comprising a code; at least one processor adapted to execute said code in which said code comprising: code instructions for identifying a plurality of records each comprising at least one object image associated with at least one textual field; code instructions for applying a visual analysis of a visual similarity between respective said object images of said plurality of records to yield a plurality of sub clusters; code instructions for uniting said plurality of sub clusters into a plurality of clusters according to text similarity between said object images by applying a text similarity function on each said at least one textual field; code instructions for labeling each cluster of the plurality of clusters with a label reflecting a common semantic factor of respective said textual fields of members in each cluster; code instructions for displaying a catalog wherein the label of each cluster of the plurality of clusters is presented in association with the representative image thereof, the catalog is displayed as part of a user interface at a user terminal; wherein the visual similarity provides a measure of resemblances between two visual objects based on local descriptors in the visual objects. 15. The system according to claim 13 , wherein said at least one processor is adapted to execute said code in which said code further comprises code instructions for filtering out copyrighted records from said plurality of records, wherein a copyrighted object image of a copyrighted record exhibits a visual similarity above a specified level with an object image ranked above a specified level of relevance retrieved by an image search engine applied to at least one textual field associated with the object image.

12. In a laser printer controller, an alignment device for converting a series of input data words each in a first word orientation into a series of output data words, each in a second word orientation comprising: latch means for receiving a first input data word of a first word orientation and holding for a predetermined period the output of the first input data word; and cut and paste logic means coupled to said latch means for receiving, from said latch means, the output of the first data word and for receiving a current data word, said cut and paste logic means combining a portion of said first data word with a portion of said current data word in a predetermined sequence so as to provide an output data word of a second word orientation.

12. In a laser printer controller, an alignment device for converting a series of input data words each in a first word orientation into a series of output data words, each in a second word orientation comprising: latch means for receiving a first input data word of a first word orientation and holding for a predetermined period the output of the first input data word; and cut and paste logic means coupled to said latch means for receiving, from said latch means, the output of the first data word and for receiving a current data word, said cut and paste logic means combining a portion of said first data word with a portion of said current data word in a predetermined sequence so as to provide an output data word of a second word orientation. 15. The device of claim 12 further comprising offset logic means for providing a control signal to said cut and paste logic means, said control signal establishing the size of each of said first word portion and said second word portion in said output data word, and rotate logic means coupled to said cut and paste logic means for receiving said output data word and rotating the position of said first word portion with said current word portion for providing said output word.

10. A system for searching data, the system comprising: a storage device, wherein the storage device stores a vector space library comprising a set of inflected data fields, and wherein the set of inflected data fields are formed from a set of lightweight directory access protocol data fields; and a vector space module, wherein the vector space module converts each alphanumeric character of a search query comprising one or more alphanumeric characters from a set of alphanumeric characters comprising letters ranging from A-Z and numbers ranging from 0-9 into a respective corresponding phonetic variant in a one to one relationship to form an inflected search query in response to receiving a search query-using an alphanumeric phonetic hash that includes a mapping of the set of alphanumeric characters into a set of phonetic variants, wherein each phonetic variant is represented as a spelled out word that corresponds to a unique character in the set of alphanumeric characters, and wherein the inflected search query is a vector space having a set of vectors wherein each vector corresponds to a respective individual alphanumeric character of the search query; identifies a set of inflected data fields of a vector space library satisfying the inflected search query, wherein the set of inflected data fields are formed from a set of lightweight directory access protocol data fields of a set of lightweight directory access protocol records, wherein an inflected data field is a vector space comprising a group of vectors; calculates a relevancy score for the records of the set of records that satisfies the inflected search query, wherein the relevancy score is calculated as a percentage of vectors of an inflected data field that are in common with the vectors of the inflected search query; determines whether the relevancy score meets a modifiable predetermined threshold; calculates search parameters as a percentage of vectors of the inflected search query that are in common with the vectors of the inflected data field; and responsive to the relevancy score meets the modifiable predetermined threshold generates a search result listing records of the set of records satisfying the search query and conforming to the searching parameters.

10. A system for searching data, the system comprising: a storage device, wherein the storage device stores a vector space library comprising a set of inflected data fields, and wherein the set of inflected data fields are formed from a set of lightweight directory access protocol data fields; and a vector space module, wherein the vector space module converts each alphanumeric character of a search query comprising one or more alphanumeric characters from a set of alphanumeric characters comprising letters ranging from A-Z and numbers ranging from 0-9 into a respective corresponding phonetic variant in a one to one relationship to form an inflected search query in response to receiving a search query-using an alphanumeric phonetic hash that includes a mapping of the set of alphanumeric characters into a set of phonetic variants, wherein each phonetic variant is represented as a spelled out word that corresponds to a unique character in the set of alphanumeric characters, and wherein the inflected search query is a vector space having a set of vectors wherein each vector corresponds to a respective individual alphanumeric character of the search query; identifies a set of inflected data fields of a vector space library satisfying the inflected search query, wherein the set of inflected data fields are formed from a set of lightweight directory access protocol data fields of a set of lightweight directory access protocol records, wherein an inflected data field is a vector space comprising a group of vectors; calculates a relevancy score for the records of the set of records that satisfies the inflected search query, wherein the relevancy score is calculated as a percentage of vectors of an inflected data field that are in common with the vectors of the inflected search query; determines whether the relevancy score meets a modifiable predetermined threshold; calculates search parameters as a percentage of vectors of the inflected search query that are in common with the vectors of the inflected data field; and responsive to the relevancy score meets the modifiable predetermined threshold generates a search result listing records of the set of records satisfying the search query and conforming to the searching parameters. 12. The system of claim 10 , wherein the a vector space module generate the vector space library having the set of inflected data fields using the alphanumeric hash, wherein the set of inflected data fields are formed from a set of lightweight directory access protocol data fields.

10. An article of manufacture comprising at least one non-transitory 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 a template that includes at least one tag that identifies at least one list of elements, the at least one list of elements comprising a set of elements; determining a format for the at least one list of elements at least in part by determining, based on a characteristic of the set of elements, whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence; and using the at least one list of elements and the determined format to automatically generate output text that includes the at least one list of elements formatted according to the determined format, the determined format indicating whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence.

10. An article of manufacture comprising at least one non-transitory 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 a template that includes at least one tag that identifies at least one list of elements, the at least one list of elements comprising a set of elements; determining a format for the at least one list of elements at least in part by determining, based on a characteristic of the set of elements, whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence; and using the at least one list of elements and the determined format to automatically generate output text that includes the at least one list of elements formatted according to the determined format, the determined format indicating whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence. 16. The article of manufacture of claim 10 , wherein determining the format for the at least one list of elements comprises determining at least one formatting parameter for the at least one list of elements, and wherein the at least one formatting parameter specifies formatting information for an enumerated list format of the at least one list.

15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response.

15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. 17. The apparatus of claim 15 wherein the match/search algorithm processes the input speech through a plurality of models with states, and the acoustic models are adapted by modifying statistics associated with the model states.

21. A method performed by one or more server devices, the method comprising: identifying, by at least one of the one or more server devices, a blog document that is responsive to a search query; generating, by at least one of the one or more server devices, a first score for the blog document based on a relevance of the blog document to the search query; generating, by at least one of the one or more server devices, a second score for the blog document based on a quality of the blog document independent of the search query, where the second score is based on: a first indication of whether ads appear in a blogroll associated with the blog document or blog metadata associated with the blog document, and a second indication of whether ads appear in blog posts in the blog document; generating, by at least one of the one or more server devices, a third score based on the first and second scores; and providing, by at least one of the one or more server devices, information relating to the blog document based on the third score.

21. A method performed by one or more server devices, the method comprising: identifying, by at least one of the one or more server devices, a blog document that is responsive to a search query; generating, by at least one of the one or more server devices, a first score for the blog document based on a relevance of the blog document to the search query; generating, by at least one of the one or more server devices, a second score for the blog document based on a quality of the blog document independent of the search query, where the second score is based on: a first indication of whether ads appear in a blogroll associated with the blog document or blog metadata associated with the blog document, and a second indication of whether ads appear in blog posts in the blog document; generating, by at least one of the one or more server devices, a third score based on the first and second scores; and providing, by at least one of the one or more server devices, information relating to the blog document based on the third score. 22. The method of claim 21 , where generating the third score includes: increasing or decreasing the first score based on the second score.

1. A method of providing related links in a web page, comprising: retrieving textual information associated with a web page upon loading of the web page at a client device; extracting, by one or more computers, a set of keywords from the received textual information, wherein the keywords are representative of content of the web page, wherein extracting the set of keywords from the received textual information includes: parsing the textual information associated with the web page to identify a language of the textual information, segmenting each text segment in the textual information into a set of separate words or phrases in accordance with the identified language of the textual information, removing the stop words of the identified language from the set of separate words or phrases, and returning the set of words or phrases as the set of keywords; ranking the extracted set of keywords using a keyword repository, wherein the keyword repository maintains a list of keywords and their respective rankings; selecting one or more representative keywords from the extracted set of keywords based on the ranking; sending the one or more representative keywords as a search query to a search engine to obtain a list of search results ordered by their respective rankings; and returning a specified number of search results with the highest rankings to the client for display, wherein the received search results are responsive to the one or more representative keywords extracted from textual information associated with a web page loading at a client device and wherein the received search results are displayed as related links within a particular designated region of the web page, wherein the related links are links to other web pages related to the loading web page.

1. A method of providing related links in a web page, comprising: retrieving textual information associated with a web page upon loading of the web page at a client device; extracting, by one or more computers, a set of keywords from the received textual information, wherein the keywords are representative of content of the web page, wherein extracting the set of keywords from the received textual information includes: parsing the textual information associated with the web page to identify a language of the textual information, segmenting each text segment in the textual information into a set of separate words or phrases in accordance with the identified language of the textual information, removing the stop words of the identified language from the set of separate words or phrases, and returning the set of words or phrases as the set of keywords; ranking the extracted set of keywords using a keyword repository, wherein the keyword repository maintains a list of keywords and their respective rankings; selecting one or more representative keywords from the extracted set of keywords based on the ranking; sending the one or more representative keywords as a search query to a search engine to obtain a list of search results ordered by their respective rankings; and returning a specified number of search results with the highest rankings to the client for display, wherein the received search results are responsive to the one or more representative keywords extracted from textual information associated with a web page loading at a client device and wherein the received search results are displayed as related links within a particular designated region of the web page, wherein the related links are links to other web pages related to the loading web page. 9. The method of claim 1 , wherein the keyword repository is constructed by performing statistical analysis on at least one of the following: the textual data on the web pages crawled by a search engine from the web; and logged query data input by users.