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20. A computer program product comprising a non-transitory computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: receive input from a first user, the received input associated with published content on a webpage; determine a context of the first user based on the input associated with the published content; retrieve content and context from a plurality of web site servers hosing a plurality of different websites, wherein the context is used to determine (1) what information is added to a sharing interface and (2) which one of the plurality of different websites will the sharing interface be pushed to, the context including information about the webpage based on the determined context; generate customized content by processing the retrieved content based on the determined context; receive and process a request for the sharing interface; provide the sharing interface including the customized content using the context and an endorsement; add the retrieved content based on the context to the sharing interface, the sharing interface overlaid on a portion of the webpage and including at least one area for displaying the retrieved content and receiving the customized content, the at least one area for displaying the retrieved content and receiving customized content allowing for additional input of information into the sharing interface including input of comments and at least one user identifier associated with a second user, the second user an intended recipient of the customized content; add an action button to the sharing interface; send the sharing interface for display; transfer the customized content in the sharing interface based on the context in response to user selection of the action button; and send the customized content to the second user associated with the at least one user identifier.

20. A computer program product comprising a non-transitory computer useable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: receive input from a first user, the received input associated with published content on a webpage; determine a context of the first user based on the input associated with the published content; retrieve content and context from a plurality of web site servers hosing a plurality of different websites, wherein the context is used to determine (1) what information is added to a sharing interface and (2) which one of the plurality of different websites will the sharing interface be pushed to, the context including information about the webpage based on the determined context; generate customized content by processing the retrieved content based on the determined context; receive and process a request for the sharing interface; provide the sharing interface including the customized content using the context and an endorsement; add the retrieved content based on the context to the sharing interface, the sharing interface overlaid on a portion of the webpage and including at least one area for displaying the retrieved content and receiving the customized content, the at least one area for displaying the retrieved content and receiving customized content allowing for additional input of information into the sharing interface including input of comments and at least one user identifier associated with a second user, the second user an intended recipient of the customized content; add an action button to the sharing interface; send the sharing interface for display; transfer the customized content in the sharing interface based on the context in response to user selection of the action button; and send the customized content to the second user associated with the at least one user identifier. 21. The computer program product of claim 20 wherein the user input is a search query and the published content is at least one search result.

8. A computer program product, comprising: a non-transitory computer-readable storage device having computer-executable program instructions embodied thereon that when executed by a computer cause the computer to extract card information, comprising: computer-executable program instructions to identify a first area of the image, the first area being selected as a potential location of one or more digits on the image; computer-executable program instructions to perform a classification algorithm on data encompassed by the first area; computer-executable program instructions to compare the image to one or more card models associated with a user, the one or more models comprising digit distribution patterns of data displayed on the image; and computer-executable program instructions to perform an optical character recognition algorithm on areas of the card that are anticipated by the one or more computing devices as comprising digits based on the application of the card models and the identified lines.

8. A computer program product, comprising: a non-transitory computer-readable storage device having computer-executable program instructions embodied thereon that when executed by a computer cause the computer to extract card information, comprising: computer-executable program instructions to identify a first area of the image, the first area being selected as a potential location of one or more digits on the image; computer-executable program instructions to perform a classification algorithm on data encompassed by the first area; computer-executable program instructions to compare the image to one or more card models associated with a user, the one or more models comprising digit distribution patterns of data displayed on the image; and computer-executable program instructions to perform an optical character recognition algorithm on areas of the card that are anticipated by the one or more computing devices as comprising digits based on the application of the card models and the identified lines. 10. The computer program product of claim 8 , the computer-executable program instructions further comprising comparing the model associated with the authenticated result to a database of card types to determine a card type of the card in the image.

1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon.

1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon. 10. The game apparatus as claimed in claim 1, comprising an instruction booklet.

1. A method for a user to create a report through voice output, comprising: (a) receiving by a computer information from user input via a user input device; (b) processing by the computer the information, wherein said processing step utilizes a heuristic algorithm; (c) performing by the computer a task resultant from said processing step, wherein said performing step further comprises a step of making a heuristic selection of one or more macros from a macro library; (d) preparing by the computer a response based on said performing step; (e) communicating the response as voice output verbalized through use of a voice output device; and (f) repeating said steps (a)-(e) until the report is completed.

1. A method for a user to create a report through voice output, comprising: (a) receiving by a computer information from user input via a user input device; (b) processing by the computer the information, wherein said processing step utilizes a heuristic algorithm; (c) performing by the computer a task resultant from said processing step, wherein said performing step further comprises a step of making a heuristic selection of one or more macros from a macro library; (d) preparing by the computer a response based on said performing step; (e) communicating the response as voice output verbalized through use of a voice output device; and (f) repeating said steps (a)-(e) until the report is completed. 6. The method of claim 1 , wherein the heuristic selection of the macro is based on matching the information received via the user input on the user input device with macro content.

1. A method for processing a function with a plurality of execution spaces comprising: creating an internal compiler representation for said function, wherein said creating comprises: copying substantially all lexical tokens corresponding to a body of said function; and inserting said lexical tokens into a plurality of conditional if-statements, wherein a conditional if-statement is generated for each corresponding execution space of said plurality of execution spaces, and wherein each conditional if-statement determines which execution space said function is executing in; and during compilation, performing overload resolution at a call site of an overloaded function by checking for compatibility with a first execution space specified by one of said plurality of conditional if-statements, wherein said overloaded function is called within said body of said function.

1. A method for processing a function with a plurality of execution spaces comprising: creating an internal compiler representation for said function, wherein said creating comprises: copying substantially all lexical tokens corresponding to a body of said function; and inserting said lexical tokens into a plurality of conditional if-statements, wherein a conditional if-statement is generated for each corresponding execution space of said plurality of execution spaces, and wherein each conditional if-statement determines which execution space said function is executing in; and during compilation, performing overload resolution at a call site of an overloaded function by checking for compatibility with a first execution space specified by one of said plurality of conditional if-statements, wherein said overloaded function is called within said body of said function. 7. The method of claim 1 , wherein each of said plurality of conditional if-statements and associated execution space corresponds to a discrete parse tree.

11. A non-transitory computer-readable medium storing instructions, which when executed by a processing device, cause the processing device to perform method comprising: receiving, within a datacenter management user interface, an action request to perform an action; determining, in response to receiving the action request, a first suggested object compatible with the action request, wherein the first suggested object is a datacenter or a component within the datacenter, wherein the component may be physical or virtual, and wherein the first suggested object is not displayed as a directly selectable option within the datacenter management user interface when the action request is received; and providing, in response to determining the first suggested object compatible with the action request, a first command suggestion within the datacenter management user interface, wherein the first command suggestion comprises the first suggested object.

11. A non-transitory computer-readable medium storing instructions, which when executed by a processing device, cause the processing device to perform method comprising: receiving, within a datacenter management user interface, an action request to perform an action; determining, in response to receiving the action request, a first suggested object compatible with the action request, wherein the first suggested object is a datacenter or a component within the datacenter, wherein the component may be physical or virtual, and wherein the first suggested object is not displayed as a directly selectable option within the datacenter management user interface when the action request is received; and providing, in response to determining the first suggested object compatible with the action request, a first command suggestion within the datacenter management user interface, wherein the first command suggestion comprises the first suggested object. 17. The medium of claim 11 , the method further comprising determining a second suggested object is compatible with the action request and ranking the first and second suggested objects based on one or more of: frequency of accesses to each respective object within the datacenter management user interface, and current user context within the datacenter management user interface.

4. The method of claim 1, further comprising: (e) setting a correlation threshold for performing the resulting action.

4. The method of claim 1, further comprising: (e) setting a correlation threshold for performing the resulting action. 6. The method of claim 4, further comprising: (f) storing data that corresponds to the topic-evaluation vector if the generated query is found in the topic evaluation vector to be above the correlation threshold.

8. A non-transitory computer-readable storage medium storing computer-readable instructions, which when executed, cause a computing device to: store, by at least one processor, first data associated with prior communications sent to a user, the first data comprising a first profile for a caller that creates a voice message for the user, and the prior communications including at least one prior communication received from the caller; send, by the at least one processor, to a speech recognition system, the voice message for transcribing using at least a portion of the first data to provide a transcribed message; receive, from the speech recognition system, the transcribed message; and cause a presentation on a display, the presentation comprising the transcribed message, and the presentation further comprising options for selection of a corrected word by the user to correct a misspelled word in the transcribed message.

8. A non-transitory computer-readable storage medium storing computer-readable instructions, which when executed, cause a computing device to: store, by at least one processor, first data associated with prior communications sent to a user, the first data comprising a first profile for a caller that creates a voice message for the user, and the prior communications including at least one prior communication received from the caller; send, by the at least one processor, to a speech recognition system, the voice message for transcribing using at least a portion of the first data to provide a transcribed message; receive, from the speech recognition system, the transcribed message; and cause a presentation on a display, the presentation comprising the transcribed message, and the presentation further comprising options for selection of a corrected word by the user to correct a misspelled word in the transcribed message. 11. The storage medium of claim 8 , wherein the first data is further associated with prior activities of the user including manner of operation of the computing device.

1. A computer-implemented method comprising: obtaining training acoustic data corresponding to a user's utterance of one or more words that include one or more particular subwords; dynamically generating a verification phrase based at least on one or more of the particular subwords included in the words uttered by the user in the training acoustic data; prompting, by a mobile device that is in a locked mode, the user to speak the dynamically generated verification phrase; and in response to determining that the user has likely spoken the dynamically generated verification phrase, determining, by the mobile device, whether to exit the locked mode.

1. A computer-implemented method comprising: obtaining training acoustic data corresponding to a user's utterance of one or more words that include one or more particular subwords; dynamically generating a verification phrase based at least on one or more of the particular subwords included in the words uttered by the user in the training acoustic data; prompting, by a mobile device that is in a locked mode, the user to speak the dynamically generated verification phrase; and in response to determining that the user has likely spoken the dynamically generated verification phrase, determining, by the mobile device, whether to exit the locked mode. 5. The method of claim 1 , wherein the subwords comprise phonemes.

7. A system for generating a monotonic classifier, the system comprising: a processor; and a memory, wherein the memory comprises one or more programming instructions for performing a method for generating a monotonic classifier, the method comprising: mapping a plurality of feature vectors to a plurality of ordered classes, wherein each feature vector maps to a corresponding class, for each class other than a lowest-ordered class, training a binary classifier to distinguish between the class and a preceding class, wherein training a binary classifier comprises: determining a data set impurity value for a data set of feature vectors, wherein the data set impurity value equals the sum, over all classes, of the product of (i) the number of feature vectors in the data set having a particular class divided by the number of feature vectors in the data set and (ii) the logarithm of the number of feature vectors in the data set having the particular class divided by the number of feature vectors in the data set, determining a decision rule for separating the data set into a plurality of subsets that maximizes the decrease in impurity, wherein the decrease in impurity equals the data set impurity value for the data set minus, for each subset, the product of a number of feature vectors in the subset and a data set impurity value for the subset divided by the number of feature vectors in the data set, and repeating the determining a data set impurity and the determining a decision rule on one or more subsets until the data set impurity value for each subset is minimized, and ordering the binary classifiers as a monotonic classifier based on the class corresponding to each binary classifier, wherein a number of classes in the plurality of ordered classes is one more than a number of binary classifiers.

7. A system for generating a monotonic classifier, the system comprising: a processor; and a memory, wherein the memory comprises one or more programming instructions for performing a method for generating a monotonic classifier, the method comprising: mapping a plurality of feature vectors to a plurality of ordered classes, wherein each feature vector maps to a corresponding class, for each class other than a lowest-ordered class, training a binary classifier to distinguish between the class and a preceding class, wherein training a binary classifier comprises: determining a data set impurity value for a data set of feature vectors, wherein the data set impurity value equals the sum, over all classes, of the product of (i) the number of feature vectors in the data set having a particular class divided by the number of feature vectors in the data set and (ii) the logarithm of the number of feature vectors in the data set having the particular class divided by the number of feature vectors in the data set, determining a decision rule for separating the data set into a plurality of subsets that maximizes the decrease in impurity, wherein the decrease in impurity equals the data set impurity value for the data set minus, for each subset, the product of a number of feature vectors in the subset and a data set impurity value for the subset divided by the number of feature vectors in the data set, and repeating the determining a data set impurity and the determining a decision rule on one or more subsets until the data set impurity value for each subset is minimized, and ordering the binary classifiers as a monotonic classifier based on the class corresponding to each binary classifier, wherein a number of classes in the plurality of ordered classes is one more than a number of binary classifiers. 11. The system of claim 7 wherein mapping a plurality of feature vectors to a plurality of ordered classes comprises one or more programming instructions for: ordering the plurality of classes in a linear order; and for each feature vector, assigning the feature vector to a particular class, wherein the feature vector is not greater than any feature vector corresponding to a class that is greater than the particular class.

1. A computer-implemented method of assessing an educational program having multiple ordered activities defining multiple learner tracks, the method comprising: receiving baseline performance index scores and post-activity performance index scores for a plurality of learners engaging in the educational program by executing first instructions in a computer system, wherein the baseline performance index scores are derived from a performance index test administered to the learners prior to any of the activities, and the post-activity performance index scores are derived from the performance index test administered to the learners after each of the activities; organizing the learners into learner groups based on how many of the activities a learner has completed by executing second instructions in the computer system; for each given learner group, calculating a baseline average score using the baseline performance index scores of learners in the given learner group, calculating a post-activity average score for each of the activities which have been completed by learners in the given learner group, and calculating first statistical differences between the baseline average score and a final one of the post-activity average scores for the given learner group, and between each post-activity average score and any successive post-activity average scores for the given learner group by executing third instructions in the computer system; receiving pre-test scores and corresponding post-test scores for learners who have completed at least one of the activities, wherein the pre-test scores and post-test scores are derived from separate activity tests administered prior to and after each activity, and the separate activity tests include questions in each of a plurality of domains including at least knowledge, competence, confidence and performance by executing fourth instructions in the computer system; receiving post-curriculum assessment scores for learners who have completed a selection of the activities, wherein the post-curriculum assessment scores are derived from the performance index test and the separate activity tests administered to the learners no earlier than a designated period of time after completion of the selection of the activities by executing fifth instructions in the computer system; for each given domain, calculating pre-test domain average scores using the pre-test scores for questions in the given domain, calculating post-test domain average scores using the post-test scores for questions in the given domain, and calculating second statistical differences between the pre-test domain average scores and corresponding post-test domain average scores by executing sixth instructions in the computer system; for each given activity, calculating a pre-test activity average score using the pre-test scores for the given activity, calculating a post-test activity average score using the post-test scores for the given activity, and calculating third statistical differences between the pre-test activity average scores and corresponding post-test activity average scores by executing seventh instructions in the computer system; calculating a post-curriculum assessment average score using the post-curriculum assessment scores by executing eighth instructions in the computer system; calculating fourth statistical differences between the baseline average score and the post-curriculum assessment average score and between the post-activity average scores and the post-curriculum assessment average score by executing ninth instructions in the computer system; and identifying any of the first, second, third or fourth statistical differences which are equal to or less than a predetermined probability threshold by executing tenth instructions in the computer system.

1. A computer-implemented method of assessing an educational program having multiple ordered activities defining multiple learner tracks, the method comprising: receiving baseline performance index scores and post-activity performance index scores for a plurality of learners engaging in the educational program by executing first instructions in a computer system, wherein the baseline performance index scores are derived from a performance index test administered to the learners prior to any of the activities, and the post-activity performance index scores are derived from the performance index test administered to the learners after each of the activities; organizing the learners into learner groups based on how many of the activities a learner has completed by executing second instructions in the computer system; for each given learner group, calculating a baseline average score using the baseline performance index scores of learners in the given learner group, calculating a post-activity average score for each of the activities which have been completed by learners in the given learner group, and calculating first statistical differences between the baseline average score and a final one of the post-activity average scores for the given learner group, and between each post-activity average score and any successive post-activity average scores for the given learner group by executing third instructions in the computer system; receiving pre-test scores and corresponding post-test scores for learners who have completed at least one of the activities, wherein the pre-test scores and post-test scores are derived from separate activity tests administered prior to and after each activity, and the separate activity tests include questions in each of a plurality of domains including at least knowledge, competence, confidence and performance by executing fourth instructions in the computer system; receiving post-curriculum assessment scores for learners who have completed a selection of the activities, wherein the post-curriculum assessment scores are derived from the performance index test and the separate activity tests administered to the learners no earlier than a designated period of time after completion of the selection of the activities by executing fifth instructions in the computer system; for each given domain, calculating pre-test domain average scores using the pre-test scores for questions in the given domain, calculating post-test domain average scores using the post-test scores for questions in the given domain, and calculating second statistical differences between the pre-test domain average scores and corresponding post-test domain average scores by executing sixth instructions in the computer system; for each given activity, calculating a pre-test activity average score using the pre-test scores for the given activity, calculating a post-test activity average score using the post-test scores for the given activity, and calculating third statistical differences between the pre-test activity average scores and corresponding post-test activity average scores by executing seventh instructions in the computer system; calculating a post-curriculum assessment average score using the post-curriculum assessment scores by executing eighth instructions in the computer system; calculating fourth statistical differences between the baseline average score and the post-curriculum assessment average score and between the post-activity average scores and the post-curriculum assessment average score by executing ninth instructions in the computer system; and identifying any of the first, second, third or fourth statistical differences which are equal to or less than a predetermined probability threshold by executing tenth instructions in the computer system. 2. The method of claim 1 wherein: the statistical differences are calculated using paired sample t testing for the performance index test; and the predetermined probability threshold is a P value of 0.05.

1. An information processing device for associating first text information with first numerical information of a time series of a given indicator, comprising: a first phrase database for storing a first phrase, representing a change in first numerical information over a first time period, generated based on changes in said first numerical information, in association with the first time period and with the first numerical information; wherein, said first phrase indicates whether said first numerical information has risen, declined, or stably shifted according to one or more predetermined thresholds within the first time period; an associating portion for associating said first numerical information and first text information based on said first phrase; an outputting portion for outputting said first numerical information and said first text information for said first time period corresponding to said first phrase, associated by said associating portion; said associating portion comprises a first retrieving portion that retrieves said first text information using a first retrieval condition that includes said first phrase, wherein said first retrieving portion normalizes an instance of the first phrase with a superordinate concept or a subordinate concept with a predetermined synonym dictionary, and wherein said first retrieving portion retrieves said first text information including said normalized instance of the first phrase; said outputting portion outputs said retrieved first text information associated with said first numerical information in said first time period; said first phrase database stores said first phrase that indicates a change in said first numerical information in the first time period, and associated with the first numerical information, for each of a plurality of second numerical information including said first numerical information; wherein said associating portion comprises a central processing unit controlling: an extracting portion for extracting, from said retrieved first text information, a second phrase indicating a change in third numerical information; an index registration unit for registering the second phrase as first index information for each of a plurality of pieces of the retrieved first text information; a second phrase database for storing the registered first index information; a second retrieving portion for retrieving, from said second numerical information, a fourth numerical information associated with said first phrase that satisfies second retrieval conditions, using the second retrieval conditions including said second phrase; the second retrieving portion configured to retrieve a second time period corresponding to the first phrase matching said second retrieval conditions including said second phrase, in which the second phrase indicates the change in the third numerical information; wherein: said outputting portion further outputs by a command of the central processing unit, in association with said retrieved first text information, said fourth numerical information, retrieved by said second retrieving portion including said second time period.

1. An information processing device for associating first text information with first numerical information of a time series of a given indicator, comprising: a first phrase database for storing a first phrase, representing a change in first numerical information over a first time period, generated based on changes in said first numerical information, in association with the first time period and with the first numerical information; wherein, said first phrase indicates whether said first numerical information has risen, declined, or stably shifted according to one or more predetermined thresholds within the first time period; an associating portion for associating said first numerical information and first text information based on said first phrase; an outputting portion for outputting said first numerical information and said first text information for said first time period corresponding to said first phrase, associated by said associating portion; said associating portion comprises a first retrieving portion that retrieves said first text information using a first retrieval condition that includes said first phrase, wherein said first retrieving portion normalizes an instance of the first phrase with a superordinate concept or a subordinate concept with a predetermined synonym dictionary, and wherein said first retrieving portion retrieves said first text information including said normalized instance of the first phrase; said outputting portion outputs said retrieved first text information associated with said first numerical information in said first time period; said first phrase database stores said first phrase that indicates a change in said first numerical information in the first time period, and associated with the first numerical information, for each of a plurality of second numerical information including said first numerical information; wherein said associating portion comprises a central processing unit controlling: an extracting portion for extracting, from said retrieved first text information, a second phrase indicating a change in third numerical information; an index registration unit for registering the second phrase as first index information for each of a plurality of pieces of the retrieved first text information; a second phrase database for storing the registered first index information; a second retrieving portion for retrieving, from said second numerical information, a fourth numerical information associated with said first phrase that satisfies second retrieval conditions, using the second retrieval conditions including said second phrase; the second retrieving portion configured to retrieve a second time period corresponding to the first phrase matching said second retrieval conditions including said second phrase, in which the second phrase indicates the change in the third numerical information; wherein: said outputting portion further outputs by a command of the central processing unit, in association with said retrieved first text information, said fourth numerical information, retrieved by said second retrieving portion including said second time period. 2. The information processing device as set forth in claim 1 , wherein: said outputting portion: outputs so as to display to a user said retrieved first text information retrieved by said first retrieving portion so that a location corresponding to said first retrieval conditions is identifiable; and outputs so as to display said fourth numerical information to the user when said location corresponding to said first retrieval conditions is selected by the user.

3. A data division apparatus which divides multi-dimensional data including a plurality of data pieces, comprising: a data input unit which inputs the multi-dimensional data; a division plane candidate creator which creates a plurality of division plane candidates for dividing the multi-dimensional data; a data provisional division unit which provisionally divides the multi-dimensional data by using the division plane candidates to generate clusters from each of the division plane candidates, the clusters each including one or more data piece; a model generator which generates models representing the clusters, per each of the division plane candidates; an evaluation value calculator which calculates evaluation values for evaluating the division plane candidates, on the basis of the models generated associated with the division plane candidates and the multi-dimensional data; a division candidate selector which compares evaluation values respectively corresponding to the division plane candidates and selects a division plane candidate having a highest evaluation value; and a data division unit which divides the multi-dimensional data by using the selected division plane candidate; wherein the evaluation value calculator comprises: a class number assigning unit which assigns class numbers to clusters after provisional division and assigns the class numbers to the data pieces in the multi-dimensional data; a classification rule generator which generates a decision tree to predict a class number from data piece, based on the multi-dimensional data assigned the class numbers; and an expanded evaluation value calculator which calculates an expanded evaluation value based on at least either of precision and size of the decision tree and the evaluation value, wherein the division candidate selector uses the expanded evaluation value instead of the evaluation value.

3. A data division apparatus which divides multi-dimensional data including a plurality of data pieces, comprising: a data input unit which inputs the multi-dimensional data; a division plane candidate creator which creates a plurality of division plane candidates for dividing the multi-dimensional data; a data provisional division unit which provisionally divides the multi-dimensional data by using the division plane candidates to generate clusters from each of the division plane candidates, the clusters each including one or more data piece; a model generator which generates models representing the clusters, per each of the division plane candidates; an evaluation value calculator which calculates evaluation values for evaluating the division plane candidates, on the basis of the models generated associated with the division plane candidates and the multi-dimensional data; a division candidate selector which compares evaluation values respectively corresponding to the division plane candidates and selects a division plane candidate having a highest evaluation value; and a data division unit which divides the multi-dimensional data by using the selected division plane candidate; wherein the evaluation value calculator comprises: a class number assigning unit which assigns class numbers to clusters after provisional division and assigns the class numbers to the data pieces in the multi-dimensional data; a classification rule generator which generates a decision tree to predict a class number from data piece, based on the multi-dimensional data assigned the class numbers; and an expanded evaluation value calculator which calculates an expanded evaluation value based on at least either of precision and size of the decision tree and the evaluation value, wherein the division candidate selector uses the expanded evaluation value instead of the evaluation value. 4. The data division apparatus according to claim 3 , wherein the expanded evaluation value calculator calculates the expanded evaluation value by adding a value obtained by multiplying the precision of the decision tree by a first weighting coefficient and a value obtained by multiplying the size of the decision tree by a second weighting coefficient to the evaluation value.

2. A system comprising: one or more sensors configured to sense one or more physical characteristics of an authoring user, wherein said one or more sensors configured to sense one or more physical characteristics of an authoring user, comprises: a functional near infrared (fNIR) device; an acquisition module configured to acquire data indicative of an inferred mental state of the authoring user based, at least in part, on the one or more physical characteristics sensed by the one or more sensors; and an association module configured to associate the data indicative of the inferred mental state of the authoring user with an electronic message.

2. A system comprising: one or more sensors configured to sense one or more physical characteristics of an authoring user, wherein said one or more sensors configured to sense one or more physical characteristics of an authoring user, comprises: a functional near infrared (fNIR) device; an acquisition module configured to acquire data indicative of an inferred mental state of the authoring user based, at least in part, on the one or more physical characteristics sensed by the one or more sensors; and an association module configured to associate the data indicative of the inferred mental state of the authoring user with an electronic message. 32. The system of claim 2 , further comprising: at least one of an email application, an instant message (IM) application, an audio application, or a video application.

1. A computer-implemented method for identifying plausible sources of error in a risk assessment system, comprising: identifying, by a computer, a first variable and a second variable of the risk assessment system, wherein an initial distribution of the first variable is a first hypothesis and an initial distribution of the second variable is a second hypothesis; implementing, by the computer, a Bayesian network to represent implications between the first and second variables; determining, by the computer, an initial probability of the first hypothesis that the first variable has not changed given the second hypothesis that the second variable has not changed, wherein the initial probability is based on a state of knowledge at the time of determining the initial probability; receiving, by the computer, data regarding the first and second variables after determining the initial probability of the first hypothesis; identifying, by the computer, a change of value in the first or second variable; determining, by the computer, by probabilistic induction at least one cause of the change of value in the first or second variable, wherein the at least one cause is a plausible source of error; and determining, by the computer, the plausibility that the change is an error in the data by evaluating the initial probability of the first hypothesis based on the at least one cause.

1. A computer-implemented method for identifying plausible sources of error in a risk assessment system, comprising: identifying, by a computer, a first variable and a second variable of the risk assessment system, wherein an initial distribution of the first variable is a first hypothesis and an initial distribution of the second variable is a second hypothesis; implementing, by the computer, a Bayesian network to represent implications between the first and second variables; determining, by the computer, an initial probability of the first hypothesis that the first variable has not changed given the second hypothesis that the second variable has not changed, wherein the initial probability is based on a state of knowledge at the time of determining the initial probability; receiving, by the computer, data regarding the first and second variables after determining the initial probability of the first hypothesis; identifying, by the computer, a change of value in the first or second variable; determining, by the computer, by probabilistic induction at least one cause of the change of value in the first or second variable, wherein the at least one cause is a plausible source of error; and determining, by the computer, the plausibility that the change is an error in the data by evaluating the initial probability of the first hypothesis based on the at least one cause. 12. The method of claim 1 , wherein providing an initial probability of the first hypothesis comprises: providing a prior probability of the at least one variable; and providing an initial conditional probability of the at least one variable.

31. The method of claim 26 including the steps of: generating a list of words from said tabulation and text typesetting data; and combining said word list in said magnetic media for retention as index data in said master memory.

31. The method of claim 26 including the steps of: generating a list of words from said tabulation and text typesetting data; and combining said word list in said magnetic media for retention as index data in said master memory. 33. The method of claim 31 including step of associating each said word of said word list with a select field associated therewith to provide a unique word list for retention as index data in said mater memory.

15. A processor-based method for reducing a binary input image to produce a reduced image wherein the image is divided into M.times.N tiles, each tile has M pixels down and N pixels across, and each tile is mapped to a single pixel in the reduced image, comprising the steps, carried out once for each tile, of: evaluating a particular plurality of the pixels in the tile, the particular plurality being smaller in number than the number of pixels in the tile; determining whether at least a threshold number of the evaluated pixels are ON; and turning ON the pixel in the reduced image if and only if the result of said determining step is affirmative.

15. A processor-based method for reducing a binary input image to produce a reduced image wherein the image is divided into M.times.N tiles, each tile has M pixels down and N pixels across, and each tile is mapped to a single pixel in the reduced image, comprising the steps, carried out once for each tile, of: evaluating a particular plurality of the pixels in the tile, the particular plurality being smaller in number than the number of pixels in the tile; determining whether at least a threshold number of the evaluated pixels are ON; and turning ON the pixel in the reduced image if and only if the result of said determining step is affirmative. 16. The method of claim 15 wherein the particular plurality of pixels is a horizontal 1.times.N array in the tile.

12. A method, implemented by a computing device comprising a processor and one or more output devices communicatively connected to the processor, the method comprising: providing, with the processor, a computer-controlled character in a virtual world; associating, with the processor, the computer-controlled character with a semantic knowledgebase; responding, with the processor, to an initiation of an interaction with the computer-controlled character by combining semantic representations from the semantic knowledgebase with semantic representations from the virtual world, thereby generating semantic dialog elements dynamically generated based on both the combined semantic structures and inputs from the user, and providing the semantic dialog elements via one or more of the output devices; in which the semantic dialog elements generated comprise one or more user dialog elements, and one or more computer-controlled character dialog elements responsive to the user dialog elements.

12. A method, implemented by a computing device comprising a processor and one or more output devices communicatively connected to the processor, the method comprising: providing, with the processor, a computer-controlled character in a virtual world; associating, with the processor, the computer-controlled character with a semantic knowledgebase; responding, with the processor, to an initiation of an interaction with the computer-controlled character by combining semantic representations from the semantic knowledgebase with semantic representations from the virtual world, thereby generating semantic dialog elements dynamically generated based on both the combined semantic structures and inputs from the user, and providing the semantic dialog elements via one or more of the output devices; in which the semantic dialog elements generated comprise one or more user dialog elements, and one or more computer-controlled character dialog elements responsive to the user dialog elements. 13. The method of claim 12 , further comprising providing one or more of the user dialog elements in a user-selectable dialog menu.

7. The method of claim 6 , further comprising searching for XBRL concepts matching search conditions within at least one searched entity selected from the group consisting of the received XBRL document and the first and second versions of the XBRL taxonomy.

7. The method of claim 6 , further comprising searching for XBRL concepts matching search conditions within at least one searched entity selected from the group consisting of the received XBRL document and the first and second versions of the XBRL taxonomy. 8. The method of claim 7 , wherein the search conditions comprise searching for a new XBRL concept in the second version of the XBRL taxonomy.

18. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: identifying structured document data in a document, the structured document data including information identifying one or more entities and, for each entity, a resource locator specifying a resource location of a resource for the entity; determining one or more terms associated with a particular entity of the one or more entities, the determining the one or more terms comprising: identifying anchor text in the structured document data, the anchor text including the one or more terms; determining a number of documents in a set of documents that include the identified anchor text; and determining that the number of documents exceed a threshold number of documents; generating one or more synthetic queries from the structured document data, the generating comprising generating a synthetic query that includes the anchor text; storing the synthetic query in an augmentation query data store; identifying search results that are relevant to the synthetic query; associating, in the augmentation query data store, the identified search results and the resource for the particular entity with the synthetic query; and storing at least a portion of the identified search results and a search result for the resource for the particular entity in a cached search results store for use in an augmented search operation, wherein the stored search results are provided with other search results in response to the augmented search operation, the other search results being responsive to a received query for which the augmented search operation is performed.

18. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: identifying structured document data in a document, the structured document data including information identifying one or more entities and, for each entity, a resource locator specifying a resource location of a resource for the entity; determining one or more terms associated with a particular entity of the one or more entities, the determining the one or more terms comprising: identifying anchor text in the structured document data, the anchor text including the one or more terms; determining a number of documents in a set of documents that include the identified anchor text; and determining that the number of documents exceed a threshold number of documents; generating one or more synthetic queries from the structured document data, the generating comprising generating a synthetic query that includes the anchor text; storing the synthetic query in an augmentation query data store; identifying search results that are relevant to the synthetic query; associating, in the augmentation query data store, the identified search results and the resource for the particular entity with the synthetic query; and storing at least a portion of the identified search results and a search result for the resource for the particular entity in a cached search results store for use in an augmented search operation, wherein the stored search results are provided with other search results in response to the augmented search operation, the other search results being responsive to a received query for which the augmented search operation is performed. 20. The non-transitory computer storage medium of claim 18 , wherein the operation of identifying search results that are relevant to the synthetic query comprises the operations of: identifying a domain name of a resource location that matches one or more terms in the synthetic query; identifying the document at the resource location for referencing in a search result for the synthetic query; and associating the document with the synthetic query so that the document is identified as a search result responsive to a user query that matches the synthetic query.

13. One or more non-transitory computer-readable media having computer executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: determining that a user has interacted with a first item of a catalog of items; parsing explicit associative relationships between the first item and at least one type of related items from the catalog of items, the explicit associative relationships including words or phrases that define a relationship between the first item and the at least one type of related items, wherein the relationship is at least one of: an optional accessory relationship that indicates that the at least one type of related items are both suggested for use with the first item and not necessary for using the first item, a necessary accessory relationship that indicates that the at least one type of related items are necessary for using the first item, or a consumable accessory relationship that indicates that the at least one type of related items is consumed during use in conjunction with the first item; based at least partly on the parsing, identifying, in the other items, related items that are determined to be usable in conjunction with the first item; and presenting, to the user, one or more recommendations that identify at least some related items of the at least one type of related items, wherein the one or more recommendations include an explanation of a nature of the relationship.

13. One or more non-transitory computer-readable media having computer executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: determining that a user has interacted with a first item of a catalog of items; parsing explicit associative relationships between the first item and at least one type of related items from the catalog of items, the explicit associative relationships including words or phrases that define a relationship between the first item and the at least one type of related items, wherein the relationship is at least one of: an optional accessory relationship that indicates that the at least one type of related items are both suggested for use with the first item and not necessary for using the first item, a necessary accessory relationship that indicates that the at least one type of related items are necessary for using the first item, or a consumable accessory relationship that indicates that the at least one type of related items is consumed during use in conjunction with the first item; based at least partly on the parsing, identifying, in the other items, related items that are determined to be usable in conjunction with the first item; and presenting, to the user, one or more recommendations that identify at least some related items of the at least one type of related items, wherein the one or more recommendations include an explanation of a nature of the relationship. 19. The one or more non-transitory computer-readable media as recited in claim 13 , wherein the operations further comprise: determining that the user has interacted with the first item via a website or an application associated with a service provider; and dynamically presenting the one or more recommendations via the website or the application in response to determining that the user has interacted with the first item.

23. A reading machine comprises: a computing device; an image input device coupled to the computing device for capturing images; and a computer program product tangible embodied on a computer readable medium for causing the computing device to examine multiple individual images, the computer program product comprising instructions for causing the computing device to: perform optical character recognition on a pair of captured images to produce recognized text from each of the images; detect text in one of the pair of individual images that is also found in the other one of the pair of images; combine recognized text from each of the images based on the detected common text; analyze the combined text to determine if incomplete text phrases are present in the combined text from the pair of images at edge portions of either of the images, and when incomplete text phrases are present in the combined text from the pair of images. generate commands to signal a user with user-instructions that guide a user to move an image input device that captures the pair of individual images in a direction to capture more of the text, with the user-instructions to guide based at least in part on the detected incomplete text.

23. A reading machine comprises: a computing device; an image input device coupled to the computing device for capturing images; and a computer program product tangible embodied on a computer readable medium for causing the computing device to examine multiple individual images, the computer program product comprising instructions for causing the computing device to: perform optical character recognition on a pair of captured images to produce recognized text from each of the images; detect text in one of the pair of individual images that is also found in the other one of the pair of images; combine recognized text from each of the images based on the detected common text; analyze the combined text to determine if incomplete text phrases are present in the combined text from the pair of images at edge portions of either of the images, and when incomplete text phrases are present in the combined text from the pair of images. generate commands to signal a user with user-instructions that guide a user to move an image input device that captures the pair of individual images in a direction to capture more of the text, with the user-instructions to guide based at least in part on the detected incomplete text. 24. The reading machine of claim 23 wherein common text between two strings from the pair of images is detected by searching for the longest common subsequence of characters in the strings.

41. The method of claim 40 wherein the development environment comprises an interpreter component that uses the output of the first-phase translation tool comprising: an instruction interpreter which emulates the hardware platform in the execution of platform-specific hardware instructions; a dataflow simulator which emulates a streaming data environment, providing inputs to and collecting outputs from state machine streams; and a program execution flow controller to examine computations and data in-flight and drive computations back and forth.

41. The method of claim 40 wherein the development environment comprises an interpreter component that uses the output of the first-phase translation tool comprising: an instruction interpreter which emulates the hardware platform in the execution of platform-specific hardware instructions; a dataflow simulator which emulates a streaming data environment, providing inputs to and collecting outputs from state machine streams; and a program execution flow controller to examine computations and data in-flight and drive computations back and forth. 43. The method of claim 41 wherein the development environment comprises a live inspection component comprising: an inspection method that instruments and attaches to a live running program on a particular hardware program, providing insights into the shape of a data graph; and an inspection method, executing after attachment, then extracts the state of the dataflow computation of a running program which provides an extremely precise and direct insight into computation along with data in consideration.

1. A system comprising: a hardware processor; a parser to, parse user interface information to be included within a user interface to be displayed to a user by an information display application; and identify at least one field, within the user interface, to receive user information from a user; a memory storage device to store data, the data including: the user information, the user interface information, a predefined authorized set of fields to receive the user information, predefined information corresponding to the predefined authorized set of fields, a list of addresses of fraudulent sources of the user interface information, and a list of addresses of verified sources of the user interface information; a detection module to determine, based on the list of addresses of fraudulent sources and based on the list of addresses of verified sources, whether the user interface information is associated with fraudulent activity or originates from a verified source; a form fill module to, in response to determining that the user interface information is associated with fraudulent activity, provide, using the hardware processor, a warning indicia relative to the at least one field of the user interface displayed to the user by the information display application, disable automatic provision of the user information into the at least one field, and prevent the user from manually inputting information into the at least one field that is displayed to the user by the information display application, and in response to determining that the user interface information originates from a verified source, enable automatic provision of the user information into the at least one field based on the at least one field corresponding to the predefined authorized set of fields and based on predefined information that corresponds to the at least one field; and a disposable credit card number module to, generate, in response to the determining that the user interface information originates from a verified source, a limited use credit card number for a financial transaction, and provide the limited use credit card number to the form fill module, wherein the form fill module is configured to automatically fill the limited use credit card number into a credit card number field, designated as such by the detection module, for the financial transaction in response to receiving the limited use credit card number from the disposable credit card number module and based on the credit card number field corresponding to the predefined authorized set of fields.

1. A system comprising: a hardware processor; a parser to, parse user interface information to be included within a user interface to be displayed to a user by an information display application; and identify at least one field, within the user interface, to receive user information from a user; a memory storage device to store data, the data including: the user information, the user interface information, a predefined authorized set of fields to receive the user information, predefined information corresponding to the predefined authorized set of fields, a list of addresses of fraudulent sources of the user interface information, and a list of addresses of verified sources of the user interface information; a detection module to determine, based on the list of addresses of fraudulent sources and based on the list of addresses of verified sources, whether the user interface information is associated with fraudulent activity or originates from a verified source; a form fill module to, in response to determining that the user interface information is associated with fraudulent activity, provide, using the hardware processor, a warning indicia relative to the at least one field of the user interface displayed to the user by the information display application, disable automatic provision of the user information into the at least one field, and prevent the user from manually inputting information into the at least one field that is displayed to the user by the information display application, and in response to determining that the user interface information originates from a verified source, enable automatic provision of the user information into the at least one field based on the at least one field corresponding to the predefined authorized set of fields and based on predefined information that corresponds to the at least one field; and a disposable credit card number module to, generate, in response to the determining that the user interface information originates from a verified source, a limited use credit card number for a financial transaction, and provide the limited use credit card number to the form fill module, wherein the form fill module is configured to automatically fill the limited use credit card number into a credit card number field, designated as such by the detection module, for the financial transaction in response to receiving the limited use credit card number from the disposable credit card number module and based on the credit card number field corresponding to the predefined authorized set of fields. 12. The system of claim 1 , wherein the warning indicia is provided within the at least one field to prevent the user from manually inputting information into the at least one field.

1. A computer system comprising: at least one processor, said computer system configured for: (A) receiving entity data comprising information associated with an online retailer and including one or more of: a name associated with the online retailer, a location associated with the online retailer; one or more products offered for sale by the online retailer; one or more prices associated with the one or more products; characteristics of customers who typically purchase from the online retailer; characteristics of customers who typically purchase from competitors of the online retailer; one or more categories of products and/or services sold by the online retailer; and one or more price ranges of products typically sold by the online retailer; (B) receiving social network data comprising data associated with a user; (C) receiving a set of search terms associated with the user for use in an Internet search, wherein the set of search terms comprise one or more search terms input by the user; (D) intercepting the set of search terms prior to performance of the Internet search; (E) creating a revised set of search terms from the intercepted set of search terms based at least in part on data selected from a group consisting of: the social network data; and the entity data; and (F) initiating an Internet search based, at least in part, on the revised set of search terms.

1. A computer system comprising: at least one processor, said computer system configured for: (A) receiving entity data comprising information associated with an online retailer and including one or more of: a name associated with the online retailer, a location associated with the online retailer; one or more products offered for sale by the online retailer; one or more prices associated with the one or more products; characteristics of customers who typically purchase from the online retailer; characteristics of customers who typically purchase from competitors of the online retailer; one or more categories of products and/or services sold by the online retailer; and one or more price ranges of products typically sold by the online retailer; (B) receiving social network data comprising data associated with a user; (C) receiving a set of search terms associated with the user for use in an Internet search, wherein the set of search terms comprise one or more search terms input by the user; (D) intercepting the set of search terms prior to performance of the Internet search; (E) creating a revised set of search terms from the intercepted set of search terms based at least in part on data selected from a group consisting of: the social network data; and the entity data; and (F) initiating an Internet search based, at least in part, on the revised set of search terms. 5. The computer system of claim 1 , wherein: (A) the Internet search returns one or more search results; and (B) the one or more search results are received by a client device associated with the user.

3. The computer-implemented method of claim 1 , further comprising, identifying a ranking associated with each identified data artifact.

3. The computer-implemented method of claim 1 , further comprising, identifying a ranking associated with each identified data artifact. 4. The computer-implemented method of claim 3 , wherein the subset of injected identified artifacts presented on the enterprise workspace page is selected based upon the identified ranking.

1. A method of rendering a document on a computerized device with language-related content in accordance with a selected language, comprising: identifying a first language content identifier in the document; generating a secure request using one or more of a public encryption key of a public/private key pair and secure authorization credentials; providing the secure request for language-related content to a language server, the language-related content being associated with a second language content identifier; receiving, from the language server in a secure response that is responsive to the secure request, the language-related content for which the second language content identifier corresponds to the first language content identifier; obtaining the language-related content from the secure response by one or more of decrypting the secure response and authenticating a digital signature associated with the secure response; and inserting at least a portion of the language-related content into the document at a location associated with the first language content identifier.

1. A method of rendering a document on a computerized device with language-related content in accordance with a selected language, comprising: identifying a first language content identifier in the document; generating a secure request using one or more of a public encryption key of a public/private key pair and secure authorization credentials; providing the secure request for language-related content to a language server, the language-related content being associated with a second language content identifier; receiving, from the language server in a secure response that is responsive to the secure request, the language-related content for which the second language content identifier corresponds to the first language content identifier; obtaining the language-related content from the secure response by one or more of decrypting the secure response and authenticating a digital signature associated with the secure response; and inserting at least a portion of the language-related content into the document at a location associated with the first language content identifier. 11. The method according to claim 1 , further comprising: receiving a language file that includes the language-related content.

7. An apparatus for running a computer program with a first part in a first programming language with a first data structure and a second part in a second programming language with a second data structure, which is different than the first data structure, comprising: means for compiling the first part of the computer program into a compiled first part of the computer program with a compiled first data structure; means for compiling the second part of the computer program, generating a second compiled part and transforming the second data structure of the second part of the computer program so that it is compatible with the compiled first data structure, so that the compiled second part of the computer program is able to read data in formatted according to the compiled first data structure; means for running the first compiled part; means for running the second compiled part; and means for sharing data between the first compiled part and the second compiled part formatted according to the compiled first data structure.

7. An apparatus for running a computer program with a first part in a first programming language with a first data structure and a second part in a second programming language with a second data structure, which is different than the first data structure, comprising: means for compiling the first part of the computer program into a compiled first part of the computer program with a compiled first data structure; means for compiling the second part of the computer program, generating a second compiled part and transforming the second data structure of the second part of the computer program so that it is compatible with the compiled first data structure, so that the compiled second part of the computer program is able to read data in formatted according to the compiled first data structure; means for running the first compiled part; means for running the second compiled part; and means for sharing data between the first compiled part and the second compiled part formatted according to the compiled first data structure. 9. The apparatus, as recited in claim 7, wherein the means for compiling the second part of the computer program, comprises a means for using the persistent shared symbol table to transform the second data structure.

9. One or more computer storage media storing computer executable instructions which when executed by one or more processors of one or more computers implement a method for debugging a declarative language application comprising: executing the declarative language application within a framework, wherein during execution of the declarative language application, one or more runtime objects are instantiated wherein at least one of the one or more runtime objects is a graphical user interface button which is displayed to a user, the graphical user interface button being a component of the declarative language application such that the button is generated during execution of the declarative language application whether the declarative language application is executed within or without the framework; while the declarative language application is being executed, receiving input from the user that selects one of the at least one graphical user interface buttons, the selection specifying the user's desire to view debugging information related to the selected graphical user interface button; and in response to the user input, displaying the debugging information related to the selected graphical user interface button, wherein the debugging information includes: lines of code within the source code of the declarative language application where the selected graphical user interface button is defined; a hierarchy of other graphical user interface elements that are related to the selected graphical user interface button; and values of the selected graphical user interface button.

9. One or more computer storage media storing computer executable instructions which when executed by one or more processors of one or more computers implement a method for debugging a declarative language application comprising: executing the declarative language application within a framework, wherein during execution of the declarative language application, one or more runtime objects are instantiated wherein at least one of the one or more runtime objects is a graphical user interface button which is displayed to a user, the graphical user interface button being a component of the declarative language application such that the button is generated during execution of the declarative language application whether the declarative language application is executed within or without the framework; while the declarative language application is being executed, receiving input from the user that selects one of the at least one graphical user interface buttons, the selection specifying the user's desire to view debugging information related to the selected graphical user interface button; and in response to the user input, displaying the debugging information related to the selected graphical user interface button, wherein the debugging information includes: lines of code within the source code of the declarative language application where the selected graphical user interface button is defined; a hierarchy of other graphical user interface elements that are related to the selected graphical user interface button; and values of the selected graphical user interface button. 13. The one or more computer storage media of claim 9 wherein displaying the lines of code further includes displaying event handlers associated with the selected graphical user interface button.

1. A method of creating a keyboard state table mapping a chording keyboard state k to a symbol s, for a chording keyboard comprising K keyboards states and a symbol set of S symbols, comprising the steps of: a) constructing an array of K*(K−1) entries wherein each entry represents a keyboard state transition of the chording keyboard from a first keyboard state k 1 to a second keyboard state k 2 ; b) constructing an exercise adapted to be performed by users of the chording keyboard wherein the users use the chording keyboard to generate a series of keyboard state transitions; c) measuring the difficulty with which a user generates each transition, such difficulty, as a single scalar, the, “psychomotor cost” of that transition; d) aggregating the psychomotor costs from different users of the exercise, for each transition in the array; e) entering the aggregated psychomotor cost for each transition in the array; f) identifying a text corpus comprising sequential symbols from the symbol set; g) creating a first keyboard state table that associates with each of the K keyboard states one symbol from the set of S symbols; assigning the first keyboard state table a keyboard state table under test; h) encoding the text corpus using the keyboard state table under test; i) summing the total psychomotor costs for all of the sequential transitions to complete step h, using the array to determine the psychomotor cost for each transition used in step h); this sum being the total psychomotor cost for the keyboard state table under test using the corpus; k) creating a set of alternative keyboard state tables by permuting a different subset of table lines from the keyboard state table under test; wherein the size of the subset is Z table lines; l) performing steps h) and i) for each table in the set of alternative keyboard state tables; wherein each table in the set of alternative keyboard state tables now becomes one keyboard state table under test; thus creating multiple keyboard state tables under test and copies of steps of this method; m) selecting the one table from the set of alternative keyboard state tables that has the lowest total psychomotor cost; the selected table becoming a new keyboard state table under test; n) repeating steps k) through m) until a terminating condition is reached; o) using a last selected table as the keyboard state table created by this method; wherein the chording keyboard is free of a requirement to release all keys between chords.

1. A method of creating a keyboard state table mapping a chording keyboard state k to a symbol s, for a chording keyboard comprising K keyboards states and a symbol set of S symbols, comprising the steps of: a) constructing an array of K*(K−1) entries wherein each entry represents a keyboard state transition of the chording keyboard from a first keyboard state k 1 to a second keyboard state k 2 ; b) constructing an exercise adapted to be performed by users of the chording keyboard wherein the users use the chording keyboard to generate a series of keyboard state transitions; c) measuring the difficulty with which a user generates each transition, such difficulty, as a single scalar, the, “psychomotor cost” of that transition; d) aggregating the psychomotor costs from different users of the exercise, for each transition in the array; e) entering the aggregated psychomotor cost for each transition in the array; f) identifying a text corpus comprising sequential symbols from the symbol set; g) creating a first keyboard state table that associates with each of the K keyboard states one symbol from the set of S symbols; assigning the first keyboard state table a keyboard state table under test; h) encoding the text corpus using the keyboard state table under test; i) summing the total psychomotor costs for all of the sequential transitions to complete step h, using the array to determine the psychomotor cost for each transition used in step h); this sum being the total psychomotor cost for the keyboard state table under test using the corpus; k) creating a set of alternative keyboard state tables by permuting a different subset of table lines from the keyboard state table under test; wherein the size of the subset is Z table lines; l) performing steps h) and i) for each table in the set of alternative keyboard state tables; wherein each table in the set of alternative keyboard state tables now becomes one keyboard state table under test; thus creating multiple keyboard state tables under test and copies of steps of this method; m) selecting the one table from the set of alternative keyboard state tables that has the lowest total psychomotor cost; the selected table becoming a new keyboard state table under test; n) repeating steps k) through m) until a terminating condition is reached; o) using a last selected table as the keyboard state table created by this method; wherein the chording keyboard is free of a requirement to release all keys between chords. 8. The method of claim 1 wherein: the method of claim 1 is free of perceptual, motor or psychomotor costs associated with individual chords.

11. A system for presenting ranked comments based on a correlation between a portion of a video and comments associated with the video, the system comprising: one or more hardware processors configured to: receive first text data of words in a video presented to a first user in a first instance of a user interface; receive second text data that is part of a first user comment posted by the first user in association with the video, wherein the first user comment was posted using the first instance of the user interface; identify a first string of characters from the second text data that is likely to include a quote of the first text data, wherein the first string of characters includes a plurality of words; in response to identifying the first string of characters, compare the first string of characters to at least a second string of characters from the first text data; determine how different the first string of characters is from the second string of characters based on the comparison; determine a degree of correlation between the first string of characters and the first text data based at least in part on how different the second string of characters is from the first string of characters, wherein the degree of correlation is less than it would be if there were no differences between the two strings by an amount that is based on how different the two strings of characters are; generate a score for the first comment based at least in part on how closely the first string of characters quotes the second string of characters represented by the degree of correlation and based at least in part on a length of the first string of characters; determine a ranking of a plurality of comments associated with the video, including the first user comment and a plurality of previously posted comments, based at least in part on the score; cause at least two of the plurality of comments associated with the video to be presented to a second user in association with the video presented in a second instance of the user interface in an order that is based at least in part on the ranking; and cause a link to a portion of the video that corresponds to the second string of characters to be associated with the first user comment based on the degree of correlation between the first string of characters and the second string of characters, wherein selection of the link causes the portion of the video to be presented in the second instance of the user interface.

11. A system for presenting ranked comments based on a correlation between a portion of a video and comments associated with the video, the system comprising: one or more hardware processors configured to: receive first text data of words in a video presented to a first user in a first instance of a user interface; receive second text data that is part of a first user comment posted by the first user in association with the video, wherein the first user comment was posted using the first instance of the user interface; identify a first string of characters from the second text data that is likely to include a quote of the first text data, wherein the first string of characters includes a plurality of words; in response to identifying the first string of characters, compare the first string of characters to at least a second string of characters from the first text data; determine how different the first string of characters is from the second string of characters based on the comparison; determine a degree of correlation between the first string of characters and the first text data based at least in part on how different the second string of characters is from the first string of characters, wherein the degree of correlation is less than it would be if there were no differences between the two strings by an amount that is based on how different the two strings of characters are; generate a score for the first comment based at least in part on how closely the first string of characters quotes the second string of characters represented by the degree of correlation and based at least in part on a length of the first string of characters; determine a ranking of a plurality of comments associated with the video, including the first user comment and a plurality of previously posted comments, based at least in part on the score; cause at least two of the plurality of comments associated with the video to be presented to a second user in association with the video presented in a second instance of the user interface in an order that is based at least in part on the ranking; and cause a link to a portion of the video that corresponds to the second string of characters to be associated with the first user comment based on the degree of correlation between the first string of characters and the second string of characters, wherein selection of the link causes the portion of the video to be presented in the second instance of the user interface. 12. The system of claim 11 , wherein the score is boosted based on the length of the first string of characters.

17. The language reordering system of claim 15 wherein said preprocessing module is further configured to generate reordering probabilities by calculating probabilities of reordering words from said word string into said reordered word strings.

17. The language reordering system of claim 15 wherein said preprocessing module is further configured to generate reordering probabilities by calculating probabilities of reordering words from said word string into said reordered word strings. 18. The language reordering system of claim 17 wherein said preprocessing module is further configured to identify at least one statistically preferred reordered word string from said reordered word strings based on said reordering probabilities.

1. A method for managing state data of a service in a service-oriented architecture by establishing a pluggable meta-data processor comprising: establishing a platform independent, extensible meta-data information model to define meta-data about the state data of the service; establishing an extensible meta-data definition comprising an extensible set of attributes of the state data of the service, so as to enable the service to extend its state with change notification semantics; configuring one or more extensible semantic processors for interpreting the semantics of a state change query created and sent by a requesting client directly to the service, wherein query language and the one or more semantic processors are each chosen by the client, and which state change query is forwarded from the service to a client-chosen semantic processor; configuring a controller meta-data processor; and defining contracts among said semantic processors.

1. A method for managing state data of a service in a service-oriented architecture by establishing a pluggable meta-data processor comprising: establishing a platform independent, extensible meta-data information model to define meta-data about the state data of the service; establishing an extensible meta-data definition comprising an extensible set of attributes of the state data of the service, so as to enable the service to extend its state with change notification semantics; configuring one or more extensible semantic processors for interpreting the semantics of a state change query created and sent by a requesting client directly to the service, wherein query language and the one or more semantic processors are each chosen by the client, and which state change query is forwarded from the service to a client-chosen semantic processor; configuring a controller meta-data processor; and defining contracts among said semantic processors. 2. The method of claim 1 , further comprising configuring platform dependent models to facilitate semantic processing of meta-data of the state data of the service based on said extensible meta-data information model.

1. A face recognition method on a computing device, comprising: obtaining a plurality of training face images which belongs to a plurality of face classes, wherein a face class includes one or more training face images and represents an identification of the one or more training face images; obtaining a plurality of training dictionaries corresponding to the plurality of training face images, wherein the plurality of training dictionaries include a plurality of deep feature matrices; obtaining an input face image; partitioning the input face image into a plurality of blocks; extracting corresponding deep feature vectors of the plurality of blocks of the input face image using a deep learning network; applying a collaborative representation model to represent the deep feature vectors of the blocks of the input face image with the training dictionaries and representation vectors; computing residual errors for the face classes, a residual error for a face class being a summation of errors for all blocks corresponding to the training face images in the face class, wherein an error for a block exists between a feature vector of the block in the input face image and the collaborative representation model of the block corresponding to the face class; classifying the input face image by selecting a face class that yields a minimum residual error as a recognition face class; and presenting the recognition face class of the input face image.

1. A face recognition method on a computing device, comprising: obtaining a plurality of training face images which belongs to a plurality of face classes, wherein a face class includes one or more training face images and represents an identification of the one or more training face images; obtaining a plurality of training dictionaries corresponding to the plurality of training face images, wherein the plurality of training dictionaries include a plurality of deep feature matrices; obtaining an input face image; partitioning the input face image into a plurality of blocks; extracting corresponding deep feature vectors of the plurality of blocks of the input face image using a deep learning network; applying a collaborative representation model to represent the deep feature vectors of the blocks of the input face image with the training dictionaries and representation vectors; computing residual errors for the face classes, a residual error for a face class being a summation of errors for all blocks corresponding to the training face images in the face class, wherein an error for a block exists between a feature vector of the block in the input face image and the collaborative representation model of the block corresponding to the face class; classifying the input face image by selecting a face class that yields a minimum residual error as a recognition face class; and presenting the recognition face class of the input face image. 5. The face recognition method according to claim 1 , further comprising: storing user preference information along with the training dictionaries corresponding to one or more users; and after obtaining the face class of the input face image, recommending personalized contents to a user corresponding to the face class according to the user preference information.

1. A method for providing access to a resource on a network, comprising the steps of: receiving at an access server an identification of said resource, said identification includes an absolute portion and a query portion; using said query portion to identify a first access rule from a plurality of access rules stored at said access server; determining whether access to said resource is authorized based on said identification of said resource without granting authorization to said resource, said determining including accessing said first access rule for said resource and accessing an identity profile for a first user to determine whether at least a portion of said first access rule is satisfied based on information in said identity profile, wherein said first access rule is not part of said identity profile; and allowing access to said resource, said step of allowing access is not performed if said first access rule is not satisfied.

1. A method for providing access to a resource on a network, comprising the steps of: receiving at an access server an identification of said resource, said identification includes an absolute portion and a query portion; using said query portion to identify a first access rule from a plurality of access rules stored at said access server; determining whether access to said resource is authorized based on said identification of said resource without granting authorization to said resource, said determining including accessing said first access rule for said resource and accessing an identity profile for a first user to determine whether at least a portion of said first access rule is satisfied based on information in said identity profile, wherein said first access rule is not part of said identity profile; and allowing access to said resource, said step of allowing access is not performed if said first access rule is not satisfied. 2. The method according to claim 1 , wherein: said first access rule is an authorization rule.

13. 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 a query having an original term; determining a plurality of substitution contexts for the original term, wherein each substitution context includes one or more context terms, and wherein, when the substitution context is associated with a substitute term, the substitution context specifies substituting the original term with the substitute term in the query if and only if the one or more context terms occur in the query at a position relative to the original term specified by the substitution context; computing respective scores for each first substitution context of the plurality of substitution contexts for the original term including: generating first alternate set comprising terms that each occur at least once in a textual collection at a position specified by the first substitution context, the position being relative to one or more context terms of the first substitution context, comprising respective first rates for each first term in the first alternate set, each first rate for a first term representing (i) how often the first term occurs in the textual collection at the position specified by the first substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, generating a second alternate set comprising terms that each occur at least once in a textual collection at a position specified by a different second substitution context of the plurality of substitution contexts for the original term, the position being relative to one or more context terms of the second substitution context, computing respective second rates for each second term in the second alternate set, each second rate for a second term representing (i) how often the second term occurs in the textual collection at the position specified by the second substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, computing an alternate set difference between the first alternate set and the second alternate set, the alternate set difference representing a measure of divergence between the computed first rates for the first alternate set and the computed second rates for the second alternate set, and computing the score for the first substitution context relative to the second substitution context based on the alternate set difference between the first alternate set and the second alternate set; classifying each of the plurality of substitution contexts into a first category or a second category based on the respective score computed for each substitution context; associating the original term with one or more substitution contexts in the first category; and providing only substitution contexts in the first category to a substitute term generation process that generates substitute terms for the original term in the query.

13. 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 a query having an original term; determining a plurality of substitution contexts for the original term, wherein each substitution context includes one or more context terms, and wherein, when the substitution context is associated with a substitute term, the substitution context specifies substituting the original term with the substitute term in the query if and only if the one or more context terms occur in the query at a position relative to the original term specified by the substitution context; computing respective scores for each first substitution context of the plurality of substitution contexts for the original term including: generating first alternate set comprising terms that each occur at least once in a textual collection at a position specified by the first substitution context, the position being relative to one or more context terms of the first substitution context, comprising respective first rates for each first term in the first alternate set, each first rate for a first term representing (i) how often the first term occurs in the textual collection at the position specified by the first substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, generating a second alternate set comprising terms that each occur at least once in a textual collection at a position specified by a different second substitution context of the plurality of substitution contexts for the original term, the position being relative to one or more context terms of the second substitution context, computing respective second rates for each second term in the second alternate set, each second rate for a second term representing (i) how often the second term occurs in the textual collection at the position specified by the second substitution context compared to (ii) how often the original term occurs in the textual collection at the position specified by the first substitution context, computing an alternate set difference between the first alternate set and the second alternate set, the alternate set difference representing a measure of divergence between the computed first rates for the first alternate set and the computed second rates for the second alternate set, and computing the score for the first substitution context relative to the second substitution context based on the alternate set difference between the first alternate set and the second alternate set; classifying each of the plurality of substitution contexts into a first category or a second category based on the respective score computed for each substitution context; associating the original term with one or more substitution contexts in the first category; and providing only substitution contexts in the first category to a substitute term generation process that generates substitute terms for the original term in the query. 17. The computer program product of claim 13 , wherein the operations further comprise: determining that at least one substitution context is classified in the first category; and in response to determining that at least one substitution context is in the first category, classifying a general context into the second category.

1. A system comprising: an imaging device that acquires an image; and, an acquisition layer logically located between a source manager operating in accordance with the TWAIN protocol and the imaging device, the source manager being called by an application when a user of the system requests to acquire the image, the acquisition layer including imaging acquisition logic that receives the image from the imaging device and performs optical character recognition (OCR) that extracts machine editable text from the image, wherein the acquisition layer forwards the image to the application and makes the machine editable text available to the user.

1. A system comprising: an imaging device that acquires an image; and, an acquisition layer logically located between a source manager operating in accordance with the TWAIN protocol and the imaging device, the source manager being called by an application when a user of the system requests to acquire the image, the acquisition layer including imaging acquisition logic that receives the image from the imaging device and performs optical character recognition (OCR) that extracts machine editable text from the image, wherein the acquisition layer forwards the image to the application and makes the machine editable text available to the user. 18. The system of claim 1 wherein optical character recognition (OCR) that extracts machine editable text includes extracting machine editable text from a bar code.

1. A method for automatic extraction of process goals from a semantically annotated structured process model of a process comprising model elements comprising functions and events named by natural language expressions and annotated with semantic linkages to a reference process ontology comprising the steps of: (a) splitting said process model, at each exit split connector that leads to more than one end event, into a plurality of partial process models separated for each end event of said process model, such that each partial process model of the plurality of partial process models has one or more of the model elements and only one end event; (b) creating for each partial process model an annotated partial process model by separately annotating the one or more of the model elements of each partial process model with extracted process goals and constraints, such that (1) each start event is annotated with an extracted root goal constraint, (2) each function is annotated with an extracted process goal, (3) each event is annotated with an extracted local goal constraint, and (4) the end event is annotated with an extracted root goal, wherein each process goal represents a purpose or an outcome of process; (c) decoupling of the process goals from each annotated partial process model; and (d) generating a hierarchical process goal tree for each annotated partial process model by organizing the decoupled process goals as goal nodes into the hierarchical process goal tree starting with the end event as a root goal node that is decomposed into a set of subgoals by inserting the goal nodes and decomposition nodes into the goal tree depending on the annotated model elements detected.

1. A method for automatic extraction of process goals from a semantically annotated structured process model of a process comprising model elements comprising functions and events named by natural language expressions and annotated with semantic linkages to a reference process ontology comprising the steps of: (a) splitting said process model, at each exit split connector that leads to more than one end event, into a plurality of partial process models separated for each end event of said process model, such that each partial process model of the plurality of partial process models has one or more of the model elements and only one end event; (b) creating for each partial process model an annotated partial process model by separately annotating the one or more of the model elements of each partial process model with extracted process goals and constraints, such that (1) each start event is annotated with an extracted root goal constraint, (2) each function is annotated with an extracted process goal, (3) each event is annotated with an extracted local goal constraint, and (4) the end event is annotated with an extracted root goal, wherein each process goal represents a purpose or an outcome of process; (c) decoupling of the process goals from each annotated partial process model; and (d) generating a hierarchical process goal tree for each annotated partial process model by organizing the decoupled process goals as goal nodes into the hierarchical process goal tree starting with the end event as a root goal node that is decomposed into a set of subgoals by inserting the goal nodes and decomposition nodes into the goal tree depending on the annotated model elements detected. 6. The method according to claim 1 , wherein a named process element is a function provided for performing a task on a process object to transform said process object from an initial state to a resulting state or an event comprising a text clause.

1. A method for monitoring transmission of email through a computer system, said computer system comprising a server and one or more clients having an email account, the method comprising: (a) gathering statistics relating to transmission behavior of prior emails relating to a first email account on said computer system; (b) generating a profile relating to the transmission behavior of email relating to said first email account based on said statistics, wherein generating a profile comprises grouping email addresses into one or more cliques based on the prior occurrence of email addresses within the same emails in a group of mails; and (c) determining if a violation of email security has occurred by comparing one or more select emails relating to said first email account to said profile.

1. A method for monitoring transmission of email through a computer system, said computer system comprising a server and one or more clients having an email account, the method comprising: (a) gathering statistics relating to transmission behavior of prior emails relating to a first email account on said computer system; (b) generating a profile relating to the transmission behavior of email relating to said first email account based on said statistics, wherein generating a profile comprises grouping email addresses into one or more cliques based on the prior occurrence of email addresses within the same emails in a group of mails; and (c) determining if a violation of email security has occurred by comparing one or more select emails relating to said first email account to said profile. 3. The method according to claim 1 , wherein gathering statistics relating to the transmission behavior of prior emails comprises gathering statistics relating to the email addresses of email sent by said first email account.

1. A text entry system comprising: a user input device comprising: an auto-correcting keyboard region comprising a plurality of the characters of a character set, wherein locations having known coordinates in the auto-correcting keyboard region are associated with one or more of the character set members, wherein a location is determined when a user interacts with the user input device within the auto-correcting keyboard region and the determined interaction location is added to a current input sequence; and a memory containing a plurality of objects, wherein one or more objects comprise a string of one or a plurality of characters forming all or part of a word or phrase; an output device; and a processor coupled to the user input device, memory, and output device, said processor comprising: a distance value calculation component which, for a determined interaction location in said current input sequence, calculates a set of distance values between the interaction location and the known coordinate locations corresponding to one or a plurality of characters within the auto-correcting region; an object evaluation component which, for said current input sequence, identifies one or a plurality of candidate objects in memory, and for one or more identified candidate objects, evaluates identified candidate objects by calculating a matching metric for each candidate object by summing the distance values calculated from each interaction location in the input sequence to the location assigned to the character in the corresponding position of the candidate object and applying a weighting function, wherein the weighting function comprises multiplying the sum of the distance values by the base 2 logarithm of the ordinal ranking of the object, and, if more than one candidate object is identified, ranks the evaluated candidate objects based on the calculated matching metric values; and a selection component for identifying candidate objects according to their evaluated ranking, presenting any identified objects to the user, and enabling the user to select from among any presented objects for output to the output device.

1. A text entry system comprising: a user input device comprising: an auto-correcting keyboard region comprising a plurality of the characters of a character set, wherein locations having known coordinates in the auto-correcting keyboard region are associated with one or more of the character set members, wherein a location is determined when a user interacts with the user input device within the auto-correcting keyboard region and the determined interaction location is added to a current input sequence; and a memory containing a plurality of objects, wherein one or more objects comprise a string of one or a plurality of characters forming all or part of a word or phrase; an output device; and a processor coupled to the user input device, memory, and output device, said processor comprising: a distance value calculation component which, for a determined interaction location in said current input sequence, calculates a set of distance values between the interaction location and the known coordinate locations corresponding to one or a plurality of characters within the auto-correcting region; an object evaluation component which, for said current input sequence, identifies one or a plurality of candidate objects in memory, and for one or more identified candidate objects, evaluates identified candidate objects by calculating a matching metric for each candidate object by summing the distance values calculated from each interaction location in the input sequence to the location assigned to the character in the corresponding position of the candidate object and applying a weighting function, wherein the weighting function comprises multiplying the sum of the distance values by the base 2 logarithm of the ordinal ranking of the object, and, if more than one candidate object is identified, ranks the evaluated candidate objects based on the calculated matching metric values; and a selection component for identifying candidate objects according to their evaluated ranking, presenting any identified objects to the user, and enabling the user to select from among any presented objects for output to the output device. 20. The system of claim 1 , wherein a candidate is selected through an alternate input modality.

1. A method performed by at least one computer systems of providing an archival index of a plurality of documents, the method comprising: maintaining an index of a plurality of documents, the index relating phrases contained in at least some of the documents with documents containing the phrases; accessing a document of the plurality of documents; determining, using a processor of the at least one computer system, whether the document has changed since a previous date the document was indexed; responsive to determining that the document has changed, indicating a first date range, including the previous date, for which the document is valid; indexing the document to obtain current information-retrieval relevance data for the document, the current information-retrieval relevance data including phrases contained in a current version of the document; storing the current information-retrieval relevance data in association with a current date range for the document; and maintaining previous information-retrieval relevance data for the document in association with the first date range, the previous information-retrieval relevance data including phrases contained in a version of the document that was valid during the first date range.

1. A method performed by at least one computer systems of providing an archival index of a plurality of documents, the method comprising: maintaining an index of a plurality of documents, the index relating phrases contained in at least some of the documents with documents containing the phrases; accessing a document of the plurality of documents; determining, using a processor of the at least one computer system, whether the document has changed since a previous date the document was indexed; responsive to determining that the document has changed, indicating a first date range, including the previous date, for which the document is valid; indexing the document to obtain current information-retrieval relevance data for the document, the current information-retrieval relevance data including phrases contained in a current version of the document; storing the current information-retrieval relevance data in association with a current date range for the document; and maintaining previous information-retrieval relevance data for the document in association with the first date range, the previous information-retrieval relevance data including phrases contained in a version of the document that was valid during the first date range. 11. The method of claim 1 , wherein indexing the document to obtain current information-retrieval relevance data for the document includes generating a posting list for a phrase contained in the document and associating a document identifier with the phrase in the posting list.

14. A non-transitory computer-readable medium comprising instructions for execution on a processor, the instructions including: storing, in an application record data store, a plurality of application records corresponding respectively to a plurality of applications; storing, in a privacy record data store, for each application of at least some of the plurality of applications, a global privacy indicator specific to the application and applicable to all users; in response to receiving a first search query from a user device: identifying a plurality of search results responsive to the first search query from the application record data store, the plurality of search results corresponding to respective ones of the plurality of application records; for each search result of the plurality of search results, selectively determining a privacy indicator based on the privacy record data store; determining a search sensitivity value based on the privacy indicators; declaring the first search query as private based on the search sensitivity value; transmitting the plurality of search results to the user device; and in response to the first search query being declared as private, transmitting a search privacy indicator to the user device.

14. A non-transitory computer-readable medium comprising instructions for execution on a processor, the instructions including: storing, in an application record data store, a plurality of application records corresponding respectively to a plurality of applications; storing, in a privacy record data store, for each application of at least some of the plurality of applications, a global privacy indicator specific to the application and applicable to all users; in response to receiving a first search query from a user device: identifying a plurality of search results responsive to the first search query from the application record data store, the plurality of search results corresponding to respective ones of the plurality of application records; for each search result of the plurality of search results, selectively determining a privacy indicator based on the privacy record data store; determining a search sensitivity value based on the privacy indicators; declaring the first search query as private based on the search sensitivity value; transmitting the plurality of search results to the user device; and in response to the first search query being declared as private, transmitting a search privacy indicator to the user device. 17. The non-transitory computer-readable medium of claim 14 wherein the user device generated the first search query based on input from a first user, and wherein the instructions for determining the privacy indicator for a first application of the at least some of the plurality of applications include: in response to presence of a user privacy indicator with respect to the first user and the first application, selecting the user privacy indicator; and in response to not being overridden by presence of the user privacy indicator, selecting the global privacy indicator specific to the first application.

13. A system of providing speech recognition to a user on a mobile device, the system comprising: a hearing assistance application on a mobile device, the mobile device having a display screen, the hearing assistance application configured to receive audio data and transmit the audio data; a hearing assistance processor configured for real-time data exchange with the hearing assistance application, at least one voice processor and at least one recognition processor, the hearing assistance processor configured to receive the audio data from the hearing assistance application and transmit the audio data to the at least one recognition processor to convert the audio data into corresponding text data, receive the text data from the at least one recognition processor, and transmit the text data to the hearing assistance application; the hearing assistance application configured to display at least a portion of the text data on the display screen of the mobile device and receive confirmation to transmit the audio data, the text data or additional audio data derived from the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor is configured to, in response to receiving the confirmation, transmit the audio data, the text data, or the additional audio data derived from the text data to the telephony device via the at least one voice processor, the hearing assistance processor is configured to receive additional audio data from the telephony device and interact with the at least one recognition processor to determine if the additional audio data is clear or otherwise of sufficient quality to be processed by the at least one recognition processor, and upon determining that the additional audio data is not clear or of insufficient quality to be processed, sending audio feedback to the telephony device that prompts for improved audio data; the hearing assistance application being configured to receive additional audio data from the user of the mobile device and transmit the additional audio data to the hearing assistance processor; the hearing assistance processor being configured to transmit the additional audio data to the at least one recognition processor to convert the additional audio data into corresponding additional text data, receive the additional text data from the at least one recognition processor, and transmit the additional text data to the hearing assistance application; the hearing assistance application being configured to display at least a portion of the additional text data on the display screen of the mobile device and receive confirmation to transmit the additional audio data or the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor being configured to, in response to receiving the confirmation, transmit the additional audio data, the text data or generated audio data corresponding to the text data to the telephony device via the at least one voice processor.

13. A system of providing speech recognition to a user on a mobile device, the system comprising: a hearing assistance application on a mobile device, the mobile device having a display screen, the hearing assistance application configured to receive audio data and transmit the audio data; a hearing assistance processor configured for real-time data exchange with the hearing assistance application, at least one voice processor and at least one recognition processor, the hearing assistance processor configured to receive the audio data from the hearing assistance application and transmit the audio data to the at least one recognition processor to convert the audio data into corresponding text data, receive the text data from the at least one recognition processor, and transmit the text data to the hearing assistance application; the hearing assistance application configured to display at least a portion of the text data on the display screen of the mobile device and receive confirmation to transmit the audio data, the text data or additional audio data derived from the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor is configured to, in response to receiving the confirmation, transmit the audio data, the text data, or the additional audio data derived from the text data to the telephony device via the at least one voice processor, the hearing assistance processor is configured to receive additional audio data from the telephony device and interact with the at least one recognition processor to determine if the additional audio data is clear or otherwise of sufficient quality to be processed by the at least one recognition processor, and upon determining that the additional audio data is not clear or of insufficient quality to be processed, sending audio feedback to the telephony device that prompts for improved audio data; the hearing assistance application being configured to receive additional audio data from the user of the mobile device and transmit the additional audio data to the hearing assistance processor; the hearing assistance processor being configured to transmit the additional audio data to the at least one recognition processor to convert the additional audio data into corresponding additional text data, receive the additional text data from the at least one recognition processor, and transmit the additional text data to the hearing assistance application; the hearing assistance application being configured to display at least a portion of the additional text data on the display screen of the mobile device and receive confirmation to transmit the additional audio data or the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor being configured to, in response to receiving the confirmation, transmit the additional audio data, the text data or generated audio data corresponding to the text data to the telephony device via the at least one voice processor. 18. The system of claim 13 , wherein the hearing assistance processor is configured to identify a user providing the audio data and transmit the identity of the user to the at least one recognition processor to improve accuracy of recognition.

1. A board game, comprising: a game board having thereon a plurality of labeled scripture boxes arranged into a plurality of labeled categories, said scripture boxes being contiguous within each said category said categories being arranged in a closed circuit; and a plurality of scripture cards each identified by a corresponding scripture box label, each scripture card having thereon an indicia representing at least one biblical scripture such that each said scripture card is assignable to a corresponding scripture box during the play of the game; a chance box located in said closed circuit between a selected pair of categories; at least one each of a set of chance cards identified by label as CHALLENGE, FEEDBACK, PLAY AGAIN or LOSE TURN; and a plurality of CHALLENGE cards each identifying by label a permutation of challenge among a plurality of players.

1. A board game, comprising: a game board having thereon a plurality of labeled scripture boxes arranged into a plurality of labeled categories, said scripture boxes being contiguous within each said category said categories being arranged in a closed circuit; and a plurality of scripture cards each identified by a corresponding scripture box label, each scripture card having thereon an indicia representing at least one biblical scripture such that each said scripture card is assignable to a corresponding scripture box during the play of the game; a chance box located in said closed circuit between a selected pair of categories; at least one each of a set of chance cards identified by label as CHALLENGE, FEEDBACK, PLAY AGAIN or LOSE TURN; and a plurality of CHALLENGE cards each identifying by label a permutation of challenge among a plurality of players. 6. The board game of claim 1, wherein said chance box is identified by label as one of CHALLENGE, FEEDBACK, PLAY AGAIN or LOSE TURN.

8. The method of claim 5 , wherein transforming the expanded stored phoneme vector into an orthogonal form uses singular-value decomposition and wherein transforming the expanded received-signal vector into an orthogonal form using singular-value decomposition further conforms the stored-phoneme vector into the hypersphere.

8. The method of claim 5 , wherein transforming the expanded stored phoneme vector into an orthogonal form uses singular-value decomposition and wherein transforming the expanded received-signal vector into an orthogonal form using singular-value decomposition further conforms the stored-phoneme vector into the hypersphere. 9. The method of claim 8 , wherein determining a distance associated with the orthogonal form of the expanded received-signal vector and each orthogonal form of the expanded stored-phoneme vectors further comprises: comparing a distance from the center of the hypersphere of the orthogonal form of the expanded received-signal vector with a distance from the center of the hypersphere for each orthogonal form of the expanded stored-phoneme vector.

13. An apparatus comprising: means for determining a sentiment value associated with anchortext of a search engine result and for determining a sentiment value of a web page referenced by the anchortext; and means for determining whether there is a divergence between the sentiment value associated with the anchortext and the sentiment value associated with the web page.

13. An apparatus comprising: means for determining a sentiment value associated with anchortext of a search engine result and for determining a sentiment value of a web page referenced by the anchortext; and means for determining whether there is a divergence between the sentiment value associated with the anchortext and the sentiment value associated with the web page. 14. The apparatus of claim 13 , and further comprising: means for determining whether said divergence between the sentiment value associated with the anchortext and the sentiment value associated with the web page is a valid condition.

1. A method comprising: receiving a search request from a search user; creating a network of entities, the network including relationships among the entities, wherein the entities include a search user entity representing the search user and one or more result entities; defining trust components and similarity components for the relationships among the entities, wherein the similarity components express relative similarity of the entities and the trust components express relative trust among the entities; identifying a plurality of search results, wherein the one or more result entities provide the plurality of search results and the plurality of search results are identified based on the search request; for the plurality of search results provided by the one or more result entities, determining, from the network, a set of relationships connecting the search user entity to the one or more result entities along one or more paths; determining, based on the set of relationships connecting the search user entity to the one or more result entities, relevance values for the plurality of search results, wherein the relevance values are determined based on both: individual similarity components that express relative similarity of individual entities along the one or more paths, and individual trust components that express relative trust among the individual entities along the one or more paths; ranking the plurality of search results based on the relevance values for the plurality of search results; and presenting, to the search user, individual search results from the plurality of search results according to the ranking, wherein at least the ranking is performed by a hardware computer processor.

1. A method comprising: receiving a search request from a search user; creating a network of entities, the network including relationships among the entities, wherein the entities include a search user entity representing the search user and one or more result entities; defining trust components and similarity components for the relationships among the entities, wherein the similarity components express relative similarity of the entities and the trust components express relative trust among the entities; identifying a plurality of search results, wherein the one or more result entities provide the plurality of search results and the plurality of search results are identified based on the search request; for the plurality of search results provided by the one or more result entities, determining, from the network, a set of relationships connecting the search user entity to the one or more result entities along one or more paths; determining, based on the set of relationships connecting the search user entity to the one or more result entities, relevance values for the plurality of search results, wherein the relevance values are determined based on both: individual similarity components that express relative similarity of individual entities along the one or more paths, and individual trust components that express relative trust among the individual entities along the one or more paths; ranking the plurality of search results based on the relevance values for the plurality of search results; and presenting, to the search user, individual search results from the plurality of search results according to the ranking, wherein at least the ranking is performed by a hardware computer processor. 7. The method of claim 1 , wherein an individual result entity is an organization that provides one or more of the individual search results that are presented to the search user.

13. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in an instructional environment, train of a dynamic string analysis handler of a string analysis module to effectively handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application, wherein the dynamic string analysis handler is operating in a training mode, wherein an effectiveness of the dynamic string analysis handler is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, upon completion of the training, synthesize a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon interactions between the dynamic string analysis handler and client application when handling the subset of string queries during training, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in the operational environment, dynamically handle the plurality of string queries having the plurality of contextual metadata received from the client application in accordance with the string analysis algorithm selection policy by the dynamic string analysis handler, wherein the dynamic string analysis handler is operating in a production mode, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined.

13. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in an instructional environment, train of a dynamic string analysis handler of a string analysis module to effectively handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application, wherein the dynamic string analysis handler is operating in a training mode, wherein an effectiveness of the dynamic string analysis handler is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, upon completion of the training, synthesize a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon interactions between the dynamic string analysis handler and client application when handling the subset of string queries during training, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when in the operational environment, dynamically handle the plurality of string queries having the plurality of contextual metadata received from the client application in accordance with the string analysis algorithm selection policy by the dynamic string analysis handler, wherein the dynamic string analysis handler is operating in a production mode, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined. 14. The computing system of claim 13 , wherein program instructions to train the dynamic string analysis handler in the instructional environment further comprise: program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to receive a query request from the client application, wherein said query request comprises the string query of the subset and the plurality of contextual metadata associated with the string query of the subset; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, select a string analysis algorithm from a plurality of string analysis algorithms available for use by the string analysis module that best addresses the received query request, wherein said selection utilizes a heuristic strategy; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, execute the selected string analysis algorithm upon the string query of the subset; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, convey results of the execution of the selected string analysis algorithm to the client application; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, receive selection feedback having a selection score from the client application for the results of the executed string analysis algorithm, wherein said selection score quantitatively expresses the effectiveness of the selected string analysis algorithm; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, when the received selection feedback, indicate an unsatisfactory selection of the string analysis algorithm, automatically modifying the heuristic strategy with respect to at least one of the string query of the subset, the plurality of contextual metadata associated with the string query of the subset, and a plurality of selection rules that influence the heuristic strategy.

1. An information handling system that serves as a question and answering (QA) system, the system comprising: one or more processors; a memory coupled to at least one of the processors; a network adapter that connects the information handling system to a computer network; and a set of instructions stored in the memory and executed by at least one of the processors to utilize unstructured corpora, wherein the set of instructions perform actions of: receiving, from a first user, a question at a question answering (QA) system; identifying a set of one or more second users that are subjects of the question; generating a private corpora associated with the first user, wherein the private corpora is generated from a first set of one or more private data stores associated with a first user and a second set of one or more private data stores associated with the set of one or more second users, wherein access to the second set of private data stores is provided to the first user by the set of second users; retrieving responsive data to the question from the private corpora, wherein the responsive data is ranked based on a relevance to the question; identifying one or more likely answers based on the ranked responsive data; and providing the one or more likely answers to the first user.

1. An information handling system that serves as a question and answering (QA) system, the system comprising: one or more processors; a memory coupled to at least one of the processors; a network adapter that connects the information handling system to a computer network; and a set of instructions stored in the memory and executed by at least one of the processors to utilize unstructured corpora, wherein the set of instructions perform actions of: receiving, from a first user, a question at a question answering (QA) system; identifying a set of one or more second users that are subjects of the question; generating a private corpora associated with the first user, wherein the private corpora is generated from a first set of one or more private data stores associated with a first user and a second set of one or more private data stores associated with the set of one or more second users, wherein access to the second set of private data stores is provided to the first user by the set of second users; retrieving responsive data to the question from the private corpora, wherein the responsive data is ranked based on a relevance to the question; identifying one or more likely answers based on the ranked responsive data; and providing the one or more likely answers to the first user. 3. The information handling system of claim 1 wherein the actions further comprise: receiving one or more access restrictions from a selected one of the set of second users, wherein the access restrictions prevent the first user from accessing one or more types of data from the selected second user's private data stores.

15. An exchange computer system configured to distribute market data, the system comprising: a processor; a computer-readable medium containing computer-executable instructions that, when executed by the processor, cause the system to perform the steps comprising: (a) transmitting a first template defining a plurality of fields; (b) transmitting a first market data message having a plurality of fields separated by delimiters and formatted in accordance with the first template; (c) after (b) transmitting a second template defining a plurality of fields and being different from the first template; and (d) transmitting a second market data message having a plurality of fields separated by delimiters and formatted in accordance with the second template.

15. An exchange computer system configured to distribute market data, the system comprising: a processor; a computer-readable medium containing computer-executable instructions that, when executed by the processor, cause the system to perform the steps comprising: (a) transmitting a first template defining a plurality of fields; (b) transmitting a first market data message having a plurality of fields separated by delimiters and formatted in accordance with the first template; (c) after (b) transmitting a second template defining a plurality of fields and being different from the first template; and (d) transmitting a second market data message having a plurality of fields separated by delimiters and formatted in accordance with the second template. 16. The exchange computer system of claim 15 , wherein at least one delimiter is used to identify a repeated group in the first template.

1. A method, comprising: displaying a plurality of edited changes associated with an editable file on a display associated with a computing device in response to receipt of a request via a user input device to display the plurality of edited changes; displaying, proximate to the displayed plurality of edited changes, a separate contextual representation of the editable file that comprises a contiguous series of individually expandable and compressible blank representations of pages of the editable file, where each subsequent blank page representation in the contiguous series shares one common border with a respective previous blank page representation in the contiguous series; displaying a context indicator within an expanded blank page representation of the separate contextual representation of the editable file that represents a location within the editable file associated with a first of the displayed plurality of edited changes; and iteratively updating, in response to detection of user selections of elements of the displayed plurality of edited changes received via the user input device, the context indicator within iteratively expanded blank page representations of the separate contextual representation of the editable file to represent a location within the editable file associated with each selected element of the displayed plurality of edited changes.

1. A method, comprising: displaying a plurality of edited changes associated with an editable file on a display associated with a computing device in response to receipt of a request via a user input device to display the plurality of edited changes; displaying, proximate to the displayed plurality of edited changes, a separate contextual representation of the editable file that comprises a contiguous series of individually expandable and compressible blank representations of pages of the editable file, where each subsequent blank page representation in the contiguous series shares one common border with a respective previous blank page representation in the contiguous series; displaying a context indicator within an expanded blank page representation of the separate contextual representation of the editable file that represents a location within the editable file associated with a first of the displayed plurality of edited changes; and iteratively updating, in response to detection of user selections of elements of the displayed plurality of edited changes received via the user input device, the context indicator within iteratively expanded blank page representations of the separate contextual representation of the editable file to represent a location within the editable file associated with each selected element of the displayed plurality of edited changes. 7. The method of claim 1 , further comprising: maintaining, within a memory of the computing device, a redo history comprising a plurality of reverted editing changes associated with the editable file; adding a selected one of the plurality of edited changes to the redo history; displaying the plurality of reverted editing changes; receiving a request to redo the selected one of the plurality of edited changes from the user via the user input device; and performing, in response to the request to redo the selected one of the plurality of edited changes from the user via the user input device, the selected one of the plurality of edited changes for the editable file.

7. The method of claim 6 , comprising, in response to the appeal request for the sponsor account: submitting an additional landing page to the intrusion detection engine, the additional landing page being associated with an additional sponsored content item of the sponsor account; receiving, from the intrusion detection engine, an additional intrusion score, the additional intrusion score being related to the additional landing page; and determining whether the additional intrusion score exceeds the intrusion threshold.

7. The method of claim 6 , comprising, in response to the appeal request for the sponsor account: submitting an additional landing page to the intrusion detection engine, the additional landing page being associated with an additional sponsored content item of the sponsor account; receiving, from the intrusion detection engine, an additional intrusion score, the additional intrusion score being related to the additional landing page; and determining whether the additional intrusion score exceeds the intrusion threshold. 9. The method of claim 7 , comprising: allowing serving of the sponsored content item and the additional sponsored content item when none of the intrusion score and the additional intrusion score exceeds the intrusion threshold.

5. The method of claim 2 , comprising associating a first weight with the click count and a second weight with the skip count.

5. The method of claim 2 , comprising associating a first weight with the click count and a second weight with the skip count. 6. The method of claim 5 , wherein the score assigned to the query term reordering rule satisfies: W ⁢ ⁢ 1 ⁢ ( click ⁢ ⁢ count ) W ⁢ ⁢ 1 ⁢ ( click ⁢ ⁢ count ) + W ⁢ ⁢ 2 ⁢ ( skip ⁢ ⁢ count ) wherein W1 represents the first weight associated with the click count and W2 represents the second weight associated with the skip count.

2. The method of claim 1 , further comprising: preparing, by a scripting framework, data associated with the exit node; and updating, by the scripting framework, any changed data resulting from execution of the code snippet.

2. The method of claim 1 , further comprising: preparing, by a scripting framework, data associated with the exit node; and updating, by the scripting framework, any changed data resulting from execution of the code snippet. 8. The method of claim 2 , wherein the business object infrastructure is associated with a hosted enterprise resource planning software-as-a-service solution.

1. A system for managing form-generated data related to a patient encounter, wherein the form-generated data is generated by electronic writing system configured to generate location information that identifies the location of a user writing on the form, the form having designated information fields at different locations on the form, the system comprising: a contextualizer configured to translate location information related to a user writing on a form to a contextualized data element, wherein the form has designated information fields at different locations on the form and wherein the contextualized data element comprises contextual information that is associated with the user writing, wherein the contextualizer includes a mapping data set that maps user areas on the form to labels that are associated with the designated information fields and wherein the contextualizer is configured to identify a label from the location information by comparing the location information to the mapping data set, the contextualized data element comprising the label; and wherein the contextualized data element is distributed to an Electronic Medical Record (EMR)/Electronic Health Record (EHR) application, which utilizes the label in the contextualized data element to perform a function that is related to the user writing on the form, via a publish/subscribe protocol in which the EMR/EHR application subscribes to a specific contextualized data element by identifying the label associated with the contextualized data element.

1. A system for managing form-generated data related to a patient encounter, wherein the form-generated data is generated by electronic writing system configured to generate location information that identifies the location of a user writing on the form, the form having designated information fields at different locations on the form, the system comprising: a contextualizer configured to translate location information related to a user writing on a form to a contextualized data element, wherein the form has designated information fields at different locations on the form and wherein the contextualized data element comprises contextual information that is associated with the user writing, wherein the contextualizer includes a mapping data set that maps user areas on the form to labels that are associated with the designated information fields and wherein the contextualizer is configured to identify a label from the location information by comparing the location information to the mapping data set, the contextualized data element comprising the label; and wherein the contextualized data element is distributed to an Electronic Medical Record (EMR)/Electronic Health Record (EHR) application, which utilizes the label in the contextualized data element to perform a function that is related to the user writing on the form, via a publish/subscribe protocol in which the EMR/EHR application subscribes to a specific contextualized data element by identifying the label associated with the contextualized data element. 11. The system of claim 1 , wherein the labels include taxonomic information that indicates a relationship of the designated information fields relative to each other.

1. A computer-implemented method, comprising: reading text data corresponding to one or more messages, wherein the text data comprises natural language content; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data, and wherein the language patterns comprise at least one of part-of-speech, syntactic role, and sentiment associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training; wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error in the created one or more semantic annotations, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed.

1. A computer-implemented method, comprising: reading text data corresponding to one or more messages, wherein the text data comprises natural language content; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data, and wherein the language patterns comprise at least one of part-of-speech, syntactic role, and sentiment associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training; wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error in the created one or more semantic annotations, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. 7. The method of claim 1 , wherein identifying the annotation error comprises identifying a categorization error from a named entity recognition (NER) model.

20. The system of claim 19 wherein selection of a navigational control associated with a first direction initiates presentation of the primary content object stream having an earlier chronological value associated therewith than a most previously presented content object stream.

20. The system of claim 19 wherein selection of a navigational control associated with a first direction initiates presentation of the primary content object stream having an earlier chronological value associated therewith than a most previously presented content object stream. 21. The system of claim 20 wherein selection of a navigational control associated with a second direction, opposite the first direction, initiates presentation of a content object having a later chronological value associated therewith than a previously presented content object stream.

9. An apparatus for providing a search recommendation, the apparatus comprising: a first search term obtaining unit that obtains a first search term, the first search term input by a user; a keyword matching unit that matches the first search term with at least one keyword in a list to select the at least one keyword from the list, a respective keyword in the list corresponding to at least one search recommendation; a first search recommendation providing unit that obtains one or more search recommendations corresponding to the at least one keyword and provides the one or more search recommendations corresponding to the at least one keyword to the user as one or more search recommendations of the first search term; a historical behavior obtaining unit that obtains a historical user behavior relating to the respective keyword from a log record; a document obtaining unit that obtaining a document generated by the historical user behavior; a text segmenting unit that applies a text segmentation of the document to obtain one or more candidate recommendations; and a filtering unit that filters the one or more candidate recommendations according to importance degree characteristics of the one or more candidate recommendations and improves a probability that the at least one search recommendation fits user requirements and reduces a number of user searches, search time, and search traffic by using a candidate recommendation passing the filtering as a search recommendation corresponding to the respective keyword.

9. An apparatus for providing a search recommendation, the apparatus comprising: a first search term obtaining unit that obtains a first search term, the first search term input by a user; a keyword matching unit that matches the first search term with at least one keyword in a list to select the at least one keyword from the list, a respective keyword in the list corresponding to at least one search recommendation; a first search recommendation providing unit that obtains one or more search recommendations corresponding to the at least one keyword and provides the one or more search recommendations corresponding to the at least one keyword to the user as one or more search recommendations of the first search term; a historical behavior obtaining unit that obtains a historical user behavior relating to the respective keyword from a log record; a document obtaining unit that obtaining a document generated by the historical user behavior; a text segmenting unit that applies a text segmentation of the document to obtain one or more candidate recommendations; and a filtering unit that filters the one or more candidate recommendations according to importance degree characteristics of the one or more candidate recommendations and improves a probability that the at least one search recommendation fits user requirements and reduces a number of user searches, search time, and search traffic by using a candidate recommendation passing the filtering as a search recommendation corresponding to the respective keyword. 11. The apparatus of claim 9 , wherein the filtering unit obtains the importance degree characteristics of the one or more candidate recommendations based on related data before a preset time point.

14. A method of modifying a first document including content and a barcode encoding data related to the first document, said barcode comprising barcode elements each having a predetermined form, said method comprising the steps of: detecting a plurality of the barcode elements of the barcode in a representation of the first document; determining a visual difference between each of the detected barcode elements and the predetermined form of the barcode element; and removing at least some of the degradation of the content of the first document based on the determined visual difference, in order to compensate for degradation of the first document, wherein at least the determining and removing steps are implemented using a processor.

14. A method of modifying a first document including content and a barcode encoding data related to the first document, said barcode comprising barcode elements each having a predetermined form, said method comprising the steps of: detecting a plurality of the barcode elements of the barcode in a representation of the first document; determining a visual difference between each of the detected barcode elements and the predetermined form of the barcode element; and removing at least some of the degradation of the content of the first document based on the determined visual difference, in order to compensate for degradation of the first document, wherein at least the determining and removing steps are implemented using a processor. 19. The method according to claim 14 , further comprising the step of combining the determined visual difference for the detected plurality of barcode elements to form an overall visual adjustment factor for the first document.

1. A method of checking electronic text document files containing descriptions of products and/or services on a computing system comprising: defining a plurality of separate target audiences for the electronic text document files using the computing system; wherein said plurality of separate target audiences are associated with a plurality of separate associated undesirable content vocabularies; receiving a plurality of electronic text document files designated to be communicated to said plurality of separate target audiences including a plurality of identified intended recipients; wherein at least two of said plurality of intended recipients are from different ones of said plurality of separate target audiences; providing at least one first electronic filter containing a first set of words corresponding to a first one of said separate associated undesirable content vocabularies for a first target audience; providing at least one second electronic filter containing a second set of words corresponding to a second one of said separate associated undesirable content vocabularies for a second target audience; wherein said first set of words and said second set of words are designated as offensive and/or inappropriate for communication with a corresponding designated first or second target audience respectively for the products and/or services; checking said plurality of electronic text document files for inappropriate content concerning the products and/or services with the computing system using said first and/or second electronic filter prior to initially distributing said plurality of electronic text document files to any designated identified intended recipients; wherein said first and second electronic filters can be invoked selectively by an operator of the computing system on a document-by-document basis, such that a first content in a first electronic text document file is not processed with said electronic filters, and a second content in a second electronic text document file is processed based on both said first electronic filter and said second electronic filters; controlling distribution of said plurality of electronic text document files to corresponding designated target audiences and said plurality of identified intended recipients with the computing system based on checking content with said electronic filters.

1. A method of checking electronic text document files containing descriptions of products and/or services on a computing system comprising: defining a plurality of separate target audiences for the electronic text document files using the computing system; wherein said plurality of separate target audiences are associated with a plurality of separate associated undesirable content vocabularies; receiving a plurality of electronic text document files designated to be communicated to said plurality of separate target audiences including a plurality of identified intended recipients; wherein at least two of said plurality of intended recipients are from different ones of said plurality of separate target audiences; providing at least one first electronic filter containing a first set of words corresponding to a first one of said separate associated undesirable content vocabularies for a first target audience; providing at least one second electronic filter containing a second set of words corresponding to a second one of said separate associated undesirable content vocabularies for a second target audience; wherein said first set of words and said second set of words are designated as offensive and/or inappropriate for communication with a corresponding designated first or second target audience respectively for the products and/or services; checking said plurality of electronic text document files for inappropriate content concerning the products and/or services with the computing system using said first and/or second electronic filter prior to initially distributing said plurality of electronic text document files to any designated identified intended recipients; wherein said first and second electronic filters can be invoked selectively by an operator of the computing system on a document-by-document basis, such that a first content in a first electronic text document file is not processed with said electronic filters, and a second content in a second electronic text document file is processed based on both said first electronic filter and said second electronic filters; controlling distribution of said plurality of electronic text document files to corresponding designated target audiences and said plurality of identified intended recipients with the computing system based on checking content with said electronic filters. 4. The method of claim 1 , wherein said electronic filters include at least one customizable filter containing inappropriate racist words.

54. A server computer implemented method of online document collaboration by authorized users, the method comprising the following steps performed by the server computer system: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to approve or disapprove the one or more modifications made to the first document by the first user, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user.

54. A server computer implemented method of online document collaboration by authorized users, the method comprising the following steps performed by the server computer system: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to approve or disapprove the one or more modifications made to the first document by the first user, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user. 67. The server computer implemented method of claim 54 , wherein if the first document is being used by a predetermined number of simultaneous users, the server computer system is capable of notifying a subsequent requester seeking access to the first document that the first document is unavailable for access at the time.

5. A method of transferring data via a communication session between a client application on a first network and a server application on a second network, the method comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application on the second network is behind a second firewall that is different from the first firewall.

5. A method of transferring data via a communication session between a client application on a first network and a server application on a second network, the method comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application on the second network is behind a second firewall that is different from the first firewall. 12. The method of claim 5 , wherein the communication session comprises a telnet session.

8. An information processing system for characterizing workloads in a data warehouse system, the system comprising: a memory; a processor communicatively coupled to the memory; and a workload characterizer communicatively coupled to the memory and the processor, the workload characterizer configured to perform a method comprising: collecting a set of accounting data associated with a data warehouse system comprising at least one database; determining, based on the set of accounting data, a set of query concurrency information associated with the database, the set of query concurrency information identifying, for a plurality of queries, a number of queries executed on the database simultaneously and a duration of execution of such queries; determining, based on the set of accounting data, a set of processor utilization distribution information associated with the plurality of queries, wherein determining the set of processor utilization distribution information comprises determining, for each query, a processor access time associated with such query; and creating a sorted list comprising each of the processor access times, wherein each position of the sorted list corresponds to a processor utilization distribution percentile; determining, based on the set of accounting data, a set of data access information indicating a quantity of data accessed by each query in the plurality of queries; and generating a workload profile associated with the database based on the set of query concurrency information, the set of processor utilization distribution information, and the set of data access information.

8. An information processing system for characterizing workloads in a data warehouse system, the system comprising: a memory; a processor communicatively coupled to the memory; and a workload characterizer communicatively coupled to the memory and the processor, the workload characterizer configured to perform a method comprising: collecting a set of accounting data associated with a data warehouse system comprising at least one database; determining, based on the set of accounting data, a set of query concurrency information associated with the database, the set of query concurrency information identifying, for a plurality of queries, a number of queries executed on the database simultaneously and a duration of execution of such queries; determining, based on the set of accounting data, a set of processor utilization distribution information associated with the plurality of queries, wherein determining the set of processor utilization distribution information comprises determining, for each query, a processor access time associated with such query; and creating a sorted list comprising each of the processor access times, wherein each position of the sorted list corresponds to a processor utilization distribution percentile; determining, based on the set of accounting data, a set of data access information indicating a quantity of data accessed by each query in the plurality of queries; and generating a workload profile associated with the database based on the set of query concurrency information, the set of processor utilization distribution information, and the set of data access information. 12. The information processing system claim 8 , wherein determining the set of query concurrency information comprises: sorting a set of start and end times associated with the plurality of queries.

10. The system of claim 1 wherein said dictionary entries in said dictionary fall within at least two of a Cantonese category, an English category, a mixed Cantonese-English category.

10. The system of claim 1 wherein said dictionary entries in said dictionary fall within at least two of a Cantonese category, an English category, a mixed Cantonese-English category. 14. The system of claim 10 wherein said Cantonese-English category includes combined phrases selected from both a standard Cantonese language and a standard English language.

20. A system according to claim 16 , wherein the grammar guesser is configured to automatically: for each element, assign at least one class to the element, wherein each of the at least one class is assigned to the element based at least in part based on the contents of the element; and for each row, assign a class to the row, wherein the class is assigned to the row based at least in part on the classes assigned to the elements of the row.

20. A system according to claim 16 , wherein the grammar guesser is configured to automatically: for each element, assign at least one class to the element, wherein each of the at least one class is assigned to the element based at least in part based on the contents of the element; and for each row, assign a class to the row, wherein the class is assigned to the row based at least in part on the classes assigned to the elements of the row. 22. A system according to claim 20 , wherein the grammar guesser is configured to define, for each row, a trigger grammar and a filter grammar based at least in part on the class of the row and headings of the row.

10. A system for patching a software error in a mobile computing device application, comprising: a mobile computing device configured to use a wireless cellular link as its primary mode of communication that is arranged to: execute the application, detect when the error occurs, wherein the error is an error that occurred during execution of the application such that a process that is executing the application crashes, determine whether crash data related to the error has been previously transmitted; and only in response to determining that the error has not been previously transmitted, compile crash data when the error is detected, wherein the crash data identifies the state of the mobile computing device and the application when the error occurred; a crash server coupled to the mobile computing device, wherein the crash server is arranged to: receive the crash data from the mobile computing device, determine the availability of an application fix that addresses the error, wherein the application fix is determined to be available when the crash data corresponds to registration information that identifies the mobile computing device, the application fix and the error; a patch detection server coupled to the crash server, wherein the patch detection server is arranged to: receive crash information from the crash server, the crash information based on the registration information and the crash data, process the crash information to determine the type of error and the location of the corresponding application fix, and generate an Extensible Markup Language (XML) file based on the crash information, wherein the XML file identifies the application fix and locates the application fix; and a patch server coupled to the patch detection server through a web services interface, wherein the patch server is arranged to receive the XML file from the patch detection server, locate the application fix based on the XML file and a patch identifier associated with the application fix, and send the application fix to the mobile computing device; wherein the application is modified on the mobile computing device using the application fix such that the modified application overcomes the error.

10. A system for patching a software error in a mobile computing device application, comprising: a mobile computing device configured to use a wireless cellular link as its primary mode of communication that is arranged to: execute the application, detect when the error occurs, wherein the error is an error that occurred during execution of the application such that a process that is executing the application crashes, determine whether crash data related to the error has been previously transmitted; and only in response to determining that the error has not been previously transmitted, compile crash data when the error is detected, wherein the crash data identifies the state of the mobile computing device and the application when the error occurred; a crash server coupled to the mobile computing device, wherein the crash server is arranged to: receive the crash data from the mobile computing device, determine the availability of an application fix that addresses the error, wherein the application fix is determined to be available when the crash data corresponds to registration information that identifies the mobile computing device, the application fix and the error; a patch detection server coupled to the crash server, wherein the patch detection server is arranged to: receive crash information from the crash server, the crash information based on the registration information and the crash data, process the crash information to determine the type of error and the location of the corresponding application fix, and generate an Extensible Markup Language (XML) file based on the crash information, wherein the XML file identifies the application fix and locates the application fix; and a patch server coupled to the patch detection server through a web services interface, wherein the patch server is arranged to receive the XML file from the patch detection server, locate the application fix based on the XML file and a patch identifier associated with the application fix, and send the application fix to the mobile computing device; wherein the application is modified on the mobile computing device using the application fix such that the modified application overcomes the error. 15. The system of claim 10 , wherein the mobile computing device is further arranged to modify the application by burning the application fix in memory of the mobile computing device.

12. A method, comprising: receiving, by at least a hardware component, source commands to establish a configuration to control a computer networking function in a computer networking device, wherein the source commands are written in a source command language; selectively translating, by at least the hardware component, the source commands from the source command language to target commands written in a target command language, wherein the translation is based, at least in part, on a function-to-function translation model; and establishing, by at least the hardware component, the configuration in the computer networking device based on the target commands.

12. A method, comprising: receiving, by at least a hardware component, source commands to establish a configuration to control a computer networking function in a computer networking device, wherein the source commands are written in a source command language; selectively translating, by at least the hardware component, the source commands from the source command language to target commands written in a target command language, wherein the translation is based, at least in part, on a function-to-function translation model; and establishing, by at least the hardware component, the configuration in the computer networking device based on the target commands. 13. The method of claim 12 , wherein the translation that is based, at least in part, on the function-to-function translation model comprises: identifying functional effects that would be produced by executing the source commands in a given order; identifying functional effects that would be produced by executing the target commands in a given order; identifying functional effects that can be produced both by the source commands being executed in a given order and by the target commands being executed in a given order; and identifying a first functional effect that can be produced by the source commands being executed in a given order and a related second functional effect that can be produced by the target commands being executed in a given order.

6. A system for computer-implemented detection software vulnerabilities by applying a rule set to test for vulnerabilities in computer software, the rule set comprising at least one vulnerability characterisation rule, the system incorporating computer apparatus incorporating a computer program stored in a hardware recording medium and being programmed by such computer program to carry out the steps of: a) receiving a training data set of computer software incorporating positive and negative vulnerability examples and expressed as programs flagged to indicate either presence or absence of vulnerability, the programs comprising instructions each incorporating an identifier to indicate its associated program, the instruction's address, an instruction operator and a list of instruction operands, b) receiving a rule generalisation which is processable to transform it into the at least one vulnerability characterisation rule, and c) processing the rule generalisation to transform it into a more specific rule generalisation by employing logic of at least First-Order and adding to the rule generalisation at least one of a condition, a variable, a constant, a unification of variables and a function based on the training data set and background knowledge relating to attributes of the training data set and consisting of at least one of concepts, facts of interest and functions for calculating values of interest from items of data, d) evaluating the more specific rule generalisation by applying it to the training data set to identify vulnerabilities, and e) incorporating the more specific rule generalisation in the rule set if it classifies vulnerabilities in the training data set adequately in terms of covering at least some of the positive vulnerability examples, f) applying the rule set to a test program for vulnerability detection therein, and g) providing an alert or a report to a user regarding vulnerability detection in the test program resulting from operation of the method in order to enable corrective action to be taken.

6. A system for computer-implemented detection software vulnerabilities by applying a rule set to test for vulnerabilities in computer software, the rule set comprising at least one vulnerability characterisation rule, the system incorporating computer apparatus incorporating a computer program stored in a hardware recording medium and being programmed by such computer program to carry out the steps of: a) receiving a training data set of computer software incorporating positive and negative vulnerability examples and expressed as programs flagged to indicate either presence or absence of vulnerability, the programs comprising instructions each incorporating an identifier to indicate its associated program, the instruction's address, an instruction operator and a list of instruction operands, b) receiving a rule generalisation which is processable to transform it into the at least one vulnerability characterisation rule, and c) processing the rule generalisation to transform it into a more specific rule generalisation by employing logic of at least First-Order and adding to the rule generalisation at least one of a condition, a variable, a constant, a unification of variables and a function based on the training data set and background knowledge relating to attributes of the training data set and consisting of at least one of concepts, facts of interest and functions for calculating values of interest from items of data, d) evaluating the more specific rule generalisation by applying it to the training data set to identify vulnerabilities, and e) incorporating the more specific rule generalisation in the rule set if it classifies vulnerabilities in the training data set adequately in terms of covering at least some of the positive vulnerability examples, f) applying the rule set to a test program for vulnerability detection therein, and g) providing an alert or a report to a user regarding vulnerability detection in the test program resulting from operation of the method in order to enable corrective action to be taken. 9. A system for detection of software vulnerabilities according to claim 6 wherein the rule set incorporates a rule which classifies a program as vulnerable if there is a copying loop defined as a portion of code that copies to a register from a source pointer, changes the source pointer, copies from the register into a destination pointer, changes that destination pointer, and has a control flow path from the code portion's end back to the code portion's beginning thus forming a loop.

11. A computer-implemented method to allow partner services to provide pricing information to a user based on a group of information maintained for the user, the method comprising: storing one or more groups of information for a user, wherein each group of information is associated with a distinct topic and includes multiple information items; verifying that the user has granted one or more partner services access to a group of information associated with the user; for each partner service that is has been granted access to the group of information: allowing the partner service to access the information items in the group of information associated with the user; and receiving, from the partner service, pricing information associated with at least one of the accessed information items; providing to the user at least some of the received pricing information from the partner services granted access; receiving, from the user, a selection of a partner service from which to purchase an information item; and transmitting the purchase selection to the selected partner service to allow the partner service to fulfill the purchase selection.

11. A computer-implemented method to allow partner services to provide pricing information to a user based on a group of information maintained for the user, the method comprising: storing one or more groups of information for a user, wherein each group of information is associated with a distinct topic and includes multiple information items; verifying that the user has granted one or more partner services access to a group of information associated with the user; for each partner service that is has been granted access to the group of information: allowing the partner service to access the information items in the group of information associated with the user; and receiving, from the partner service, pricing information associated with at least one of the accessed information items; providing to the user at least some of the received pricing information from the partner services granted access; receiving, from the user, a selection of a partner service from which to purchase an information item; and transmitting the purchase selection to the selected partner service to allow the partner service to fulfill the purchase selection. 15. The method of claim 11 , further comprising collecting a fee from the partner services for providing pricing information to the user.

12. A data processing system having at least one processor capable of providing an automatic response to a received user input, the system being programmed to automatically: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a full user input representing the entire answerable statement, calculate for each of a plurality of predefined answerable statements, a metric that is, at least in part, based on a frequency with which the predefined answerable statement had been selected by previous users; and (b) (1) if the metric for one of the predefined answerable statements exceeds a threshold, send, to the user's device, information representing a response associated with said one of the predefined answerable statements, and (2) if part (b)(1) does not apply, send, to the user's device, information representing the corresponding at least one of the predefined answerable statements, which predefined answerable statements are selected based on the respective associated metrics.

12. A data processing system having at least one processor capable of providing an automatic response to a received user input, the system being programmed to automatically: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a full user input representing the entire answerable statement, calculate for each of a plurality of predefined answerable statements, a metric that is, at least in part, based on a frequency with which the predefined answerable statement had been selected by previous users; and (b) (1) if the metric for one of the predefined answerable statements exceeds a threshold, send, to the user's device, information representing a response associated with said one of the predefined answerable statements, and (2) if part (b)(1) does not apply, send, to the user's device, information representing the corresponding at least one of the predefined answerable statements, which predefined answerable statements are selected based on the respective associated metrics. 21. The data processing system of claim 12 wherein the information sent to the user's device in part (b)(2) is more than one predefined answerable statements ranked in order of their respective metrics.

19. An apparatus, comprising: a display having touch sensitive display surface that is responsive to pen-based user input; a control unit that is bidirectionally coupled to the display and responsive to a user selecting displayed text from a first display location using the pen, and further responsive to a first signal generated using the pen, to copy the selected displayed text to a text window and to display the copied text in the text window said control unit further responsive to the user selecting a second display location using the pen, and to a second signal, to copy the displayed text from the text window to the second display location; and a wireless transceiver, in which the first signal is generated automatically when the pen is lifted from the touch sensitive surface after the displayed text is selected.

19. An apparatus, comprising: a display having touch sensitive display surface that is responsive to pen-based user input; a control unit that is bidirectionally coupled to the display and responsive to a user selecting displayed text from a first display location using the pen, and further responsive to a first signal generated using the pen, to copy the selected displayed text to a text window and to display the copied text in the text window said control unit further responsive to the user selecting a second display location using the pen, and to a second signal, to copy the displayed text from the text window to the second display location; and a wireless transceiver, in which the first signal is generated automatically when the pen is lifted from the touch sensitive surface after the displayed text is selected. 25. The apparatus of claim 19 , said control unit further changing, in response to user input, the text displayed in the text window prior to copying the displayed text from the buffer to the second display location.

8. A computer-readable device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a broadcast video program from a first source; recording the broadcast video program, to yield a recorded video program; performing an analysis of images and text associated with the recorded video program, to generate a content-based index, wherein the content-based index: is generated independent of index information transmitted with the broadcast video program; and is generated by combining extracted images and the text from the recorded video program with network-based content provided by an external source, the network-based content being transmitted separately from the broadcast video program; automatically, via a processor and without user input, supplementing the content-based index with the network-based content as the content-based index is generated, wherein the network-based content is from a second source that is distinct from the first source and the external source; presenting a search field, wherein presenting of the search field occurs on a first computing device different from a second computing device which displays the broadcast video program, wherein the first computing device is a hand-held device comprising a touch-sensitive screen; receiving user input in the search field, the user input describing one of an item and an activity; searching the content-based index to identify a location in the recorded video program associated with the user input; and playing back the recorded video program starting at the location on the second device.

8. A computer-readable device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a broadcast video program from a first source; recording the broadcast video program, to yield a recorded video program; performing an analysis of images and text associated with the recorded video program, to generate a content-based index, wherein the content-based index: is generated independent of index information transmitted with the broadcast video program; and is generated by combining extracted images and the text from the recorded video program with network-based content provided by an external source, the network-based content being transmitted separately from the broadcast video program; automatically, via a processor and without user input, supplementing the content-based index with the network-based content as the content-based index is generated, wherein the network-based content is from a second source that is distinct from the first source and the external source; presenting a search field, wherein presenting of the search field occurs on a first computing device different from a second computing device which displays the broadcast video program, wherein the first computing device is a hand-held device comprising a touch-sensitive screen; receiving user input in the search field, the user input describing one of an item and an activity; searching the content-based index to identify a location in the recorded video program associated with the user input; and playing back the recorded video program starting at the location on the second device. 10. The computer-readable device of claim 8 , wherein generating the content-based index further comprises generating a searchable database of images and text from the broadcast video program and one of: a content-based sampling module to extract images, a textual module to extract text and an automatic speech recognition module to extract text.

4. The method of claim 3 , wherein the received query is modified upon determining that the value predefined to represent NULL values would be returned by applying the extended comparison operator to the column data, the method further comprising: executing the modified query.

4. The method of claim 3 , wherein the received query is modified upon determining that the value predefined to represent NULL values would be returned by applying the extended comparison operator to the column data, the method further comprising: executing the modified query. 5. The method of claim 4 , wherein the value predefined to represent NULL values is the largest value capable of being stored in the column data, wherein searching the set of column values comprises identifying column values matching at least one of: (i) the value predefined to represent NULL values, (ii) a value between a specified value in the first predicate and the value predefined to represent NULL values, and (iii) the specified value in the first predicate, wherein the extended comparison operator comprises each individual extended operator selected from the group comprising: (i) an extended greater than operator, (ii) an extended equals operator, and (iii) an extended greater than or equals operator.

1. A computer-implemented method comprising: retrieving a markup language document including server side script code specified using personalme page (PHP) syntax, wherein the server side script code is for execution on a server in response to a request for the markup language document; generating C++ code from the server side script code, wherein the generated C++ code comprises: one or more C++ classes comprising code corresponding to the server side script code, one or more C++ header files storing information describing structures of the C++ classes, and code for memory allocation of objects instantiated from the C++ classes; and compiling the generated C++ code to object code, wherein the object code is invoked for processing the markup language document.

1. A computer-implemented method comprising: retrieving a markup language document including server side script code specified using personalme page (PHP) syntax, wherein the server side script code is for execution on a server in response to a request for the markup language document; generating C++ code from the server side script code, wherein the generated C++ code comprises: one or more C++ classes comprising code corresponding to the server side script code, one or more C++ header files storing information describing structures of the C++ classes, and code for memory allocation of objects instantiated from the C++ classes; and compiling the generated C++ code to object code, wherein the object code is invoked for processing the markup language document. 6. The computer-implemented method of claim 1 , wherein the server side script code comprises a first declaration of a function and a second declaration of the function and the generated C++ code comprises a structure with a function pointer to one of a first C++ function corresponding to the first declaration and a second C++ function corresponding to the second declaration.

5. The method as set forth in claim 1 wherein said analyzing comprises: constructing a graph in which the terms are represented as nodes and edges connect the nodes, each of the edges representing a frequency of co-occurrence of the terms represented by the nodes connected by the corresponding edge; and partitioning the graph to form the sets.

5. The method as set forth in claim 1 wherein said analyzing comprises: constructing a graph in which the terms are represented as nodes and edges connect the nodes, each of the edges representing a frequency of co-occurrence of the terms represented by the nodes connected by the corresponding edge; and partitioning the graph to form the sets. 6. The method as set forth in claim 5 wherein said partitioning further takes into account how often the terms are found in the content corpora.

19. A method for interactive voice response mapping used in a transaction between a waiting party and a queuing party, the queuing party having a queuing calling system (QCS), the method comprising communicating with the QCS and extracting navigational information from the QCS and at least partially generating an IVR map of the QCS, and further performing map validation by comparing the IVR map with extracted navigational information, and determining if a certain threshold of matching is not met.

19. A method for interactive voice response mapping used in a transaction between a waiting party and a queuing party, the queuing party having a queuing calling system (QCS), the method comprising communicating with the QCS and extracting navigational information from the QCS and at least partially generating an IVR map of the QCS, and further performing map validation by comparing the IVR map with extracted navigational information, and determining if a certain threshold of matching is not met. 25. The method of claim 19 , further designating at least one queuing party as frequently changing, and performing frequent IVR map validation for the at least one queuing party.

54. The method of encoding according to any one of claims 46 to 49 , wherein in order to binarize at least one syntactic element, depending on values of the already encoded bits of the syntactic element, two or more independent methods of binarization are used; at least two groups of context models are selected using binarized values obtained by various methods of binarization; and/or at least two groups of context models are selected by a current ordinal number of the encoded bit in a binarized string obtained from a current syntactic element.

54. The method of encoding according to any one of claims 46 to 49 , wherein in order to binarize at least one syntactic element, depending on values of the already encoded bits of the syntactic element, two or more independent methods of binarization are used; at least two groups of context models are selected using binarized values obtained by various methods of binarization; and/or at least two groups of context models are selected by a current ordinal number of the encoded bit in a binarized string obtained from a current syntactic element. 57. The method of encoding according to claim 54 , wherein unary encoding, and/or encoding according to the Huffman method, and/or encoding by the Golomb code, and/or encoding by the universal code, is used in various combinations as the methods of binarization.

5. A method of processing a document, the method comprising: analyzing, with a computer, an eXtended Stylesheet Language (“XSL”) file comprising a set of data, wherein a first portion of the data is static data and wherein a second portion of the data is dynamic data; extracting the static data from the XSL file to produce a modified XSL file comprising the dynamic data; applying a set of eXtended Markup Language (“XML”) data to the modified XSL file to create an intermediate file comprising at least some of the XML data formatted according to a format specified by the XSL file; and merging the intermediate file with the static data extracted from the XSL file to produce an output file formatted as specified by the XSL file and comprising at least some of the XML data and the static data of the XSL file.

5. A method of processing a document, the method comprising: analyzing, with a computer, an eXtended Stylesheet Language (“XSL”) file comprising a set of data, wherein a first portion of the data is static data and wherein a second portion of the data is dynamic data; extracting the static data from the XSL file to produce a modified XSL file comprising the dynamic data; applying a set of eXtended Markup Language (“XML”) data to the modified XSL file to create an intermediate file comprising at least some of the XML data formatted according to a format specified by the XSL file; and merging the intermediate file with the static data extracted from the XSL file to produce an output file formatted as specified by the XSL file and comprising at least some of the XML data and the static data of the XSL file. 10. A method as recited by claim 5 , wherein the dynamic data comprises a static XSL element with a dynamic attribute, such that the static XSL element is treated as dynamic data.

1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of a first gesture detected at a presence-sensitive input device, the first gesture to select a first sequence of one or more keys from the plurality of keys; determining, by the computing device, a set of candidate strings based at least in part on characters associated with the first sequence of one or more keys; outputting, by the computing device and for display, at least one of the set of candidate strings; receiving, by the computing device, an indication of a second gesture detected at the presence-sensitive input device, the second gesture to select a second sequence of one or more keys from the plurality of keys; determining, by the computing device, whether characters associated with the second sequence of one or more keys are included in a first candidate word of a lexicon, the first candidate word being based at least in part on the characters associated with the first sequence of one or more keys, and: if the computing device determines that the characters associated with the second sequence of one or more keys are included in the first candidate word, modifying, by the computing device, the set of candidate strings based at least in part on the first candidate word, and if the computing device determines that the characters associated with the second sequence of one or more keys are not included in the first candidate word, modifying, by the computing device, the set of candidate strings based at least in part on a second candidate word of the lexicon, the second candidate word not being based on the characters associated with the first sequence of one or more keys; and outputting, by the computing device and for display, at least one of the modified set of candidate strings.

1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of a first gesture detected at a presence-sensitive input device, the first gesture to select a first sequence of one or more keys from the plurality of keys; determining, by the computing device, a set of candidate strings based at least in part on characters associated with the first sequence of one or more keys; outputting, by the computing device and for display, at least one of the set of candidate strings; receiving, by the computing device, an indication of a second gesture detected at the presence-sensitive input device, the second gesture to select a second sequence of one or more keys from the plurality of keys; determining, by the computing device, whether characters associated with the second sequence of one or more keys are included in a first candidate word of a lexicon, the first candidate word being based at least in part on the characters associated with the first sequence of one or more keys, and: if the computing device determines that the characters associated with the second sequence of one or more keys are included in the first candidate word, modifying, by the computing device, the set of candidate strings based at least in part on the first candidate word, and if the computing device determines that the characters associated with the second sequence of one or more keys are not included in the first candidate word, modifying, by the computing device, the set of candidate strings based at least in part on a second candidate word of the lexicon, the second candidate word not being based on the characters associated with the first sequence of one or more keys; and outputting, by the computing device and for display, at least one of the modified set of candidate strings. 14. The method of claim 1 , wherein the indication of the first gesture includes a group of alignment points traversed by the gesture, the alignment points determined based on a plurality of features associated with the first gesture, the method further comprising: determining, by the computing device, respective cost values for at least a first key and a second key, wherein the respective cost values represent a probability that an alignment point of the group of alignment points indicates a key included in the plurality of keys; determining, by the computing device, at least one candidate string including a character associated with the first key, the candidate string having an associated cost value based at least in part on the cost value for the first key; determining, by the computing device, at least one candidate string including a character associated with the second key, the candidate string having an associated cost value based at least in part on the cost value for the second key; and adding, by the computing device, the determined candidate strings to the set of candidate strings.

20. The system of claim 17 , wherein the processor electronics are further configured to perform operations comprising: generating a disclosure of the state dependent content in the electronic document; and associating the disclosure with the electronic document.

20. The system of claim 17 , wherein the processor electronics are further configured to perform operations comprising: generating a disclosure of the state dependent content in the electronic document; and associating the disclosure with the electronic document. 21. The system of claim 20 , wherein the processor electronics are further configured to perform operations comprising: digitally signing the electronic document, the attestation, and the disclosure.

11. A computer program product comprising a computer readable storage medium not including a propagated signal having stored therein computer usable program code for causing a computer to automatically identify a breaking scenario during an automated software build, the computer usable program code, which when executed by a computer hardware system, causes the computer hardware system to perform: identifying a build artifact from a list of build artifacts in a repository; comparing the build artifact to a current software build; identifying a delta between the build artifact and the current software build; determining whether the delta had a link to a rule in a rules database; responsive to the delta being linked to the rule, determining whether the rule identifies a breaking scenario; and responsive to the rule identifying the breaking scenario, taking an action specified by the rule.

11. A computer program product comprising a computer readable storage medium not including a propagated signal having stored therein computer usable program code for causing a computer to automatically identify a breaking scenario during an automated software build, the computer usable program code, which when executed by a computer hardware system, causes the computer hardware system to perform: identifying a build artifact from a list of build artifacts in a repository; comparing the build artifact to a current software build; identifying a delta between the build artifact and the current software build; determining whether the delta had a link to a rule in a rules database; responsive to the delta being linked to the rule, determining whether the rule identifies a breaking scenario; and responsive to the rule identifying the breaking scenario, taking an action specified by the rule. 13. The computer program product of claim 11 , wherein the method performs continuously during the automated software build.

1. A secure document data capture system for generating a data structure, comprising a data field value associated with each of a plurality of identified data fields, from a document image comprising text representing each of such data field values, the secure document data capture system comprising: a character recognition system receiving the document image and recognizing characters within the text to generate, for each of the identified data fields, a data field value for association therewith; a validation engine for identifying a subset of the identified data fields, the subset of the identified data fields being those data fields with which its associated data field value includes at least one suspect character, a suspect character being a character which fails to comply with a validation rule thereby indicating that that character recognition system erred in recognizing such character; an exception handling system: providing an exception image to a first client system, the exception image comprising a portion of the document image which includes text of the at least one suspect character with a context portion of the document image redacted, the context portion of the document image being a portion of the document image which comprises text which discloses a meaning of the at least one suspect character; and receiving from the first client system, user input of a replacement character for each suspect character; and the secure data capture system generating the data structure utilizing, for each identified data field, the data field values generated by the character recognition system with substitution of the replacement character from the exception handling system for each suspect character.

1. A secure document data capture system for generating a data structure, comprising a data field value associated with each of a plurality of identified data fields, from a document image comprising text representing each of such data field values, the secure document data capture system comprising: a character recognition system receiving the document image and recognizing characters within the text to generate, for each of the identified data fields, a data field value for association therewith; a validation engine for identifying a subset of the identified data fields, the subset of the identified data fields being those data fields with which its associated data field value includes at least one suspect character, a suspect character being a character which fails to comply with a validation rule thereby indicating that that character recognition system erred in recognizing such character; an exception handling system: providing an exception image to a first client system, the exception image comprising a portion of the document image which includes text of the at least one suspect character with a context portion of the document image redacted, the context portion of the document image being a portion of the document image which comprises text which discloses a meaning of the at least one suspect character; and receiving from the first client system, user input of a replacement character for each suspect character; and the secure data capture system generating the data structure utilizing, for each identified data field, the data field values generated by the character recognition system with substitution of the replacement character from the exception handling system for each suspect character. 2. The secure document data capture system of claim 1 , wherein: the exception handling system further: provides the exception image to a second client system; receives from the second client system, user input of a replacement character for each suspect character; and the secure data capture system substitutes the replacement character from the exception handling system for each suspect character only when the replacement character form the first client system and the replacement character from the second client system are the same.

20. The computer storage medium of claim 18 , wherein determining the hover weighting comprises applying a sigmoid function to the total click count for the search query.

20. The computer storage medium of claim 18 , wherein determining the hover weighting comprises applying a sigmoid function to the total click count for the search query. 21. The computer storage medium of claim 20 , wherein the sigmoid function defines a range of total click counts for which the hover weighting varies based on the total click count for the search query, the range of total click counts being defined by an upper total click value and a lower total click value, and wherein the hover weighting increases as the total click count for the search query approaches the lower click value, and wherein the hover weighting decreases as the total click count for the search query approaches the upper click value.

1. A method for operating a user interface of a machine comprising at least one processor, the method comprising: identifying, by the at least one processor, a plurality of tokens in a targeted text listing; filtering, by the at least one processor, a first token of the plurality of tokens according to a first set of exclusion rules, whereby the first token is excluded as an instance of a similar spelling error if it satisfies any rule of the first set of exclusion rules; when the first token has not been excluded as an instance of a similar spelling error according to the first set of exclusion rules, determining, by the at least one processor, whether a second token of the plurality of tokens is similar to the first token based on a predetermined number of different characters between the first token and the second token; when the first token and the second token are similar, filtering, by the at least one processor, the first token and the second token according to a second set of exclusion rules, whereby the first token is excluded as an instance of a similar spelling error if it satisfies any rule of the second set of exclusion rules; when the first token has not been excluded as an instance of a similar spelling error according to the second set of exclusion rules, identifying, by the at least one processor, the first token as an instance of a similar spelling error based on the second token; and providing, by the at least one processor to the user interface, the similar spelling error instance including the first token and the second token.

1. A method for operating a user interface of a machine comprising at least one processor, the method comprising: identifying, by the at least one processor, a plurality of tokens in a targeted text listing; filtering, by the at least one processor, a first token of the plurality of tokens according to a first set of exclusion rules, whereby the first token is excluded as an instance of a similar spelling error if it satisfies any rule of the first set of exclusion rules; when the first token has not been excluded as an instance of a similar spelling error according to the first set of exclusion rules, determining, by the at least one processor, whether a second token of the plurality of tokens is similar to the first token based on a predetermined number of different characters between the first token and the second token; when the first token and the second token are similar, filtering, by the at least one processor, the first token and the second token according to a second set of exclusion rules, whereby the first token is excluded as an instance of a similar spelling error if it satisfies any rule of the second set of exclusion rules; when the first token has not been excluded as an instance of a similar spelling error according to the second set of exclusion rules, identifying, by the at least one processor, the first token as an instance of a similar spelling error based on the second token; and providing, by the at least one processor to the user interface, the similar spelling error instance including the first token and the second token. 4. The method of claim 1 , wherein filtering the first token according to the first set of exclusion rules further comprises: identifying, by the at least one processor, an occurrence of a predefined phrase in the plurality of tokens; and for each token of the plurality of tokens within the occurrence of the predefined phrase, excluding, by the at least one processor, the token from being identified as an instance of a similar spelling error.

12. A non-transitory computer-readable medium having stored thereon program code, the program code executable by a computer to: determine a starting point for each of a plurality of ontology contexts, each starting point including terms matching a set of words, the set of words including a plurality of words; determine a term set corresponding to the set of words in the ontology context of each starting point; rank the starting points and selectively using a predetermined number of the ranked starting points; rank the term sets determined for all of the starting points; and provide an output of the term sets in a ranked order.

12. A non-transitory computer-readable medium having stored thereon program code, the program code executable by a computer to: determine a starting point for each of a plurality of ontology contexts, each starting point including terms matching a set of words, the set of words including a plurality of words; determine a term set corresponding to the set of words in the ontology context of each starting point; rank the starting points and selectively using a predetermined number of the ranked starting points; rank the term sets determined for all of the starting points; and provide an output of the term sets in a ranked order. 14. The computer-readable medium of claim 12 , wherein each starting point has a cover rate of the set of words above a predetermined threshold, wherein the cover rate for the starting point is defined as the number of covered words of the set of words by the starting point divided by a total number of the set of words.

13. A system comprising: a first memory device; a second memory device; and a processor to execute processor-executable program code in order to cause the system to: receive first text, the first text comprising a first identifier and first additional text; store the first additional text in an area of the first memory device associated with the first identifier; receive second text, the second text comprising the first identifier and second additional text; store the second additional text in the area of the first memory device associated with the first identifier; determine that a characteristic of text stored in the area of the first memory device has reached a threshold, the text stored in the area of the first memory device comprising at least the first additional text and the second additional text; in response to the determination, generate a semantic representation of the text stored in the area of the first memory device; and store the semantic representation in association with the first identifier in the second memory device.

13. A system comprising: a first memory device; a second memory device; and a processor to execute processor-executable program code in order to cause the system to: receive first text, the first text comprising a first identifier and first additional text; store the first additional text in an area of the first memory device associated with the first identifier; receive second text, the second text comprising the first identifier and second additional text; store the second additional text in the area of the first memory device associated with the first identifier; determine that a characteristic of text stored in the area of the first memory device has reached a threshold, the text stored in the area of the first memory device comprising at least the first additional text and the second additional text; in response to the determination, generate a semantic representation of the text stored in the area of the first memory device; and store the semantic representation in association with the first identifier in the second memory device. 15. A system according to claim 13 , the processor to execute processor-executable program code in order to further cause the system to: receive third text, the third text comprising the first identifier, third additional text-and a hyperlink; follow the hyperlink to retrieve fourth text associated with the hyperlink; generate a second semantic representation of the third additional text and the fourth text; combine the second semantic representation with the stored semantic representation; and store the combined semantic representation in association with the first identifier in the second memory device.

7. The system of claim 6 , wherein the any of the closure-friendly operators determined not to exist are dynamically generated using one or more optimization techniques.

7. The system of claim 6 , wherein the any of the closure-friendly operators determined not to exist are dynamically generated using one or more optimization techniques. 8. The system of claim 7 , wherein the one or more optimization techniques comprise just-in-time compilation, code caching, code libraries, or lazy evaluation.

1. A method for determining a set of rules for ordering text of a language, said method comprising: receiving information that indicates a target order of sets of characters in text of a language; determining strengths of differences between the characters based on the target order; identifying strings of characters that were sorted in the target order as a shorter string of characters; identifying strings of characters that were sorted in the target order as a longer string of characters; and determining, using a processor, a set of rules for ordering text of the language based on the strengths of differences between the characters, the identified strings of characters that were sorted in the target order as a shorter string, and the identified strings of characters that were sorted in the target order as a longer string, wherein the target order is a sequential ordering among the sets of characters in the text of the language.

1. A method for determining a set of rules for ordering text of a language, said method comprising: receiving information that indicates a target order of sets of characters in text of a language; determining strengths of differences between the characters based on the target order; identifying strings of characters that were sorted in the target order as a shorter string of characters; identifying strings of characters that were sorted in the target order as a longer string of characters; and determining, using a processor, a set of rules for ordering text of the language based on the strengths of differences between the characters, the identified strings of characters that were sorted in the target order as a shorter string, and the identified strings of characters that were sorted in the target order as a longer string, wherein the target order is a sequential ordering among the sets of characters in the text of the language. 3. The method of claim 1 , wherein receiving the information that indicates the target order comprises interpreting information from a written text.

172. The computer program product of claim 151 , the computer readable medium further storing: program code for receiving the job description; program code for storing the job description in the resume database; and program code for sending a portion of the result set to a recruiter, wherein the result set includes at least one matching resume from the resume database, each said at least one matching resume satisfying the job description.

172. The computer program product of claim 151 , the computer readable medium further storing: program code for receiving the job description; program code for storing the job description in the resume database; and program code for sending a portion of the result set to a recruiter, wherein the result set includes at least one matching resume from the resume database, each said at least one matching resume satisfying the job description. 180. The computer program product of claim 172 , wherein a reference to the portion of the result set is sent.

1. A method comprising: maintaining a plurality of page objects on a social networking system, the plurality of page objects corresponding to a cluster of pages on the social networking system that describe an equivalent concept; ranking, by a processor, a plurality of pages of the cluster of pages based on a hierarchy of rules analyzing attributes of the plurality of pages of the cluster of pages and profile information of a user requesting a page of the cluster of pages, the hierarchy of rules comprising consideration of information associated with a source of the plurality of pages; selecting, based on the ranking associated with the plurality of pages, a best page of the cluster of pages describing the equivalent concept; storing an indicator in a page object of the plurality of page objects, the page object corresponding to the selected best page, where the indicator identifies the page object as the best page of the cluster of pages describing the equivalent concept; and directing the user requesting a page of the cluster of pages to the selected best page.

1. A method comprising: maintaining a plurality of page objects on a social networking system, the plurality of page objects corresponding to a cluster of pages on the social networking system that describe an equivalent concept; ranking, by a processor, a plurality of pages of the cluster of pages based on a hierarchy of rules analyzing attributes of the plurality of pages of the cluster of pages and profile information of a user requesting a page of the cluster of pages, the hierarchy of rules comprising consideration of information associated with a source of the plurality of pages; selecting, based on the ranking associated with the plurality of pages, a best page of the cluster of pages describing the equivalent concept; storing an indicator in a page object of the plurality of page objects, the page object corresponding to the selected best page, where the indicator identifies the page object as the best page of the cluster of pages describing the equivalent concept; and directing the user requesting a page of the cluster of pages to the selected best page. 9. The method of claim 1 , wherein ranking, by a processor, a plurality of pages of the cluster of pages based on a hierarchy of rules analyzing attributes of the plurality of pages of the cluster of pages and profile information of a user requesting a page of the cluster of pages further comprises: in response to determining that none of the cluster of pages are authentic pages and determining that none of the cluster of pages are sourced from a third-party encyclopedic entry associated with the equivalent concept for the cluster of pages, ranking the plurality of pages of the cluster of pages based on a number of users expressing interest in each page of the plurality of pages.

7. An information processing apparatus configured to display a main display document generated from print data of all parts of a print document, the information processing apparatus comprising: at least one processor and at least one memory coupled to each other and operating to: generate a temporary display document, to be displayed prior to the main display document, based on print data of at least one part fewer than all parts of the print document; display the generated temporary display document; determine whether all parts of the print document are acquired; when it is determined that the all parts of the print document are acquired, generate the main display document including all pages of the print document based on the print data of the acquired all parts of the print document; and change a display from the temporary display document to the main display document when the main display document is generated, wherein the at least one processor and the at least one memory further operate to: (i) determine whether to display the temporary display document according to an output status of the parts of the print document, (ii) determine whether all parts of the print document have already been output before generation of the temporary display document is completed, and (iii) determine that the temporary display document should not be displayed when it is determined that all parts of the print document have already been output before generation of the temporary display document is completed.

7. An information processing apparatus configured to display a main display document generated from print data of all parts of a print document, the information processing apparatus comprising: at least one processor and at least one memory coupled to each other and operating to: generate a temporary display document, to be displayed prior to the main display document, based on print data of at least one part fewer than all parts of the print document; display the generated temporary display document; determine whether all parts of the print document are acquired; when it is determined that the all parts of the print document are acquired, generate the main display document including all pages of the print document based on the print data of the acquired all parts of the print document; and change a display from the temporary display document to the main display document when the main display document is generated, wherein the at least one processor and the at least one memory further operate to: (i) determine whether to display the temporary display document according to an output status of the parts of the print document, (ii) determine whether all parts of the print document have already been output before generation of the temporary display document is completed, and (iii) determine that the temporary display document should not be displayed when it is determined that all parts of the print document have already been output before generation of the temporary display document is completed. 14. The information processing apparatus according to claim 7 , wherein: (i) the at least one processor and at least one memory generate the temporary display document by generating an empty temporary display document and sequentially adding the parts to the temporary display document; and (ii) the at least one processor and at least one memory generate the main display document by generating an empty main display document and sequentially adding the parts to the main display document.

10. A computer program product for facilitating accurate review of a document, the computer program product being encoded on one or more machine-readable storage media and comprising: instruction for manipulating by a computer a scanned image of the document, instruction for indicating to a reader portions of the document which have been already reviewed in a previous or master document, wherein the document comprises two or more documents, instruction for indicating to the reader the similarities and/or differences between the two or more documents, and instruction for re-ordering of the two or more documents by moving documents which have a large set of same or similar changes together so as to facilitate their review consecutively allowing more text, diagrams, and photos to be marked as the same.

10. A computer program product for facilitating accurate review of a document, the computer program product being encoded on one or more machine-readable storage media and comprising: instruction for manipulating by a computer a scanned image of the document, instruction for indicating to a reader portions of the document which have been already reviewed in a previous or master document, wherein the document comprises two or more documents, instruction for indicating to the reader the similarities and/or differences between the two or more documents, and instruction for re-ordering of the two or more documents by moving documents which have a large set of same or similar changes together so as to facilitate their review consecutively allowing more text, diagrams, and photos to be marked as the same. 15. The computer program product of claim 10 , further comprising instruction for hyperlinking corresponding sections of the two or more documents to each other.

9. The computing device of claim 1 , wherein the protection service is further configured to automatically control sharing of the selected digital payload with the recipient computing device based on determining that a sending context is inconsistent with the prospective recipient.

9. The computing device of claim 1 , wherein the protection service is further configured to automatically control sharing of the selected digital payload with the recipient computing device based on determining that a sending context is inconsistent with the prospective recipient. 10. The computing system of claim 9 , wherein the sending context indicates that a time at which the selected payload is being shared is during a work timeframe or a personal timeframe.

26. The electronic device of claim 25 , wherein the operational state of the electronic comprises one or more applications running on the electronic device when the electronic device is recording the at least a portion of the voice command.

26. The electronic device of claim 25 , wherein the operational state of the electronic comprises one or more applications running on the electronic device when the electronic device is recording the at least a portion of the voice command. 28. The electronic device of claim 26 , wherein the contextual information comprises a status of the one or more applications.

1. A computer-implemented method for selecting a portion of a content repository for replication, comprising: receiving, at a graphical user interface (GUI) operating on a computer, a selection of a content item in a content repository and an input describing one or more desired relationship patterns for replication, the relationship patterns associated with an ontology describing logical relationships between the selected content item and other content items in the content repository, the content repository including a plurality of content items, wherein the content items comprise digital documents, wherein the ontology is stored in one or more tags associated with one or more content items in the content repository; generating a query for the desired relationship patterns; identifying the selected content item and related content items of the content repository to replicate to a target storage device based on a storage capacity of the target storage device, wherein the target storage device is separate from the content repository, wherein the related content items comprise a logical relationship with the selected content item based on the desired relationship patterns; and selecting the identified content items of the content repository.

1. A computer-implemented method for selecting a portion of a content repository for replication, comprising: receiving, at a graphical user interface (GUI) operating on a computer, a selection of a content item in a content repository and an input describing one or more desired relationship patterns for replication, the relationship patterns associated with an ontology describing logical relationships between the selected content item and other content items in the content repository, the content repository including a plurality of content items, wherein the content items comprise digital documents, wherein the ontology is stored in one or more tags associated with one or more content items in the content repository; generating a query for the desired relationship patterns; identifying the selected content item and related content items of the content repository to replicate to a target storage device based on a storage capacity of the target storage device, wherein the target storage device is separate from the content repository, wherein the related content items comprise a logical relationship with the selected content item based on the desired relationship patterns; and selecting the identified content items of the content repository. 12. The computer-implemented method of claim 1 , wherein the ontology is stored in a triplestore.

13. The one or more computer systems of claim 11 , wherein the category is determined through a process, wherein the process includes one of the following: simple prediction, smoothed browse node prediction, expanded query group, N-Gram generative model, estimated probability as prior, or interpolation between multiple prediction models.

13. The one or more computer systems of claim 11 , wherein the category is determined through a process, wherein the process includes one of the following: simple prediction, smoothed browse node prediction, expanded query group, N-Gram generative model, estimated probability as prior, or interpolation between multiple prediction models. 16. The one or more computer systems of claim 13 , wherein the estimated probability as prior uses a formula: P ⁡ ( Click x | Q ) = ∑ Click x + α N + α / P est ⁡ ( Click x | Q ) wherein P is a probability, a is a smoothing factor, Click x is an observation of a click in browse node x, N is a number of observations of query Q, w x is a weight for an impression, and P est (Click x |Q) identifies a prior for clicks in browse node x using an N-Gram-based estimate.

1. A method of constructing a model of recognizing English pronunciation variations, applying to a computer connected to a non-transitory recording medium, for recognizing English pronunciations with intonations influenced by different non-English native languages, the method at least comprising: 1) providing a plurality of English expressions and at least one phonetic alphabet corresponding to each of the English expressions by the non-transitory recording medium, and collecting a plurality of corresponding sound information according to the phonetic alphabet of each of the English expression by the computer; 2) corresponding phonetic alphabets of the non-English native language and English to a plurality of international phonetic alphabets (IPAs) by the computer, so as to form a plurality of pronunciation models, wherein the computer forms each pronunciation models; 2-1) collecting a plurality of phonetic alphabet pronunciations directed to one of the IPAs, and converts each of the phonetic alphabet pronunciations into a corresponding characteristic value; 2-2) forming the characteristic values into a value group and calculates a grouping threshold value corresponding to the characteristic values; 2-3) calculating the computer calculates a mean value of the value group; 2-4) obtaining a first characteristic value from the value group which is away from the mean value by a maximum numerical distance; 2-5) calculating a second characteristic value in the value group which is away from the first characteristic value by a maximum numerical distance; 2-6) calculating numerical distances, wherein a first distance is calculated between each characteristic value and the first characteristic value and a second distance is calculated between each characteristic value and the second characteristic value, and forming value groups by the first distances and the second distances, one of the two value groups containing the characteristic values close to the first characteristic value and the other one of the two value groups containing the characteristic values close to the second characteristic value, respectively; 2-7) obtaining a within-group distance and a between-group distance of the two value groups, so as to calculate a grouping standard; and 2-8) determining whether the grouping standard is higher than the grouping threshold value through comparison, if yes, calculating each mean value of the two value groups and then, the step 2-4) to the step 2-8) are repeated for each one of the two value groups respectively, and if no, obtaining each value group of the pronunciation model that the computer want to form; 3) converting the sound information of each of the English expressions by using the pronunciation models, and constructing a pronunciation variation network corresponding to the English expression with reference to the phonetic alphabet of the English expression by the computer, so as to detect whether each of the English expressions has a pronunciation variation path; and 4) summarizing each of the pronunciation variation paths to form a plurality of pronunciation variation rules by the computer.

1. A method of constructing a model of recognizing English pronunciation variations, applying to a computer connected to a non-transitory recording medium, for recognizing English pronunciations with intonations influenced by different non-English native languages, the method at least comprising: 1) providing a plurality of English expressions and at least one phonetic alphabet corresponding to each of the English expressions by the non-transitory recording medium, and collecting a plurality of corresponding sound information according to the phonetic alphabet of each of the English expression by the computer; 2) corresponding phonetic alphabets of the non-English native language and English to a plurality of international phonetic alphabets (IPAs) by the computer, so as to form a plurality of pronunciation models, wherein the computer forms each pronunciation models; 2-1) collecting a plurality of phonetic alphabet pronunciations directed to one of the IPAs, and converts each of the phonetic alphabet pronunciations into a corresponding characteristic value; 2-2) forming the characteristic values into a value group and calculates a grouping threshold value corresponding to the characteristic values; 2-3) calculating the computer calculates a mean value of the value group; 2-4) obtaining a first characteristic value from the value group which is away from the mean value by a maximum numerical distance; 2-5) calculating a second characteristic value in the value group which is away from the first characteristic value by a maximum numerical distance; 2-6) calculating numerical distances, wherein a first distance is calculated between each characteristic value and the first characteristic value and a second distance is calculated between each characteristic value and the second characteristic value, and forming value groups by the first distances and the second distances, one of the two value groups containing the characteristic values close to the first characteristic value and the other one of the two value groups containing the characteristic values close to the second characteristic value, respectively; 2-7) obtaining a within-group distance and a between-group distance of the two value groups, so as to calculate a grouping standard; and 2-8) determining whether the grouping standard is higher than the grouping threshold value through comparison, if yes, calculating each mean value of the two value groups and then, the step 2-4) to the step 2-8) are repeated for each one of the two value groups respectively, and if no, obtaining each value group of the pronunciation model that the computer want to form; 3) converting the sound information of each of the English expressions by using the pronunciation models, and constructing a pronunciation variation network corresponding to the English expression with reference to the phonetic alphabet of the English expression by the computer, so as to detect whether each of the English expressions has a pronunciation variation path; and 4) summarizing each of the pronunciation variation paths to form a plurality of pronunciation variation rules by the computer. 3. The method of constructing a model of recognizing English pronunciation variations as claimed in claim 1 , wherein the characteristic values of at least one value group of the pronunciation model correspond to the phonetic alphabets of the English.

18. An information gathering system for optimizing searching as in claim 1 further includes a search process to identify business entities associated with one or more of the business activities in the SIC predefined taxonomy, which do not have a website.

18. An information gathering system for optimizing searching as in claim 1 further includes a search process to identify business entities associated with one or more of the business activities in the SIC predefined taxonomy, which do not have a website. 19. An information gathering system for optimizing searching as in claim 18 wherein the process to identify business entities associated with one or more of the business activities in the SIC predefined taxonomy, which do not have a website, further includes logic to assign each of the business entities identified to new categories created in the updated classification system.

11. A non-transitory computer program product storing instructions, which when executed by at least one data processor forming part of at least one computing system, result in operations comprising: receiving, at a client from a server, a dashboard container comprising a spreadsheet file and a dashboard structure file both in a text-based, language-independent data interchange format, the dashboard container having resulted from conversion by the server of the spreadsheet file and the dashboard structure file into the text-based, language-independent data interchange format, the spreadsheet file comprising cells including a first cell that includes a first formula and one or more referenced cells upon which evaluation of the first formula depends, the first formula being expressed as an object in the text-based, language-independent data interchange format, the dashboard structure file comprising metadata for use in rendering a dashboard comprising a plurality of components, at least one of the plurality of components comprising a visual component; rendering, at the client, the dashboard to include the spreadsheet and the plurality of components of the dashboard based at least on the received dashboard container; registering a first listener for the first formula on each of the one or more referenced cells; upon the first listener being notified of a change in any of the one or more referenced cells, notifying, by the first listener, a second listener for a second formula registered on the first cell by a second cell of the spreadsheet that comprises the second formula, the notifying occurring without evaluating the first formula based on the change; recursively evaluating the second cell and the first cell according to the first listener and at least the second listener to enable updating the visual component, which relies upon the second cell; and initiating, using a second rendering of the dashboard using the spreadsheet file, the dashboard structure file and results of the recursively evaluating.

11. A non-transitory computer program product storing instructions, which when executed by at least one data processor forming part of at least one computing system, result in operations comprising: receiving, at a client from a server, a dashboard container comprising a spreadsheet file and a dashboard structure file both in a text-based, language-independent data interchange format, the dashboard container having resulted from conversion by the server of the spreadsheet file and the dashboard structure file into the text-based, language-independent data interchange format, the spreadsheet file comprising cells including a first cell that includes a first formula and one or more referenced cells upon which evaluation of the first formula depends, the first formula being expressed as an object in the text-based, language-independent data interchange format, the dashboard structure file comprising metadata for use in rendering a dashboard comprising a plurality of components, at least one of the plurality of components comprising a visual component; rendering, at the client, the dashboard to include the spreadsheet and the plurality of components of the dashboard based at least on the received dashboard container; registering a first listener for the first formula on each of the one or more referenced cells; upon the first listener being notified of a change in any of the one or more referenced cells, notifying, by the first listener, a second listener for a second formula registered on the first cell by a second cell of the spreadsheet that comprises the second formula, the notifying occurring without evaluating the first formula based on the change; recursively evaluating the second cell and the first cell according to the first listener and at least the second listener to enable updating the visual component, which relies upon the second cell; and initiating, using a second rendering of the dashboard using the spreadsheet file, the dashboard structure file and results of the recursively evaluating. 12. A computer program product as in claim 11 , wherein the dashboard is rendered in a browser.

2. A system according to claim 1 , wherein the keyword processing means further comprises: storage means for storing item definition data defining the items of information in the information database; item matching means for matching recognized keywords or phrases to the item definition data; and item scoring means for keeping an item score for each item of information in dependence upon the number of keywords or phrases matched to each item.

2. A system according to claim 1 , wherein the keyword processing means further comprises: storage means for storing item definition data defining the items of information in the information database; item matching means for matching recognized keywords or phrases to the item definition data; and item scoring means for keeping an item score for each item of information in dependence upon the number of keywords or phrases matched to each item. 3. A system according to claim 2 , wherein the keyword processing means further comprises: item sorting means arranged to sort the items of information in dependence on the respective item scores.