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AIPD_nlp_sentence_dataset

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2. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information configured to allow access to a plurality of different online applications in association with an online application system, the different online applications including a first online application that provides access to a first one or more files stored at one or more servers associated with the first online application, a second online application that provides access to a second one or more files stored at one or more servers associated with the second online application, a third online application that provides access to a third one or more files stored at one or more servers associated with the third online application, and a fourth online application that provides access to a fourth one or more files stored at one or more servers associated with the fourth online application; code for receiving the global unique user login information in connection with a user logging in; code for identifying at least one first online application identifier associated with the first online application for registration purposes; code for identifying at least one second online application identifier associated with the second online application for registration purposes; code for identifying at least one third online application identifier associated with the third online application for registration purposes; code for identifying at least one fourth online application identifier associated with the fourth online application for registration purposes; code for receiving an indication to add access to the first online application for registration purposes; code for receiving an indication to add access to the second online application for registration purposes; code for receiving an indication to add access to the third online application for registration purposes; code for receiving an indication to add access to the fourth online application for registration purposes; code for, in connection with the at least one first online application identifier associated with the first online application, allowing registration of the first online application by: utilizing data required for the first online application, and receiving preference information associated with the first online application; code for, in connection with the at least one second online application identifier associated with the second online application, allowing registration of the second online application by: utilizing data required for the second online application, and receiving preference information associated with the second online application; code for, in connection with the at least one third online application identifier associated with the third online application, allowing registration of the third online application by: utilizing data required for the third online application, and receiving preference information associated with the third online application; code for, in connection with the at least one fourth online application identifier associated with the fourth online application, allowing registration of the fourth online application by: utilizing data required for the fourth online application, and receiving preference information associated with the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application, utilizing the data required for the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application, utilizing the data required for the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application, utilizing the data required for the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application, utilizing the data required for the fourth online application; code for identifying a document in association with the online application system; code for receiving a request from a logged-in user; code for, in response to the request, displaying an interface for receiving an indication of one or more tags, the interface including: at least one text box for receiving manually inserted tags, and a list of potential tags; code for, utilizing the interface, receiving the indication of the one or more tags; and code for correlating the one or more tags with the document.

2. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information configured to allow access to a plurality of different online applications in association with an online application system, the different online applications including a first online application that provides access to a first one or more files stored at one or more servers associated with the first online application, a second online application that provides access to a second one or more files stored at one or more servers associated with the second online application, a third online application that provides access to a third one or more files stored at one or more servers associated with the third online application, and a fourth online application that provides access to a fourth one or more files stored at one or more servers associated with the fourth online application; code for receiving the global unique user login information in connection with a user logging in; code for identifying at least one first online application identifier associated with the first online application for registration purposes; code for identifying at least one second online application identifier associated with the second online application for registration purposes; code for identifying at least one third online application identifier associated with the third online application for registration purposes; code for identifying at least one fourth online application identifier associated with the fourth online application for registration purposes; code for receiving an indication to add access to the first online application for registration purposes; code for receiving an indication to add access to the second online application for registration purposes; code for receiving an indication to add access to the third online application for registration purposes; code for receiving an indication to add access to the fourth online application for registration purposes; code for, in connection with the at least one first online application identifier associated with the first online application, allowing registration of the first online application by: utilizing data required for the first online application, and receiving preference information associated with the first online application; code for, in connection with the at least one second online application identifier associated with the second online application, allowing registration of the second online application by: utilizing data required for the second online application, and receiving preference information associated with the second online application; code for, in connection with the at least one third online application identifier associated with the third online application, allowing registration of the third online application by: utilizing data required for the third online application, and receiving preference information associated with the third online application; code for, in connection with the at least one fourth online application identifier associated with the fourth online application, allowing registration of the fourth online application by: utilizing data required for the fourth online application, and receiving preference information associated with the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application, utilizing the data required for the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application, utilizing the data required for the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application, utilizing the data required for the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application, utilizing the data required for the fourth online application; code for identifying a document in association with the online application system; code for receiving a request from a logged-in user; code for, in response to the request, displaying an interface for receiving an indication of one or more tags, the interface including: at least one text box for receiving manually inserted tags, and a list of potential tags; code for, utilizing the interface, receiving the indication of the one or more tags; and code for correlating the one or more tags with the document. 107. The computer program product of claim 2 , wherein the computer program product is configured such that the preference information associated with the first online application is entered via a registration interface dedicated to the first online application.

6. A non-transitory computer readable storage medium storing instructions that, when executed by a processor included in a computing device, cause the computing device to control a manner in which a software application accesses an application programming interface (API), by carrying out steps that include: receiving, from the software application executing on the computing device, a request to access the API; extracting, from the API, first license information that identifies whether all software applications executing on the computing device are permitted to access the API; identifying, based on the first license information, that not all software applications executing on the computing device are permitted to access the API; and in response to identifying: extracting, from the software application, second license information that identifies whether the software application is permitted to access the API, determining, based on the second license information, that the software application is permitted to access the API, and in response to determining: granting the software application access to the API.

6. A non-transitory computer readable storage medium storing instructions that, when executed by a processor included in a computing device, cause the computing device to control a manner in which a software application accesses an application programming interface (API), by carrying out steps that include: receiving, from the software application executing on the computing device, a request to access the API; extracting, from the API, first license information that identifies whether all software applications executing on the computing device are permitted to access the API; identifying, based on the first license information, that not all software applications executing on the computing device are permitted to access the API; and in response to identifying: extracting, from the software application, second license information that identifies whether the software application is permitted to access the API, determining, based on the second license information, that the software application is permitted to access the API, and in response to determining: granting the software application access to the API. 7. The non-transitory computer readable storage medium of claim 6 , wherein the API comprises a toolkit, a framework, a runtime library, a dynamic link library, or an applet, and the request to access the API is generated by a calling function or an object associated with the software application.

11. A computer-implemented method for facilitating performance by task performers of tasks from task requesters, the method comprising: receiving indications of multiple available tasks supplied by task requesters, each of the tasks being available for performance by one or more task performers; and for each of at least one of multiple task performers who are available to perform tasks, obtaining information about prior activities of the task performer that include performing one or more tasks supplied by one or more task requesters; automatically determining one or more attributes of tasks that are appropriate for the task performer based at least in part on the prior activities of the task performer, and identifying one or more of the multiple available tasks for the task performer based at least in part on the identified tasks each having at least one of the determined attributes, the automatic determining being performed by one or more configured computer processors and including weighting at least some of the obtained information about the prior activities of the task performer based on recency of the prior activities, such that a first prior activity of the task performer has a greater impact on the determining than does a second prior activity of the task performer if the first prior activity occurred more recently than the second prior activity; and providing one or more indications of the identified tasks to the task performer as recommendations.

11. A computer-implemented method for facilitating performance by task performers of tasks from task requesters, the method comprising: receiving indications of multiple available tasks supplied by task requesters, each of the tasks being available for performance by one or more task performers; and for each of at least one of multiple task performers who are available to perform tasks, obtaining information about prior activities of the task performer that include performing one or more tasks supplied by one or more task requesters; automatically determining one or more attributes of tasks that are appropriate for the task performer based at least in part on the prior activities of the task performer, and identifying one or more of the multiple available tasks for the task performer based at least in part on the identified tasks each having at least one of the determined attributes, the automatic determining being performed by one or more configured computer processors and including weighting at least some of the obtained information about the prior activities of the task performer based on recency of the prior activities, such that a first prior activity of the task performer has a greater impact on the determining than does a second prior activity of the task performer if the first prior activity occurred more recently than the second prior activity; and providing one or more indications of the identified tasks to the task performer as recommendations. 20. The method of claim 11 wherein, for each of one or more of the at least one task performers, the identifying of the one or more tasks for the task performer is further based at least in part on information about other task performers that are similar to the task performer, the information reflecting prior activities of the other task performers and/or attributes of the other task performers.

1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service.

1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service. 20. The system of claim 1 : wherein the at least one of the networked device and the networked service is further configured to communicate with the sandboxed program by polling a message queue, and wherein the message queue is configured to store a message from the sandboxed program.

7. The method of claim 6 , further comprising: parsing the text into a plurality of candidate labels, each candidate label being a unique n-gram of the text; and wherein the determining, obtaining and classifying are performed for each of the candidate labels.

7. The method of claim 6 , further comprising: parsing the text into a plurality of candidate labels, each candidate label being a unique n-gram of the text; and wherein the determining, obtaining and classifying are performed for each of the candidate labels. 9. The method of claim 7 , wherein determining that an image classification model is trained for an n-gram matching the candidate label comprises determining that an image classification model is trained for an n-gram that is the same as the candidate label.

4. The machine translation system of claim 1 wherein the translation component generates a plurality of rank ordered translation hypotheses and wherein the re-ranking component re-ranks the plurality of rank ordered translation hypotheses based on the grammatical elements assigned to each hypothesis.

4. The machine translation system of claim 1 wherein the translation component generates a plurality of rank ordered translation hypotheses and wherein the re-ranking component re-ranks the plurality of rank ordered translation hypotheses based on the grammatical elements assigned to each hypothesis. 6. The machine translation system of claim 4 wherein the re-ranking component generates the plurality additional textual of translation hypotheses by varying the grammatical elements assigned to each of the first plurality of rank ordered translation hypotheses.

1. In a grammar checking system, a system for detection and correction of inflection for words in a sentence, comprising: means for providing a list of incorrect words which do not follow normal language rules as to pluralization, past tense, past participle and superlative formation, along with the roots and morphological features thereof, said list being based on incorrect grammar; means for detecting words in said sentence which match a word in said list of incorrect words, thereby to identify an incorrect word; and, means for suggesting replacement words for a detected incorrect word including means responsive to the root and morphologic features of said incorrect words for identifying the incorrect word and its root and morphology and means including a natural language dictionary for selecting appropriate form of the word with said root and morphological features, thereby to suggest the correct word.

1. In a grammar checking system, a system for detection and correction of inflection for words in a sentence, comprising: means for providing a list of incorrect words which do not follow normal language rules as to pluralization, past tense, past participle and superlative formation, along with the roots and morphological features thereof, said list being based on incorrect grammar; means for detecting words in said sentence which match a word in said list of incorrect words, thereby to identify an incorrect word; and, means for suggesting replacement words for a detected incorrect word including means responsive to the root and morphologic features of said incorrect words for identifying the incorrect word and its root and morphology and means including a natural language dictionary for selecting appropriate form of the word with said root and morphological features, thereby to suggest the correct word. 4. The system of claim 1, wherein said means for providing said list includes a natural language dictionary and a list of normal rules of word formation, means for comparing words from said natural language dictionary and said list of normal rules to generate a further list of both non-real words and correct words, and means responsive to said last list and said natural language dictionary for providing as said incorrect word only those words from said further list which are not in said natural language dictionary.

13. The device of claim 1 , wherein phoneme-specific experts system includes at least one feature transform module configured to apply a transform to a respective one of the plurality of targeted features streams in order to emphasize spectral differences between a particular problematic phoneme and at least one conflicting phoneme.

13. The device of claim 1 , wherein phoneme-specific experts system includes at least one feature transform module configured to apply a transform to a respective one of the plurality of targeted features streams in order to emphasize spectral differences between a particular problematic phoneme and at least one conflicting phoneme. 14. The device of claim 13 , wherein the at least one feature transform module is configured to apply a linear discriminant analysis transform.

10. The method of claim 1 , wherein generating the hierarchical data structure comprises: generating, by the natural language platform, at least one annotation prompt for each topical node among the two or more topical nodes in the hierarchical data structure, said annotation prompt configured to elicit an annotation about said topical node indicating a level of accuracy of placement of the node within the hierarchical data structure; causing display of, by the natural language platform, the at least one annotation prompt for each topical node; and receiving, by the natural language platform, for each topical node, the annotation in response to the displayed annotation prompt.

10. The method of claim 1 , wherein generating the hierarchical data structure comprises: generating, by the natural language platform, at least one annotation prompt for each topical node among the two or more topical nodes in the hierarchical data structure, said annotation prompt configured to elicit an annotation about said topical node indicating a level of accuracy of placement of the node within the hierarchical data structure; causing display of, by the natural language platform, the at least one annotation prompt for each topical node; and receiving, by the natural language platform, for each topical node, the annotation in response to the displayed annotation prompt. 11. The method of claim 10 , further comprising evaluating performance of the hierarchical data structure based on the annotations.

1. A method of operating an access computing system comprising: using the access computing system to access a set of records maintained by a target computing system in a first database associated with a first entity over an internet based network, said first database being configured to respond to user queries for said records over said network using a first query protocol presented in a first interface; wherein said target computing system first query protocol restricts a user to using a first set of N parameters (N>=1) for locating matching records in said first database, said first set of N parameters being data fields associated with the set of records; further wherein said first interface of said target computing system constrains the user to use said first query protocol when accessing records in said first database, and further constrains the user to view only a single record at a time within a web browser; automatically generating a prioritized schedule with the access computing system identifying an ordering for accessing said set of records, which prioritized schedule is based in part on both the following computing operations: a) processing and identifying a likelihood of new data appearing within said set of records based on historical analysis of data change patterns in said records in said database, including computed correlations of occurrence and timing between distinct successive events in such records; and b) processing and identifying a likelihood of user interest in selected ones of said set of records based on historical analysis of user access, including other users of the access computing system, to such set of records; automatically retrieving said set of records in accordance with said prioritized schedule by automatically generating queries with the access computing system that emulate a user accessing said records using said first query protocol; configuring a second database with the computing system to store said set of records; configuring a second interface for accessing said of records in said second database, said second interface including a second query protocol which includes both said first set of N parameters for locating matching records in said second database as well as at least one search parameter in addition to said first set of N parameters; wherein said access computing system allows access to the set of records maintained at the target computing system using a different interface and a different protocol which emulates and enhances access options for querying the set of records, including by permitting the user to view more than one record at a time within said web browser.

1. A method of operating an access computing system comprising: using the access computing system to access a set of records maintained by a target computing system in a first database associated with a first entity over an internet based network, said first database being configured to respond to user queries for said records over said network using a first query protocol presented in a first interface; wherein said target computing system first query protocol restricts a user to using a first set of N parameters (N>=1) for locating matching records in said first database, said first set of N parameters being data fields associated with the set of records; further wherein said first interface of said target computing system constrains the user to use said first query protocol when accessing records in said first database, and further constrains the user to view only a single record at a time within a web browser; automatically generating a prioritized schedule with the access computing system identifying an ordering for accessing said set of records, which prioritized schedule is based in part on both the following computing operations: a) processing and identifying a likelihood of new data appearing within said set of records based on historical analysis of data change patterns in said records in said database, including computed correlations of occurrence and timing between distinct successive events in such records; and b) processing and identifying a likelihood of user interest in selected ones of said set of records based on historical analysis of user access, including other users of the access computing system, to such set of records; automatically retrieving said set of records in accordance with said prioritized schedule by automatically generating queries with the access computing system that emulate a user accessing said records using said first query protocol; configuring a second database with the computing system to store said set of records; configuring a second interface for accessing said of records in said second database, said second interface including a second query protocol which includes both said first set of N parameters for locating matching records in said second database as well as at least one search parameter in addition to said first set of N parameters; wherein said access computing system allows access to the set of records maintained at the target computing system using a different interface and a different protocol which emulates and enhances access options for querying the set of records, including by permitting the user to view more than one record at a time within said web browser. 2. The method of claim 1 , wherein said data fields include a single numerical entry field.

1. A method for training a semantic ability of a subject, the method being performed by a computer, the method comprising: a. displaying a linguistic task to a subject on a display of the computer, said linguistic task comprising providing one or more words, wherein said linguistic task is directed to training the subject in a specific semantic skill or skills; b. providing a plurality of linguistic clues to the subject, through the display of the computer, said plurality of linguistic clues comprising content capable of activating concepts related to said one or more words but wherein said content does not include said one or more words or synonyms thereof, wherein said linguistic clues are selected such that the subject integrates said plurality of linguistic clues to solve said linguistic task, wherein said linguistic clue comprises an image, audio, video, text or a combination thereof; c. receiving a solution to said linguistic task by the subject through the computer; and d. when said solution is not correct, providing one or more additional linguistic clues to the subject, said one or more additional linguistic clues comprising content capable of activating concepts related to said one or more words, wherein the subject integrates said one or more additional linguistic clues with said plurality of linguistic clues to solve said linguistic task, and wherein i) said content does not include said one or more words or synonyms thereof, or ii) when said content does include said one or more words or synonyms thereof, said content does not comprise written text; wherein said plurality of clues is revealed sequentially according to a requirement for integration of said plurality of linguistic clues by the subject; wherein each clue is revealed separately, such that only one clue is revealed at a given time; wherein said providing said linguistic clues to the subject further comprises penalizing the subject when the subject requests display of a previously displayed clue.

1. A method for training a semantic ability of a subject, the method being performed by a computer, the method comprising: a. displaying a linguistic task to a subject on a display of the computer, said linguistic task comprising providing one or more words, wherein said linguistic task is directed to training the subject in a specific semantic skill or skills; b. providing a plurality of linguistic clues to the subject, through the display of the computer, said plurality of linguistic clues comprising content capable of activating concepts related to said one or more words but wherein said content does not include said one or more words or synonyms thereof, wherein said linguistic clues are selected such that the subject integrates said plurality of linguistic clues to solve said linguistic task, wherein said linguistic clue comprises an image, audio, video, text or a combination thereof; c. receiving a solution to said linguistic task by the subject through the computer; and d. when said solution is not correct, providing one or more additional linguistic clues to the subject, said one or more additional linguistic clues comprising content capable of activating concepts related to said one or more words, wherein the subject integrates said one or more additional linguistic clues with said plurality of linguistic clues to solve said linguistic task, and wherein i) said content does not include said one or more words or synonyms thereof, or ii) when said content does include said one or more words or synonyms thereof, said content does not comprise written text; wherein said plurality of clues is revealed sequentially according to a requirement for integration of said plurality of linguistic clues by the subject; wherein each clue is revealed separately, such that only one clue is revealed at a given time; wherein said providing said linguistic clues to the subject further comprises penalizing the subject when the subject requests display of a previously displayed clue. 7. The method of claim 1 , further comprising providing an incentive to the subject to provide said solution through the computer; wherein said incentive comprises one or more of points to obtain a reward, points convertible to monetary value, points relating to progress and/or points for comparison between different users.

12. A computer-based method for training a user in the operation of an abacus comprising: generating a series of mathematical problems without displaying the mathematical problems to a user; converting the mathematical problems into corresponding hand movements for manipulation of beads of the abacus; generating animations of the corresponding hand movements; displaying the animations to the user without displaying the mathematical problems to the user; accepting user input describing the mathematical problems, which have not been displayed to the user; comparing the user input to the mathematical problems to determine the accuracy of the user input; formulating a measure of user mastery based on the accuracy of the user input; and adjusting the series of mathematical problems based on the measure of user mastery.

12. A computer-based method for training a user in the operation of an abacus comprising: generating a series of mathematical problems without displaying the mathematical problems to a user; converting the mathematical problems into corresponding hand movements for manipulation of beads of the abacus; generating animations of the corresponding hand movements; displaying the animations to the user without displaying the mathematical problems to the user; accepting user input describing the mathematical problems, which have not been displayed to the user; comparing the user input to the mathematical problems to determine the accuracy of the user input; formulating a measure of user mastery based on the accuracy of the user input; and adjusting the series of mathematical problems based on the measure of user mastery. 16. The method of claim 12 , wherein the generating a series of mathematical problems comprises selecting parameters of the mathematical problems randomly.

6. The speech recognition system of claim 1 wherein the dynamic visual feature extraction apparatus further comprises transducer means for sensing of motion between the selected facial features and for converting the sensed motion into an electrical signal representative of the motion for use in generating the visual dynamic feature vector set of signals.

6. The speech recognition system of claim 1 wherein the dynamic visual feature extraction apparatus further comprises transducer means for sensing of motion between the selected facial features and for converting the sensed motion into an electrical signal representative of the motion for use in generating the visual dynamic feature vector set of signals. 7. The speech recognition system of claim 6 wherein the sensed selected facial features comprise upper lip motion relative to lower lip motion, relative mouth corner to corner motion, and relative nose to chin motion.

1. A method of computerized detection of clustered microcalcifications in a digital mammogram derived from an original radiographic image, comprising: producing a multi-pixel difference image of said digital mammogram to remove low-frequency structured anatomic background; performing a global gray-level thresholding of said difference image to produce a global thresholded image, including producing a histogram of the difference image, setting a global threshold based on a pre-selected percentage of pixels at the high end of the histogram, retaining unchanged in said difference image those pixels having a value above said global threshold, and setting to a predetermined constant the values of those pixels in the difference image which have a value below said global threshold; performing area filtering by means of morphological erosion on the image data resulting after global thresholding thereby to produce an area filtered image in which small signals are selectively removed; and processing said area filtered image in which small signals are selectively removed to identify microcalcifications; wherein said step of performing area filtering comprises: defining plural structuring elements each having a size of at least two pixels, sequentially defining each pixel in the image after global thresholding as an operating pixel and sequentially overlaying each operating pixel with each structuring element; determining, for each operating pixel sequentially overlaid by each structuring element, the minimum pixel value of the pixels overlaid by each structuring element in relation to the same operating pixel; determining the maximum of the minimum pixel values determined in relation to the same operating pixel; and setting the value of each pixel in the output area-filtered image corresponding to the position of the operating pixel in the global thresholded image to the respective maximum of said minimum values determined in the preceding step.

1. A method of computerized detection of clustered microcalcifications in a digital mammogram derived from an original radiographic image, comprising: producing a multi-pixel difference image of said digital mammogram to remove low-frequency structured anatomic background; performing a global gray-level thresholding of said difference image to produce a global thresholded image, including producing a histogram of the difference image, setting a global threshold based on a pre-selected percentage of pixels at the high end of the histogram, retaining unchanged in said difference image those pixels having a value above said global threshold, and setting to a predetermined constant the values of those pixels in the difference image which have a value below said global threshold; performing area filtering by means of morphological erosion on the image data resulting after global thresholding thereby to produce an area filtered image in which small signals are selectively removed; and processing said area filtered image in which small signals are selectively removed to identify microcalcifications; wherein said step of performing area filtering comprises: defining plural structuring elements each having a size of at least two pixels, sequentially defining each pixel in the image after global thresholding as an operating pixel and sequentially overlaying each operating pixel with each structuring element; determining, for each operating pixel sequentially overlaid by each structuring element, the minimum pixel value of the pixels overlaid by each structuring element in relation to the same operating pixel; determining the maximum of the minimum pixel values determined in relation to the same operating pixel; and setting the value of each pixel in the output area-filtered image corresponding to the position of the operating pixel in the global thresholded image to the respective maximum of said minimum values determined in the preceding step. 2. The method according to claim 1, wherein said step of processing said area filtered image comprises: performing local gray-level thresholding on the area filtered image to produce a threshold image in which pixels having a value below a local threshold are set to a uniform background value and pixels having values above the local threshold retain their values; performing texture discrimination on the threshold image by removing background trend therefrom and setting to a predetermined value those pixels having a first moment of power spectrum greater than a predetermined value thereby to produce a texture discriminated image; performing cluster filtering of the texture discriminated image to produce a cluster image of single-pixel signals identifying locations of potential microcalcifications; extracting predetermined features from locations in the digital mammogram identified in said cluster filtering step; and identifying microcalcifications based on the features extracted in said extracting step.

6. The system of claim 5 , wherein the processing unit is further configured to identify the service in a plurality of services according to a runtime selection rule.

6. The system of claim 5 , wherein the processing unit is further configured to identify the service in a plurality of services according to a runtime selection rule. 7. The system of claim 6 , wherein the runtime selection rule includes any one or more of the following selection rules: selection of the service with the lowest price, selection of the service with the fastest execution, selection of the service with the highest reliability.

4. A method of generating a text line classifier, the method comprising: selecting a plurality of text characters from a font reservoir; varying an aspect of the plurality of text characters to form a plurality of character samples; randomly arranging a number of character samples from the plurality of character samples to form a line of character samples; varying an aspect of the line of character samples to form a line of text characters; and extracting from the line of text characters one or more of a gradient orientation histogram feature, a gradient magnitude histogram feature, a pixel histogram feature, and a pixel histogram change feature.

4. A method of generating a text line classifier, the method comprising: selecting a plurality of text characters from a font reservoir; varying an aspect of the plurality of text characters to form a plurality of character samples; randomly arranging a number of character samples from the plurality of character samples to form a line of character samples; varying an aspect of the line of character samples to form a line of text characters; and extracting from the line of text characters one or more of a gradient orientation histogram feature, a gradient magnitude histogram feature, a pixel histogram feature, and a pixel histogram change feature. 5. The method of claim 4 , wherein: a number of text characters of the plurality of text characters differ only in that the number of text characters has a different font; and the font reservoir includes Asian characters.

7. A communication device comprising: a microphone; a speaker; an input device; a display; a camera; an antenna; a voice communicating implementer which implements voice communication by utilizing said microphone and said speaker; an OCR implementer which extracts alphanumeric data from an image retrieved via said camera; a sound caller ID implementer which outputs a specific sound from said speaker which corresponds to the caller of incoming call; an auto time adjusting implementer which automatically adjusts the clock of said communication device in accordance with a wireless signal received by said antenna; a calculation implementer which implements mathematical calculation by utilizing digits input via said input device; a word processing implementer which includes a bold formatting implementer, an italic formatting implementer, and/or a font formatting implementer, wherein said bold formatting implementer changes alphanumeric data to bold, said italic formatting implementer changes alphanumeric data to italic, and said font formatting implementer changes alphanumeric data to a selected font; a stereo audio data output implementer which outputs audio data in a stereo fashion; a digital camera implementer, wherein the output from said camera is stored in said communication device with the image quality identified by the user in advance to said output; a multiple language displaying implementer, wherein a specific language is selected from a plurality of languages, and the interface to operate said communication device is displayed with said specific language; a caller's information displaying implementer which displays a personal information regarding caller on said display when a phone call is received; an icon software implementer, wherein the software program indicated by an icon is executed when said icon is selected; a spreadsheet displaying implementer which displays a spreadsheet on said display, wherein said spreadsheet includes a plurality of cells which are aligned in a matrix fashion; and a TV remote controlling implementer which outputs a TV control signal, wherein said TV control signal is a wireless signal to control a TV tuner.

7. A communication device comprising: a microphone; a speaker; an input device; a display; a camera; an antenna; a voice communicating implementer which implements voice communication by utilizing said microphone and said speaker; an OCR implementer which extracts alphanumeric data from an image retrieved via said camera; a sound caller ID implementer which outputs a specific sound from said speaker which corresponds to the caller of incoming call; an auto time adjusting implementer which automatically adjusts the clock of said communication device in accordance with a wireless signal received by said antenna; a calculation implementer which implements mathematical calculation by utilizing digits input via said input device; a word processing implementer which includes a bold formatting implementer, an italic formatting implementer, and/or a font formatting implementer, wherein said bold formatting implementer changes alphanumeric data to bold, said italic formatting implementer changes alphanumeric data to italic, and said font formatting implementer changes alphanumeric data to a selected font; a stereo audio data output implementer which outputs audio data in a stereo fashion; a digital camera implementer, wherein the output from said camera is stored in said communication device with the image quality identified by the user in advance to said output; a multiple language displaying implementer, wherein a specific language is selected from a plurality of languages, and the interface to operate said communication device is displayed with said specific language; a caller's information displaying implementer which displays a personal information regarding caller on said display when a phone call is received; an icon software implementer, wherein the software program indicated by an icon is executed when said icon is selected; a spreadsheet displaying implementer which displays a spreadsheet on said display, wherein said spreadsheet includes a plurality of cells which are aligned in a matrix fashion; and a TV remote controlling implementer which outputs a TV control signal, wherein said TV control signal is a wireless signal to control a TV tuner. 8. The communication device of claim 7 , wherein said communication device is a handheld device.

1. A system of retrieving documents comprising the steps of: coding a plurality of stored documents as respective document feature vector; generating a query feature vector based on a query document; and performing one or more logical operations between the query feature vector and said document feature vector to obtain respective similarity measures.

1. A system of retrieving documents comprising the steps of: coding a plurality of stored documents as respective document feature vector; generating a query feature vector based on a query document; and performing one or more logical operations between the query feature vector and said document feature vector to obtain respective similarity measures. 4. The system of claim 1 , further comprising a step selected from the set comprising: returning results which lie above a certain similarity threshold, and/or retrieving a user definable number of documents which have the highest similarity.

10. The counterfeit-resistant document of claim 8, wherein said coating of ink and said substrate have different uniform directional reflective properties.

10. The counterfeit-resistant document of claim 8, wherein said coating of ink and said substrate have different uniform directional reflective properties. 11. The counterfeit-resistant document of claim 10, wherein a color of said coating of ink matches a color of said substrate, such that said coating is not readily ascertainable by the unaided eye when viewed from a first angle approximately perpendicular to said surface of said substrate, and said coating is readily ascertainable by the unaided eye when viewed from a second angle different than said first angle.

1. An apparatus for brokering information between a plurality of clients using identifiers uniquely defining a plurality of data constructs, comprising: a processor configured to: accept a new data construct from an authoring entity; assign a globally unique identifier to the new data construct; store the new data construct and the assigned globally unique identifier in a database; broker between the authoring entity and a second entity commercially distinct from the authoring entity to provide at least one of the second entity access to the new data construct by reference to the assigned globally unique identifier of the new data construct and provide the authoring entity access to an at least one of a plurality of pre-existing data constructs for use with the new data construct by reference to a globally unique identifier of the existing data construct; the brokering includes: comparing the new data construct to the plurality pre-existing data constructs to identify one or more pre-existing data constructs that are usable by the new data construct; and presenting the identified data constructs to the authoring entity for selection; the new data construct includes logic defining an output of the new data construct as a function of at least one of: a globally unique identifier of an existing data construct; and the portion of the data set associated with the new data construct.

1. An apparatus for brokering information between a plurality of clients using identifiers uniquely defining a plurality of data constructs, comprising: a processor configured to: accept a new data construct from an authoring entity; assign a globally unique identifier to the new data construct; store the new data construct and the assigned globally unique identifier in a database; broker between the authoring entity and a second entity commercially distinct from the authoring entity to provide at least one of the second entity access to the new data construct by reference to the assigned globally unique identifier of the new data construct and provide the authoring entity access to an at least one of a plurality of pre-existing data constructs for use with the new data construct by reference to a globally unique identifier of the existing data construct; the brokering includes: comparing the new data construct to the plurality pre-existing data constructs to identify one or more pre-existing data constructs that are usable by the new data construct; and presenting the identified data constructs to the authoring entity for selection; the new data construct includes logic defining an output of the new data construct as a function of at least one of: a globally unique identifier of an existing data construct; and the portion of the data set associated with the new data construct. 6. The apparatus of claim 1 , wherein the processor is configured to index the new data construct and the assigned globally unique identifier of the new data construct.

7. An apparatus, comprising: a processor; a memory storing at least one context sensitive dictionary having a plurality of first words therein, a subset of one or more of the first words being associated with one or more respective associated words and phrases, the or each respective associated word and phrase representing an instance of the first word with which it is associated; a display configured to display images to a user under the control of the processor; and a user input that enables user character input; wherein the processor is further configured to cause the apparatus to: compare input characters when input with the first words in the at least one context sensitive dictionary; determine, in dependence on the comparison, one or more first words in the context sensitive dictionary corresponding, at least partially, to the input characters; and select, in dependence on the determination, one or more associated words and phrases associated with the determined first words; the display being configured to display the selected one or more associated words and phrases to the user as a substitution for the input characters.

7. An apparatus, comprising: a processor; a memory storing at least one context sensitive dictionary having a plurality of first words therein, a subset of one or more of the first words being associated with one or more respective associated words and phrases, the or each respective associated word and phrase representing an instance of the first word with which it is associated; a display configured to display images to a user under the control of the processor; and a user input that enables user character input; wherein the processor is further configured to cause the apparatus to: compare input characters when input with the first words in the at least one context sensitive dictionary; determine, in dependence on the comparison, one or more first words in the context sensitive dictionary corresponding, at least partially, to the input characters; and select, in dependence on the determination, one or more associated words and phrases associated with the determined first words; the display being configured to display the selected one or more associated words and phrases to the user as a substitution for the input characters. 8. The apparatus according to claim 7 , further comprising a renderer capable of communicating by wire or wirelessly with an external server via a network.

1. A method for finding and accessing desired content from audio and video content sources, the method steps comprising: providing a server with a processing unit, the server is constructed, configured and coupled to enable communication over a network; the server provides for user interconnection with the server over the network using a computing device positioned remotely from the server; the server and computing device running non-transitory computer-readable storage media with executable programs stored thereon; the computing device monitoring a broadcast; the executable programs: extracting captions from a broadcast in near real-time; aggregating the captions in a database in a cloud computing system; indexing the database content; searching the captions for a mention of at least one target; analyzing the results for desired content; and indexing into the database to extract the desired content; and thereby providing a method for quickly finding and accessing desired audio and video content from a large number of sources.

1. A method for finding and accessing desired content from audio and video content sources, the method steps comprising: providing a server with a processing unit, the server is constructed, configured and coupled to enable communication over a network; the server provides for user interconnection with the server over the network using a computing device positioned remotely from the server; the server and computing device running non-transitory computer-readable storage media with executable programs stored thereon; the computing device monitoring a broadcast; the executable programs: extracting captions from a broadcast in near real-time; aggregating the captions in a database in a cloud computing system; indexing the database content; searching the captions for a mention of at least one target; analyzing the results for desired content; and indexing into the database to extract the desired content; and thereby providing a method for quickly finding and accessing desired audio and video content from a large number of sources. 9. The method of claim 1 , further including the step of creating captions for un-captioned audio content.

8. A data processing apparatus, comprising: one or more processors; an HTTP proxy server hosted on one or more of the one or more processors; an SMTP mail transfer agent that is coupled to the HTTP proxy server; electronic mail processing logic that comprises one or more sequences of instructions which, when executed by the one or more processors, cause the one or more processors to perform the steps of: receiving an electronic mail message that comprises one or more hyperlinks; modifying each of the one or more hyperlinks in the electronic mail message by associating, with the one or more hyperlinks, an identifier value that indicates origin information; delivering the modified electronic mail message to a recipient account; in response to receiving a user request to access a specified hyperlink in the modified electronic mail message, retrieving the associated identifier value for the specified hyperlink, and determining whether access to the specified hyperlink is allowed based on the retrieved associated identifier value.

8. A data processing apparatus, comprising: one or more processors; an HTTP proxy server hosted on one or more of the one or more processors; an SMTP mail transfer agent that is coupled to the HTTP proxy server; electronic mail processing logic that comprises one or more sequences of instructions which, when executed by the one or more processors, cause the one or more processors to perform the steps of: receiving an electronic mail message that comprises one or more hyperlinks; modifying each of the one or more hyperlinks in the electronic mail message by associating, with the one or more hyperlinks, an identifier value that indicates origin information; delivering the modified electronic mail message to a recipient account; in response to receiving a user request to access a specified hyperlink in the modified electronic mail message, retrieving the associated identifier value for the specified hyperlink, and determining whether access to the specified hyperlink is allowed based on the retrieved associated identifier value. 12. The apparatus as recited in claim 8 , further comprising instructions which, when executed, cause receiving the user request to access the specified hyperlink at the HTTP proxy server, and receiving the electronic mail message at the SMTP mail transfer agent.

1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive a natural language document comprising tabular data; analyze the tabular data within the natural language document to identify at least one portion of the tabular data comprising an erroneous or missing data value; determine, for the at least one portion, a functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data by reference to the natural language document; determine for the at least one portion, a correct data value for the erroneous or missing data value of the at least one portion of the tabular data based on the determined functional dependency of the at least one portion; modify the tabular data to replace the erroneous or missing data value with the correct data value and thereby generate a modified tabular data structure; and perform a processing operation on the modified tabular data structure to generate a resulting output.

1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive a natural language document comprising tabular data; analyze the tabular data within the natural language document to identify at least one portion of the tabular data comprising an erroneous or missing data value; determine, for the at least one portion, a functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data by reference to the natural language document; determine for the at least one portion, a correct data value for the erroneous or missing data value of the at least one portion of the tabular data based on the determined functional dependency of the at least one portion; modify the tabular data to replace the erroneous or missing data value with the correct data value and thereby generate a modified tabular data structure; and perform a processing operation on the modified tabular data structure to generate a resulting output. 2. The computer program product of claim 1 , wherein the natural language document is an original document of a corpus of information, and wherein the modified tabular data structure is part of a modified document that replaces the original document in the corpus of information.

21. A system for annotating webpage content, the system comprising: a computerized device communicatively coupled with a webpage server under control of a third party and with an annotations repository under control of an entity different from the third party, the computerized device including: a browser configured to perform first operations comprising, the first operations comprising receiving, from a user associated with the computerized device, a request to access a webpage being hosted by the webpage server, where the user is other than both the third party and the entity different from the third party, in response to said receiving from the user the request to access the webpage, requesting the webpage from the webpage server, and receiving a response from the webpage server including a current instance of the webpage, and the browser is further configured to perform second operations, the second operations comprising requesting, from the annotations repository in response to said receiving from the user the request to access the webpage, a collection of annotations made to the webpage by the user associated with the computerized device, the annotations collection being stored at the annotations repository, the annotations collection including one or more annotations relating to corresponding one or more portions of webpage content of the webpage, receiving a response from the annotations repository including the requested annotations collection, and concurrently displaying the current instance of the webpage received with the response from the webpage server and the annotations collection received with the response from the annotations repository, such that the one or more annotations included in the received annotations collection are overlaid on the corresponding one or more portions of the webpage content of the received current instance of the webpage.

21. A system for annotating webpage content, the system comprising: a computerized device communicatively coupled with a webpage server under control of a third party and with an annotations repository under control of an entity different from the third party, the computerized device including: a browser configured to perform first operations comprising, the first operations comprising receiving, from a user associated with the computerized device, a request to access a webpage being hosted by the webpage server, where the user is other than both the third party and the entity different from the third party, in response to said receiving from the user the request to access the webpage, requesting the webpage from the webpage server, and receiving a response from the webpage server including a current instance of the webpage, and the browser is further configured to perform second operations, the second operations comprising requesting, from the annotations repository in response to said receiving from the user the request to access the webpage, a collection of annotations made to the webpage by the user associated with the computerized device, the annotations collection being stored at the annotations repository, the annotations collection including one or more annotations relating to corresponding one or more portions of webpage content of the webpage, receiving a response from the annotations repository including the requested annotations collection, and concurrently displaying the current instance of the webpage received with the response from the webpage server and the annotations collection received with the response from the annotations repository, such that the one or more annotations included in the received annotations collection are overlaid on the corresponding one or more portions of the webpage content of the received current instance of the webpage. 39. The system of claim 21 , wherein the computerized device is further communicatively coupled with a second annotations repository under control of a second entity different from the third party, and the second operations further comprise informing the user associated with the computerized device of a second annotations collection being available at the second annotations repository, the second annotations collection having been authored by a second author different from the user associated with the computerized device, and being associated with the webpage, the second annotations collection including one or more annotations relating to corresponding one or more portions of webpage content of the webpage, receiving, from the user associated with the computerized device in response to said informing, a request to access the second annotations collection, in response to said receiving, from the user, of the request to access the second collection, requesting the second annotations collection from the second annotations repository, receiving a response from the second annotations repository including the second annotations collection, and concurrently displaying the current instance of the webpage received from the webpage server, the second annotations collection received from the second annotations repository and the annotations collection received from the annotations repository, such that the one or more annotations included in the initially received annotations collection and the one or more annotations included in the received second annotations collection are overlaid on the corresponding portions of the webpage content of the received current instance of the webpage.

1. A method comprising: receiving item category data by a computing device, wherein the item category data comprises a plurality of nodes and each node is associated with an item category of a plurality of item categories; receiving a plurality of queries by the computing device; for each query of the plurality of queries, providing an indicator of one or more items that are responsive to the query of a plurality of items by the computing device, wherein the plurality of items comprise at least one of products or services; for each query of the plurality of queries, receiving a selection of an item indicated by the provided indicator of one or more items by the computing device; receiving item data that associates an item category of the plurality of item categories with each item of the plurality of items by the computing device; based on the selected item for each query of the plurality of queries and the item category associated with each item, generating training data by the computing device, wherein the training data comprises a mapping of queries to item categories; for each query and item category in the mapping, determining a count of the number of times that the item category is associated with the query in the mapping by the computing device; combining the training data and item category data by, for each determined count for each item category, associating the determined count with the node of the plurality of nodes associated with the item category by the computing device; receiving another query by the computing device; receiving a classifier by the computing device, wherein the classifier, when applied to a node of the plurality of nodes using the received query by the computing device, results in a generated probability that the received query is intended for the item category associated with the node; applying the classifier to the plurality of nodes using the received query by the computing device until a generated probability for a node is below a threshold probability resulting in a list of item categories and a generated probability for each item category; ranking the item categories in the list of item categories based on the generated probabilities by the computing device; and providing the item categories in a ranked order by the computing device through a network.

1. A method comprising: receiving item category data by a computing device, wherein the item category data comprises a plurality of nodes and each node is associated with an item category of a plurality of item categories; receiving a plurality of queries by the computing device; for each query of the plurality of queries, providing an indicator of one or more items that are responsive to the query of a plurality of items by the computing device, wherein the plurality of items comprise at least one of products or services; for each query of the plurality of queries, receiving a selection of an item indicated by the provided indicator of one or more items by the computing device; receiving item data that associates an item category of the plurality of item categories with each item of the plurality of items by the computing device; based on the selected item for each query of the plurality of queries and the item category associated with each item, generating training data by the computing device, wherein the training data comprises a mapping of queries to item categories; for each query and item category in the mapping, determining a count of the number of times that the item category is associated with the query in the mapping by the computing device; combining the training data and item category data by, for each determined count for each item category, associating the determined count with the node of the plurality of nodes associated with the item category by the computing device; receiving another query by the computing device; receiving a classifier by the computing device, wherein the classifier, when applied to a node of the plurality of nodes using the received query by the computing device, results in a generated probability that the received query is intended for the item category associated with the node; applying the classifier to the plurality of nodes using the received query by the computing device until a generated probability for a node is below a threshold probability resulting in a list of item categories and a generated probability for each item category; ranking the item categories in the list of item categories based on the generated probabilities by the computing device; and providing the item categories in a ranked order by the computing device through a network. 6. The method of claim 1 , wherein the classifier generates a probability that the received query is intended for an item category associated with the node of the plurality of nodes by determining the count associated with the node for the received query and generating the probability using the determined count.

8. The method of claim 6 wherein determining comprises using a combination of features comprising: (a) Kullback-Leibler divergence; (b) autocorrelation; (c) kurtosis; (d) Kleinberg's burst model.

8. The method of claim 6 wherein determining comprises using a combination of features comprising: (a) Kullback-Leibler divergence; (b) autocorrelation; (c) kurtosis; (d) Kleinberg's burst model. 9. The method of claim 8 wherein determining comprises using a content clarity.

14. The method of claim 13 , wherein the semantic directory lists one or more of services, assumptions and processing methodologies of the plurality of participants.

14. The method of claim 13 , wherein the semantic directory lists one or more of services, assumptions and processing methodologies of the plurality of participants. 15. The method of claim 14 , further comprising the step of externalizing the services, assumptions, and processing methodologies of the plurality of participants, wherein the externalization is performed using one or more of specifically designed ontologies and federated ontologies.

8. A method of reducing writing problems in prose, the method comprising: scanning a sentence for at least one sign; determining that a sign is present in the sentence, the sign representing a possible occurrence of a writing problem, the sign comprising the word “it” and two commas appearing between a “to be” verb and the word “that”; and identifying, in connection with the sign, an edit that changes the sentence in a way that addresses the writing problem, the edit comprising deletion of all of the words from “it” through “that”, except for the words between the two commas; said method performed by a computer system that comprises one or more computers.

8. A method of reducing writing problems in prose, the method comprising: scanning a sentence for at least one sign; determining that a sign is present in the sentence, the sign representing a possible occurrence of a writing problem, the sign comprising the word “it” and two commas appearing between a “to be” verb and the word “that”; and identifying, in connection with the sign, an edit that changes the sentence in a way that addresses the writing problem, the edit comprising deletion of all of the words from “it” through “that”, except for the words between the two commas; said method performed by a computer system that comprises one or more computers. 10. The method of claim 8 , further comprising outputting the edit to a user via a user interface that enables the user to accept or reject the edit.

34. The method for publication and distribution of educational materials of claim 25 further comprising: receiving over a communications network one or more revisions to one or more of the segments, incorporating the revisions in the segments to create revised segments, and storing the revised segments.

34. The method for publication and distribution of educational materials of claim 25 further comprising: receiving over a communications network one or more revisions to one or more of the segments, incorporating the revisions in the segments to create revised segments, and storing the revised segments. 36. The method for publication and distribution of educational materials of claim 34 further comprising: generating an email message alerting those who have selected a segment for inclusion in the compilation that a revision of the segment has been stored.

1. A system comprising: at least one hardware processor programmed to provide an identity manager programmed to manage a plurality of user identities of an individual user, the plurality of user identities pertaining to the individual user and describing different sets of personal information of the individual user, and to select one or more of the user identities of the user that satisfy a set of identity requirements of a security policy obtained from an environment; a privacy engine operatively associated with a plurality of privacy preferences, the privacy engine programmed to evaluate one or more privacy preferences of the one or more selected user identities of the user against a privacy policy obtained from the environment to determine which of the selected user identities satisfy the at least one privacy preference; and a policy editor programmed to process a privacy policy from the environment, generate a reduced version thereof, and supply the reduced privacy policy as the privacy policy used by the privacy engine evaluation.

1. A system comprising: at least one hardware processor programmed to provide an identity manager programmed to manage a plurality of user identities of an individual user, the plurality of user identities pertaining to the individual user and describing different sets of personal information of the individual user, and to select one or more of the user identities of the user that satisfy a set of identity requirements of a security policy obtained from an environment; a privacy engine operatively associated with a plurality of privacy preferences, the privacy engine programmed to evaluate one or more privacy preferences of the one or more selected user identities of the user against a privacy policy obtained from the environment to determine which of the selected user identities satisfy the at least one privacy preference; and a policy editor programmed to process a privacy policy from the environment, generate a reduced version thereof, and supply the reduced privacy policy as the privacy policy used by the privacy engine evaluation. 4. The system of claim 1 , further comprises a privacy editor programmed to provide at least one categorized group of user identity attributes, and to determine a privacy preference for each category.

16. A system for providing thematic information to provide a visual theme for documents, comprising: a computer readable storage medium encoded with a theme object for conveying thematic information for visual display of documents; wherein the theme object is defined using a markup language and is stored in a theme file; wherein the definition of the theme object is maintained separately within the theme file from other objects that define the document and that are each maintained separately; and wherein a schema defines and enforces rules for displaying the theme object; an operating system executed on a processor; wherein the operating system provides an application programming interface (API) to the theme object; an application suite executed on a processor; wherein the application suite comprises a first application for authoring a first kind of document using the API to the theme object, and comprising a second application that is different from the first application for authoring a second kind of document using the API to the theme object; wherein the first kind of document is associated with a first file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the first file format; wherein the second kind of document is associated with a second file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the second file format; wherein the theme object provides a common appearance for the first kind of document and the second kind of document.

16. A system for providing thematic information to provide a visual theme for documents, comprising: a computer readable storage medium encoded with a theme object for conveying thematic information for visual display of documents; wherein the theme object is defined using a markup language and is stored in a theme file; wherein the definition of the theme object is maintained separately within the theme file from other objects that define the document and that are each maintained separately; and wherein a schema defines and enforces rules for displaying the theme object; an operating system executed on a processor; wherein the operating system provides an application programming interface (API) to the theme object; an application suite executed on a processor; wherein the application suite comprises a first application for authoring a first kind of document using the API to the theme object, and comprising a second application that is different from the first application for authoring a second kind of document using the API to the theme object; wherein the first kind of document is associated with a first file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the first file format; wherein the second kind of document is associated with a second file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the second file format; wherein the theme object provides a common appearance for the first kind of document and the second kind of document. 17. The system of claim 16 wherein the first application is a spreadsheet application and the second application is a word processing application.

32. A computer implemented method, comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations before search results responsive to the query are identified: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting one or more of the one or more splits according to the overall score for each split; and augmenting the query with the subterms of each selected split.

32. A computer implemented method, comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations before search results responsive to the query are identified: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting one or more of the one or more splits according to the overall score for each split; and augmenting the query with the subterms of each selected split. 33. The method of claim 32 , wherein generating one or more splits of the first compound term comprises incrementally analyzing prefixes of increasing length of the first compound term to identify subterms of the prefix that appear in the dictionary.

1. A method comprising: selecting, by a computing device, sets of two or more text candidates from a plurality of text candidates corresponding to vocal input; for each set of the sets of two or more text candidates, outputting, by the computing device, representations of each of the respective two or more text candidates in the set to a plurality of users, wherein the representations are outputted as audio; receiving selections from each of the plurality of users of one of the respective two or more text candidates from each set, wherein the selections are based at least in part on satisfying a criterion; and determining that a text candidate included in the plurality of text candidates has a highest probability out of the plurality of text candidates of being a correct textual transcription of the vocal input based at least in part on the selections from the plurality of users, wherein the text candidate is a least-selected candidate by the plurality of users out of the plurality of text candidates.

1. A method comprising: selecting, by a computing device, sets of two or more text candidates from a plurality of text candidates corresponding to vocal input; for each set of the sets of two or more text candidates, outputting, by the computing device, representations of each of the respective two or more text candidates in the set to a plurality of users, wherein the representations are outputted as audio; receiving selections from each of the plurality of users of one of the respective two or more text candidates from each set, wherein the selections are based at least in part on satisfying a criterion; and determining that a text candidate included in the plurality of text candidates has a highest probability out of the plurality of text candidates of being a correct textual transcription of the vocal input based at least in part on the selections from the plurality of users, wherein the text candidate is a least-selected candidate by the plurality of users out of the plurality of text candidates. 9. The method of claim 1 , wherein: the plurality of text candidates are produced by a plurality of automatic speech recognition (ASR) engines.

1. A processor-implemented method, comprising: receiving an input from a user identifying an initial document in a collection of documents; identifying other documents in the collection of documents that are related to the initial document, comprising: assigning scores to a plurality of compressed document surrogates corresponding to the collection of documents, the scores depending on an occurrence in the compressed document surrogates of at least one term in the initial document, wherein a score S D of a compressed document surrogate D in the plurality of compressed document surrogates is determined by crediting the compressed document surrogate D, for each term T in the initial document which occurs in the compressed document surrogate D, with an amount proportional to Robertson's term frequency TF TD and to IDF T where TF TD =N TD /( N TD +K 1 +K 2 *( L D /L 0 )),and N TD is the number of times the term T occurs in compressed document surrogate D, L D is the length of compressed document surrogate D, L 0 is the average length of a document in the collection of documents, K 1 and K 2 are constants, and IDF T = log((N+K 3 )/N T )/log(N+K 4 ), and N is the number of documents in the collection of documents, N T is the number of documents containing the term T in the collection of documents, and K 3 and K 4 are constants; selecting a set of documents from the collection of documents, the set of documents comprising documents corresponding to those of the plurality of compressed document surrogates assigned the highest scores; and presenting information identifying the set of documents to the user.

1. A processor-implemented method, comprising: receiving an input from a user identifying an initial document in a collection of documents; identifying other documents in the collection of documents that are related to the initial document, comprising: assigning scores to a plurality of compressed document surrogates corresponding to the collection of documents, the scores depending on an occurrence in the compressed document surrogates of at least one term in the initial document, wherein a score S D of a compressed document surrogate D in the plurality of compressed document surrogates is determined by crediting the compressed document surrogate D, for each term T in the initial document which occurs in the compressed document surrogate D, with an amount proportional to Robertson's term frequency TF TD and to IDF T where TF TD =N TD /( N TD +K 1 +K 2 *( L D /L 0 )),and N TD is the number of times the term T occurs in compressed document surrogate D, L D is the length of compressed document surrogate D, L 0 is the average length of a document in the collection of documents, K 1 and K 2 are constants, and IDF T = log((N+K 3 )/N T )/log(N+K 4 ), and N is the number of documents in the collection of documents, N T is the number of documents containing the term T in the collection of documents, and K 3 and K 4 are constants; selecting a set of documents from the collection of documents, the set of documents comprising documents corresponding to those of the plurality of compressed document surrogates assigned the highest scores; and presenting information identifying the set of documents to the user. 2. The method of claim 1 , wherein assigning the scores, selecting the set of documents, and presenting the information identifying the set of documents to the user are performed automatically when a user accesses the initial document, without user intervention.

72. The system of claim 1 , wherein at least one sensor of the plurality of sensors measures in real-time object poses of at least one object of the plurality of objects.

72. The system of claim 1 , wherein at least one sensor of the plurality of sensors measures in real-time object poses of at least one object of the plurality of objects. 74. The system of claim 72 , wherein the at least one sensor is affixed to the at least one object.

1. A method operable in a computer-enabled apparatus, said method comprising: establishing a user profile for a user based on various interests of the user; establishing a virtual unified space including a virtual library on the computer-enabled apparatus; populating the virtual library with a plurality of different virtual media collections in accordance with the user profile, wherein the plurality of the different virtual media collections includes information obtained directly from at least a broadcasted television signal; and browsing the virtual library by moving between the plurality of different media collections under user control; searching the virtual unified space with a search engine under user control; and filtering the results of the searching step in accordance with the user profile and the browsing step, wherein said filtering comprises explicit and implicit filtering, wherein said explicit filtering provides filtering of from information from said plurality of different media collections and said implicit filtering draws from collaborative data among said plurality of different media collections and similar user profiles; prioritizing results of said filtering step; and updating the user profile in accordance with at least one selection of the results of the filtering step, wherein said updating is reflected in a ratio in responding to said user's current programming choice or specific requests.

1. A method operable in a computer-enabled apparatus, said method comprising: establishing a user profile for a user based on various interests of the user; establishing a virtual unified space including a virtual library on the computer-enabled apparatus; populating the virtual library with a plurality of different virtual media collections in accordance with the user profile, wherein the plurality of the different virtual media collections includes information obtained directly from at least a broadcasted television signal; and browsing the virtual library by moving between the plurality of different media collections under user control; searching the virtual unified space with a search engine under user control; and filtering the results of the searching step in accordance with the user profile and the browsing step, wherein said filtering comprises explicit and implicit filtering, wherein said explicit filtering provides filtering of from information from said plurality of different media collections and said implicit filtering draws from collaborative data among said plurality of different media collections and similar user profiles; prioritizing results of said filtering step; and updating the user profile in accordance with at least one selection of the results of the filtering step, wherein said updating is reflected in a ratio in responding to said user's current programming choice or specific requests. 9. The method as in claim 1 further comprising augmenting the user profile in accordance with a collaborative data base.

1. A method, comprising: for a subject category of interest having a plurality N of sub-categories, where N is an integer greater than one, training over a first set of images a plurality of image classifiers to yield a plurality of pre-trained classifiers (C 1 . . . C N ), where each individual one of the pre-trained classifiers is trained to recognize one sub-category of the plurality of sub-categories; obtaining a second set of images (i=1 . . . M) from at least one social media web site that a person has shared/posted/pinned or otherwise expressed an interest in, where M represents a total number of images in the second set of images; applying at least some of the pre-trained classifiers (C 1 . . . C N ) to each image i in the second set of images; obtaining a classification score vector {right arrow over (S)} i =[s 1 . . . s N ] for image i(i=1 . . . M), where s j indicates a classification score output from a classifier C j by applying it to image i; aggregating the M classification score vectors over all of the images of the second set of images; deriving a data construct that is descriptive of a preference profile of the person with respect to the sub-categories of the category of interest as a probability distribution over the N sub-categories; and characterizing by how much the person's profile differs from an average profile of a group of persons by assigning the person to a segment, where P a represents a probability vector for the person, and calculating an average P segment _ i for each segment i, where a degree to which the person is a member of the segment i is a dot product of the two vectors: P a• P segment _ i /(| P a | |P segment _ i |).

1. A method, comprising: for a subject category of interest having a plurality N of sub-categories, where N is an integer greater than one, training over a first set of images a plurality of image classifiers to yield a plurality of pre-trained classifiers (C 1 . . . C N ), where each individual one of the pre-trained classifiers is trained to recognize one sub-category of the plurality of sub-categories; obtaining a second set of images (i=1 . . . M) from at least one social media web site that a person has shared/posted/pinned or otherwise expressed an interest in, where M represents a total number of images in the second set of images; applying at least some of the pre-trained classifiers (C 1 . . . C N ) to each image i in the second set of images; obtaining a classification score vector {right arrow over (S)} i =[s 1 . . . s N ] for image i(i=1 . . . M), where s j indicates a classification score output from a classifier C j by applying it to image i; aggregating the M classification score vectors over all of the images of the second set of images; deriving a data construct that is descriptive of a preference profile of the person with respect to the sub-categories of the category of interest as a probability distribution over the N sub-categories; and characterizing by how much the person's profile differs from an average profile of a group of persons by assigning the person to a segment, where P a represents a probability vector for the person, and calculating an average P segment _ i for each segment i, where a degree to which the person is a member of the segment i is a dot product of the two vectors: P a• P segment _ i /(| P a | |P segment _ i |). 5. The method of claim 1 , where aggregating the M classification score vectors comprises thresholding each classification score to obtain a binary output and counting the number of classification score vectors falling into each sub-category.

28. A system, comprising: a display; a computer-readable storage medium comprising a script repository for electronically storing one or more scripts; and one or more processors that execute an input method editor (IME), that receive a user input to the IME, that determine, based on the user input, whether to process the user input with a script engine, that: when the user input indicates that the user input is to be processed with the script engine: provide the user input to the script engine, select the script from the script repository, process the user input through the script using the script engine to generate one or more candidates, and provide the one or more candidates to be displayed on the display; when the user input indicates that the user input is not to be processed with the script engine: provide the user input to the IME engine, and process the user input with the IME engine to generate one or more candidates, and provide the one or more candidates to be displayed on the display; and receive an extension mode input indicating operation of the IME in an extension mode, operate the IME in the extension mode in response to receiving the extension mode input, and provide all user input to the script engine when operating in the extension mode.

28. A system, comprising: a display; a computer-readable storage medium comprising a script repository for electronically storing one or more scripts; and one or more processors that execute an input method editor (IME), that receive a user input to the IME, that determine, based on the user input, whether to process the user input with a script engine, that: when the user input indicates that the user input is to be processed with the script engine: provide the user input to the script engine, select the script from the script repository, process the user input through the script using the script engine to generate one or more candidates, and provide the one or more candidates to be displayed on the display; when the user input indicates that the user input is not to be processed with the script engine: provide the user input to the IME engine, and process the user input with the IME engine to generate one or more candidates, and provide the one or more candidates to be displayed on the display; and receive an extension mode input indicating operation of the IME in an extension mode, operate the IME in the extension mode in response to receiving the extension mode input, and provide all user input to the script engine when operating in the extension mode. 43. The system of claim 28 , wherein the user input is provided in a first language.

1. A speech-recognition device which acquires an internal recognition result from its recognition processing of input speech data and an external recognition result from recognition processing of said input speech data by one or more external recognition devices external to the speech-recognition device to determine a final recognition result, the speech-recognition device comprising: memory including: an acoustic model in which feature quantities of speeches are modeled; a language model in which notations and readings of recognition-object words of the speech-recognition device are stored; and a reading dictionary in which pairs of the notations and the readings of the recognition-object words and words other than the recognition-object words are stored; and circuitry configured to: transmit said input speech data to the one or more external recognition devices; analyze the input speech data to calculate a feature vector; perform, using the acoustic model, pattern collation between the calculated feature vector and each word stored in the language model to calculate their respective acoustic likelihoods; output, as the internal recognition result, a corresponding notation, a corresponding reading, and a corresponding acoustic likelihood of top one or more high-ranking words; acquire the external recognition result from recognition processing of the input speech data by the one or more external recognition devices, extract a reading corresponding to a notation included in said external recognition result using the reading dictionary, and output a result composed of said external recognition result and the extracted reading; perform, using the acoustic model, pattern collation between the calculated feature vector and the output result to calculate an acoustic likelihood for the external recognition result; and compare the corresponding acoustic likelihood of the internal recognition result with the acoustic likelihood of the external recognition result to determine the final recognition result.

1. A speech-recognition device which acquires an internal recognition result from its recognition processing of input speech data and an external recognition result from recognition processing of said input speech data by one or more external recognition devices external to the speech-recognition device to determine a final recognition result, the speech-recognition device comprising: memory including: an acoustic model in which feature quantities of speeches are modeled; a language model in which notations and readings of recognition-object words of the speech-recognition device are stored; and a reading dictionary in which pairs of the notations and the readings of the recognition-object words and words other than the recognition-object words are stored; and circuitry configured to: transmit said input speech data to the one or more external recognition devices; analyze the input speech data to calculate a feature vector; perform, using the acoustic model, pattern collation between the calculated feature vector and each word stored in the language model to calculate their respective acoustic likelihoods; output, as the internal recognition result, a corresponding notation, a corresponding reading, and a corresponding acoustic likelihood of top one or more high-ranking words; acquire the external recognition result from recognition processing of the input speech data by the one or more external recognition devices, extract a reading corresponding to a notation included in said external recognition result using the reading dictionary, and output a result composed of said external recognition result and the extracted reading; perform, using the acoustic model, pattern collation between the calculated feature vector and the output result to calculate an acoustic likelihood for the external recognition result; and compare the corresponding acoustic likelihood of the internal recognition result with the acoustic likelihood of the external recognition result to determine the final recognition result. 6. The speech-recognition device of claim 1 , wherein the extracted reading for said external recognition result corresponds to a symbol sequence associated with the acoustic model.

6. The method of claim 1 further comprising: filtering a list of securities based on the user profile to generate the recommended securities; and presenting the recommended securities to the user for possible security swaps, wherein securities can be added to or removed from the current financial portfolio.

6. The method of claim 1 further comprising: filtering a list of securities based on the user profile to generate the recommended securities; and presenting the recommended securities to the user for possible security swaps, wherein securities can be added to or removed from the current financial portfolio. 12. The method of claim 6 further comprising: allowing the user to select at least one security from the filtered list of securities; swapping the selected securities with securities in the current financial portfolio; analyzing the effect of said swapping on the current financial portfolio; and displaying, via the computing device, the analysis.

1. A method for accessing information from XML documents stored in a base table within a relational database, the method comprising the computer-implemented steps of: identifying, within the XML documents, a set of nodes to be indexed; for each node in the set of nodes to be indexed, storing, in an index, an entry for the node, wherein the entry for a given node includes location data that identifies a location of XML content associated with the XML document that contains the given node, and at least one of: (a) hierarchical data that indicates a hierarchical position of the given node within the XML document that contains the given node; and (b) path data that corresponds to a path, through the structure of the XML document that contains the given node, to the given node; wherein the entry for the given node further includes a locator value that indicates a starting position, within the XML content that resides at said location, of an XML fragment associated with the given node; wherein the index includes a plurality of index entries that correspond to a plurality of nodes of a particular XML document of the XML documents; wherein each of the plurality of index entries includes the same location data, which identifies the location within the base table, of XML content for the particular XML document; wherein the locator value for each of the plurality of index entries indicates a different starting position within the XML content for the particular XML document stored at the location within the base table, wherein the starting position indicated by the locator value in each given index entry, of the plurality of index entries, is the starting position of the XML fragment corresponding to the node associated with said each given index entry; and using the index to locate information within the XML documents in response to requests for information from the XML documents, wherein using the index comprises locating the XML content associated with the given node based on at least the location data.

1. A method for accessing information from XML documents stored in a base table within a relational database, the method comprising the computer-implemented steps of: identifying, within the XML documents, a set of nodes to be indexed; for each node in the set of nodes to be indexed, storing, in an index, an entry for the node, wherein the entry for a given node includes location data that identifies a location of XML content associated with the XML document that contains the given node, and at least one of: (a) hierarchical data that indicates a hierarchical position of the given node within the XML document that contains the given node; and (b) path data that corresponds to a path, through the structure of the XML document that contains the given node, to the given node; wherein the entry for the given node further includes a locator value that indicates a starting position, within the XML content that resides at said location, of an XML fragment associated with the given node; wherein the index includes a plurality of index entries that correspond to a plurality of nodes of a particular XML document of the XML documents; wherein each of the plurality of index entries includes the same location data, which identifies the location within the base table, of XML content for the particular XML document; wherein the locator value for each of the plurality of index entries indicates a different starting position within the XML content for the particular XML document stored at the location within the base table, wherein the starting position indicated by the locator value in each given index entry, of the plurality of index entries, is the starting position of the XML fragment corresponding to the node associated with said each given index entry; and using the index to locate information within the XML documents in response to requests for information from the XML documents, wherein using the index comprises locating the XML content associated with the given node based on at least the location data. 6. The method of claim 1 further comprising building a secondary index for accessing an entry, in said index, for a parent node based on hierarchy information associated with a child node of said parent node; wherein an entry in the secondary index for the child node includes a value that identifies the entry, in said index, for the parent node.

12. The method as recited in claim 11 , further comprising controlling the video sensor in accordance with the configuration information.

12. The method as recited in claim 11 , further comprising controlling the video sensor in accordance with the configuration information. 13. The method as recited in claim 12 , wherein the configuration information includes at least one of the group comprising pan, zoom, or tilt information.

1. A computer-implemented method, comprising: generating, by a processor of a machine, a user interface for presentation on a user device, the user interface including perceptible user interface elements allowing a user to view title information; receiving a title of an item being listed; determining, by a processor of the machine, a concept, the concept including two or more terms in the title of the item being listed; accessing, from a networked database, a plurality of co-occurring terms stored in a co-occurring terms table, each co-occurring term in the co-occurring terms table including a first set of words and a second word, the first set of words and the second word corresponding to terms that have occurred together in stored search queries and to terms that have occurred together in stored item information corresponding to title information of items previously listed for sale on an online marketplace; generating, by a processor of the machine, a matching of the concept with one or more co-occurring terms of the plurality of co-occurring terms, the matching being based on the concept matching the first set of words of the one or more co-occurring terms; selecting, by a processor of the machine, at least one co-occurring term from the plurality of co-occurring terms based on the matching and based on a desirability score associated with the at least one co-occurring term; transmitting instructions to cause display, on the user interface, of the at least one co-occurring term and the associated desirability score; generating, using one or more processors, a suggestion of a modification to the title of the item being listed, the modification modifying the title by adding to the concept or removing from the concept a second word of the selected at least one co-occurring term, the suggestion of the modification including presenting the concept in conjunction with the second word of the selected at least one co-occurring term; and transmitting instructions to cause display, on the user interface, of the suggestion of the modification.

1. A computer-implemented method, comprising: generating, by a processor of a machine, a user interface for presentation on a user device, the user interface including perceptible user interface elements allowing a user to view title information; receiving a title of an item being listed; determining, by a processor of the machine, a concept, the concept including two or more terms in the title of the item being listed; accessing, from a networked database, a plurality of co-occurring terms stored in a co-occurring terms table, each co-occurring term in the co-occurring terms table including a first set of words and a second word, the first set of words and the second word corresponding to terms that have occurred together in stored search queries and to terms that have occurred together in stored item information corresponding to title information of items previously listed for sale on an online marketplace; generating, by a processor of the machine, a matching of the concept with one or more co-occurring terms of the plurality of co-occurring terms, the matching being based on the concept matching the first set of words of the one or more co-occurring terms; selecting, by a processor of the machine, at least one co-occurring term from the plurality of co-occurring terms based on the matching and based on a desirability score associated with the at least one co-occurring term; transmitting instructions to cause display, on the user interface, of the at least one co-occurring term and the associated desirability score; generating, using one or more processors, a suggestion of a modification to the title of the item being listed, the modification modifying the title by adding to the concept or removing from the concept a second word of the selected at least one co-occurring term, the suggestion of the modification including presenting the concept in conjunction with the second word of the selected at least one co-occurring term; and transmitting instructions to cause display, on the user interface, of the suggestion of the modification. 9. The method of claim 1 , further comprising: identifying the one of the co-occurring terms from among the plurality of co-occurring terms in the co-occurring terms table, based on a frequency of co-occurrence in the stored item information of the first set of words and the second word in the one of the plurality of co-occurring terms.

17. A computer-readable storage medium containing program code, comprising: (a) program code for receiving a search query; (b) program code for determining whether the search query has been previously received; (c) program code for if the search query has not been previously received, (i) receiving a new result set associated with the search query, (ii) storing the new result set associated with the search query in an offline-accessible data store, and (iii) outputting the new result set as a search result of the search query; (d) program code for if the search query has been previously received, (i) retrieving a previously stored result set associated with the search query from the offline-accessible data store, the previously stored result set comprising a plurality of categories each of which comprises one or more articles, (ii) determining whether at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, and (iii) responsive to a determination that the at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, outputting the at least one of the plurality of categories of the previously stored result set associated with the search query as a search result of the search query.

17. A computer-readable storage medium containing program code, comprising: (a) program code for receiving a search query; (b) program code for determining whether the search query has been previously received; (c) program code for if the search query has not been previously received, (i) receiving a new result set associated with the search query, (ii) storing the new result set associated with the search query in an offline-accessible data store, and (iii) outputting the new result set as a search result of the search query; (d) program code for if the search query has been previously received, (i) retrieving a previously stored result set associated with the search query from the offline-accessible data store, the previously stored result set comprising a plurality of categories each of which comprises one or more articles, (ii) determining whether at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, and (iii) responsive to a determination that the at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, outputting the at least one of the plurality of categories of the previously stored result set associated with the search query as a search result of the search query. 18. The computer-readable storage medium of claim 17 , wherein the program code for determining whether the search query has been previously received comprises program code for comparing the search query to a list of previously received search queries.

7. An information receiving apparatus, comprising: an m-bit data word input for an m-bit data word including an inversion signal and an n-bit data word; a determiner coupled to the m-bit data word input and comprising an information output for an information signal representing an information, the information signal depending on whether the number of 0s or 1s within bits of the m-bit data word is within a predetermined range; a data word output for an actually transmitted n-bit data word; a reconstructer being coupled to the m-bit data word input and comprising a reconstruction output coupled to the data word output so that the actually transmitted n-bit data word is inverted or non-inverted relative to the n-bit data word depending on the inversion signal; and a discarder coupled in series to the reconstructer, between the m-bit data word input and the reconstruction output, the discarder being coupled to the information output, to enable a passage from the input of the interface to the reconstruction output or prevent the passage, depending on the information.

7. An information receiving apparatus, comprising: an m-bit data word input for an m-bit data word including an inversion signal and an n-bit data word; a determiner coupled to the m-bit data word input and comprising an information output for an information signal representing an information, the information signal depending on whether the number of 0s or 1s within bits of the m-bit data word is within a predetermined range; a data word output for an actually transmitted n-bit data word; a reconstructer being coupled to the m-bit data word input and comprising a reconstruction output coupled to the data word output so that the actually transmitted n-bit data word is inverted or non-inverted relative to the n-bit data word depending on the inversion signal; and a discarder coupled in series to the reconstructer, between the m-bit data word input and the reconstruction output, the discarder being coupled to the information output, to enable a passage from the input of the interface to the reconstruction output or prevent the passage, depending on the information. 9. The information receiving apparatus according to claim 7 , wherein the information signal depends on whether the number of 0s or 1s within the m-bit data word is not below a predetermined limit.

1. A user interface apparatus for a computing system, said apparatus comprising: a display device displaying a graphical keyboard image; an input source comprising a designating device, said input source providing an input comprising key information and path information, said key information representing a key of said graphical keyboard image, said path information representing a series of points designated by said designating device, wherein said path information comprises a direction of displacement of said designating device; an output generator, responsive to said key information and said path information provided by said input source, for producing a keycode data defing an output character by applying a modifier corresponding to said path information to an input character corresponding to said key information, with said modifier being determined according to said direction of displacement; and a buffer, wherein said keycode data produced by said output generator is stored in said buffer.

1. A user interface apparatus for a computing system, said apparatus comprising: a display device displaying a graphical keyboard image; an input source comprising a designating device, said input source providing an input comprising key information and path information, said key information representing a key of said graphical keyboard image, said path information representing a series of points designated by said designating device, wherein said path information comprises a direction of displacement of said designating device; an output generator, responsive to said key information and said path information provided by said input source, for producing a keycode data defing an output character by applying a modifier corresponding to said path information to an input character corresponding to said key information, with said modifier being determined according to said direction of displacement; and a buffer, wherein said keycode data produced by said output generator is stored in said buffer. 11. The apparatus of claim 1 wherein said input source provides said key information according to one point of said series.

17. The computer-readable medium as in claim 11 , where the output array is formed by merging a result of semantic and syntactic validations to provide a merged result.

17. The computer-readable medium as in claim 11 , where the output array is formed by merging a result of semantic and syntactic validations to provide a merged result. 18. The computer-readable medium as in claim 17 , further comprising translating the merged result into a JSON document that expresses the array.

19. A computer program product with control instructions for implementing a computer-implemented method of automatically selecting and typing a subset of available family members for DNA profiling to a missing person to identify or exclude a typed unknown biological specimen for implementation on computer apparatus comprising a processor, an input device coupled to the processor, an output device coupled to the processor and a memory for storing profile data obtained from said typed unknown biological specimen coupled to the processor, the control instructions for the method comprising: (a) first computer instructions for storing relationships in said memory between said missing person and said available family members in a pedigree via said input device; (b) second computer instructions using the relative discriminating power of the pedigree with at least two combinations of said available family members to automatically select a combination of available family members for DNA typing; (c) third computer instructions for using a selected DNA typing technology for typing the automatically selected combination of available family members to obtain DNA profile data and storing said DNA profile data for said automatically selected combination in said memory; (d) fourth computer instructions using the pedigree and said stored DNA profile data of said automatically selected combination to calculate a likelihood function value using an adaptation of an Elston Stewart algorithm between the stored profile data obtained from said typed unknown biological specimen and said stored profile data for said automatically selected combination of available family members via said processor; and (e) fourth computer instructions outputting a decision whether said typed unknown biological specimen originates from said missing person and said pedigree or to exclude said typed unknown biological specimen as unrelated to the pedigree, the first through fourth computer instructions forming an instruction sequence.

19. A computer program product with control instructions for implementing a computer-implemented method of automatically selecting and typing a subset of available family members for DNA profiling to a missing person to identify or exclude a typed unknown biological specimen for implementation on computer apparatus comprising a processor, an input device coupled to the processor, an output device coupled to the processor and a memory for storing profile data obtained from said typed unknown biological specimen coupled to the processor, the control instructions for the method comprising: (a) first computer instructions for storing relationships in said memory between said missing person and said available family members in a pedigree via said input device; (b) second computer instructions using the relative discriminating power of the pedigree with at least two combinations of said available family members to automatically select a combination of available family members for DNA typing; (c) third computer instructions for using a selected DNA typing technology for typing the automatically selected combination of available family members to obtain DNA profile data and storing said DNA profile data for said automatically selected combination in said memory; (d) fourth computer instructions using the pedigree and said stored DNA profile data of said automatically selected combination to calculate a likelihood function value using an adaptation of an Elston Stewart algorithm between the stored profile data obtained from said typed unknown biological specimen and said stored profile data for said automatically selected combination of available family members via said processor; and (e) fourth computer instructions outputting a decision whether said typed unknown biological specimen originates from said missing person and said pedigree or to exclude said typed unknown biological specimen as unrelated to the pedigree, the first through fourth computer instructions forming an instruction sequence. 20. The computer program product of claim 19 wherein said DNA typing technology comprises STR DNA typing.

1. A method for generating an electronic form on a data processing device, comprising: receiving an input of a form descriptor code comprising a plurality of characters that represent components of an electronic form; comparing characters of the form descriptor code with stored mappings between characters and electronic form components, to determine required components of an electronic form; and generating an electronic form that comprises the determined required electronic form components, wherein the comparing and generating are performed by a processor of the data processing device.

1. A method for generating an electronic form on a data processing device, comprising: receiving an input of a form descriptor code comprising a plurality of characters that represent components of an electronic form; comparing characters of the form descriptor code with stored mappings between characters and electronic form components, to determine required components of an electronic form; and generating an electronic form that comprises the determined required electronic form components, wherein the comparing and generating are performed by a processor of the data processing device. 4. The method of claim 1 , further comprising comparing characters of the form descriptor code with stored mappings between characters and addressing information, for determining an address to transmit the generated electronic form to.

1. A contents management method for a media management apparatus, the method comprising: displaying at least one first graphical user interface object representing an external device connected to the media management apparatus and second graphical user interface objects representing contents stored in the connected external device; receiving a selection of a first or second graphical user interface object of the displayed first and second graphical user interface objects; detecting an input drag of the selected graphical user interface object; filtering, in response to detecting the input drag, the displayed first and second graphical user interface objects based on one or more attributes associated with the dragged graphical user interface object; and displaying, in response to filtering the displayed first and second graphical user interface objects, a filtered set of graphical user interface objects, wherein displaying the filtered set of graphical user interface objects comprises: detecting a drag of a search object comprising a keyword to an area where the first and second graphical user interface objects are displayed; checking metadata associated with the first and second graphical user interface objects displayed in proximity to the search object; and sticking, to the search object, graphical user interface objects comprising metadata comprising the keyword.

1. A contents management method for a media management apparatus, the method comprising: displaying at least one first graphical user interface object representing an external device connected to the media management apparatus and second graphical user interface objects representing contents stored in the connected external device; receiving a selection of a first or second graphical user interface object of the displayed first and second graphical user interface objects; detecting an input drag of the selected graphical user interface object; filtering, in response to detecting the input drag, the displayed first and second graphical user interface objects based on one or more attributes associated with the dragged graphical user interface object; and displaying, in response to filtering the displayed first and second graphical user interface objects, a filtered set of graphical user interface objects, wherein displaying the filtered set of graphical user interface objects comprises: detecting a drag of a search object comprising a keyword to an area where the first and second graphical user interface objects are displayed; checking metadata associated with the first and second graphical user interface objects displayed in proximity to the search object; and sticking, to the search object, graphical user interface objects comprising metadata comprising the keyword. 7. The contents management method of claim 1 , further comprising: detecting a wag of the search object; and separating, in response to detecting the wag of the search object, at least one of the stuck graphical user interface objects representing content of relatively lower priority among the graphical user interface objects stuck to the search object.

11. The system of claim 9 , wherein the first network protocol is one of Common Industrial Protocol (CIP), Fieldbus, Profibus, Hart, Modbus, ASI-bus, or Foundation Fieldbus.

11. The system of claim 9 , wherein the first network protocol is one of Common Industrial Protocol (CIP), Fieldbus, Profibus, Hart, Modbus, ASI-bus, or Foundation Fieldbus. 12. The system of claim 11 , wherein the second network protocol is at least one of Common Industrial Protocol (CIP), Fieldbus, Profibus, Hart, Modbus, ASI-bus, or Foundation Fieldbus.

1. A computer-implemented method executed by a processor that performs operations for reducing ambiguities present in electronically stored words, the operations comprising: receiving a plurality of characters in electronic form, the received plurality of characters corresponding to a sequence of words and including an ambiguous word that has one or more characters whose value is substantially uncertain; comparing at least some of the words in the sequence to a first ontology, the first ontology defining a plurality of nodes, each node being associated with a word, and each node being connected to at least one other node by a link, each link being associated with a concept that relates the words associated with the nodes connected by the link in a predetermined context, wherein at least some of the nodes are associated with non-textual image information that identifies an enhancement to character-based text.

1. A computer-implemented method executed by a processor that performs operations for reducing ambiguities present in electronically stored words, the operations comprising: receiving a plurality of characters in electronic form, the received plurality of characters corresponding to a sequence of words and including an ambiguous word that has one or more characters whose value is substantially uncertain; comparing at least some of the words in the sequence to a first ontology, the first ontology defining a plurality of nodes, each node being associated with a word, and each node being connected to at least one other node by a link, each link being associated with a concept that relates the words associated with the nodes connected by the link in a predetermined context, wherein at least some of the nodes are associated with non-textual image information that identifies an enhancement to character-based text. 8. The method of claim 1 , wherein the plurality of characters is received from an optical character recognition (OCR) device configured to convert written character image information to character information in electronic form.

8. The method of claim 1 , wherein said complex type is an opaque type.

8. The method of claim 1 , wherein said complex type is an opaque type. 9. The method of claim 8 , wherein: converting said instance of said complex type includes invoking a user registered function registered to convert instances of said complex type to logical representations of said instances; and converting said logical representation to said second storage format includes invoking a user registered function registered to convert logical representations of instances of said complex type to said second storage format.

2. The method of claim 1 , wherein the first preset rule includes: returning a corresponding result and using the corresponding result as a first partial regular expression when the first character string satisfies a second preset rule.

2. The method of claim 1 , wherein the first preset rule includes: returning a corresponding result and using the corresponding result as a first partial regular expression when the first character string satisfies a second preset rule. 4. The method of claim 2 , wherein the second preset rule includes: returning a first preset identifier when the first character string is not empty, the first character string is composed of numbers, and the first character of the to-be-collected character string is not a number.

1. A method of enhancing service diagnostics for root cause analysis of an identified problem in a vehicle by generating a functional taxonomy database that is utilized in cooperation with a structural taxonomy database, the structural taxonomy database identifying structural relationships between parts of a vehicle, and the functional taxonomy database identifying functional relationships between parts of the vehicle, the method comprising the steps of: obtaining service data of previously serviced vehicles from a memory storage device, the service data identifying parts serviced on the vehicles during a respective service repair; compiling the service data based on a history of service repairs for each vehicle; identifying each vehicle within the compiled service data having at least two service repairs performed within a predetermined period of time; identifying combinations of parts serviced for each vehicle; determining a count indicating a number of times each combination appears in the compiled service data for the identified vehicles having at least two service repairs; identifying the combinations having counts greater than a predetermined threshold; determining whether any of the combinations having counts greater than the predetermined threshold are present in the structural taxonomy database; selecting only the combinations that are not present in the structural taxonomy database and have counts greater than the predetermined threshold; and updating a functional taxonomy database by assigning the selected combinations to the function taxonomy database, wherein the functional taxonomy database and the structural taxonomy database are made available to a service technician via a computer to assist the service technician in diagnosing the root cause.

1. A method of enhancing service diagnostics for root cause analysis of an identified problem in a vehicle by generating a functional taxonomy database that is utilized in cooperation with a structural taxonomy database, the structural taxonomy database identifying structural relationships between parts of a vehicle, and the functional taxonomy database identifying functional relationships between parts of the vehicle, the method comprising the steps of: obtaining service data of previously serviced vehicles from a memory storage device, the service data identifying parts serviced on the vehicles during a respective service repair; compiling the service data based on a history of service repairs for each vehicle; identifying each vehicle within the compiled service data having at least two service repairs performed within a predetermined period of time; identifying combinations of parts serviced for each vehicle; determining a count indicating a number of times each combination appears in the compiled service data for the identified vehicles having at least two service repairs; identifying the combinations having counts greater than a predetermined threshold; determining whether any of the combinations having counts greater than the predetermined threshold are present in the structural taxonomy database; selecting only the combinations that are not present in the structural taxonomy database and have counts greater than the predetermined threshold; and updating a functional taxonomy database by assigning the selected combinations to the function taxonomy database, wherein the functional taxonomy database and the structural taxonomy database are made available to a service technician via a computer to assist the service technician in diagnosing the root cause. 10. The method of claim 1 wherein an identified combination is based on specific repair sequence in replacing the parts.

16. The method of claim 9 , wherein the user gaze information comprises a gaze duration.

16. The method of claim 9 , wherein the user gaze information comprises a gaze duration. 17. The method of claim 16 , further comprising: providing an alert if the gaze duration exceeds a predefined threshold.

1. An integrated circuit chip comprising programmable intelligent search memory for content search wherein said programmable intelligent search memory performs regular expression based search and wherein said regular expression comprises an interval symbol, said interval symbol comprises a symbol and further comprising a) a lower limit; b) an upper limit; or c) a combination thereof; the programmable intelligent search memory using one or more regular expressions, said one or more regular expressions comprising one or more symbols or characters, said one or more regular expressions further comprising one or more of said interval symbols, said one or more regular expressions converted into one or more finite state automata representing the functionality of said one or more regular expressions for programming in said programmable intelligent search memory, said one or more finite state automata comprising a plurality of states, said plurality of states derived from said one or more symbols or characters or said one or more interval symbols of said one or more regular expressions, said content comprising one or more input symbols provided as input to said programmable intelligent search memory, said programmable intelligent search memory comprising at least one of each of: a. a symbol memory circuit to store said one or more symbols; b. an interval symbol memory circuit to store said one or more interval symbols; c. an interval symbol evaluation circuit coupled to said interval symbol memory circuit to evaluate a match of said one or more interval symbols stored in said interval symbol memory circuit with said one or more symbols of said content; d. a symbol evaluation circuit coupled to said symbol memory circuit to evaluate a match of said one or more symbols stored in said symbol memory circuit with said one or more symbols of said content; e. a state dependent vector (SDV) memory circuit to store state transition controls for said one or more finite state automata; f. a current state vector memory (CSV) circuit to store said plurality of states; and g. a state transition circuit coupled to said symbol evaluation circuit, said interval symbol evaluation circuit, said current state vector memory circuit and said state dependent vector memory circuit to perform state transition from one or more first states to one or more second states of said plurality of states of said one or more finite state automata.

1. An integrated circuit chip comprising programmable intelligent search memory for content search wherein said programmable intelligent search memory performs regular expression based search and wherein said regular expression comprises an interval symbol, said interval symbol comprises a symbol and further comprising a) a lower limit; b) an upper limit; or c) a combination thereof; the programmable intelligent search memory using one or more regular expressions, said one or more regular expressions comprising one or more symbols or characters, said one or more regular expressions further comprising one or more of said interval symbols, said one or more regular expressions converted into one or more finite state automata representing the functionality of said one or more regular expressions for programming in said programmable intelligent search memory, said one or more finite state automata comprising a plurality of states, said plurality of states derived from said one or more symbols or characters or said one or more interval symbols of said one or more regular expressions, said content comprising one or more input symbols provided as input to said programmable intelligent search memory, said programmable intelligent search memory comprising at least one of each of: a. a symbol memory circuit to store said one or more symbols; b. an interval symbol memory circuit to store said one or more interval symbols; c. an interval symbol evaluation circuit coupled to said interval symbol memory circuit to evaluate a match of said one or more interval symbols stored in said interval symbol memory circuit with said one or more symbols of said content; d. a symbol evaluation circuit coupled to said symbol memory circuit to evaluate a match of said one or more symbols stored in said symbol memory circuit with said one or more symbols of said content; e. a state dependent vector (SDV) memory circuit to store state transition controls for said one or more finite state automata; f. a current state vector memory (CSV) circuit to store said plurality of states; and g. a state transition circuit coupled to said symbol evaluation circuit, said interval symbol evaluation circuit, said current state vector memory circuit and said state dependent vector memory circuit to perform state transition from one or more first states to one or more second states of said plurality of states of said one or more finite state automata. 9. The integrated circuit chip of claim 1 , wherein one or more finite state automata further comprise said one or more states wherein each state of said one or more states is entered from a set of said one or more states coupled to said each state using the same symbol of said content being searched.

11. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory; the memory having stored therein a number of linguistic elements, an alphabet, and a number of objects; at least some of the linguistic elements each being in the alphabet; the number of objects comprising a number of language objects; the language objects each comprising a number of the linguistic elements in the alphabet; the input apparatus including a plurality of input members; at least some of the input members each having a number of the linguistic elements assigned thereto, at least some of the linguistic elements assigned to the at least some of the input members being inactive while others of the linguistic elements assigned to the at least some of the input members being active, the alphabet including only the active linguistic elements; and the alphabet being expandable to have added thereto a number of additional linguistic elements upon entry of a new language object having at least a first linguistic element not already in the alphabet.

11. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory; the memory having stored therein a number of linguistic elements, an alphabet, and a number of objects; at least some of the linguistic elements each being in the alphabet; the number of objects comprising a number of language objects; the language objects each comprising a number of the linguistic elements in the alphabet; the input apparatus including a plurality of input members; at least some of the input members each having a number of the linguistic elements assigned thereto, at least some of the linguistic elements assigned to the at least some of the input members being inactive while others of the linguistic elements assigned to the at least some of the input members being active, the alphabet including only the active linguistic elements; and the alphabet being expandable to have added thereto a number of additional linguistic elements upon entry of a new language object having at least a first linguistic element not already in the alphabet. 15. The handheld electronic device of claim 11 wherein the alphabet comprises a static portion and a modifiable portion, the at least a first new linguistic element being added to the modifiable portion of the alphabet.

9. The method of claim 1 , wherein there are multiple different types of edges.

9. The method of claim 1 , wherein there are multiple different types of edges. 12. The method of claim 9 , wherein the multiple different types of edges comprise a mixed edge type that defines a logical dependency between nodes and an ordered or hierarchical dependency between nodes.

5. The method according to claim 1 wherein said determining step further includes the step of consulting an optimized list of file formats from which to perform said translation of said stored data file to the requested file format.

5. The method according to claim 1 wherein said determining step further includes the step of consulting an optimized list of file formats from which to perform said translation of said stored data file to the requested file format. 6. The method according to claim 5 wherein said list is indexed by said requested file format.

10. On a computing device, a method for recognizing speech of a user, comprising: receiving depth information of a physical space from a depth camera; identifying one or more gestures performed by the user based on the depth information; receiving audio information from one or more microphones; determining a speech input from the audio input; if the speech input comprises an ambiguous term, then utilizing one or more of the one or more gestures and social network information obtained from a remote service to identify an unambiguous term corresponding to the ambiguous term, the social network information including contacts from a social network, and wherein identifying the unambiguous term comprises identifying another user from the social network information; and after identifying the unambiguous term, taking an action on the computing device based on the speech input and the unambiguous term.

10. On a computing device, a method for recognizing speech of a user, comprising: receiving depth information of a physical space from a depth camera; identifying one or more gestures performed by the user based on the depth information; receiving audio information from one or more microphones; determining a speech input from the audio input; if the speech input comprises an ambiguous term, then utilizing one or more of the one or more gestures and social network information obtained from a remote service to identify an unambiguous term corresponding to the ambiguous term, the social network information including contacts from a social network, and wherein identifying the unambiguous term comprises identifying another user from the social network information; and after identifying the unambiguous term, taking an action on the computing device based on the speech input and the unambiguous term. 16. The method of claim 10 , further comprising additionally utilizing digital content consumption information of the user to disambiguate the speech input.

8. A method comprising: recognizing, by use of a processor, two or more logogram radicals; and generating one or more logogram phrases for the two or more logogram radicals, wherein each logogram phrase comprises a first logogram embodying a first logogram radical of the two or more logogram radicals and a second logogram embodying a second logogram radical of the two or more logogram radicals.

8. A method comprising: recognizing, by use of a processor, two or more logogram radicals; and generating one or more logogram phrases for the two or more logogram radicals, wherein each logogram phrase comprises a first logogram embodying a first logogram radical of the two or more logogram radicals and a second logogram embodying a second logogram radical of the two or more logogram radicals. 9. The method of claim 8 , wherein the one or more logogram phrases are generated in response to a usage history.

5. The system of claim 4 wherein the received query includes a where clause comprising the predicates.

5. The system of claim 4 wherein the received query includes a where clause comprising the predicates. 6. The system of claim 5 wherein the received query comprises an order clause comprising a sort criteria, wherein the query executor further sorts the stream of tuples according to the sort criteria.

4. The method of claim 1 , wherein determining that at least a portion of the input audio matches a recognition grammar comprises determining that the at least a portion of the input audio matches a voice command.

4. The method of claim 1 , wherein determining that at least a portion of the input audio matches a recognition grammar comprises determining that the at least a portion of the input audio matches a voice command. 5. The method of claim 4 , wherein the voice command relates to performing a web-based search and wherein the recognition grammar is a search grammar that includes at least one generic speech node corresponding to web-search parameters.

1. A method for integrating a service into an application, the method comprising: receiving an application extensibility description for an application, the application extensibility description including a set of application extension points; receiving a service description for a service, the service description including a set of service elements; receiving a specification of an integration design comprising a plurality of atomic adaptation patterns to link particular service elements in the service description to particular application extension points in the application extensibility description, wherein the plurality of atomic adaptation patterns define a plurality of steps for integrating the service into a plurality of application layers of the application, the application layers comprising a presentation layer, a business process layer, a service layer, and a configuration layer, and wherein each atomic adaptation pattern comprises one or more ports coupled to particular service elements in the service description and one or more ports coupled to particular application extension points in the application extensibility description; generating, by a computing device, an integration description based on the integration design, wherein the integration description is used to execute integration of the application with the service; generating a query for a recommendation for connecting an application extension point in the application extensibility description to a service element in the service description based on a context, the context being a state of the adaption/extension of the service into the application; searching a semantic model to determine a search result indicating a recommended connection of an application extension point in the application extensibility description to a service element in the service description based on the query; and changing the integration design based on the recommended connection.

1. A method for integrating a service into an application, the method comprising: receiving an application extensibility description for an application, the application extensibility description including a set of application extension points; receiving a service description for a service, the service description including a set of service elements; receiving a specification of an integration design comprising a plurality of atomic adaptation patterns to link particular service elements in the service description to particular application extension points in the application extensibility description, wherein the plurality of atomic adaptation patterns define a plurality of steps for integrating the service into a plurality of application layers of the application, the application layers comprising a presentation layer, a business process layer, a service layer, and a configuration layer, and wherein each atomic adaptation pattern comprises one or more ports coupled to particular service elements in the service description and one or more ports coupled to particular application extension points in the application extensibility description; generating, by a computing device, an integration description based on the integration design, wherein the integration description is used to execute integration of the application with the service; generating a query for a recommendation for connecting an application extension point in the application extensibility description to a service element in the service description based on a context, the context being a state of the adaption/extension of the service into the application; searching a semantic model to determine a search result indicating a recommended connection of an application extension point in the application extensibility description to a service element in the service description based on the query; and changing the integration design based on the recommended connection. 7. The method of claim 1 , further comprising: parsing the integration description to determine parameterized information, the parameterized information generated based on the integration design being connected to the first port and the service element being connected to the second port; and adapting the application to extend it to use the service based on the parameterized information.

12. A system comprising: one or more computer processors; one or more computer-readable storage memories embodying processor-executable instructions which, responsive to execution by the one or more computer processors, are configured to: receive, from a gaming platform, data representing a first paralinguistic indicator, the first paralinguistic indicator represented in a first data format associated with the gaming platform; translate the first paralinguistic indicator to a second data format associated with a real time messaging platform; send the translated first paralinguistic indicator to the real time messaging platform; receive, from the real time messaging platform, data representing a second paralinguistic indicator, the second paralinguistic indicator represented in the second data format associated with the real time messaging platform; translate the second paralinguistic indicator to the first data format associated with the gaming platform; and send the translated second paralinguistic indicator to the gaming platform, wherein the gaming platform is a virtual world platform and the real time messaging platform is an instant messaging platform.

12. A system comprising: one or more computer processors; one or more computer-readable storage memories embodying processor-executable instructions which, responsive to execution by the one or more computer processors, are configured to: receive, from a gaming platform, data representing a first paralinguistic indicator, the first paralinguistic indicator represented in a first data format associated with the gaming platform; translate the first paralinguistic indicator to a second data format associated with a real time messaging platform; send the translated first paralinguistic indicator to the real time messaging platform; receive, from the real time messaging platform, data representing a second paralinguistic indicator, the second paralinguistic indicator represented in the second data format associated with the real time messaging platform; translate the second paralinguistic indicator to the first data format associated with the gaming platform; and send the translated second paralinguistic indicator to the gaming platform, wherein the gaming platform is a virtual world platform and the real time messaging platform is an instant messaging platform. 13. The system of claim 12 , wherein the data representing the first paralinguistic indicator or the data representing the second paralinguistic indicator comprises eXtensible Markup Language (XML) data.

11. A computer-readable storage device comprising computer-executable instructions that, when executed by a processor, cause the processor to perform acts comprising: defining in processor-readable memory a factor graph including a factor graph model replicated for each variable node of a set of variable nodes, each variable node being informed by one or more factors in the factor graph model, each factor being implemented as a regression tree; and training structure and parameterization of regression trees of the factor graph using an objective function and training data having a plurality of datasets, each dataset having elements of at least one labeled property, wherein the training determines parameters of energy functions for leaf nodes of the regression trees.

11. A computer-readable storage device comprising computer-executable instructions that, when executed by a processor, cause the processor to perform acts comprising: defining in processor-readable memory a factor graph including a factor graph model replicated for each variable node of a set of variable nodes, each variable node being informed by one or more factors in the factor graph model, each factor being implemented as a regression tree; and training structure and parameterization of regression trees of the factor graph using an objective function and training data having a plurality of datasets, each dataset having elements of at least one labeled property, wherein the training determines parameters of energy functions for leaf nodes of the regression trees. 13. The computer-readable storage device of claim 11 , wherein the computer-executable instructions, when executed by the processor, further cause the processor to perform acts comprising: executing the factor graph on a dataset having elements of at least one unlabeled property to determine a label for the at least one unlabeled property for each element.

11. The system of claim 10 , is further configured to obtain and store GPS coordinates, the GPS coordinates being stored at least within the draft blog entry; and generate a blogging tour map based on the GPS coordinates within the draft blog entry, the blogging tour map comprising a plurality of nodes, each node representing an automatically generated blog entry, and where each node is situated on at a location on the blogging tour mapbased on the GPS coordinates.

11. The system of claim 10 , is further configured to obtain and store GPS coordinates, the GPS coordinates being stored at least within the draft blog entry; and generate a blogging tour map based on the GPS coordinates within the draft blog entry, the blogging tour map comprising a plurality of nodes, each node representing an automatically generated blog entry, and where each node is situated on at a location on the blogging tour mapbased on the GPS coordinates. 13. The system of claim 11 , further comprising: browsing a webpage having a Uniform Resource Locator (URL) on the wireless mobile device, and automatically inserting the URL into the draft blog entry in the predetermined format.

8. A method comprising: (a) recognizing utterances of a speaker through converting the utterances into a recognized string, the utterances being received by a speaker input and converted to digital signals; (b) comparing the recognized string with a reference string to determine errors; (c) calculating estimated weights for sections of the utterances; (d) marking the errors in the utterances and providing corresponding estimated weights to form adaptation enrollment data; and (e) using the adaptation enrollment data to convert a speaker independent model to a speaker dependent model; wherein calculating the estimated weights comprises computing an average likelihood difference per frame and then computing a weight value by averaging the average likelihood difference over all error words.

8. A method comprising: (a) recognizing utterances of a speaker through converting the utterances into a recognized string, the utterances being received by a speaker input and converted to digital signals; (b) comparing the recognized string with a reference string to determine errors; (c) calculating estimated weights for sections of the utterances; (d) marking the errors in the utterances and providing corresponding estimated weights to form adaptation enrollment data; and (e) using the adaptation enrollment data to convert a speaker independent model to a speaker dependent model; wherein calculating the estimated weights comprises computing an average likelihood difference per frame and then computing a weight value by averaging the average likelihood difference over all error words. 13. The method of claim 8 wherein calculating the estimated weights further comprises: running a force alignment program on the reference string to obtain statistics of references; decoding the utterances to obtain statistics of 1-best hypothesis; and aligning the 1-best hypothesis with the reference string to obtain the error words.

12. A method for using turns to analyze human speech, comprising: providing a computer with a memory, providing a microphone operably connected to said computer, providing a data stream record operable within said memory, providing an archival database operable within said memory, providing software program operable in said computer, said software program being arranged to analyze turns and turn content received by said microphone, said software program being arranged to analyze said turn content by recognizing and tabulating turns as a pause, in-breath, vowel extension, sentence intonation, question intonation, or word, and to attribute said turn to an individual speaker, storing all of said turns in said archival database, and tabulating, categorizing, and storing said turns in said data stream record for retrieval, whereby said data stream record contains a retrievable record of turns uttered by said human speaker.

12. A method for using turns to analyze human speech, comprising: providing a computer with a memory, providing a microphone operably connected to said computer, providing a data stream record operable within said memory, providing an archival database operable within said memory, providing software program operable in said computer, said software program being arranged to analyze turns and turn content received by said microphone, said software program being arranged to analyze said turn content by recognizing and tabulating turns as a pause, in-breath, vowel extension, sentence intonation, question intonation, or word, and to attribute said turn to an individual speaker, storing all of said turns in said archival database, and tabulating, categorizing, and storing said turns in said data stream record for retrieval, whereby said data stream record contains a retrievable record of turns uttered by said human speaker. 20. The method of claim 12 wherein said method for using turns to analyze human speech is used in forensics by: (a) recording a first person's speech, (b) analyzing said first person's speech using said software program and storing said first person's speech in said first person's data stream record, (c) recording a second person's speech, (d) analyzing said second person's speech using said software program and storing said second person's speech in said second person's data stream record, and (e) comparing said first person's data stream record with said second person's data stream record in order to determine whether or not said first person is the same as said second person even though said first person's data stream and said second person's data stream are not identical in wording.

15. Computer-readable storage media for identifying a translated text string, the computer-readable storage media having computer-executable instructions embodied thereon, wherein, when executed by at least one processor, the computer-executable instructions cause the processor to: receive, from a developer computing device, an application identifier associated with a computer application and a plurality of input text strings from the computer application; convert the plurality of input text strings into a plurality of input text tokens; store a setup profile including the application identifier and the plurality of input text tokens; receive a locale request, from a user computing device, including the application identifier and a locale identifier, the locale identifier identifying a language of use for the computer application; identify a matching entry included within a localization table for each of the plurality of input text tokens, wherein each matching entry includes a stored text token matching the respective input text token, a stored locale identifier matching the locale identifier, and an associated translated text string; generate a configuration file including the application identifier, the matched locale identifier, and the associated translated text strings for each of the plurality of input text tokens; and transmit the configuration file to the user computing device.

15. Computer-readable storage media for identifying a translated text string, the computer-readable storage media having computer-executable instructions embodied thereon, wherein, when executed by at least one processor, the computer-executable instructions cause the processor to: receive, from a developer computing device, an application identifier associated with a computer application and a plurality of input text strings from the computer application; convert the plurality of input text strings into a plurality of input text tokens; store a setup profile including the application identifier and the plurality of input text tokens; receive a locale request, from a user computing device, including the application identifier and a locale identifier, the locale identifier identifying a language of use for the computer application; identify a matching entry included within a localization table for each of the plurality of input text tokens, wherein each matching entry includes a stored text token matching the respective input text token, a stored locale identifier matching the locale identifier, and an associated translated text string; generate a configuration file including the application identifier, the matched locale identifier, and the associated translated text strings for each of the plurality of input text tokens; and transmit the configuration file to the user computing device. 20. The computer-readable storage media of claim 15 , wherein the plurality of input text strings includes at least one of a measurement text string and a currency text string, and the computer-executable instructions further cause the processor to: translate at least one of the measurement text string and the currency text string, based on the identified matching entry for each of the input text tokens.

14. A software shell as claimed in claim 2 wherein the activation/agenda manager module includes a mechanism for interrupting execution of a knowledge source and executing a higher priority knowledge source in accordance with the knowledge source priority scheme.

14. A software shell as claimed in claim 2 wherein the activation/agenda manager module includes a mechanism for interrupting execution of a knowledge source and executing a higher priority knowledge source in accordance with the knowledge source priority scheme. 15. A software shell as claimed in claim 14 wherein the activation/agenda manager module includes a mechanism for determining whether an interrupted knowledge source should be rescheduled for execution.

18. A computer for interacting with a user, the computer having access to an electronic knowledge database and structured and programmed to, automatically: (a) generate a structured representation of a received user input; (b) compare the structured representation of the received user input with a plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user input, cause the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; further, the computer is structured and programmed to: (i) when a match is identified in part (c), generate a second structural representation of a second received user input; and (ii) compare the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective actions fields specifying at least one action; (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, cause the at least one action specified by the action field associated with the matching one of the second plurality of expected user statement fields to be performed.

18. A computer for interacting with a user, the computer having access to an electronic knowledge database and structured and programmed to, automatically: (a) generate a structured representation of a received user input; (b) compare the structured representation of the received user input with a plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user input, cause the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; further, the computer is structured and programmed to: (i) when a match is identified in part (c), generate a second structural representation of a second received user input; and (ii) compare the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective actions fields specifying at least one action; (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, cause the at least one action specified by the action field associated with the matching one of the second plurality of expected user statement fields to be performed. 21. The computer of claim 18 wherein, further, the computer is structured and programmed to: (i) present to the user for review a list of previously received user textual inputs and corresponding responses previously sent by the computer; (ii) thereafter, receiving at least one of the previously received user inputs that has been altered by the user; and (iii) in response, provide an updated response.

1. A method of associating a context hashtag with information content that is stored in an electronically searchable format in a computer network, the method comprising: displaying to a user, via an editor in execution on a user system, information content to be associated with a context hashtag; receiving an indication from the user, via the user system, the indication for selecting the context hashtag to be associated with the displayed information content, the selected context hashtag having associated therewith at least a tag name, context information that is other than only the tag name, and creator-specific information that identifies uniquely a single entity, and wherein the context hashtag is uniquely identifiable based on a combination of the creator-specific information and at least one of the tag name and the context information; in response to receiving the indication from the user, inserting computer readable instruction code into the displayed information content, the computer readable instruction code for generating a graphical representation of the context hashtag based on data retrieved from a context hashtag record stored in a database; and storing the selected information content, including the inserted computer readable instruction code, in the computer network.

1. A method of associating a context hashtag with information content that is stored in an electronically searchable format in a computer network, the method comprising: displaying to a user, via an editor in execution on a user system, information content to be associated with a context hashtag; receiving an indication from the user, via the user system, the indication for selecting the context hashtag to be associated with the displayed information content, the selected context hashtag having associated therewith at least a tag name, context information that is other than only the tag name, and creator-specific information that identifies uniquely a single entity, and wherein the context hashtag is uniquely identifiable based on a combination of the creator-specific information and at least one of the tag name and the context information; in response to receiving the indication from the user, inserting computer readable instruction code into the displayed information content, the computer readable instruction code for generating a graphical representation of the context hashtag based on data retrieved from a context hashtag record stored in a database; and storing the selected information content, including the inserted computer readable instruction code, in the computer network. 2. The method of claim 1 , wherein the single entity is selected from the group consisting of: an individual, a group of individuals, a company, an institution and an association.

15. The method according to claim 1 , wherein the modifying further comprises filtering at least one element of the at least one result set.

15. The method according to claim 1 , wherein the modifying further comprises filtering at least one element of the at least one result set. 17. The method according to claim 15 , wherein the filtering further identifies a value of the at least one element against at least one other element of the result set.

1. A computer-implemented information retrieval system comprising: a query component configured to receive and process a query to retrieve a document having different language styles as data streams, the data streams including at least a first stream for a first portion of the document and a second stream for a second portion of the document, wherein the second stream is different from the first stream and the second portion is different from the first portion; a model component configured to create multiple language models for the data streams of the document, the multiple language models characterizing the data streams for document ranking, the multiple language models comprising at least a first language model for the first portion of the document and a second language model for the second portion of the document, wherein the second language model is different from the first language model; an estimation component configured to estimate mixture weights for the multiple language models; a smoothing component configured to apply smoothing to the multiple language models to generate similar cardinality among the multiple language models for linearly combining scores output by the multiple language models; and a processor configured to execute the query component, the model component, the estimation component, and the smoothing component.

1. A computer-implemented information retrieval system comprising: a query component configured to receive and process a query to retrieve a document having different language styles as data streams, the data streams including at least a first stream for a first portion of the document and a second stream for a second portion of the document, wherein the second stream is different from the first stream and the second portion is different from the first portion; a model component configured to create multiple language models for the data streams of the document, the multiple language models characterizing the data streams for document ranking, the multiple language models comprising at least a first language model for the first portion of the document and a second language model for the second portion of the document, wherein the second language model is different from the first language model; an estimation component configured to estimate mixture weights for the multiple language models; a smoothing component configured to apply smoothing to the multiple language models to generate similar cardinality among the multiple language models for linearly combining scores output by the multiple language models; and a processor configured to execute the query component, the model component, the estimation component, and the smoothing component. 2. The system of claim 1 , wherein the mixture weights are computed as a measure of adaptability that the document matches language expressed in the query.

1. A method comprising: for each known text sample of a plurality of known text samples, each known text sample having a text type, generating, by a processor, an image of the known text sample; for each optical character recognition (OCR) engine of a plurality of OCR engines, inputting the image of the known text sample, by the processor, into the OCR engine; receiving output text corresponding to the image of the known text sample, by the processor, from the OCR engine; and, comparing the output text received from the OCR engine with the known text sample, by the processor, to determine a confidence value of the OCR engine for the text type of the known text sample, wherein for each OCR engine of one or more of the OCR engines, periodically redetermining the confidence values of the OCR engine.

1. A method comprising: for each known text sample of a plurality of known text samples, each known text sample having a text type, generating, by a processor, an image of the known text sample; for each optical character recognition (OCR) engine of a plurality of OCR engines, inputting the image of the known text sample, by the processor, into the OCR engine; receiving output text corresponding to the image of the known text sample, by the processor, from the OCR engine; and, comparing the output text received from the OCR engine with the known text sample, by the processor, to determine a confidence value of the OCR engine for the text type of the known text sample, wherein for each OCR engine of one or more of the OCR engines, periodically redetermining the confidence values of the OCR engine. 7. The method of claim 1 , wherein comparing the output text received from the OCR engine with the known text sample to determine the confidence value of the OCR engine for the text type of the known text sample comprises: for each word of a plurality of words of the output text, comparing the word with a corresponding word of the known text sample to determine whether the word of the output text is identical to the corresponding word of the known text sample; where the word of the output text is identical to the corresponding word of the known text sample, incrementing a score by a number of characters within the word of the output text; dividing the score by a total number of characters within the words of the output text, to yield the confidence value of the OCR engine for the text type of the known text sample.

11. The system of claim 8 wherein the specification comprises an XML Document Type Definition that describes element names and XML syntax rules for creating a description of the document.

11. The system of claim 8 wherein the specification comprises an XML Document Type Definition that describes element names and XML syntax rules for creating a description of the document. 12. The system of claim 11 wherein the description comprises a well-formed XML document file generated responsive to the XML Document Type Definition.

1. A method for presenting a written work, the method comprising: recognizing within a written work one more character identity attributes; comparing the one or more character identity attributes with one or more character identities; selecting one of the one or more character identities based on the comparing, the selected character identity including a voice that corresponds to the one or more character identity attributes; identifying one or more portions of the written work associated with the character identity; associating the voice of the selected character identity with the identified portions to define one or more voice-portion associations; storing the voice-portion associations in a storage device; and providing the voice-portion associations from the storage device to a user computing device for presentation of the identified portions using the voice of the selected character identity.

1. A method for presenting a written work, the method comprising: recognizing within a written work one more character identity attributes; comparing the one or more character identity attributes with one or more character identities; selecting one of the one or more character identities based on the comparing, the selected character identity including a voice that corresponds to the one or more character identity attributes; identifying one or more portions of the written work associated with the character identity; associating the voice of the selected character identity with the identified portions to define one or more voice-portion associations; storing the voice-portion associations in a storage device; and providing the voice-portion associations from the storage device to a user computing device for presentation of the identified portions using the voice of the selected character identity. 4. The method of claim 1 , wherein recognizing the one or more character identity attributes comprises recognizing a gender for the character identity.

1. A speech recognition method implemented in a computer, comprising: receiving a speech input in a first noise environment which comprises a sequence of observations; determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, comprising: providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognise speech in a second noise environment, said model having a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation; adapting the model trained in the second environment to that of the first environment; the speech recognition method further comprising determining the likelihood of a sequence of observations occurring in a given language using a language model; combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein adapting the model trained in the second environment to that of the first environment comprises: adapting the model parameters of the model trained in the second noise environment to those of the first noise environment using transform parameters to produce a target distribution, wherein the transform parameters have a block diagonal form and are regression class dependent, each regression class comprising a plurality of probability distributions; mimicking the target distribution using a linear regression type distribution, said linear regression type distribution comprising mimicked transform parameters; and estimating the mimicked transformed parameters.

1. A speech recognition method implemented in a computer, comprising: receiving a speech input in a first noise environment which comprises a sequence of observations; determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, comprising: providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognise speech in a second noise environment, said model having a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation; adapting the model trained in the second environment to that of the first environment; the speech recognition method further comprising determining the likelihood of a sequence of observations occurring in a given language using a language model; combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein adapting the model trained in the second environment to that of the first environment comprises: adapting the model parameters of the model trained in the second noise environment to those of the first noise environment using transform parameters to produce a target distribution, wherein the transform parameters have a block diagonal form and are regression class dependent, each regression class comprising a plurality of probability distributions; mimicking the target distribution using a linear regression type distribution, said linear regression type distribution comprising mimicked transform parameters; and estimating the mimicked transformed parameters. 19. A non-transient carrier medium carrying computer readable instructions for controlling the computer to carry out the method of claim 1 .

17. A method comprising: engaging in a speech dialog with a user to determine an intent of the user, wherein engaging in the speech dialog comprises engaging in a first dialog turn, a second dialog turn, and a third dialog turn with the user wherein engaging in the first dialog turn comprises: receiving a first audio signal produced by a first device, the first audio signal representing first user speech; and determining, based at least in part on providing the first audio signal to a speech service, a first meaning of the first user speech; wherein engaging in the second dialog turn comprises: receiving a second audio signal produced using a microphone of a second device, the second audio signal representing second user speech; determining, based at least in part on providing the second audio signal to the speech service, a second meaning of the second user speech; and wherein engaging in the third dialog turn comprises: receiving, based at least in part on a predefined time period elapsing after engaging in the second dialog turn without actuation of a talk control of the first device, a third audio signal from the second device, the third audio signal representing third user speech; and determining a third meaning of the third user speech.

17. A method comprising: engaging in a speech dialog with a user to determine an intent of the user, wherein engaging in the speech dialog comprises engaging in a first dialog turn, a second dialog turn, and a third dialog turn with the user wherein engaging in the first dialog turn comprises: receiving a first audio signal produced by a first device, the first audio signal representing first user speech; and determining, based at least in part on providing the first audio signal to a speech service, a first meaning of the first user speech; wherein engaging in the second dialog turn comprises: receiving a second audio signal produced using a microphone of a second device, the second audio signal representing second user speech; determining, based at least in part on providing the second audio signal to the speech service, a second meaning of the second user speech; and wherein engaging in the third dialog turn comprises: receiving, based at least in part on a predefined time period elapsing after engaging in the second dialog turn without actuation of a talk control of the first device, a third audio signal from the second device, the third audio signal representing third user speech; and determining a third meaning of the third user speech. 20. The method of claim 17 , further comprising: analyzing the first audio signal to recognize the first user speech; and analyzing the second audio signal to recognize the second user speech.

43. A computing device configured to facilitate performance by task performers of tasks from task requesters, comprising: one or more processors; and one or more modules that are configured to, when executed by at least one of the one or more processors, for each of one or more task performers: obtain information about the task performer, the obtained information reflecting at least some prior activities of the task performer; receive indications of one or more available tasks supplied by one or more task requesters; automatically identify at least one of the available tasks as being preferred for the task performer based at least in part on an analysis of the obtained information about the task performer and on information about the identified tasks, wherein the analysis of the obtained information about the task performer includes weighting at least some of the obtained information about the prior activities of the task performer based on recency of the prior activities, such that a first prior activity of the task performer has a greater impact on the identifying than does a second prior activity of the task performer if the first prior activity occurred more recently than the second prior activity; and provide one or more indications to the task performer of at least one of the identified tasks.

43. A computing device configured to facilitate performance by task performers of tasks from task requesters, comprising: one or more processors; and one or more modules that are configured to, when executed by at least one of the one or more processors, for each of one or more task performers: obtain information about the task performer, the obtained information reflecting at least some prior activities of the task performer; receive indications of one or more available tasks supplied by one or more task requesters; automatically identify at least one of the available tasks as being preferred for the task performer based at least in part on an analysis of the obtained information about the task performer and on information about the identified tasks, wherein the analysis of the obtained information about the task performer includes weighting at least some of the obtained information about the prior activities of the task performer based on recency of the prior activities, such that a first prior activity of the task performer has a greater impact on the identifying than does a second prior activity of the task performer if the first prior activity occurred more recently than the second prior activity; and provide one or more indications to the task performer of at least one of the identified tasks. 46. The computing device of claim 43 wherein the one or more modules include software instructions for execution by at least one of the one or more processors.

3. The method of claim 1 wherein the actions determining a sentiment between each of the child posts and the parent post further comprise: establishing a sentiment score of each of the child posts based on an identified sentiment of each of the child posts to the parent post.

3. The method of claim 1 wherein the actions determining a sentiment between each of the child posts and the parent post further comprise: establishing a sentiment score of each of the child posts based on an identified sentiment of each of the child posts to the parent post. 4. The method of claim 3 wherein the actions further comprise: identifying the sentiment of each of the child posts by utilizing the resolved anaphors between the child posts and the parent post.

19. At a computer system, a method for ranking tables for inclusion in a response to a search query including one or more keywords, the method comprising: accessing a list of candidate tables for inclusion in a search query response, the list of candidate tables having been previously filtered from a compiled list of tables, each candidate table filtered by having an approximate ranking score meeting a score threshold to be considered a candidate table; for each candidate table: generating a hit matrix for the candidate table, including for any of the one or more keywords contained in the candidate table: determining that one or more fields in one or more parts of the candidate table contain a hit for the keyword and, for each of the one or more fields, computing a location of the keyword hit within the field; accessing table features for the candidate table from a feature index; generating a hit matrix overlay for the candidate table by overlaying the hit matrix with the accessed table features to distinguish keyword hits in different semantic locations inside the candidate table, overlaying the hit matrix including mapping keyword hit locations into logical regions of the candidate table; computing one or more dynamic features of the candidate table from the hit matrix overlay; and generating a ranking score for the candidate table at least from the one or more dynamic features.

19. At a computer system, a method for ranking tables for inclusion in a response to a search query including one or more keywords, the method comprising: accessing a list of candidate tables for inclusion in a search query response, the list of candidate tables having been previously filtered from a compiled list of tables, each candidate table filtered by having an approximate ranking score meeting a score threshold to be considered a candidate table; for each candidate table: generating a hit matrix for the candidate table, including for any of the one or more keywords contained in the candidate table: determining that one or more fields in one or more parts of the candidate table contain a hit for the keyword and, for each of the one or more fields, computing a location of the keyword hit within the field; accessing table features for the candidate table from a feature index; generating a hit matrix overlay for the candidate table by overlaying the hit matrix with the accessed table features to distinguish keyword hits in different semantic locations inside the candidate table, overlaying the hit matrix including mapping keyword hit locations into logical regions of the candidate table; computing one or more dynamic features of the candidate table from the hit matrix overlay; and generating a ranking score for the candidate table at least from the one or more dynamic features. 38. The method of claim 19 , wherein generating a hit matrix overlay for the candidate table comprises generating a spatial hit pattern overlay for the candidate table.

7. A non-transitory, computer-readable storage medium storing computer program code, the computer program code comprising instructions executable by a first device of a first user to perform a method for interacting with a web search infrastructure, the first user having a preference for reading text of a first language, the web search infrastructure gathering first web text of a second language, the method comprising: directing the first device to receive a second language related delivery comprising second language related data from the web search infrastructure, wherein the second language related delivery comprises digital delivery of at least a portion of a browser agent configured to provide a toolbar on a web browser screen, the toolbar including buttons for enabling translation from the first language to at least one second language; and directing the first device to perform translation related processing using the second language related data in at least a portion of the translation related processing, the translation related processing including: (i) automatically identifying, based on the second language related data, the second language within first search results received from the web search infrastructure, the first search results including at least a portion of the first web text, and the second language related data being received before receiving the first search results; and (ii) managing a translation from the second language to the first language relating to the first web text; (iii) presenting the translation results in the new window, wherein the translation results are determined by using a conjugate terms database, and wherein the translation results include results having meanings that differ from one another due to alternate meanings of a search string in the first language used to produce the first search results.

7. A non-transitory, computer-readable storage medium storing computer program code, the computer program code comprising instructions executable by a first device of a first user to perform a method for interacting with a web search infrastructure, the first user having a preference for reading text of a first language, the web search infrastructure gathering first web text of a second language, the method comprising: directing the first device to receive a second language related delivery comprising second language related data from the web search infrastructure, wherein the second language related delivery comprises digital delivery of at least a portion of a browser agent configured to provide a toolbar on a web browser screen, the toolbar including buttons for enabling translation from the first language to at least one second language; and directing the first device to perform translation related processing using the second language related data in at least a portion of the translation related processing, the translation related processing including: (i) automatically identifying, based on the second language related data, the second language within first search results received from the web search infrastructure, the first search results including at least a portion of the first web text, and the second language related data being received before receiving the first search results; and (ii) managing a translation from the second language to the first language relating to the first web text; (iii) presenting the translation results in the new window, wherein the translation results are determined by using a conjugate terms database, and wherein the translation results include results having meanings that differ from one another due to alternate meanings of a search string in the first language used to produce the first search results. 11. The non-transitory, computer-readable storage medium of claim 7 , wherein the computer program code comprises web browsing code.

4. The method as claimed in claim 2 , wherein said step (A) generates said discrimination result, on the basis of a frame size contained in a frame within said first code sequence.

4. The method as claimed in claim 2 , wherein said step (A) generates said discrimination result, on the basis of a frame size contained in a frame within said first code sequence. 5. The method as claimed in claim 4 , wherein said frame size is represented by a size of payload in this frame.

10. A computer readable media having stored computer program instructions for evaluating the contents of a message, comprising computer program instructions for characterizing a message segment, wherein the message segment further comprises a packet in a packet-switched network; computer program instructions for scanning the message segment to define a stream of tokens associated with the message segment; computer program instructions for associating the message segment with a meta session through the stream of tokens, wherein the meta session is made persistent across message transactions and different HTTP sessions by storing data generated by the meta session on a persistent storage medium; computer program instructions for parsing the token stream to extract substructures according to a grammar; computer program instructions for determining rules associated with the tokens, the rules defining actions for intrusion detection and prevention; computer program instructions for executing the actions associated with the message segment; and computer program instructions for queuing the message segments for transmission, wherein the each of the computer program instructions in the computer readable media are executed by an integrated circuit.

10. A computer readable media having stored computer program instructions for evaluating the contents of a message, comprising computer program instructions for characterizing a message segment, wherein the message segment further comprises a packet in a packet-switched network; computer program instructions for scanning the message segment to define a stream of tokens associated with the message segment; computer program instructions for associating the message segment with a meta session through the stream of tokens, wherein the meta session is made persistent across message transactions and different HTTP sessions by storing data generated by the meta session on a persistent storage medium; computer program instructions for parsing the token stream to extract substructures according to a grammar; computer program instructions for determining rules associated with the tokens, the rules defining actions for intrusion detection and prevention; computer program instructions for executing the actions associated with the message segment; and computer program instructions for queuing the message segments for transmission, wherein the each of the computer program instructions in the computer readable media are executed by an integrated circuit. 12. The computer readable media of claim 10 , wherein the computer program instruction for characterizing a message segment includes, computer program instructions for determining a grammar type of the message.

19. A computer system for facilitating document classification, the computer system comprising a processing unit coupled to a computer storage medium, the computer storage medium having stored thereon a plurality of computer software components executable by the processing unit in communication with a database, the computer software components comprising: a training component configured to parse a plurality of documents into features, at least one of the features including a plurality of terms derived from text associated with at least one of the plurality of documents, each of the documents being classified in at least one pre-defined class; a classifying component configured to classify at least one document into one or more of the pre-defined classes, wherein classifying comprises: (a) pre-classifying each of the plurality of documents into one or more pre-defined classes of a hierarchical structure, wherein the hierarchical structure arranges the one or more predefined classes into a parent classes and child classes; (b) ascertaining that the at least one feature occurs more frequently than a threshold frequency within more documents of the plurality of documents than a document threshold; and the database for storing the at least one feature as a vocabulary associated with at least one predefined class of the one or more predefined classes into which the plurality of documents is pre-classified, wherein the at least one predefined class comprises a child class that is connected by a branch connection to a parent class; and wherein the at least one feature is stored as a vocabulary associated with the connected parent class.

19. A computer system for facilitating document classification, the computer system comprising a processing unit coupled to a computer storage medium, the computer storage medium having stored thereon a plurality of computer software components executable by the processing unit in communication with a database, the computer software components comprising: a training component configured to parse a plurality of documents into features, at least one of the features including a plurality of terms derived from text associated with at least one of the plurality of documents, each of the documents being classified in at least one pre-defined class; a classifying component configured to classify at least one document into one or more of the pre-defined classes, wherein classifying comprises: (a) pre-classifying each of the plurality of documents into one or more pre-defined classes of a hierarchical structure, wherein the hierarchical structure arranges the one or more predefined classes into a parent classes and child classes; (b) ascertaining that the at least one feature occurs more frequently than a threshold frequency within more documents of the plurality of documents than a document threshold; and the database for storing the at least one feature as a vocabulary associated with at least one predefined class of the one or more predefined classes into which the plurality of documents is pre-classified, wherein the at least one predefined class comprises a child class that is connected by a branch connection to a parent class; and wherein the at least one feature is stored as a vocabulary associated with the connected parent class. 20. The computer system of claim 19 , wherein storing the at least one feature as a vocabulary associated with the connected parent class comprises: determining a probability of occurrence of the at least one feature stored as a vocabulary associated with the at least one predefined class; comparing the probability of occurrence against probabilities of occurrence determined for each of the one or more predefined classes that exist on an equivalent level of the hierarchical structure as the at least one predefined class; and storing the at least one feature as a vocabulary associated with the parent class connected to the at least one predefined class upon ascertaining that the probability of occurrence associated with the at least one predefined class is greater than any of the probabilities of occurrence determined for each of the one or more predefined classes that exist on the equivalent level of the hierarchical structure.

1. A computer-implemented method for use with a document management system, the computer-implemented method comprising: using a computer system to perform the steps of: retrieving data for a case file from the document management system; creating a visual representation for the case file, the visual representation comprising: a case identifier of the case file; an action field including a data entry field for receiving markings from a user for updating a record in the document management system corresponding to the case file, the markings including a plurality of boxes indicating predetermined actions, user notes to correct the record or prognoses; an index comprising a listing of a first plurality of documents associated with the case file, a first plurality of links to electronic versions of the first plurality of documents in the listing, and a plurality of textual summaries corresponding to the first plurality of documents in the listing, the index divided into a plurality of categories, each category containing a subset of documents in the listing; a plurality of thumbnail images of one or more of the first plurality of documents associated with the case file; a summary of a portion of the first plurality of documents associated with the case file and information specified by the user; and a plurality of related tokens for a plurality of related cases indicating a status of the plurality of related cases and a second plurality of links to electronic versions of a second plurality of documents corresponding to the plurality of related cases; and printing, on a printed medium, a first token that is a physical representation of the retrieved data, the first token comprising the visual representation of the case file.

1. A computer-implemented method for use with a document management system, the computer-implemented method comprising: using a computer system to perform the steps of: retrieving data for a case file from the document management system; creating a visual representation for the case file, the visual representation comprising: a case identifier of the case file; an action field including a data entry field for receiving markings from a user for updating a record in the document management system corresponding to the case file, the markings including a plurality of boxes indicating predetermined actions, user notes to correct the record or prognoses; an index comprising a listing of a first plurality of documents associated with the case file, a first plurality of links to electronic versions of the first plurality of documents in the listing, and a plurality of textual summaries corresponding to the first plurality of documents in the listing, the index divided into a plurality of categories, each category containing a subset of documents in the listing; a plurality of thumbnail images of one or more of the first plurality of documents associated with the case file; a summary of a portion of the first plurality of documents associated with the case file and information specified by the user; and a plurality of related tokens for a plurality of related cases indicating a status of the plurality of related cases and a second plurality of links to electronic versions of a second plurality of documents corresponding to the plurality of related cases; and printing, on a printed medium, a first token that is a physical representation of the retrieved data, the first token comprising the visual representation of the case file. 2. The method of claim 1 further comprising formatting the data and the index to create the visual representation of the case file to fit in a predetermined area of the physical representation.

27. A color management apparatus for building a color transformation workflow for transforming source-side color image data into corresponding destination-side color image data, the color management apparatus comprising: a computer-readable memory which stores computer-executable process steps, a module library, a profile library and a rule library, and a processor constructed to execute the computer-executable process steps stored in the memory; wherein the module library includes plural module entries each corresponding to a respective function module which implements color processing functionality, wherein each module entry comprises at least a module locator specifying a location for the function module, wherein for at least some of the module entries of the module library, the module entry further comprises a profile interface definition which specifies an interface for supply of parameters which characterize the function module, wherein the profile library includes plural profile entries each corresponding to a respective source of parameters that characterize a function module, wherein each profile entry comprises at least a profile locator specifying a location for the source of parameters, and a profile interface definition which specifies an interface for supply of the parameters to the function module characterized thereby, wherein the rule library includes entries for plural external rules and entries for plural internal rules, wherein each such external rule is associated with function modules located by module entries in the module library, and wherein the external rules and the internal rules characterize color transformation workflows of the color management module, and wherein the process steps stored in the memory cause the processor to convert source-side color image data into corresponding destination-side color image data, and include computer-executable process steps to: receive factual input including factual input derived from the source-side color image data; determine a sequence of function modules and sources of parameters from the module library and profile library, respectively, by using the factual input from the interface and the plural internal and external rules in the rule library; and build the color transformation workflow from the determined sequence of function modules and sources of parameters.

27. A color management apparatus for building a color transformation workflow for transforming source-side color image data into corresponding destination-side color image data, the color management apparatus comprising: a computer-readable memory which stores computer-executable process steps, a module library, a profile library and a rule library, and a processor constructed to execute the computer-executable process steps stored in the memory; wherein the module library includes plural module entries each corresponding to a respective function module which implements color processing functionality, wherein each module entry comprises at least a module locator specifying a location for the function module, wherein for at least some of the module entries of the module library, the module entry further comprises a profile interface definition which specifies an interface for supply of parameters which characterize the function module, wherein the profile library includes plural profile entries each corresponding to a respective source of parameters that characterize a function module, wherein each profile entry comprises at least a profile locator specifying a location for the source of parameters, and a profile interface definition which specifies an interface for supply of the parameters to the function module characterized thereby, wherein the rule library includes entries for plural external rules and entries for plural internal rules, wherein each such external rule is associated with function modules located by module entries in the module library, and wherein the external rules and the internal rules characterize color transformation workflows of the color management module, and wherein the process steps stored in the memory cause the processor to convert source-side color image data into corresponding destination-side color image data, and include computer-executable process steps to: receive factual input including factual input derived from the source-side color image data; determine a sequence of function modules and sources of parameters from the module library and profile library, respectively, by using the factual input from the interface and the plural internal and external rules in the rule library; and build the color transformation workflow from the determined sequence of function modules and sources of parameters. 35. A color management apparatus according to claim 27 , wherein the computer-readable memory further stores a fact database, wherein the fact database includes at least the received factual input, wherein the rule engine accesses the rule library and the fact database to derive a conclusion, and wherein the conclusion derived by the rule engine is the sequence of function modules and sources of parameters used to build the color transformation workflow.

1. A computer-implemented method for analyzing domain name registrar and hosting provider relationships, the method comprising: receiving a list of domain names; determining registrar information and hosting provider information associated with each domain name of the list of domain names; and generating a registrar-to-hosting-provider graph based on the registrar information and the hosting provider information associated with each domain name, wherein: the registrar-to-hosting-provider graph comprises: nodes representing registrars and nodes representing hosting providers; and edges comprising one or more edge attributes representing one or more common associations between the registrars and the hosting providers; the one or more edge attributes comprise a number of domain names of the list of domain names; and each edge corresponds to at least one domain name associated with a registrar and a hosting provider.

1. A computer-implemented method for analyzing domain name registrar and hosting provider relationships, the method comprising: receiving a list of domain names; determining registrar information and hosting provider information associated with each domain name of the list of domain names; and generating a registrar-to-hosting-provider graph based on the registrar information and the hosting provider information associated with each domain name, wherein: the registrar-to-hosting-provider graph comprises: nodes representing registrars and nodes representing hosting providers; and edges comprising one or more edge attributes representing one or more common associations between the registrars and the hosting providers; the one or more edge attributes comprise a number of domain names of the list of domain names; and each edge corresponds to at least one domain name associated with a registrar and a hosting provider. 2. The method of claim 1 , further comprising: requesting the list of domain names.

1. An input method for completing a missing text or a phrase on a display of a device terminal, comprising: receiving an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the device terminal; receiving an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receiving an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the device terminal, wherein the second phrase or the second sentence follows after the first punctuation; detecting a first location of a cursor on the display of the device terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identifying by the device terminal, one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; using the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, querying for a first next text or a first next phrase from a word library in a memory of the device terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; outputting on the display of the device terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detecting a second location of the cursor on the display of the device terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, and wherein the second location of the cursor is positioned after the first punctuation; identifying by the device terminal, one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; using the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, querying for a second next text or a second next phrase from the word library in the memory of the device terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and outputting on the display of the device terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence.

1. An input method for completing a missing text or a phrase on a display of a device terminal, comprising: receiving an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the device terminal; receiving an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receiving an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the device terminal, wherein the second phrase or the second sentence follows after the first punctuation; detecting a first location of a cursor on the display of the device terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identifying by the device terminal, one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; using the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, querying for a first next text or a first next phrase from a word library in a memory of the device terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; outputting on the display of the device terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detecting a second location of the cursor on the display of the device terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, and wherein the second location of the cursor is positioned after the first punctuation; identifying by the device terminal, one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; using the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, querying for a second next text or a second next phrase from the word library in the memory of the device terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and outputting on the display of the device terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence. 5. The input method according to claim 1 , wherein the querying for the second next text or the second next phrase from the word library in the memory of the device terminal, comprises: grouping by the device terminal, the second previous text or the second previous phrase according to an input sequence and frequently used words, and using a last input group of a character or a word as an index; and querying the word library from the memory for expressions and sentences comprising the index, and using an expression or a sentence that exists in the found expressions and sentences but does not exist in the index as the second next text or the second next phrase.

22. A computer-implemented method performed by one or more computer processors for database message building, comprising: displaying, through a user interface of a computer system, both an item window including structured data associated with at least one field of a record selected in a database and a message building window separate and distinct from the item window; receiving text input from a user through the message building window; retrieving tokens specified by the user through the item window, the tokens representing structured data selected by the user and associated with the selected database record; displaying a string in the message building window, the string including a combination of the text input and the tokens, wherein the message building window enables the user to publish the displayed string to an external source; and the retrieving tokens specified by the user through the item window further comprises: in response to the user indicating a specific position in the message building window, displaying field names for the at least one field in the item window; and populating the message building window with the tokens at the specific location of the message window in response to a selection of a field name.

22. A computer-implemented method performed by one or more computer processors for database message building, comprising: displaying, through a user interface of a computer system, both an item window including structured data associated with at least one field of a record selected in a database and a message building window separate and distinct from the item window; receiving text input from a user through the message building window; retrieving tokens specified by the user through the item window, the tokens representing structured data selected by the user and associated with the selected database record; displaying a string in the message building window, the string including a combination of the text input and the tokens, wherein the message building window enables the user to publish the displayed string to an external source; and the retrieving tokens specified by the user through the item window further comprises: in response to the user indicating a specific position in the message building window, displaying field names for the at least one field in the item window; and populating the message building window with the tokens at the specific location of the message window in response to a selection of a field name. 23. The method of claim 22 , wherein enabling the user to publish the displayed string to an external source further comprising: receiving input through the user interface specifying publication of the message displayed in the message building window; and responsive to the input, publishing the message to a user specified target application or network resource.

8. A method for altering visualized parameters for a gesture filter of an application, the gesture filter being designed to recognize whether to recognize a user of the application has performed a particular gesture from data comprising information about position or movement of the user, the method comprising: receiving data captured by a capture device, the data comprising information about user position or movement; displaying a visual output of the application; displaying a visual representation of at least one aspect of the user data, the visual representation comprising a list comprising the gesture filter; displaying a skeletal map associated with the user data; in response to user selection of a gesture filter from the list, displaying an indication of at least one body part involved in the performance of the gesture that the gesture filter is designed to recognize; in response to the system processing the data with the gesture filter and the adjustable parameter, displaying a representation indicating whether the position or movement represented by the data would be recognized by the gesture filter as the performance of the gesture that the gesture filter is designed to recognize; receiving, via a user interface of the display, a change to a parameter of the gesture filter of the application; altering the gesture filter corresponding to the received change; and displaying a representation of whether processing the data with the gesture filter and the changed parameter causes the system to determine that the position or movement represented by the data would be recognized by the gesture filter as the performance of the gesture that the gesture filter is designed to recognize.

8. A method for altering visualized parameters for a gesture filter of an application, the gesture filter being designed to recognize whether to recognize a user of the application has performed a particular gesture from data comprising information about position or movement of the user, the method comprising: receiving data captured by a capture device, the data comprising information about user position or movement; displaying a visual output of the application; displaying a visual representation of at least one aspect of the user data, the visual representation comprising a list comprising the gesture filter; displaying a skeletal map associated with the user data; in response to user selection of a gesture filter from the list, displaying an indication of at least one body part involved in the performance of the gesture that the gesture filter is designed to recognize; in response to the system processing the data with the gesture filter and the adjustable parameter, displaying a representation indicating whether the position or movement represented by the data would be recognized by the gesture filter as the performance of the gesture that the gesture filter is designed to recognize; receiving, via a user interface of the display, a change to a parameter of the gesture filter of the application; altering the gesture filter corresponding to the received change; and displaying a representation of whether processing the data with the gesture filter and the changed parameter causes the system to determine that the position or movement represented by the data would be recognized by the gesture filter as the performance of the gesture that the gesture filter is designed to recognize. 15. The method of claim 8 , wherein the visual representation comprises a skeletal map of at least part of the user corresponding to the data, further comprising: displaying an indication in the visual representation of at least one part of the skeletal map that corresponds to a selected gesture filter.

21. A method of identifying end-of-speech within an audio stream, comprising: step for analyzing each window of the audio stream in a speech discriminator; step for assigning a classification to said each window based on speech discriminator output corresponding to said each window, the classification being selected from a classification set comprising a first classification label corresponding to presence of speech within said each window, a second classification label corresponding to silence within said each window, and a third classification label corresponding to noise in said each window; incrementing a speech counter in response to said each window being assigned the first classification label; incrementing a silence counter in response to said each window being assigned the second classification label; incrementing a noise counter in response to said each window being assigned the third classification label; step for determining when the speech counter exceeds a first limit; clearing the speech counter, the silence counter, and the noise counter in response to the speech counter exceeds a first limit; step for weighting at least one of the silence counter and the noise counter to obtain weighted silence and noise values; step for combining the weighted silence and noise values in a result; step for comparing the result to a second limit; and step for identifying end-of-speech within the audio stream in response to the result reaching the second limit; wherein the steps for analyzing, assigning are performed by at least one processor.

21. A method of identifying end-of-speech within an audio stream, comprising: step for analyzing each window of the audio stream in a speech discriminator; step for assigning a classification to said each window based on speech discriminator output corresponding to said each window, the classification being selected from a classification set comprising a first classification label corresponding to presence of speech within said each window, a second classification label corresponding to silence within said each window, and a third classification label corresponding to noise in said each window; incrementing a speech counter in response to said each window being assigned the first classification label; incrementing a silence counter in response to said each window being assigned the second classification label; incrementing a noise counter in response to said each window being assigned the third classification label; step for determining when the speech counter exceeds a first limit; clearing the speech counter, the silence counter, and the noise counter in response to the speech counter exceeds a first limit; step for weighting at least one of the silence counter and the noise counter to obtain weighted silence and noise values; step for combining the weighted silence and noise values in a result; step for comparing the result to a second limit; and step for identifying end-of-speech within the audio stream in response to the result reaching the second limit; wherein the steps for analyzing, assigning are performed by at least one processor. 22. A method according to claim 21 , further comprising delimiting end of an audio section within the audio stream when end-of-speech is identified to obtain a delimited audio section.

24. The computer system of claim 23 in which the processor is further configured for: determining a name for the child block based on a transformation applied to the parent block and a name of the parent block.

24. The computer system of claim 23 in which the processor is further configured for: determining a name for the child block based on a transformation applied to the parent block and a name of the parent block. 25. The computer system of claim 24 in which the processor is further configured for: associating one or more tuning actions with the child block using the name of the child block.

8. A system executed by a processor for protecting client computers; comprising: an initial filter that gathers scripting-language-data from webpage data; a signature database of signatures of known scripting-language-data exploits; a parser that generates a parse tree from the scripting-language-data; a normalization and signature matching component that reduces a complexity of the parse tree, generates a representation of at least a portion of a structure of the parse tree, and prevents the scripting-language-data from reaching an intended recipient when the representation matches one of the signatures of known scripting-language-data exploits; and an analysis component that identifies characteristics of the scripting-language-data, scores the characteristics of scripting-language-data based upon a likelihood that the characteristics of the scripting-language-data are associated with malicious scripting-language data, and determines whether to block the scripting-language-data from reaching the intended recipient based upon a score of characteristics of a normalized scripting-language-data and a score of characteristics of inspection data based on the scripting language-data.

8. A system executed by a processor for protecting client computers; comprising: an initial filter that gathers scripting-language-data from webpage data; a signature database of signatures of known scripting-language-data exploits; a parser that generates a parse tree from the scripting-language-data; a normalization and signature matching component that reduces a complexity of the parse tree, generates a representation of at least a portion of a structure of the parse tree, and prevents the scripting-language-data from reaching an intended recipient when the representation matches one of the signatures of known scripting-language-data exploits; and an analysis component that identifies characteristics of the scripting-language-data, scores the characteristics of scripting-language-data based upon a likelihood that the characteristics of the scripting-language-data are associated with malicious scripting-language data, and determines whether to block the scripting-language-data from reaching the intended recipient based upon a score of characteristics of a normalized scripting-language-data and a score of characteristics of inspection data based on the scripting language-data. 11. The system of claim 8 , wherein the shellcode module does not disassemble the one or more strings unless the one or mores strings exceeds a size threshold.

3. In a computing environment, a system comprising: a category selection mechanism coupled to an intermediate taxonomy and a target taxonomy and configured to select a subset of intermediate taxonomy categories represented in the intermediate taxonomy based on relevance to target taxonomy categories represented in the target taxonomy, wherein the category selection mechanism is configured to compute the relevance based on relative probability scores between the intermediate taxonomy categories and the target taxonomy categories, individual relative probability scores corresponding to a probability of a corresponding intermediate taxonomy category generating one or more of the target taxonomy categories; a taxonomy bridging mechanism configured to process the subset of intermediate taxonomy categories to construct a bridging classifier for use in relating online queries to individual target taxonomy categories in the target taxonomy, the taxonomy bridging mechanism configured to determine relationship values between one or more of the intermediate taxonomy categories and one or more of the target taxonomy categories to construct the bridging classifier a computing device configured to implement at least one of the category selection mechanism or the taxonomy bridging mechanism.

3. In a computing environment, a system comprising: a category selection mechanism coupled to an intermediate taxonomy and a target taxonomy and configured to select a subset of intermediate taxonomy categories represented in the intermediate taxonomy based on relevance to target taxonomy categories represented in the target taxonomy, wherein the category selection mechanism is configured to compute the relevance based on relative probability scores between the intermediate taxonomy categories and the target taxonomy categories, individual relative probability scores corresponding to a probability of a corresponding intermediate taxonomy category generating one or more of the target taxonomy categories; a taxonomy bridging mechanism configured to process the subset of intermediate taxonomy categories to construct a bridging classifier for use in relating online queries to individual target taxonomy categories in the target taxonomy, the taxonomy bridging mechanism configured to determine relationship values between one or more of the intermediate taxonomy categories and one or more of the target taxonomy categories to construct the bridging classifier a computing device configured to implement at least one of the category selection mechanism or the taxonomy bridging mechanism. 5. The system of claim 3 wherein the category selection mechanism operates in an offline state relative to the taxonomy bridging classifier relating the online queries to the individual target taxonomy categories in the target taxonomy.

6. The device of claim 1 , wherein at least one of the one or more speech codebooks is based on a hidden Markov model.

6. The device of claim 1 , wherein at least one of the one or more speech codebooks is based on a hidden Markov model. 7. The device of claim 6 , wherein the one or more codebooks based on the hidden Markov model provide, in sequence, a plurality of features vectors representing spectral characteristics of speech for a given frame for the plurality of frames.