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6. The teaching method of claim 1 wherein the second displaying step includes the step of sequentially displaying said chosen words at said main portion.

6. The teaching method of claim 1 wherein the second displaying step includes the step of sequentially displaying said chosen words at said main portion. 8. The teaching method of claim 6 further comprising the step of spacing said sequentially displayed chosen words according to the temporal spacing between the vocalizing of said sequentially displayed chosen words.

5. The distributed data annotation server system of claim 1 , wherein the distributed data annotation application further configures the processor to update source data metadata for at least one piece of source data using the received annotations and the annotator metadata.

5. The distributed data annotation server system of claim 1 , wherein the distributed data annotation application further configures the processor to update source data metadata for at least one piece of source data using the received annotations and the annotator metadata. 6. The distributed data annotation server system of claim 5 , wherein the source data metadata includes a measure of the difficulty of describing the source data.

1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query.

1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query. 2. The method of claim 1 , further comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to the first user; and a plurality of second nodes corresponding to the plurality of entities, respectively.

8. A method for monitoring conversations at a call center between customers and call center agents in real-time, the method comprising: calculating emotion scores for agents and respective customers in real-time during conversations between the agents and the respective customers; calculating, for each conversation, a first frequency based on the calculated customer emotion scores, wherein calculating the first frequency comprises determining a number of the calculated customer emotions scores that equal or exceed an emotion score threshold during a specified time interval that is less than the entire respective conversation; calculating, for each conversation, a second frequency based on the calculated agent emotion scores, wherein calculating the second frequency comprises determining a number of the calculated agent emotions scores that equal or exceed the emotion score threshold during the specified time interval; detecting, in real-time, specified words or phrases spoken by either the agents or the respective customers during the conversations; displaying, in real-time at an agent station of each agent currently having a conversation with a customer, a visual representation based on the calculated second frequency and a visual representation based on the calculated first frequency; recording conversations between agents and customers; storing the calculated emotion scores for agents and customers; tagging each recorded conversation with event tags, wherein: each event tag represents one of the first frequency, the second frequency, or a generated word/phrase event, and in response to a selection of an event tag, corresponding calculated emotion scores and generated word/phrase events are displayed; and identifying specified emotions and specified additional word/phrase events that were generated during the recorded conversations.

8. A method for monitoring conversations at a call center between customers and call center agents in real-time, the method comprising: calculating emotion scores for agents and respective customers in real-time during conversations between the agents and the respective customers; calculating, for each conversation, a first frequency based on the calculated customer emotion scores, wherein calculating the first frequency comprises determining a number of the calculated customer emotions scores that equal or exceed an emotion score threshold during a specified time interval that is less than the entire respective conversation; calculating, for each conversation, a second frequency based on the calculated agent emotion scores, wherein calculating the second frequency comprises determining a number of the calculated agent emotions scores that equal or exceed the emotion score threshold during the specified time interval; detecting, in real-time, specified words or phrases spoken by either the agents or the respective customers during the conversations; displaying, in real-time at an agent station of each agent currently having a conversation with a customer, a visual representation based on the calculated second frequency and a visual representation based on the calculated first frequency; recording conversations between agents and customers; storing the calculated emotion scores for agents and customers; tagging each recorded conversation with event tags, wherein: each event tag represents one of the first frequency, the second frequency, or a generated word/phrase event, and in response to a selection of an event tag, corresponding calculated emotion scores and generated word/phrase events are displayed; and identifying specified emotions and specified additional word/phrase events that were generated during the recorded conversations. 13. The method of claim 8 , further comprising sending an alert to a supervisor station when calculated customer emotion scores equal or exceed a specified emotion score threshold at a frequency that is equal to or higher than a specified frequency threshold.

1. An apparatus comprising: a processor; a computer readable memory; a user interface to receive user inputs and to display outputs to a user; and wherein: the computer readable memory contains a series of computer-executable instructions to be executed by the processor which enable the formulation of a mathematical expression by the user via the user interface, the mathematical expression comprising a selection of objects from a library of object types contained in the computer readable memory, the object types comprising primitive objects and non-primitive objects, wherein non-primitive objects have at least one field which in turn can host additional objects, and primitive objects have no fields, and wherein: the mathematical expression formulated by the user is defined by a single computer readable data structure which is generated automatically by the series of computer-executable instructions in response to the user inputs, and is stored in the computer readable memory; each object and each field is defined by a mathematical significance assigned thereto within the single computer readable data structure; the single computer readable data structure combines functions of a content tree data structure, and of a presentation tree data structure, for the mathematical expression; the single computer readable data structure contains presentation data sufficient to enable complete, automatic formatting of the mathematical expression for the display; the single computer readable data structure contains content data sufficient to enable automatic computation of the mathematical expression by the processor; the user interface enables the user to edit the mathematical expression; editing of the mathematical expression by the user via the user interface results in automatic modification of the single computer readable data structure; and the series of computer-executable instructions include a series of steps to identify the user inputs with at least some of the objects, and to display the mathematical expression defined by the single computer readable data structure via the display.

1. An apparatus comprising: a processor; a computer readable memory; a user interface to receive user inputs and to display outputs to a user; and wherein: the computer readable memory contains a series of computer-executable instructions to be executed by the processor which enable the formulation of a mathematical expression by the user via the user interface, the mathematical expression comprising a selection of objects from a library of object types contained in the computer readable memory, the object types comprising primitive objects and non-primitive objects, wherein non-primitive objects have at least one field which in turn can host additional objects, and primitive objects have no fields, and wherein: the mathematical expression formulated by the user is defined by a single computer readable data structure which is generated automatically by the series of computer-executable instructions in response to the user inputs, and is stored in the computer readable memory; each object and each field is defined by a mathematical significance assigned thereto within the single computer readable data structure; the single computer readable data structure combines functions of a content tree data structure, and of a presentation tree data structure, for the mathematical expression; the single computer readable data structure contains presentation data sufficient to enable complete, automatic formatting of the mathematical expression for the display; the single computer readable data structure contains content data sufficient to enable automatic computation of the mathematical expression by the processor; the user interface enables the user to edit the mathematical expression; editing of the mathematical expression by the user via the user interface results in automatic modification of the single computer readable data structure; and the series of computer-executable instructions include a series of steps to identify the user inputs with at least some of the objects, and to display the mathematical expression defined by the single computer readable data structure via the display. 51. The apparatus of claim 1 and wherein the user interface comprises a display device, and the library of object types comprises a textbox object.

59. A non-transitory computer-readable medium having encoded thereon a method for decreasing the perceived end user latency while interacting with a database, the method comprising: aggregating metadata associated with media in the database; displaying on a user interface of an endpoint device, a first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface wherein the endpoint device communicates with the digital media server via at least one of multiple connections between the endpoint device and the digital media server, wherein endpoint device and the digital media server negotiate a number of objects to be presented; performing at least one first predictive background query of the database based on the displayed first set of query results and prior to a user invoking any action within the user interface; receiving and storing the another set of query results for each of the query results in the displayed first set of query results from the at least one first predictive background query; receiving user input at a user interface; generating at least one query based on the user input; comparing the at least one generated query to the at least one first predictive background query; performing at least one second predictive background query of the database in response to the at least one first predictive background query not encompassing the at least one generated query; and displaying the another set of query results received from the at least one first predictive background query that correspond to the generated query via the user interface in response to the at least one first predictive background query encompassing the at least one generated query.

59. A non-transitory computer-readable medium having encoded thereon a method for decreasing the perceived end user latency while interacting with a database, the method comprising: aggregating metadata associated with media in the database; displaying on a user interface of an endpoint device, a first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface wherein the endpoint device communicates with the digital media server via at least one of multiple connections between the endpoint device and the digital media server, wherein endpoint device and the digital media server negotiate a number of objects to be presented; performing at least one first predictive background query of the database based on the displayed first set of query results and prior to a user invoking any action within the user interface; receiving and storing the another set of query results for each of the query results in the displayed first set of query results from the at least one first predictive background query; receiving user input at a user interface; generating at least one query based on the user input; comparing the at least one generated query to the at least one first predictive background query; performing at least one second predictive background query of the database in response to the at least one first predictive background query not encompassing the at least one generated query; and displaying the another set of query results received from the at least one first predictive background query that correspond to the generated query via the user interface in response to the at least one first predictive background query encompassing the at least one generated query. 66. The method of claim 59 , wherein performing the at least one second predictive background query further comprises performing the query while awaiting to receive user input.

11. A system comprising: a computer device comprising a processor, graphical interface, and a system memory in communication with the processor via a communication medium, the system memory configured to store programmed computer code, which when executed by the processor, causes the processor to perform operations for accommodating a plurality of translations of a source text string into a limited available display area of a visual element in the graphical interface, the operations comprising: receiving an input source text string in the display area of the visual element; receiving input specifying a source language for the source text string; receiving input selecting two or more target languages for the source text string to be translated into; obtaining translations of the source text string in each of the selected two or more target languages; displaying, in response to the input source text string, a set of translation vectors, each translation vector comprising one possible translation of the source text string for each of the selected two or more target languages; receiving a selection of a translation vector that contains a translation of the source text string corresponding to an intended meaning of the source text string; and calculating a minimum display area necessary for the visual element to display a longest translation of the translations contained in the selected translation vector, wherein the display area of the visual element in the graphical interface is adjusted to encompass the minimum display area such that the longest translation fits within the display area of the visual element.

11. A system comprising: a computer device comprising a processor, graphical interface, and a system memory in communication with the processor via a communication medium, the system memory configured to store programmed computer code, which when executed by the processor, causes the processor to perform operations for accommodating a plurality of translations of a source text string into a limited available display area of a visual element in the graphical interface, the operations comprising: receiving an input source text string in the display area of the visual element; receiving input specifying a source language for the source text string; receiving input selecting two or more target languages for the source text string to be translated into; obtaining translations of the source text string in each of the selected two or more target languages; displaying, in response to the input source text string, a set of translation vectors, each translation vector comprising one possible translation of the source text string for each of the selected two or more target languages; receiving a selection of a translation vector that contains a translation of the source text string corresponding to an intended meaning of the source text string; and calculating a minimum display area necessary for the visual element to display a longest translation of the translations contained in the selected translation vector, wherein the display area of the visual element in the graphical interface is adjusted to encompass the minimum display area such that the longest translation fits within the display area of the visual element. 13. The system of claim 11 wherein the set of translation vectors comprise alternative translations of the source text string to account for ambiguities in the source language.

9. The non-transitory computer-readable storage medium of claim 1 , further comprising an instruction for selectively engaging portions of the specialized tools and storing all intermediate results inside a plurality of data-structures.

9. The non-transitory computer-readable storage medium of claim 1 , further comprising an instruction for selectively engaging portions of the specialized tools and storing all intermediate results inside a plurality of data-structures. 11. The non-transitory computer-readable storage medium of claim 9 , further comprising an instruction for storing intermediate results methodically.

1. A computer-implemented method of generating a document revision history for versions of a document managed by a first electronic document management system (EDMS), the method comprising, by a second EDMS: importing, from the first EDMS into a first location of the second EDMS, metadata describing a first document revision history for the versions of the document managed by the first EDMS, wherein the first document revision history comprises metadata attributes in a first format associated with the first EDMS and describes an actual revision history of the document; generating, from the metadata describing the first document revision history, a second document revision history comprising metadata attributes in a second format associated with the second EDMS, wherein the second document revision history provides a mirrored revision history mirroring the actual revision history, and wherein one or more metadata attributes in the second format are distinct from one or more corresponding metadata attributes in the first format; importing the second document revision history from the first location into a repository managed by the second EDMS; and importing the versions of the document from the first location into the repository managed by the second EDMS.

1. A computer-implemented method of generating a document revision history for versions of a document managed by a first electronic document management system (EDMS), the method comprising, by a second EDMS: importing, from the first EDMS into a first location of the second EDMS, metadata describing a first document revision history for the versions of the document managed by the first EDMS, wherein the first document revision history comprises metadata attributes in a first format associated with the first EDMS and describes an actual revision history of the document; generating, from the metadata describing the first document revision history, a second document revision history comprising metadata attributes in a second format associated with the second EDMS, wherein the second document revision history provides a mirrored revision history mirroring the actual revision history, and wherein one or more metadata attributes in the second format are distinct from one or more corresponding metadata attributes in the first format; importing the second document revision history from the first location into a repository managed by the second EDMS; and importing the versions of the document from the first location into the repository managed by the second EDMS. 5. The method of claim 1 , further comprising: prior to generating the second document revision history, determining that one or more of the versions of the document are stored in the second EDMS and determining that the document has been modified by users of the first EDMS and second EDMS after previously being imported; and when importing the second document revision history from the first location into the repository managed by the second EDMS, overwriting at least a portion of an existing revision history associated with the one or more versions of the document stored in the second EDMS.

49. A computer-readable medium comprising an application program interface, the application program interface configurable to assemble software components of an automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information.

49. A computer-readable medium comprising an application program interface, the application program interface configurable to assemble software components of an automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information. 53. A computer-readable medium as claimed in claim 49 in which at least one of said application programs is a workflow program in which one or more document files are routed to one or more workstations based on information identified by content instructions.

10. A computer-implemented method for facilitating portability of web meeting interactions, the method comprising: providing for display, by a client device associated with a participant identifier, at least a first portion of an interaction record received from a server device, wherein the first portion of the interaction record includes a first annotating input associated with a first instance of a web meeting identifier, and wherein the first annotating input includes a first unique descriptor that references the participant identifier, the first instance, and a time; transmitting, by the client device and to the server device, a selection from at least the first portion of the interaction record, the selection including the first annotating input and transmitted to export at least the selected first annotating input to a second instance of the web meeting identifier; and providing for display, by the client device for the second instance, at least a second portion of the interaction record received from the server device, wherein the second portion includes a second annotating input generated by the server device based on a portion of the selected first annotating input, wherein the second annotating input includes a second unique descriptor that at least references the second instance, wherein the web meeting identifier defines a topical framework from which each instance thereof, including the first instance and the second instance, inherits its characteristics, and wherein each instance of the web meeting identifier corresponds to one occurrence of a web meeting.

10. A computer-implemented method for facilitating portability of web meeting interactions, the method comprising: providing for display, by a client device associated with a participant identifier, at least a first portion of an interaction record received from a server device, wherein the first portion of the interaction record includes a first annotating input associated with a first instance of a web meeting identifier, and wherein the first annotating input includes a first unique descriptor that references the participant identifier, the first instance, and a time; transmitting, by the client device and to the server device, a selection from at least the first portion of the interaction record, the selection including the first annotating input and transmitted to export at least the selected first annotating input to a second instance of the web meeting identifier; and providing for display, by the client device for the second instance, at least a second portion of the interaction record received from the server device, wherein the second portion includes a second annotating input generated by the server device based on a portion of the selected first annotating input, wherein the second annotating input includes a second unique descriptor that at least references the second instance, wherein the web meeting identifier defines a topical framework from which each instance thereof, including the first instance and the second instance, inherits its characteristics, and wherein each instance of the web meeting identifier corresponds to one occurrence of a web meeting. 11. The method of claim 10 , wherein the first unique descriptor further references a recording of the first instance, wherein the recording is stored independent of the first annotating input.

5. The method of claim 1 , wherein analyzing the relationships between users who wrote the original text and/or the one or more comments included in the plurality of threads comprises providing a weight based on at least one of: frequency of writing, number of texts, the length of at least some of the one or more comments, time interval between writing, and semantics of texts in each thread, computing a harmonic mean with respect to the weight, and determining intimacy levels of the users based on the harmonic mean.

5. The method of claim 1 , wherein analyzing the relationships between users who wrote the original text and/or the one or more comments included in the plurality of threads comprises providing a weight based on at least one of: frequency of writing, number of texts, the length of at least some of the one or more comments, time interval between writing, and semantics of texts in each thread, computing a harmonic mean with respect to the weight, and determining intimacy levels of the users based on the harmonic mean. 6. The method of claim 5 , wherein the weight is applied to two different users (u l , u 2 ) and computing the harmonic mean comprises computing relation scores of a corresponding user group by: Score u 1 ⁢ u 2 ⁡ ( T 1 ) = ⁢ H ⁡ ( W ⁡ ( u 1 ) , W ⁡ ( u 2 ) ) = ⁢ 2 * W ⁡ ( u 1 ) * W ⁡ ( u 2 ) W ⁡ ( u 1 ) + W ⁡ ( u 2 ) where, Score u1,u2 (T 1 ) denotes a relation score in a first thread (T1), H denotes harmonic mean, W denotes weight applied to user, and W(u 1 ) is weight applied to user u 1 , and W(u 2 ) is weight applied to user u 2 .

17. A non-transitory computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to perform a method comprising: transcribing speech data using a first automatic speech recognition pass, which operates at a first transcription rate, to produce a first transcription data and a first word graph; displaying a displayed part comprising an indication of a second automatic speech recognition pass which is forthcoming and at least part of the first transcription data corresponding to a portion of the speech data after displaying the displayed part, transcribing the speech data using the second automatic speech recognition pass, wherein the second automatic speech recognition pass uses the first word graph, wherein the second automatic speech recognition pass produces a second transcription data and a second word graph, and wherein the second automatic speech recognition pass is slower than the first automatic speech recognition pass; and upon completing the second automatic speech recognition pass, updating the displayed part based at least in part on the second transcription data.

17. A non-transitory computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to perform a method comprising: transcribing speech data using a first automatic speech recognition pass, which operates at a first transcription rate, to produce a first transcription data and a first word graph; displaying a displayed part comprising an indication of a second automatic speech recognition pass which is forthcoming and at least part of the first transcription data corresponding to a portion of the speech data after displaying the displayed part, transcribing the speech data using the second automatic speech recognition pass, wherein the second automatic speech recognition pass uses the first word graph, wherein the second automatic speech recognition pass produces a second transcription data and a second word graph, and wherein the second automatic speech recognition pass is slower than the first automatic speech recognition pass; and upon completing the second automatic speech recognition pass, updating the displayed part based at least in part on the second transcription data. 18. The non-transitory computer-readable storage medium of claim 17 , wherein the first automatic speech recognition pass operates at real time.

9. An apparatus that creates a presentation to a user, comprising: a processor that executes a computer program to support the presentation; a memory that stores information under the control of the processor; logic that presents information indicative of a goal, the goal being associated with a skill required for the user in a business endeavor; logic that integrates information that motivates accomplishment of the goal; logic that monitors progress toward the goal and provides feedback that further motivates accomplishment of the goal, wherein: the feedback is characterized by a set of profiles and topics; the profiles trigger the topics in a concept tree to obtain a plurality of activated topics; and the feedback is selected from the plurality of activated topics in the concept tree by: identifying a top-most target group with an activated topic; if the top-most target group is a first type of feedback, selecting that feedback for display to the user without examining any other activated topics; and if the top-most target group is a second type of feedback different from the first type of feedback, grouping the activated feedback in the children target groups and assembling it into a feedback paragraph for display to the user; and logic that performs regression analysis of the computer program as the presentation subsequently executes.

9. An apparatus that creates a presentation to a user, comprising: a processor that executes a computer program to support the presentation; a memory that stores information under the control of the processor; logic that presents information indicative of a goal, the goal being associated with a skill required for the user in a business endeavor; logic that integrates information that motivates accomplishment of the goal; logic that monitors progress toward the goal and provides feedback that further motivates accomplishment of the goal, wherein: the feedback is characterized by a set of profiles and topics; the profiles trigger the topics in a concept tree to obtain a plurality of activated topics; and the feedback is selected from the plurality of activated topics in the concept tree by: identifying a top-most target group with an activated topic; if the top-most target group is a first type of feedback, selecting that feedback for display to the user without examining any other activated topics; and if the top-most target group is a second type of feedback different from the first type of feedback, grouping the activated feedback in the children target groups and assembling it into a feedback paragraph for display to the user; and logic that performs regression analysis of the computer program as the presentation subsequently executes. 15. An apparatus that creates a presentation as recited in claim 9 , including logic that organizes the regression analysis information in a company preferred manner to facilitate performance metrics for the company.

11. A computer program product, comprising: a computer readable medium; and computer program instructions stored on the computer readable medium that, when processed by a computer, instruct the computer to perform a process of synchronizing text with audio in a multimedia file, wherein the multimedia file includes previously synchronized video and audio, wherein the multimedia file has a start time and a stop time that defines a timeline for the multimedia file, wherein the frames of the video and the corresponding audio are each associated with respective points in time along the timeline, the process comprising: receiving the multimedia file and parsing the audio therefrom, but maintaining the timeline synchronization between the video and the audio; receiving closed-captioned data associated with the multimedia file, wherein the closed-captioned data contains closed-captioned text, wherein each word of the closed-captioned text is associated with a corresponding word spoken in the audio, wherein each word of the closed-captioned text has a high degree of accuracy with the corresponding word spoken in the audio but a low correlation with the respective point in time along the timeline at which the corresponding word was spoken in the audio; using automated speech recognition (ASR) software, generating ASR text of the parsed audio, wherein each word of the ASR text is associated approximately with the corresponding words spoken in the audio, wherein each word of the ASR text has a lower degree of accuracy with the corresponding words spoken in the audio than the respective words of the closed-captioned text but a high correlation with the respective point in time along the timeline at which the corresponding word was spoken in the audio; thereafter, using N-gram analysis, comparing each word of the closed-captioned text with a plurality of words of the ASR text until a match is found; and for each matched word from the closed-captioned text, associating therewith the respective point in time along the timeline of the matched word from the ASR text corresponding therewith, whereby each closed-captioned word is associated with a respective point on the timeline corresponding to the same point in time on the timeline in which the word is actually spoken in the audio and occurs within the video.

11. A computer program product, comprising: a computer readable medium; and computer program instructions stored on the computer readable medium that, when processed by a computer, instruct the computer to perform a process of synchronizing text with audio in a multimedia file, wherein the multimedia file includes previously synchronized video and audio, wherein the multimedia file has a start time and a stop time that defines a timeline for the multimedia file, wherein the frames of the video and the corresponding audio are each associated with respective points in time along the timeline, the process comprising: receiving the multimedia file and parsing the audio therefrom, but maintaining the timeline synchronization between the video and the audio; receiving closed-captioned data associated with the multimedia file, wherein the closed-captioned data contains closed-captioned text, wherein each word of the closed-captioned text is associated with a corresponding word spoken in the audio, wherein each word of the closed-captioned text has a high degree of accuracy with the corresponding word spoken in the audio but a low correlation with the respective point in time along the timeline at which the corresponding word was spoken in the audio; using automated speech recognition (ASR) software, generating ASR text of the parsed audio, wherein each word of the ASR text is associated approximately with the corresponding words spoken in the audio, wherein each word of the ASR text has a lower degree of accuracy with the corresponding words spoken in the audio than the respective words of the closed-captioned text but a high correlation with the respective point in time along the timeline at which the corresponding word was spoken in the audio; thereafter, using N-gram analysis, comparing each word of the closed-captioned text with a plurality of words of the ASR text until a match is found; and for each matched word from the closed-captioned text, associating therewith the respective point in time along the timeline of the matched word from the ASR text corresponding therewith, whereby each closed-captioned word is associated with a respective point on the timeline corresponding to the same point in time on the timeline in which the word is actually spoken in the audio and occurs within the video. 14. The computer program product of claim 11 wherein, within the process, the step of comparing each word of the closed-captioned text with a plurality of words of the ASR text until a match is found further comprises the step of moving on to the next respective word of the closed-captioned text for comparison purposes if the prior word of the closed-captioned text is not matched with any of the plurality of words of the ASR text.

8. A computer-readable storage medium having computer-executable instructions, which when executed perform steps, comprising: determining relationship values between intermediate taxonomy categories represented in an intermediate taxonomy and target taxonomy categories represented in a target taxonomy; selecting a subset of intermediate taxonomy categories represented in the intermediate taxonomy based on relevance to the target taxonomy categories represented in the target taxonomy, wherein the selecting the subset comprises: computing one or more 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 taxonomies; and selecting the subset based on the one or more relative probability scores; processing the subset of intermediate categories to construct a bridging using the relationship values; and receiving an online query and utilizing the bridging classifier to locate an individual target taxonomy category.

8. A computer-readable storage medium having computer-executable instructions, which when executed perform steps, comprising: determining relationship values between intermediate taxonomy categories represented in an intermediate taxonomy and target taxonomy categories represented in a target taxonomy; selecting a subset of intermediate taxonomy categories represented in the intermediate taxonomy based on relevance to the target taxonomy categories represented in the target taxonomy, wherein the selecting the subset comprises: computing one or more 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 taxonomies; and selecting the subset based on the one or more relative probability scores; processing the subset of intermediate categories to construct a bridging using the relationship values; and receiving an online query and utilizing the bridging classifier to locate an individual target taxonomy category. 10. The computer-readable storage medium of claim 8 , wherein utilizing the bridging classifier to locate an individual target taxonomy category includes determining the individual target category as a function of a conditional probability of a node in the target taxonomy as determined from the intermediate taxonomy.

1. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing text represented by characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of expressions in the document not contained in a stop list and having at least a first predetermined level of complexity, said stop list stored in the memory of said computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring expressions determined in step (a), said seed list stored in said memory of said computer; c) using said computer, automatically forming a summary of the document comprised of regions in the document containing at least two members of said seed list, said summary stored in said memory of said computer; and d) using said computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the members of said seed list to said stop list and reducing said first predetermined level of complexity.

1. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing text represented by characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of expressions in the document not contained in a stop list and having at least a first predetermined level of complexity, said stop list stored in the memory of said computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring expressions determined in step (a), said seed list stored in said memory of said computer; c) using said computer, automatically forming a summary of the document comprised of regions in the document containing at least two members of said seed list, said summary stored in said memory of said computer; and d) using said computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the members of said seed list to said stop list and reducing said first predetermined level of complexity. 22. The method of claim 1, wherein said predetermined length of said summary is no greater than one page.

21. A method comprising: under control of one or more computing systems configured with executable instructions, generating a searchable item index of terms in an electronic item, the searchable item index comprising a list of location identifiers indicating a location at which each term appears within the electronic item; generating a searchable item-specific master index of terms in the electronic item, the item-specific master index comprising a list of terms used in the electronic item and, for each term, a reference to an item index entry for the respective term, the reference to an item index entry comprising an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item; and transmitting the item index and the master index to a handheld electronic book reader device.

21. A method comprising: under control of one or more computing systems configured with executable instructions, generating a searchable item index of terms in an electronic item, the searchable item index comprising a list of location identifiers indicating a location at which each term appears within the electronic item; generating a searchable item-specific master index of terms in the electronic item, the item-specific master index comprising a list of terms used in the electronic item and, for each term, a reference to an item index entry for the respective term, the reference to an item index entry comprising an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item; and transmitting the item index and the master index to a handheld electronic book reader device. 26. The method of claim 21 , further comprising generating a searchable item index of terms for plural electronic items, and for each of the plural electronic items, generating a searchable item-specific master index of terms in the respective electronic item.

6. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: obtaining, during an unsupervised classification phase of a spoken dialog system, a semantic classifier input and a corresponding label attributed to the semantic classifier input; determining, via a processor, whether the corresponding label is correct based on logged interaction data, to yield a correctness result, wherein the logged interaction data comprises: data describing user speech; a non-speech user action indicating one of a negative training example and a positive training example; and an input/output pair having an input and an output, the input comprising a speech recognition result in a lattice form and the output comprising one of an outcome of a call, a confirmation by a user, and a call hang-up, the output being a result of the input; generating an entry for an adaptation corpus based on the correctness result; and adapting operation of a semantic classifier based on the adaptation corpus.

6. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: obtaining, during an unsupervised classification phase of a spoken dialog system, a semantic classifier input and a corresponding label attributed to the semantic classifier input; determining, via a processor, whether the corresponding label is correct based on logged interaction data, to yield a correctness result, wherein the logged interaction data comprises: data describing user speech; a non-speech user action indicating one of a negative training example and a positive training example; and an input/output pair having an input and an output, the input comprising a speech recognition result in a lattice form and the output comprising one of an outcome of a call, a confirmation by a user, and a call hang-up, the output being a result of the input; generating an entry for an adaptation corpus based on the correctness result; and adapting operation of a semantic classifier based on the adaptation corpus. 9. The spoken dialog system of claim 6 , wherein determining whether the corresponding label is correct further comprises: calculating a confidence level indicative of an estimated probability that the corresponding label is correct; and determining that the corresponding label is correct when the calculated confidence level is greater than a predetermined threshold.

1. A computer implemented method for managing electronically delivered information channels, comprising: receiving, by a computing device having a channel personalization engine, from one of a first subscriber device associated with a subscriber and a second subscriber device associated with the subscriber, via a computer network and internet connection, a selection of non-textual category data entered by the subscriber via an interface of one of the first subscriber device and the second subscriber device, and a plurality of subscriber interest category data entered by the subscriber via the interface of one of the first subscriber device and the second subscriber device; identifying content associated with the non-textual category data and content associated with the subscriber interest category data; creating, by the channel personalization engine, a subscriber channel associated with the subscriber and configured to stream at least a portion of the content associated with the non-textual category data to the subscriber via the computer network and internet connection, and the subscriber channel configured to stream at least a portion of the content associated with the subscriber interest category data to the subscriber via the computer network and internet connection to at least one of the first subscriber device and the second subscriber device, the subscriber channel including the content associated with the non-textual category data and including the content associated with the subscriber interest category data, wherein the subscriber channel is a customized subscriber channel of the subscriber created by the channel personalization engine at least in part responsive to the non-textual category data entered by the subscriber and the plurality of subscriber interest category data entered by the subscriber; streaming, through the subscriber channel from the channel personalization engine via the computer network and internet connection to the first subscriber device, the portion of the content associated with the non-textual category data to the subscriber in a first format configured for display on the first subscriber device; streaming, through the subscriber channel from the channel personalization engine to the second subscriber device, the portion of the content associated with the subscriber interest category data to the subscriber in a second format configured for display on the second subscriber device during a time period of continuous transmission of the content associated with the non-textual category data from the channel personalization engine to the subscriber in the first format configured for display on the first subscriber device; receiving, by the channel personalization engine via the computer network and internet connection from a first user device, data entered into an interface of the first user device including at least one of second non-textual category data and user interest category data, wherein the first user device is a different device than the first subscriber device and the second subscriber device; determining, by the channel personalization engine, that a first user associated with the first user device has an interest in a portion of content of the subscriber channel, the determining at least in part responsive to the non-textual category data and the user interest category data entered by the first user via the first user device; streaming the portion of content of the subscriber channel to the first user via the first user device; and restricting the first user device's access of the subscriber channel to the portion of the content of the subscriber channel in which the first user associated with the first user device is determined to have the interest.

1. A computer implemented method for managing electronically delivered information channels, comprising: receiving, by a computing device having a channel personalization engine, from one of a first subscriber device associated with a subscriber and a second subscriber device associated with the subscriber, via a computer network and internet connection, a selection of non-textual category data entered by the subscriber via an interface of one of the first subscriber device and the second subscriber device, and a plurality of subscriber interest category data entered by the subscriber via the interface of one of the first subscriber device and the second subscriber device; identifying content associated with the non-textual category data and content associated with the subscriber interest category data; creating, by the channel personalization engine, a subscriber channel associated with the subscriber and configured to stream at least a portion of the content associated with the non-textual category data to the subscriber via the computer network and internet connection, and the subscriber channel configured to stream at least a portion of the content associated with the subscriber interest category data to the subscriber via the computer network and internet connection to at least one of the first subscriber device and the second subscriber device, the subscriber channel including the content associated with the non-textual category data and including the content associated with the subscriber interest category data, wherein the subscriber channel is a customized subscriber channel of the subscriber created by the channel personalization engine at least in part responsive to the non-textual category data entered by the subscriber and the plurality of subscriber interest category data entered by the subscriber; streaming, through the subscriber channel from the channel personalization engine via the computer network and internet connection to the first subscriber device, the portion of the content associated with the non-textual category data to the subscriber in a first format configured for display on the first subscriber device; streaming, through the subscriber channel from the channel personalization engine to the second subscriber device, the portion of the content associated with the subscriber interest category data to the subscriber in a second format configured for display on the second subscriber device during a time period of continuous transmission of the content associated with the non-textual category data from the channel personalization engine to the subscriber in the first format configured for display on the first subscriber device; receiving, by the channel personalization engine via the computer network and internet connection from a first user device, data entered into an interface of the first user device including at least one of second non-textual category data and user interest category data, wherein the first user device is a different device than the first subscriber device and the second subscriber device; determining, by the channel personalization engine, that a first user associated with the first user device has an interest in a portion of content of the subscriber channel, the determining at least in part responsive to the non-textual category data and the user interest category data entered by the first user via the first user device; streaming the portion of content of the subscriber channel to the first user via the first user device; and restricting the first user device's access of the subscriber channel to the portion of the content of the subscriber channel in which the first user associated with the first user device is determined to have the interest. 17. The computer implemented method of claim 1 , comprising: simultaneously providing content of the subscriber channel to the subscriber via at least one of the first subscriber device and the second subscriber device, and to a user different than the subscriber via at least one user device.

2. An image processing method; the method operating on image data, the image data defining an image that includes a first number of locations, the image having an image characteristic relative to each of the locations; the method measuring the image characteristic for the image to a degree of statistical significance; the method comprising steps of: for each of a second number of locations in the image, each of which is randomly selected, operating on the image data to obtain respective sample result data, each location's sample result data measuring the image characteristic relative to the location; each location's sample result data including, for each of a set of two or more directions extending from the location, a respective data item; and combining the respective sample result data of the second number of locations to obtain image result data; the second number being smaller than the first number but sufficient that the image result data measure the image characteristic for the image to the degree of statistical significance; the step of combining the respective sample result data comprising a substep of combining, for each of the set of two or more directions, the respective data items to obtain a respective direction data item.

2. An image processing method; the method operating on image data, the image data defining an image that includes a first number of locations, the image having an image characteristic relative to each of the locations; the method measuring the image characteristic for the image to a degree of statistical significance; the method comprising steps of: for each of a second number of locations in the image, each of which is randomly selected, operating on the image data to obtain respective sample result data, each location's sample result data measuring the image characteristic relative to the location; each location's sample result data including, for each of a set of two or more directions extending from the location, a respective data item; and combining the respective sample result data of the second number of locations to obtain image result data; the second number being smaller than the first number but sufficient that the image result data measure the image characteristic for the image to the degree of statistical significance; the step of combining the respective sample result data comprising a substep of combining, for each of the set of two or more directions, the respective data items to obtain a respective direction data item. 3. The method of claim 2 in which each of the respective data items in each location's sample result data indicates a distance, each direction data item being an average of distances indicated by the direction's respective data items.

9. The method of claim 1 , wherein identifying a matching activation phrase within the confidence threshold comprises: determining that the detected first speech matches the matching activation phrase with a confidence that exceeds a first confidence threshold.

9. The method of claim 1 , wherein identifying a matching activation phrase within the confidence threshold comprises: determining that the detected first speech matches the matching activation phrase with a confidence that exceeds a first confidence threshold. 11. The method of claim 9 , wherein the first confidence threshold is higher than the second confidence threshold.

15. A computer readable storage medium bearing computer executable instructions implementable on a physical machine, for annotating instances of objects, comprising: configuring a plurality of object instances to be annotated by annotations of different types, wherein an annotation of at least one object instance is a value of a specified type; and providing an interface configured to provide a set of annotation operations associated with said annotation of the at least one object instance, wherein said set of annotation operations are configured to annotate data associated with said annotation of the at least one object instance using a type corresponding to said specified type, wherein said set of annotation operations comprises a retrieve operation, wherein said retrieve operation is configurable to retrieve annotations according to a weakly typed scenario and a strongly typed scenario, wherein a particular type is used as a search key in the weakly typed scenario, and wherein a generic parameter is used as the search key in the strongly typed scenario.

15. A computer readable storage medium bearing computer executable instructions implementable on a physical machine, for annotating instances of objects, comprising: configuring a plurality of object instances to be annotated by annotations of different types, wherein an annotation of at least one object instance is a value of a specified type; and providing an interface configured to provide a set of annotation operations associated with said annotation of the at least one object instance, wherein said set of annotation operations are configured to annotate data associated with said annotation of the at least one object instance using a type corresponding to said specified type, wherein said set of annotation operations comprises a retrieve operation, wherein said retrieve operation is configurable to retrieve annotations according to a weakly typed scenario and a strongly typed scenario, wherein a particular type is used as a search key in the weakly typed scenario, and wherein a generic parameter is used as the search key in the strongly typed scenario. 17. The computer readable storage medium according to claim 15 , further comprising of configuring said set of operations to one of (a) adding said annotation of the at least one object instance, (b) retrieving said annotation of the at least one object instance, and (c) removing said annotation of the at least one object instance.

5. The method of claim 1 , where determining that the one or more search terms are associated with the particular domain name includes: determining that the one or more search terms match information identifying a particularly entity, the information identifying the particular entity being included in a data structure, and the data structure including information identifying a plurality of entities.

5. The method of claim 1 , where determining that the one or more search terms are associated with the particular domain name includes: determining that the one or more search terms match information identifying a particularly entity, the information identifying the particular entity being included in a data structure, and the data structure including information identifying a plurality of entities. 7. The method of claim 5 , where the plurality of entities includes a plurality of: a particular news source, a particular store, a particular brand, a particular manufacturer, a particular product category, a particular product model, a particular location, a particular individual, or a particular organization.

1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, context data from a client device of a user; selecting, by the one or more computers, a user context corresponding to the context data from the client device, the user context being selected from among a plurality of user contexts, and the user context indicating a level of complexity of speech that the user is likely able to comprehend at a given time when the context data was received; selecting, by the one or more computers and from among a plurality of candidate text segments that correspond to different levels of complexity of speech, the text segment for text-to-speech synthesis by a text-to-speech module that best matches the selected user context; generating, by the one or more computers, audio data comprising a synthesized utterance of the selected text segment using the text-to-speech module; and providing, by the one or more computers and to the client device, the audio data comprising the synthesized utterance of the selected text segment.

1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, context data from a client device of a user; selecting, by the one or more computers, a user context corresponding to the context data from the client device, the user context being selected from among a plurality of user contexts, and the user context indicating a level of complexity of speech that the user is likely able to comprehend at a given time when the context data was received; selecting, by the one or more computers and from among a plurality of candidate text segments that correspond to different levels of complexity of speech, the text segment for text-to-speech synthesis by a text-to-speech module that best matches the selected user context; generating, by the one or more computers, audio data comprising a synthesized utterance of the selected text segment using the text-to-speech module; and providing, by the one or more computers and to the client device, the audio data comprising the synthesized utterance of the selected text segment. 4. The method of claim 1 , wherein receiving the context data comprises receiving data indicating a location, speed, or movement pattern of the client device; and wherein selecting the user context comprises selecting the user context based on the location, speed, or movement pattern of the client device indicated by the context data.

1. A method for routing calls comprising: receiving a call from a customer; extracting features from an utterance of the call; based on the extracted features, predicting a class and a complexity of a dialogue to be conducted between the customer and an agent, wherein the class c of the dialogue is computed according to Equation 1: p θ ⁡ ( c ❘ d ) = 1 1 + e - ( θ 0 c + θ 1 c · ϕ ⁡ ( d ) ) ( 1 ) where φ(d) is a feature vector derived from the features extracted from the utterance d; θ c vector of parameters to learn for each dialogue class c; and θ 0 c is a regularization vector; with a routing model, generating a routing strategy for steering the call to one of a plurality of types of agent, based on the predicted class and complexity of the dialogue and a cost assigned to the type of agent, a first of the plurality of types of agent being assigned a higher cost than a second of the types of agent; and outputting the routing strategy, wherein at least one of the extracting features, predicting the class and the complexity, and generating the routing strategy is performed with a processor.

1. A method for routing calls comprising: receiving a call from a customer; extracting features from an utterance of the call; based on the extracted features, predicting a class and a complexity of a dialogue to be conducted between the customer and an agent, wherein the class c of the dialogue is computed according to Equation 1: p θ ⁡ ( c ❘ d ) = 1 1 + e - ( θ 0 c + θ 1 c · ϕ ⁡ ( d ) ) ( 1 ) where φ(d) is a feature vector derived from the features extracted from the utterance d; θ c vector of parameters to learn for each dialogue class c; and θ 0 c is a regularization vector; with a routing model, generating a routing strategy for steering the call to one of a plurality of types of agent, based on the predicted class and complexity of the dialogue and a cost assigned to the type of agent, a first of the plurality of types of agent being assigned a higher cost than a second of the types of agent; and outputting the routing strategy, wherein at least one of the extracting features, predicting the class and the complexity, and generating the routing strategy is performed with a processor. 13. A computer program product comprising a non-transitory recording medium storing instructions, which when executed on a computer, causes the computer to perform the method of claim 1 .

1. A proofing tool for a computer-aided design (CAD) object having a plurality of drawing notes, the tool stored in a memory of a computer system having a processor, the memory storing the CAD object, the tool comprising: an extractor operable to extract the plurality of drawing notes from the CAD object; a rule module to obtain a rule from the memory, the rule including a plurality of keywords, the rule being required for the CAD object and conveying information relating to the manufacturing of the CAD object; a comparator operable to compare the plurality of extracted drawing notes with the rule; and a tagging module operable to generate a flag when the plurality of extracted drawing notes do not satisfy the rule.

1. A proofing tool for a computer-aided design (CAD) object having a plurality of drawing notes, the tool stored in a memory of a computer system having a processor, the memory storing the CAD object, the tool comprising: an extractor operable to extract the plurality of drawing notes from the CAD object; a rule module to obtain a rule from the memory, the rule including a plurality of keywords, the rule being required for the CAD object and conveying information relating to the manufacturing of the CAD object; a comparator operable to compare the plurality of extracted drawing notes with the rule; and a tagging module operable to generate a flag when the plurality of extracted drawing notes do not satisfy the rule. 11. The tool of claim 1 , wherein the CAD object includes at least one of a CAD model of an apparatus and a CAD drawing of an apparatus.

8. The computer readable-media as recited in claim 1 , wherein the instructions perform the step of applying a filtering process to a selected term.

8. The computer readable-media as recited in claim 1 , wherein the instructions perform the step of applying a filtering process to a selected term. 13. The computer readable-media as recited in claim 8 , wherein the filtering process comprises comparing a consonant pair at the start of the misspelled entry and of a selected term.

1. A computer-implemented method for generating an image configured to program a parallel machine from source code, the method comprising: converting source code of an uncompiled executable software application into an automaton comprising a plurality of interconnected states; converting the automaton into a netlist, the netlist comprising instances corresponding to states of the automaton, wherein the instances correspond to hardware elements of the parallel machine, wherein converting the automaton into a netlist includes grouping states of the automaton together based on a physical design of the parallel machine; and converting the netlist into the image, the image comprising compiled binary data to program the parallel machine to correspond to the instances of the netlist, such that the compiled binary data is arranged to program the parallel machine to provide the functionality specified by the source code of the uncompiled executable software application when the image is loaded onto the parallel machine.

1. A computer-implemented method for generating an image configured to program a parallel machine from source code, the method comprising: converting source code of an uncompiled executable software application into an automaton comprising a plurality of interconnected states; converting the automaton into a netlist, the netlist comprising instances corresponding to states of the automaton, wherein the instances correspond to hardware elements of the parallel machine, wherein converting the automaton into a netlist includes grouping states of the automaton together based on a physical design of the parallel machine; and converting the netlist into the image, the image comprising compiled binary data to program the parallel machine to correspond to the instances of the netlist, such that the compiled binary data is arranged to program the parallel machine to provide the functionality specified by the source code of the uncompiled executable software application when the image is loaded onto the parallel machine. 15. The method of claim 1 , wherein the instances of the netlist comprise general purpose instances and special purpose instances, wherein the general purpose instances correspond to general purpose states of the automaton and the special purpose instances correspond to special purpose states of the automaton.

24. The new device of claim 15 wherein the display means comprises: an upper substrate consisting of a translucent material, the upper substrate having an exterior surface and an interior surface, the input pen means being configured to be manipulated by the user proximate the upper substrate; a lower substrate spaced from the upper substrate, the lower substrate having an exterior surface and an interior surface; a plurality of first electrodes; a plurality of second electrodes, the second electrodes intersecting the first electrodes; electro-optic material within an interstitial region between the upper and lower substrates; and spacing means disposed between the interior surface of the upper substrate and the interior surface of the lower substrate for preventing relative movement between the upper and lower substrates in response to contact by the input pen means against the exterior surface of the upper substrate, so as to prevent display distortion; and wherein the pen sense control means is connected to the first and second electrodes and the input pen means and responsive to electrical coupling of the first and second electrodes with the input pen means for producing position signals correlated to positions of the input pen means with respect to crosspoints corresponding to intersections of the first and second electrodes as the user manipulates the input pen means; and wherein the display control means is connected to the first and second electrodes and responsive to the position signals for energizing the electro-optic material in the vicinity of corresponding crosspoints.

24. The new device of claim 15 wherein the display means comprises: an upper substrate consisting of a translucent material, the upper substrate having an exterior surface and an interior surface, the input pen means being configured to be manipulated by the user proximate the upper substrate; a lower substrate spaced from the upper substrate, the lower substrate having an exterior surface and an interior surface; a plurality of first electrodes; a plurality of second electrodes, the second electrodes intersecting the first electrodes; electro-optic material within an interstitial region between the upper and lower substrates; and spacing means disposed between the interior surface of the upper substrate and the interior surface of the lower substrate for preventing relative movement between the upper and lower substrates in response to contact by the input pen means against the exterior surface of the upper substrate, so as to prevent display distortion; and wherein the pen sense control means is connected to the first and second electrodes and the input pen means and responsive to electrical coupling of the first and second electrodes with the input pen means for producing position signals correlated to positions of the input pen means with respect to crosspoints corresponding to intersections of the first and second electrodes as the user manipulates the input pen means; and wherein the display control means is connected to the first and second electrodes and responsive to the position signals for energizing the electro-optic material in the vicinity of corresponding crosspoints. 26. The device of claim 24 wherein the pen signal is connected to the first and second electrodes to be transmitted from the vicinity of corresponding crosspoints and received by the input pen means for producing the position signals.

1. A decision making mechanism of an active perception module of a robot, the active perception module including at least one processing unit executing one or more instructions from a non-transitory machine-readable medium, said decision making mechanism being operable to decide on at least one prospective action of a robot from a set of actions of said robot by: the active perception module computing a prior probabilistic representation of a prior environment state; the active perception module updating of said prior probabilistic representation with targets of a new observation following the at least one prospective action after an action period, the action period comprising a period for incorporating an action observation pair into an update of an environment state, thereby reducing at least one uncertainty in a posterior probabilistic representation of a posterior environment state to be reached after an appliance of said at least one prospective action, wherein said posterior probabilistic representation is a probabilistic representation resulting from said updating; the active perception module determining an information gain between said prior probabilistic representation and said posterior probabilistic representation by use of at least one information theoretic measure; and the active perception module evaluating said at least one prospective action by estimating the costs of executing said at least one prospective action during the action period and estimating said information gain at the end of the action period.

1. A decision making mechanism of an active perception module of a robot, the active perception module including at least one processing unit executing one or more instructions from a non-transitory machine-readable medium, said decision making mechanism being operable to decide on at least one prospective action of a robot from a set of actions of said robot by: the active perception module computing a prior probabilistic representation of a prior environment state; the active perception module updating of said prior probabilistic representation with targets of a new observation following the at least one prospective action after an action period, the action period comprising a period for incorporating an action observation pair into an update of an environment state, thereby reducing at least one uncertainty in a posterior probabilistic representation of a posterior environment state to be reached after an appliance of said at least one prospective action, wherein said posterior probabilistic representation is a probabilistic representation resulting from said updating; the active perception module determining an information gain between said prior probabilistic representation and said posterior probabilistic representation by use of at least one information theoretic measure; and the active perception module evaluating said at least one prospective action by estimating the costs of executing said at least one prospective action during the action period and estimating said information gain at the end of the action period. 14. The decision making mechanism according to claim 1 , wherein the decision making mechanism is configured to terminate said deciding if a desired quality criteria is reached.

15. A non-transitory machine readable medium that stores instructions which when performed by a machine, cause the machine to perform operations comprising: determining a social networking service that a social networking application is associated with; locating in the social networking application a custom markup language tag, the custom markup language tag written in a first custom markup language, the custom markup language tag specifying an instruction to implement a particular functionality; determining that the custom markup language tag should be replaced either with a set of one or more source code commands, or with a second custom markup language tag defined by the social networking service, and written in a second custom markup language, the determination based upon the determined social networking service and one or more criteria, the second custom markup language tag and the set of source code commands both containing instructions, which when executed, implement the particular functionality of the custom markup language tag in the first language; responsive to a determination that the custom markup language tag should be replaced with the set of source code commands, replacing the custom markup language tag with the set of source code commands, the set of source code commands being a source code language that is not a markup language; and responsive to a determination that the custom markup language tag should be replaced with the second custom markup language tag, replacing the custom markup language tag with the second custom markup language tag.

15. A non-transitory machine readable medium that stores instructions which when performed by a machine, cause the machine to perform operations comprising: determining a social networking service that a social networking application is associated with; locating in the social networking application a custom markup language tag, the custom markup language tag written in a first custom markup language, the custom markup language tag specifying an instruction to implement a particular functionality; determining that the custom markup language tag should be replaced either with a set of one or more source code commands, or with a second custom markup language tag defined by the social networking service, and written in a second custom markup language, the determination based upon the determined social networking service and one or more criteria, the second custom markup language tag and the set of source code commands both containing instructions, which when executed, implement the particular functionality of the custom markup language tag in the first language; responsive to a determination that the custom markup language tag should be replaced with the set of source code commands, replacing the custom markup language tag with the set of source code commands, the set of source code commands being a source code language that is not a markup language; and responsive to a determination that the custom markup language tag should be replaced with the second custom markup language tag, replacing the custom markup language tag with the second custom markup language tag. 19. The machine readable medium of claim 15 , wherein the instructions further comprise instructions, which when performed by the machine, cause the machine to perform the operations further comprising: locating in the social networking application a third custom markup language tag in the first custom markup language, the third custom markup language tag specifying an instruction to implement a second particular functionality; determining that the third custom markup language tag should be replaced either with a fourth custom markup language tag in the second language, or with a second set of one or more source code commands based upon the determined social networking service and based upon the one or more criteria, the fourth custom markup language tag and the second set of source code commands, both containing instructions, which when executed implement the second particular functionality of the third custom markup language tag; responsive to a determination that the custom markup language tag should be replaced with the set of source commands, replacing the third custom markup language tag with the second set of source code commands, the second set of source code commands being a source code language that is not a markup language; and responsive to a determination that the third custom markup language tag should be replaced with the fourth custom markup language tag, replacing the third custom markup language tag with the fourth custom markup language tag.

1. A method for automatically ascertaining a geographic location, the method comprising: capturing a digital image of at least a portion of sky visible upward from the geographic location; automatically generating, by a processor, a plurality of digital sky light scattering models, each sky light scattering model characterizing light, as the light would appear from a corresponding candidate geographic location after the light was emitted by at least one light source disposed proximate the candidate geographic location and subsequently scattered by particulates disposed in an atmosphere proximate the at least one light source; automatically associating, by a processor, each sky light scattering model with the corresponding candidate geographic location; automatically searching, by a processor, the plurality of sky light scattering models for a matching sky light scattering model that matches the image within a match criterion; and as a result of the searching, the matching sky light scattering model is found, automatically outputting, by a processor, to at least one of: a display panel, a map selector, a guidance system, a navigation system and/or a control system, the candidate geographic location associated with the matching sky light scattering model as the ascertained geographic location.

1. A method for automatically ascertaining a geographic location, the method comprising: capturing a digital image of at least a portion of sky visible upward from the geographic location; automatically generating, by a processor, a plurality of digital sky light scattering models, each sky light scattering model characterizing light, as the light would appear from a corresponding candidate geographic location after the light was emitted by at least one light source disposed proximate the candidate geographic location and subsequently scattered by particulates disposed in an atmosphere proximate the at least one light source; automatically associating, by a processor, each sky light scattering model with the corresponding candidate geographic location; automatically searching, by a processor, the plurality of sky light scattering models for a matching sky light scattering model that matches the image within a match criterion; and as a result of the searching, the matching sky light scattering model is found, automatically outputting, by a processor, to at least one of: a display panel, a map selector, a guidance system, a navigation system and/or a control system, the candidate geographic location associated with the matching sky light scattering model as the ascertained geographic location. 12. The method according to claim 1 , wherein for each sky light scattering model, characterizing the light comprises characterizing color of the light, color pattern of the light, intensity of the light, intensity pattern of the light, continuity of the light, location of the light in the sky, height of the light in the sky, width of the light in the sky and/or shape of the light in the sky, as apparent from the corresponding candidate geographic location.

1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method comprising: causing, by a computer system, an executable program to be run; obtaining, by a computer system, a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; obtaining, by a computer system, an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; extracting, by a computer system, class information from the general ontology; generating, by a computer system, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; generating, by a computer system, a programming interface based on the class information, wherein the programming interface allows the executable program to access the supplemental information; and providing, by a computer system, the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application to be made available via the executable program without recompiling the entire executable program.

1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method comprising: causing, by a computer system, an executable program to be run; obtaining, by a computer system, a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; obtaining, by a computer system, an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; extracting, by a computer system, class information from the general ontology; generating, by a computer system, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; generating, by a computer system, a programming interface based on the class information, wherein the programming interface allows the executable program to access the supplemental information; and providing, by a computer system, the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application to be made available via the executable program without recompiling the entire executable program. 11. The method of claim 1 , wherein the supplemental information includes a data model for encoding metadata and knowledge on the Semantic Web using facts expressed as triples.

36. The method of claim 35 , wherein providing the user with a visual representation comprises: generating a graphical representation that emphasizes distinctions between facts of different objects.

36. The method of claim 35 , wherein providing the user with a visual representation comprises: generating a graphical representation that emphasizes distinctions between facts of different objects. 37. The method of claim 36 , wherein a fact is comprised of an attribute and a value, wherein multiple objects possess a same attribute, and wherein the graphical representation emphasizes distinctions between different values of an attribute possessed by multiple objects.

14. A method executed by a relational database management system of the type wherein a table function returns a set of result rows which are represented in an SQL statement by a container for the table function, the relational database management system executing on a processor that has access to a storage device and the method comprising the steps of: receiving the SQL statement; making an SQL string which does not include the table function and which, when executed, will return a set of result rows which is equivalent to the set of result rows returned by the container function; and rewriting the SQL statement such that the container is replaced with the SQL string prior to executing the SQL statement.

14. A method executed by a relational database management system of the type wherein a table function returns a set of result rows which are represented in an SQL statement by a container for the table function, the relational database management system executing on a processor that has access to a storage device and the method comprising the steps of: receiving the SQL statement; making an SQL string which does not include the table function and which, when executed, will return a set of result rows which is equivalent to the set of result rows returned by the container function; and rewriting the SQL statement such that the container is replaced with the SQL string prior to executing the SQL statement. 19. The method set forth in claim 14 wherein the step of making the SQL string is optional and the method further comprises the step performed when the step of making the SQL string is not performed of: executing the table function when the SQL statement is executed.

13. The computing device of claim 8 , wherein the one or more programs comprise instructions for computing the Unicode weights for the strings s p s p+1 . . . s n and t p t p+1 . . . t m are computed, the computation comprising: for each character, performing a lookup in a Unicode weight table to identify a respective primary weight, a respective accent weight, and a respective case-weight; forming a primary Unicode weight w p as a concatenation of the identified primary weights; forming an accent Unicode weight w a as a concatenation of the identified accent weights; forming a case Unicode weight w c as a concatenation of the identified case weights; and forming the Unicode weight as a concatenation w p +w a +w c of the primary Unicode weight, the accent Unicode weight, and the case Unicode weight.

13. The computing device of claim 8 , wherein the one or more programs comprise instructions for computing the Unicode weights for the strings s p s p+1 . . . s n and t p t p+1 . . . t m are computed, the computation comprising: for each character, performing a lookup in a Unicode weight table to identify a respective primary weight, a respective accent weight, and a respective case-weight; forming a primary Unicode weight w p as a concatenation of the identified primary weights; forming an accent Unicode weight w a as a concatenation of the identified accent weights; forming a case Unicode weight w c as a concatenation of the identified case weights; and forming the Unicode weight as a concatenation w p +w a +w c of the primary Unicode weight, the accent Unicode weight, and the case Unicode weight. 14. The computing device of claim 13 , wherein the collation order is in accordance with a specified language, and the Unicode weight table is selected according to the specified language.

42. The method of claim 41 comprising the further step of: (d) combining the accumulated label votes together to provide a likelihood score for the subject word.

42. The method of claim 41 comprising the further step of: (d) combining the accumulated label votes together to provide a likelihood score for the subject word. 43. The method of claim 42 comprising the further step of: (e) repeating steps (c) and (d) for each word in the vocabulary; and (f) selecting the n words having the highest likelihood scores as candidate words, where n is a predefined integer.

5. A server computing device including one or more processors and a non-transitory memory having instructions stored thereon that, when executed by the one or more processors, causes the server computing device to perform operations comprising: obtaining data specifying future travel plans for a user associated with a client computing device, the future travel plans being in a region that utilizes a language that is foreign to the user; predicting, based on the future travel plans, an expected future offline period during which the client computing device is unlikely to have a network connection; determining an expected path of travel by the user during the expected future offline period; identifying one or more points of along the expected path of travel, each point of interest being indicative of a specific location where the user is likely to require translation of foreign language text, wherein identifying a particular point of interest as one of the one or more points of interest is based on (1) known information about the availability of translated foreign language text at the particular point of interest, and (2) a likelihood that the user will require translation of foreign language text at the particular point of interest exceeding a threshold likelihood; obtaining portions of foreign language text associated with the one or more points of interest, wherein each portion of foreign language text is intended to aid the user while he/she is at the corresponding point of interest; obtaining, prior to the expected future offline period, translated portions of text representing translations of the portions of foreign language text to a preferred language of the user; and transmitting, to the client computing device prior to the expected future offline period, the translated portions of text and instructions for outputting the translated portions of text, wherein receipt of the translated portions of text and the instructions causes the client computing device to: determine an output time or an output location specified by a particular instruction of the transmitted instructions, detect that an output condition is satisfied when a current time or a current location of the client computing device matches the output time or the output location, generate a rendered display comprising the translated portions of text, and display, on a display of the client computing device, the rendered display in response to detecting that the output condition is satisfied.

5. A server computing device including one or more processors and a non-transitory memory having instructions stored thereon that, when executed by the one or more processors, causes the server computing device to perform operations comprising: obtaining data specifying future travel plans for a user associated with a client computing device, the future travel plans being in a region that utilizes a language that is foreign to the user; predicting, based on the future travel plans, an expected future offline period during which the client computing device is unlikely to have a network connection; determining an expected path of travel by the user during the expected future offline period; identifying one or more points of along the expected path of travel, each point of interest being indicative of a specific location where the user is likely to require translation of foreign language text, wherein identifying a particular point of interest as one of the one or more points of interest is based on (1) known information about the availability of translated foreign language text at the particular point of interest, and (2) a likelihood that the user will require translation of foreign language text at the particular point of interest exceeding a threshold likelihood; obtaining portions of foreign language text associated with the one or more points of interest, wherein each portion of foreign language text is intended to aid the user while he/she is at the corresponding point of interest; obtaining, prior to the expected future offline period, translated portions of text representing translations of the portions of foreign language text to a preferred language of the user; and transmitting, to the client computing device prior to the expected future offline period, the translated portions of text and instructions for outputting the translated portions of text, wherein receipt of the translated portions of text and the instructions causes the client computing device to: determine an output time or an output location specified by a particular instruction of the transmitted instructions, detect that an output condition is satisfied when a current time or a current location of the client computing device matches the output time or the output location, generate a rendered display comprising the translated portions of text, and display, on a display of the client computing device, the rendered display in response to detecting that the output condition is satisfied. 6. The server computing device of claim 5 , wherein the expected future offline period is defined between two overnight stays by the user at one or more hotels, and wherein the server computing device obtains and transmits the translated portions of text to the client computing device during a first of the two overnight stays.

1. A method for configuring and executing card content management (CCM) operations in a declarative manner, comprising: composing a CCM operation declaration, wherein each CCM operation includes one or more CCM scripts, the composing the CCM operation declaration including graphically authoring the CCM operation declaration, wherein the graphically authoring includes dragging and dropping icons representing scripts into a field and connecting the icons into a sequence using constructs; storing the CCM operation declaration in memory; when provisioning is needed, fetching applicable scripts for the CCM operation declaration from the memory and creating parsed scripts by parsing the applicable scripts; preparing an execution context needed for each script in the CCM operation declaration, wherein all needed parameter values are set and the parsed scripts are stored in an iterator in a desired order of execution; and executing the scripts in an order specified in the CCM operation declaration.

1. A method for configuring and executing card content management (CCM) operations in a declarative manner, comprising: composing a CCM operation declaration, wherein each CCM operation includes one or more CCM scripts, the composing the CCM operation declaration including graphically authoring the CCM operation declaration, wherein the graphically authoring includes dragging and dropping icons representing scripts into a field and connecting the icons into a sequence using constructs; storing the CCM operation declaration in memory; when provisioning is needed, fetching applicable scripts for the CCM operation declaration from the memory and creating parsed scripts by parsing the applicable scripts; preparing an execution context needed for each script in the CCM operation declaration, wherein all needed parameter values are set and the parsed scripts are stored in an iterator in a desired order of execution; and executing the scripts in an order specified in the CCM operation declaration. 5. The method as recited in claim 1 , wherein the CCM operation declaration is written in one of extensible markup language (XML) and Javascript object notation (JSON).

17. The computer program product of claim 15 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the computer readable program code instructions for execution by the computer processing unit further cause the computer processing unit to classify the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories.

17. The computer program product of claim 15 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the computer readable program code instructions for execution by the computer processing unit further cause the computer processing unit to classify the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories. 18. The computer program product of claim 17 , wherein the computer readable program code instructions for execution by the computer processing unit further cause the computer processing unit to identify the generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having the common occupational identity indicia by: recognizing a type of network access used by the user to submit the text string query; determining a predominant occupational identity associated with the recognized type of network access; and retrieving search history common to pluralities of users that share the determined predominant occupational identity as the generic occupational identity search data.

1. A method for establishing an aid in diagnosis of a complex system of an aircraft comprising a plurality of sub-systems, at least one sub-system of the plurality of sub-systems comprising circuitry configured to monitor and provide notifications regarding at least one detected event, the method using: a failure condition graph at least partially modeling the complex system, the failure condition graph comprising a plurality of peaks, each peak being connected by a logic implication relationship to at least one other peak of the plurality of peaks, the plurality of peaks comprising: one peak representing a failure condition event; and one peak representing only at least one element of the complex system, the at least one element being able to break down, and the method comprising: receiving at least one message of notification of occurrence of the at least one detected event; creating a set of failure events, each said failure event of the set of failure events being associated with a peak of the failure condition graph linked to the at least one received notification message; for each said failure event of the set of failure events, constructing, from the failure condition graph, at least one logic expression leading to the failure event, the at least one logic expression being based on elements of the complex system; creating at least one group of failure events of the set of failure events, the at least one element being common to two logic expressions linked to two separate failure events of the at least one group, the logic expressions associated with the failure events of the at least one group representing a diagnosis relating to the at least one detected event; and determining minimal vertexes of the logic expressions of the failure events of the at least one group of failure events, the minimal vertexes forming minimal diagnoses of the diagnosis relating to the at least one detected event.

1. A method for establishing an aid in diagnosis of a complex system of an aircraft comprising a plurality of sub-systems, at least one sub-system of the plurality of sub-systems comprising circuitry configured to monitor and provide notifications regarding at least one detected event, the method using: a failure condition graph at least partially modeling the complex system, the failure condition graph comprising a plurality of peaks, each peak being connected by a logic implication relationship to at least one other peak of the plurality of peaks, the plurality of peaks comprising: one peak representing a failure condition event; and one peak representing only at least one element of the complex system, the at least one element being able to break down, and the method comprising: receiving at least one message of notification of occurrence of the at least one detected event; creating a set of failure events, each said failure event of the set of failure events being associated with a peak of the failure condition graph linked to the at least one received notification message; for each said failure event of the set of failure events, constructing, from the failure condition graph, at least one logic expression leading to the failure event, the at least one logic expression being based on elements of the complex system; creating at least one group of failure events of the set of failure events, the at least one element being common to two logic expressions linked to two separate failure events of the at least one group, the logic expressions associated with the failure events of the at least one group representing a diagnosis relating to the at least one detected event; and determining minimal vertexes of the logic expressions of the failure events of the at least one group of failure events, the minimal vertexes forming minimal diagnoses of the diagnosis relating to the at least one detected event. 11. The method according to claim 1 , wherein the one peak representing the failure condition event represents an interface between two of the plurality of sub-systems.

38. The storage medium of claim 33 , wherein the interface mechanism is an Application Program Interface (API) running in the external environment.

38. The storage medium of claim 33 , wherein the interface mechanism is an Application Program Interface (API) running in the external environment. 39. The storage medium of claim 38 , wherein a function in the late bound environment is called from within the external program environment using the API.

3. The apparatus according to claim 1 , further comprising a search unit configured to conduct a refined search for the document set using a keyword selected from keywords presented by the presentation unit, and to obtain a partial document set, and wherein the clustering unit calculates the statistical correlation degrees between the basic terms based on the partial document set, calculates the conceptual correlation degrees between the basic terms based on the general concept dictionary, and re-clusters the basic terms based on the weighted sums, the second selection unit re-selects keywords of respective clusters from the basic terms and the technical terms based on a re-clustering result of the basic terms, and the presentation unit presents the re-selected keywords.

3. The apparatus according to claim 1 , further comprising a search unit configured to conduct a refined search for the document set using a keyword selected from keywords presented by the presentation unit, and to obtain a partial document set, and wherein the clustering unit calculates the statistical correlation degrees between the basic terms based on the partial document set, calculates the conceptual correlation degrees between the basic terms based on the general concept dictionary, and re-clusters the basic terms based on the weighted sums, the second selection unit re-selects keywords of respective clusters from the basic terms and the technical terms based on a re-clustering result of the basic terms, and the presentation unit presents the re-selected keywords. 5. The apparatus according to claim 3 , wherein the presentation unit decides priority levels of respective documents included in the partial document set using a previously selected keyword, and presents information associated with respective documents included in the partial document set according to the priority levels.

26. A computer implemented method for website editing, the method comprising: providing an editor interface in a browser simultaneous with a website, the editor interface for editing the website, the editor interface comprising: a menu design interface, the menu design interface for allowing a user to modify media content of the website and comprising a simulated website menu representing a website menu; wherein the menu design interface allows a user to drag and drop media content from a media library to a simulated menu item in the simulated website menu to position the media content in a webpage corresponding to the simulated menu item; receiving user input through the editor interface; modifying website data corresponding to the website based on the user input; and updating display of the website within the browser based on the modified website data, wherein the website is updated in real-time based on the user input received via the editor interface.

26. A computer implemented method for website editing, the method comprising: providing an editor interface in a browser simultaneous with a website, the editor interface for editing the website, the editor interface comprising: a menu design interface, the menu design interface for allowing a user to modify media content of the website and comprising a simulated website menu representing a website menu; wherein the menu design interface allows a user to drag and drop media content from a media library to a simulated menu item in the simulated website menu to position the media content in a webpage corresponding to the simulated menu item; receiving user input through the editor interface; modifying website data corresponding to the website based on the user input; and updating display of the website within the browser based on the modified website data, wherein the website is updated in real-time based on the user input received via the editor interface. 38. The method of claim 26 , further comprising receiving the website data corresponding to the website over a network.

19. A non-transitory computer-readable storage device encoded with instructions which, when executed by one or more computers, cause the one or more computers to perform operations comprising: training each of a plurality of predictive models using training data, wherein the predictive models include two or more predictive models of a same type that are trained with different combinations of features of the training data; generating, for each of the plurality of trained predictive models, a respective score that represents an estimation of an effectiveness of the respective trained predictive model; receiving a request for a prediction that includes input data from a client system; in response to receiving the request for the prediction, selecting a first subset of the plurality of trained predictive models based on the respective scores of the trained predictive models in the first subset, wherein the plurality of trained predictive models includes the first subset and a second subset, each subset comprises at least one trained predictive model, the first subset and the second subset are disjoint sets, and the predictive models in the first subset have higher respective scores than predictive models that were not selected; obtaining a respective predictive output from only each of the selected predictive models in the first subset based on the request and using the input data; combining the predictive outputs to generate a result; and providing the result to the client system.

19. A non-transitory computer-readable storage device encoded with instructions which, when executed by one or more computers, cause the one or more computers to perform operations comprising: training each of a plurality of predictive models using training data, wherein the predictive models include two or more predictive models of a same type that are trained with different combinations of features of the training data; generating, for each of the plurality of trained predictive models, a respective score that represents an estimation of an effectiveness of the respective trained predictive model; receiving a request for a prediction that includes input data from a client system; in response to receiving the request for the prediction, selecting a first subset of the plurality of trained predictive models based on the respective scores of the trained predictive models in the first subset, wherein the plurality of trained predictive models includes the first subset and a second subset, each subset comprises at least one trained predictive model, the first subset and the second subset are disjoint sets, and the predictive models in the first subset have higher respective scores than predictive models that were not selected; obtaining a respective predictive output from only each of the selected predictive models in the first subset based on the request and using the input data; combining the predictive outputs to generate a result; and providing the result to the client system. 26. The storage device of claim 19 wherein the plurality of trained predictive models includes a Naïve Bayes model, a Perceptron model, a Support Vector Machine model, a linear regression model, a k-nearest neighbor model, or a logistic regression model.

1. A method programmed in a non-transitory memory of a device comprising: a. automatically accessing a web page; b. automatically analyzing web page content of the web page; c. automatically fact checking the web page content with the device by comparing the web page content with source information to determine the factual accuracy of the web page content, including computing a source result value based on source quantities and source ratings, wherein the source result value is used to determine a result of the fact checking, wherein fact checking includes a first fact check and a second fact check, wherein the first fact check and the second fact check each utilize a different set of fact checking criteria; and d. automatically indicating a status of the web page content in real-time based on the result of the comparison of the web page content with the source information.

1. A method programmed in a non-transitory memory of a device comprising: a. automatically accessing a web page; b. automatically analyzing web page content of the web page; c. automatically fact checking the web page content with the device by comparing the web page content with source information to determine the factual accuracy of the web page content, including computing a source result value based on source quantities and source ratings, wherein the source result value is used to determine a result of the fact checking, wherein fact checking includes a first fact check and a second fact check, wherein the first fact check and the second fact check each utilize a different set of fact checking criteria; and d. automatically indicating a status of the web page content in real-time based on the result of the comparison of the web page content with the source information. 16. The method of claim 1 further comprising detecting an entity within the web page content, and indicating a validity rating of the entity, wherein the validity rating includes statistical information regarding factual accuracy of comments made by the entity.

1. A computer-implemented method of automatically generating a coherence score for a text using a scoring model, comprising: identifying a plurality of lexical chains within a text to be scored with a processing system, wherein a lexical chain comprises a set of words spaced within the text, certain words in the lexical chain being non-contiguous; identifying a discourse element within the text with the processing system based on lookup operations with a computer database of discourse elements, wherein the discourse element comprises a word within the text; determining a coherence metric with the processing system based on a relationship between the lexical chains and the discourse element; wherein determining the coherence metric comprises determining: a first count of lexical chains that end before the discourse element; a second count of lexical chains that begin after the discourse element; and a third count of lexical chains that begin before and end after the discourse element; wherein the coherence metric is determined based on the first count, the second count, and the third count; generating a coherence score using the processing system by applying a scoring model to the coherence metric, wherein the scoring model comprises multiple weighted features whose feature weights are determined by training the scoring model relative to a plurality of training texts, the coherence score being combined with other non-lexical chain features by an automated essay evaluation engine to determine a transmitted quality level of the text.

1. A computer-implemented method of automatically generating a coherence score for a text using a scoring model, comprising: identifying a plurality of lexical chains within a text to be scored with a processing system, wherein a lexical chain comprises a set of words spaced within the text, certain words in the lexical chain being non-contiguous; identifying a discourse element within the text with the processing system based on lookup operations with a computer database of discourse elements, wherein the discourse element comprises a word within the text; determining a coherence metric with the processing system based on a relationship between the lexical chains and the discourse element; wherein determining the coherence metric comprises determining: a first count of lexical chains that end before the discourse element; a second count of lexical chains that begin after the discourse element; and a third count of lexical chains that begin before and end after the discourse element; wherein the coherence metric is determined based on the first count, the second count, and the third count; generating a coherence score using the processing system by applying a scoring model to the coherence metric, wherein the scoring model comprises multiple weighted features whose feature weights are determined by training the scoring model relative to a plurality of training texts, the coherence score being combined with other non-lexical chain features by an automated essay evaluation engine to determine a transmitted quality level of the text. 7. The method of claim 1 , wherein the discourse element identifies a continuation of a topic within the text.

9. A method for a text-to-speech (TTS) system to update individual entries in a phonetic dictionary, comprising the steps of: receiving an indication from an end-user that the TTS system has mispronounced at least one word; after receiving said indication, recording a verbal pronunciation of the at least one word as spoken by the end-user; determining a phonetic transcription that corresponds to the at least one word as spoken by the end-user; and storing the phonetic transcription in the dictionary.

9. A method for a text-to-speech (TTS) system to update individual entries in a phonetic dictionary, comprising the steps of: receiving an indication from an end-user that the TTS system has mispronounced at least one word; after receiving said indication, recording a verbal pronunciation of the at least one word as spoken by the end-user; determining a phonetic transcription that corresponds to the at least one word as spoken by the end-user; and storing the phonetic transcription in the dictionary. 13. The method of claim 9, further comprising the steps of: using the phonetic transcription to speak the at least one word back to the end-user for validation; and receiving an acceptance or a rejection of the phonetic transcription from the end-user.

20. A web agent creator embodied on a tangible computer readable medium coupled to a processor for creating a web agent to acquire product information from the world wide web, said web agent creator comprising: a web browser user interface, a pattern expression discovery algorithm coupled to said user interface, said algorithm including means for discovering patterns of product information, a results editor coupled to said user interface and said pattern expression discovery algorithm, said results editor having means for editing product information, an agent generator coupled to said user interface and said results editor, said generator having means for generating said web agent having characteristics determined by said algorithm, and a form value editor coupled to said user interface and said agent generator, said form value editor having means for setting parameters of said web agent, said web agent creator providing the tangible result of a web agent executable on a processor which together acquire product information from the world wide web.

20. A web agent creator embodied on a tangible computer readable medium coupled to a processor for creating a web agent to acquire product information from the world wide web, said web agent creator comprising: a web browser user interface, a pattern expression discovery algorithm coupled to said user interface, said algorithm including means for discovering patterns of product information, a results editor coupled to said user interface and said pattern expression discovery algorithm, said results editor having means for editing product information, an agent generator coupled to said user interface and said results editor, said generator having means for generating said web agent having characteristics determined by said algorithm, and a form value editor coupled to said user interface and said agent generator, said form value editor having means for setting parameters of said web agent, said web agent creator providing the tangible result of a web agent executable on a processor which together acquire product information from the world wide web. 22. The web agent creator according to claim 20 , wherein: said pattern expression discovery algorithm is an XPath discovery algorithm, said user interface indicates a DOM tree of text selected by the user interface to said XPath discovery algorithm, said results editor, said agent generator, and said form value editor.

15. A computer-implemented process comprising: processing user input to modify an electronic document, wherein the electronic document has associated comment data and activity data, wherein the comment data defines a collection of comments and comprises, for each comment, a reference to a location within the electronic document, data indicating a user that added the comment, and content of the comment, and wherein the activity data defines a collection of actions and comprises, for each action, data indicating a type of action, and data indicating a user associated with the action, presenting a graphical user interface including: a document pane configured to display a graphical representation of the electronic document, a graphical representation of comments, displayed in association with the document pane, based on the comment data associated with the electronic document, and a graphical representation of actions, displayed in associated with the document pane, based on the activity data associated with the electronic document; in response to an input associated with a displayed comment, marking the comment as resolved by setting the value associated with the comment to indicate the comment is resolved and by adding an action to the activity data associated with the electronic document to indicate the comment is resolved; and in response to an input associated with a displayed action related to a resolved comment, marking the comment as unresolved by setting the value associated with the resolved comment to indicate the comment is unresolved.

15. A computer-implemented process comprising: processing user input to modify an electronic document, wherein the electronic document has associated comment data and activity data, wherein the comment data defines a collection of comments and comprises, for each comment, a reference to a location within the electronic document, data indicating a user that added the comment, and content of the comment, and wherein the activity data defines a collection of actions and comprises, for each action, data indicating a type of action, and data indicating a user associated with the action, presenting a graphical user interface including: a document pane configured to display a graphical representation of the electronic document, a graphical representation of comments, displayed in association with the document pane, based on the comment data associated with the electronic document, and a graphical representation of actions, displayed in associated with the document pane, based on the activity data associated with the electronic document; in response to an input associated with a displayed comment, marking the comment as resolved by setting the value associated with the comment to indicate the comment is resolved and by adding an action to the activity data associated with the electronic document to indicate the comment is resolved; and in response to an input associated with a displayed action related to a resolved comment, marking the comment as unresolved by setting the value associated with the resolved comment to indicate the comment is unresolved. 16. The computer-implemented process of claim 15 , wherein displaying comments comprises displaying a graphical representation of only unresolved comments.

4. The method of claim 2 , wherein the UI is rendered in accordance with a UI rendering frame rate; and wherein updated custom rendering instructions are stored at the synchronization object at a custom instruction frame rate.

4. The method of claim 2 , wherein the UI is rendered in accordance with a UI rendering frame rate; and wherein updated custom rendering instructions are stored at the synchronization object at a custom instruction frame rate. 5. The method of claim 4 , wherein when application frame rate is less than the UI rendering frame rate, and wherein the method further comprises reusing custom rendering instructions for multiple frames of the UI.

33. A machine-implemented method comprising: identifying instances in a plurality of speech segments; creating feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances in the plurality of speech segments onto a feature space, wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments, which were provided in sound data for a speech synthesis system; clustering the feature vectors using a similarity measure in the feature space; and replacing the clustered instances corresponding to the clustered feature vectors within a radius by a single instance.

33. A machine-implemented method comprising: identifying instances in a plurality of speech segments; creating feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances in the plurality of speech segments onto a feature space, wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments, which were provided in sound data for a speech synthesis system; clustering the feature vectors using a similarity measure in the feature space; and replacing the clustered instances corresponding to the clustered feature vectors within a radius by a single instance. 46. The machine-implemented method of claim 33 wherein the clustering process comprises a sequentially clustering process, wherein the sequentially clustering process comprises a coarse partition into a set of superclusters, and a fine partition of the superclusters into a set of clusters.

10. The system of claim 8 , wherein the first answer and the second answer each comprise one of a verbal answer and a text-based answer.

10. The system of claim 8 , wherein the first answer and the second answer each comprise one of a verbal answer and a text-based answer. 11. The system of claim 10 , wherein an analysis of the verbal answer further comprises analyzing one of an answer pace, a tonal quality and a voice frequency.

15. A system for analyzing ballistic trajectories comprising: a database storing trajectory data for known ballistic objects; a preprocessor executing program instructions which, when executed, cause the preprocessor to: determine invariants for each of the known ballistic objects based on the trajectory data in the database; define a reference graph having nodes corresponding to the invariants for each of the known ballistic objects; and define a query graph having nodes connected to the nodes of the reference graph corresponding to anticipated queries to be made using the query graph; at least one sensor for monitoring trajectories of one or more observed objects; a runtime processor executing program instructions which, when executed, cause the runtime processor to input into the reference graph one or more sets of invariants corresponding to the trajectories of the one or more observed objects monitored by the at least one sensor, each of the one or more sets of invariants traversing through the nodes of the reference graph corresponding to the each of the one or more sets of invariants and leaving a record in the nodes traversed; and an interface configured to allow selection of a query for the query graph corresponding to one or more range of invariants, said query generating a query result identifying the nodes of the reference graph that satisfy the query; wherein the runtime processor further executes program instructions which, when executed, cause the runtime processor to identify records left in the identified nodes, thereby determining an identity of the one or more observed objects that satisfy the query.

15. A system for analyzing ballistic trajectories comprising: a database storing trajectory data for known ballistic objects; a preprocessor executing program instructions which, when executed, cause the preprocessor to: determine invariants for each of the known ballistic objects based on the trajectory data in the database; define a reference graph having nodes corresponding to the invariants for each of the known ballistic objects; and define a query graph having nodes connected to the nodes of the reference graph corresponding to anticipated queries to be made using the query graph; at least one sensor for monitoring trajectories of one or more observed objects; a runtime processor executing program instructions which, when executed, cause the runtime processor to input into the reference graph one or more sets of invariants corresponding to the trajectories of the one or more observed objects monitored by the at least one sensor, each of the one or more sets of invariants traversing through the nodes of the reference graph corresponding to the each of the one or more sets of invariants and leaving a record in the nodes traversed; and an interface configured to allow selection of a query for the query graph corresponding to one or more range of invariants, said query generating a query result identifying the nodes of the reference graph that satisfy the query; wherein the runtime processor further executes program instructions which, when executed, cause the runtime processor to identify records left in the identified nodes, thereby determining an identity of the one or more observed objects that satisfy the query. 19. The system of claim 15 , wherein the anticipated queries used by the preprocessor to define the query graph include combinations of a range of invariants defining a particular search volume and a range of invariants defining a particular timespan.

13. A non-transitory computer readable medium that stores a modeling profile defining a semantic extension to a modeling language, wherein the modeling profile stored on the computer readable medium comprises: a plurality of tagged profile constructs that assign new properties to standard model elements associated with the modeling language, wherein the new properties that the plurality of tagged profile constructs assign to the standard model elements associated with the modeling language define a semantic extension to the modeling language; a plurality of stereotyped profile constructs that add supplemental values or constraints to the standard model elements associated with the modeling language, wherein the supplemental values or constraints that the plurality of stereotyped profile constructs add to the standard model elements associated with the modeling language further define the semantic extension to the modeling language; and a plurality of mapping algorithms that map the plurality of tagged profile constructs and the plurality of stereotyped profile constructs to an object-oriented constructs construct in an object-oriented programming language having semantic features that support inferencing over rules without an instantiated inference engine, wherein the semantic extension defined in the modeling profile provides the modeling language with the semantic features that support inferencing over rules in the object-oriented programming language.

13. A non-transitory computer readable medium that stores a modeling profile defining a semantic extension to a modeling language, wherein the modeling profile stored on the computer readable medium comprises: a plurality of tagged profile constructs that assign new properties to standard model elements associated with the modeling language, wherein the new properties that the plurality of tagged profile constructs assign to the standard model elements associated with the modeling language define a semantic extension to the modeling language; a plurality of stereotyped profile constructs that add supplemental values or constraints to the standard model elements associated with the modeling language, wherein the supplemental values or constraints that the plurality of stereotyped profile constructs add to the standard model elements associated with the modeling language further define the semantic extension to the modeling language; and a plurality of mapping algorithms that map the plurality of tagged profile constructs and the plurality of stereotyped profile constructs to an object-oriented constructs construct in an object-oriented programming language having semantic features that support inferencing over rules without an instantiated inference engine, wherein the semantic extension defined in the modeling profile provides the modeling language with the semantic features that support inferencing over rules in the object-oriented programming language. 17. The computer readable medium of claim 13 , wherein the plurality of stereotyped profile constructs include a domain interface member profile construct that defines an action to execute in response to the standard model elements associated with the modeling language satisfying a condition, and wherein the plurality of tagged profile constructs include an action profile construct that defines the action and a condition profile construct that defines the condition.

1. A method to identify compounding relationships between edits in an electronic document, comprising: receiving, by a processor, a set of one or more first edits and a second edit to the electronic document; receiving, by the processor, an acceptance of the second edit from an editor of the electronic document; identifying, by the processor, a shared position of the set of one or more first edits and the second edit in the electronic document; filtering the set of one or more first edits to remove deletions in the electronic document and include insertions and modifications in the electronic document, to obtain at least a subset of the one or more first edits; determining, by the processor, that the subset of one or more first edits and the second edit have compounding relationships based at least in part on the identification, by determining that the subset of one or more first edits are required to be accepted in order for the second edit to be accepted; and in response to the determining that the subset of one or more first edits and the second edit have the compounding relationships, automatically accepting, by the processor, the subset of one or more first edits in response to receiving the acceptance of the second edit.

1. A method to identify compounding relationships between edits in an electronic document, comprising: receiving, by a processor, a set of one or more first edits and a second edit to the electronic document; receiving, by the processor, an acceptance of the second edit from an editor of the electronic document; identifying, by the processor, a shared position of the set of one or more first edits and the second edit in the electronic document; filtering the set of one or more first edits to remove deletions in the electronic document and include insertions and modifications in the electronic document, to obtain at least a subset of the one or more first edits; determining, by the processor, that the subset of one or more first edits and the second edit have compounding relationships based at least in part on the identification, by determining that the subset of one or more first edits are required to be accepted in order for the second edit to be accepted; and in response to the determining that the subset of one or more first edits and the second edit have the compounding relationships, automatically accepting, by the processor, the subset of one or more first edits in response to receiving the acceptance of the second edit. 8. The method of claim 1 , wherein the subset of one or more first edits and the second edit have compounding relationships when the second edit is dependent on the subset of one or more first edits, wherein the subset of one or more first edits comprises a first modification of an element to obtain a modified element, and the second edit comprises a second modification of the modified element.

11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal based educational environment, comprising: (a) a code segment that analyzes user responses to ascertain user characteristics (b) a code segment that analyzes user responses to ascertain user characteristics; (c) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component that motivates accomplishment of the goal for use in the business simulation; and (d) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages, based on the user characteristics, that further motivates accomplishment of the goal.

11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal based educational environment, comprising: (a) a code segment that analyzes user responses to ascertain user characteristics (b) a code segment that analyzes user responses to ascertain user characteristics; (c) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component that motivates accomplishment of the goal for use in the business simulation; and (d) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages, based on the user characteristics, that further motivates accomplishment of the goal. 12. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component to provide a goal based educational environment as recited in claim 11, including a code segment that instantiates a particular feedback model based on the characteristics of the user.

1. A computer-implemented method, comprising: identifying a candidate query from queries stored in a query log, wherein identifying the candidate query comprises: identifying a query from the queries stored in a query log; determining whether the query was submitted at least a minimum number of times during a time period; determining whether the query was submitted less than a maximum number of times during the time period; and identifying, by one or more computer processors, the query as the candidate query if the query was submitted at least the minimum number of times and less than the maximum number of times during the time period; generating relevancy scores for a plurality of web documents, each relevancy score associated with a corresponding web document and being a measure of the relevance of the candidate query to the web document; selecting a web document having an associated relevancy score that exceeds a relevancy threshold; and associating the selected web document with the candidate query.

1. A computer-implemented method, comprising: identifying a candidate query from queries stored in a query log, wherein identifying the candidate query comprises: identifying a query from the queries stored in a query log; determining whether the query was submitted at least a minimum number of times during a time period; determining whether the query was submitted less than a maximum number of times during the time period; and identifying, by one or more computer processors, the query as the candidate query if the query was submitted at least the minimum number of times and less than the maximum number of times during the time period; generating relevancy scores for a plurality of web documents, each relevancy score associated with a corresponding web document and being a measure of the relevance of the candidate query to the web document; selecting a web document having an associated relevancy score that exceeds a relevancy threshold; and associating the selected web document with the candidate query. 4. The method of claim 1 , wherein generating relevancy scores for a plurality of web documents comprises searching only a proper subset of a collection of web documents with the candidate query, the proper subset of the collection of web documents being the plurality of web documents.

3. The non-transitory computer readable medium of claim 2 , wherein the retrieving of the candidate situation comprises retrieving a situation having continuous utterances that match a flow of dialogue act of the last utterances inputted by the first and second user terminals from the dialogue situation information database.

3. The non-transitory computer readable medium of claim 2 , wherein the retrieving of the candidate situation comprises retrieving a situation having continuous utterances that match a flow of dialogue act of the last utterances inputted by the first and second user terminals from the dialogue situation information database. 4. The computer program non-transitory computer readable medium of claim 3 , wherein the retrieving of the candidate situation comprises retrieving a situation that matches a relationship between a first user of the first user terminal and a second user of the second user terminal from the dialogue situation information database when inferring the relationship between the first user and the second user from the generated dialogue situation information.

8. A system for identifying a primary document version of a document from a plurality of document versions of the document, the system comprising: one or more memories to store a source-priority list comprising a plurality of document sources, each document source having an associated priority of authority, where the priorities include higher priorities and lower priorities; and one or more processors to: access at least one data repository to obtain metadata for each document version of the document versions; determine, based on the metadata, a source of each document version; determine, from the source-priority list, a priority of authority for the source of each document version; select a document version, of the document versions, having the source with a highest priority of authority and a qualified citation count based on a citation count measure; and provide the document version having the source with a highest priority of authority for presentation.

8. A system for identifying a primary document version of a document from a plurality of document versions of the document, the system comprising: one or more memories to store a source-priority list comprising a plurality of document sources, each document source having an associated priority of authority, where the priorities include higher priorities and lower priorities; and one or more processors to: access at least one data repository to obtain metadata for each document version of the document versions; determine, based on the metadata, a source of each document version; determine, from the source-priority list, a priority of authority for the source of each document version; select a document version, of the document versions, having the source with a highest priority of authority and a qualified citation count based on a citation count measure; and provide the document version having the source with a highest priority of authority for presentation. 11. The system of claim 8 , where, when selecting the document version having the source with a highest priority of authority, the processor is further to: select a document version having both a highest priority of authority and a greatest length based on a length measure.

6. A method comprising: in response to receiving a database statement, determining whether a user that initiated the database statement is authorized to access data from a plurality of data realms; for each data realm of the plurality of data realms, determining an authorization result and generating a data realm predicate that reflects the authorization result; wherein the data realm predicate is one of a plurality of data realm predicates generated for the database statement; wherein a particular predicate comprises the plurality of data realm predicates; performing one or more normalizations on the particular predicate to remove one or more data realm predicates from the plurality of data realm predicates to generate a normalized predicate that does not include the one or more data realm predicates; generating an execution plan based on the normalized predicate and not based on the one or more data realm predicates.

6. A method comprising: in response to receiving a database statement, determining whether a user that initiated the database statement is authorized to access data from a plurality of data realms; for each data realm of the plurality of data realms, determining an authorization result and generating a data realm predicate that reflects the authorization result; wherein the data realm predicate is one of a plurality of data realm predicates generated for the database statement; wherein a particular predicate comprises the plurality of data realm predicates; performing one or more normalizations on the particular predicate to remove one or more data realm predicates from the plurality of data realm predicates to generate a normalized predicate that does not include the one or more data realm predicates; generating an execution plan based on the normalized predicate and not based on the one or more data realm predicates. 7. The method of claim 6 , wherein performing one of the one or more normalizations comprises: identifying a portion of the particular predicate that comprises an inverted data realm predicate that is AND'd with a false predicate; replacing the portion of the particular predicate with the false predicate.

11. A computer program product for controlling copying of a document, the computer program product comprising a computer readable medium including a computer readable program, wherein the computer readable program upon being executed on a computer causes the computer to perform activities comprising: optically capturing contents of the document to produce a captured document; performing optical object recognition on the captured document in an attempt to find a recognized object of the captured document; providing a first prompt if said optical object recognition does not recognize any object, said first prompt inquiring whether the document is copyrighted; providing a second prompt if said optical object recognition results in finding said recognized object, said second prompt warning that the document is subject to limitations concerning copying; comparing the recognized object to objects in an object database if said optical object recognition results in finding said recognized object, wherein each of the objects of said object database is associated with at least one output rule from an output rule database comprising at least three output rules including an authorization rule, a block rule, and a notification rule; determining a content output for the recognized object based on said at least one output rule associated with the recognized object; and providing the content output based on said at least one output rule.

11. A computer program product for controlling copying of a document, the computer program product comprising a computer readable medium including a computer readable program, wherein the computer readable program upon being executed on a computer causes the computer to perform activities comprising: optically capturing contents of the document to produce a captured document; performing optical object recognition on the captured document in an attempt to find a recognized object of the captured document; providing a first prompt if said optical object recognition does not recognize any object, said first prompt inquiring whether the document is copyrighted; providing a second prompt if said optical object recognition results in finding said recognized object, said second prompt warning that the document is subject to limitations concerning copying; comparing the recognized object to objects in an object database if said optical object recognition results in finding said recognized object, wherein each of the objects of said object database is associated with at least one output rule from an output rule database comprising at least three output rules including an authorization rule, a block rule, and a notification rule; determining a content output for the recognized object based on said at least one output rule associated with the recognized object; and providing the content output based on said at least one output rule. 19. The computer program product of claim 11 , wherein the output rule database comprises at least a first output rule based on said recognized object being a symbol associated with a first copying limitation, and a second output rule based on said recognized object being predefined content associated with a second copying limitation.

17. An article of manufacture comprising a computer readable storage medium having code executed to generate methods deployed at a server and invoked by a client application, wherein the code causes operations to be performed, the operations comprising: receiving a file including code defining a class implementing at least one method in an information model for a device management schema and wherein one of the at least one method relates to device management operations with respect to a device; translating the file to produce an object oriented implementation of the class and the at least one method for the device management operations for the device in an object oriented programming (OOP) language file; adding protocol statements of the information model to the OOP file to enable the client application to invoke the at least one method on the server to perform the device management operations with respect to the device; and compiling the OOP file to produce an executable object capable of being invoked by a call to a method invocation statement, wherein the client application calling the method invocation statement causes execution of the protocol statements and the at least one method in the executable object to invoke the at least one method on the server to cause the device management operations of the method with respect to the device.

17. An article of manufacture comprising a computer readable storage medium having code executed to generate methods deployed at a server and invoked by a client application, wherein the code causes operations to be performed, the operations comprising: receiving a file including code defining a class implementing at least one method in an information model for a device management schema and wherein one of the at least one method relates to device management operations with respect to a device; translating the file to produce an object oriented implementation of the class and the at least one method for the device management operations for the device in an object oriented programming (OOP) language file; adding protocol statements of the information model to the OOP file to enable the client application to invoke the at least one method on the server to perform the device management operations with respect to the device; and compiling the OOP file to produce an executable object capable of being invoked by a call to a method invocation statement, wherein the client application calling the method invocation statement causes execution of the protocol statements and the at least one method in the executable object to invoke the at least one method on the server to cause the device management operations of the method with respect to the device. 20. The article of manufacture of claim 17 , wherein the device management schema implements a core model including classes and methods common to all areas of device management and wherein the at least one method invoked through the executable object is a member of class in an extension schema providing classes related to a specific technology.

11. The visualization system of claim 1 wherein the processor is further configured to represent the information on the user interface as data objects movable in said space and wherein said user interface is adapted to represent said data objects in accordance with a user selectable level of detail.

11. The visualization system of claim 1 wherein the processor is further configured to represent the information on the user interface as data objects movable in said space and wherein said user interface is adapted to represent said data objects in accordance with a user selectable level of detail. 12. The visualization system of claim 11 wherein the processor is further configured to emphasize a selected data object on the user interface in response to a pointing input of said user, at least one of a magnitude and a duration of emphasis being applied to the selected data object in response to a duration of said pointing input.

28. A computer readable storage medium comprising computer-executable instructions for: receiving an option list of allowable options for an application, the option list comprising a first option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving a command line for the application, the received command line comprising a second option; parsing the received command line to determine if the second option matches the first option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options.

28. A computer readable storage medium comprising computer-executable instructions for: receiving an option list of allowable options for an application, the option list comprising a first option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving a command line for the application, the received command line comprising a second option; parsing the received command line to determine if the second option matches the first option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options. 29. The computer readable storage medium of claim 28 , comprising further computer-executable instructions for: comparing a number of characters of the second option on the command line with a minimum number of characters required to uniquely identify the first option of the option list.

38. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for outputting data based on anomaly detection, the method comprising: receiving an input dataset; using a binary anomaly detection model to determine whether an input dataset is likely to contain an anomaly, wherein the binary anomaly detection model is used to determine whether the input dataset is likely to contain an anomaly by checking the binary anomaly detection model for an n-gram in the input dataset; if the input dataset is determined to be likely to contain an anomaly, dropping the input dataset; and if the input dataset is determined to be unlikely to contain an anomaly, outputting the input dataset based on whether the input dataset contains an anomaly.

38. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for outputting data based on anomaly detection, the method comprising: receiving an input dataset; using a binary anomaly detection model to determine whether an input dataset is likely to contain an anomaly, wherein the binary anomaly detection model is used to determine whether the input dataset is likely to contain an anomaly by checking the binary anomaly detection model for an n-gram in the input dataset; if the input dataset is determined to be likely to contain an anomaly, dropping the input dataset; and if the input dataset is determined to be unlikely to contain an anomaly, outputting the input dataset based on whether the input dataset contains an anomaly. 40. The medium of claim 38 , the method further comprising: determining whether the input dataset contains malicious n-grams; and if the input dataset is determined to not contain malicious n-grams, using the input dataset to perform a function related to the input dataset.

2. The method of claim 1 , further including expressing device interactions based on device descriptions and abstract device interactions, whereby device functionality and device interactions are logically separated, allowing description of the devices and a set of possible ways that the devices may interact.

2. The method of claim 1 , further including expressing device interactions based on device descriptions and abstract device interactions, whereby device functionality and device interactions are logically separated, allowing description of the devices and a set of possible ways that the devices may interact. 3. The method of claim 2 , wherein the task external description outlines task suggestions for interaction with a user.

14. A non-transitory computer storage medium having computer executable instructions which when executed by a computer cause the computer to perform operations comprising: receiving topic information for a document, the information including at least one topic and a weight for each topic, where the topic relates to content of the document, and the weight represents how strongly the topic is associated with the document; receiving authorship information for the document, the information including, for each topic in the document, at least one author and an authorship percentage for each author; updating an authority signature value for a first author of a first topic based on a product of the authorship percentage for the first author of the first topic and the weight of the first topic in the document, where the first topic is included in the received topic information; receiving topic information for a second document, the information including at least one topic and a weight for each topic; receiving authorship information for the second document, the information including, for each topic in the second document, at least one author and an authorship percentage for each author; and updating the authority signature value for the first author of the first topic based on a product of the second document first topic authorship percentage for the first author and the weight of the first topic in the second document.

14. A non-transitory computer storage medium having computer executable instructions which when executed by a computer cause the computer to perform operations comprising: receiving topic information for a document, the information including at least one topic and a weight for each topic, where the topic relates to content of the document, and the weight represents how strongly the topic is associated with the document; receiving authorship information for the document, the information including, for each topic in the document, at least one author and an authorship percentage for each author; updating an authority signature value for a first author of a first topic based on a product of the authorship percentage for the first author of the first topic and the weight of the first topic in the document, where the first topic is included in the received topic information; receiving topic information for a second document, the information including at least one topic and a weight for each topic; receiving authorship information for the second document, the information including, for each topic in the second document, at least one author and an authorship percentage for each author; and updating the authority signature value for the first author of the first topic based on a product of the second document first topic authorship percentage for the first author and the weight of the first topic in the second document. 16. The non-transitory computer storage medium of claim 14 , which further causes the computer to perform further operations comprising: storing a plurality of authority signature values in a database; and retrieving and displaying information regarding one or more authors from the database having a predetermined rank or authority signature value for a query topic in response to a request regarding the query topic.

7. The method of claim 2 wherein the expression is an expression tree that is generated based on a set of example structured images.

7. The method of claim 2 wherein the expression is an expression tree that is generated based on a set of example structured images. 9. The method of claim 7 wherein the bottom-up inference rule can identify the bounding boxes, wherein the bounding boxes comprise a first bounding box that matches a parent expression in the expression tree, given a second bounding box and a third bounding box that match at least two child expressions in the expression tree.

17. The computer-readable storage medium of claim 15 , the computer-readable storage medium having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising: retrieving preferences of the subscriber; and communicating the text to the recipient address based on the preferences.

17. The computer-readable storage medium of claim 15 , the computer-readable storage medium having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising: retrieving preferences of the subscriber; and communicating the text to the recipient address based on the preferences. 18. The computer-readable storage medium of claim 17 , wherein the preferences are retrieved from a consolidated network repository.

1. A computer-implemented method of database access comprising: receiving, at a processor, an identifier of a database; annotating a schema of the database with a plurality of expressions which describe probability distributions over entries in the database; using the annotated schema to access the database and to obtain, as a result of inference on the accessed data according to the annotated schema, one or more predictive probability distributions over entries of cells in the database; and the result of the inference being generated by an inference engine, generating the result of the inference comprising sending to the inference engine at least one of: database column types; or an indication of whether the database columns are input, latent, or observable.

1. A computer-implemented method of database access comprising: receiving, at a processor, an identifier of a database; annotating a schema of the database with a plurality of expressions which describe probability distributions over entries in the database; using the annotated schema to access the database and to obtain, as a result of inference on the accessed data according to the annotated schema, one or more predictive probability distributions over entries of cells in the database; and the result of the inference being generated by an inference engine, generating the result of the inference comprising sending to the inference engine at least one of: database column types; or an indication of whether the database columns are input, latent, or observable. 2. A method as claimed in claim 1 comprising adding at least one column to a schema of the database, the column arranged to store data learnt by inference algorithms applied to data stored in the database.

6. A text entry system, comprising: (a) a user input device comprising an auto-correcting keyboard region comprising a plurality of the characters of a character set, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, wherein user interaction with the user input device within the auto-correcting keyboard region determines a location associated with the user interaction and wherein the determined interaction location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object comprises a string of one or more character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined interaction location in the input sequence of interactions, calculates a set of distance values between the interaction locations and the known coordinate locations corresponding to one or more character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for a generated input sequence, evaluates at least one candidate object in memory by calculating a matching metric based on the calculated distance values for the object; and ranks the evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component which presents said at least one candidate object to the user according to its ranking, and enables the user to select among presented objects for output to the text display area on the output device.

6. A text entry system, comprising: (a) a user input device comprising an auto-correcting keyboard region comprising a plurality of the characters of a character set, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, wherein user interaction with the user input device within the auto-correcting keyboard region determines a location associated with the user interaction and wherein the determined interaction location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object comprises a string of one or more character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined interaction location in the input sequence of interactions, calculates a set of distance values between the interaction locations and the known coordinate locations corresponding to one or more character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for a generated input sequence, evaluates at least one candidate object in memory by calculating a matching metric based on the calculated distance values for the object; and ranks the evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component which presents said at least one candidate object to the user according to its ranking, and enables the user to select among presented objects for output to the text display area on the output device. 9. The system of claim 6 , wherein a user selection of a character set member or function that is associated with an interaction outside of the auto-correcting keyboard region accepts and outputs the determined highest ranked candidate object at a text insertion point in the text display area prior to outputting the selected character set member at the text insertion point in the text display area or prior to executing the function.

1. A computing system, comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the computing system to: assign a telephone number to a customer account to enable the customer account to send and receive a data transmission using the telephone number and a voice-enabled communications device, the voice-enabled communications device connected to a data network to receive an uninterrupted user utterance; initiate the data transmission upon the receipt of the uninterrupted user utterance, the data transmission representing audio input data corresponding to the uninterrupted user utterance that includes a spoken instruction for performing an action and an intended recipient for the action; generate text data from the audio input data by performing automated speech recognition on the audio input data; generate message body data by performing natural language processing on the text data, the message body data being a first portion of the text data; identify the intended recipient by performing natural language processing on the text data in response to the spoken instruction, the intended recipient being identified in a different portion of the text data than the first portion of the text data; determine that an electronic communication to be sent to the intended recipient is a first electronic communication being sent to the intended recipient from the customer account as part of the action; generate an introductory text message including information to indicate to the intended recipient a name of a user of the customer account; generate a text message that includes the message body data; send the introductory text message to a recipient device using a recipient account of the intended recipient; and send the text message to the recipient device.

1. A computing system, comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the computing system to: assign a telephone number to a customer account to enable the customer account to send and receive a data transmission using the telephone number and a voice-enabled communications device, the voice-enabled communications device connected to a data network to receive an uninterrupted user utterance; initiate the data transmission upon the receipt of the uninterrupted user utterance, the data transmission representing audio input data corresponding to the uninterrupted user utterance that includes a spoken instruction for performing an action and an intended recipient for the action; generate text data from the audio input data by performing automated speech recognition on the audio input data; generate message body data by performing natural language processing on the text data, the message body data being a first portion of the text data; identify the intended recipient by performing natural language processing on the text data in response to the spoken instruction, the intended recipient being identified in a different portion of the text data than the first portion of the text data; determine that an electronic communication to be sent to the intended recipient is a first electronic communication being sent to the intended recipient from the customer account as part of the action; generate an introductory text message including information to indicate to the intended recipient a name of a user of the customer account; generate a text message that includes the message body data; send the introductory text message to a recipient device using a recipient account of the intended recipient; and send the text message to the recipient device. 3. The computing system of claim 1 , wherein the instructions, when executed further enable the computing system to: identify a contacts authority list that includes one or more contacts; use automatic speech recognition (ASR) techniques on the audio input data to generate the text data that represents words; use natural language understanding (NLU) techniques on the text data to determine the intended recipient; analyze the contacts authority list to identify the intended recipient as one of the one or more contacts; and identify a mobile telephone number for the recipient device.

8. An automatic new word extraction system, comprising: a segmentor which segments a cleaned corpus in a domain to form a segmented corpus; a splitter which splits the segmented corpus to form sub strings, and which counts the number of the sub strings appearing in the corpus; and a filter which filters out false candidates to output new words, wherein the new words are words not contained in a base vocabulary; wherein the segmenting and the splitting is not dependent upon word boundaries; wherein new words are determined based upon the domain of the cleaned corpus; wherein the splitter builds a GAST (general atom suffix tree) contained in a reduced memory space; wherein the GAST limits the length of character sub strings.

8. An automatic new word extraction system, comprising: a segmentor which segments a cleaned corpus in a domain to form a segmented corpus; a splitter which splits the segmented corpus to form sub strings, and which counts the number of the sub strings appearing in the corpus; and a filter which filters out false candidates to output new words, wherein the new words are words not contained in a base vocabulary; wherein the segmenting and the splitting is not dependent upon word boundaries; wherein new words are determined based upon the domain of the cleaned corpus; wherein the splitter builds a GAST (general atom suffix tree) contained in a reduced memory space; wherein the GAST limits the length of character sub strings. 9. The automatic word extraction system according to claim 8 , wherein the segmentor uses punctuations, Arabic digits and alphabetic strings, or new word patterns to segment the cleaned corpus.

14. A computer-readable storage device having additional instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a spoken user search query at a portable device; determining a present location based on the portable device; incorporating a granularity description of the present location into a local language model used to process the spoken user search query, the granularity description using weights for topologically concentric locations to determine probabilities; and outputting results associated with the spoken user search query based on the present location and a term in the spoken user search query.

14. A computer-readable storage device having additional instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a spoken user search query at a portable device; determining a present location based on the portable device; incorporating a granularity description of the present location into a local language model used to process the spoken user search query, the granularity description using weights for topologically concentric locations to determine probabilities; and outputting results associated with the spoken user search query based on the present location and a term in the spoken user search query. 20. The computer-readable storage device of claim 14 , the computer-readable storage device having additional instruction stored which result in the operations further comprising: collecting queries at the portable device, wherein the queries are both textual and spoken; analyzing the queries for a query location; determining the query location from the analysis and the present location; dividing the collection of queries into geographical areas, wherein the geographical areas are based on the determined query locations; estimating language and acoustic models for each geographical area; and training a speech recognition application using the estimated language and acoustic models.

1. A method for using input signal quality to improve speech recognition, comprising: obtaining quantitative measurements of the quality of an input signal of a speech recognition system, the quantitative measurements including at least a signal-to-noise ratio and a loudness of the input signal; analyzing the quantitative measurements to categorize the quality of the input signal into a qualitative category; and establishing a rejection threshold used in rejecting a speech recognition result for speech included in the input signal in dependence on the qualitative category of the input signal quality, the speech recognition result having a confidence score indicating a level of confidence in an accuracy of the speech recognition result, the rejection threshold establishing which confidence scores indicate that the speech recognition result is to be rejected as being incorrectly recognized.

1. A method for using input signal quality to improve speech recognition, comprising: obtaining quantitative measurements of the quality of an input signal of a speech recognition system, the quantitative measurements including at least a signal-to-noise ratio and a loudness of the input signal; analyzing the quantitative measurements to categorize the quality of the input signal into a qualitative category; and establishing a rejection threshold used in rejecting a speech recognition result for speech included in the input signal in dependence on the qualitative category of the input signal quality, the speech recognition result having a confidence score indicating a level of confidence in an accuracy of the speech recognition result, the rejection threshold establishing which confidence scores indicate that the speech recognition result is to be rejected as being incorrectly recognized. 4. The method of claim 1 , wherein the rejection threshold is set in an underlying multivariate Gaussian distribution within an acoustic model of the speech recognition system.

1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value.

1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value. 2. The system of claim 1 , wherein: the primitives include generic application-level protocol analysis language primitives; the generic decoder uses a syntax that also applies to protocol parsing; or both the primitives include generic application-level protocol analysis language primitives and the generic decoder uses the syntax that also applies to protocol parsing.

1. A method for extensibility of binding definitions for a user interface application, the method comprising: performing, by a computer system programmed with code stored in a memory and executing by a processor of the computer system to configure the computer system into a machine: obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; performing a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; performing a second transformation of the framework to generate a first presentation style for the first grammar level; obtaining the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application.

1. A method for extensibility of binding definitions for a user interface application, the method comprising: performing, by a computer system programmed with code stored in a memory and executing by a processor of the computer system to configure the computer system into a machine: obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; performing a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; performing a second transformation of the framework to generate a first presentation style for the first grammar level; obtaining the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application. 6. The method of claim 1 , wherein the second grammar level compatible with the user interface application is fixed.

28. The method of claim 27 , further comprising: a. having a tier of access with at least one remote employee user I/O device; and b. providing at least one remote employee user designated by one remote company user.

28. The method of claim 27 , further comprising: a. having a tier of access with at least one remote employee user I/O device; and b. providing at least one remote employee user designated by one remote company user. 29. The method of claim 28 , further comprising: a. associating each individual advertisement inventory listing with a unique inventory code and with a unique market area; and b. associating each company user and each employee user with a unique market area.

26. A system for the creation of user-requested telephony features, comprising: a service creation environment comprising an application operable to: receive a plurality of instructions defining a graphical representation of an implementation of one or more telephony features for an endpoint, the graphical representation comprising a plurality of graphical elements, each graphical element representing at least a portion of a state process of the one or more telephony features; generate the graphical representation in accordance with the plurality of instructions; convert a first graphical element into a first text command; convert a second graphical element into a second text command, the first and second text commands specifying a plurality of actions of the state process; determine customized feature logic comprising the first and second text commands, the first and second text commands operable to provide the one or more telephony features for the endpoint; and the endpoint in communication with the service creation environment, the endpoint comprising an integrated service framework operable to store the feature logic to create the one or more telephony features.

26. A system for the creation of user-requested telephony features, comprising: a service creation environment comprising an application operable to: receive a plurality of instructions defining a graphical representation of an implementation of one or more telephony features for an endpoint, the graphical representation comprising a plurality of graphical elements, each graphical element representing at least a portion of a state process of the one or more telephony features; generate the graphical representation in accordance with the plurality of instructions; convert a first graphical element into a first text command; convert a second graphical element into a second text command, the first and second text commands specifying a plurality of actions of the state process; determine customized feature logic comprising the first and second text commands, the first and second text commands operable to provide the one or more telephony features for the endpoint; and the endpoint in communication with the service creation environment, the endpoint comprising an integrated service framework operable to store the feature logic to create the one or more telephony features. 31. The system of claim 26 , wherein the one or more telephony features are operable to receive an intercept at the occurrence of an event.

11. A method, comprising: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign; identifying a change made to the paid portion of the search advertising campaign; determining, with a computing device and based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating, with the computing device, a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in a storage medium in association with an indication of the change.

11. A method, comprising: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign; identifying a change made to the paid portion of the search advertising campaign; determining, with a computing device and based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating, with the computing device, a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in a storage medium in association with an indication of the change. 20. The method of claim 11 , further comprising: generating a mathematical model for determining an estimated synergy score based on the generated synergy score; and storing the mathematical model in the storage medium.

5. A method of controlling a television receiver having an audio-video (AV) decoder configured to process a television signal received by a tuner and a net connecting module configured to connect to an Internet server, comprising: selecting and maintaining initial setup information that indicates at least a menu language when setting up the television receiver; gaining access by the television receiver to a web server while transmitting a language request signal to the web server; and determining the language request signal by the television receiver to request the same language as the selected menu language indicated in the initial setup information, wherein the language request signal used for browsing is automatically determined when the menu language is decided by the user, and wherein the language request signal is configured to cause the web server to deliver content in the selected menu language when setting up the television receiver.

5. A method of controlling a television receiver having an audio-video (AV) decoder configured to process a television signal received by a tuner and a net connecting module configured to connect to an Internet server, comprising: selecting and maintaining initial setup information that indicates at least a menu language when setting up the television receiver; gaining access by the television receiver to a web server while transmitting a language request signal to the web server; and determining the language request signal by the television receiver to request the same language as the selected menu language indicated in the initial setup information, wherein the language request signal used for browsing is automatically determined when the menu language is decided by the user, and wherein the language request signal is configured to cause the web server to deliver content in the selected menu language when setting up the television receiver. 7. The method of controlling the television receiver of claim 5 , wherein the language content of the same language as the menu language designated in the initial setup information is extracted from language content of various languages received through the net connecting module.

12. A machine-readable storage device storing instructions that, when executed by a processor of a machine, cause the machine to perform operations comprising: receiving, from a device of a first entity, a message directed to a second entity that includes a selection of a first language construct in a first language and an indication of a second entity from a first entity; identifying, from a stored constructs table, a construct identifier corresponding to the first language construct; determining, using a hardware processor, a language identifier corresponding to the second entity that is to receive a translation of the first language construct in a second language, the language identifier corresponding to the second language; retrieving a second language construct by finding an entry in a translated construct table that contains both the construct identifier and the language identifier corresponding to the second entity, the second language construct being a translation of the first language construct in the second language; and generating a translated message that comprises the second language construct; and transmitting, to a device of the second user, the translated message that comprises the second language construct.

12. A machine-readable storage device storing instructions that, when executed by a processor of a machine, cause the machine to perform operations comprising: receiving, from a device of a first entity, a message directed to a second entity that includes a selection of a first language construct in a first language and an indication of a second entity from a first entity; identifying, from a stored constructs table, a construct identifier corresponding to the first language construct; determining, using a hardware processor, a language identifier corresponding to the second entity that is to receive a translation of the first language construct in a second language, the language identifier corresponding to the second language; retrieving a second language construct by finding an entry in a translated construct table that contains both the construct identifier and the language identifier corresponding to the second entity, the second language construct being a translation of the first language construct in the second language; and generating a translated message that comprises the second language construct; and transmitting, to a device of the second user, the translated message that comprises the second language construct. 16. The machine-readable storage device of claim 12 , wherein the construct identifier comprises a numerical construct identifier.

1. A computer-implemented method comprising: receiving a current location of a user's electronic device; retrieving data identifying a plurality of points of interest within a predetermined distance to the current location; ranking each point of interest based at least in part on the point of interest's proximity to the current location, wherein for at least one point of interest the ranking is further based on one or more updates associated with the point of interest, where each update comprises data about the point of interest input by an author other than the user into an online social network that includes the user; and providing data identifying one or more of the points of interest to the electronic device for presentation to the user on a display of the electronic device based on the ranking.

1. A computer-implemented method comprising: receiving a current location of a user's electronic device; retrieving data identifying a plurality of points of interest within a predetermined distance to the current location; ranking each point of interest based at least in part on the point of interest's proximity to the current location, wherein for at least one point of interest the ranking is further based on one or more updates associated with the point of interest, where each update comprises data about the point of interest input by an author other than the user into an online social network that includes the user; and providing data identifying one or more of the points of interest to the electronic device for presentation to the user on a display of the electronic device based on the ranking. 2. The method of claim 1 , wherein ranking each point of interest based on one or more updates associated with the point of interest includes basing the ranking on how recent each update was input compared to the time at which the current location was received.

4. The method of claim 1 wherein the knowledge data for each question and answer additionally comprises spatial, temporal, social and topical data that related to each of the second plurality of users who consumed the knowledge data at the time the knowledge data was consumed.

4. The method of claim 1 wherein the knowledge data for each question and answer additionally comprises spatial, temporal, social and topical data that related to each of the second plurality of users who consumed the knowledge data at the time the knowledge data was consumed. 5. The method of claim 4 wherein the identified knowledge data is ranked based on the closeness of fit between social network data, spatial data, temporal data and topical data that is available, via the network, that relates to the identified user and the spatial, temporal, social and topical data that related to each of the second plurality of users who consumed the identified knowledge data at the time the knowledge data was consumed.

9. An apparatus, comprising: a processor; and a memory, at least one of the processor or the memory being adapted for: ascertaining an intent of a query; determining a relevance of each one of a plurality of lines of text of a document based upon the intent of the query, content of the query, and content of each of the plurality of lines of text, wherein the document is a single search result returned in response to the query; ranking the plurality of lines of text according to the determined relevance of each of the plurality of lines of text; and generating a summary of the single search result using a subset of the plurality of lines of text based upon the ranking of the plurality of lines of text.

9. An apparatus, comprising: a processor; and a memory, at least one of the processor or the memory being adapted for: ascertaining an intent of a query; determining a relevance of each one of a plurality of lines of text of a document based upon the intent of the query, content of the query, and content of each of the plurality of lines of text, wherein the document is a single search result returned in response to the query; ranking the plurality of lines of text according to the determined relevance of each of the plurality of lines of text; and generating a summary of the single search result using a subset of the plurality of lines of text based upon the ranking of the plurality of lines of text. 14. The apparatus as recited in claim 9 , wherein ascertaining the intent of the query comprises: obtaining a numerical value that indicates both a degree to which the query is navigational and a degree to which the query is informational.

6. The method of claim 1 further comprising a step of filtering the content of the conversation between the parties in order to identify key words utilized in the following process: automatically searching the at least one database for information associated with the key words; and transmitting information identified as associated with the key words to at least one party participating in the call.

6. The method of claim 1 further comprising a step of filtering the content of the conversation between the parties in order to identify key words utilized in the following process: automatically searching the at least one database for information associated with the key words; and transmitting information identified as associated with the key words to at least one party participating in the call. 7. The method of claim 6 wherein the step of automatically searching a database for information associated with the key words further comprises a step of utilizing the metadata associated with the call to further refine the information identified as associated with the key words.

1. A system for transaction card customization including a centralized issuer hub providing a single point of website integration for applicants in different countries, the system comprising: a centralized issuer hub comprising a server that coordinates data exchange between at least two of a plurality of local issuer country websites and a card customization services for processing applicant requests for a customized transaction card, the card customization services allowing an applicant to customize an image to be added to a front surface of the customized transaction card; wherein a local issuer country website provides a browser-based user interface for the applicant; wherein the transaction card customization services includes a website that recognizes an issuer country of the applicant and launches a dedicated country-specific website for the applicant based upon on a country of origin of the local issuer country website; wherein the transaction card customization services further includes a syndication layer that adds country-specific content to a base website that serves up the dedicated country-specific website for the applicant, the base website including central features and functionality that make up the credit card customization software application without including any issuer-specific enhancements, branding, foreign language, colors, artwork and website links.

1. A system for transaction card customization including a centralized issuer hub providing a single point of website integration for applicants in different countries, the system comprising: a centralized issuer hub comprising a server that coordinates data exchange between at least two of a plurality of local issuer country websites and a card customization services for processing applicant requests for a customized transaction card, the card customization services allowing an applicant to customize an image to be added to a front surface of the customized transaction card; wherein a local issuer country website provides a browser-based user interface for the applicant; wherein the transaction card customization services includes a website that recognizes an issuer country of the applicant and launches a dedicated country-specific website for the applicant based upon on a country of origin of the local issuer country website; wherein the transaction card customization services further includes a syndication layer that adds country-specific content to a base website that serves up the dedicated country-specific website for the applicant, the base website including central features and functionality that make up the credit card customization software application without including any issuer-specific enhancements, branding, foreign language, colors, artwork and website links. 9. The system of claim 1 , wherein the card customization services website comprises a browser-based user interface displaying a graphical representation of an applicant submitted image that is uploaded by the applicant from a remote location, such that the image may be manipulated by the applicant from the remote location.

7. The method of claim 1 , further comprising determining whether the at least one attribute of the first query item is compatible with the at least one particular attribute defined for the second query item.

7. The method of claim 1 , further comprising determining whether the at least one attribute of the first query item is compatible with the at least one particular attribute defined for the second query item. 8. The method of claim 7 , further comprising, in an instance there are multiple attributes of the first query item that are compatible with the at least one particular attribute defined for the second query item, determining each of the attributes of the first query item that is compatible with the at least one particular attribute defined for the second query item.

1. A method for generating a circuit design, comprising method operations of: accessing a register table identifying characteristics of each register for a functional block of the circuit, the characteristics including a register name and a register type, wherein each register is divided into bit fields, each bit field having characteristics of a bit field name and a bit field width indicating a size of the bit field; importing data from the register table into a database; and processing the data imported into the database to generate a design specification for the functional block, the design specification being generated to implement the identified characteristics of each register, wherein each operation of the method is executed by a processor.

1. A method for generating a circuit design, comprising method operations of: accessing a register table identifying characteristics of each register for a functional block of the circuit, the characteristics including a register name and a register type, wherein each register is divided into bit fields, each bit field having characteristics of a bit field name and a bit field width indicating a size of the bit field; importing data from the register table into a database; and processing the data imported into the database to generate a design specification for the functional block, the design specification being generated to implement the identified characteristics of each register, wherein each operation of the method is executed by a processor. 3. The method of claim 1 , wherein the method operation of accessing a register table identifying characteristics of each register for a functional block of the circuit includes: identifying control and status registers defined in a hardware description language; and generating the register table from the identified control and status registers.

2. The at least one computer readable medium of claim 1 , wherein the first set includes a plurality of fields, and wherein automatically analyzing includes, for each field of the plurality of fields in the first set, automatically analyzing the medical transcription to identify at least one indicating phrase associated with each field.

2. The at least one computer readable medium of claim 1 , wherein the first set includes a plurality of fields, and wherein automatically analyzing includes, for each field of the plurality of fields in the first set, automatically analyzing the medical transcription to identify at least one indicating phrase associated with each field. 5. The at least one computer readable medium of claim 2 , wherein associating the text disposed proximately to the at least one indicating phrase includes adding an indicator to the text disposed proximately to the at least one indicating phrase.

1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a request to search the resume database; receive search criteria; send a database query to the resume database, the database query including the search criteria; receive a result set in response to the database query, the result set including at least one matching resume; and send the result set in a response to the request, wherein the resume database includes at least one resume, and a parsed resume associated with each resume, wherein each resume includes at least one skill or experience-related phrase, wherein each skill or experience-related phrase has an experience range determined by examining a use of the skill or experience-related phrase in the resume, and a term of experience based on the experience range, wherein the term of experience for each skill or experience-related phrase having multiple occurrences in the resume is a summation of the term of experience, or a portion of the term of experience, for each occurrence of the skill or experience-related phrase associated with a different experience range, wherein each parsed resume includes each said at least one skill or experience-related phrase located in the resume, the term of experience for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase, and wherein each matching resume is one of said at least one resume having the parsed resume associated with the matching resume satisfying the search criteria.

1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a request to search the resume database; receive search criteria; send a database query to the resume database, the database query including the search criteria; receive a result set in response to the database query, the result set including at least one matching resume; and send the result set in a response to the request, wherein the resume database includes at least one resume, and a parsed resume associated with each resume, wherein each resume includes at least one skill or experience-related phrase, wherein each skill or experience-related phrase has an experience range determined by examining a use of the skill or experience-related phrase in the resume, and a term of experience based on the experience range, wherein the term of experience for each skill or experience-related phrase having multiple occurrences in the resume is a summation of the term of experience, or a portion of the term of experience, for each occurrence of the skill or experience-related phrase associated with a different experience range, wherein each parsed resume includes each said at least one skill or experience-related phrase located in the resume, the term of experience for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase, and wherein each matching resume is one of said at least one resume having the parsed resume associated with the matching resume satisfying the search criteria. 5. The system of claim 1 , wherein to receive the result set, the processor is further configured to: receive a portion of the result set in response to the database query.

14. The system of claim 12 , wherein: determining that a term of the original query is a potentially inaccurate term comprises determining that the term is typographically incorrect; and generating one or more derivative queries from the original query comprises generating a derivative query that includes only the terms of the original query that are not the potentially inaccurate term.

14. The system of claim 12 , wherein: determining that a term of the original query is a potentially inaccurate term comprises determining that the term is typographically incorrect; and generating one or more derivative queries from the original query comprises generating a derivative query that includes only the terms of the original query that are not the potentially inaccurate term. 16. The system of claim 14 , wherein determining that the term is typographically incorrect comprises determining a usage quality measure that is a measure of quality of term usage of synonym terms in the context of the resources.

1. A computer implemented method comprising: receiving an abstract phrase comprising a text phrase and a variable at a particular position in the text phrase; receiving a text value for the variable; combining the text phrase of the abstract phrase and the text value according to the particular position of the variable; and applying, by a computer system, an integration rule at a boundary of the text phrase of the abstract phrase and the text value to produce an integrated phrase, the integration rule based on a language rule, wherein the integration rule changes a portion of a word of the text phrase of the abstract phrase or a portion of a word of the text value so that the text phrase and the text value comply with the integration rule.

1. A computer implemented method comprising: receiving an abstract phrase comprising a text phrase and a variable at a particular position in the text phrase; receiving a text value for the variable; combining the text phrase of the abstract phrase and the text value according to the particular position of the variable; and applying, by a computer system, an integration rule at a boundary of the text phrase of the abstract phrase and the text value to produce an integrated phrase, the integration rule based on a language rule, wherein the integration rule changes a portion of a word of the text phrase of the abstract phrase or a portion of a word of the text value so that the text phrase and the text value comply with the integration rule. 2. The method of claim 1 : wherein combining the text phrase of the abstract phrase and the text value comprises: creating a delimited phrase, comprising: inserting the text value into the abstract phrase at the particular position indicated by the variable; and inserting a delimiter before and/or after the inserted text value; wherein applying the integration rule comprises: determining whether the delimited phrase satisfies a condition of the rule, the determining based at least in part on the location of a delimiter within the delimited phrase; responsive to the determination, performing an action of the rule, the action comprising modifying the delimited phrase; and wherein the method further comprises: creating an integrated phrase, comprising removing delimiters from the delimited phrase.

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

1. A speech recognition dictionary creating support device comprising: a speech data storage section storing speech data; a prosodic information extracting section extracting prosodic information including at least a speech power value from the speech data; a speech data dividing section extracting an utterance section having a period with a power value equal to or larger than a predetermined threshold value lasting a preset time or longer from the speech data based on the prosodic information, and dividing the utterance section into sections, each of which has a power value equal to or lamer than a predetermined threshold value continuing for a given time or longer, to generate divided speech data; a phoneme sequence acquiring section executing a phoneme recognition process on the divided speech data to acquire phoneme sequence data for each divided speech data; a clustering section executing a clustering process on the phoneme sequence data to generate clusters each of which is a set of classified phoneme sequence data; an evaluation value calculating section calculating an evaluation value for each of the clusters based on the prosodic information for the divided speech data corresponding to the phoneme sequence data constituting the cluster; a candidate cluster selecting section selecting clusters for which the evaluation value is equal to or larger than a given value, as candidate clusters; and a listening target data selecting section determining one of the phoneme sequence data from the phoneme sequence data constituting the cluster for each of the candidate clusters to be a representative phoneme sequence and selecting the divided speech data corresponding to the representative phoneme sequence, as listening target speech data, and wherein the evaluation value calculating section includes dictionary data for a morpheme analysis process, and extracts a phrase classified as a predetermined word class from the dictionary data, calculates an appearance probability, in the extracted phrase, of a common phoneme subsequence constituting in the cluster, and calculates the evaluation value for the cluster based on the appearance probability. 4. The speech recognition dictionary creating support device according to claim 1 , wherein the evaluation value calculating section calculates an appearance frequency of each phoneme sequence data in all the divided speech data, and calculates the evaluation value for the cluster based on the appearance frequency.

1. A method of defining a JavaScript (JS) object to process application programming interface (API) requests, the method comprising: defining a JS file to define a set of behavioral descriptions of the JS object; in response to a determination that a request to add a set of properties has been received, defining a JS object notation (JSON) file to define a set of property descriptions of the JS object; based on a common name for the JS and JSON files, creating an association between the JS and JSON files; attaching the associated JS and JSON files to a data source abstractor upon receiving a request for such; and storing the JS and JSON files on a machine readable medium, wherein the association allows an object instantiator to instantiate the JS object from the behavioral description in the JS file and the property description in the JSON file, wherein the instantiated JS object processes API requests received from a plurality of devices to provide data from a plurality of resources to the plurality of devices.

1. A method of defining a JavaScript (JS) object to process application programming interface (API) requests, the method comprising: defining a JS file to define a set of behavioral descriptions of the JS object; in response to a determination that a request to add a set of properties has been received, defining a JS object notation (JSON) file to define a set of property descriptions of the JS object; based on a common name for the JS and JSON files, creating an association between the JS and JSON files; attaching the associated JS and JSON files to a data source abstractor upon receiving a request for such; and storing the JS and JSON files on a machine readable medium, wherein the association allows an object instantiator to instantiate the JS object from the behavioral description in the JS file and the property description in the JSON file, wherein the instantiated JS object processes API requests received from a plurality of devices to provide data from a plurality of resources to the plurality of devices. 2. The method of claim 1 , wherein at least one of the plurality of resources comprises a data storage, wherein the set of property descriptions of the JSON file comprises a description of the data storage that enables the JS object to retrieve data from the data storage.

17. A system comprising: one or more processors; and a memory, coupled to the one or more processors, comprising program instructions that, responsive to execution by the one or more processors, cause the one or more processors to: generate a first event record associated with one or more telephone calls handled by one or more telecommunications systems in one or more networks; apply, using a first fraud detection test, a first fraud detection rule of a plurality of fraud detection rules to the first event record, the first event record being of an account and corresponding to information associated with suspected fraud at a first time; generate, based on applying the first fraud detection rule, a first fraud alarm; generate a second event record associated with the one or more telephone calls handled by the one or more telecommunications systems in the one or more networks, the second event record being of the account and corresponding to the information associated with the suspected fraud at a second time; apply, using a second fraud detection test, a dynamically reconfigured fraud detection rule, of a plurality of dynamically reconfigured fraud detection rules, to the second event record; generate, based on applying the dynamically reconfigured fraud detection rule, a second fraud alarm, the second fraud alarm being different than the first fraud alarm; obtain first information from a plurality of devices; obtain an enhanced first fraud alarm by enhancing the first fraud alarm based on the first information, the first information being based on a first type of alarm associated with the first fraud alarm, and the first information including additional information and information indicating how the additional information is to be added to the first fraud alarm to obtain the enhanced first fraud alarm; obtain second information from the plurality of devices; obtain an enhanced second fraud alarm by enhancing the second fraud alarm based on the second information, the second information being based on a second type of alarm associated with the second fraud alarm, and the second information including other information and information indicating how the other information is to be added to the second fraud alarm to obtain the enhanced second fraud alarm; correlate the enhanced first fraud alarm with the enhanced second fraud alarm into a fraud case for the account; and institute one or more switch-based automatic number identification (ANI) blocks based on correlating the enhanced first fraud alarm with the enhanced second fraud alarm.

17. A system comprising: one or more processors; and a memory, coupled to the one or more processors, comprising program instructions that, responsive to execution by the one or more processors, cause the one or more processors to: generate a first event record associated with one or more telephone calls handled by one or more telecommunications systems in one or more networks; apply, using a first fraud detection test, a first fraud detection rule of a plurality of fraud detection rules to the first event record, the first event record being of an account and corresponding to information associated with suspected fraud at a first time; generate, based on applying the first fraud detection rule, a first fraud alarm; generate a second event record associated with the one or more telephone calls handled by the one or more telecommunications systems in the one or more networks, the second event record being of the account and corresponding to the information associated with the suspected fraud at a second time; apply, using a second fraud detection test, a dynamically reconfigured fraud detection rule, of a plurality of dynamically reconfigured fraud detection rules, to the second event record; generate, based on applying the dynamically reconfigured fraud detection rule, a second fraud alarm, the second fraud alarm being different than the first fraud alarm; obtain first information from a plurality of devices; obtain an enhanced first fraud alarm by enhancing the first fraud alarm based on the first information, the first information being based on a first type of alarm associated with the first fraud alarm, and the first information including additional information and information indicating how the additional information is to be added to the first fraud alarm to obtain the enhanced first fraud alarm; obtain second information from the plurality of devices; obtain an enhanced second fraud alarm by enhancing the second fraud alarm based on the second information, the second information being based on a second type of alarm associated with the second fraud alarm, and the second information including other information and information indicating how the other information is to be added to the second fraud alarm to obtain the enhanced second fraud alarm; correlate the enhanced first fraud alarm with the enhanced second fraud alarm into a fraud case for the account; and institute one or more switch-based automatic number identification (ANI) blocks based on correlating the enhanced first fraud alarm with the enhanced second fraud alarm. 18. The system of claim 17 , where the one or more processors, when correlating the enhanced first fraud alarm with the enhanced second fraud alarm, are to: correlate the enhanced first fraud alarm with the enhanced second fraud alarm based on common aspects of the first fraud alarm and the second fraud alarm, and the one or more processors, when generating the first fraud alarm, are to: conform the first event record to a predetermined format by normalizing the first event record.

1. A method for reporting traffic information using pre-recorded audio, comprising the steps of: receiving data for a set of traffic incidents, said data including parameters for each of said traffic incidents, one or more of said parameters include at least one code representing a value for said parameter; identifying groups of files that store speech for describing said traffic incidents, each group of files is associated with at least one of said incidents, said step of identifying groups comprises the steps of: for each incident of at least a subset of said traffic incidents, accessing parameters for said incident, and for each parameter of at least a subset of said accessed parameters, identifying one or more files that store speech using a set of information correlating codes for said parameter to references to audio files; and automatically presenting said stored speech from each group of files.

1. A method for reporting traffic information using pre-recorded audio, comprising the steps of: receiving data for a set of traffic incidents, said data including parameters for each of said traffic incidents, one or more of said parameters include at least one code representing a value for said parameter; identifying groups of files that store speech for describing said traffic incidents, each group of files is associated with at least one of said incidents, said step of identifying groups comprises the steps of: for each incident of at least a subset of said traffic incidents, accessing parameters for said incident, and for each parameter of at least a subset of said accessed parameters, identifying one or more files that store speech using a set of information correlating codes for said parameter to references to audio files; and automatically presenting said stored speech from each group of files. 39. A method according to claim 1, wherein: said step of automatically presenting includes presenting an audio/visual program that includes said stored speech, said audio/visual program does not require user interaction during presentation.

18. The system of claim 13 , wherein the processor operatively coupled to the memory is further configured to transform the sensitivity matrix into a second matrix wherein each sub-matrix in the second matrix contains class identity information about an exemplar from a same sub-matrix of the sensitivity matrix.

18. The system of claim 13 , wherein the processor operatively coupled to the memory is further configured to transform the sensitivity matrix into a second matrix wherein each sub-matrix in the second matrix contains class identity information about an exemplar from a same sub-matrix of the sensitivity matrix. 19. The system of claim 18 , wherein the class identity for each sub-matrix in the second matrix is created from a set of one or more indexes corresponding to a class identity in a same sub-matrix in the sensitivity matrix.