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AIPD_nlp_sentence_dataset_v2

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9. A computer-readable storage medium containing a program which, when executed by a processor, performs an operation for identifying anomaly object types during classification of image data captured by a video camera, the operation comprising: receiving a micro-feature vector including multiple micro-feature values, each micro-feature value based on at least one pixel-level characteristic of a foreground patch that depicts a foreground object within the image data; classifying the foreground object as depicting a first object type corresponding to a first object type cluster of the object type clusters based on the micro-feature vector; computing a probability density function for the object type clusters; computing a probability density value for the micro-feature vector; evaluating a rareness measure of the micro-feature vector, wherein the rareness measure estimates a likelihood of observing the micro-feature vector, based on the probability density function and the probability density value; and identifying the foreground object as an anomaly object type when the rareness measure is below a specified threshold.

9. A computer-readable storage medium containing a program which, when executed by a processor, performs an operation for identifying anomaly object types during classification of image data captured by a video camera, the operation comprising: receiving a micro-feature vector including multiple micro-feature values, each micro-feature value based on at least one pixel-level characteristic of a foreground patch that depicts a foreground object within the image data; classifying the foreground object as depicting a first object type corresponding to a first object type cluster of the object type clusters based on the micro-feature vector; computing a probability density function for the object type clusters; computing a probability density value for the micro-feature vector; evaluating a rareness measure of the micro-feature vector, wherein the rareness measure estimates a likelihood of observing the micro-feature vector, based on the probability density function and the probability density value; and identifying the foreground object as an anomaly object type when the rareness measure is below a specified threshold. 10. The computer-readable storage medium of claim 9 , wherein the foreground object is identified as the anomaly object type when the rareness measure is greater than a threshold value.

1. A method, implemented in a computer system, of associating an input/output device with a portable scanner, comprising: receiving, at a computer system and from a scanner, a device identifier scanned from the scanner while displayed on an electronic device; associating, in a database in the computer system, the electronic device with the scanner based at least in part on the device identifier of the electronic device; receiving, at the computer system and from the scanner, scanned data scanned by the scanner; selecting, by the computer system, based at least in part on the device identifier associated with the scanner, the electronic device to send the scanned data; and sending, by the computer system, the scanned data to the selected electronic device.

1. A method, implemented in a computer system, of associating an input/output device with a portable scanner, comprising: receiving, at a computer system and from a scanner, a device identifier scanned from the scanner while displayed on an electronic device; associating, in a database in the computer system, the electronic device with the scanner based at least in part on the device identifier of the electronic device; receiving, at the computer system and from the scanner, scanned data scanned by the scanner; selecting, by the computer system, based at least in part on the device identifier associated with the scanner, the electronic device to send the scanned data; and sending, by the computer system, the scanned data to the selected electronic device. 6. The method of claim 1 , further comprising: establishing a communication session with the electronic device based, at least in part, on the received device identifier.

1. One or more computer-readable storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method for entity conflation using a persistent entity index, the method comprising: receiving information about an entity, the information including at least one attribute associated with the entity, the at least one attribute describing a characteristic of the entity; matching the entity with one or more existing entities in the persistent entity index, wherein the persistent entity index includes entity-attribute pairs associated therewith and the entity-attribute pairs include all received attributes that describe one or more characteristics of an associated entity; determining whether the at least one attribute describing the one or more characteristics of the entity is present within the persistent entity index; aggregating the at least one attribute associated with the entity with the entity-attribute pairs within the persistent entity index; and incrementally updating the persistent entity index to include updated entity-attribute pairs including any subsequently received attributes describing one or more characteristics of the entity at a predetermined time interval.

1. One or more computer-readable storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method for entity conflation using a persistent entity index, the method comprising: receiving information about an entity, the information including at least one attribute associated with the entity, the at least one attribute describing a characteristic of the entity; matching the entity with one or more existing entities in the persistent entity index, wherein the persistent entity index includes entity-attribute pairs associated therewith and the entity-attribute pairs include all received attributes that describe one or more characteristics of an associated entity; determining whether the at least one attribute describing the one or more characteristics of the entity is present within the persistent entity index; aggregating the at least one attribute associated with the entity with the entity-attribute pairs within the persistent entity index; and incrementally updating the persistent entity index to include updated entity-attribute pairs including any subsequently received attributes describing one or more characteristics of the entity at a predetermined time interval. 3. The one or more computer-readable storage media of claim 1 , wherein ranking the entity with respect to the one or more matched existing entities comprises ranking the entity utilizing the at least one attribute and using the machine-learning approach.

5. The method according to claim 1 , wherein the selecting the matching website comprises: comparing the search term and each of the identified other websites; and choosing one of the other websites having the highest similarity to the search term as the matching website.

5. The method according to claim 1 , wherein the selecting the matching website comprises: comparing the search term and each of the identified other websites; and choosing one of the other websites having the highest similarity to the search term as the matching website. 7. The method according to claim 5 , wherein the comparing comprises: calculating a number of same or similar topics shared by the search term and the identified other websites.

1. A method of generating at least one font file customized to a specific multimedia file that includes textual elements, the method comprising: receiving a multimedia file including audio data, video data, and a track containing subtitle textual elements and a corresponding original font file by a processor; identifying a plurality of time segments within the multimedia file including audio data, video data, and associated textual elements using the processor; generating a unique character set for each time segment including each of the characters in the textual elements associated with the time segment; generating at least one modified font file for each time segment including fewer characters than the original font file, and all of the characters in the unique character set associated with the time segment, by the processor, wherein each modified font file is specifically matched to the textual elements associated with an identified time segment; marking each modified font file to signify a time period during the playback of audio data and video data in which the modified font file is dynamically accessible within the memory of a playback device for rendering associated textual elements; and incorporating the modified font files into the multimedia file.

1. A method of generating at least one font file customized to a specific multimedia file that includes textual elements, the method comprising: receiving a multimedia file including audio data, video data, and a track containing subtitle textual elements and a corresponding original font file by a processor; identifying a plurality of time segments within the multimedia file including audio data, video data, and associated textual elements using the processor; generating a unique character set for each time segment including each of the characters in the textual elements associated with the time segment; generating at least one modified font file for each time segment including fewer characters than the original font file, and all of the characters in the unique character set associated with the time segment, by the processor, wherein each modified font file is specifically matched to the textual elements associated with an identified time segment; marking each modified font file to signify a time period during the playback of audio data and video data in which the modified font file is dynamically accessible within the memory of a playback device for rendering associated textual elements; and incorporating the modified font files into the multimedia file. 6. The method of claim 1 wherein the generated font file is not guaranteed to be useable for another multimedia file different from the received multimedia file.

3. The method of claim 2 , wherein the searching the one or more repositories comprises searching for the relation between the topic information and one or more types of terminologies related to the knowledge information, wherein the determining one or more metaphors is based at least in part on the one or more types of terminologies.

3. The method of claim 2 , wherein the searching the one or more repositories comprises searching for the relation between the topic information and one or more types of terminologies related to the knowledge information, wherein the determining one or more metaphors is based at least in part on the one or more types of terminologies. 4. The method of claim 3 , further comprising obtaining a selection of the one or more types of terminologies from an interface.

4. A distributed capture system for managing legacy documents, the distributed capture system comprising: a data storage device; and a processor operatively coupled to a memory device, said data storage device, and a user-input device configured to receive an input from a user, the processor being configured to, receive an electronic legacy document, wherein said electronic legacy document is one of a plurality of original electronic formats, determine whether the electronic legacy document requires a user input from the user, enable the user to input a user input via the user-input device, wherein if said user input is detected, the user input is subsequently applied to the electronic legacy document pursuant to a predetermined rule, and if no user input is detected, then the processor enables the conversion of the electronic legacy document, convert the electronic legacy document, including any user input applied to the electronic legacy document, from the one of a plurality of original electronic formats to a predetermined format that is compatible with a plurality of different document management systems, said predetermined format comprising an image portion and a text portion, generate an index having a plurality of document keywords, wherein the index is generated based at least in part on the text portion associated with the electronic legacy document, access one or more document classification templates, each of said one or more document classification templates representing a different document type, wherein each of said one or more document classification templates comprises one or more template keywords, compare one or more of said document keywords with one or more of said template keywords for one or more of said document classification templates, automatically match the electronic legacy document with one or more document classification templates identified during said comparison step, automatically classify the electronic legacy document as one or more of a plurality of document types based at least in part upon the one or more document classification template matches identified during said match step, and store the electronic legacy document to said data storage device.

4. A distributed capture system for managing legacy documents, the distributed capture system comprising: a data storage device; and a processor operatively coupled to a memory device, said data storage device, and a user-input device configured to receive an input from a user, the processor being configured to, receive an electronic legacy document, wherein said electronic legacy document is one of a plurality of original electronic formats, determine whether the electronic legacy document requires a user input from the user, enable the user to input a user input via the user-input device, wherein if said user input is detected, the user input is subsequently applied to the electronic legacy document pursuant to a predetermined rule, and if no user input is detected, then the processor enables the conversion of the electronic legacy document, convert the electronic legacy document, including any user input applied to the electronic legacy document, from the one of a plurality of original electronic formats to a predetermined format that is compatible with a plurality of different document management systems, said predetermined format comprising an image portion and a text portion, generate an index having a plurality of document keywords, wherein the index is generated based at least in part on the text portion associated with the electronic legacy document, access one or more document classification templates, each of said one or more document classification templates representing a different document type, wherein each of said one or more document classification templates comprises one or more template keywords, compare one or more of said document keywords with one or more of said template keywords for one or more of said document classification templates, automatically match the electronic legacy document with one or more document classification templates identified during said comparison step, automatically classify the electronic legacy document as one or more of a plurality of document types based at least in part upon the one or more document classification template matches identified during said match step, and store the electronic legacy document to said data storage device. 14. The distributed capture system of claim 4 , wherein the distributed capture system is configured to communicate the electronic legacy document to a separate computer system.

19. The method of claim 1 : further comprising, measuring a dialog attribute trend over the course of the dialog; and wherein effecting includes, effecting a next dialog rule in response to the dialog attribute trend.

19. The method of claim 1 : further comprising, measuring a dialog attribute trend over the course of the dialog; and wherein effecting includes, effecting a next dialog rule in response to the dialog attribute trend. 20. The method of claim 19 : wherein measuring includes, monitoring how an evolution of the dialog resulted in the dialog attribute reaching the instantaneous value.

19. An interactive shopping advisor comprising: one or more processors for executing programs; a non-transitory memory operatively coupled to the one or more processors; a network interface device operatively coupled to the one or more processors for communicating with a user via a communications network; and a program stored in the memory for: configuring a plurality of long short term memory modules as a recurrent neural network, wherein the plurality of long short term memory modules are each provided with one or more respective gates for determining when a corresponding input value of a plurality of input values should persist in memory, and when the corresponding input value should comprise an output value; receiving a natural language query for a product search, wherein each respective long short term memory module of the plurality of long short term memory modules receives a corresponding word from the natural language query; generating an initial product recommendation from the natural language query; receiving a natural language preference parameter for refining the product search; mapping the natural language preference parameter to a product attribute value for the product search; identifying an adjustment orientation of the product attribute value from the natural language preference parameter; and applying the adjustment orientation to the natural language query to provide a refined product recommendation for the product search by determining, for each of the one or more respective gates, when the corresponding input value should persist in memory, and when the corresponding input value should comprise an output value.

19. An interactive shopping advisor comprising: one or more processors for executing programs; a non-transitory memory operatively coupled to the one or more processors; a network interface device operatively coupled to the one or more processors for communicating with a user via a communications network; and a program stored in the memory for: configuring a plurality of long short term memory modules as a recurrent neural network, wherein the plurality of long short term memory modules are each provided with one or more respective gates for determining when a corresponding input value of a plurality of input values should persist in memory, and when the corresponding input value should comprise an output value; receiving a natural language query for a product search, wherein each respective long short term memory module of the plurality of long short term memory modules receives a corresponding word from the natural language query; generating an initial product recommendation from the natural language query; receiving a natural language preference parameter for refining the product search; mapping the natural language preference parameter to a product attribute value for the product search; identifying an adjustment orientation of the product attribute value from the natural language preference parameter; and applying the adjustment orientation to the natural language query to provide a refined product recommendation for the product search by determining, for each of the one or more respective gates, when the corresponding input value should persist in memory, and when the corresponding input value should comprise an output value. 23. The interactive shopping advisor of claim 19 further configured for constructing a plurality of value-word pairs for a product attribute, each value-word pair comprising a respective product attribute value associated with a corresponding comment word.

25. A server, comprising: a processor configured with processor-executable instructions to perform operations comprising: applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors; computing an answer ratio for one or more nodes of the boosted decision tree; and determining which factors in the first family of classifier models have a high probability of enabling a mobile device to conclusively determine whether a mobile device behavior is not benign based on computed answer ratios.

25. A server, comprising: a processor configured with processor-executable instructions to perform operations comprising: applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors; computing an answer ratio for one or more nodes of the boosted decision tree; and determining which factors in the first family of classifier models have a high probability of enabling a mobile device to conclusively determine whether a mobile device behavior is not benign based on computed answer ratios. 26. The server of claim 25 , wherein the processor is configured with processor-executable instructions to perform operations further comprising: applying the factors to the corpus of behavior vectors to generate a second family of classifier models that identify fewer data points as being relevant for enabling the mobile device to conclusively determine whether the mobile device behavior is not benign; and generating a mobile device classifier based on the second family of classifier models.

13. A computer system for automatically determining document relevance, the computer system comprising computer hardware configured to perform operations comprising: representing a plurality of terms as a tree data structure comprising internal nodes and leaf nodes interconnected by respective node connections; assigning to each of the leaf nodes of the tree data structure a respective one of the terms; assigning to at least one of the leaf nodes a respective location specifying a designated location for the term assigned to the leaf node to appear within a document; assigning a respective operator to each of the internal nodes of the tree data structure; assigning a respective operator to each of the node connections in the tree data structure; and calculating a respective relevance value for at least one document as a function of occurrence in the at least one document of the terms respectively assigned to the leaf nodes of the tree data structure, the operators assigned to parent internal nodes of the corresponding leaf nodes, and the weights assigned to the associated node connections and, for each of the leaf nodes assigned a respective location, occurrence of the term assigned to the leaf node at the location in the at least one document specified by the respective location assigned to the leaf node.

13. A computer system for automatically determining document relevance, the computer system comprising computer hardware configured to perform operations comprising: representing a plurality of terms as a tree data structure comprising internal nodes and leaf nodes interconnected by respective node connections; assigning to each of the leaf nodes of the tree data structure a respective one of the terms; assigning to at least one of the leaf nodes a respective location specifying a designated location for the term assigned to the leaf node to appear within a document; assigning a respective operator to each of the internal nodes of the tree data structure; assigning a respective operator to each of the node connections in the tree data structure; and calculating a respective relevance value for at least one document as a function of occurrence in the at least one document of the terms respectively assigned to the leaf nodes of the tree data structure, the operators assigned to parent internal nodes of the corresponding leaf nodes, and the weights assigned to the associated node connections and, for each of the leaf nodes assigned a respective location, occurrence of the term assigned to the leaf node at the location in the at least one document specified by the respective location assigned to the leaf node. 16. The computer system of claim 13 wherein the computer hardware is to perform operations comprising: calculating a relevance value for at least one document for the terms assigned to leaf nodes of the tree structure; and presenting to a user as results of a search query at least one document resulting from the search query meeting a given relevance threshold value.

2. The non-transitory computer-readable recording medium according to claim 1 , further comprising evaluating a heading candidate when among the determined sets are a first set including a data item and the headings identifying the data item and a second set where among the headings, a single heading is positioned differently from the headings of the first set, wherein the evaluating includes selecting, as a proper determined set, the first set or the second set based on a position of the single heading and a position of the data item, and the outputting includes outputting the proper determined set.

2. The non-transitory computer-readable recording medium according to claim 1 , further comprising evaluating a heading candidate when among the determined sets are a first set including a data item and the headings identifying the data item and a second set where among the headings, a single heading is positioned differently from the headings of the first set, wherein the evaluating includes selecting, as a proper determined set, the first set or the second set based on a position of the single heading and a position of the data item, and the outputting includes outputting the proper determined set. 3. The non-transitory computer-readable recording medium according to claim 2 , wherein the evaluating includes selecting the proper determined set based on the position of the single heading on the form relative to the data item.

51. A computer-aided learning system for more than one user to work on a subject, the system comprising: a notepad for a user to take notes while working on the subject through the system; a controller configured to set a duration of time for users to communicate among themselves in a dialogue session to allow them to work on materials on the subject, monitor at least one user's input during the dialogue session so as to have the monitored input available for analysis, and guide the user to take notes; and wherein the guidance to take notes is based on at least one of the user's inputs when the user is working on the subject; and based on the analysis, the controller guides at least one user back to the subject in the dialogue session when one or more users have been distracted from the subject for a duration of time.

51. A computer-aided learning system for more than one user to work on a subject, the system comprising: a notepad for a user to take notes while working on the subject through the system; a controller configured to set a duration of time for users to communicate among themselves in a dialogue session to allow them to work on materials on the subject, monitor at least one user's input during the dialogue session so as to have the monitored input available for analysis, and guide the user to take notes; and wherein the guidance to take notes is based on at least one of the user's inputs when the user is working on the subject; and based on the analysis, the controller guides at least one user back to the subject in the dialogue session when one or more users have been distracted from the subject for a duration of time. 52. A computer-aided learning system as recited in claim 51 wherein the system is configured to allow the user to cut materials the user has received, and paste the materials in the notepad.

14. A computer-implemented method of generating automated tags for a video file, the method comprising: generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; generating a list of top concepts for the video file in light of the one or more automated tags associated with the video file; establishing a relationship between the video file and at least one other video file based on corresponding top concepts between the video file and the at least one other video file; and generating a heat map for the video file, wherein the heat map comprises a graphical display that indicates offset locations of words within the video file with the highest rankings.

14. A computer-implemented method of generating automated tags for a video file, the method comprising: generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; generating a list of top concepts for the video file in light of the one or more automated tags associated with the video file; establishing a relationship between the video file and at least one other video file based on corresponding top concepts between the video file and the at least one other video file; and generating a heat map for the video file, wherein the heat map comprises a graphical display that indicates offset locations of words within the video file with the highest rankings. 18. The computer-implemented method of generating automated tags for a video file as in claim 14 , further comprising cross-referencing words with the plurality of words to determine correlations between words or to construct phrases, wherein the cross-referencing of the word or words is configured to increase the ranking of the word or words.

9. A system comprising: a computing device that includes at least one processor, memory, and at least one program module according to which the computing device is configured to: maintain an index that comprises tokens that correspond to words that are included in a file in a storage including words added to the file and words deleted from the file, wherein the maintained index of tokens correspond to the added words and the deleted words; determine whether the file is located in a protected namespace; receive an event indicative of deletion of the file; when the file is located in the protected namespace: copy the file to backup storage; update the index with new tokens corresponding to added words included in the file; maintain tokens for added words and deleted words in the index subsequent to the file in the protected namespace being deleted from the storage, wherein the maintained tokens correspond to the added and deleted words; and delete the file from the storage.

9. A system comprising: a computing device that includes at least one processor, memory, and at least one program module according to which the computing device is configured to: maintain an index that comprises tokens that correspond to words that are included in a file in a storage including words added to the file and words deleted from the file, wherein the maintained index of tokens correspond to the added words and the deleted words; determine whether the file is located in a protected namespace; receive an event indicative of deletion of the file; when the file is located in the protected namespace: copy the file to backup storage; update the index with new tokens corresponding to added words included in the file; maintain tokens for added words and deleted words in the index subsequent to the file in the protected namespace being deleted from the storage, wherein the maintained tokens correspond to the added and deleted words; and delete the file from the storage. 11. The system of claim 9 in which the file is in a non-protected namespace when it is not designated for backup to the backup storage.

1. A computer system for displaying a user interface, comprising: a storage medium; and a display, wherein the computer system is enabled to parse information received by the computer system into component portions of the received information, determine raw features of the component portions, and visually render on the display a user interface comprising: a first region displaying at least one of the component portions of the parsed information; and a second region enabled to receive user input designating a hierarchical level of at least one of the displayed component portions of the parsed information with respect to other component portions based on the determined raw features, wherein the computer system stores an association between said user input and the at least one of the component portions of the parsed information, wherein said association is used to train model parameters of an algorithm for automatically determining the hierarchical levels of component portions of parsed information from said raw features, wherein the computer system is further enabled to store multiple associations linking user input to multiple component portions of the parsed information, respectively, and train model parameters of an algorithm for determining the hierarchical levels of component portions of parsed information, using said multiple associations.

1. A computer system for displaying a user interface, comprising: a storage medium; and a display, wherein the computer system is enabled to parse information received by the computer system into component portions of the received information, determine raw features of the component portions, and visually render on the display a user interface comprising: a first region displaying at least one of the component portions of the parsed information; and a second region enabled to receive user input designating a hierarchical level of at least one of the displayed component portions of the parsed information with respect to other component portions based on the determined raw features, wherein the computer system stores an association between said user input and the at least one of the component portions of the parsed information, wherein said association is used to train model parameters of an algorithm for automatically determining the hierarchical levels of component portions of parsed information from said raw features, wherein the computer system is further enabled to store multiple associations linking user input to multiple component portions of the parsed information, respectively, and train model parameters of an algorithm for determining the hierarchical levels of component portions of parsed information, using said multiple associations. 9. The computer system according to claim 1 , further comprising: a third region, upon whose interaction with, provides at least one alternate view in said first region of said information having been parsed.

29. A computer-readable medium having stored thereon a data structure for processing documents in a document database, the computer-readable medium comprising: a first data field for generating an initial ranking of retrieved documents using an information retrieval system and based upon a user search query provided by a user; a second data field for displaying to the user the initial ranking of the retrieved documents; a third data field for permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents; a fourth data field for generating respective relevancies of the user-selected vocabulary words; a fifth data field for generating a re-ranking of the retrieved documents based on the generated respective relevancies of the vocabulary words; a sixth data field for displaying for the user the re-ranking of the documents, and for each document being displayed, also displaying its initial ranking; and a seventh data field for generating the plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents before generating the initial ranking of retrieved documents.

29. A computer-readable medium having stored thereon a data structure for processing documents in a document database, the computer-readable medium comprising: a first data field for generating an initial ranking of retrieved documents using an information retrieval system and based upon a user search query provided by a user; a second data field for displaying to the user the initial ranking of the retrieved documents; a third data field for permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents; a fourth data field for generating respective relevancies of the user-selected vocabulary words; a fifth data field for generating a re-ranking of the retrieved documents based on the generated respective relevancies of the vocabulary words; a sixth data field for displaying for the user the re-ranking of the documents, and for each document being displayed, also displaying its initial ranking; and a seventh data field for generating the plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents before generating the initial ranking of retrieved documents. 35. A computer-readable medium according to claim 29 further comprising an eleventh data field for selecting N top ranked documents from the retrieved documents before processing the plurality of vocabulary words, with N being an integer greater than 1; and wherein generating the respective relevancies in said third data field and generating the re-ranking in said fourth data field are with respect to the N top-ranked documents.

24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer.

24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer. 27. The method of claim 24 , wherein observations on the database messages based at least in part on the query-language statements extracted at the decoding layer comprise one or more of the following: subject database instances of the query-language statements; vendors of database implementations of the subject database instances; software and versions of the software in the database implementations; network protocols and versions of the network protocols used to communicate the database messages; protocol drivers at the database servers, versions of the protocol drivers, and application programming interfaces (APIs) at the database servers; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; protocol drivers at the clients, versions of the protocol drivers, and APIs at the clients; devices hosting the clients; application frameworks at the clients; hostnames, IP addresses, MAC addresses, and network ports of the clients 12 ; OSs, versions of the OSs, and attributes of the OSs of the clients 12 ; a number of queries communicated from each of the clients to each of one or more database instances; and a rate at which queries communicated from each of the clients to each of one or more database instances.

9. A computer-implemented method for analyzing requirements data, comprising: receiving a search query comprising search terms; identifying a first requirement based on a degree of relatedness between the search terms and the textual content of the first requirement; identifying a plurality of soft links between the first requirement and a plurality of related requirements, wherein each of the plurality of soft links represents a relatedness score between the first requirement and a related requirement from the plurality of related requirements, and each of the relatedness scores exceeds a threshold; ranking the plurality of related requirements based on their relatedness scores; and providing the highest ranked requirement to a user via a computer device.

9. A computer-implemented method for analyzing requirements data, comprising: receiving a search query comprising search terms; identifying a first requirement based on a degree of relatedness between the search terms and the textual content of the first requirement; identifying a plurality of soft links between the first requirement and a plurality of related requirements, wherein each of the plurality of soft links represents a relatedness score between the first requirement and a related requirement from the plurality of related requirements, and each of the relatedness scores exceeds a threshold; ranking the plurality of related requirements based on their relatedness scores; and providing the highest ranked requirement to a user via a computer device. 13. The computer-implemented method of claim 9 , further comprising adding a related term to the search query that is determined by a subject matter expert or technician to be related to a search term.

13. The search engine server of claim 12 , wherein the processing circuitry, memory, and network circuitry are further operable to match synonyms of the conjugate English terms to that of text associated with websites having international language support, resulting in a listing of websites that match the retrieved synonyms.

13. The search engine server of claim 12 , wherein the processing circuitry, memory, and network circuitry are further operable to match synonyms of the conjugate English terms to that of text associated with websites having international language support, resulting in a listing of websites that match the retrieved synonyms. 14. The search engine server of claim 13 , wherein the processing circuitry, memory, and network circuitry are further operable to rank the listed websites having international language support, wherein ranking is based upon the extent of the match between the conjugate English terms and text associated with the websites.

1. A gaming device comprising: a playfield that includes a plurality of display positions, wherein each display position, is used to display a letter of an alphabet, wherein a letter may be combined with adjacent letters to form a word, wherein the display positions are configured into groups, and wherein at least one word is hidden in the playfield, means for continuously shifting the letters at display positions in a group relative to the letters at display positions in another group, wherein a letter at a display position is continuously shifted to an adjacent display position in a group, means for randomly stopping said shifting of letters, means for determining if a hidden word is uncovered when the shifting of letters is randomly stopped, and means for determining a payout amount associated with uncovered word.

1. A gaming device comprising: a playfield that includes a plurality of display positions, wherein each display position, is used to display a letter of an alphabet, wherein a letter may be combined with adjacent letters to form a word, wherein the display positions are configured into groups, and wherein at least one word is hidden in the playfield, means for continuously shifting the letters at display positions in a group relative to the letters at display positions in another group, wherein a letter at a display position is continuously shifted to an adjacent display position in a group, means for randomly stopping said shifting of letters, means for determining if a hidden word is uncovered when the shifting of letters is randomly stopped, and means for determining a payout amount associated with uncovered word. 7. A gaming device as recited in claim 1 , wherein said means for randomly stopping the continuous shifting of letters employs a random number generator.

25. The system of claim 1 wherein each of the synsets is stored in a table and is defined by fields including: a synset ID, a grammar type, a list of lemmas, a set of attributes, a set of semantic links, and a gloss.

25. The system of claim 1 wherein each of the synsets is stored in a table and is defined by fields including: a synset ID, a grammar type, a list of lemmas, a set of attributes, a set of semantic links, and a gloss. 26. The system of claim 25 wherein each lemma and is defined by fields including: a list of synset IDs, and lemma attributes.

1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of a gesture at a presence-sensitive input device to select fewer than all of a group of the plurality of keys that corresponds to a candidate word, the indication of the gesture based at least in part on detecting an input unit at a plurality of locations of the presence-sensitive input device; responsive to the detecting and while the gesture has not yet terminated: incrementally updating a plurality of letter chains, each letter chain including a different respective combination of letters associated with respective keys of the plurality of keys, wherein each letter chain is assigned a respective combined cost value of a plurality of respective combined cost values based on cost values for the respective keys of the plurality of keys that are in proximity to the gesture; determining, by the computing device and based at least in part on the plurality of letter chains, a plurality of candidate words; outputting, based on a letter chain of the plurality of letter chains being assigned to a highest combined cost value of the plurality of respective combined cost values, the candidate word for display at a first location of the display device; and responsive to determining, based on the input unit no longer being detected at the presence-sensitive input device, that the gesture has terminated prior to selecting all of the group of the plurality of keys that corresponds to the candidate word, outputting the candidate word for display at a second location of the display device, wherein the second location corresponds to a text entry area.

1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of a gesture at a presence-sensitive input device to select fewer than all of a group of the plurality of keys that corresponds to a candidate word, the indication of the gesture based at least in part on detecting an input unit at a plurality of locations of the presence-sensitive input device; responsive to the detecting and while the gesture has not yet terminated: incrementally updating a plurality of letter chains, each letter chain including a different respective combination of letters associated with respective keys of the plurality of keys, wherein each letter chain is assigned a respective combined cost value of a plurality of respective combined cost values based on cost values for the respective keys of the plurality of keys that are in proximity to the gesture; determining, by the computing device and based at least in part on the plurality of letter chains, a plurality of candidate words; outputting, based on a letter chain of the plurality of letter chains being assigned to a highest combined cost value of the plurality of respective combined cost values, the candidate word for display at a first location of the display device; and responsive to determining, based on the input unit no longer being detected at the presence-sensitive input device, that the gesture has terminated prior to selecting all of the group of the plurality of keys that corresponds to the candidate word, outputting the candidate word for display at a second location of the display device, wherein the second location corresponds to a text entry area. 10. The method of claim 1 , further comprising responsive to the detecting and while the input unit is detected at the presence-sensitive input device audibly outputting the candidate word at a speaker.

8. The method of claim 1 wherein determining whether a hyperlink-bound semantic object can be promoted to a first-level concept object further comprises: determining a number of hyperlink-based objects bound to the semantic object; and when the number of hyperlink-based objects bound to the semantic object exceeds a threshold number, determining that the semantic object can be promoted to a first-level concept object.

8. The method of claim 1 wherein determining whether a hyperlink-bound semantic object can be promoted to a first-level concept object further comprises: determining a number of hyperlink-based objects bound to the semantic object; and when the number of hyperlink-based objects bound to the semantic object exceeds a threshold number, determining that the semantic object can be promoted to a first-level concept object. 9. The method of claim 8 wherein determining whether a hyperlink-bound semantic object can be promoted to a first-level concept object further comprises: determining patterns and distributions of hyperlinks encoded by hyperlink-based objects bound to the semantic object; determining interrelationships between hyperlink-based objects bound to the semantic object; and using the determined patterns and distributions of hyperlink encoded by hyperlink-based objects and the determined interrelationships between hyperlink-based objects, in addition to the number of hyperlinks bound to the semantic object, to determine whether a hyperlink-bound semantic object can be promoted to a first-level concept object.

1. A method for determining content that is significant to a user within a web page, the method comprising: electronically receiving an indication from a user that the user finds significant content that appears within a web page presently displayed to the user; only after receiving the indication, electronically analyzing, using at least one processor, the web page to identify a set of topics associated with the content that appears within the web page in response to the received indication; only after analyzing the web page to identify the set of topics, selecting, from the set of topics, a subset of topics that characterizes the content that the user found significant within the web page, the topics included within the set of topics that are not included within the subset of topics being topics that are associated with the content of the web page but that are deemed not to characterize the content that the user found significant within the web page; and updating a user profile associated with the user based on the subset of topics; wherein a user profile associated with a user is stored on a host device and updating the user profile is performed by the host device; receiving a request for content from a user; receiving a user identity associated with the user; accessing a user profile associated with the user identity; determining content to provide in response to the request based on information within the accessed user profile; and transmitting the content to a client device for display to the user.

1. A method for determining content that is significant to a user within a web page, the method comprising: electronically receiving an indication from a user that the user finds significant content that appears within a web page presently displayed to the user; only after receiving the indication, electronically analyzing, using at least one processor, the web page to identify a set of topics associated with the content that appears within the web page in response to the received indication; only after analyzing the web page to identify the set of topics, selecting, from the set of topics, a subset of topics that characterizes the content that the user found significant within the web page, the topics included within the set of topics that are not included within the subset of topics being topics that are associated with the content of the web page but that are deemed not to characterize the content that the user found significant within the web page; and updating a user profile associated with the user based on the subset of topics; wherein a user profile associated with a user is stored on a host device and updating the user profile is performed by the host device; receiving a request for content from a user; receiving a user identity associated with the user; accessing a user profile associated with the user identity; determining content to provide in response to the request based on information within the accessed user profile; and transmitting the content to a client device for display to the user. 25. The method of claim 1 wherein a user profile associated with a user is stored on a client device and updating the user profile is performed by the client device.

6. A method comprising: causing a document to be displayed in a documentation display area of a user interface; causing a plurality of macro options to be displayed in a macro display area of the user interface that is adjacent to the documentation display area, individual ones of the plurality of macro options being associated with different external components configured to access different types of external medical data; determining an identifier associated with the document; receiving, within the macro display area, a selection of a macro option from the plurality of macro options displayed, wherein selection of the macro option initiates a macro that provides instructions to launch an external component; launching, based at least in part on the macro, the external component within a launched external component display area of the user interface, the launched external component display area being presented contemporaneously with the documentation display area and the macro display area; providing, by at least one processor, component-specific context data of the document to the launched external component; accessing, by the launched external component and via at least one remote storage location, external medical data of a particular type for a user identified by the identifier; causing the accessed external medical data to be displayed within the launched external component display area, wherein the accessed external medical data corresponds to the component-specific context data of the document; processing user interactions associated with the accessed external medical data displayed within the launched external component display area, the user interactions modifying the accessed external medical data to produce modified external medical data; capturing a message sent from the launched external component to the at least one remote storage location, the message including at least a portion of the modified external medical data; and automatically rendering a portion of the document displayed in the documentation display area based at least in part on the portion of the modified external medical data included in the captured message.

6. A method comprising: causing a document to be displayed in a documentation display area of a user interface; causing a plurality of macro options to be displayed in a macro display area of the user interface that is adjacent to the documentation display area, individual ones of the plurality of macro options being associated with different external components configured to access different types of external medical data; determining an identifier associated with the document; receiving, within the macro display area, a selection of a macro option from the plurality of macro options displayed, wherein selection of the macro option initiates a macro that provides instructions to launch an external component; launching, based at least in part on the macro, the external component within a launched external component display area of the user interface, the launched external component display area being presented contemporaneously with the documentation display area and the macro display area; providing, by at least one processor, component-specific context data of the document to the launched external component; accessing, by the launched external component and via at least one remote storage location, external medical data of a particular type for a user identified by the identifier; causing the accessed external medical data to be displayed within the launched external component display area, wherein the accessed external medical data corresponds to the component-specific context data of the document; processing user interactions associated with the accessed external medical data displayed within the launched external component display area, the user interactions modifying the accessed external medical data to produce modified external medical data; capturing a message sent from the launched external component to the at least one remote storage location, the message including at least a portion of the modified external medical data; and automatically rendering a portion of the document displayed in the documentation display area based at least in part on the portion of the modified external medical data included in the captured message. 11. The method according to claim 6 , wherein the launched external component display area comprises a pop-up window within the user interface that enables the portion of the modified external medical data to be automatically rendered within the portion of the document.

13. The electronic device of claim 8 , wherein the e-book application module is further configured to: upon continued re-sizing of the media interface, determine that a total width of the media interface is large enough to display two primary content displays in the presentation pane; display an additional primary content display in the presentation pane in the media interface, wherein the vertical margin panes are reduced or removed to accommodate the additional primary content display; fade out the display of the note; and re-display the glyph in the presentation pane.

13. The electronic device of claim 8 , wherein the e-book application module is further configured to: upon continued re-sizing of the media interface, determine that a total width of the media interface is large enough to display two primary content displays in the presentation pane; display an additional primary content display in the presentation pane in the media interface, wherein the vertical margin panes are reduced or removed to accommodate the additional primary content display; fade out the display of the note; and re-display the glyph in the presentation pane. 14. The electronic device of claim 13 , wherein the e-book application module is further configured to: upon continued re-sizing of the media interface, scale the glyph in accordance with the dynamically measured size of the vertical margin panes, wherein the glyph is scaled according to a scaling factor correlated to the size of the vertical margin panes.

11. The method of claim 1 , wherein said plurality of encoder modes comprises a NELP encoder mode, wherein the speech signal is represented by a residual signal generated by filtering the speech signal with a Linear Predictive Coding (LPC) analysis filter, and wherein said encoding comprises: (i) estimating the energy of the residual signal, and (ii) selecting a codevector from a first codebook, wherein said codevector approximates said estimated energy; and wherein decoding comprises: (i) generating a random vector, (ii) retrieving said codevector from a second codebook, (iii) scaling said random vector based on said codevector, such that the energy of said scaled random vector approximates said estimated energy, and (iv) filtering said scaled random vector with a LPC synthesis filter, wherein said filtered scaled random vector forms said synthesized speech signal.

11. The method of claim 1 , wherein said plurality of encoder modes comprises a NELP encoder mode, wherein the speech signal is represented by a residual signal generated by filtering the speech signal with a Linear Predictive Coding (LPC) analysis filter, and wherein said encoding comprises: (i) estimating the energy of the residual signal, and (ii) selecting a codevector from a first codebook, wherein said codevector approximates said estimated energy; and wherein decoding comprises: (i) generating a random vector, (ii) retrieving said codevector from a second codebook, (iii) scaling said random vector based on said codevector, such that the energy of said scaled random vector approximates said estimated energy, and (iv) filtering said scaled random vector with a LPC synthesis filter, wherein said filtered scaled random vector forms said synthesized speech signal. 12. The method of claim 11 , wherein the speech signal is divided into frames, wherein each of said frames comprises two or more subframes, wherein estimating the energy comprises estimating the energy of the residual signal for each of said subframes, and wherein said codevector comprises a value approximating said estimated energy for each of said subframes.

9. A handheld electronic device comprising: an input apparatus comprising a plurality of keys, at least some of the keys each having a number of linguistic elements assigned thereto; an output apparatus; a memory having a plurality of language objects stored therein; and a processor, configured to: detect a number of key selections corresponding with an ambiguous input; set a threshold, the threshold having a value of at least two; only after determining that the number of key selections is greater than or equal to the threshold, generate a first set of predicted language objects corresponding to the ambiguous input; and provide, at a text input location on the output apparatus, an output comprising a first predicted language object selected from the first set of predicted language objects.

9. A handheld electronic device comprising: an input apparatus comprising a plurality of keys, at least some of the keys each having a number of linguistic elements assigned thereto; an output apparatus; a memory having a plurality of language objects stored therein; and a processor, configured to: detect a number of key selections corresponding with an ambiguous input; set a threshold, the threshold having a value of at least two; only after determining that the number of key selections is greater than or equal to the threshold, generate a first set of predicted language objects corresponding to the ambiguous input; and provide, at a text input location on the output apparatus, an output comprising a first predicted language object selected from the first set of predicted language objects. 14. The device of claim 9 , wherein the processor is further configured to: detect an additional key selection as a further ambiguous input; generate a second set of predicted language objects corresponding to the ambiguous input and the further ambiguous input; and replace the first predicted language object provided at the text input location with a second predicted language object selected from the second set of predicted language objects.

14. A computer-readable storage medium containing instructions for generating a document index by operations comprising: for each of a plurality of values of an attribute of documents, the values having an ordering, determining a number of different encrypted instances to generate for the value, and generating the determined number of different encrypted instances of the value so that the value serves as a basis for generating each of the determined number of different encrypted instances of the value, wherein the number of encrypted instances of at least one of the values is greater than one, wherein each encrypted instance is unique, and wherein each of the generated encrypted instances of the value decrypts to the value, storing the generated encrypted instances of the value; and generating a mapping of the values of the attribute to each document having that value for the attribute, wherein the mapping maps different encrypted instances of a value to different documents; providing the generated mapping to a document storage service; and identifying an encrypted document that matches a query that specified a value for the attribute by, determining a lower bound on encrypted instances associated with the value specified by the query, determining an upper bound on encrypted instances associated with the value specified by the query, sending the determined lower and upper bounds to a document storage service, and receiving from the document storage service an indication of at least one document associated with an encrypted instance between the lower and upper bounds.

14. A computer-readable storage medium containing instructions for generating a document index by operations comprising: for each of a plurality of values of an attribute of documents, the values having an ordering, determining a number of different encrypted instances to generate for the value, and generating the determined number of different encrypted instances of the value so that the value serves as a basis for generating each of the determined number of different encrypted instances of the value, wherein the number of encrypted instances of at least one of the values is greater than one, wherein each encrypted instance is unique, and wherein each of the generated encrypted instances of the value decrypts to the value, storing the generated encrypted instances of the value; and generating a mapping of the values of the attribute to each document having that value for the attribute, wherein the mapping maps different encrypted instances of a value to different documents; providing the generated mapping to a document storage service; and identifying an encrypted document that matches a query that specified a value for the attribute by, determining a lower bound on encrypted instances associated with the value specified by the query, determining an upper bound on encrypted instances associated with the value specified by the query, sending the determined lower and upper bounds to a document storage service, and receiving from the document storage service an indication of at least one document associated with an encrypted instance between the lower and upper bounds. 19. The computer-readable storage medium of claim 14 , wherein generating the determined number of different encrypted instances of a first value of the set of ordered values comprises: generating a first encrypted instance of the first value by encrypting the first value; generating a second encrypted instance of the first value by adding a randomly-generated value to the first encrypted instance of the first value; generating a third encrypted instance of the first value by adding a randomly-generated value to the second encrypted instance of the first value; and generating a fourth encrypted instance of the first value by adding a randomly-generated value to the third encrypted instance of the first value, so that the first value is associated with at least four different encrypted instances of the first value and each encrypted instances is associated with exactly one value of the set of ordered values.

1. A non-transitory storage medium encoded with machine-readable computer program code for providing search and reference functions for a messaging system, the non-transitory storage medium including instructions for causing a computer to implement a method, comprising: receiving a request to search a data archive for reference information relating to at least one keyword selected by a messaging system user, said messaging system user actively engaged in composing a message or a response to a message, and wherein further, said at least one keyword is selected from a body of said message's text; searching said data archive; if a reference is found, presenting said reference to said messaging system user within said message; wherein said data archive includes information gathered from said messaging system user's message folder and at least one of: a local data storage system; and a shared online repository; and further comprising instructions for causing said computer to implement: integrating process software for providing said search and reference functions for a messaging system, said integrating process software further comprising: determining if said process software will execute on at least one server; identifying an address of said at least one server; checking said at least one server for operating systems, applications, and version numbers for validation with said process software, and identifying any missing software applications for said at least one server that are required for integration; updating said at least one server with respect to any operating system and application that is not validated for said process software, and providing any of said missing software applications for said at least one server required for said integration; identifying client addresses and checking client computers for operating systems, applications, and version numbers for validation with said process software, and identifying any software applications missing from said client computers that are required for integration; updating said client computers with respect to any operating system and application that is not validated for said process software, and providing any missing software application for said client computers required for said integration; and installing said process software on said client computers and said at least one server.

1. A non-transitory storage medium encoded with machine-readable computer program code for providing search and reference functions for a messaging system, the non-transitory storage medium including instructions for causing a computer to implement a method, comprising: receiving a request to search a data archive for reference information relating to at least one keyword selected by a messaging system user, said messaging system user actively engaged in composing a message or a response to a message, and wherein further, said at least one keyword is selected from a body of said message's text; searching said data archive; if a reference is found, presenting said reference to said messaging system user within said message; wherein said data archive includes information gathered from said messaging system user's message folder and at least one of: a local data storage system; and a shared online repository; and further comprising instructions for causing said computer to implement: integrating process software for providing said search and reference functions for a messaging system, said integrating process software further comprising: determining if said process software will execute on at least one server; identifying an address of said at least one server; checking said at least one server for operating systems, applications, and version numbers for validation with said process software, and identifying any missing software applications for said at least one server that are required for integration; updating said at least one server with respect to any operating system and application that is not validated for said process software, and providing any of said missing software applications for said at least one server required for said integration; identifying client addresses and checking client computers for operating systems, applications, and version numbers for validation with said process software, and identifying any software applications missing from said client computers that are required for integration; updating said client computers with respect to any operating system and application that is not validated for said process software, and providing any missing software application for said client computers required for said integration; and installing said process software on said client computers and said at least one server. 4. The non-transitory storage medium of claim 1 , wherein said reference is provided to said messaging system user in the form of at least one of: a hypertext link; a Uniform Resource Locator; a web address; a document; a report; and a memo.

15. The mobile device of claim 12 , wherein the handwriting messaging client is further configured to poll for new image data representative of other handwriting input sent from another mobile device.

15. The mobile device of claim 12 , wherein the handwriting messaging client is further configured to poll for new image data representative of other handwriting input sent from another mobile device. 16. The mobile device of claim 15 , wherein the handwriting messaging client is further configured to periodically poll for the new image data representative of the other handwriting input sent from the other mobile device.

5. A method of recording text subtitle data on a recording medium using a recording apparatus, the method comprising: recording at least one main AV data and a plurality of subtitle information segments on the recording medium using the recording apparatus, each one of the subtitle information segments being represented by each PES packet of transport packets and having a one-to-one correspondence with each PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein each one of the subtitle information segments includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment identified as the text data includes at least one first style information and palette information, the palette information including a palette identifier identifying the corresponding palette information for controlling color attributes of the text data, wherein a second subtitle information segment identified as the text data includes at least two text subtitle regions, each of the text subtitle regions including second style information applied to the text data for managing reproduction of the text data by the reproducing device, each of the text subtitle regions being linked to the first style information defined in the first subtitle information segment by an identifier, each of the text subtitle regions including length information for indicating a length of a number of characters of a text string on the corresponding text subtitle region to be displayed, wherein the graphic data is multiplexed with the main AV data into a file while the text data is separate from the main AV data, wherein either one of the graphic data or the text data is displayed together with the main AV data.

5. A method of recording text subtitle data on a recording medium using a recording apparatus, the method comprising: recording at least one main AV data and a plurality of subtitle information segments on the recording medium using the recording apparatus, each one of the subtitle information segments being represented by each PES packet of transport packets and having a one-to-one correspondence with each PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein each one of the subtitle information segments includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment identified as the text data includes at least one first style information and palette information, the palette information including a palette identifier identifying the corresponding palette information for controlling color attributes of the text data, wherein a second subtitle information segment identified as the text data includes at least two text subtitle regions, each of the text subtitle regions including second style information applied to the text data for managing reproduction of the text data by the reproducing device, each of the text subtitle regions being linked to the first style information defined in the first subtitle information segment by an identifier, each of the text subtitle regions including length information for indicating a length of a number of characters of a text string on the corresponding text subtitle region to be displayed, wherein the graphic data is multiplexed with the main AV data into a file while the text data is separate from the main AV data, wherein either one of the graphic data or the text data is displayed together with the main AV data. 8. The method of claim 5 , wherein the second subtitle information segment identified as the text data includes an indicator of a number of the at least one text subtitle region.

12. The apparatus of claim 10 , wherein said hardware processor is configured for determining a sensitivity of the current hotspot event and making the hotspot information materials online based upon whether the sensitivity of the current hotspot event satisfies the sensitivity screening threshold.

12. The apparatus of claim 10 , wherein said hardware processor is configured for determining a sensitivity of the current hotspot event and making the hotspot information materials online based upon whether the sensitivity of the current hotspot event satisfies the sensitivity screening threshold. 15. The apparatus of claim 12 , wherein said hardware processor is configured for acquiring an offline mode, the offline mode comprising at least one of automatic offline, delay offline and manual offline; and wherein said hardware processor is configured for at least one of: making the corresponding hotspot information materials offline based upon a fifth determination that the offline mode is the automatic offline and a sixth determination that the sensitivity has reached a third preset condition that is lower than a second preset sensitivity; making the corresponding hotspot information materials offline based upon a seventh determination that the offline mode is the delay offline and an eighth determination that the sensitivity has reached a fourth preset condition being lower than the second preset sensitivity and a preset time lasting under the second preset sensitivity; and making the corresponding hotspot information materials offline according to an offline instruction based upon a ninth determination that the offline mode is the manual offline.

15. A system for automatically tagging and manually editing electronic content, comprising: one or more computers, comprising one or more processors, storing: a plurality of concepts stored in a database, wherein each concept is hierarchically under a domain and is unique within the domain, wherein each domain has its own hierarchical structure wherein each domain has its own hierarchical structure; wherein at least one of said each domain is a category selected from the group including but not limited to a problem, a procedure, a diagnosis, a medication, and an allergy; a plurality of descriptions stored in a database, wherein a description is an alternative way to express a concept, wherein each description also is unique within a given domain, wherein each description relates to a respective concept, wherein said descriptions have a many-to-one relationship with each of said plurality of concepts, and wherein each description has a presence factor indicative of a strength of the relationship between it and its related concept, the presence factor also indicative of a physician's intent when the description is generally used by physicians; a plurality of items of electronic content, where each electronic content item includes portions and each portion is reviewed to determine if said portion matches one or more of said concepts by determining if said portion relates to one or more of said plurality of descriptions associated with a given concept; a plurality of content tags representing locations and identifications of portions of the electronic content that relate to one or more of said plurality of descriptions, wherein said content tags have a many-to-many relationship with said plurality of descriptions, wherein said electronic content items have a many-to-many relationship with said plurality of content tags; a plurality of rankings for the electronic content, the rankings generated in response to a query and based at least on the presence factor for the descriptions of content tags applied to the electronic content; and a list of the electronic content sorted by the plurality of rankings; and a database including a table for storing information relating to said electronic content.

15. A system for automatically tagging and manually editing electronic content, comprising: one or more computers, comprising one or more processors, storing: a plurality of concepts stored in a database, wherein each concept is hierarchically under a domain and is unique within the domain, wherein each domain has its own hierarchical structure wherein each domain has its own hierarchical structure; wherein at least one of said each domain is a category selected from the group including but not limited to a problem, a procedure, a diagnosis, a medication, and an allergy; a plurality of descriptions stored in a database, wherein a description is an alternative way to express a concept, wherein each description also is unique within a given domain, wherein each description relates to a respective concept, wherein said descriptions have a many-to-one relationship with each of said plurality of concepts, and wherein each description has a presence factor indicative of a strength of the relationship between it and its related concept, the presence factor also indicative of a physician's intent when the description is generally used by physicians; a plurality of items of electronic content, where each electronic content item includes portions and each portion is reviewed to determine if said portion matches one or more of said concepts by determining if said portion relates to one or more of said plurality of descriptions associated with a given concept; a plurality of content tags representing locations and identifications of portions of the electronic content that relate to one or more of said plurality of descriptions, wherein said content tags have a many-to-many relationship with said plurality of descriptions, wherein said electronic content items have a many-to-many relationship with said plurality of content tags; a plurality of rankings for the electronic content, the rankings generated in response to a query and based at least on the presence factor for the descriptions of content tags applied to the electronic content; and a list of the electronic content sorted by the plurality of rankings; and a database including a table for storing information relating to said electronic content. 16. The system according to claim 15 , wherein said plurality of concepts are interrelated in a tree or graph structure.

15. The method of claim 1 , wherein the generation of parameters comprises generating mel-cepstral parameters, comprising the steps of: a) initializing a first element of a generated parameter vector; b) determining a frame increment value; c) determining if the frame is voiced, wherein; i) if the segment is unvoiced, applying the mathematical equation: mcep(i)=(mcep(i−1)+mcep mean(i))/2; ii) if the segment is voiced and is a first frame, then applying the mathematical equation: mcep(i)=(mcep(i−1)+mcep mean(i))/2; and iii) if the segment is voiced and is not a first frame, then applying the mathematical equation: mcep(i)=(mcep(i−1)+mcep delta(i)+mcep mean(i))/2; d) determining if a linguistic segment has ended, wherein: i) if the linguistic segment has ended, removing abrupt changes of the parameter trajectory, and adjusting global variance; and ii) if the linguistic segment has not ended, repeating the process beginning with step (a).

15. The method of claim 1 , wherein the generation of parameters comprises generating mel-cepstral parameters, comprising the steps of: a) initializing a first element of a generated parameter vector; b) determining a frame increment value; c) determining if the frame is voiced, wherein; i) if the segment is unvoiced, applying the mathematical equation: mcep(i)=(mcep(i−1)+mcep mean(i))/2; ii) if the segment is voiced and is a first frame, then applying the mathematical equation: mcep(i)=(mcep(i−1)+mcep mean(i))/2; and iii) if the segment is voiced and is not a first frame, then applying the mathematical equation: mcep(i)=(mcep(i−1)+mcep delta(i)+mcep mean(i))/2; d) determining if a linguistic segment has ended, wherein: i) if the linguistic segment has ended, removing abrupt changes of the parameter trajectory, and adjusting global variance; and ii) if the linguistic segment has not ended, repeating the process beginning with step (a). 19. The method of claim 15 , wherein the determining if a frame is voiced comprises examining predicted values for the spectral parameters, wherein a voiced segment comprises valid values.

15. A system comprising: one or more processors; memory storing executable instructions that, when executed by the one or more processors to perform acts comprising: collecting information from a source of input, the information being related to statistics in a video game, determining a need for presentation of additional information in response to the collected information, identifying media associated with at least a portion of the video game based on the statistics in response to determining the need, providing the identified media for presentation, determining if the identified media is useful, and increasing a rank of the identified media for subsequent ranking and ordering of the identified media in response to determining the identified media is useful.

15. A system comprising: one or more processors; memory storing executable instructions that, when executed by the one or more processors to perform acts comprising: collecting information from a source of input, the information being related to statistics in a video game, determining a need for presentation of additional information in response to the collected information, identifying media associated with at least a portion of the video game based on the statistics in response to determining the need, providing the identified media for presentation, determining if the identified media is useful, and increasing a rank of the identified media for subsequent ranking and ordering of the identified media in response to determining the identified media is useful. 17. The system of claim 15 , wherein the collected information is retrieved from a pattern of play in the video game.

8. A system comprising: a memory device for storing instructions executable by a processor; a processor for executing instructions stored in the memory, at least a portion of those instructions representing an item listing presentation management module, which, when executed by the processor, is to process a query to i) identify a set of item listings, each item listing associated with an item or service being offered for sale and assigned to a leaf-level category, ii) obtain for the query a click probability score for each leaf-level category to which an item listing satisfying the query has been assigned, the click probability score for a particular leaf-level category derived by dividing a number of clicks for the particular leaf-level category by the total number of clicks for all leaf-level categories to which an item listing satisfying the query has been assigned, iii) identify up to a predetermined number of leaf-level categories with click probability scores exceeding a threshold score, iv) for each of the identified leaf-level categories, calculate a category boost score for use in determining the order in which the item listings are to be presented in a search results page, and iv) cause a search results page to be presented with the item listings ordered based in part on the category boost score for the leaf-level category to which each item listing is assigned.

8. A system comprising: a memory device for storing instructions executable by a processor; a processor for executing instructions stored in the memory, at least a portion of those instructions representing an item listing presentation management module, which, when executed by the processor, is to process a query to i) identify a set of item listings, each item listing associated with an item or service being offered for sale and assigned to a leaf-level category, ii) obtain for the query a click probability score for each leaf-level category to which an item listing satisfying the query has been assigned, the click probability score for a particular leaf-level category derived by dividing a number of clicks for the particular leaf-level category by the total number of clicks for all leaf-level categories to which an item listing satisfying the query has been assigned, iii) identify up to a predetermined number of leaf-level categories with click probability scores exceeding a threshold score, iv) for each of the identified leaf-level categories, calculate a category boost score for use in determining the order in which the item listings are to be presented in a search results page, and iv) cause a search results page to be presented with the item listings ordered based in part on the category boost score for the leaf-level category to which each item listing is assigned. 14. The system of claim 8 , wherein the item listing presentation management module is to identify additional leaf-level categories up to the predetermined number of categories, the additional leaf-level categories having click probability scores equal to or greater than some predetermined percentage of the click probability score of the leaf-level category with the lowest click probability score that is higher than the threshold score, if the number of leaf-level categories having a click probability score greater than or equal to the threshold score is less than the predetermined number.

11. A method according to claim 10, wherein said step (b) starts or stops reading performance data in response to manipulation of the phrase select operator.

11. A method according to claim 10, wherein said step (b) starts or stops reading performance data in response to manipulation of the phrase select operator. 13. A method according to claim 11, wherein said step (b) starts reading the performance data of the selected phrase from a start thereof.

1. A text presentation apparatus presenting text for a speaker to read aloud for voice recording, the apparatus comprising: a text storing unit configured to store first text; a presenting unit configured to present the first text; a determination unit configured to determine whether or not the first text needs to be replaced, on the basis of a speaker's input for the first text presented; a preliminary text storing unit configured to store preliminary text; a select unit configured to select, if it is determined that the first text needs to be replaced, second text to replace the first text from among the preliminary text, the selecting being performed on the basis of attribute information describing an attribute of the first text and on the basis of at least one of attribute information describing pronunciation of the first text and attribute information describing a stress type of the first text; and a control unit configured to control the presenting unit so that the presenting unit presents the second text, wherein: the pieces of attribute information are associated with respective degrees of importance; and the select unit, if it is determined that the first text needs to be replaced, calculates, for each piece of the preliminary text that is associated with the attribute information having an attribute value matching that of at least one of the pieces of attribute information on the first text, the sum of the degrees of importance that are associated with pieces of attribute information having matching attribute values, and selects the second text that maximizes the sum of the degrees of importance.

1. A text presentation apparatus presenting text for a speaker to read aloud for voice recording, the apparatus comprising: a text storing unit configured to store first text; a presenting unit configured to present the first text; a determination unit configured to determine whether or not the first text needs to be replaced, on the basis of a speaker's input for the first text presented; a preliminary text storing unit configured to store preliminary text; a select unit configured to select, if it is determined that the first text needs to be replaced, second text to replace the first text from among the preliminary text, the selecting being performed on the basis of attribute information describing an attribute of the first text and on the basis of at least one of attribute information describing pronunciation of the first text and attribute information describing a stress type of the first text; and a control unit configured to control the presenting unit so that the presenting unit presents the second text, wherein: the pieces of attribute information are associated with respective degrees of importance; and the select unit, if it is determined that the first text needs to be replaced, calculates, for each piece of the preliminary text that is associated with the attribute information having an attribute value matching that of at least one of the pieces of attribute information on the first text, the sum of the degrees of importance that are associated with pieces of attribute information having matching attribute values, and selects the second text that maximizes the sum of the degrees of importance. 10. The apparatus according to claim 1 , wherein: the attribute information is necessary to create a synthesis dictionary, the synthesis dictionary being used to create a synthesized speech, and the attribute information includes, as the attribute value, pronunciation, stress type of a stress key phrase, type of a low-frequency phoneme included in a text, and number of stressed phrases that constitute a text.

2. The voice access system of claim 1 , wherein said voice recognition unit and said speech processing server are further configured to interact with one another to determine query criteria, send said query criteria to said enterprise data system, receive data from said enterprise data system, and provide feedback data to said user via said telephone connection; said query criteria correspond to said ad hoc query; said data is based on said query criteria; and said feedback data corresponds to data received from said enterprise data system in a verbal format.

2. The voice access system of claim 1 , wherein said voice recognition unit and said speech processing server are further configured to interact with one another to determine query criteria, send said query criteria to said enterprise data system, receive data from said enterprise data system, and provide feedback data to said user via said telephone connection; said query criteria correspond to said ad hoc query; said data is based on said query criteria; and said feedback data corresponds to data received from said enterprise data system in a verbal format. 7. The voice access system of claim 2 , wherein said voice recognition unit comprises a voice application; and said voice application is configured to manage interactions with said voice access system.

11. A non-transitory computer readable storage medium with program instructions for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the medium comprising the instructions for: receiving an ontology query and returning a set of terms of the ontology as the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology; and providing the referential integrity constraint for the constrained object, whereby when an operation in the relational database management system adds a value to the constrained object, permitting the operation only if the added value is a member of the set of terms, the constrained object comprising a constrained column that is defined in the relational database management system and the act of providing comprises: making a term object with a column, values in the column being the members of the returned set of terms; and using the column of the term object to define the referential integrity constraint for the constrained object; and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms.

11. A non-transitory computer readable storage medium with program instructions for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the medium comprising the instructions for: receiving an ontology query and returning a set of terms of the ontology as the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology; and providing the referential integrity constraint for the constrained object, whereby when an operation in the relational database management system adds a value to the constrained object, permitting the operation only if the added value is a member of the set of terms, the constrained object comprising a constrained column that is defined in the relational database management system and the act of providing comprises: making a term object with a column, values in the column being the members of the returned set of terms; and using the column of the term object to define the referential integrity constraint for the constrained object; and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms. 14. The medium set forth in claim 11 wherein: in the altering of one or more values, when a term in the constrained object is no longer contained in the different set of terms, giving the term in the constrained object a null value.

17. A system comprising: a processor; a non-transitory storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: receiving logic executed by the processor for receiving a request from a mobile device over a network; determining logic executed by the processor for determining whether the request includes one or more of a search query and geo-location information; when it is determined that the request includes the search query and excludes the geo-location information: generating logic executed by the processor for generating a search result based on the search query; parsing logic executed by the processor for parsing the search results to determine a first geo-location; and determining logic executed by the processor for determining the at least one virtual billboard in proximity with the first geo-location derived from the search result; and communicating logic executed by the processor for communicating the at least one virtual billboard to the mobile device; when it is determined that the request includes the geo-location information identifying a second geo-location and excludes the search query: determining logic executed by the processor for determining the at least one further virtual billboard in proximity with the second geo-location identified by the geo-location information; and communicating logic executed by the processor for communicating the at least one further virtual billboard to the mobile device; and when it is determined that the request includes the geo-location information identifying a second geo-location and includes the search query: generating logic executed by the processor for generating a further search result based on the query and the received geo-location information identifying the second geo-location; parsing logic executed by the processor for parsing the further search results to determine a third geo-location; determining logic executed by the processor for determining one or more virtual billboards in proximity with one or more of the second geo-location or the third geo-location; and communicating logic executed by the processor for communicating the one or more virtual billboards to the mobile device.

17. A system comprising: a processor; a non-transitory storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: receiving logic executed by the processor for receiving a request from a mobile device over a network; determining logic executed by the processor for determining whether the request includes one or more of a search query and geo-location information; when it is determined that the request includes the search query and excludes the geo-location information: generating logic executed by the processor for generating a search result based on the search query; parsing logic executed by the processor for parsing the search results to determine a first geo-location; and determining logic executed by the processor for determining the at least one virtual billboard in proximity with the first geo-location derived from the search result; and communicating logic executed by the processor for communicating the at least one virtual billboard to the mobile device; when it is determined that the request includes the geo-location information identifying a second geo-location and excludes the search query: determining logic executed by the processor for determining the at least one further virtual billboard in proximity with the second geo-location identified by the geo-location information; and communicating logic executed by the processor for communicating the at least one further virtual billboard to the mobile device; and when it is determined that the request includes the geo-location information identifying a second geo-location and includes the search query: generating logic executed by the processor for generating a further search result based on the query and the received geo-location information identifying the second geo-location; parsing logic executed by the processor for parsing the further search results to determine a third geo-location; determining logic executed by the processor for determining one or more virtual billboards in proximity with one or more of the second geo-location or the third geo-location; and communicating logic executed by the processor for communicating the one or more virtual billboards to the mobile device. 18. The system of claim 17 , further comprising: filtering logic executed by the processor for filtering the at least one virtual billboard, the at least one further virtual billboard or the one or more virtual billboards based on at least one of a user preference, a type of the at least one virtual billboard, a time, or a keyword included in the query.

42. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising: a control application stored in the memory, the control application comprising instructions to: retain contextual information for a second application; receive a notification from the second application that the retained contextual information is outdated; receive an indication that a text manipulation event has occurred based on a keyboard input that modifies text in a user interface of the second application, wherein the keyboard input is generated based on input with a keyboard that includes keys with corresponding hit zones; send a query to the second application to obtain updated contextual information established by the second application prior to the event, wherein the updated contextual information is based on internal state information for the second application that is not directly accessible by the control application, and the updated contextual information provides context to the text manipulation event that occurred at the location in the user interface of the second application; receive the updated contextual information from the second application; and adjust a size of the hit zone of one or more keys on the keyboard based on the updated contextual information providing context to the text manipulation event; and wherein the one or more commands cause the second application to execute the one or more commands issued by the control application.

42. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising: a control application stored in the memory, the control application comprising instructions to: retain contextual information for a second application; receive a notification from the second application that the retained contextual information is outdated; receive an indication that a text manipulation event has occurred based on a keyboard input that modifies text in a user interface of the second application, wherein the keyboard input is generated based on input with a keyboard that includes keys with corresponding hit zones; send a query to the second application to obtain updated contextual information established by the second application prior to the event, wherein the updated contextual information is based on internal state information for the second application that is not directly accessible by the control application, and the updated contextual information provides context to the text manipulation event that occurred at the location in the user interface of the second application; receive the updated contextual information from the second application; and adjust a size of the hit zone of one or more keys on the keyboard based on the updated contextual information providing context to the text manipulation event; and wherein the one or more commands cause the second application to execute the one or more commands issued by the control application. 51. The non-transitory computer-readable storage medium of claim 42 , wherein the second application includes instructions to notify the control application that contextual information obtained by the control application from the second application can no longer be relied upon by the control application.

11. A method implemented on a computer, comprising: storing a plurality of reports in a repository, wherein each report includes information automatically retrieved from a data source, where the information is structured in accordance with a report schema that specifies the form in which the information should be presented, wherein the report schema defines separate report elements as structural components found inside a report, the report interpreting the information from the data source and performs calculations based on at least one calculation model; extracting, from each report of the plurality of reports in the report repository, report element instance context metadata and report element instance context data to define indexed fields, wherein the report element instance context metadata specifies metadata that affects evaluation of a report element instance according to the at least one calculation model including context with information used to calculate a report element instance and the report element instance context data specifies data that affects evaluation of the report element instance; receiving a search query; applying the search query against the indexed fields; and compiling search query results to produce a list of relevant report element instances, wherein each report element instance is a single occurrence of a report element in a report and reports are ranked based on a composite ranking factor, the composite ranking factor being compiled from two or more ranking methods including a method based on a report element instance's level of hierarchy in a report or sub-report.

11. A method implemented on a computer, comprising: storing a plurality of reports in a repository, wherein each report includes information automatically retrieved from a data source, where the information is structured in accordance with a report schema that specifies the form in which the information should be presented, wherein the report schema defines separate report elements as structural components found inside a report, the report interpreting the information from the data source and performs calculations based on at least one calculation model; extracting, from each report of the plurality of reports in the report repository, report element instance context metadata and report element instance context data to define indexed fields, wherein the report element instance context metadata specifies metadata that affects evaluation of a report element instance according to the at least one calculation model including context with information used to calculate a report element instance and the report element instance context data specifies data that affects evaluation of the report element instance; receiving a search query; applying the search query against the indexed fields; and compiling search query results to produce a list of relevant report element instances, wherein each report element instance is a single occurrence of a report element in a report and reports are ranked based on a composite ranking factor, the composite ranking factor being compiled from two or more ranking methods including a method based on a report element instance's level of hierarchy in a report or sub-report. 17. The method according to claim 11 wherein the search query is received from a user.

16. A system for detecting autism in a natural language environment, the system comprising: a microphone configured to capture a sound signal of a key child to create a plurality of audio signals; a sound recorder configured to store the plurality of audio signals; and a computer programmed with software for the specialized purpose of processing recordings captured by the microphone and sound recorder combination, the computer programmed to execute a method including: (a) segmenting audio signals captured by the microphone and sound recorder combination using the computer programmed for the specialized purpose into a plurality of recording segments; (b) determining which of the plurality of recording segments correspond to the key child; (c) determining which of the plurality of recording segments that correspond to the key child are classified as key child recordings; (d) extracting phone-based and transparent features of the key child recordings; (e) comparing the phone-based and transparent features of the key child recordings to known phone-based and cluster-based transparent features for children, wherein the cluster-based transparent features are developed according to cluster-based transparent parameter analysis; and (f) determining a likelihood of autism based on the comparing of (e); and a display of a user, configured to display the likelihood of autism.

16. A system for detecting autism in a natural language environment, the system comprising: a microphone configured to capture a sound signal of a key child to create a plurality of audio signals; a sound recorder configured to store the plurality of audio signals; and a computer programmed with software for the specialized purpose of processing recordings captured by the microphone and sound recorder combination, the computer programmed to execute a method including: (a) segmenting audio signals captured by the microphone and sound recorder combination using the computer programmed for the specialized purpose into a plurality of recording segments; (b) determining which of the plurality of recording segments correspond to the key child; (c) determining which of the plurality of recording segments that correspond to the key child are classified as key child recordings; (d) extracting phone-based and transparent features of the key child recordings; (e) comparing the phone-based and transparent features of the key child recordings to known phone-based and cluster-based transparent features for children, wherein the cluster-based transparent features are developed according to cluster-based transparent parameter analysis; and (f) determining a likelihood of autism based on the comparing of (e); and a display of a user, configured to display the likelihood of autism. 21. The system of claim 16 wherein there are 64 clusters of predetermined clusters of child speech for children above 15 months and 16 clusters of predetermined clusters of child speech for children under 15 months.

1. An apparatus for analyzing non-deterministic results of a search query of data representing analogue information, such as audio data, comprising: a processor and a user interface, the processor being operably in communication with a plurality of audio data sources or databases representing the content thereof and adapted to communicate with the user interface which enables the user to query one or more audio data sources for the presence of search constituents within the audio data, wherein the processor is adapted to determine the non-deterministic likelihood of occurrence of the search constituent within at least part of each of the searched data sources for a user query and the user interface is adapted to present to the user the search results in a form including: a portlet presenting the overall search results (such as search strings) against part or all of the search query structure for a data source(s); a portlet presenting the data source (such as by source name) of one or more data source(s); a portlet presenting a data source filter tree for selecting currently active source(s); a portlet presenting the hit(s) of the search phrase(s) for a data source; and a portlet presenting the hit location(s) within a data source, and wherein at least one of the portlets presents the user with information related to the non-deterministic likelihood of occurrence of the search constituent as a probability of the relevance of a searched data source of the search query and parts of the search query, and the user interface further enabling the user to select and inspect at least part of the searched data source(s) for the presence of the search constituents; wherein each of the portlets is presented to the user with relevancy scores to the data as determined by the non-deterministic results and each portlet is updated and synchronized during a change-of-state cascade event whenever the state is changed within any one of the portlets; and wherein each of the portlets enable a user to edit the probable relevance of the data source, convert the non-deterministic results that are returned by the search of the audio data to deterministic results based on the relevancy score by the user interaction with the data source, and altering the relevance of that data source computed for the overall query.

1. An apparatus for analyzing non-deterministic results of a search query of data representing analogue information, such as audio data, comprising: a processor and a user interface, the processor being operably in communication with a plurality of audio data sources or databases representing the content thereof and adapted to communicate with the user interface which enables the user to query one or more audio data sources for the presence of search constituents within the audio data, wherein the processor is adapted to determine the non-deterministic likelihood of occurrence of the search constituent within at least part of each of the searched data sources for a user query and the user interface is adapted to present to the user the search results in a form including: a portlet presenting the overall search results (such as search strings) against part or all of the search query structure for a data source(s); a portlet presenting the data source (such as by source name) of one or more data source(s); a portlet presenting a data source filter tree for selecting currently active source(s); a portlet presenting the hit(s) of the search phrase(s) for a data source; and a portlet presenting the hit location(s) within a data source, and wherein at least one of the portlets presents the user with information related to the non-deterministic likelihood of occurrence of the search constituent as a probability of the relevance of a searched data source of the search query and parts of the search query, and the user interface further enabling the user to select and inspect at least part of the searched data source(s) for the presence of the search constituents; wherein each of the portlets is presented to the user with relevancy scores to the data as determined by the non-deterministic results and each portlet is updated and synchronized during a change-of-state cascade event whenever the state is changed within any one of the portlets; and wherein each of the portlets enable a user to edit the probable relevance of the data source, convert the non-deterministic results that are returned by the search of the audio data to deterministic results based on the relevancy score by the user interaction with the data source, and altering the relevance of that data source computed for the overall query. 17. The apparatus according to claim 1 , comprising an editor interface which enables a user to define a new complex query or to modify an existing one by defining additional search constituents and/or modifying existing search constituents.

11. A method comprising: receiving stroke data; identifying, by use of a processor, a handwritten character from stroke data; mapping the handwritten character to a user-specific font character based on the stroke data, wherein mapping the handwritten character to a user-specific font character comprises: determining whether the stroke data of the handwritten character matches a font character of a user-specific font set associated with a user inputting the stroke data, selecting a matching font character, in response to the stroke data matching the font character, and generating a new font character based on the stroke data, in response to the stroke data not matching any font character of the font set; and storing, to a file, a character encoding corresponding to the user-specific font character.

11. A method comprising: receiving stroke data; identifying, by use of a processor, a handwritten character from stroke data; mapping the handwritten character to a user-specific font character based on the stroke data, wherein mapping the handwritten character to a user-specific font character comprises: determining whether the stroke data of the handwritten character matches a font character of a user-specific font set associated with a user inputting the stroke data, selecting a matching font character, in response to the stroke data matching the font character, and generating a new font character based on the stroke data, in response to the stroke data not matching any font character of the font set; and storing, to a file, a character encoding corresponding to the user-specific font character. 17. The method of claim 11 , further comprising determining a character position of the handwritten character, wherein storing a character encoding corresponding to the user-specific font character further comprises associating the character encoding with the character position and with the user-specific font character.

11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying a search query, the search query including one or more terms; determining that one or more terms in the search query are associated with a domain; receiving ranked search results responsive to the search query, the search results having a ranked order and including at least a first and a second search result each associated with the domain, wherein the second search result has a lower ranking in the ranked order than the first search result, the second search result is not adjacent to the first search in the ranked order, and the first and second search results are associated with the domain based on the respective resources referenced by the search results each having a uniform resource locator that includes the domain; grouping a number of search results associated with the domain together to generate a new ranking, including promoting the lower-ranked second search result associated with the domain to be ranked adjacent to the first search result associated with the domain; reordering the search results by the new ranking, wherein the first and second search results are adjacent in the new ranking, and the second search result is adjacent in the new ranking to a third search result associated with a different domain; and providing the reordered search results for presentation.

11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying a search query, the search query including one or more terms; determining that one or more terms in the search query are associated with a domain; receiving ranked search results responsive to the search query, the search results having a ranked order and including at least a first and a second search result each associated with the domain, wherein the second search result has a lower ranking in the ranked order than the first search result, the second search result is not adjacent to the first search in the ranked order, and the first and second search results are associated with the domain based on the respective resources referenced by the search results each having a uniform resource locator that includes the domain; grouping a number of search results associated with the domain together to generate a new ranking, including promoting the lower-ranked second search result associated with the domain to be ranked adjacent to the first search result associated with the domain; reordering the search results by the new ranking, wherein the first and second search results are adjacent in the new ranking, and the second search result is adjacent in the new ranking to a third search result associated with a different domain; and providing the reordered search results for presentation. 13. The system of claim 11 , wherein determining that one or more terms in the search query are associated with a domain comprises determining that the search results include multiple search results associated with the domain.

23. The non-transitory computer readable medium of claim 18 , wherein assembling the audio program comprises placing a segue between the first audio presentation and the second audio presentation.

23. The non-transitory computer readable medium of claim 18 , wherein assembling the audio program comprises placing a segue between the first audio presentation and the second audio presentation. 24. The non-transitory computer readable medium of claim 23 , wherein the segue comprises at least a portion of a music recording, and wherein the portion is obtained from the client device or from a network-accessible music server.

8. A computer-implemented method for providing information in a system including an information database that stores information contents and a metadata database that stores metadata describing the information contents, the method comprising: detecting an intention of an information provider by using a result of a syntax analysis of keywords inputted by the information provider; extracting a plurality of metadata which describe information contents meeting the detected intention of the information provider from the metadata stored in the metadata database; generating an editor in a table form in which the plurality of metadata extracted from the metadata stored in the metadata database are paired with a plurality of metadata fields of the editor and displaying the generated editor to the information provider; receiving a plurality of metadata items inputted by the information provider through the plurality of metadata fields of the editor; determining a store directory for storing contents in the information database according to the detected intention of the information provider; and storing information contents represented by the plurality of inputted metadata items integrated with the plurality of metadata in the directory of the information database determined according to the detected intention of the information provider.

8. A computer-implemented method for providing information in a system including an information database that stores information contents and a metadata database that stores metadata describing the information contents, the method comprising: detecting an intention of an information provider by using a result of a syntax analysis of keywords inputted by the information provider; extracting a plurality of metadata which describe information contents meeting the detected intention of the information provider from the metadata stored in the metadata database; generating an editor in a table form in which the plurality of metadata extracted from the metadata stored in the metadata database are paired with a plurality of metadata fields of the editor and displaying the generated editor to the information provider; receiving a plurality of metadata items inputted by the information provider through the plurality of metadata fields of the editor; determining a store directory for storing contents in the information database according to the detected intention of the information provider; and storing information contents represented by the plurality of inputted metadata items integrated with the plurality of metadata in the directory of the information database determined according to the detected intention of the information provider. 12. The method of claim 8 , wherein the inputted keywords are one of a word unit, a phrase unit and a sentence unit.

13. The computer-based system of claim 12 , further comprising a single computing device or a distributed networked computer system, wherein the modules execute on the single computing device, or wherein the modules, or subcomponents of the modules, execute as distributed across multiple networked computing devices in the distributed networked computer system, and the modules are accessible by programmatic interfaces accessible to the User Interface invoked at a relevant computing device operated by the user.

13. The computer-based system of claim 12 , further comprising a single computing device or a distributed networked computer system, wherein the modules execute on the single computing device, or wherein the modules, or subcomponents of the modules, execute as distributed across multiple networked computing devices in the distributed networked computer system, and the modules are accessible by programmatic interfaces accessible to the User Interface invoked at a relevant computing device operated by the user. 40. The computer-based system of claim 13 , wherein the single computing device is any of a desktop, laptop, pen computer, PDA or a mobile phone.

16. A method, comprising: using a processor to retrieve a plurality of citations each composed by one of a plurality of subjects citing one or more of a plurality of objects that fit searching criteria, wherein a citation is an online posting of an opinion of an object by a subject; using a processor to identify one or more attributes associated with citations, and determine a selection and ranking of objects cited by the citations and using one or more attributes as a filter to select objects; ranking of objects cited by the citations and use one or more attributes as a filter to select objects, identified attributes being transferred from one entity to other search entities, the transferred attributes facilitating a selection and ranking of cited targets for a search result; transferring the identified attributes from the entities of the citations where the attributes are available to the one or more objects; selecting the objects as a search result based on the matching of the search criteria with the attributes transferred to the objects from the citations; using an influence evaluation engine to calculate influence scores of entities that determine a ranking of any subset of objects obtained from the plurality of citations; the influence evaluation engine, which in operation, calculates influence scores of the plurality of subjects that compose the plurality of citations citing the plurality of objects; and enabling a citation centric search process that focuses on influence of the plurality subjects that cite the plurality of objects.

16. A method, comprising: using a processor to retrieve a plurality of citations each composed by one of a plurality of subjects citing one or more of a plurality of objects that fit searching criteria, wherein a citation is an online posting of an opinion of an object by a subject; using a processor to identify one or more attributes associated with citations, and determine a selection and ranking of objects cited by the citations and using one or more attributes as a filter to select objects; ranking of objects cited by the citations and use one or more attributes as a filter to select objects, identified attributes being transferred from one entity to other search entities, the transferred attributes facilitating a selection and ranking of cited targets for a search result; transferring the identified attributes from the entities of the citations where the attributes are available to the one or more objects; selecting the objects as a search result based on the matching of the search criteria with the attributes transferred to the objects from the citations; using an influence evaluation engine to calculate influence scores of entities that determine a ranking of any subset of objects obtained from the plurality of citations; the influence evaluation engine, which in operation, calculates influence scores of the plurality of subjects that compose the plurality of citations citing the plurality of objects; and enabling a citation centric search process that focuses on influence of the plurality subjects that cite the plurality of objects. 18. The method of claim 16 , further comprising: sorting timestamps of the citations of an object and ascribing the earliest timestamp to the object as the object's birth timestamp, which provides an accurate estimate of when the object was created.

1. A method of assessing a key child's expressive language development, comprising: processing an audio recording taken in the key child's language environment to identify segments of the recording that correspond to the key child's vocalizations, wherein a computing device configured to perform the processing is used and the processing includes categorizing a plurality of segments of the audio recording into a plurality of categories, the plurality of categories including categories selected from the group consisting of vocalizations, cries, vegetative sounds, and fixed sounds, and determining which of the plurality of segments characterized as vocalizations are segments of the recording that correspond to the key child's vocalizations by comparing the plurality of segments characterized as vocalizations to a plurality of models; applying an adult automatic speech recognition phone decoder to segments of the key child's vocalizations to identify each occurrence of each of a plurality of phone categories, wherein each of the phone categories corresponds to a pre-defined speech sound; determining a distribution for the phone categories; and using the distribution in an age-based model to assess the key child's expressive language development.

1. A method of assessing a key child's expressive language development, comprising: processing an audio recording taken in the key child's language environment to identify segments of the recording that correspond to the key child's vocalizations, wherein a computing device configured to perform the processing is used and the processing includes categorizing a plurality of segments of the audio recording into a plurality of categories, the plurality of categories including categories selected from the group consisting of vocalizations, cries, vegetative sounds, and fixed sounds, and determining which of the plurality of segments characterized as vocalizations are segments of the recording that correspond to the key child's vocalizations by comparing the plurality of segments characterized as vocalizations to a plurality of models; applying an adult automatic speech recognition phone decoder to segments of the key child's vocalizations to identify each occurrence of each of a plurality of phone categories, wherein each of the phone categories corresponds to a pre-defined speech sound; determining a distribution for the phone categories; and using the distribution in an age-based model to assess the key child's expressive language development. 13. The method of claim 1 , wherein the vocalizations include words, phrases, marginal syllables, consonant-vowel sequences, utterances, phonemes, sequence phonemes, phoneme-like sounds, protophones, lip-trilling sounds, canonical syllables, repetitive babbles, and pitch variations.

9. An apparatus for monitoring an operation of a system characterized by operational parameters, comprising: a non-parametric empirical model for generating estimates of parameter values in response to receiving a query vector of multiple query sensor values for different monitored parameters for a model characterizing the system; a distance estimation engine for determining robust distances between the query vector and each of a set of predetermined historical vectors of multiple historical sensor values for the non-parametric empirical model based on an implementation of an elemental kernel function including: performing an elemental calculation between each query sensor value of the query vector and a corresponding historical sensor value of the historical vector wherein each elemental calculation results in a single elemental contributor for each pair of corresponding query and historical sensor values, eliminating at least one, but less than all, of the elemental contributors formed from at least one comparison between the query vector and the historical vector, and calculating the robust distance between the query vector and the historical vector using a calculation with the remaining elemental contributors; determining weights for the monitored parameters based on the robust distances calculated using the query vector; and combining the weights with the predetermined historical vectors to make predictions for the system.

9. An apparatus for monitoring an operation of a system characterized by operational parameters, comprising: a non-parametric empirical model for generating estimates of parameter values in response to receiving a query vector of multiple query sensor values for different monitored parameters for a model characterizing the system; a distance estimation engine for determining robust distances between the query vector and each of a set of predetermined historical vectors of multiple historical sensor values for the non-parametric empirical model based on an implementation of an elemental kernel function including: performing an elemental calculation between each query sensor value of the query vector and a corresponding historical sensor value of the historical vector wherein each elemental calculation results in a single elemental contributor for each pair of corresponding query and historical sensor values, eliminating at least one, but less than all, of the elemental contributors formed from at least one comparison between the query vector and the historical vector, and calculating the robust distance between the query vector and the historical vector using a calculation with the remaining elemental contributors; determining weights for the monitored parameters based on the robust distances calculated using the query vector; and combining the weights with the predetermined historical vectors to make predictions for the system. 11. The apparatus of claim 9 , wherein the non-parametric empirical model is based on a similarity based model.

4. A method for providing a voicemail to text conversion service, comprising: storing an email address and a name of a user for the user of a voicemail to text conversion service in a memory of a voicemail platform, the email address comprising the name of the user including at least a first and last name of the user; receiving a voicemail message for the user at the voicemail platform; sending the voicemail message and the email address together from the voicemail platform to a speech engine external to the voicemail platform, the speech engine configured to parse the email address and extract a correct spelling of the name of the user from the email address, recognize every occurrence of the name of the user within the voicemail message, and use the email address to correctly spell each corresponding occurrence of the name of the user within converted text of the voicemail message; receiving the converted text at the voicemail platform from the speech engine which is converted, by a processor, from the voicemail message using the email address to correctly spell all occurrences of the name of the user within the voicemail message; and sending the converted text from the voicemail platform to a device of the user.

4. A method for providing a voicemail to text conversion service, comprising: storing an email address and a name of a user for the user of a voicemail to text conversion service in a memory of a voicemail platform, the email address comprising the name of the user including at least a first and last name of the user; receiving a voicemail message for the user at the voicemail platform; sending the voicemail message and the email address together from the voicemail platform to a speech engine external to the voicemail platform, the speech engine configured to parse the email address and extract a correct spelling of the name of the user from the email address, recognize every occurrence of the name of the user within the voicemail message, and use the email address to correctly spell each corresponding occurrence of the name of the user within converted text of the voicemail message; receiving the converted text at the voicemail platform from the speech engine which is converted, by a processor, from the voicemail message using the email address to correctly spell all occurrences of the name of the user within the voicemail message; and sending the converted text from the voicemail platform to a device of the user. 5. The method according to claim 4 , wherein the converted text is delivered to the device of the user via an email message.

3. The method as recited in claim 1 , wherein editing the captured portion of the reference document further comprises: annotating the captured portion of the reference document.

3. The method as recited in claim 1 , wherein editing the captured portion of the reference document further comprises: annotating the captured portion of the reference document. 7. The method of claim 3 , wherein annotating of the captured portion of the reference document further comprises: displaying the captured portion of the reference document to be annotated; receiving a first input from a user designating a first point in the captured portion of the reference document defining a corner of an annotation rectangle; receiving a second input from the user designating a second point in the captured portion of the reference document defining an opposite corner of the annotation rectangle; and annotating the captured portion of the reference document from the first point to the second point of the annotation rectangle when the second input is released.

2. The method of claim 1 wherein the at least one distinguishing characteristic is obtained from a former communication between the sender and the recipient.

2. The method of claim 1 wherein the at least one distinguishing characteristic is obtained from a former communication between the sender and the recipient. 5. The method of claim 2 wherein the at least one distinguishing characteristic includes behavioral demographic information extracted from a previous voice or text communication with the sender.

10. A computer-implemented method of managing a user profile, comprising: selecting an entity with which to conduct online information exchange session; dynamically exposing a portion of a user profile to the entity in response to an active negotiation with the selected entity, the entity providing an incentive based on an amount the portions of the profile exposed to the entity wherein the value of the incentive is negotiated based on quality of the user information exposed, the portion of the user profile includes spam filter settings that when exposed to the entity enables the entity to prepare content for communications through the user's spam filter; and actively negotiating an amount of advertising that is pushed by the entity based on the amount of the portions of the profile exposed.

10. A computer-implemented method of managing a user profile, comprising: selecting an entity with which to conduct online information exchange session; dynamically exposing a portion of a user profile to the entity in response to an active negotiation with the selected entity, the entity providing an incentive based on an amount the portions of the profile exposed to the entity wherein the value of the incentive is negotiated based on quality of the user information exposed, the portion of the user profile includes spam filter settings that when exposed to the entity enables the entity to prepare content for communications through the user's spam filter; and actively negotiating an amount of advertising that is pushed by the entity based on the amount of the portions of the profile exposed. 17. The method of claim 10 , further comprising exposing the portion of the user profile related to personal information that allows personalized presentation of at least one of an advertisement and content.

11. The non-transitory computer-readable medium of claim 9 , wherein the non-transitory computer-readable medium further comprises instructions for receiving input from the user's friends in the social network, the input representing ratings of a plurality of products and services and expressing trust in friends of the social network to provide a rating.

11. The non-transitory computer-readable medium of claim 9 , wherein the non-transitory computer-readable medium further comprises instructions for receiving input from the user's friends in the social network, the input representing ratings of a plurality of products and services and expressing trust in friends of the social network to provide a rating. 12. The non-transitory computer-readable medium of claim 11 , wherein the non-transitory computer-readable medium further comprises: instructions for receiving user input representing a request for a recommendation for a product or service; instructions for forming the data set based on information stored for selected friends of the social network, the selected friends comprising friends that expressed a rating of a product or service and friends that expressed a level of trust in the friends that expressed a rating of a product or service.

12. The method of claim 1 , wherein the social content product interface is provided on a page on the social networking system, wherein the page is associated with an indexed graph object stored on the social networking system, and wherein providing the social content product interface to the viewing user further comprises: filtering received graph objects by the indexed graph object stored on the social networking system; aggregating the filtered graph objects and associated graph actions; and providing the aggregated filtered graph objects and associated graph actions in the social content product interface.

12. The method of claim 1 , wherein the social content product interface is provided on a page on the social networking system, wherein the page is associated with an indexed graph object stored on the social networking system, and wherein providing the social content product interface to the viewing user further comprises: filtering received graph objects by the indexed graph object stored on the social networking system; aggregating the filtered graph objects and associated graph actions; and providing the aggregated filtered graph objects and associated graph actions in the social content product interface. 13. The method of claim 12 , wherein aggregating the filtered graph objects and associated graph actions further comprises: retrieving metadata about the filtered graph objects; and grouping the filtered graph objects by the metadata shared between the filtered graph objects.

9. A transcription method according to claim 8 , further including determining whether the customer terminated the call in response to an agent transcriber becoming available.

9. A transcription method according to claim 8 , further including determining whether the customer terminated the call in response to an agent transcriber becoming available. 10. A transcription method according to claim 9 , further including passing the entire recorded audio message file to an available agent transcriber.

14. A computer implemented system for benchmarking a brand based on social media strength of said brand, comprising: a brand monitoring platform comprising at least one processor configured to execute modules of said brand monitoring platform for monitoring said brand in a virtual social media environment, said modules of said brand monitoring platform comprising: an information acquisition module that acquires input information on said brand; an industry identification module that identifies industries related to said brand and competing brands in said identified industries using said acquired input information on said brand; said information acquisition module that acquires social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment via a network; a category generation module that dynamically generates categories in one or more hierarchical levels in each of said identified industries based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources; a sorting module that sorts said acquired social media information related to said brand and said competing brands in said each of said identified industries into one or more of said dynamically generated categories in said one or more hierarchical levels using a sorting interface; a scoring module that determines an audience score for said brand and each of said competing brands by measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment based on one or more of a plurality of weighted audience score metric parameters using said sorted social media information; said scoring module that determines an engagement score for said brand and said each of said competing brands by measuring interaction between said brand and said each of said competing brands and their followers based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information; said scoring module that generates an aggregate score for said brand and said each of said competing brands using said determined audience score and said determined engagement score; and said scoring module that determines said social media strength of said brand in comparison with said competing brands in said virtual social media environment by assigning a rank to said brand and said each of said competing brands based on said aggregate score for said benchmarking of said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment; whereby said generated aggregate score of said brand and said each of said competing brands benchmarks said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment.

14. A computer implemented system for benchmarking a brand based on social media strength of said brand, comprising: a brand monitoring platform comprising at least one processor configured to execute modules of said brand monitoring platform for monitoring said brand in a virtual social media environment, said modules of said brand monitoring platform comprising: an information acquisition module that acquires input information on said brand; an industry identification module that identifies industries related to said brand and competing brands in said identified industries using said acquired input information on said brand; said information acquisition module that acquires social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment via a network; a category generation module that dynamically generates categories in one or more hierarchical levels in each of said identified industries based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources; a sorting module that sorts said acquired social media information related to said brand and said competing brands in said each of said identified industries into one or more of said dynamically generated categories in said one or more hierarchical levels using a sorting interface; a scoring module that determines an audience score for said brand and each of said competing brands by measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment based on one or more of a plurality of weighted audience score metric parameters using said sorted social media information; said scoring module that determines an engagement score for said brand and said each of said competing brands by measuring interaction between said brand and said each of said competing brands and their followers based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information; said scoring module that generates an aggregate score for said brand and said each of said competing brands using said determined audience score and said determined engagement score; and said scoring module that determines said social media strength of said brand in comparison with said competing brands in said virtual social media environment by assigning a rank to said brand and said each of said competing brands based on said aggregate score for said benchmarking of said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment; whereby said generated aggregate score of said brand and said each of said competing brands benchmarks said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment. 23. The computer implemented system of claim 14 , wherein said modules of said brand monitoring platform further comprise a configuration module that configures one or more of said weighted audience score metric parameters and one or more of said weighted engagement score metric parameters for said determination of said audience score and said engagement score respectively, based on predetermined criteria.

1. A method of displaying secondary data associated with primary data, comprising: generating a three-dimensional visualization of the primary data using a display device, the three-dimensional visualization including a plurality of primary graphical elements representing primary quantitative values and a plurality of primary labels respectively associated with and proximate to the primary graphical elements, the primary graphical elements and primary labels being presented on a front plane of the three-dimensional visualization, the front plane defining first and second axes, and at least one of the primary graphical elements having associated secondary graphical elements representing secondary quantitative values wherein the secondary graphical elements are presented along a third axis of the three-dimensional visualization, the third axis being different from the first and second axes; detecting that the at least one primary graphical elements has been selected; and responsive to said detecting, transitioning the three-dimensional visualization by moving the secondary graphical elements from the third axis of the three-dimensional visualization to the front plane of the three-dimensional visualization.

1. A method of displaying secondary data associated with primary data, comprising: generating a three-dimensional visualization of the primary data using a display device, the three-dimensional visualization including a plurality of primary graphical elements representing primary quantitative values and a plurality of primary labels respectively associated with and proximate to the primary graphical elements, the primary graphical elements and primary labels being presented on a front plane of the three-dimensional visualization, the front plane defining first and second axes, and at least one of the primary graphical elements having associated secondary graphical elements representing secondary quantitative values wherein the secondary graphical elements are presented along a third axis of the three-dimensional visualization, the third axis being different from the first and second axes; detecting that the at least one primary graphical elements has been selected; and responsive to said detecting, transitioning the three-dimensional visualization by moving the secondary graphical elements from the third axis of the three-dimensional visualization to the front plane of the three-dimensional visualization. 5. The method of claim 1 wherein said transitioning further includes shifting certain ones of the primary graphical elements along the first axis to provide spacing to accommodate the secondary graphical elements at the front plane.

10. The non-transitory computer-readable medium according to claim 9 , wherein for each multi-dimensional graphic objects the method further comprises the steps of: constructing a composite model for segmenting the multi-dimensional graphic dataset by determining at least two constituent structures that are incorporated in or related to the multi-dimensional graphic object; and forming the composite model based on respective constituent models that correspond to the respective determined constituent structures, the composite model being operative to segment the multi-dimensional graphic dataset by controlling the constituent models.

10. The non-transitory computer-readable medium according to claim 9 , wherein for each multi-dimensional graphic objects the method further comprises the steps of: constructing a composite model for segmenting the multi-dimensional graphic dataset by determining at least two constituent structures that are incorporated in or related to the multi-dimensional graphic object; and forming the composite model based on respective constituent models that correspond to the respective determined constituent structures, the composite model being operative to segment the multi-dimensional graphic dataset by controlling the constituent models. 11. The non-transitory computer-readable medium according to claim 10 , wherein an interface is selected for enabling a communication between the multi-dimensional graphic objects and the associated geometric template.

1. A method for implementing web applications, comprising: projecting, using a processor of a computing device, one element of a web page of a web application into a view of the web page, the view being a visual representation of a model of the web page, the model including application data and rules, wherein the web application is associated with a browser-level background page that lacks a user interface of its own and that acts as a container for all views of the web application, including the view of the web page, and wherein every window created by the web application shows a different view of the browser-level background page; using a controller to mediate input and convert user input to the web application into commands for the view or the model; and transposing, by the controller, the one element projected in the view of the web page and another element using an insertion point that represents a defined location in a shadow document object model subtree, without affecting a document object model tree of the web page.

1. A method for implementing web applications, comprising: projecting, using a processor of a computing device, one element of a web page of a web application into a view of the web page, the view being a visual representation of a model of the web page, the model including application data and rules, wherein the web application is associated with a browser-level background page that lacks a user interface of its own and that acts as a container for all views of the web application, including the view of the web page, and wherein every window created by the web application shows a different view of the browser-level background page; using a controller to mediate input and convert user input to the web application into commands for the view or the model; and transposing, by the controller, the one element projected in the view of the web page and another element using an insertion point that represents a defined location in a shadow document object model subtree, without affecting a document object model tree of the web page. 6. The method of claim 1 , wherein the shadow document object model subtree is hosted by an element in the document model tree of the web page.

1. A method for transporting text in a real-time Internet Protocol (IP) media transport session, comprising: receiving text signaling from a network or from a text generation device; converting the text signaling into text characters; formatting the identified text characters into Real Time Protocol (RTP) text packets that are associated with the real-time IP media transport session; generating RTP media packets that are also associated with the same real-time IP media transport session; receiving analog tones representing text characters; extracting a digital meaning from the analog tones; discarding other analog volume and duration signaling characteristics from the analog tones; converting the digital meaning of the analog tones into a corresponding real text character; formatting the real text character into a packet payload in one of the RTP text packets without sending the discarded volume and duration signaling characteristics from the analog tones interleaving the RTP text packets with the RTP media packets; assigning sequentially increasing packet numbers to each of the individual interleaved RTP text packets and RTP media packets that correspond to a sequential combined order that each of the interleaved RTP text packets and RTP media packets are sent on a packet switched network and that all correspond with the single same real-time IP media transport session; sending the interleaved text packets and media packets over the packet switched network using the same single real-time IP media transport session.

1. A method for transporting text in a real-time Internet Protocol (IP) media transport session, comprising: receiving text signaling from a network or from a text generation device; converting the text signaling into text characters; formatting the identified text characters into Real Time Protocol (RTP) text packets that are associated with the real-time IP media transport session; generating RTP media packets that are also associated with the same real-time IP media transport session; receiving analog tones representing text characters; extracting a digital meaning from the analog tones; discarding other analog volume and duration signaling characteristics from the analog tones; converting the digital meaning of the analog tones into a corresponding real text character; formatting the real text character into a packet payload in one of the RTP text packets without sending the discarded volume and duration signaling characteristics from the analog tones interleaving the RTP text packets with the RTP media packets; assigning sequentially increasing packet numbers to each of the individual interleaved RTP text packets and RTP media packets that correspond to a sequential combined order that each of the interleaved RTP text packets and RTP media packets are sent on a packet switched network and that all correspond with the single same real-time IP media transport session; sending the interleaved text packets and media packets over the packet switched network using the same single real-time IP media transport session. 3. The method according to claim 1 including adding a second text sequencing only to the RTP text packets that sequentially numbers the RTP text packets in an order transmitted in the IP media transport session independently of the sequential packet numbers used for the interleaved RTP media and RTP text packets.

14. A system for ranking auctions, comprising: at least one processor; memory storing instructions that, when executed cause the processor to: store relevance information for each of a plurality of auctions with respect to a plurality of search terms: receive selection information for a selected auction of the plurality of auctions when a first user performs a selection action with respect to the selected auction and at least one first search term; update the relevance information for the selected auction based at least in part upon the received selection information; receive a query from a second user; identifies auctions that satisfy the received query using a mapping of auctions to query terms, the mapping including the relevance information for each of the identified auctions with respect to the at least one search term; generate a ranking for at least some of the identified auctions using the relevance information for each second term in the query mapped to at least one of the identified actions; and provide ordered search results corresponding to the ranked auctions for display to the user.

14. A system for ranking auctions, comprising: at least one processor; memory storing instructions that, when executed cause the processor to: store relevance information for each of a plurality of auctions with respect to a plurality of search terms: receive selection information for a selected auction of the plurality of auctions when a first user performs a selection action with respect to the selected auction and at least one first search term; update the relevance information for the selected auction based at least in part upon the received selection information; receive a query from a second user; identifies auctions that satisfy the received query using a mapping of auctions to query terms, the mapping including the relevance information for each of the identified auctions with respect to the at least one search term; generate a ranking for at least some of the identified auctions using the relevance information for each second term in the query mapped to at least one of the identified actions; and provide ordered search results corresponding to the ranked auctions for display to the user. 16. The system of claim 14 , wherein the selection action corresponds to a bid placed by another user at an auction that was identified as satisfying a query including at least one common search term.

20. A computer system comprising: a computer having at least one computer processor, wherein the computer is configured to at least: cause a display of at least a portion of a body of text of an electronic document within a first user interface on a display associated with the computer; receive a selection of at least one external resource; receive a selection of at least a portion of the body of text within the first user interface; identify at least two established facts within the selected portion of the body of text using the at least one computer processor; identify a contradiction between the at least two established facts within the body of text using the at least one computer processor; determine whether the at least one external resource comprises information regarding the contradiction; in response to determining that the at least one external resource comprises information regarding the contradiction, generate information regarding a first change to the electronic document based at least in part on the information regarding the contradiction; and cause a display of at least a second user interface on the display, wherein the second user interface is superimposed over at least a portion of the first user interface, and wherein the second user interface comprises at least some of the information regarding the first change to the electronic document to address the contradiction; and receive a first instruction to implement the first change to the electronic document via the second user interface.

20. A computer system comprising: a computer having at least one computer processor, wherein the computer is configured to at least: cause a display of at least a portion of a body of text of an electronic document within a first user interface on a display associated with the computer; receive a selection of at least one external resource; receive a selection of at least a portion of the body of text within the first user interface; identify at least two established facts within the selected portion of the body of text using the at least one computer processor; identify a contradiction between the at least two established facts within the body of text using the at least one computer processor; determine whether the at least one external resource comprises information regarding the contradiction; in response to determining that the at least one external resource comprises information regarding the contradiction, generate information regarding a first change to the electronic document based at least in part on the information regarding the contradiction; and cause a display of at least a second user interface on the display, wherein the second user interface is superimposed over at least a portion of the first user interface, and wherein the second user interface comprises at least some of the information regarding the first change to the electronic document to address the contradiction; and receive a first instruction to implement the first change to the electronic document via the second user interface. 21. The computer system of claim 20 , wherein the computer is further configured to at least: calculate a confidence level of the contradiction according to a formula, wherein the formula comprises at least one of: a factor relating to a location of at least one of the at least two established facts within the electronic document, a factor relating to a proximity of the at least two established facts within the electronic document, or a factor relating to a context of at least one of the at least two established facts within the electronic document, and wherein whether the at least one external resource comprises information regarding the contradiction is determined based at least in part on the confidence level of the contradiction.

11. A system comprising: a memory storing instructions; and at least one processor coupled to the memory and configured to execute the instructions; wherein the instructions, when executed by the at least one processor, cause the at least one processor to execute a method comprising: creating a design environment for a user, wherein said design environment: (i) displays an editable representation of a design from a first encoding of the design inside the design environment; and (ii) allows said user to apply a design font to a portion of text in said design; accepting a mapping from said user, wherein said mapping maps said design font to a set of target fonts; generating a markup language representation of said design; and applying said mapping to said design, at least in part, by generating a script to modify an object model of said design after said object model has been instantiated, and said object model of said design is instantiated after said applying step; wherein: said portion of text in said design is not displayed using said target font while said design is edited in said design environment; said portion of text in said markup language representation is displayed using said target font while said design is rendered outside of said design environment in an external player or inside said design environment in a virtual external player instantiated within said design environment; said first encoding links said design font to said portion of text in said editable representation of said design; a second encoding exported from the design environment links said set of target fonts to said portion of text in said markup language representation of said design; and said first encoding and said second encoding are different encodings.

11. A system comprising: a memory storing instructions; and at least one processor coupled to the memory and configured to execute the instructions; wherein the instructions, when executed by the at least one processor, cause the at least one processor to execute a method comprising: creating a design environment for a user, wherein said design environment: (i) displays an editable representation of a design from a first encoding of the design inside the design environment; and (ii) allows said user to apply a design font to a portion of text in said design; accepting a mapping from said user, wherein said mapping maps said design font to a set of target fonts; generating a markup language representation of said design; and applying said mapping to said design, at least in part, by generating a script to modify an object model of said design after said object model has been instantiated, and said object model of said design is instantiated after said applying step; wherein: said portion of text in said design is not displayed using said target font while said design is edited in said design environment; said portion of text in said markup language representation is displayed using said target font while said design is rendered outside of said design environment in an external player or inside said design environment in a virtual external player instantiated within said design environment; said first encoding links said design font to said portion of text in said editable representation of said design; a second encoding exported from the design environment links said set of target fonts to said portion of text in said markup language representation of said design; and said first encoding and said second encoding are different encodings. 15. The system of claim 11 , wherein said second encoding is a markup language encoding.

7. The device according to claim 1 , wherein the proportional distance criteria comprises a sequence of pages in the first document.

7. The device according to claim 1 , wherein the proportional distance criteria comprises a sequence of pages in the first document. 8. The device according to claim 7 , wherein the sequence includes pages prior to and subsequent to the current page.

8. A system for ranking Web pages in a Web search engine, the system comprising: at least one processor; a communication interface; and a memory containing a plurality of program instructions configured to cause the at least one processor to: receive, via the communication interface over a network, a Web search query from a particular user, the Web search query including at least one keyword; identify one or more Web pages that contain the at least one keyword; determine, for each of the one or more Web pages, a raw page ranking; adjust the raw page ranking of each of at least one Web page among the one or more Web pages based on direct evidence of how interesting the respective Web page is to users to produce an adjusted page ranking, the direct evidence being derived from clickstream data collected from the users; and present, as search results, the at least one Web page to the particular user in accordance with the adjusted page rankings, wherein the direct evidence of how interesting a Web page is to users includes a measure of how often the users traverse to or from the Web page in browsing the Web and a measure of how many users have recently visited the Web page compared with how many users normally visit the Web page, and wherein the measure of how many users have recently visited the Web page compared with how many users normally visit the Web page is given greater weight than the measure of how often the users traverse to or from the Web page in browsing the Web.

8. A system for ranking Web pages in a Web search engine, the system comprising: at least one processor; a communication interface; and a memory containing a plurality of program instructions configured to cause the at least one processor to: receive, via the communication interface over a network, a Web search query from a particular user, the Web search query including at least one keyword; identify one or more Web pages that contain the at least one keyword; determine, for each of the one or more Web pages, a raw page ranking; adjust the raw page ranking of each of at least one Web page among the one or more Web pages based on direct evidence of how interesting the respective Web page is to users to produce an adjusted page ranking, the direct evidence being derived from clickstream data collected from the users; and present, as search results, the at least one Web page to the particular user in accordance with the adjusted page rankings, wherein the direct evidence of how interesting a Web page is to users includes a measure of how often the users traverse to or from the Web page in browsing the Web and a measure of how many users have recently visited the Web page compared with how many users normally visit the Web page, and wherein the measure of how many users have recently visited the Web page compared with how many users normally visit the Web page is given greater weight than the measure of how often the users traverse to or from the Web page in browsing the Web. 14. The system of claim 8 , wherein the measure of how many users have recently visited the Web page compared with how many users normally visit the Web page is given greater weight than the measure of how often the users traverse to or from the Web page in browsing the Web by a factor of at least 10.

1. A method of operating an application service to enhance document productivity, the method comprising: identifying an attempt to add a data connection in a document; in response to identifying the attempt to add the data connection in the document, identifying at least one other document as relevant to the attempt; and communicating a suggestion that identifies at least a portion of the other document for surfacing in a user interface to the application service.

1. A method of operating an application service to enhance document productivity, the method comprising: identifying an attempt to add a data connection in a document; in response to identifying the attempt to add the data connection in the document, identifying at least one other document as relevant to the attempt; and communicating a suggestion that identifies at least a portion of the other document for surfacing in a user interface to the application service. 7. The method of claim 1 wherein identifying the attempt to add the data connection in the document comprises receiving text entered via the user interface to the application service and examining the text for attempts to add data connections in the document.

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

15. A machine-readable storage medium having instructions recorded therein for at least one processor, such that when the at least one processor executes the instructions, a method is performed comprising: detecting, by the at least one processor, an existence of a matrix structure or a multiline expression structure formed by a plurality of atoms of handwritten input; applying, by the at least one processor, a plurality of rewriting rules of an extended grammar parsing framework to atoms, included in a plurality of regions and a plurality of partitions, to produce a plurality of recognition results, the plurality of regions including a plurality of configuration regions and the plurality of partitions including a plurality of configuration partitions, the extended grammar parsing framework having been formed by adding a plurality of tabular structure productions to a grammar parsing framework, the applying a plurality of rewriting rules of an extended grammar parsing framework to atoms, included in a plurality of regions and a plurality of partitions, to produce a plurality of recognition results, further comprising: preventing an application of a unary production on a configuration region if the configuration region includes at least one configuration partition; and selecting and displaying, by the at least one processor, a best recognition result from among the plurality of recognition results. 16. The machine-readable storage medium of claim 15 , wherein the selecting and displaying a best recognition result from among the plurality of recognition results further comprises: selecting the best recognition result from among a plurality of possible recognition results based on a sum of scores assigned to each one of the plurality of rewriting rules applied to produce each respective one of the plurality of possible recognition results.

4. The method of claim 3 wherein step (e) further includes the step of: (iv) for said word not spoken during the training session, repeating steps (i), (ii), and (iii) for each piece thereof; each word piece having a string of output-related models associated therewith.

4. The method of claim 3 wherein step (e) further includes the step of: (iv) for said word not spoken during the training session, repeating steps (i), (ii), and (iii) for each piece thereof; each word piece having a string of output-related models associated therewith. 5. The method of claim 4 wherein step (e) further includes the step of: (v) concatenating the strings in the same order as the word pieces said strings represent to form a word baseform of output related models.

9. A system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive a plurality of past computer network queries; identify among the plurality of past computer network queries a plurality sub-queries each including one or more contiguous words from a past query of the plurality of past computer network queries, the plurality of sub-queries including start sub-queries including a starting word of the past query and end sub-queries including an ending word of the past query; for each sub-query of the plurality of sub-queries: generate a start sub-query count equal to a number of occurrences of the each sub query of the plurality of sub-queries as a start sub-query; generate an end sub-query count equal to a number of occurrences of the each sub query of the plurality of sub-queries as an end sub-query; generate a score that: is a function of the start sub-query count and the end sub-query count; decreases with increasing start sub-query count; and increases with increasing end sub-query count; receive an ecommerce query including a plurality of terms; for a plurality of first phrases including contiguous terms of the plurality of terms, determine weights for the plurality of first phrases according to scores of a sub-query of the plurality of sub-queries corresponding to the plurality of first phrases; submit the ecommerce query to a search engine with the weights for the plurality of first phrases; receive results from the search engine; and return the results.

9. A system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive a plurality of past computer network queries; identify among the plurality of past computer network queries a plurality sub-queries each including one or more contiguous words from a past query of the plurality of past computer network queries, the plurality of sub-queries including start sub-queries including a starting word of the past query and end sub-queries including an ending word of the past query; for each sub-query of the plurality of sub-queries: generate a start sub-query count equal to a number of occurrences of the each sub query of the plurality of sub-queries as a start sub-query; generate an end sub-query count equal to a number of occurrences of the each sub query of the plurality of sub-queries as an end sub-query; generate a score that: is a function of the start sub-query count and the end sub-query count; decreases with increasing start sub-query count; and increases with increasing end sub-query count; receive an ecommerce query including a plurality of terms; for a plurality of first phrases including contiguous terms of the plurality of terms, determine weights for the plurality of first phrases according to scores of a sub-query of the plurality of sub-queries corresponding to the plurality of first phrases; submit the ecommerce query to a search engine with the weights for the plurality of first phrases; receive results from the search engine; and return the results. 15. The system of claim 9 , wherein the executable and operational data are further effective to cause the one or more processors to generate the score that is a function of the start sub-query count and the end sub-query count by generating the score such that that the score decreases with increasing start sub-query count.

4. The method of claim 1 , further comprising the step of: repeating the step of identifying a plurality of Page URIs and the step of identifying a plurality of second File URIs until a break condition is met.

4. The method of claim 1 , further comprising the step of: repeating the step of identifying a plurality of Page URIs and the step of identifying a plurality of second File URIs until a break condition is met. 5. The method of claim 4 , wherein the break condition comprises a break condition selected from the group consisting of: a number of depths of walkthrough, a total number of files collected, a timeout of walkthrough; and a number of pages visited.

1. A method comprising: placing an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoking a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtaining information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; using the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identifying items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and ranking the relevant items.

1. A method comprising: placing an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoking a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtaining information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; using the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identifying items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and ranking the relevant items. 9. The method as claimed in claim 1 further including using the extracted keywords to produce a contextual advertisement placement.

89. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information comprises e-mail addresses; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender.

89. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information comprises e-mail addresses; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. 100. The method of claim 89 wherein the first activity information comprises sending an instant message from the sender to the recipient.

15. The method of claim 11 , wherein the underlying source code comprises a set of elements designating objects to be created, and relationships between these objects specifies how the objects are wired together.

15. The method of claim 11 , wherein the underlying source code comprises a set of elements designating objects to be created, and relationships between these objects specifies how the objects are wired together. 16. The method of claim 15 , wherein the changes are changes to source level elements.

9. 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: analyzing acoustic features of a received audio signal from a communication device; identifying a repeating pattern of meta-data associated with the acoustic features, wherein the repeating pattern of meta-data comprises a speed of a caller associated with the communication device; classifying a background environment of the caller based on the acoustic features and the repeating pattern of meta-data, to yield a background environment classification; selecting an acoustic model matched to the background environment classification from a plurality of acoustic models; and performing speech recognition on the received audio signal using the acoustic model.

9. 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: analyzing acoustic features of a received audio signal from a communication device; identifying a repeating pattern of meta-data associated with the acoustic features, wherein the repeating pattern of meta-data comprises a speed of a caller associated with the communication device; classifying a background environment of the caller based on the acoustic features and the repeating pattern of meta-data, to yield a background environment classification; selecting an acoustic model matched to the background environment classification from a plurality of acoustic models; and performing speech recognition on the received audio signal using the acoustic model. 13. The system of claim 9 , where the meta-data comprises one of global positioning system coordinates, elevation, automatic number identification information, computing device identification number (comprised of an internet protocol address or MAC address), uniform resource locator address, individual environmental habits, personal profile information, time, and rate of movement.

4. An information classification device according to claim 1 , wherein the character information extracting means comprises extraction information storing means for storing extraction information to extract the character strings from the character information of the data, and extracts the character strings from the character information of the data based on the extraction information.

4. An information classification device according to claim 1 , wherein the character information extracting means comprises extraction information storing means for storing extraction information to extract the character strings from the character information of the data, and extracts the character strings from the character information of the data based on the extraction information. 8. An information classification device according to claim 4 , wherein: the character information extracting means further comprises a keyword dictionary for storing keyword information defining keywords extracted as the character strings for the each class as the extraction information storing means; and the character information extracting means further comprises: data storing means for storing data such as a document; text data extracting means for referring to the data stored in the data storing means to extract text data from the data referred to; and keyword extracting means for extracting the keywords from the extracted text data based on the keyword information stored in the keyword dictionary to generate a keyword string as the character string.

1. A method of identifying digital content related to a portion of a block of text, the method comprising: receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; and the digital content comprises still or moving digital images; providing the block of text to a computer-implemented service that: separates the one or more words included in the block of text into one or more segments comprising phrases or individual words; searches a dataset of digital content based on the one or more segmented phrases or individual words; retrieves from the dataset one or more digital content items or identifiers associated with the one or more digital content items, wherein the digital content items are related to the one or more segmented phrases or individual words, the dataset of digital content containing licensing information regarding the one or more digital content items are licensed or unlicensed; determines from the licensing information, for each of the one or more retrieved digital content items or identifiers, whether a license has been indicated; receiving an indication from the computer-implemented service of retrieved digital content items or identifiers for which a license has been indicated; presenting the indication of retrieved digital content items or identifiers to a user; receiving a selection of one or more of the presented digital content items or identifiers from the user; and receiving for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text.

1. A method of identifying digital content related to a portion of a block of text, the method comprising: receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; and the digital content comprises still or moving digital images; providing the block of text to a computer-implemented service that: separates the one or more words included in the block of text into one or more segments comprising phrases or individual words; searches a dataset of digital content based on the one or more segmented phrases or individual words; retrieves from the dataset one or more digital content items or identifiers associated with the one or more digital content items, wherein the digital content items are related to the one or more segmented phrases or individual words, the dataset of digital content containing licensing information regarding the one or more digital content items are licensed or unlicensed; determines from the licensing information, for each of the one or more retrieved digital content items or identifiers, whether a license has been indicated; receiving an indication from the computer-implemented service of retrieved digital content items or identifiers for which a license has been indicated; presenting the indication of retrieved digital content items or identifiers to a user; receiving a selection of one or more of the presented digital content items or identifiers from the user; and receiving for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text. 3. The method of claim 1 wherein the digital content comprises digital images.

8. A device for dynamic adjustment of text input system components, the device comprising: one or more processors; and a text input system; a machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the device to perform operations comprising: receiving an indication of user activity with respect to the text input system; determining one or more activity indicators based on at least the user activity, the one or more activity indicators corresponding to typing habits of a user, including at least one of variance of exact touch position within one or more keys and drift of a recorded touch position for the one or more keys; identifying one or more components of the text input system, each component providing a typing assistance functionality to the user and being associated with a set of parameters, the one or more components including a key target resizing component associated with a set of parameters comprising an amount of inactive space around each key and a size of an active area for each key; and for each of the one or more components: determining, by the one or more processors, whether the component should be adjusted based on the one or more activity indicators; and dynamically adjusting the component when it is determined that the component should be adjusted based on the one or more activity indicators, wherein dynamically adjusting the component comprises adjusting the set of parameters associated with the component.

8. A device for dynamic adjustment of text input system components, the device comprising: one or more processors; and a text input system; a machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the device to perform operations comprising: receiving an indication of user activity with respect to the text input system; determining one or more activity indicators based on at least the user activity, the one or more activity indicators corresponding to typing habits of a user, including at least one of variance of exact touch position within one or more keys and drift of a recorded touch position for the one or more keys; identifying one or more components of the text input system, each component providing a typing assistance functionality to the user and being associated with a set of parameters, the one or more components including a key target resizing component associated with a set of parameters comprising an amount of inactive space around each key and a size of an active area for each key; and for each of the one or more components: determining, by the one or more processors, whether the component should be adjusted based on the one or more activity indicators; and dynamically adjusting the component when it is determined that the component should be adjusted based on the one or more activity indicators, wherein dynamically adjusting the component comprises adjusting the set of parameters associated with the component. 15. The system of claim 8 , further comprising a touchscreen configured to interact with the text input system.

12. The method of claim 1 in which each document is associated with location information indicating the location of each portion of document content within the document.

12. The method of claim 1 in which each document is associated with location information indicating the location of each portion of document content within the document. 15. The method of claim 12 in which the step of copying the portions of document content from the second customized document to the amended first customized document comprises the step of using the location information associated with the amended first customized document to determine the location in the amended first customized document to which the portions of document content should be copied.

20. A computer system, comprising: a processor configured to: obtain an object tree comprising a plurality of hierarchically organized objects, each object containing data and methods for processing a corresponding definitional element of said display page; modify said object tree at runtime; and invoke said methods of the objects comprising the object tree to generate, dynamically at runtime, a plurality of definitional statements, each definitional statement being associated with one or more definitional elements of said display page; and a memory configured to store said object tree; wherein said methods for processing a corresponding definitional element of said display page comprise computer instructions which when executed generate said plurality of definitional statements; wherein said definitional statements comprise hypertext markup language (HTML) or other statements usable by a browser or other software to render the display page; and wherein the display page generated using the objects comprising the object tree as modified reflects the modification made to said object tree at runtime.

20. A computer system, comprising: a processor configured to: obtain an object tree comprising a plurality of hierarchically organized objects, each object containing data and methods for processing a corresponding definitional element of said display page; modify said object tree at runtime; and invoke said methods of the objects comprising the object tree to generate, dynamically at runtime, a plurality of definitional statements, each definitional statement being associated with one or more definitional elements of said display page; and a memory configured to store said object tree; wherein said methods for processing a corresponding definitional element of said display page comprise computer instructions which when executed generate said plurality of definitional statements; wherein said definitional statements comprise hypertext markup language (HTML) or other statements usable by a browser or other software to render the display page; and wherein the display page generated using the objects comprising the object tree as modified reflects the modification made to said object tree at runtime. 24. The system of claim 20 , wherein said object tree is modified based at least in part on an output provided at runtime by an application.

9. A system for document retrieval in a network environment where documents are stored with corresponding privacy codes, comprising: a query server computer in communication with the network, the query server computer configured to receive a query including a keyword and an access code identifier from a requester and generate a second index of words in the privacy index from documents having access codes corresponding to the access code identifier; and generate a privacy index of all documents available on the network indexed by their corresponding privacy codes, the privacy codes defining permitted conditions of document access that are securely associated with the documents according to the control of at least one document custodian for each document.

9. A system for document retrieval in a network environment where documents are stored with corresponding privacy codes, comprising: a query server computer in communication with the network, the query server computer configured to receive a query including a keyword and an access code identifier from a requester and generate a second index of words in the privacy index from documents having access codes corresponding to the access code identifier; and generate a privacy index of all documents available on the network indexed by their corresponding privacy codes, the privacy codes defining permitted conditions of document access that are securely associated with the documents according to the control of at least one document custodian for each document. 10. The system according to claim 9 , comprising: a search engine in communication with the network and configured to: receive a query from a requester; and generate a list of documents from said privacy index which match search parameters of the query and privacy codes of the requester.

10. A computer-implemented method for providing a translation of a set of one or more terms or phrases from a source language to more than one target language, the method comprising the steps of: (a) providing a repository in a memory for storing one or more translations of said set of one or more terms or phrases in said more than one target language; (b) collecting said one or more translations for said set of one or more terms or phrases in said more than one target language provided by one or more users wherein collecting said one or more translations comprises the steps of: (1) obtaining one or more translations in said more than one target language for individual terms or phrases of said set of one or more terms or phrases provided by said one or more users; and (2) storing said one or more translations for said individual terms or phrases in said repository, wherein the method further comprises the steps of: (c) storing a first particular target language and a second particular target language identified by a user; and (d) in response to receiving a user's request for a preferred translation of said set of one or more terms or phrases: (1) retrieving said user's first particular target language and said user's second particular target language; (2) identifying said preferred translation for each individual term or phrase of said set of one or more terms or phrases, wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said first particular target language; (3) in response to a translation not being provided for an individual term or phrase of said set of one or more terms or phrases for said user's first target language, identifying said preferred translation for said individual term or phrase wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said user's second target language; and (4) causing display of said identified preferred translation to said user.

10. A computer-implemented method for providing a translation of a set of one or more terms or phrases from a source language to more than one target language, the method comprising the steps of: (a) providing a repository in a memory for storing one or more translations of said set of one or more terms or phrases in said more than one target language; (b) collecting said one or more translations for said set of one or more terms or phrases in said more than one target language provided by one or more users wherein collecting said one or more translations comprises the steps of: (1) obtaining one or more translations in said more than one target language for individual terms or phrases of said set of one or more terms or phrases provided by said one or more users; and (2) storing said one or more translations for said individual terms or phrases in said repository, wherein the method further comprises the steps of: (c) storing a first particular target language and a second particular target language identified by a user; and (d) in response to receiving a user's request for a preferred translation of said set of one or more terms or phrases: (1) retrieving said user's first particular target language and said user's second particular target language; (2) identifying said preferred translation for each individual term or phrase of said set of one or more terms or phrases, wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said first particular target language; (3) in response to a translation not being provided for an individual term or phrase of said set of one or more terms or phrases for said user's first target language, identifying said preferred translation for said individual term or phrase wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said user's second target language; and (4) causing display of said identified preferred translation to said user. 11. The method of claim 10 , wherein said preferred translation for said individual term or phrase is a translation stored a most number of times in said repository in said particular target language.

19. A system comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: analyzing, using a time series engine, a distribution of unstructured time-stamped data to identify a plurality of potential time series data hierarchies for structuring the unstructured time-stamped data, wherein a potential time series data hierarchy is a framework for structuring the data through use of multiple time series, and wherein the time series engine is at a server layer of a time series computing system; performing, using the time series engine, an analysis of the plurality of potential time series data hierarchies, wherein performing the analysis of the plurality of potential time series data hierarchies includes determining an optimal time series frequency and a data sufficiency metric for each of the plurality of potential time series data hierarchies; comparing data sufficiency metrics for the plurality of potential time series data hierarchies; selecting a hierarchy of the plurality of potential time series data hierarchies based on the comparison of the data sufficiency metrics; structuring the unstructured time-stamped data into structured time-stamped data according to the hierarchy and the optimal time series frequency, wherein structuring the transformed time-stamped data into the structured time-stamped data is performed using a single pass of the unstructured time-stamped data through the time series engine; computing a plurality of transformations of the structured time-stamped data using the single pass of the structured time-stamped data through the time series engine; transforming the structured time-stamped data into transformed time-stamped data according to the plurality of transformations; and providing, using an application programming interface, the transformed time-stamped data for visual presentation.

19. A system comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: analyzing, using a time series engine, a distribution of unstructured time-stamped data to identify a plurality of potential time series data hierarchies for structuring the unstructured time-stamped data, wherein a potential time series data hierarchy is a framework for structuring the data through use of multiple time series, and wherein the time series engine is at a server layer of a time series computing system; performing, using the time series engine, an analysis of the plurality of potential time series data hierarchies, wherein performing the analysis of the plurality of potential time series data hierarchies includes determining an optimal time series frequency and a data sufficiency metric for each of the plurality of potential time series data hierarchies; comparing data sufficiency metrics for the plurality of potential time series data hierarchies; selecting a hierarchy of the plurality of potential time series data hierarchies based on the comparison of the data sufficiency metrics; structuring the unstructured time-stamped data into structured time-stamped data according to the hierarchy and the optimal time series frequency, wherein structuring the transformed time-stamped data into the structured time-stamped data is performed using a single pass of the unstructured time-stamped data through the time series engine; computing a plurality of transformations of the structured time-stamped data using the single pass of the structured time-stamped data through the time series engine; transforming the structured time-stamped data into transformed time-stamped data according to the plurality of transformations; and providing, using an application programming interface, the transformed time-stamped data for visual presentation. 25. The system of claim 19 , wherein the unstructured time-stamped data is analyzed by applying a seasonality test, an intermittency test, or a trending data test.

1. A method, comprising: identifying, using at least one hardware processor, a plurality of different previously-submitted search queries; filtering, using at least one evaluation file, the plurality of different previously-submitted search queries to remove one or more specified words from the plurality of different previously-submitted search queries to generate a plurality of filtered search queries, wherein the at least one evaluation file includes at least one of instructions or parameters for generating at least one canonical search query form of the plurality of different previously-submitted search queries; modifying, using the at least one evaluation file, remaining words in the plurality of filtered search queries to generate a plurality of modified search queries; determining, as search queries that map to a particular canonical search query form, a subset of the plurality of different previously-submitted search queries that are used to generate, as a result of filtering the plurality of different previously-submitted search queries and modifying the plurality of filtered search queries using the at least one evaluation file, the particular canonical search query form; ranking the search queries that map to the particular canonical search query form based, at least in part, on a frequency of submission of each different previously-submitted search query that maps to the particular canonical search query form; and identifying, based on the ranking, a particular one of the different previously-submitted search queries in the ranked search queries that map to the particular canonical search query form as a representative search query of the search queries that map to the particular canonical search query form.

1. A method, comprising: identifying, using at least one hardware processor, a plurality of different previously-submitted search queries; filtering, using at least one evaluation file, the plurality of different previously-submitted search queries to remove one or more specified words from the plurality of different previously-submitted search queries to generate a plurality of filtered search queries, wherein the at least one evaluation file includes at least one of instructions or parameters for generating at least one canonical search query form of the plurality of different previously-submitted search queries; modifying, using the at least one evaluation file, remaining words in the plurality of filtered search queries to generate a plurality of modified search queries; determining, as search queries that map to a particular canonical search query form, a subset of the plurality of different previously-submitted search queries that are used to generate, as a result of filtering the plurality of different previously-submitted search queries and modifying the plurality of filtered search queries using the at least one evaluation file, the particular canonical search query form; ranking the search queries that map to the particular canonical search query form based, at least in part, on a frequency of submission of each different previously-submitted search query that maps to the particular canonical search query form; and identifying, based on the ranking, a particular one of the different previously-submitted search queries in the ranked search queries that map to the particular canonical search query form as a representative search query of the search queries that map to the particular canonical search query form. 2. The method of claim 1 , wherein the plurality of different previously-submitted search queries include a plurality of previously-searched questions with each previously-searched question including a word indicating a question.

1. A method of speaker verification, the method comprising: identifying, by a processor, a target speaker's speech, using a known speaker voiceprint, from an audio recording that includes the target speaker's speech and a known speaker's speech, the known speaker voiceprint corresponding to the known speaker, wherein using the known speaker voiceprint includes enabling exclusion of speech segments of the known speaker's speech to reduce a total number of speech segments used to verify the target speaker's speech to improve accuracy with reduced processing time or power for verifying relative to having all speech segments of the target and known speaker's speech under consideration; and verifying, by the processor, the target speaker based on the target speaker's voiceprint, an accuracy of the known speaker voiceprint being higher relative to an accuracy of the target speaker's voiceprint.

1. A method of speaker verification, the method comprising: identifying, by a processor, a target speaker's speech, using a known speaker voiceprint, from an audio recording that includes the target speaker's speech and a known speaker's speech, the known speaker voiceprint corresponding to the known speaker, wherein using the known speaker voiceprint includes enabling exclusion of speech segments of the known speaker's speech to reduce a total number of speech segments used to verify the target speaker's speech to improve accuracy with reduced processing time or power for verifying relative to having all speech segments of the target and known speaker's speech under consideration; and verifying, by the processor, the target speaker based on the target speaker's voiceprint, an accuracy of the known speaker voiceprint being higher relative to an accuracy of the target speaker's voiceprint. 2. The method of claim 1 , wherein the known speaker is an agent of a call center and the target speaker is a caller to the call center that is conversing with the agent.

6. A method comprising: recognizing a plurality of textual strings within a written work, wherein each textual string is associated with a character identity of a plurality of character identities within the written work; for the character identity; calculating, by one or more hardware processors, a significance value based at least in part on a frequency of occurrence of one or more textual strings associated with the character identity; determining that the character identity is included in other written works; updating the significance value for the character identity based at least in part on the inclusion of the character identity in the other written works; and selecting a primary textual string from the one or more textual strings associated with the character identity; and providing a list of at least a portion of the plurality of character identities, the list including the primary textual string and other primary textual strings for the at least the portion of the plurality of character identities and the list being sorted based at least in part on the significance value.

6. A method comprising: recognizing a plurality of textual strings within a written work, wherein each textual string is associated with a character identity of a plurality of character identities within the written work; for the character identity; calculating, by one or more hardware processors, a significance value based at least in part on a frequency of occurrence of one or more textual strings associated with the character identity; determining that the character identity is included in other written works; updating the significance value for the character identity based at least in part on the inclusion of the character identity in the other written works; and selecting a primary textual string from the one or more textual strings associated with the character identity; and providing a list of at least a portion of the plurality of character identities, the list including the primary textual string and other primary textual strings for the at least the portion of the plurality of character identities and the list being sorted based at least in part on the significance value. 18. The method as recited in claim 6 , further comprising: identifying a motion picture corresponding to the written work; comparing the one or more textual strings associated with the character identity to a collection of motion picture character names; selecting, for the character identity, a motion picture character name from the collection of motion picture character names that most closely matches the one or more textual strings associated with the character identity; and associating the motion picture character name selected with the character identity in the written work.

14. The method of claim 13 , wherein the language statistics analyzing step further comprises: calculating language statistics information for article portions in earlier pages than the page having the first block segment; and determining a probability that the first block segment in the candidate continuing article portion has a continuing article portion based on the calculated earlier language statistics information.

14. The method of claim 13 , wherein the language statistics analyzing step further comprises: calculating language statistics information for article portions in earlier pages than the page having the first block segment; and determining a probability that the first block segment in the candidate continuing article portion has a continuing article portion based on the calculated earlier language statistics information. 17. The method of claim 14 , wherein the language statistics information comprises word frequency information, and the continuation language statistics analyzing step includes calculating match scores based on word frequencies in text in the first block segment and text in the article portions on earlier pages.

6. The system as recited in claim 1, wherein said set top box further comprises a memory operably coupled to said receiver configured to store said glyph.

6. The system as recited in claim 1, wherein said set top box further comprises a memory operably coupled to said receiver configured to store said glyph. 8. The system as recited in claim 6, wherein said memory is a flash memory.

13. A system comprising: a machine-readable storage medium containing at least a dynamic validating editor, wherein the dynamic validating editor includes instructions for: receiving at least one indication of at least one user edit to a portion of a document; representing the portion of the document as a node within a hierarchical representation of the document; determining a type of the node; determining whether a customized editor is available for the portion of the document; and when the customized editor is available, populating at least part of the customized editor dynamically based, at least in part, on (i) the type of the node, (ii) imported classes from a schema, and (iii) at least one restriction that is specified by an enum in the schema and that is applicable to the node.

13. A system comprising: a machine-readable storage medium containing at least a dynamic validating editor, wherein the dynamic validating editor includes instructions for: receiving at least one indication of at least one user edit to a portion of a document; representing the portion of the document as a node within a hierarchical representation of the document; determining a type of the node; determining whether a customized editor is available for the portion of the document; and when the customized editor is available, populating at least part of the customized editor dynamically based, at least in part, on (i) the type of the node, (ii) imported classes from a schema, and (iii) at least one restriction that is specified by an enum in the schema and that is applicable to the node. 14. The system of claim 13 , further comprising the document.

7. At a computer system, a method for presenting message conversation data, the method comprising: an act of receiving a command to present message conversation data for an electronic mail conversation that includes one or more electronic mail messages; an act of accessing an electronic mail conversation item that represents the electronic mail conversation, the electronic mail conversation item including a plurality of conversation attribute values that represent the attributes of the electronic mail conversation including an identification of each message associated with the conversation and corresponding one or more participants of each message and a recipient delta field identifying a list of entities that were added or removed from each message that has been identified as being associated with the conversation, and wherein the electronic mail conversation item is responsively updated and persisted whenever any electronic mail message corresponding to the electronic mail conversation is received, and by at least updating the conversation attribute values to ensure that every participant in the electronic mail conversation and every received message corresponding to the conversation is reflected in the electronic mail conversation item; an act of retrieving persisted conversation attribute values from the electronic mail conversation item; an act of presenting the retrieved conversation attribute values along with portions of the one or more electronic mail messages; an act of receiving an indication from a user that the received electronic mail message and any electronic mail messages determined to be part of the conversation are to be ignored; an act of scanning each of the folders in the user's mailbox for electronic mail messages that are related by subject to the received electronic mail message, wherein scanning includes scanning for both previously sent messages in a sent items folder and scanning for previously received messages in at least one other mailbox folder; an act of moving the received electronic mail message, any previously sent or received email messages and any subsequently sent or received electronic mail messages identified by the scan as part of the conversation to an ignored conversations folder; and an act of displaying the electronic mail conversation including the conversation's corresponding messages, the displayed conversation including the following in a single application window: a topic header, at least a portion of each message contributed to the conversation including an indication of who sent the message, each message including a URL link to any additional message body text, a participant change indication proximally placed next to each message where a participant was added or removed from the conversation including an identification of the participant who was added or removed, a number of messages indicator indicating the number of messages in the conversation, a timespan indicator indicating how long the conversation has existed, an active participants indicator indicating the participants that have contributed to the conversation and a most active participant indicator indicating the conversation participant that has contributed the most number of messages to the conversation.

7. At a computer system, a method for presenting message conversation data, the method comprising: an act of receiving a command to present message conversation data for an electronic mail conversation that includes one or more electronic mail messages; an act of accessing an electronic mail conversation item that represents the electronic mail conversation, the electronic mail conversation item including a plurality of conversation attribute values that represent the attributes of the electronic mail conversation including an identification of each message associated with the conversation and corresponding one or more participants of each message and a recipient delta field identifying a list of entities that were added or removed from each message that has been identified as being associated with the conversation, and wherein the electronic mail conversation item is responsively updated and persisted whenever any electronic mail message corresponding to the electronic mail conversation is received, and by at least updating the conversation attribute values to ensure that every participant in the electronic mail conversation and every received message corresponding to the conversation is reflected in the electronic mail conversation item; an act of retrieving persisted conversation attribute values from the electronic mail conversation item; an act of presenting the retrieved conversation attribute values along with portions of the one or more electronic mail messages; an act of receiving an indication from a user that the received electronic mail message and any electronic mail messages determined to be part of the conversation are to be ignored; an act of scanning each of the folders in the user's mailbox for electronic mail messages that are related by subject to the received electronic mail message, wherein scanning includes scanning for both previously sent messages in a sent items folder and scanning for previously received messages in at least one other mailbox folder; an act of moving the received electronic mail message, any previously sent or received email messages and any subsequently sent or received electronic mail messages identified by the scan as part of the conversation to an ignored conversations folder; and an act of displaying the electronic mail conversation including the conversation's corresponding messages, the displayed conversation including the following in a single application window: a topic header, at least a portion of each message contributed to the conversation including an indication of who sent the message, each message including a URL link to any additional message body text, a participant change indication proximally placed next to each message where a participant was added or removed from the conversation including an identification of the participant who was added or removed, a number of messages indicator indicating the number of messages in the conversation, a timespan indicator indicating how long the conversation has existed, an active participants indicator indicating the participants that have contributed to the conversation and a most active participant indicator indicating the conversation participant that has contributed the most number of messages to the conversation. 12. The method as recited in claim 7 , wherein the act of retrieving persisted conversation attribute values from the electronic mail conversation item comprises an act of sending conversation data to a message client.

7. A non-transitory computer readable storage medium storing one or more computer programs executed by a computerized server system, the one or more computer programs comprising instructions to generate a facts database, the instructions including: instructions to access a source document from a document host; instructions to extract one or more facts from the source document; instructions to identify a set of linking documents that have one or more links to the source document, wherein a respective link contains anchor text; instructions to generate a set of candidate labels from the anchor text of the linking documents, a respective candidate label of the set of candidate labels comprising text extracted from the anchor text in the one or more links to the source document in the set of linking documents; instructions to select a respective candidate label from the set of candidate labels as a unifying subject of the one or more facts extracted from the source document; and instructions to store in the facts database an information set distinct from the source document, wherein the information set includes the unifying subject, one or more entries corresponding to the one or more facts extracted from the source document, and source document information for the one or more facts corresponding to the one or more entries.

7. A non-transitory computer readable storage medium storing one or more computer programs executed by a computerized server system, the one or more computer programs comprising instructions to generate a facts database, the instructions including: instructions to access a source document from a document host; instructions to extract one or more facts from the source document; instructions to identify a set of linking documents that have one or more links to the source document, wherein a respective link contains anchor text; instructions to generate a set of candidate labels from the anchor text of the linking documents, a respective candidate label of the set of candidate labels comprising text extracted from the anchor text in the one or more links to the source document in the set of linking documents; instructions to select a respective candidate label from the set of candidate labels as a unifying subject of the one or more facts extracted from the source document; and instructions to store in the facts database an information set distinct from the source document, wherein the information set includes the unifying subject, one or more entries corresponding to the one or more facts extracted from the source document, and source document information for the one or more facts corresponding to the one or more entries. 8. The computer readable storage medium of claim 7 , further comprising instructions to: select one or more labels of the candidate labels according to predefined criteria; and associate the selected second labels with the source document and the one or more facts extracted from the source document.

11. An apparatus for object detection and recognition comprising: memory and a processor; an input device coupled to the processor and configured to receive an image to undergo object detection and recognition; an input device coupled to the processor and configured to access a pre-specified classifier stored in the memory, the classifier configured to estimate a belief distribution over parts for each image element of the received image; a conditional random field model stored in the memory; and an inference mechanism coupled to the processor and configured to carry out an inference process on the conditional random field model to force a global part labeling which is substantially layout-consistent and thereby generate a part label map for the received image, the part label map comprising, for each image element of the received image, a label indicating which of a plurality of parts the image element is assigned to, each part being a densely represented image area; the processor being configured to: form the classifier during a training phase using a plurality of training images together with a mask for each training image indicating which pixels in the training image correspond to objects to be recognized and which correspond to background that is not required to be recognized; during the training phase, form an initial part label map for a training image by dividing the image into a plurality of parts having a consistent pair-wise ordering such that the parts contiguously cover the image; and ensure that the parts meet constraints related to image elements, the image elements being non-immediate neighbors.

11. An apparatus for object detection and recognition comprising: memory and a processor; an input device coupled to the processor and configured to receive an image to undergo object detection and recognition; an input device coupled to the processor and configured to access a pre-specified classifier stored in the memory, the classifier configured to estimate a belief distribution over parts for each image element of the received image; a conditional random field model stored in the memory; and an inference mechanism coupled to the processor and configured to carry out an inference process on the conditional random field model to force a global part labeling which is substantially layout-consistent and thereby generate a part label map for the received image, the part label map comprising, for each image element of the received image, a label indicating which of a plurality of parts the image element is assigned to, each part being a densely represented image area; the processor being configured to: form the classifier during a training phase using a plurality of training images together with a mask for each training image indicating which pixels in the training image correspond to objects to be recognized and which correspond to background that is not required to be recognized; during the training phase, form an initial part label map for a training image by dividing the image into a plurality of parts having a consistent pair-wise ordering such that the parts contiguously cover the image; and ensure that the parts meet constraints related to image elements, the image elements being non-immediate neighbors. 13. An apparatus as claimed in claim 11 wherein the conditional random field model comprises a hidden layer of part labels.

12. The method of claim 11 , wherein the multimedia objects are extracted from the multimedia content by steps further comprising: segmenting the content of each multimedia type in the multimedia object into segments within the multimedia object by media segmentation processing; and generating at least one feature description for at least one of the segments by feature extraction and annotation, wherein the generated media object descriptions comprise the at least one feature description for the at least one of the segments.

12. The method of claim 11 , wherein the multimedia objects are extracted from the multimedia content by steps further comprising: segmenting the content of each multimedia type in the multimedia object into segments within the multimedia object by media segmentation processing; and generating at least one feature description for at least one of the segments by feature extraction and annotation, wherein the generated media object descriptions comprise the at least one feature description for the at least one of the segments. 17. The method of claim 12 , wherein generating media object hierarchy descriptions generates media object hierarchy descriptions of the media object descriptions based on relationships of media objects represented by the media object descriptions, and wherein the relationships are selected from the group comprising media feature relationships, semantic feature relationships, temporal feature relationships, and spatial feature relationships.

24. A method, performed by a content search system including a parser, a rules database memory device, a normalizer having a decoder and a plurality of transducers, and a search engine, for determining whether an input string matches one or more rules stored in the rules database, comprising: extracting selected portions of the input string, using the parser, to form a filtered input string; forwarding, by the parser, the filtered input string to the normalizer; generating, by the parser, an activation signal for at least one of the plurality of transducers within the normalizer; decoding the filtered input string, by the decoder, to produce an un-encoded filtered input string; activating each transducer of the plurality of transducers for which an activation signal has been generated; removing a field-specific obfuscation from the un-encoded filtered input string using the at least one activated transducer; forwarding the normalized un-encoded filtered input string to the search engine; generating a rule select signal, using the parser, in response to the selected portions of the input string; selecting a set of rules in the rules database memory device in response to the rule select signal; and loading the selected set of rules from the rules database memory device into the search engine; wherein each transducer of the plurality of transducers is configured to be activated or deactivated in response to a signal from the parser.

24. A method, performed by a content search system including a parser, a rules database memory device, a normalizer having a decoder and a plurality of transducers, and a search engine, for determining whether an input string matches one or more rules stored in the rules database, comprising: extracting selected portions of the input string, using the parser, to form a filtered input string; forwarding, by the parser, the filtered input string to the normalizer; generating, by the parser, an activation signal for at least one of the plurality of transducers within the normalizer; decoding the filtered input string, by the decoder, to produce an un-encoded filtered input string; activating each transducer of the plurality of transducers for which an activation signal has been generated; removing a field-specific obfuscation from the un-encoded filtered input string using the at least one activated transducer; forwarding the normalized un-encoded filtered input string to the search engine; generating a rule select signal, using the parser, in response to the selected portions of the input string; selecting a set of rules in the rules database memory device in response to the rule select signal; and loading the selected set of rules from the rules database memory device into the search engine; wherein each transducer of the plurality of transducers is configured to be activated or deactivated in response to a signal from the parser. 25. The method of claim 24 , further comprising: generating a trigger signal, using the parser, in response to the selected portions of the input string; and selectively enabling the search engine in response to the trigger signal.