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1. A system for retrieving and generating targeted information comprising: one or more processors; a matching unit stored on a memory and executable by the one or more processors, the matching unit receiving an input image, performing document recognition on the input image and producing recognized text; a first comparison engine coupled to the matching unit, the first comparison engine receiving the recognized text from the matching unit, receiving user profile information and generating a list of relevant topics based on the recognized text and the user profile information; a second comparison engine coupled to the matching unit, the second comparison engine receiving the recognized text from the matching unit, receiving targeted information and generating a list of relevant information; a first weight adjuster coupled to the first comparison engine, the first weight adjuster adjusting a weight of at least one of the relevant topics in the list of relevant topics using user context information, wherein adjusting the weight of the at least one of the relevant topics includes determining word relevancy by calculating a distance from a center of the input image outward using a distance measure; and a third comparison engine coupled to the first comparison engine and the second comparison engine, the third comparison engine generating a final list of targeted information by comparing the list of relevant topics to the list of relevant information.

1. A system for retrieving and generating targeted information comprising: one or more processors; a matching unit stored on a memory and executable by the one or more processors, the matching unit receiving an input image, performing document recognition on the input image and producing recognized text; a first comparison engine coupled to the matching unit, the first comparison engine receiving the recognized text from the matching unit, receiving user profile information and generating a list of relevant topics based on the recognized text and the user profile information; a second comparison engine coupled to the matching unit, the second comparison engine receiving the recognized text from the matching unit, receiving targeted information and generating a list of relevant information; a first weight adjuster coupled to the first comparison engine, the first weight adjuster adjusting a weight of at least one of the relevant topics in the list of relevant topics using user context information, wherein adjusting the weight of the at least one of the relevant topics includes determining word relevancy by calculating a distance from a center of the input image outward using a distance measure; and a third comparison engine coupled to the first comparison engine and the second comparison engine, the third comparison engine generating a final list of targeted information by comparing the list of relevant topics to the list of relevant information. 6. The system of claim 1 , further comprising a second weight adjuster coupled to the second comparison engine and the third comparison engine, the second weight adjuster adjusting a weight of the at least one piece of relevant information in the list of relevant information using user context information, the adjusting of the weight including determining a feature match between the user context information and the at least one piece of relevant information based on at least one of a proximity search and a time search.

1. A computer-implemented method comprising: receiving data encoding sounds produced by a human voice; extracting a monophonic melody line from an audio channel of the data encoding the sounds produced by the human voice; providing, to a recognizer that recognizes songs from sounds produced by a human voice, the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice; comparing, at the recognizer that recognizes songs from sounds produced by a human voice, the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice with one or more monophonic melody lines of candidate videos of a subset of a set of candidate videos that are each (i) identified as being associated with a particular song, and (ii) are classified as a cappella video recordings; determining, based on the comparison, that the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice matches one or more of the one or more monophonic melody lines of the candidate videos of the subset; and in response to determining that the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice matches one or more of the one or more monophonic melody lines of the candidate videos of the subset, providing an identifier of the particular song for output.

1. A computer-implemented method comprising: receiving data encoding sounds produced by a human voice; extracting a monophonic melody line from an audio channel of the data encoding the sounds produced by the human voice; providing, to a recognizer that recognizes songs from sounds produced by a human voice, the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice; comparing, at the recognizer that recognizes songs from sounds produced by a human voice, the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice with one or more monophonic melody lines of candidate videos of a subset of a set of candidate videos that are each (i) identified as being associated with a particular song, and (ii) are classified as a cappella video recordings; determining, based on the comparison, that the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice matches one or more of the one or more monophonic melody lines of the candidate videos of the subset; and in response to determining that the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice matches one or more of the one or more monophonic melody lines of the candidate videos of the subset, providing an identifier of the particular song for output. 2. The method of claim 1 , wherein comparing the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice with the one or more monophonic melody lines of the candidate videos of the subset comprises: selecting, from among a collection of videos, the set of candidate videos that are each (i) identified as being associated with the particular song, and (ii) are classified as a cappella video recordings; extracting, from each of the candidate videos of the set that (i) are identified as being associated with the particular song, and (ii) are classified as a cappella video recordings, a monophonic melody line from an audio channel of the candidate video; selecting, from among the set of candidate videos that are each (i) identified as being associated with the particular song, and (ii) are classified as a cappella video recordings, the subset of candidate videos based on a similarity of the monophonic melody lines of the candidate videos of the subset with each other; and providing, to the recognizer that recognizes songs from sounds produced by a human voice, one or more of the monophonic melody lines of the candidate videos of the subset.

1. A computer-implementable method for performing cognitive computing operations comprising: receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph, the data enriching performing sentiment analysis, geotagging and entity detection operations on the streams of data from the plurality of data sources, the processing being performed by a cognitive inference and learning system, the cognitive inference and learning system executing on a hardware processor of an information processing system and interacting with the plurality of data sources, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising a cognitive engine, the cognitive engine processing the streams of data from the plurality of data sources; incorporating enriched data resulting from the performed data enriching into the cognitive graph as nodes within the cognitive graph; defining a cognitive persona within the cognitive graph, the cognitive persona corresponding to an archetype user model, the defining comprising associating attributes with respective nodes of a set of nodes in the cognitive graph, links among the set of nodes being weighted to provide a weighted cognitive graph, weighting of the links representing a relevance between attributes associated with respective nodes; associating a user with the cognitive persona; and, performing a cognitive computing operation based upon the cognitive persona associated with the user, the cognitive computing operation comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources.

1. A computer-implementable method for performing cognitive computing operations comprising: receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph, the data enriching performing sentiment analysis, geotagging and entity detection operations on the streams of data from the plurality of data sources, the processing being performed by a cognitive inference and learning system, the cognitive inference and learning system executing on a hardware processor of an information processing system and interacting with the plurality of data sources, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising a cognitive engine, the cognitive engine processing the streams of data from the plurality of data sources; incorporating enriched data resulting from the performed data enriching into the cognitive graph as nodes within the cognitive graph; defining a cognitive persona within the cognitive graph, the cognitive persona corresponding to an archetype user model, the defining comprising associating attributes with respective nodes of a set of nodes in the cognitive graph, links among the set of nodes being weighted to provide a weighted cognitive graph, weighting of the links representing a relevance between attributes associated with respective nodes; associating a user with the cognitive persona; and, performing a cognitive computing operation based upon the cognitive persona associated with the user, the cognitive computing operation comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources. 2. The method of claim 1 , wherein: the cognitive persona represents a set of attributes, each of the set of attributes corresponding to a node of the set of nodes; and, an amount of weighting between nodes of the set of nodes corresponds to a degree of relevance between the persona and the attributes.

6. The process of claim 1 , further comprising the step of: periodically checking free space in said UDB and, if said free space is less than a predetermined amount, then removing from said UDB said words that have said frequency counts below a predetermined threshold.

6. The process of claim 1 , further comprising the step of: periodically checking free space in said UDB and, if said free space is less than a predetermined amount, then removing from said UDB said words that have said frequency counts below a predetermined threshold. 7. The process of claim 6 , wherein said removing step removes said user-defined words having said frequency counts below said predetermined threshold after removing other words having said frequency counts below said predetermined threshold.

13. The method of claim 11 , further comprising determining a frequency value associated with the classification based at least in part on keywords associated with the classification made by the predictive model.

13. The method of claim 11 , further comprising determining a frequency value associated with the classification based at least in part on keywords associated with the classification made by the predictive model. 15. The method of claim 13 , further comprising determining the reward based at least in part on the frequency value and the confidence value associated with the classification.

21. A non-transitory computer readable medium storing logic for auditing a plurality of transaction documents, the logic operable when executed to: transmit a query comprising at least one query criteria from a local computer associated with a user to a centrally located computer associated with a transaction management system; receive, from the centrally located computer, a plurality of transaction documents satisfying the at least one query criteria; before display of any one of the plurality of documents, pre-load the plurality of transaction documents in a temporary storage space that is located on the local computer; after each of the plurality of transaction documents are pre-loaded in the temporary storage space on the local computer, display, by the local computer, a first one of the plurality of transaction documents to the user; receive, by the local computer, a user input from the user; in response to receiving the user input, perform, by the local computer, at least one operation on a first one of the plurality of transaction documents stored in the temporary storage space that is located on the local computer; and automatically display, without further user input, a second one of the plurality of transaction documents to the user.

21. A non-transitory computer readable medium storing logic for auditing a plurality of transaction documents, the logic operable when executed to: transmit a query comprising at least one query criteria from a local computer associated with a user to a centrally located computer associated with a transaction management system; receive, from the centrally located computer, a plurality of transaction documents satisfying the at least one query criteria; before display of any one of the plurality of documents, pre-load the plurality of transaction documents in a temporary storage space that is located on the local computer; after each of the plurality of transaction documents are pre-loaded in the temporary storage space on the local computer, display, by the local computer, a first one of the plurality of transaction documents to the user; receive, by the local computer, a user input from the user; in response to receiving the user input, perform, by the local computer, at least one operation on a first one of the plurality of transaction documents stored in the temporary storage space that is located on the local computer; and automatically display, without further user input, a second one of the plurality of transaction documents to the user. 34. The non-transitory computer readable medium of claim 21 , wherein: the user input identifies the at least one operation to be performed on the first one of the plurality of transaction documents; and the second one of the plurality of transaction documents is displayed to the user in response to the user input identifying the at least one operation to be performed and in response to the performance of the operation but before receiving any further user input.

11. The system of claim 1 , further enables presenting two characters in each screen of said adaptable keyboard, wherein each character is associated with a different language, wherein each of said two characters is presented at a different side of said adaptable key, wherein said touch-sensing mechanism enables identifying touch areas, to allow determining the character of the language that was typed by the user, and wherein identifying a pressing movement in the area of the character of the other language enables automatically switching from the currently used language to the other.

11. The system of claim 1 , further enables presenting two characters in each screen of said adaptable keyboard, wherein each character is associated with a different language, wherein each of said two characters is presented at a different side of said adaptable key, wherein said touch-sensing mechanism enables identifying touch areas, to allow determining the character of the language that was typed by the user, and wherein identifying a pressing movement in the area of the character of the other language enables automatically switching from the currently used language to the other. 12. The system of claim 11 , wherein the two characters are presented upon each adaptable key in a manner that emphasizes the character of the currently used language.

14. An apparatus according to claim 11 wherein said master lexicon verification means comprises differential decoding means responsive to a differential coding of a first lexicon entry for generating a signal representative of a linguistic expression, said differential encoding being representative of a difference in character content between the linguistic expression represented in said first lexicon entry and a second linguistic expression represented in a second said lexicon entry.

14. An apparatus according to claim 11 wherein said master lexicon verification means comprises differential decoding means responsive to a differential coding of a first lexicon entry for generating a signal representative of a linguistic expression, said differential encoding being representative of a difference in character content between the linguistic expression represented in said first lexicon entry and a second linguistic expression represented in a second said lexicon entry. 15. An apparatus according to claim 14 wherein said differential decoding means comprises means responsive to at least one of i. a differential coding which coding is explicitly representative of an alphanumeric character of said first linguistic expression, and ii. a differential coding which is indirectly representative of a character sequence of said first linguistic expression, said character sequence being common to said first linguistic expression and a third linguistic expression represented in a third lexicon entry for generating signals representative of a character sequence of said first expression.

11. A communications system comprising: a speech interface for accessing a speech recognizer operable for receiving speech input during limited time recognition window, means for mapping available time of the recognition window to a spatial representation in animated form using one of a graphical modality, haptic modality or auditory modality.

11. A communications system comprising: a speech interface for accessing a speech recognizer operable for receiving speech input during limited time recognition window, means for mapping available time of the recognition window to a spatial representation in animated form using one of a graphical modality, haptic modality or auditory modality. 17. A system according to claim 11 wherein the means for mapping comprises a haptic interface and the spatial representation comprises an animated pattern of haptic stimulation.

1. A method for providing mixed reality contents for learning through a story-based virtual experience, comprising: capturing a user image of a user within an actual environment; setting an action zone within a virtual world in which a 3D image of the virtual world having the story is synthesized with the user image and setting a corner coordinate of the action zone as a reference point for the action zone within the 3D image of the virtual world; tracking a user position from the user image and calculating the tracked user position as four rectangular corner coordinates; converting the four rectangular corner coordinates into a 3D coordinate; matching the 3D coordinate to the corner coordinate of the action zone; and displaying a synthesized image of the user and the virtual world that is based on matching the 3D coordinate to the corner coordinate of the action zone.

1. A method for providing mixed reality contents for learning through a story-based virtual experience, comprising: capturing a user image of a user within an actual environment; setting an action zone within a virtual world in which a 3D image of the virtual world having the story is synthesized with the user image and setting a corner coordinate of the action zone as a reference point for the action zone within the 3D image of the virtual world; tracking a user position from the user image and calculating the tracked user position as four rectangular corner coordinates; converting the four rectangular corner coordinates into a 3D coordinate; matching the 3D coordinate to the corner coordinate of the action zone; and displaying a synthesized image of the user and the virtual world that is based on matching the 3D coordinate to the corner coordinate of the action zone. 4. The method of claim 1 , wherein matching the 3D coordinate to the corner coordinate of the action zone includes changing a position of the action zone over time as the position of the user changes over time.

4. A computer program product for creating a context-based graph-relational intersect derived (CB-GRID) database for associating a real entity graph node to a synthetic entity graph node in a database system, the computer program product comprising: a non-transitory computer readable storage medium; first program instructions to establish a real entity graph node, wherein the real entity graph node identifies a real entity; second program instructions to create and store a pointer in the real entity graph node, wherein the pointer points to a primary key in a first tuple that non-contextually describes the real entity; third program instructions to create a primary relational database, wherein the primary relational database comprises the first tuple that non-contextually describes the real entity, and wherein the first tuple contains the primary key; fourth program instructions to create a context relational database, wherein the context relational database comprises a second tuple that contains a foreign key that matches the primary key in the primary relational database, and wherein the second tuple dynamically describes a context of data in the first tuple; fifth program instructions to create a contextual entity relational database, wherein the contextual entity relational database comprises a third tuple that contains data from the first tuple and the second tuple, and wherein the third tuple comprises a contextual tuple key; sixth program instructions to create a synthetic entity graph node, wherein the synthetic entity graph node is linked to the contextual entity relational database by the contextual tuple key, wherein the synthetic entity graph node describes a synthetic entity that is described by data in the contextual entity relational database, and wherein the contextual entity relational database links the real entity graph node to the synthetic entity graph node, wherein the real entity is a physical machine, and wherein the synthetic entity graph node describes a software-modeled machine that is operating outside of nominal parameters; seventh program instructions to receive and store output data from a sensor on the physical machine stored in the first tuple; eighth program instructions to receive and store model type data describing a model type of the physical machine stored in the second tuple; and ninth program instructions to receive and store software-modeled machine descriptor data stored in the third tuple, wherein the contextual entity relational database links the physical machine to the software-modeled machine that is operating outside of the nominal parameters; and wherein the first, second, third, fourth, fifth, sixth, seventh, eighth, and ninth program instructions are stored on the non-transitory computer readable storage medium.

4. A computer program product for creating a context-based graph-relational intersect derived (CB-GRID) database for associating a real entity graph node to a synthetic entity graph node in a database system, the computer program product comprising: a non-transitory computer readable storage medium; first program instructions to establish a real entity graph node, wherein the real entity graph node identifies a real entity; second program instructions to create and store a pointer in the real entity graph node, wherein the pointer points to a primary key in a first tuple that non-contextually describes the real entity; third program instructions to create a primary relational database, wherein the primary relational database comprises the first tuple that non-contextually describes the real entity, and wherein the first tuple contains the primary key; fourth program instructions to create a context relational database, wherein the context relational database comprises a second tuple that contains a foreign key that matches the primary key in the primary relational database, and wherein the second tuple dynamically describes a context of data in the first tuple; fifth program instructions to create a contextual entity relational database, wherein the contextual entity relational database comprises a third tuple that contains data from the first tuple and the second tuple, and wherein the third tuple comprises a contextual tuple key; sixth program instructions to create a synthetic entity graph node, wherein the synthetic entity graph node is linked to the contextual entity relational database by the contextual tuple key, wherein the synthetic entity graph node describes a synthetic entity that is described by data in the contextual entity relational database, and wherein the contextual entity relational database links the real entity graph node to the synthetic entity graph node, wherein the real entity is a physical machine, and wherein the synthetic entity graph node describes a software-modeled machine that is operating outside of nominal parameters; seventh program instructions to receive and store output data from a sensor on the physical machine stored in the first tuple; eighth program instructions to receive and store model type data describing a model type of the physical machine stored in the second tuple; and ninth program instructions to receive and store software-modeled machine descriptor data stored in the third tuple, wherein the contextual entity relational database links the physical machine to the software-modeled machine that is operating outside of the nominal parameters; and wherein the first, second, third, fourth, fifth, sixth, seventh, eighth, and ninth program instructions are stored on the non-transitory computer readable storage medium. 7. The computer program product of claim 4 , wherein the real entity is a physical information technology (IT) system, wherein the synthetic entity graph node describes a software-modeled IT system that is operating outside of nominal parameters, and wherein the computer program product further comprises: tenth program instructions to receive and store output data from a sensor in the physical IT system stored in the first tuple; eleventh program instructions to receive and store environmental data describing an external physical environment of the physical IT system stored in the second tuple; and twelfth program instructions to receive and store software-modeled IT system descriptor data stored in the third tuple, wherein the contextual entity relational database links the physical IT system to the software-modeled IT system that is operating outside of the nominal parameters; and wherein the tenth, eleventh, and twelfth program instructions are stored on the non-transitory computer readable storage medium.

24. The invention of claim 23 wherein combining further comprises: adjusting the preselected period of time in accordance with a quality of the ranked search result set associated with the matching advertisements.

24. The invention of claim 23 wherein combining further comprises: adjusting the preselected period of time in accordance with a quality of the ranked search result set associated with the matching advertisements. 25. The invention of claim 24 wherein the quality is the quantity of the matching advertisements.

14. The system of claim 13 , wherein the one or more processors execute the program instructions further causing a machine to: query an analytic search results library for entries matching the received plurality of product feedback search parameters, wherein the analytic search results library is a knowledgebase of product feedback search results previously processed by the intelligent product feedback analytics tool; when matching entries are absent from the analytic search results library, request the plurality of product feedback search results for the plurality of product feedback search parameters from a content aggregator, wherein said content aggregator is capable of accessing data sources required by the intelligent product feedback analytics tool; and receive the plurality of product feedback search results from the content aggregator.

14. The system of claim 13 , wherein the one or more processors execute the program instructions further causing a machine to: query an analytic search results library for entries matching the received plurality of product feedback search parameters, wherein the analytic search results library is a knowledgebase of product feedback search results previously processed by the intelligent product feedback analytics tool; when matching entries are absent from the analytic search results library, request the plurality of product feedback search results for the plurality of product feedback search parameters from a content aggregator, wherein said content aggregator is capable of accessing data sources required by the intelligent product feedback analytics tool; and receive the plurality of product feedback search results from the content aggregator. 15. The system of claim 14 , wherein the one or more processors execute the program instructions further causing a machine to: prior to querying of the analytic search results library: ascertain an existence of a search profile for an originator of the plurality of product feedback search parameters, wherein the search profile is stored by the intelligent product feedback analytics tool; and when the search profile exists for the originator, apply applicable contents of said search profile to the plurality of product feedback search parameters, wherein said application modifies a value of at least one product feedback search parameter.

8. A computer-implemented method, comprising: acquiring a first image; transmitting information associated with the first image and an assistance information to a server, the server being associated with a first feature quantity dictionary; receiving a second feature quantity dictionary from the server in response to the transmission, the second feature quantity dictionary comprising less information than the first feature quantity dictionary; and identifying, using a processor, an object within the first image using the second feature quantity dictionary, wherein the second feature quantity dictionary is a filtered version of the first feature quantity dictionary that is stored on the server, and the second feature quantity dictionary represents a subset of the first feature quantity dictionary and contains only selected contents of the first feature quantity dictionary having a highest relation to the first information and satisfying a threshold criteria, and wherein an amount of contents selected that is from the first feature quantity dictionary as the subset forming the second feature quantity dictionary is based on a capability or processing ability of a device implementing the method, and the amount of contents selected is determined and set based on a capability information contained in the assistance information transmitted to the server.

8. A computer-implemented method, comprising: acquiring a first image; transmitting information associated with the first image and an assistance information to a server, the server being associated with a first feature quantity dictionary; receiving a second feature quantity dictionary from the server in response to the transmission, the second feature quantity dictionary comprising less information than the first feature quantity dictionary; and identifying, using a processor, an object within the first image using the second feature quantity dictionary, wherein the second feature quantity dictionary is a filtered version of the first feature quantity dictionary that is stored on the server, and the second feature quantity dictionary represents a subset of the first feature quantity dictionary and contains only selected contents of the first feature quantity dictionary having a highest relation to the first information and satisfying a threshold criteria, and wherein an amount of contents selected that is from the first feature quantity dictionary as the subset forming the second feature quantity dictionary is based on a capability or processing ability of a device implementing the method, and the amount of contents selected is determined and set based on a capability information contained in the assistance information transmitted to the server. 11. The computer-implemented method of claim 8 , wherein the capability information indicates at least one of a number of pieces of data processable by the device, a number of processor cores of the device, and a memory capacity of the device.

2. The computer system of claim 1 further comprising at least one editor means for manipulating said stored flexible representations of said provider information.

2. The computer system of claim 1 further comprising at least one editor means for manipulating said stored flexible representations of said provider information. 4. The computer system of claim 2 wherein said at least one editor means includes means for entering additional information into said at least one database.

17. The program product of claim 10 , wherein said method further comprises: constructing and storing a user group interest analytic model (UGIAM) by including UIAM items associated with multiple users who utilize said BI application and belong to a user group, said UIAM items based on initial visits of said multiple users to said BI application, wherein said multiple users includes said user, and wherein said UIAM items include said first set of one or more UIAM items; updating said UGIAM based on updates of said UIAM items associated with said multiple users belonging to said user group, said updates of said UIAM items based on subsequent visits of said multiple users to said BI application, wherein said updating said UGIAM includes adjusting scores of said UIAM items associated with said multiple users belonging to said user group; and automatically generating reports based on top K scores of said adjusted scores of said UIAM items associated with said multiple users belonging to said user group, wherein K is a positive integer.

17. The program product of claim 10 , wherein said method further comprises: constructing and storing a user group interest analytic model (UGIAM) by including UIAM items associated with multiple users who utilize said BI application and belong to a user group, said UIAM items based on initial visits of said multiple users to said BI application, wherein said multiple users includes said user, and wherein said UIAM items include said first set of one or more UIAM items; updating said UGIAM based on updates of said UIAM items associated with said multiple users belonging to said user group, said updates of said UIAM items based on subsequent visits of said multiple users to said BI application, wherein said updating said UGIAM includes adjusting scores of said UIAM items associated with said multiple users belonging to said user group; and automatically generating reports based on top K scores of said adjusted scores of said UIAM items associated with said multiple users belonging to said user group, wherein K is a positive integer. 18. The program product of claim 17 , wherein said method further comprises: determining matching levels of said UIAM items, each matching level indicating whether said an interest represented by a corresponding UIAM item of said UIAM items is common among interests of said multiple users belonging to said user group according to predefined criteria; and distributing said generated reports to one or more users of said multiple users, said distributing based on said matching levels.

14. The non-transitory computer readable medium as claimed in claim 13 wherein said threshold value may be dynamically reset based on a lifetime value of a relationship with said user.

14. The non-transitory computer readable medium as claimed in claim 13 wherein said threshold value may be dynamically reset based on a lifetime value of a relationship with said user. 15. The non-transitory computer readable medium as claimed in claim 14 wherein said instructions recalculate the log likelihood ratio for each turn in said interaction.

3. The method according to claim 2 , wherein said step of determining whether said evaluating sentences are supported by said associated feedbacks comprises the steps of: determining a complimentary/critical polarity of each of said evaluating sentences on said related product features; determining a complimentary/critical polarity of each of said feedbacks on said related product features; and determining whether said evaluating sentences are supported by said associated feedbacks by evaluating said complimentary/critical polarity of said evaluating sentence and said complimentary/critical polarity of said feedback.

3. The method according to claim 2 , wherein said step of determining whether said evaluating sentences are supported by said associated feedbacks comprises the steps of: determining a complimentary/critical polarity of each of said evaluating sentences on said related product features; determining a complimentary/critical polarity of each of said feedbacks on said related product features; and determining whether said evaluating sentences are supported by said associated feedbacks by evaluating said complimentary/critical polarity of said evaluating sentence and said complimentary/critical polarity of said feedback. 8. The method according to claim 3 , wherein said complimentary/critical polarity of each of said feedbacks on said related product features is determined by a sentiment analysis technique.

5. A computer system for operating a voice domain name network for use over a telephone network including: a voice domain computer having voice recognition capability to take a call from a first caller over telephone network and to recognize a name spoken in the call; a database connected to said computer, said database containing a plurality of voice domain names wherein each voice domain name in said database includes a corresponding Internet URL and telephone number associated with a registrant of the Internet URL, wherein the voice domain names in said database are entered into the database from voice information; a search engine configured to search for a specific voice domain name in the plurality of voice domain names and to search the Internet for an Internet URL in response to the call and to perform a telephone routine to connect the call to the telephone number associated with the registrant; means for offering to register the Internet URL by voice through the telephone network if said search engine fails to find the specific voice domain; means for generating a voice offer over the telephone network to register the Internet URL for the first caller if the Internet URL is found to be unregistered on the Internet and then registering the Internet URL as a domain name on the Internet and as the specific voice domain name in said database.

5. A computer system for operating a voice domain name network for use over a telephone network including: a voice domain computer having voice recognition capability to take a call from a first caller over telephone network and to recognize a name spoken in the call; a database connected to said computer, said database containing a plurality of voice domain names wherein each voice domain name in said database includes a corresponding Internet URL and telephone number associated with a registrant of the Internet URL, wherein the voice domain names in said database are entered into the database from voice information; a search engine configured to search for a specific voice domain name in the plurality of voice domain names and to search the Internet for an Internet URL in response to the call and to perform a telephone routine to connect the call to the telephone number associated with the registrant; means for offering to register the Internet URL by voice through the telephone network if said search engine fails to find the specific voice domain; means for generating a voice offer over the telephone network to register the Internet URL for the first caller if the Internet URL is found to be unregistered on the Internet and then registering the Internet URL as a domain name on the Internet and as the specific voice domain name in said database. 7. The system of claim 5 , further comprising means for offering to sell the specific voice domain to the first caller.

10. A method as described in claim 9 , wherein the credentials supplied by the accessory device comprises a resistor value of a resistor associated with the accessory device.

10. A method as described in claim 9 , wherein the credentials supplied by the accessory device comprises a resistor value of a resistor associated with the accessory device. 11. A method as described in claim 10 , wherein multiple different types of accessory devices connectable to the host computing device have different resistor values used to distinguish between the different types of accessory devices.

13. The computer program product of claim 12 , wherein the computer readable program code is configured to: display the data set along with the graphical statistical representation on the electronic display, wherein the second graphical user interface comprises a widget that is displayed within the first graphical user interface.

13. The computer program product of claim 12 , wherein the computer readable program code is configured to: display the data set along with the graphical statistical representation on the electronic display, wherein the second graphical user interface comprises a widget that is displayed within the first graphical user interface. 14. The computer program product of claim 13 , wherein the computer readable program code is configured to: display the filtered data set along with the graphical statistical representation and graphical elements.

7. The article of manufacture non-transitory computer readable storage medium according to claim 6 , further comprising instructions to obtain the semantic relationship which when executed by the computer further causes the computer to: retrieve a current state of the report and a metadata associated with the one or more existing report objects associated with the area and the new report object, the current state of the report including an information of the area, the information including an information of the one or more existing report objects associated with the area and the area type, the metadata including a semantic relationship between the one or more existing report objects and between the new report object and the one or more existing report objects; store the one or more existing report objects in a data hull; and query the metadata to obtain the semantic relationship between the new report object and the one or more existing report objects stored in the data hull.

7. The article of manufacture non-transitory computer readable storage medium according to claim 6 , further comprising instructions to obtain the semantic relationship which when executed by the computer further causes the computer to: retrieve a current state of the report and a metadata associated with the one or more existing report objects associated with the area and the new report object, the current state of the report including an information of the area, the information including an information of the one or more existing report objects associated with the area and the area type, the metadata including a semantic relationship between the one or more existing report objects and between the new report object and the one or more existing report objects; store the one or more existing report objects in a data hull; and query the metadata to obtain the semantic relationship between the new report object and the one or more existing report objects stored in the data hull. 10. The non-transitory computer readable storage medium according to claim 7 , wherein the area of the report has the sub-area, the sub-area having one or more existing report objects, the data hull of the sub-area storing the one or more existing report objects associated with the sub-area and the one or more existing report objects associated with the area.

8. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: determine a frequency of occurrence threshold based on an expected frequency of occurrence of syntax elements in a bit stream; categorize a plurality of syntax elements of video content into first and second categories based on the frequency of occurrence threshold, wherein syntax elements which occur greater than the frequency of occurrence threshold are categorized into the first category and syntax elements which occur less than the frequency of occurrence are categorized into the second category; entropy code symbols that correspond to the first category of syntax elements and that have been subjected to a context update; and entropy code symbols that correspond to the second category of syntax elements and that have bypassed context updating.

8. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: determine a frequency of occurrence threshold based on an expected frequency of occurrence of syntax elements in a bit stream; categorize a plurality of syntax elements of video content into first and second categories based on the frequency of occurrence threshold, wherein syntax elements which occur greater than the frequency of occurrence threshold are categorized into the first category and syntax elements which occur less than the frequency of occurrence are categorized into the second category; entropy code symbols that correspond to the first category of syntax elements and that have been subjected to a context update; and entropy code symbols that correspond to the second category of syntax elements and that have bypassed context updating. 9. An apparatus according to claim 8 wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to cause a categorization of the syntax elements to be signaled at a block, slice, picture or sequence level.

8. A pronunciation variation rule extraction method comprising: storing base form pronunciation data representing base form pronunciation of speech data; generating a sub word language model from said base form pronunciation data; recognizing said speech data by using said sub word language model; extracting a difference between a recognition result of said recognizing and said base form pronunciation data by comparing said recognition result and said base form pronunciation data; and controlling one weight value for said sub word language model, wherein said controlling includes outputting a plurality of said weight values, wherein said recognizing includes recognizing said speech data for each of said plurality of weight values, and wherein said controlling further includes determining whether or not said weight value should be updated, based on said difference when said difference is extracted.

8. A pronunciation variation rule extraction method comprising: storing base form pronunciation data representing base form pronunciation of speech data; generating a sub word language model from said base form pronunciation data; recognizing said speech data by using said sub word language model; extracting a difference between a recognition result of said recognizing and said base form pronunciation data by comparing said recognition result and said base form pronunciation data; and controlling one weight value for said sub word language model, wherein said controlling includes outputting a plurality of said weight values, wherein said recognizing includes recognizing said speech data for each of said plurality of weight values, and wherein said controlling further includes determining whether or not said weight value should be updated, based on said difference when said difference is extracted. 11. The pronunciation variation rule extraction method according to claim 8 , wherein said extracting includes: calculating said difference as an editing distance between said recognition result and said base form pronunciation data; and extracting as said difference, a pronunciation variation example including a letter string pair of different portions between said recognition result and said base form pronunciation data and said weight value of said sub word language model received upon acquisition of said recognition result.

1. A computer-implemented method for use with an annotation system: wherein the annotation system includes first data for annotating a manifestation of a first instance of a first XML document; wherein the first data comprises: a first XML document identifier for the first XML document; and first annotation data representing a first association between: (a) a first manifestation of first annotation content in connection with the manifestation of the first instance of the first XML document and (b) a manifestation of a first instance of a first target in the manifestation of the first instance of a first XML document; wherein at least one of the first annotation content and the first target is not text; wherein the first data is uniquely identified by a first Unique Annotation Link Identifier (UALI); wherein the first instance of the first XML document is served by a document system; wherein the annotation system is functionally independent of the document system, wherein the annotation system and the document system share no state by contract; wherein the document system is configured to respond to a request containing the first XML document identifier with a manifestation of a second instance of the first XML document; the method comprising: (A) receiving a first request containing the first UALI; (B) in response to the first request containing the first UALI, issuing a second request to the document system, wherein the second request contains the first XML document identifier; and (C) in response to the first request containing the first UALI, manifesting the first annotation data in connection with the manifestation of the second instance of the first XML document.

1. A computer-implemented method for use with an annotation system: wherein the annotation system includes first data for annotating a manifestation of a first instance of a first XML document; wherein the first data comprises: a first XML document identifier for the first XML document; and first annotation data representing a first association between: (a) a first manifestation of first annotation content in connection with the manifestation of the first instance of the first XML document and (b) a manifestation of a first instance of a first target in the manifestation of the first instance of a first XML document; wherein at least one of the first annotation content and the first target is not text; wherein the first data is uniquely identified by a first Unique Annotation Link Identifier (UALI); wherein the first instance of the first XML document is served by a document system; wherein the annotation system is functionally independent of the document system, wherein the annotation system and the document system share no state by contract; wherein the document system is configured to respond to a request containing the first XML document identifier with a manifestation of a second instance of the first XML document; the method comprising: (A) receiving a first request containing the first UALI; (B) in response to the first request containing the first UALI, issuing a second request to the document system, wherein the second request contains the first XML document identifier; and (C) in response to the first request containing the first UALI, manifesting the first annotation data in connection with the manifestation of the second instance of the first XML document. 7. The method of claim 1 , wherein (A) comprises: (A)(1) at a client device: (A)(1)(a) receiving input containing the first UALI; (A)(1)(b) transmitting a request containing the first UALI to an annotation server; (A)(2) at the annotation server: (A)(2)(a) requesting the second instance of the first XML document from the document server; (A)(2)(b) creating a composite of the first data and the second instance of the first XML document; (A)(2)(c) transmitting the composite to the client device; and (A) (3) at the client device: (A)(3)(a) manifesting the composite.

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

2. The method of claim 1 , further comprising: preparing, by a scripting framework, data associated with the exit node; and updating, by the scripting framework, any changed data resulting from execution of the code snippet. 4. The method of claim 2 , wherein the business object is associated with at least one of a business object service provider, a process agent, or a user interface.

13. The process according to claim 11, including the step of separating individual words with a separation symbol.

13. The process according to claim 11, including the step of separating individual words with a separation symbol. 14. The process according to claim 13, wherein the separation symbol comprises a slash ( ).

8. The method of claim 1 , further comprising, determining the common noise threshold by pruning a plurality of sub-libraries with a plurality of noise thresholds and selecting one of the plurality of noise thresholds as the common noise threshold based on at least one of: a) a number of bi-phrases remaining in the bi-phrase library after pruning, and b) a translation quality score computed on translations produced with a machine translation system which employs the bi-phrase library.

8. The method of claim 1 , further comprising, determining the common noise threshold by pruning a plurality of sub-libraries with a plurality of noise thresholds and selecting one of the plurality of noise thresholds as the common noise threshold based on at least one of: a) a number of bi-phrases remaining in the bi-phrase library after pruning, and b) a translation quality score computed on translations produced with a machine translation system which employs the bi-phrase library. 10. The method of claim 8 , wherein the second sub-library includes bi-phrases of a higher complexity than the first sub-library.

1. A method for building and executing natural language policies, the method comprising: creating a first function and a second function by writing software code; creating a domain specific rule that includes the first function, the second function, a logical connection between the first function and the second function, and a variable value; creating a natural language policy in response to a user selection of the domain specific rule and an option for the variable value, wherein the option limits the variable value, and wherein the natural language policy is the domain specific rule with the variable value set to the option; and executing the natural language policy on at least one computer system.

1. A method for building and executing natural language policies, the method comprising: creating a first function and a second function by writing software code; creating a domain specific rule that includes the first function, the second function, a logical connection between the first function and the second function, and a variable value; creating a natural language policy in response to a user selection of the domain specific rule and an option for the variable value, wherein the option limits the variable value, and wherein the natural language policy is the domain specific rule with the variable value set to the option; and executing the natural language policy on at least one computer system. 8. The method of claim 1 , wherein the option limits the variable value to one of a predetermined set of variables names.

13. A method comprising; providing a processor apparatus comprising a processor and a memory on a handheld electronic device; providing a first input device, wherein the first input device is communicatively coupled with the processor apparatus; generating first inputs upon activation of the first input device; providing an output apparatus communicatively coupled with the processor apparatus, the output apparatus including a display; generating a number of second inputs upon activation of a second input device; adapting the processor apparatus to receive the first inputs outputted from the first input device and the second inputs outputted from the second input device; providing a routine that is stored in a memory, the routine being executable on the processor upon detecting a number of the first inputs, the routine being adapted to: output to the display a number of primary output items; move an indicator through the number of primary output items on the display responsive to the received second inputs outputted from the second input device and generate secondary output items in response to the second inputs outputted from the second input device.

13. A method comprising; providing a processor apparatus comprising a processor and a memory on a handheld electronic device; providing a first input device, wherein the first input device is communicatively coupled with the processor apparatus; generating first inputs upon activation of the first input device; providing an output apparatus communicatively coupled with the processor apparatus, the output apparatus including a display; generating a number of second inputs upon activation of a second input device; adapting the processor apparatus to receive the first inputs outputted from the first input device and the second inputs outputted from the second input device; providing a routine that is stored in a memory, the routine being executable on the processor upon detecting a number of the first inputs, the routine being adapted to: output to the display a number of primary output items; move an indicator through the number of primary output items on the display responsive to the received second inputs outputted from the second input device and generate secondary output items in response to the second inputs outputted from the second input device. 17. The method of claim 13 , wherein the secondary output items comprise proposed linguistic elements.

15. A method for testing comprising: obtaining a testing grammar that describes a target set of test cases to be applied to a system under test, wherein the testing grammar identifies a set of parameters utilized in the generation of the target set of test cases; determining one or more attributes of the target set of test cases that would be generated based on the set of parameters identified by the testing grammar without generating the target set of test cases from the testing grammar; and generating a modified set of test cases from the testing grammar according to the determined one or more attributes of the target set of test cases.

15. A method for testing comprising: obtaining a testing grammar that describes a target set of test cases to be applied to a system under test, wherein the testing grammar identifies a set of parameters utilized in the generation of the target set of test cases; determining one or more attributes of the target set of test cases that would be generated based on the set of parameters identified by the testing grammar without generating the target set of test cases from the testing grammar; and generating a modified set of test cases from the testing grammar according to the determined one or more attributes of the target set of test cases. 16. The method as recited in claim 15 , wherein determining one or more attributes of the target set of test cases that would be generated based on the set of parameters identified by the testing grammar without generating the target set of test cases from the testing grammar includes searching the testing grammar for terminal symbols.

19. A method of performing audio data transcription utilizing a computer-processing system, the computer-processing system having a browser-based interface, the method comprising: obtaining first audio data from at least one audio data source; transcribing the first audio data based on a voice-independent model to generate text data; sending a message notification to an owner of the first audio data, the message notification including an address where the text data is accessible through the browser-based user interface; receiving corrections to the text data updating the voice-independent model based on the corrections; and transcribing second audio data with the voice-independent model as updated.

19. A method of performing audio data transcription utilizing a computer-processing system, the computer-processing system having a browser-based interface, the method comprising: obtaining first audio data from at least one audio data source; transcribing the first audio data based on a voice-independent model to generate text data; sending a message notification to an owner of the first audio data, the message notification including an address where the text data is accessible through the browser-based user interface; receiving corrections to the text data updating the voice-independent model based on the corrections; and transcribing second audio data with the voice-independent model as updated. 22. The method of claim 19 , wherein the address includes an active link selectable by the user to access the corrected text data through the browser-based interface.

7. A healthcare diagnosis training and evaluation system comprises: a virtual patient examination simulator interface module that renders a computer graphics animation of a virtual physical exam diagnostic device and a real-time motory change to an organ or a body part of an animated virtual patient when a user's diagnostic gesture pattern is drawn with a mouse or a finger on top of the animated virtual patient on a display screen, wherein the virtual patient examination simulator interface prompts the user to specify diagnostic prediction indicators for a diagnostics result before invoking the user's diagnostic gesture pattern to initiate a diagnostics test and determine correctness of the user's diagnostic indicators, wherein the real-time motory change to the organ or the body part and the diagnostics test is associated with an ocular motor examination, and wherein the user's diagnostic gesture pattern drawn on top of the animated virtual patient is an “H” pattern gestured over the animated virtual patient's eyes with the mouse or the finger; a test mode selection interface module that generates a user selection menu for a basic linear test mode, a beginner student test mode for dynamic differential diagnosis, and an advanced student test mode for dynamic differential diagnosis; a hypothesis selection and ranking interface module that allows a student to add, delete, rank, or modify a hypothesis in the differential diagnosis list during a health questioning, a simulated physical exam, a simulated medical test, and a simulated medical tests review, wherein the hypothesis selection and ranking interface module generates a differential diagnosis management menu to create or modify a differential diagnosis list for patient condition determination; a virtual patient health questioning interface module that generates a list of health questions selected by a student, an image of a simulated virtual patient, and simulated responses from the simulated virtual patient from the list of health questions, wherein the virtual patient health questioning interface module also incorporates the differential diagnosis management menu to allow the student to create or modify the differential diagnosis list for patient condition determination; a physical exam interface module that enables the student to perform the simulated physical exam on the simulated virtual patient, wherein the physical exam interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination during or after the simulated physical exam; a hypothesis and medical test association interface module that allows the student to associate the simulated medical test to a particular hypothesis in the differential diagnosis list, wherein the hypothesis and medical test association interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination; a medical test selection and differential diagnosis commitment interface module that requires the student to commit a current set of the differential diagnosis list for computerized evaluation, while also requiring the student to finalize simulated medical test selections for patient condition determination; a medical test results interface module that generates results of the simulated medical test, wherein the results are reviewed by the student for deducing a definitive diagnosis for evaluation; a treatment and management plan composition interface module that takes the student's input for a treatment and management plan; a student diagnosis evaluation interface module that evaluates the definitive diagnosis, the treatment and management plan, and associated diagnostic reasoning to generate a grading result based on correctness of the definitive diagnosis, the treatment and management plan, and the associated diagnostic reasoning from the student; and a central processing unit (CPU) and a memory unit of a computer system or another electronic device, wherein the CPU and the memory unit execute at least one of the virtual patient examination simulator interface module, the testing mode selection interface module, the hypothesis selection and ranking interface module, the virtual patient health questioning interface module, the physical exam interface module, the hypothesis and medical test association interface module, the medical test selection and differential diagnosis commitment interface module, the medical test results interface module, the treatment and management plan composition interface module, and the student diagnosis evaluation interface module.

7. A healthcare diagnosis training and evaluation system comprises: a virtual patient examination simulator interface module that renders a computer graphics animation of a virtual physical exam diagnostic device and a real-time motory change to an organ or a body part of an animated virtual patient when a user's diagnostic gesture pattern is drawn with a mouse or a finger on top of the animated virtual patient on a display screen, wherein the virtual patient examination simulator interface prompts the user to specify diagnostic prediction indicators for a diagnostics result before invoking the user's diagnostic gesture pattern to initiate a diagnostics test and determine correctness of the user's diagnostic indicators, wherein the real-time motory change to the organ or the body part and the diagnostics test is associated with an ocular motor examination, and wherein the user's diagnostic gesture pattern drawn on top of the animated virtual patient is an “H” pattern gestured over the animated virtual patient's eyes with the mouse or the finger; a test mode selection interface module that generates a user selection menu for a basic linear test mode, a beginner student test mode for dynamic differential diagnosis, and an advanced student test mode for dynamic differential diagnosis; a hypothesis selection and ranking interface module that allows a student to add, delete, rank, or modify a hypothesis in the differential diagnosis list during a health questioning, a simulated physical exam, a simulated medical test, and a simulated medical tests review, wherein the hypothesis selection and ranking interface module generates a differential diagnosis management menu to create or modify a differential diagnosis list for patient condition determination; a virtual patient health questioning interface module that generates a list of health questions selected by a student, an image of a simulated virtual patient, and simulated responses from the simulated virtual patient from the list of health questions, wherein the virtual patient health questioning interface module also incorporates the differential diagnosis management menu to allow the student to create or modify the differential diagnosis list for patient condition determination; a physical exam interface module that enables the student to perform the simulated physical exam on the simulated virtual patient, wherein the physical exam interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination during or after the simulated physical exam; a hypothesis and medical test association interface module that allows the student to associate the simulated medical test to a particular hypothesis in the differential diagnosis list, wherein the hypothesis and medical test association interface module also incorporates the differential diagnosis management menu to allow the student to revise the differential diagnosis list for patient condition determination; a medical test selection and differential diagnosis commitment interface module that requires the student to commit a current set of the differential diagnosis list for computerized evaluation, while also requiring the student to finalize simulated medical test selections for patient condition determination; a medical test results interface module that generates results of the simulated medical test, wherein the results are reviewed by the student for deducing a definitive diagnosis for evaluation; a treatment and management plan composition interface module that takes the student's input for a treatment and management plan; a student diagnosis evaluation interface module that evaluates the definitive diagnosis, the treatment and management plan, and associated diagnostic reasoning to generate a grading result based on correctness of the definitive diagnosis, the treatment and management plan, and the associated diagnostic reasoning from the student; and a central processing unit (CPU) and a memory unit of a computer system or another electronic device, wherein the CPU and the memory unit execute at least one of the virtual patient examination simulator interface module, the testing mode selection interface module, the hypothesis selection and ranking interface module, the virtual patient health questioning interface module, the physical exam interface module, the hypothesis and medical test association interface module, the medical test selection and differential diagnosis commitment interface module, the medical test results interface module, the treatment and management plan composition interface module, and the student diagnosis evaluation interface module. 8. The healthcare diagnosis training and evaluation system of claim 7 , further comprising a summary report generation interface module that generates a summary of the student's dynamic differential diagnosis reasoning and the grading result from the student diagnosis evaluation interface module.

6. A method, implemented at least partially by a handheld electronic book reader device, the method comprising: under control of one or more systems of the handheld electronic book reader device configured with executable instructions, generating a searchable item index of terms in an electronic item; and generating a searchable master index of terms in the electronic item and other electronic items in a collection of electronic items stored in memory of the handheld electronic book reader device, wherein the master index comprises a list of terms used in electronic items in the collection and, for each term, a reference to one or more item index entries for the respective term, and wherein each reference to an item index entry comprises an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item.

6. A method, implemented at least partially by a handheld electronic book reader device, the method comprising: under control of one or more systems of the handheld electronic book reader device configured with executable instructions, generating a searchable item index of terms in an electronic item; and generating a searchable master index of terms in the electronic item and other electronic items in a collection of electronic items stored in memory of the handheld electronic book reader device, wherein the master index comprises a list of terms used in electronic items in the collection and, for each term, a reference to one or more item index entries for the respective term, and wherein each reference to an item index entry comprises an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item. 7. The method of claim 6 , further comprising adding an electronic item to the collection of electronic items, generating a searchable item index of terms in the added electronic item, and updating the master index of terms to include terms in the added electronic item.

38. A computer-readable storage medium storing computer program instructions executable by a processor for constructing a search query to execute a search of a knowledge base, the computer program instruction comprising instructions for: parsing an input query received from a user conducting the search of the knowledge base into a plurality of sub-components; matching at least one of the plurality of sub-components to concepts represented as nodes in a semantic concept network of the knowledge base that provides an index of a plurality of documents that are target concepts linked to one or more nodes in the network; selecting from the knowledge base a set of matching concepts that match at least part of the sub-components; mapping the matching concepts to a structured set of criteria and criteria values that specify a set of constraints on and scoring parameters for the matching concepts, the criteria and criteria values being linked to nodes of the matching concepts; and executing the search of the database to retrieve a set of target concepts as search results constrained by the criteria according to a relationship between the search results and the matching concepts, the search results retrieved by matching nodes of the criteria and criteria values across the network to nodes of the target concepts using transitivity, wherein the search results are scored against each of the matched concepts and the search results are ranked based on the criteria values, the search results including one or more of the documents indexed.

38. A computer-readable storage medium storing computer program instructions executable by a processor for constructing a search query to execute a search of a knowledge base, the computer program instruction comprising instructions for: parsing an input query received from a user conducting the search of the knowledge base into a plurality of sub-components; matching at least one of the plurality of sub-components to concepts represented as nodes in a semantic concept network of the knowledge base that provides an index of a plurality of documents that are target concepts linked to one or more nodes in the network; selecting from the knowledge base a set of matching concepts that match at least part of the sub-components; mapping the matching concepts to a structured set of criteria and criteria values that specify a set of constraints on and scoring parameters for the matching concepts, the criteria and criteria values being linked to nodes of the matching concepts; and executing the search of the database to retrieve a set of target concepts as search results constrained by the criteria according to a relationship between the search results and the matching concepts, the search results retrieved by matching nodes of the criteria and criteria values across the network to nodes of the target concepts using transitivity, wherein the search results are scored against each of the matched concepts and the search results are ranked based on the criteria values, the search results including one or more of the documents indexed. 41. The computer program product of claim 38 , wherein parsing an input query further comprises using regular expressions to parse the input query into the sub-components that are matched to concepts.

13. The computer-implemented method of claim 8 , further comprising generating traceback data linking the frame to a frame of the frames before the frame.

13. The computer-implemented method of claim 8 , further comprising generating traceback data linking the frame to a frame of the frames before the frame. 14. The computer-implemented method of claim 13 , further comprising confirming, based at least partly on speech recognition processing using the traceback data, that the frame corresponds to the end of the keyword.

8. A system, comprising: at least one processor; a computer-readable storage medium coupled to the processor having instructions stored thereon which, when executed by the at least one processor, cause the at least one processor to perform operations comprising: presenting a user interface (UI) layout of a particular application UI for a first context in a primary display and at least one miniature UI layout of the same particular application UI for a plurality of contexts including the first context presented in the primary display in a secondary display area adjacent to the primary display, each UI layout including a plurality of UI elements, at least a portion of the UI elements included in the first context included in the plurality of contexts in the secondary display area; receiving, from a user, a selection of a particular UI layout from the at least one miniature UI layouts presented in the secondary display area, the particular UI layout associated with a second context different from the first context; presenting the particular UI layout for the selected second context in the primary display in response to the received selection from the user; identifying a modification to at least one UI element in the context presented in the primary display; determining at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area, including the first context, based on the modification of the at least one UI element in the second context in the primary display, wherein the determined at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area is based on a set of responsive UI design rules specific to each of the at least one contexts other than the context presented in the primary display, and wherein the at least one modification includes a first modification to at least one context other than to the context presented in the primary display different than the identified modification to the at least one UI element in the context presented in the primary display; automatically performing the at least one determined modification to the UI layout in at least one of the plural contexts in the secondary display area; and presenting an updated UI layout of the particular application UI for the context in the primary display and an updated miniature UI layout of the particular application UI for the at least one of the plural contexts in the secondary display area.

8. A system, comprising: at least one processor; a computer-readable storage medium coupled to the processor having instructions stored thereon which, when executed by the at least one processor, cause the at least one processor to perform operations comprising: presenting a user interface (UI) layout of a particular application UI for a first context in a primary display and at least one miniature UI layout of the same particular application UI for a plurality of contexts including the first context presented in the primary display in a secondary display area adjacent to the primary display, each UI layout including a plurality of UI elements, at least a portion of the UI elements included in the first context included in the plurality of contexts in the secondary display area; receiving, from a user, a selection of a particular UI layout from the at least one miniature UI layouts presented in the secondary display area, the particular UI layout associated with a second context different from the first context; presenting the particular UI layout for the selected second context in the primary display in response to the received selection from the user; identifying a modification to at least one UI element in the context presented in the primary display; determining at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area, including the first context, based on the modification of the at least one UI element in the second context in the primary display, wherein the determined at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area is based on a set of responsive UI design rules specific to each of the at least one contexts other than the context presented in the primary display, and wherein the at least one modification includes a first modification to at least one context other than to the context presented in the primary display different than the identified modification to the at least one UI element in the context presented in the primary display; automatically performing the at least one determined modification to the UI layout in at least one of the plural contexts in the secondary display area; and presenting an updated UI layout of the particular application UI for the context in the primary display and an updated miniature UI layout of the particular application UI for the at least one of the plural contexts in the secondary display area. 9. The system of claim 8 , wherein the primary display includes a responsive grid for designing UI layouts.

9. The method of claim 7 , wherein the electronic devices further includes a camera and the characteristics of the environment is based on visual input provided by the camera.

9. The method of claim 7 , wherein the electronic devices further includes a camera and the characteristics of the environment is based on visual input provided by the camera. 10. The method of claim 9 , wherein the characteristics of the environment indicate that the user is looking at or towards the electronic device.

17. A non-transitory computer readable storage medium encoded with one or more computer programs, the one or more computer programs comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a search query from a user, receiving search results responsive to the search query; providing search results for display to the user; receiving one or more user interactions associated with the search results; generating a search interaction score based on the one or more user interactions; determining that the search interaction score exceeds a threshold search interaction score; receiving a reminder event relating to the search query, wherein the reminder event is prompted by an occurrence other than re-submission of the search query by the user; and in response to determining that the search interaction score exceeds the threshold search interaction score and the reminder event, providing a notification to the user relating to the search query, wherein the notification invites the user to re-engage the search query and the search results, wherein the one or more user interactions associated with the search results are selected from a group including a selection of, an endorsement of, a sharing of, and a comment on an entry in the search results, and wherein the occurrence prompting the reminder event corresponds to one or more subsequent search queries, related to or matching the search query, reaching a threshold level of popularity.

17. A non-transitory computer readable storage medium encoded with one or more computer programs, the one or more computer programs comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a search query from a user, receiving search results responsive to the search query; providing search results for display to the user; receiving one or more user interactions associated with the search results; generating a search interaction score based on the one or more user interactions; determining that the search interaction score exceeds a threshold search interaction score; receiving a reminder event relating to the search query, wherein the reminder event is prompted by an occurrence other than re-submission of the search query by the user; and in response to determining that the search interaction score exceeds the threshold search interaction score and the reminder event, providing a notification to the user relating to the search query, wherein the notification invites the user to re-engage the search query and the search results, wherein the one or more user interactions associated with the search results are selected from a group including a selection of, an endorsement of, a sharing of, and a comment on an entry in the search results, and wherein the occurrence prompting the reminder event corresponds to one or more subsequent search queries, related to or matching the search query, reaching a threshold level of popularity. 22. The non-transitory computer readable storage medium of claim 17 , wherein the reminder event is prompted by a passage of a predetermined time in which the user has not re-submitted the search query.

1. A method for providing a translation service comprising: receiving a text string written in a source language from a member via a translation interface; receiving specialized data associated with: a domain from the member via the translation interface, and an indication of confidentiality; generating a translation memory using the received specialized data; generating a set of domain-specific parameters for statistical machine translation using the received specialized data; merging the generated set of domain-specific parameters with a generic set of statistical machine translation parameters; generating a domain-based translation engine based on the received specialized data and generic data, the domain-based translation engine associated with a source language, a target language, and the domain; training the domain-based translation engine using the translation memory; receiving a selection of the generated domain-based translation engine from a plurality of domain-based translation engines, the selection received from the member via the translation interface; translating the text string into the target language using, at least in part, the selected domain-based translation engine, the merged parameters and translation memory being used by the domain-based translation engine for translating the text string; and transmitting the translated text string to the member via the translation interface over a network.

1. A method for providing a translation service comprising: receiving a text string written in a source language from a member via a translation interface; receiving specialized data associated with: a domain from the member via the translation interface, and an indication of confidentiality; generating a translation memory using the received specialized data; generating a set of domain-specific parameters for statistical machine translation using the received specialized data; merging the generated set of domain-specific parameters with a generic set of statistical machine translation parameters; generating a domain-based translation engine based on the received specialized data and generic data, the domain-based translation engine associated with a source language, a target language, and the domain; training the domain-based translation engine using the translation memory; receiving a selection of the generated domain-based translation engine from a plurality of domain-based translation engines, the selection received from the member via the translation interface; translating the text string into the target language using, at least in part, the selected domain-based translation engine, the merged parameters and translation memory being used by the domain-based translation engine for translating the text string; and transmitting the translated text string to the member via the translation interface over a network. 3. The method of claim 1 , further comprising sending the generated translation memory to the member for storage.

19. The method of claim 18 further comprising: calculating an (i+1)-th index value for an (i+1)-th bin of the syntax element based on the variable and loading one of the context models for the (i+1)-th bin based on the (i+1)-th index value at an (i+2)-th clock cycle; decoding the (i+1)-th bin and updating the one context model related to the (i+1)-th bin at an (i+3)-th clock cycle; and storing a decoded bin value for the (i+1)-th bin and detecting whether the decoding process for the syntax element is completed at the (i+3)-th clock cycle.

19. The method of claim 18 further comprising: calculating an (i+1)-th index value for an (i+1)-th bin of the syntax element based on the variable and loading one of the context models for the (i+1)-th bin based on the (i+1)-th index value at an (i+2)-th clock cycle; decoding the (i+1)-th bin and updating the one context model related to the (i+1)-th bin at an (i+3)-th clock cycle; and storing a decoded bin value for the (i+1)-th bin and detecting whether the decoding process for the syntax element is completed at the (i+3)-th clock cycle. 20. The method of claim 19 further comprising: calculating an (i+2)-th index value for an (i+2)-th bin of the syntax element based on the variable and loading one of the context models for the (i+2)-th bin based on the (i+2)-th index value at an (i+3)-th clock cycle; decoding the (i+2)-th bin and updating the one context model related to the (i+2)-th bin at an (i+4)-th clock cycle; and storing a decoded bin value for the (i+2)-th bin and detecting whether the decoding process for the syntax element is completed at the (i+4)-th clock cycle.

1. A method for associating a content item with an event, comprising: receiving a content item; determining a location associated with the received content item using a processor; comparing the received content item with an existing event, wherein the existing event comprises a previously processed content item and a previously associated location, wherein comparing the received content item with the existing event comprises: determining a weighted overlap between the determined location and the previously associated location of the existing event; determining an indicia of relatedness between the received content item and the existing event, wherein the indicia of relatedness is not based on location; wherein the indicia of relatedness includes a time overlap between a time associated with the received content item and a time associated with the existing event; wherein the time overlap comprises being within a 24 hour window; and associating the received content item with the existing event based on the comparison, wherein the comparison also includes a threshold level of indicia of relatedness between the received content item and the existing event, and wherein the threshold level of indicia of relatedness required for the content item to be determined to be associated with the existing event increases as a degree of the weighted overlap between the determined location and the location previously associated with the existing event decreases.

1. A method for associating a content item with an event, comprising: receiving a content item; determining a location associated with the received content item using a processor; comparing the received content item with an existing event, wherein the existing event comprises a previously processed content item and a previously associated location, wherein comparing the received content item with the existing event comprises: determining a weighted overlap between the determined location and the previously associated location of the existing event; determining an indicia of relatedness between the received content item and the existing event, wherein the indicia of relatedness is not based on location; wherein the indicia of relatedness includes a time overlap between a time associated with the received content item and a time associated with the existing event; wherein the time overlap comprises being within a 24 hour window; and associating the received content item with the existing event based on the comparison, wherein the comparison also includes a threshold level of indicia of relatedness between the received content item and the existing event, and wherein the threshold level of indicia of relatedness required for the content item to be determined to be associated with the existing event increases as a degree of the weighted overlap between the determined location and the location previously associated with the existing event decreases. 4. The method as in claim 1 , wherein the indicia of relatedness comprises a unigram similarity.

1. A method performed by data processing apparatus, the method comprising: obtaining search query data, the search query data including a plurality of search queries submitted by users, each search query being associated with one or more responsive search results and user selection data for the one or more search results, wherein the user selection data identifies which search results were selected by users; obtaining a plurality of score improvement lists, each score improvement list being associated with a point value, each score improvement list being an ordered list of adjusters, wherein the adjusters are serially applied in order of the adjusters in the ordered list to initial scores of a group of search results to determine a final scoring of the search results; iteratively selecting pairs of score improvement lists from a pool of score improvement lists, the pool of score improvement lists including the plurality of score improvement lists; automatically for each selected pair: separately applying the ordered list of adjusters for each score improvement list included in the selected pair to one or more search results associated with a search query from the search query data, in response to the applying, identifying, for each score improvement list in the selected pair, respective ordered search results responsive to the search query, determining a winning and losing score improvement list in the selected pair from the search query data for the search query, and adjusting the point value associated with one or more of the winning score improvement list or the losing score improvement list; repeating testing for respective pairs of score improvement lists until ending criteria are reached; and selecting one or more score improvement lists based on the respective point values after the repeated testing.

1. A method performed by data processing apparatus, the method comprising: obtaining search query data, the search query data including a plurality of search queries submitted by users, each search query being associated with one or more responsive search results and user selection data for the one or more search results, wherein the user selection data identifies which search results were selected by users; obtaining a plurality of score improvement lists, each score improvement list being associated with a point value, each score improvement list being an ordered list of adjusters, wherein the adjusters are serially applied in order of the adjusters in the ordered list to initial scores of a group of search results to determine a final scoring of the search results; iteratively selecting pairs of score improvement lists from a pool of score improvement lists, the pool of score improvement lists including the plurality of score improvement lists; automatically for each selected pair: separately applying the ordered list of adjusters for each score improvement list included in the selected pair to one or more search results associated with a search query from the search query data, in response to the applying, identifying, for each score improvement list in the selected pair, respective ordered search results responsive to the search query, determining a winning and losing score improvement list in the selected pair from the search query data for the search query, and adjusting the point value associated with one or more of the winning score improvement list or the losing score improvement list; repeating testing for respective pairs of score improvement lists until ending criteria are reached; and selecting one or more score improvement lists based on the respective point values after the repeated testing. 2. The method of claim 1 , further comprising: selecting one or more score improvement lists associated with high point values relative to other score improvement lists; breeding the one or more score improvement lists associated with high point values with each other using genetic operators to create children score improvement lists; and adding the children score improvement lists to the pool of score improvement lists during the iterative selecting.

15. A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations, the operations comprising: outputting, via a presence-sensitive display device, a graphical keyboard comprising a plurality of keys associated with characters of a first alphabet of a first language, receiving a user input comprising one or more touches on the presence-sensitive display device, constructing a character lattice corresponding to the user input based on a spatial model, the character lattice being indicative of a spatial probability of one or more potential characters corresponding to the user input, constructing a token lattice corresponding to the user input based on the character lattice, the token lattice being indicative of a collective spatial probability of one or more potential tokens corresponding to the user input, wherein each of the one or more potential tokens corresponds to a character candidate string comprising a group of characters representing a semantic or phonetic unit, constructing a word lattice corresponding to the user input based on the token lattice and a language model, the word lattice being indicative of a probability of one or more potential words corresponding to the user input, the one or more potential words comprising one or more characters of a second alphabet of a second language, selecting at least one particular potential word of the one or more potential words based on the word lattice, and outputting, via the presence-sensitive display device, the at least one particular potential word.

15. A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations, the operations comprising: outputting, via a presence-sensitive display device, a graphical keyboard comprising a plurality of keys associated with characters of a first alphabet of a first language, receiving a user input comprising one or more touches on the presence-sensitive display device, constructing a character lattice corresponding to the user input based on a spatial model, the character lattice being indicative of a spatial probability of one or more potential characters corresponding to the user input, constructing a token lattice corresponding to the user input based on the character lattice, the token lattice being indicative of a collective spatial probability of one or more potential tokens corresponding to the user input, wherein each of the one or more potential tokens corresponds to a character candidate string comprising a group of characters representing a semantic or phonetic unit, constructing a word lattice corresponding to the user input based on the token lattice and a language model, the word lattice being indicative of a probability of one or more potential words corresponding to the user input, the one or more potential words comprising one or more characters of a second alphabet of a second language, selecting at least one particular potential word of the one or more potential words based on the word lattice, and outputting, via the presence-sensitive display device, the at least one particular potential word. 19. The computer-readable storage medium of claim 15 , wherein selecting the at least one particular potential word of the one or more potential words based on the word lattice comprises: comparing the probability of each particular word of the one or more potential words corresponding to the user input to a threshold; and selecting that particular word when its associated probability satisfies the threshold.

10. The machine-readable recording medium of claim 9 , wherein the feedback includes at least part of an n-best list of ASR matched entries associated with individual utterances processed during the communication session, each ASR matched entry having an associated likelihood score.

10. The machine-readable recording medium of claim 9 , wherein the feedback includes at least part of an n-best list of ASR matched entries associated with individual utterances processed during the communication session, each ASR matched entry having an associated likelihood score. 11. The machine-readable recording medium of claim 10 , further causing the machine to perform the steps of: identifying when one of the individual utterances has been incorrectly matched based upon the feedback; and responsive to said identifying step, adjusting at least one parameter within the identified phrase-based grammar so that the likelihood score associated with the topmost entry in the n-best list is decreased when the ASR computer program next processes an utterance similar to the incorrectly identified utterance in a session involving the identified phrase-based grammar.

1. A method performed by one or more processing devices, comprising: receiving a search query from a computing device associated with a user; performing a search of electronic content based on the search query; obtaining a search result based on the search of electronic content; obtaining configurable content that relates to the search query, the configurable content including user-independent content and a field that is configurable wherein the user-independent content comprises advertising and the field comprises a text field; identifying, based on the search query, user-specific content that describes the user and is responsive to the search query, wherein the user-specific content comprises information obtained from a social network of the user; configuring the field of the configurable content based on the user-specific content to thereby produce configured content comprising the user-independent content and the user-specific content; and outputting data corresponding to the search result and the configured content for use in generating an online publication containing the search result and the configured content.

1. A method performed by one or more processing devices, comprising: receiving a search query from a computing device associated with a user; performing a search of electronic content based on the search query; obtaining a search result based on the search of electronic content; obtaining configurable content that relates to the search query, the configurable content including user-independent content and a field that is configurable wherein the user-independent content comprises advertising and the field comprises a text field; identifying, based on the search query, user-specific content that describes the user and is responsive to the search query, wherein the user-specific content comprises information obtained from a social network of the user; configuring the field of the configurable content based on the user-specific content to thereby produce configured content comprising the user-independent content and the user-specific content; and outputting data corresponding to the search result and the configured content for use in generating an online publication containing the search result and the configured content. 9. The method of claim 1 , wherein the search result comprises at least one of an online publication and a set of search results comprised of links to online publications.

15. 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: receiving, from a first user, a request to identify an individual, the request including descriptive metadata associated with the individual and/or an event attended by the individual; accessing a plurality of stories stored in a datastore, each story of the plurality of stories previously submitted by a user and comprising respective intersection metadata indicating one or more of a time or location of the story; determining, using the descriptive metadata, one or more candidate individuals included in respective stories having intersection metadata corresponding to at least a portion of the descriptive metadata; providing, to the first user, indications of the one or more candidate individuals; receiving, from the first user, a selection of a particular candidate individual as the individual; and establishing respective user introductions between the first user and the particular candidate individual.

15. 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: receiving, from a first user, a request to identify an individual, the request including descriptive metadata associated with the individual and/or an event attended by the individual; accessing a plurality of stories stored in a datastore, each story of the plurality of stories previously submitted by a user and comprising respective intersection metadata indicating one or more of a time or location of the story; determining, using the descriptive metadata, one or more candidate individuals included in respective stories having intersection metadata corresponding to at least a portion of the descriptive metadata; providing, to the first user, indications of the one or more candidate individuals; receiving, from the first user, a selection of a particular candidate individual as the individual; and establishing respective user introductions between the first user and the particular candidate individual. 20. The system of claim 15 , wherein establishing respective user introductions between the first user and the particular candidate individual comprises: providing, for presentation to the individual, information describing the descriptive metadata included in the request, and an option to approve the user introduction; receiving information identifying that the individual approved the user introduction; in response to receiving the information, providing, for presentation to the first user, a photo lineup of disparate users including the individual; and receiving a selection of the individual in the photo lineup, and providing user introductions to the first user and the individual, wherein the user introductions include user profile information associated with the first user and the individual.

13. A system comprising: a computer memory having stored thereon the following components executable by a processor; means for receiving an input, the input comprises visual data and at least one of text or audio data, wherein the visual data is from an image file; means for extracting a plurality of features from the input; means for utilizing a language parser, a speech recognition component or a pattern recognition component to extract the plurality of features, the pattern recognition component extracting the features of the image file, the features comprising physical attributes that are visually identifiable in the image file; means for generating a search query based at least in part upon a subset of the plurality of features; means for collecting and indexing search-related information across a plurality of dimensions, and building an index based upon features associated with the input; means for automatically and dynamically extracting features from searchable items and making the features available for search based upon a particular query or set of queries; means for learning, based on context information, historical data, or user feedback, what results are desired in view of a determined and inferred query, as well as how the results should be rendered; and means for generating results that include a combination of text, visual or audible data.

13. A system comprising: a computer memory having stored thereon the following components executable by a processor; means for receiving an input, the input comprises visual data and at least one of text or audio data, wherein the visual data is from an image file; means for extracting a plurality of features from the input; means for utilizing a language parser, a speech recognition component or a pattern recognition component to extract the plurality of features, the pattern recognition component extracting the features of the image file, the features comprising physical attributes that are visually identifiable in the image file; means for generating a search query based at least in part upon a subset of the plurality of features; means for collecting and indexing search-related information across a plurality of dimensions, and building an index based upon features associated with the input; means for automatically and dynamically extracting features from searchable items and making the features available for search based upon a particular query or set of queries; means for learning, based on context information, historical data, or user feedback, what results are desired in view of a determined and inferred query, as well as how the results should be rendered; and means for generating results that include a combination of text, visual or audible data. 18. The system of claim 13 , further comprising: means for retrieving a plurality of results based upon the search query; and means for filtering a subset of the plurality of results in accordance with at least one of a user context, a user preference, a relevancy factor with respect to the input or a device context.

1. A method comprising: receiving, over a network from a user, a network search query comprising at least one token; selecting, using a computing device, a plurality of suggested search terms from a suggested search term database that match the network search query, each of the plurality of suggested search terms being assigned to one of a plurality of categories; ranking, using the computing device, the plurality of suggested search terms within each of the plurality of categories; determining, using the computing device, a number of suggested search terms to be returned to the user for each of the plurality of categories, the determined number of suggested search terms returned to the user being equal to a ratio of the number of suggested search terms in the respective category to a total number of suggested search terms multiplied by a total number of displayed search terms, such that a respective timestamp for each category is calculated dependent upon each category type and is associated with a suggested search term in a category, the timestamp corresponding to a respective end time, such that search terms having a respective timestamp less than the current time are not selected; and creating, using the computing device, a consolidated result set by adding, for each of the plurality of categories, the top ranked suggested search terms in the respective category to the consolidated result set.

1. A method comprising: receiving, over a network from a user, a network search query comprising at least one token; selecting, using a computing device, a plurality of suggested search terms from a suggested search term database that match the network search query, each of the plurality of suggested search terms being assigned to one of a plurality of categories; ranking, using the computing device, the plurality of suggested search terms within each of the plurality of categories; determining, using the computing device, a number of suggested search terms to be returned to the user for each of the plurality of categories, the determined number of suggested search terms returned to the user being equal to a ratio of the number of suggested search terms in the respective category to a total number of suggested search terms multiplied by a total number of displayed search terms, such that a respective timestamp for each category is calculated dependent upon each category type and is associated with a suggested search term in a category, the timestamp corresponding to a respective end time, such that search terms having a respective timestamp less than the current time are not selected; and creating, using the computing device, a consolidated result set by adding, for each of the plurality of categories, the top ranked suggested search terms in the respective category to the consolidated result set. 8. The method of claim 1 , such that where the respective end time relates to a program title, the timestamp is equivalent to a last end time for the program scheduled on a channel.

6. A system for vocalizing a digital work of literature, comprising: a computer having a processor; and a tangible, computer-readable storage memory device encoding program instructions for causing the processor to perform operations comprising: analyzing a first digital work of literature using natural language processing to identify speaking character voice characteristics associated with context of each quote as extracted from the first work of literature; converting the character voice characteristics to audio metadata to control text-to-speech audio synthesis for each quote; transforming the audio metadata into text-to-speech engine commands, wherein each quote is associated with audio synthesis control parameters for rendering the corresponding character voice characteristics according to the context of the quotes in the first work of literature; and inputting the commands to a text-to-speech engine to cause vocalization of the first work of literature, wherein spoken quotes by characters are vocalized according to the words of each quote, character voice characteristics corresponding to each quote, and context corresponding to each quote.

6. A system for vocalizing a digital work of literature, comprising: a computer having a processor; and a tangible, computer-readable storage memory device encoding program instructions for causing the processor to perform operations comprising: analyzing a first digital work of literature using natural language processing to identify speaking character voice characteristics associated with context of each quote as extracted from the first work of literature; converting the character voice characteristics to audio metadata to control text-to-speech audio synthesis for each quote; transforming the audio metadata into text-to-speech engine commands, wherein each quote is associated with audio synthesis control parameters for rendering the corresponding character voice characteristics according to the context of the quotes in the first work of literature; and inputting the commands to a text-to-speech engine to cause vocalization of the first work of literature, wherein spoken quotes by characters are vocalized according to the words of each quote, character voice characteristics corresponding to each quote, and context corresponding to each quote. 7. The system as set forth in claim 6 wherein the program instructions further comprise instructions for inferring a narrator character for vocalization of text from the first digital work of literature which are not drawn from a character quote.

1. A computer-implemented method for modifying an existing XML schema in a database without modifying existing data that conforms to the existing XML schema in the database, the method comprising: storing data from a set of XML documents in base database structures in a database according to an XML schema, wherein the XML schema defines an XML structure for said set of XML documents; after storing the data from the set of XML documents in the base database structures, receiving a request to make one or more changes to the schema; determining that the schema, if modified by the one or more changes, would be compatible with the stored data; and wherein the step of determining that the schema, if modified by the one or more changes, would be compatible with the stored data comprises one or more of: (a) determining that the one or more changes comprise an addition of a new element to the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to add the new element; (b) determining that the one or more changes comprise a removal of an element from the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to remove the element; or (c) determining that the one or more changes affect the ordering of elements within the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to affect the ordering of elements within the schema; and in response to determining that the schema, if modified by the one or more changes, would be compatible with the stored data, modifying the base database structures in the database to reflect the changes to the schema without modifying the data from the set of XML documents that is stored in the base database structures; wherein the method is performed by one or more computing devices.

1. A computer-implemented method for modifying an existing XML schema in a database without modifying existing data that conforms to the existing XML schema in the database, the method comprising: storing data from a set of XML documents in base database structures in a database according to an XML schema, wherein the XML schema defines an XML structure for said set of XML documents; after storing the data from the set of XML documents in the base database structures, receiving a request to make one or more changes to the schema; determining that the schema, if modified by the one or more changes, would be compatible with the stored data; and wherein the step of determining that the schema, if modified by the one or more changes, would be compatible with the stored data comprises one or more of: (a) determining that the one or more changes comprise an addition of a new element to the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to add the new element; (b) determining that the one or more changes comprise a removal of an element from the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to remove the element; or (c) determining that the one or more changes affect the ordering of elements within the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to affect the ordering of elements within the schema; and in response to determining that the schema, if modified by the one or more changes, would be compatible with the stored data, modifying the base database structures in the database to reflect the changes to the schema without modifying the data from the set of XML documents that is stored in the base database structures; wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein receiving the request to make one or more changes to the schema includes receiving a request to add a new element to the schema, and wherein the step of determining that the schema, if modified by the one or more changes, would be compatible with the stored data comprises (a) determining that the one or more changes comprise an addition of the new element to the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to add the new element.

11. A computer apparatus to redirect graph queries, the computer apparatus comprising: processing instructions that direct a computing system, when executed by the computing system, to: identify a relational data query; identify whether at least one previously generated graph in a group of one or more previously generated graphs relates to the relational data query based on similarity data, the at least one previously generated graph generated prior to identifying the relational data query, and wherein the similarity data comprises at least a time stamp assessed to each graph in the group of one or more previously generated graphs at generation, and wherein identifying whether at least one previously generated graph relates to the relational data query based on the similarity data comprises identifying whether at least one previously generated graph was generated within a timing window based on the time stamp assessed to each graph in the group of one or more previously generated graphs at generation; in response to identifying that at least one previously generated graph relates to the relational data query, direct the relational data query to the at least one previously generated graph; respond to the relational data query via the at least one previously generated graph; and one or more non-transitory computer readable media that store the processing instruction.

11. A computer apparatus to redirect graph queries, the computer apparatus comprising: processing instructions that direct a computing system, when executed by the computing system, to: identify a relational data query; identify whether at least one previously generated graph in a group of one or more previously generated graphs relates to the relational data query based on similarity data, the at least one previously generated graph generated prior to identifying the relational data query, and wherein the similarity data comprises at least a time stamp assessed to each graph in the group of one or more previously generated graphs at generation, and wherein identifying whether at least one previously generated graph relates to the relational data query based on the similarity data comprises identifying whether at least one previously generated graph was generated within a timing window based on the time stamp assessed to each graph in the group of one or more previously generated graphs at generation; in response to identifying that at least one previously generated graph relates to the relational data query, direct the relational data query to the at least one previously generated graph; respond to the relational data query via the at least one previously generated graph; and one or more non-transitory computer readable media that store the processing instruction. 17. The computer apparatus of claim 11 wherein the processing instructions to identify whether at least one previously generated graph in the group of one or more previously generated graphs relates to the relational data query based on the similarity data further direct the computing system to identify whether at least one previously generated graph in the group of one or more previously generated graphs includes a required dataset to respond to the relational data query.

10. A method for implementation by one or more data processors comprising: accepting a selection of a destination document on a client device; converting the destination document into a destination document tree hierarchy; flattening the destination document tree hierarchy into a destination document hash table, comprising a set of destination document keys and a set of destination document values; retrieving the set of destination document keys from the client device; retrieving a source document, wherein the source document is a second version of the destination document, from a server device; converting the source document into a source document tree hierarchy; flattening the source document tree hierarchy into a source document hash table, comprising a set of source document key-value pairs; identifying a source document key-value pair, comprising a key and a value, wherein the key is not in the set of destination document keys; adding the source document key-value to a changelist; identifying a destination document key, wherein the destination document key is not a key in a key-value pair in the set of source document key-value pairs; and adding the destination document key to the changelist; and sending the changelist to the client device.

10. A method for implementation by one or more data processors comprising: accepting a selection of a destination document on a client device; converting the destination document into a destination document tree hierarchy; flattening the destination document tree hierarchy into a destination document hash table, comprising a set of destination document keys and a set of destination document values; retrieving the set of destination document keys from the client device; retrieving a source document, wherein the source document is a second version of the destination document, from a server device; converting the source document into a source document tree hierarchy; flattening the source document tree hierarchy into a source document hash table, comprising a set of source document key-value pairs; identifying a source document key-value pair, comprising a key and a value, wherein the key is not in the set of destination document keys; adding the source document key-value to a changelist; identifying a destination document key, wherein the destination document key is not a key in a key-value pair in the set of source document key-value pairs; and adding the destination document key to the changelist; and sending the changelist to the client device. 17. The method of claim 10 , wherein a document tree hierarchy is a generic document representation.

14. A computer-implemented system for providing annotated electronic documents, the annotations which are to be applied to the documents being stored in a first data storage, the documents being stored in a second data storage, the first data storage and the second data storage being at least one of physically separate and logically separate, said system comprising: (A) at least one merge component, configured, to, responsive to a request from the user to retrieve the at least one document: retrieve the at least one document from a second data storage as document data, retrieve at least one annotation to be applied to said at least one document from a first data storage as annotation data, said document data including at least one element corresponding to a location of the at least one annotation within said document, wherein the annotation data is image data or text, wherein each annotation can be different from every other annotation; and combine the document data and the annotation data to form a unitary single logical document displaying the annotation embedded seamlessly in the document data at the location; (B) at least one split component complementary to the merge component, the split component is configured to, responsive to a request from the user to store the document: extract the annotation data and the document data from the single logical document, update the at least one annotation in the first data storage from the extracted annotation data, and to update the at least one document in the second data storage from the extracted document data; and (C) at least one version component, configured to at least one of manage a history of changes and to maintain a separate version for the document data and the annotation data to be applied thereto, wherein the annotation data indicates a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by an XML data schema.

14. A computer-implemented system for providing annotated electronic documents, the annotations which are to be applied to the documents being stored in a first data storage, the documents being stored in a second data storage, the first data storage and the second data storage being at least one of physically separate and logically separate, said system comprising: (A) at least one merge component, configured, to, responsive to a request from the user to retrieve the at least one document: retrieve the at least one document from a second data storage as document data, retrieve at least one annotation to be applied to said at least one document from a first data storage as annotation data, said document data including at least one element corresponding to a location of the at least one annotation within said document, wherein the annotation data is image data or text, wherein each annotation can be different from every other annotation; and combine the document data and the annotation data to form a unitary single logical document displaying the annotation embedded seamlessly in the document data at the location; (B) at least one split component complementary to the merge component, the split component is configured to, responsive to a request from the user to store the document: extract the annotation data and the document data from the single logical document, update the at least one annotation in the first data storage from the extracted annotation data, and to update the at least one document in the second data storage from the extracted document data; and (C) at least one version component, configured to at least one of manage a history of changes and to maintain a separate version for the document data and the annotation data to be applied thereto, wherein the annotation data indicates a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by an XML data schema. 16. The system of claim 14 , further comprising a schema configured to identify at least one tag in the at least one element, and logic to determine tags for at least one of the document data, the annotation data, and the at least one marked-up representation.

1. A method of adapting a speech system of a vehicle, comprising: logging context data from the vehicle; logging speech data from the speech system; processing the context data from the vehicle to determine a pattern; processing the speech data to determine an interaction behavior of a user; processing the pattern with the speech data to determine a relationship between the pattern and the interaction behavior of the user; and selectively updating a profile of the user of the speech system based on the pattern and the relationship.

1. A method of adapting a speech system of a vehicle, comprising: logging context data from the vehicle; logging speech data from the speech system; processing the context data from the vehicle to determine a pattern; processing the speech data to determine an interaction behavior of a user; processing the pattern with the speech data to determine a relationship between the pattern and the interaction behavior of the user; and selectively updating a profile of the user of the speech system based on the pattern and the relationship. 4. The method of claim 1 wherein the selectively updating comprises selectively updating a prompt preference of the profile based on the pattern.

1. A system for an interactive query performed using digital hardware devices, comprising: a first input module capable of receiving input for creating a simulated personality for a first user; an expert system capable of creating and storing the simulated personality; an output module for presenting the simulated personality to a second user; an interactive query module capable of allowing the second user to communicate with the simulated personality of the first user; wherein the first input module comprises an interactive question and answer module for receiving input regarding personality traits of the first user; wherein the input module is further configured for receiving input for creating plurality of simulated personalities for the first user, each of the plurality of simulated personalities relating to a personality of the user at a time t n ; wherein the interactive query module is further configured for allowing the second user to select which of the simulated personalities of the first user with which to communicate; and wherein each time t n represents different age of the first user.

1. A system for an interactive query performed using digital hardware devices, comprising: a first input module capable of receiving input for creating a simulated personality for a first user; an expert system capable of creating and storing the simulated personality; an output module for presenting the simulated personality to a second user; an interactive query module capable of allowing the second user to communicate with the simulated personality of the first user; wherein the first input module comprises an interactive question and answer module for receiving input regarding personality traits of the first user; wherein the input module is further configured for receiving input for creating plurality of simulated personalities for the first user, each of the plurality of simulated personalities relating to a personality of the user at a time t n ; wherein the interactive query module is further configured for allowing the second user to select which of the simulated personalities of the first user with which to communicate; and wherein each time t n represents different age of the first user. 7. The system of claim 1 , wherein the second user comprises a potential employer of the first user.

13. A system comprising: a preprocessor to extract macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define parse nodes utilized by the CLI parser to analyze whether one or more CLI commands input to a CLI prompt have a proper CLI syntax; means for generating a parse graph from the macroinstructions, wherein the parse graph includes a representation of the parse nodes defined by the macroinstructions; means for hiding selected information contained within the parse nodes to create condensed parse nodes, wherein the hiding prevents further processing of the selected information; means for simplifying selected complex patterns in the parse graph to create simplified parse graph patterns; means for creating branches on an AND/OR command tree from the parse nodes, the condensed parse nodes, and the simplified parse graph patterns; and means for creating an exportable representation of the AND/OR command tree.

13. A system comprising: a preprocessor to extract macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define parse nodes utilized by the CLI parser to analyze whether one or more CLI commands input to a CLI prompt have a proper CLI syntax; means for generating a parse graph from the macroinstructions, wherein the parse graph includes a representation of the parse nodes defined by the macroinstructions; means for hiding selected information contained within the parse nodes to create condensed parse nodes, wherein the hiding prevents further processing of the selected information; means for simplifying selected complex patterns in the parse graph to create simplified parse graph patterns; means for creating branches on an AND/OR command tree from the parse nodes, the condensed parse nodes, and the simplified parse graph patterns; and means for creating an exportable representation of the AND/OR command tree. 17. The system of claim 13 further comprising means for collecting the parse nodes that terminate in a common end of line.

4. A robot controller configured to control a movement of a robot comprising an arm and a tool attached to a tip end of the arm, the tool configured to be replaced by a tool changer disposed near the robot, the robot controller being connected to a teaching information database and an interface device, the robot controller comprising a storage device configured to store teaching information, including tool information which indicates a kind of the tool, for regulating a movement of the robot provided in a work facility, the teaching information database being data-communicably connected to each of one or more of the work facilities and storing a plurality of types of the teaching information associated with work information including at least usage information of the robot, the interface device being configured to receive an input of search condition information related to a usage of the robot, to search teaching information relevant to the search condition information inputted among the plurality of types of teaching information stored in the teaching information database, to receive a selection of desired teaching information among one or more sets of the teaching information hit in the search, to receive an input of the teaching information including the tool information when there is no teaching information hit in the search, and to transfer the teaching information input from the work facility to the teaching information database in association with the work information of the robot configured to move based on the teaching information, the robot controller being configured to control the movement including a replacement movement of the tool of the robot based on the teaching information selected by the interface device and transferred from the teaching information database to the storage device.

4. A robot controller configured to control a movement of a robot comprising an arm and a tool attached to a tip end of the arm, the tool configured to be replaced by a tool changer disposed near the robot, the robot controller being connected to a teaching information database and an interface device, the robot controller comprising a storage device configured to store teaching information, including tool information which indicates a kind of the tool, for regulating a movement of the robot provided in a work facility, the teaching information database being data-communicably connected to each of one or more of the work facilities and storing a plurality of types of the teaching information associated with work information including at least usage information of the robot, the interface device being configured to receive an input of search condition information related to a usage of the robot, to search teaching information relevant to the search condition information inputted among the plurality of types of teaching information stored in the teaching information database, to receive a selection of desired teaching information among one or more sets of the teaching information hit in the search, to receive an input of the teaching information including the tool information when there is no teaching information hit in the search, and to transfer the teaching information input from the work facility to the teaching information database in association with the work information of the robot configured to move based on the teaching information, the robot controller being configured to control the movement including a replacement movement of the tool of the robot based on the teaching information selected by the interface device and transferred from the teaching information database to the storage device. 7. The robot controller according to claim 4 , wherein the interface device is configured to cause a display to display a request for the input of the teaching information when there is no teaching information hit in the search in response to a determination that no teaching information is hit in the search.

7. A computer-implemented method for generating rules for an application, the method comprising: generating a graphical user interface with a processor for creation of a navigation rule, the navigation rule indicative of where to navigate when leaving a page in the application; receiving an expression parameter, a logical operator, and at least one expression parameter value with the processor from the graphical user interface in response to user input entered through the graphical user interface, the expression parameter identifying a question, the at least one expression parameter value including at least one potential answer to the question, wherein the expression parameter and the at least one expression parameter value are operands of the logical operator; generating the navigation rule with the processor, the navigation rule including a combination of a first evaluative expression and a second evaluative expression, the first evaluative expression comprising the expression parameter, the operator, and the at least one expression parameter value; storing the first and second evaluative expressions in a database; receiving an answer to the question with the processor from user input; evaluating the first and second evaluative expressions retrieved from the database at runtime with the processor, the expression parameter set to the answer in the evaluation of the first evaluative expression; and determining a next page with the processor when navigating away from the page based on the evaluation of the first and second evaluative expressions of the navigation rule.

7. A computer-implemented method for generating rules for an application, the method comprising: generating a graphical user interface with a processor for creation of a navigation rule, the navigation rule indicative of where to navigate when leaving a page in the application; receiving an expression parameter, a logical operator, and at least one expression parameter value with the processor from the graphical user interface in response to user input entered through the graphical user interface, the expression parameter identifying a question, the at least one expression parameter value including at least one potential answer to the question, wherein the expression parameter and the at least one expression parameter value are operands of the logical operator; generating the navigation rule with the processor, the navigation rule including a combination of a first evaluative expression and a second evaluative expression, the first evaluative expression comprising the expression parameter, the operator, and the at least one expression parameter value; storing the first and second evaluative expressions in a database; receiving an answer to the question with the processor from user input; evaluating the first and second evaluative expressions retrieved from the database at runtime with the processor, the expression parameter set to the answer in the evaluation of the first evaluative expression; and determining a next page with the processor when navigating away from the page based on the evaluation of the first and second evaluative expressions of the navigation rule. 13. The computer-implemented method of claim 7 further comprising creating a page display rule, the navigation rule, or a discrepancy rule depending on what evaluative expression category is received from the graphical user interface in response to user input.

12. A system for providing assistance, by a multi-function device (MFD), for document preparation, said system comprising: one or more processors in said MFD configured to: process one or more portions for one or more field names in an electronic document, wherein said electronic document corresponds to a hand-filled document comprising a character string in a first format for a field name of said one or more field names in said hand-filled document, wherein said one or more portions are extracted from said electronic document to determine a second format and a location of said character string in said electronic document, wherein said extraction of said one or more portions from said electronic document is based on a user input that indicates a first ink color of said character string, wherein said first ink color of said character string in said electronic document is different from a second ink color of said one or more field names of said electronic document; receive a set of information in a pre-specified format for said one or more field names from a user-computing device over a communication network, wherein said set of information comprises at least a plurality of key strings and corresponding values; determine a field value for each processed portion in said electronic document based on a match between said character string in said second format and at least one of said plurality of key strings associated with field names in said received set of information; and update said electronic document based on replacement of said processed portion in said electronic document for each of said one or more field names with a corresponding determined field value at said location.

12. A system for providing assistance, by a multi-function device (MFD), for document preparation, said system comprising: one or more processors in said MFD configured to: process one or more portions for one or more field names in an electronic document, wherein said electronic document corresponds to a hand-filled document comprising a character string in a first format for a field name of said one or more field names in said hand-filled document, wherein said one or more portions are extracted from said electronic document to determine a second format and a location of said character string in said electronic document, wherein said extraction of said one or more portions from said electronic document is based on a user input that indicates a first ink color of said character string, wherein said first ink color of said character string in said electronic document is different from a second ink color of said one or more field names of said electronic document; receive a set of information in a pre-specified format for said one or more field names from a user-computing device over a communication network, wherein said set of information comprises at least a plurality of key strings and corresponding values; determine a field value for each processed portion in said electronic document based on a match between said character string in said second format and at least one of said plurality of key strings associated with field names in said received set of information; and update said electronic document based on replacement of said processed portion in said electronic document for each of said one or more field names with a corresponding determined field value at said location. 20. The system of claim 12 , wherein said set of information further comprises a plurality of field names, wherein each of said plurality of field names is associated with a corresponding key string of said plurality of key strings, wherein each key string of said plurality of key strings has a corresponding value.

1. A method for detection of page numbers in a document comprising: identifying a plurality of text fragments associated with a plurality of pages of a single document; from the identified text fragments, identifying at least one sequence, each identified sequence comprising a plurality of terms, each term derived from a text fragment selected from the plurality text fragments, the terms of a sequence complying with at least one predefined numbering scheme which defines a form and an incremental state of the terms in a sequence, the at least one numbering scheme excluding terms from a sequence which do not comply with an incremental state in which terms on each two consecutive pages vary by a constant value, the identifying of the at least one sequence comprising, for each page of a plurality of pages of the document in sequence: identifying text fragments which comprise a term that complies with the form of the predefined numbering scheme; for each of the identified fragments, determining if the term of the identified fragment complies with an incremental state accepted by an existing sequence and if so, adding the term to that sequence, the existing sequence comprising at least one term derived from a text fragment of a previous page of the document; and for each of the terms which do not comply with an incremental state accepted by an existing sequence, considering the term as a potential start of a new sequence; with a computer processor, computing a subset of the identified sequences which cover at least some of the pages of the document, wherein the computing of the set of sequences comprises applying a Viterbi algorithm to the identified sequences to identify a subset of the identified sequences; and construing of at least some of the terms of the subset of the identified sequences as page numbers of pages of the document.

1. A method for detection of page numbers in a document comprising: identifying a plurality of text fragments associated with a plurality of pages of a single document; from the identified text fragments, identifying at least one sequence, each identified sequence comprising a plurality of terms, each term derived from a text fragment selected from the plurality text fragments, the terms of a sequence complying with at least one predefined numbering scheme which defines a form and an incremental state of the terms in a sequence, the at least one numbering scheme excluding terms from a sequence which do not comply with an incremental state in which terms on each two consecutive pages vary by a constant value, the identifying of the at least one sequence comprising, for each page of a plurality of pages of the document in sequence: identifying text fragments which comprise a term that complies with the form of the predefined numbering scheme; for each of the identified fragments, determining if the term of the identified fragment complies with an incremental state accepted by an existing sequence and if so, adding the term to that sequence, the existing sequence comprising at least one term derived from a text fragment of a previous page of the document; and for each of the terms which do not comply with an incremental state accepted by an existing sequence, considering the term as a potential start of a new sequence; with a computer processor, computing a subset of the identified sequences which cover at least some of the pages of the document, wherein the computing of the set of sequences comprises applying a Viterbi algorithm to the identified sequences to identify a subset of the identified sequences; and construing of at least some of the terms of the subset of the identified sequences as page numbers of pages of the document. 3. The method of claim 1 , wherein the identifying of the at least one sequence further comprises: for an existing sequence for which no term is added for the page, performing at least one of: terminating the sequence whereby no further terms are added to the sequence for subsequent pages; and adding a hole to the sequence to identify the sequence as lacking a term for the page.

1. A computer-implemented method of generating a customized user interface representing a contract, comprising: receiving, over an electronic network, a contract description message including description information corresponding to a computer device being used to display the contract to a user; retrieving, by using a processor, the description information from the contract description message; comparing the description information with information stored in a template library and adaptor library to identify a generic user interface and a corresponding adaptor module; ranking the identified generic user interface and the identified adaptor module, wherein: the identified generic user interface is ranked when the comparison provides a plurality of potential generic user interfaces for generation of the customized user interface; and the identified adaptor module is ranked when the comparison provides a plurality of potential adaptor modules for generation of the customized user interface; and generating a contract response message based on a result of the comparison and the ranking, the response message including an instruction to generate, on the computer device, the customized user interface based on the identified generic user interface and corresponding adaptor module when the generic user interface and the corresponding adaptor module are identified.

1. A computer-implemented method of generating a customized user interface representing a contract, comprising: receiving, over an electronic network, a contract description message including description information corresponding to a computer device being used to display the contract to a user; retrieving, by using a processor, the description information from the contract description message; comparing the description information with information stored in a template library and adaptor library to identify a generic user interface and a corresponding adaptor module; ranking the identified generic user interface and the identified adaptor module, wherein: the identified generic user interface is ranked when the comparison provides a plurality of potential generic user interfaces for generation of the customized user interface; and the identified adaptor module is ranked when the comparison provides a plurality of potential adaptor modules for generation of the customized user interface; and generating a contract response message based on a result of the comparison and the ranking, the response message including an instruction to generate, on the computer device, the customized user interface based on the identified generic user interface and corresponding adaptor module when the generic user interface and the corresponding adaptor module are identified. 3. The method of claim 1 , wherein the contract description message is received in response to selection of a customization option by a user of the computer device, the description information describing the customization option.

1. A method comprising: detecting that a text string is subject to a line-wrap function that would divide the text string into a first plurality of substrings for presentation via a user interface; evaluating at least one of the first plurality of substrings against one or more prohibited text strings prohibited for presentation via the user interface; detecting, in response to the evaluating of the at least one of the first plurality of substrings against the one or more prohibited text strings, that the at least one of the first plurality of substrings is one or more prohibited text strings; and dividing the text string into a second plurality of text substrings that are different from the first plurality of text substrings, wherein the dividing the text string into the second plurality of text substrings is in response to the detecting that the at least one of the first plurality of substrings is one of the one or more prohibited text strings.

1. A method comprising: detecting that a text string is subject to a line-wrap function that would divide the text string into a first plurality of substrings for presentation via a user interface; evaluating at least one of the first plurality of substrings against one or more prohibited text strings prohibited for presentation via the user interface; detecting, in response to the evaluating of the at least one of the first plurality of substrings against the one or more prohibited text strings, that the at least one of the first plurality of substrings is one or more prohibited text strings; and dividing the text string into a second plurality of text substrings that are different from the first plurality of text substrings, wherein the dividing the text string into the second plurality of text substrings is in response to the detecting that the at least one of the first plurality of substrings is one of the one or more prohibited text strings. 3. The method of claim 1 further comprising: one or more of adding one or more characters to the at least one of the second plurality of substrings, removing one or more characters from the at least one of the second plurality of substrings, swapping characters of the at least one the second plurality of substrings, and replacing characters of the at least one the second plurality of substrings.

50. A computer-implemented method of analyzing an input digital text to differentiate between digital text in a Latin-based single byte character set and digital text in a multiple byte character set or a non-Latin based character set, the method comprising: analyzing bytes of the input digital text to determine whether at least a predetermined fraction of the bytes of the input digital text are apparently extended characters; and choosing between determining the input digital text is digital text in a Latin-based single byte character set and determining the input digital text is digital text in a multiple byte character set or a non-Latin based character set based on whether it is determined at least the predetermined fraction of the bytes of the input digital text are apparently extended characters, wherein it is determined the input digital text is digital text in a multiple byte character set or a non-Latin based character set responsive to determining at least the predetermined fraction of the bytes in the input digital text are apparently extended characters.

50. A computer-implemented method of analyzing an input digital text to differentiate between digital text in a Latin-based single byte character set and digital text in a multiple byte character set or a non-Latin based character set, the method comprising: analyzing bytes of the input digital text to determine whether at least a predetermined fraction of the bytes of the input digital text are apparently extended characters; and choosing between determining the input digital text is digital text in a Latin-based single byte character set and determining the input digital text is digital text in a multiple byte character set or a non-Latin based character set based on whether it is determined at least the predetermined fraction of the bytes of the input digital text are apparently extended characters, wherein it is determined the input digital text is digital text in a multiple byte character set or a non-Latin based character set responsive to determining at least the predetermined fraction of the bytes in the input digital text are apparently extended characters. 51. The method of claim 50 wherein the predetermined fraction is one-half.

1. A system comprising: a plurality of tags affixed to a plurality of objects, wherein the plurality of tags include a plurality of features such that each tag comprises at least one feature; a plurality of sensors, wherein a location of the plurality of sensors defines a spatial operating environment (SOE) that includes the plurality of objects, wherein the plurality of sensors detect the plurality of features; and an adaptive tracking component (ATC) running on a processor, wherein the ATC receives from each sensor of the plurality of sensors feature data corresponding to each object of the plurality of objects detected by the respective sensor, wherein the ATC generates and maintains a coherent model of relationships between the plurality of objects and the SOE by integrating the feature data from the plurality of sensors.

1. A system comprising: a plurality of tags affixed to a plurality of objects, wherein the plurality of tags include a plurality of features such that each tag comprises at least one feature; a plurality of sensors, wherein a location of the plurality of sensors defines a spatial operating environment (SOE) that includes the plurality of objects, wherein the plurality of sensors detect the plurality of features; and an adaptive tracking component (ATC) running on a processor, wherein the ATC receives from each sensor of the plurality of sensors feature data corresponding to each object of the plurality of objects detected by the respective sensor, wherein the ATC generates and maintains a coherent model of relationships between the plurality of objects and the SOE by integrating the feature data from the plurality of sensors. 10. The system of claim 1 , wherein an origin of the coherent model is defined relative to a particular tag of the plurality of tags, wherein the particular tag has a fixed pose relative to the SOE.

1. A student desk configured to incorporate brain-based movement into learning activities comprising: a frame comprising a table support including leg member portions extending upwardly from a front portion of the frame and a non-rotating seat support extending upwardly from a rear portion of the frame; a rotatable seat carried by the seat support and configured to rotate about the non-rotating seat support from a resting position to a first ending position in a first direction and from a resting position to a second ending position in a second direction; a table carried by the table support, the table having a substantially flat and smooth top face, a bottom face, and a near edge proximate to the seat; a sensory relief disposed a surface of the table other than the top face, the sensory relief comprising at least one face having at least one tactilely discernable feature accessible by a user of the student desk; a swinging footrest rotatably mounted between the leg member portions of the frame; a torsion spring having a pair of legs; a pair of barriers disposed on the seat support and associated with the torsion spring, each barrier configured to remain stationary while the seat rotates and to prevent one leg of the torsion spring from traveling in one direction from the resting position; and a pair of projections extending from the seat and operatively engaging one leg of the torsion spring, each projection moving with the seat as the seat rotates, the torsion spring opposing rotation of the seat by applying a force to the projection via the associated leg.

1. A student desk configured to incorporate brain-based movement into learning activities comprising: a frame comprising a table support including leg member portions extending upwardly from a front portion of the frame and a non-rotating seat support extending upwardly from a rear portion of the frame; a rotatable seat carried by the seat support and configured to rotate about the non-rotating seat support from a resting position to a first ending position in a first direction and from a resting position to a second ending position in a second direction; a table carried by the table support, the table having a substantially flat and smooth top face, a bottom face, and a near edge proximate to the seat; a sensory relief disposed a surface of the table other than the top face, the sensory relief comprising at least one face having at least one tactilely discernable feature accessible by a user of the student desk; a swinging footrest rotatably mounted between the leg member portions of the frame; a torsion spring having a pair of legs; a pair of barriers disposed on the seat support and associated with the torsion spring, each barrier configured to remain stationary while the seat rotates and to prevent one leg of the torsion spring from traveling in one direction from the resting position; and a pair of projections extending from the seat and operatively engaging one leg of the torsion spring, each projection moving with the seat as the seat rotates, the torsion spring opposing rotation of the seat by applying a force to the projection via the associated leg. 2. The student desk of claim 1 wherein the footrest is generally U-shaped and comprises vertical side members and a horizontal center foot contact bar disposed between the vertical side members, and horizontal extensions extending laterally outwards from the vertical side members of the footrest that are rotatably mounted to the leg member portions of the frame.

12. A computer-implemented method, comprising: generating a domain-specific dependency formulae graph for each of multiple domains based on a collection of pre-defined formulae; determining (i) each of one or more variables with a stated numerical value in a textual query and (ii) each of one or more variables without a stated numerical value in the textual query by performing semantic analysis on the textual query; normalizing each of the stated numerical values corresponding to one or more of the determined variables by automatically converting each of the stated numerical values corresponding to the one or more of the determined variables to a pre-determined canonical form, wherein said normalizing comprises processing one or more value measurement categories (i) associated with the stated numerical values and (ii) represented by natural language in the textual query; selecting one of the multiple generated domain-specific dependency formulae graphs based on the determined variables in the textual query; mapping (i) all of the determined variables and (ii) the normalized values corresponding to one or more of the determined variables to the selected dependency formulae graph; and generating a solution to the textual query by automatically computing a numerical value for each of the one or more determined variables without a stated numerical value by implementing a graphical model inference mechanism against the selected pre-defined dependency formula graph subsequent to said mapping, wherein said implementing the graphical model inference mechanism comprises inferring application of one or more distinct formulae among the pre-defined dependency formulae graph related to computing a numerical value for each of the one or more determined variables without a stated numerical value; wherein the steps are carried out by at least one computing device.

12. A computer-implemented method, comprising: generating a domain-specific dependency formulae graph for each of multiple domains based on a collection of pre-defined formulae; determining (i) each of one or more variables with a stated numerical value in a textual query and (ii) each of one or more variables without a stated numerical value in the textual query by performing semantic analysis on the textual query; normalizing each of the stated numerical values corresponding to one or more of the determined variables by automatically converting each of the stated numerical values corresponding to the one or more of the determined variables to a pre-determined canonical form, wherein said normalizing comprises processing one or more value measurement categories (i) associated with the stated numerical values and (ii) represented by natural language in the textual query; selecting one of the multiple generated domain-specific dependency formulae graphs based on the determined variables in the textual query; mapping (i) all of the determined variables and (ii) the normalized values corresponding to one or more of the determined variables to the selected dependency formulae graph; and generating a solution to the textual query by automatically computing a numerical value for each of the one or more determined variables without a stated numerical value by implementing a graphical model inference mechanism against the selected pre-defined dependency formula graph subsequent to said mapping, wherein said implementing the graphical model inference mechanism comprises inferring application of one or more distinct formulae among the pre-defined dependency formulae graph related to computing a numerical value for each of the one or more determined variables without a stated numerical value; wherein the steps are carried out by at least one computing device. 16. The computer-implemented method of claim 12 , wherein said performing semantic analysis comprises automatically identifying one or more synonyms of functional mathematical terms in the textual query.

19. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of: a server storing a document in an unstructured database column in a database, wherein the document, as stored, is not defined as being marked according to a markup language; the server analyzing the document to determine that the document comprises nodes that are marked according to the markup language as being under hierarchical paths; in response to determining that the document comprises the nodes that are marked according to the markup language as under the hierarchical paths, the server storing one or more indices that map the nodes to locations where the nodes are stored within the document, wherein the one or more indices also indicate that at least one node of the nodes is an ancestor of at least one other node of the nodes.

19. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of: a server storing a document in an unstructured database column in a database, wherein the document, as stored, is not defined as being marked according to a markup language; the server analyzing the document to determine that the document comprises nodes that are marked according to the markup language as being under hierarchical paths; in response to determining that the document comprises the nodes that are marked according to the markup language as under the hierarchical paths, the server storing one or more indices that map the nodes to locations where the nodes are stored within the document, wherein the one or more indices also indicate that at least one node of the nodes is an ancestor of at least one other node of the nodes. 26. One or more non-transitory storage media as recited in claim 19 , wherein the document is a first document, and wherein the locations are first locations, wherein the instructions, when executed by the one or more computing devices, cause: storing a second document in the unstructured database column in the database; determining that the second document does not conform to the markup language; in response to the determining that the second document does not conform to the markup language, storing in the one or more indices a mapping of a virtual node to a second location of the second document.

12. A method for reorienting a display of clusters, comprising: providing a display of clusters, each cluster having a center located at a distance relative to a common origin for the display; comparing a bounding region of each cluster to a bounding region of each other cluster and determining that two or more of the clusters overlap; and reorienting at least one of the overlapping clusters until no overlap occurs, wherein the steps are performed by a suitably-programmed computer.

12. A method for reorienting a display of clusters, comprising: providing a display of clusters, each cluster having a center located at a distance relative to a common origin for the display; comparing a bounding region of each cluster to a bounding region of each other cluster and determining that two or more of the clusters overlap; and reorienting at least one of the overlapping clusters until no overlap occurs, wherein the steps are performed by a suitably-programmed computer. 19. A method according to claim 12 , wherein a shape of each cluster comprises one of a circle and a non-circle.

6. The method of claim 1 , further comprising when the finite state-based representation has accepted the key data, generating dialogs to automatically test the finite state-based representation.

6. The method of claim 1 , further comprising when the finite state-based representation has accepted the key data, generating dialogs to automatically test the finite state-based representation. 7. The method of claim 6 , further comprising performing further testing of the finite state-based representation using stored real-call records.

13. In a speech recognition system, an apparatus for storing speech parameters, said apparatus comprising: transducer means responsive to acoustic energy for transforming said acoustic energy into analog electrical signals, wherein said acoustic energy comprises voiced speech, unvoiced speech and background noise; signal processing means for converting said analog signals to substantially equivalent forms of speech parameters and for sampling said speech parameters at a predetermined sampling rate; a binary adder coupled to said signal processing means for computing the average signal level of samples of said speech parameters from said signal processing means during predetermined periods of time; storage means coupled to said signal processing means for receiving speech parameters, said storage means comprising a plurality of m contiguous blocks which are consecutively and ordinally numbered first through mth, each of said blocks comprising an equal number of storage locations, said number of storage locations corresponding to the number of samples of said speech parameters operated upon by said means for computing average signal level during each of said predetermined periods of time; means coupled to said storage means for generating sequential addresses corresponding to individual storage locations of said storage means to permit storage of said speech parameters therein; and control means coupled to said storage means and said address generating means and responsive to said binary adder for: (a) transferring speech parameters resident in the storage locations of the second through nth blocks of said storage means into corresponding storage locations of the first through (n-1)st blocks, respectively, of said storage means; and (b) resetting said generating means to thereby cause it to address the initial storage location of the nth block of said storage means; where n is a number substantially smaller than m; when the average signal level computed by said binary adder during any of said predetermined periods of time fails to exceed a predetermined signal level.

13. In a speech recognition system, an apparatus for storing speech parameters, said apparatus comprising: transducer means responsive to acoustic energy for transforming said acoustic energy into analog electrical signals, wherein said acoustic energy comprises voiced speech, unvoiced speech and background noise; signal processing means for converting said analog signals to substantially equivalent forms of speech parameters and for sampling said speech parameters at a predetermined sampling rate; a binary adder coupled to said signal processing means for computing the average signal level of samples of said speech parameters from said signal processing means during predetermined periods of time; storage means coupled to said signal processing means for receiving speech parameters, said storage means comprising a plurality of m contiguous blocks which are consecutively and ordinally numbered first through mth, each of said blocks comprising an equal number of storage locations, said number of storage locations corresponding to the number of samples of said speech parameters operated upon by said means for computing average signal level during each of said predetermined periods of time; means coupled to said storage means for generating sequential addresses corresponding to individual storage locations of said storage means to permit storage of said speech parameters therein; and control means coupled to said storage means and said address generating means and responsive to said binary adder for: (a) transferring speech parameters resident in the storage locations of the second through nth blocks of said storage means into corresponding storage locations of the first through (n-1)st blocks, respectively, of said storage means; and (b) resetting said generating means to thereby cause it to address the initial storage location of the nth block of said storage means; where n is a number substantially smaller than m; when the average signal level computed by said binary adder during any of said predetermined periods of time fails to exceed a predetermined signal level. 17. The apparatus according to claim 13 wherein said control means includes a digital magnitude comparator.

13. A device, comprising: a display device configured to display a digital sketch comprising one or more panels, and one or more sketches each at least in part included in a respective one of the one or more panels; one or more processors to implement a comic creation module that is configured to generate the digital sketch performing operations comprising to: generate the one or more panels according to panel input specifying a border for each of the one or more panels on a displayed page of the digital sketch; generate the one or more sketches according to drawing input specifying one or more strokes on the page, wherein at least a portion of at least one of the one or more strokes is drawn in at least one of the one or more panels; erase a portion of the border for at least one of the panels according to an erase input; determine for each of the one or more panels, based on a windowing algorithm, which of the one or more strokes or portions of the one or more strokes are to be displayed in the digital sketch and which of the one or more strokes or portions of the one or more strokes are hidden in the digital sketch, the windowing algorithm configured to recognize the erased portion of the border and determine that the one or more strokes or portions of the strokes that pass through the erased portion of the border are to be displayed and the one or more strokes or portions of the strokes that do not pass through the erased portion of the border are to be hidden from display, and for a panel, the windowing algorithm configured to: determine that at least one of the strokes crosses the border of the panel; split each stroke that crosses the border of the panel to generate at least two separate strokes from the respective stroke; mark each stroke that lies inside the border of the panel to be displayed; determine at least one remaining unmarked stroke that intersects a marked stroke; and mark each remaining unmarked stroke that intersects a marked stroke as to be displayed and additional remaining unmarked strokes are hidden from display.

13. A device, comprising: a display device configured to display a digital sketch comprising one or more panels, and one or more sketches each at least in part included in a respective one of the one or more panels; one or more processors to implement a comic creation module that is configured to generate the digital sketch performing operations comprising to: generate the one or more panels according to panel input specifying a border for each of the one or more panels on a displayed page of the digital sketch; generate the one or more sketches according to drawing input specifying one or more strokes on the page, wherein at least a portion of at least one of the one or more strokes is drawn in at least one of the one or more panels; erase a portion of the border for at least one of the panels according to an erase input; determine for each of the one or more panels, based on a windowing algorithm, which of the one or more strokes or portions of the one or more strokes are to be displayed in the digital sketch and which of the one or more strokes or portions of the one or more strokes are hidden in the digital sketch, the windowing algorithm configured to recognize the erased portion of the border and determine that the one or more strokes or portions of the strokes that pass through the erased portion of the border are to be displayed and the one or more strokes or portions of the strokes that do not pass through the erased portion of the border are to be hidden from display, and for a panel, the windowing algorithm configured to: determine that at least one of the strokes crosses the border of the panel; split each stroke that crosses the border of the panel to generate at least two separate strokes from the respective stroke; mark each stroke that lies inside the border of the panel to be displayed; determine at least one remaining unmarked stroke that intersects a marked stroke; and mark each remaining unmarked stroke that intersects a marked stroke as to be displayed and additional remaining unmarked strokes are hidden from display. 15. The device as recited in claim 13 , wherein the comic creation module is configured to: apply a reading order algorithm to the one or more panels or to the one or more textual elements in each panel to determine readability of the one or more panels or readability of the one or more textual elements according to reading heuristics; and display one or more suggestions for modifications to improve the readability of the one or more panels or the readability of the one or more textual elements.

15. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query; obtaining search results that satisfy the search query, wherein the search results identify a plurality of web pages, wherein each web page is a web page on a corresponding website of a plurality of websites; computing a respective global ranking score for each website of the plurality of websites, wherein the global ranking score represents an indication of relevance of the website to the search query relative to other websites of the plurality of websites; computing an onsite ranking score for each of the plurality of web pages, wherein the onsite ranking score is computed from onsite data that is controlled by a webmaster or a developer of the corresponding website for the web page, wherein the onsite ranking score represents an indication of relevance of the web page as responsive to the search query relative to other web pages within the corresponding website; selecting, as a representative web page for a particular website from among a plurality of web pages for the particular website, a particular web page having a highest onsite ranking score among the plurality of web pages for the particular website; comparing the onsite ranking score for the representative web page to the global ranking score for the particular website; determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website; in response to determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website, assigning a new global ranking score for the particular website including modifying the global ranking score for the particular website; computing a combined ranking score for each web page of the plurality of web pages including combining a respective global ranking score for a website associated with the web page and an onsite ranking score for the web page, including using the new global ranking score for the particular website when computing the combined ranking score for web pages on the particular website; and ranking the search results according to the combined ranking scores computed for respective web pages identified by the search results.

15. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query; obtaining search results that satisfy the search query, wherein the search results identify a plurality of web pages, wherein each web page is a web page on a corresponding website of a plurality of websites; computing a respective global ranking score for each website of the plurality of websites, wherein the global ranking score represents an indication of relevance of the website to the search query relative to other websites of the plurality of websites; computing an onsite ranking score for each of the plurality of web pages, wherein the onsite ranking score is computed from onsite data that is controlled by a webmaster or a developer of the corresponding website for the web page, wherein the onsite ranking score represents an indication of relevance of the web page as responsive to the search query relative to other web pages within the corresponding website; selecting, as a representative web page for a particular website from among a plurality of web pages for the particular website, a particular web page having a highest onsite ranking score among the plurality of web pages for the particular website; comparing the onsite ranking score for the representative web page to the global ranking score for the particular website; determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website; in response to determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website, assigning a new global ranking score for the particular website including modifying the global ranking score for the particular website; computing a combined ranking score for each web page of the plurality of web pages including combining a respective global ranking score for a website associated with the web page and an onsite ranking score for the web page, including using the new global ranking score for the particular website when computing the combined ranking score for web pages on the particular website; and ranking the search results according to the combined ranking scores computed for respective web pages identified by the search results. 17. The computer program product of claim 15 , wherein the onsite ranking score for the representative web page is based on a number of occurrences of terms in the search query on the representative web page.

2. The method of claim 1 , wherein each logical branch is defined by a category specification of the data abstraction model.

2. The method of claim 1 , wherein each logical branch is defined by a category specification of the data abstraction model. 4. The method of claim 2 , wherein the data abstraction model includes a plurality of logical field specifications, each defining a particular logical field, the method further comprising: including at least one created logical link with a corresponding logical field specification of the plurality of logical field specifications.

6. The machine-readable medium of claim 4 , the process further comprising: in response to the conditional variant corresponding to an implicit condition, assigning a probability to each conditional variant model associated with the target attribute, using Bayesian reasoning and observed data of the current driving session.

6. The machine-readable medium of claim 4 , the process further comprising: in response to the conditional variant corresponding to an implicit condition, assigning a probability to each conditional variant model associated with the target attribute, using Bayesian reasoning and observed data of the current driving session. 7. The machine-readable medium of claim 6 , the process further comprising: recomputing probabilities periodically during the current driving session, using subsequently observed data of the current driving session.

5. 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: receiving a speech; recognizing the speech using a phonotactic grammar to generate a phone lattice; removing silence and filler words from the phone lattice, to yield a revised phone lattice; normalizing costs in the revised phone lattice such that a cost of a best path is set to zero; generating a cost-normalized query using factors of interest, wherein an index of words is indexed by the factors of interest; generating, by performing a first pass of entries in a database, a shortlist of recognized speech possibilities using the revised phone lattice, the index of words, and indices contained in the cost-normalized query; performing a second pass on the shortlist of recognized speech possibilities using a grammar generated from the entries in the database to obtain a final result; and providing a response to the speech based on the final result.

5. 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: receiving a speech; recognizing the speech using a phonotactic grammar to generate a phone lattice; removing silence and filler words from the phone lattice, to yield a revised phone lattice; normalizing costs in the revised phone lattice such that a cost of a best path is set to zero; generating a cost-normalized query using factors of interest, wherein an index of words is indexed by the factors of interest; generating, by performing a first pass of entries in a database, a shortlist of recognized speech possibilities using the revised phone lattice, the index of words, and indices contained in the cost-normalized query; performing a second pass on the shortlist of recognized speech possibilities using a grammar generated from the entries in the database to obtain a final result; and providing a response to the speech based on the final result. 8. The system of claim 5 , wherein the phonotactic grammar is unsmoothed and is used to recognize only N-grams which have been seen in data used to train the phonotactic grammar.

16. A computer-implemented method for providing topic broadening in interactive building of electronically-stored social indexes, comprising: accessing a corpus of articles each comprised of online textual materials; specifying a hierarchically-structured tree of topics; for each of the topics, designating a set of the articles in the corpus as on-topic positive training examples; finding a fine-grained topic model comprising a finite state pattern that matches the on-topic positive training examples, each finite state pattern comprising a pattern evaluable against the articles, wherein the pattern identifies such articles matching the on-topic positive training examples for the corresponding topic; for each of the topics, generating a coarse-grained topic model corresponding to a center of the topic comprising: randomly selecting a set of the articles in the corpus; identifying a set of characteristic words in each of the randomly-selected articles; determining a frequency of occurrence of each of the characteristic words identified in the set of randomly-selected articles; identifying a set of characteristic words in each of the articles in the on-topic positive training examples; determining a frequency of occurrence of each of the characteristic words identified in the articles in the on-topic training examples; and assigning a score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the articles in the on-topic training examples and in the set of randomly-selected articles; filtering new articles received into the corpus, comprising: matching the finite state patterns to each new article; identifying a set of characteristic words in each new article; determining a frequency of occurrence of each of the characteristic words identified in the each article; and assigning a similarity score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the new article and in the set of randomly-selected articles; and for each of the topics, ordering the new articles comprising: matching the new articles to the finite state pattern of the fine-grained topic model for the topic; for each new article that does not match the fine-grained topic model for the topic, comparing similarity scores for each of the characteristic words identified in the new article to the scores of the corresponding characteristic words in the coarse-grained topic model for the topic; and displaying each of the new articles that was not matched by the topic's fine-grained topic model and which has similarit scores close to the topic's coarse- t rained topic model's characteristic word scores articles as candidate articles for additional positive training examples.

16. A computer-implemented method for providing topic broadening in interactive building of electronically-stored social indexes, comprising: accessing a corpus of articles each comprised of online textual materials; specifying a hierarchically-structured tree of topics; for each of the topics, designating a set of the articles in the corpus as on-topic positive training examples; finding a fine-grained topic model comprising a finite state pattern that matches the on-topic positive training examples, each finite state pattern comprising a pattern evaluable against the articles, wherein the pattern identifies such articles matching the on-topic positive training examples for the corresponding topic; for each of the topics, generating a coarse-grained topic model corresponding to a center of the topic comprising: randomly selecting a set of the articles in the corpus; identifying a set of characteristic words in each of the randomly-selected articles; determining a frequency of occurrence of each of the characteristic words identified in the set of randomly-selected articles; identifying a set of characteristic words in each of the articles in the on-topic positive training examples; determining a frequency of occurrence of each of the characteristic words identified in the articles in the on-topic training examples; and assigning a score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the articles in the on-topic training examples and in the set of randomly-selected articles; filtering new articles received into the corpus, comprising: matching the finite state patterns to each new article; identifying a set of characteristic words in each new article; determining a frequency of occurrence of each of the characteristic words identified in the each article; and assigning a similarity score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the new article and in the set of randomly-selected articles; and for each of the topics, ordering the new articles comprising: matching the new articles to the finite state pattern of the fine-grained topic model for the topic; for each new article that does not match the fine-grained topic model for the topic, comparing similarity scores for each of the characteristic words identified in the new article to the scores of the corresponding characteristic words in the coarse-grained topic model for the topic; and displaying each of the new articles that was not matched by the topic's fine-grained topic model and which has similarit scores close to the topic's coarse- t rained topic model's characteristic word scores articles as candidate articles for additional positive training examples. 20. A computer-implemented method according to claim 16 , further comprising: finding the highest score within the scores of the characteristic words; and normalizing the scores of the remaining characteristic words against the highest score.

1. A method performed by a computer processor for incorporating media objects in a yearbook, the method comprising: maintaining, by a computer system, information describing customizable yearbooks for students of a school; receiving one or more videos for including in a printed hard copy of a customizable yearbook of a student, wherein the one or more videos are for presenting via a video presentation device physically attached to the printed hard copy of the customizable yearbook, the video presentation device comprising a display screen for presenting videos; receiving information describing layouts of one or more video presentation pages of the customizable yearbook, the layouts specifying: for each of the one or more videos, a position of a button for activating presentation of the video via the video presentation device, and a position in a video presentation page for physically attaching the video presentation device in a printed hard copy of the yearbook; selecting videos for suggesting to the student for including in the video presentation page of the yearbook, wherein selecting videos for suggesting to the students comprises: determining a time of capture of videos associated with the student; receiving information of timing of a current school year; and preferring videos captured within the current school year over videos captured before the current school year started; sending information describing the selected videos as suggestions for including in the video presentation page of the yearbook; and sending information describing the customizable yearbook for printing one or more hard copies of the customizable yearbook, wherein each printed hard copy of the customizable yearbook comprises the one or more video presentation pages and a video presentation device physically attached to a video presentation page.

1. A method performed by a computer processor for incorporating media objects in a yearbook, the method comprising: maintaining, by a computer system, information describing customizable yearbooks for students of a school; receiving one or more videos for including in a printed hard copy of a customizable yearbook of a student, wherein the one or more videos are for presenting via a video presentation device physically attached to the printed hard copy of the customizable yearbook, the video presentation device comprising a display screen for presenting videos; receiving information describing layouts of one or more video presentation pages of the customizable yearbook, the layouts specifying: for each of the one or more videos, a position of a button for activating presentation of the video via the video presentation device, and a position in a video presentation page for physically attaching the video presentation device in a printed hard copy of the yearbook; selecting videos for suggesting to the student for including in the video presentation page of the yearbook, wherein selecting videos for suggesting to the students comprises: determining a time of capture of videos associated with the student; receiving information of timing of a current school year; and preferring videos captured within the current school year over videos captured before the current school year started; sending information describing the selected videos as suggestions for including in the video presentation page of the yearbook; and sending information describing the customizable yearbook for printing one or more hard copies of the customizable yearbook, wherein each printed hard copy of the customizable yearbook comprises the one or more video presentation pages and a video presentation device physically attached to a video presentation page. 9. The method of claim 1 , further comprising: comparing a sum of sizes of the videos selected for including in the yearbook with a storage capacity of the video presentation device.

5. The method of claim 1 , further comprising, after the clustering, assigning to an existing cluster any text zone which has not already been assigned to a cluster by the clustering.

5. The method of claim 1 , further comprising, after the clustering, assigning to an existing cluster any text zone which has not already been assigned to a cluster by the clustering. 6. The method of claim 5 , wherein a non-clustered zone is assigned to an existing cluster based on layout proximity.

5. The method of claim 1 wherein the text alert comprises a text string.

5. The method of claim 1 wherein the text alert comprises a text string. 6. The method of claim 5 wherein the text string is an English text string.

1. A dynamic spine stabilization device comprising: a bone anchor having a housing; a cavity in the housing coaxial with the bone anchor; a deflectable post received in the cavity; the deflectable post having a retainer at a distal end and a mount at a proximal end; the retainer being secured in a pocket of the cavity of the housing such that the deflectable post may pivot and rotate about a longitudinal axis of the deflectable post; and a spring positioned in the cavity of the housing between the post and the housing such that pivoting of the post away from a position in which the longitudinal axis of the post is coaxial with the bone anchor causes compression of the spring and such that the spring applies a force upon the post pushing the post towards a position in which the longitudinal axis of the post is coaxial with the bone anchor.

1. A dynamic spine stabilization device comprising: a bone anchor having a housing; a cavity in the housing coaxial with the bone anchor; a deflectable post received in the cavity; the deflectable post having a retainer at a distal end and a mount at a proximal end; the retainer being secured in a pocket of the cavity of the housing such that the deflectable post may pivot and rotate about a longitudinal axis of the deflectable post; and a spring positioned in the cavity of the housing between the post and the housing such that pivoting of the post away from a position in which the longitudinal axis of the post is coaxial with the bone anchor causes compression of the spring and such that the spring applies a force upon the post pushing the post towards a position in which the longitudinal axis of the post is coaxial with the bone anchor. 13. The device of claim 1 , wherein said spring has an isotropic deflection profile.

1. A method for ranking an ad, comprising: retrieving an initial video frame set comprising one or more initial video frames based upon a query image; identifying one or more related video frames related to at least one initial video frame of the initial video frame set to create an expanded video frame set comprising one or more video frames, the one or more video frames of the expanded video frame set comprising at least some initial video frames and at least some related video frames, the expanded video frame set not comprising the query image; grouping at least some of the one or more video frames of the expanded video frame set into one or more clusters; and ranking an ad based upon an ad feature of the ad corresponding to a cluster feature of a cluster, at least some of at least one of the retrieving, the identifying, the grouping, or the ranking implemented at least in part via a processing unit.

1. A method for ranking an ad, comprising: retrieving an initial video frame set comprising one or more initial video frames based upon a query image; identifying one or more related video frames related to at least one initial video frame of the initial video frame set to create an expanded video frame set comprising one or more video frames, the one or more video frames of the expanded video frame set comprising at least some initial video frames and at least some related video frames, the expanded video frame set not comprising the query image; grouping at least some of the one or more video frames of the expanded video frame set into one or more clusters; and ranking an ad based upon an ad feature of the ad corresponding to a cluster feature of a cluster, at least some of at least one of the retrieving, the identifying, the grouping, or the ranking implemented at least in part via a processing unit. 2. The method of claim 1 , the identifying one or more related video frames comprising: identifying a related video frame comprising a first feature corresponding to a second feature of an initial video frame.

1. A method for the automatic composition of music, the method comprising: receiving a plurality of input sound sequences containing sound frequencies with corresponding time duration; converting the plurality of input sound sequences to a finite state automaton using a system that allows over-generation; receiving exploration rules that constrain how the finite state automaton is to be traversed; creating a path marker data structure indexing a plurality of path markers, where each path marker contains a path marker history and a path marker registry; traversing the finite state automaton with a graph exploration procedure that uses the exploration rules and the plurality of path markers to determine path across the finite state automaton, such that the path marker history and the path marker registry of particular path markers are updated when traversing the finite state automaton; and storing the paths across the finite state automaton to the path marker data structure to define recorded path markers; wherein the recorded path markers that are not found in the plurality of input sound sequences define a new music composition.

1. A method for the automatic composition of music, the method comprising: receiving a plurality of input sound sequences containing sound frequencies with corresponding time duration; converting the plurality of input sound sequences to a finite state automaton using a system that allows over-generation; receiving exploration rules that constrain how the finite state automaton is to be traversed; creating a path marker data structure indexing a plurality of path markers, where each path marker contains a path marker history and a path marker registry; traversing the finite state automaton with a graph exploration procedure that uses the exploration rules and the plurality of path markers to determine path across the finite state automaton, such that the path marker history and the path marker registry of particular path markers are updated when traversing the finite state automaton; and storing the paths across the finite state automaton to the path marker data structure to define recorded path markers; wherein the recorded path markers that are not found in the plurality of input sound sequences define a new music composition. 10. A method for generating new sound sequences based on input sounds as recited in claim 1 , further comprising converting the recorded path markers defining a new sound sequence into a written form.

24. The method of claim 21 , further comprising, if the confidence level of the second label is less than the second confidence threshold: providing the client device with the indication of the failure in recognizing the input environmental sound; identifying a set of the one or more sound models with information corresponding to at least one of a first location and a first time that match the at least one of the location information and the time information; identifying a first sound model having a greatest similarity to the input sound model from the set; and if the similarity between the input sound model and the first sound model is greater than or equal to a similarity threshold, merging the input sound model and the first sound model in the server database.

24. The method of claim 21 , further comprising, if the confidence level of the second label is less than the second confidence threshold: providing the client device with the indication of the failure in recognizing the input environmental sound; identifying a set of the one or more sound models with information corresponding to at least one of a first location and a first time that match the at least one of the location information and the time information; identifying a first sound model having a greatest similarity to the input sound model from the set; and if the similarity between the input sound model and the first sound model is greater than or equal to a similarity threshold, merging the input sound model and the first sound model in the server database. 25. The method of claim 24 , further comprising: if the similarity between the input sound model and the first sound model is less than the similarity threshold, storing the input sound model in the server database.

1. A method comprising: receiving, by one or more computers, data entered at a user interface provided on a display of a user device from a first user associated with a pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested; determining, by at least one of the computers, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, based on accessing a data repository that stores language capabilities of users within the pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and transmitting, by at least one of the computers, an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to the user device for display on the user interface, wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group.

1. A method comprising: receiving, by one or more computers, data entered at a user interface provided on a display of a user device from a first user associated with a pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested; determining, by at least one of the computers, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, based on accessing a data repository that stores language capabilities of users within the pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and transmitting, by at least one of the computers, an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to the user device for display on the user interface, wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group. 7. The method of claim 1 , wherein the permission is provided by the corresponding second user.

7. A computer-readable medium containing instructions for controlling a computer system to determine a feature contribution of a feature to documents within a hierarchy of documents, the documents being web pages, the hierarchy of documents being web pages of the same web site, by a method comprising: providing the hierarchy of the web pages, the hierarchy specifying child web pages of the web pages wherein a parent web page of the web site and a child web page of the web site have a parent and child relationship when the parent web page is identified by a parent uniform resource locator of a parent depth and the child web page is identified by a child uniform resource locator of a child depth such that the parent uniform resource locator is a prefix of the child uniform resource location and the child depth is one more than the parent depth irrespective of whether the parent web page has a link to a child web page or whether the child web page has a link to the parent web page; for each web page, identifying relevance of the web page to a topic such that when the web page has no child web pages, the relevance is based on the web page itself and when the web page has a child web page, the relevance is based on the web page and a child web page; and determining a feature contribution of the web page that factors in the feature contribution of child web pages by: when the web page has no child web pages as indicated by the hierarchy, setting the feature of the web page using the web page; when the web page has a child web page as indicated by the hierarchy, setting the feature of the web page using the web page and using a child web page.

7. A computer-readable medium containing instructions for controlling a computer system to determine a feature contribution of a feature to documents within a hierarchy of documents, the documents being web pages, the hierarchy of documents being web pages of the same web site, by a method comprising: providing the hierarchy of the web pages, the hierarchy specifying child web pages of the web pages wherein a parent web page of the web site and a child web page of the web site have a parent and child relationship when the parent web page is identified by a parent uniform resource locator of a parent depth and the child web page is identified by a child uniform resource locator of a child depth such that the parent uniform resource locator is a prefix of the child uniform resource location and the child depth is one more than the parent depth irrespective of whether the parent web page has a link to a child web page or whether the child web page has a link to the parent web page; for each web page, identifying relevance of the web page to a topic such that when the web page has no child web pages, the relevance is based on the web page itself and when the web page has a child web page, the relevance is based on the web page and a child web page; and determining a feature contribution of the web page that factors in the feature contribution of child web pages by: when the web page has no child web pages as indicated by the hierarchy, setting the feature of the web page using the web page; when the web page has a child web page as indicated by the hierarchy, setting the feature of the web page using the web page and using a child web page. 8. The computer-readable medium of claim 7 wherein the feature is a length; wherein the length is represented by the following: L ′ ⁡ ( p ) = { L ⁡ ( p ) Child ⁡ ( p ) = Φ ( 1 + α ) * L ⁡ ( p ) Child ⁡ ( p ) ≠ Φ where L′(p) represents an adjusted length of web page p, L (p) represents a length of web page p, Child (p) represents the child web pages of p, Φ represents the empty set, and α represents a factor for increasing the length of web page p.

1. A device comprising: a processor, at least partially implemented in hardware, to: generate a similarity matrix defining a similarity between a plurality of computer applications according to a categorization of application programming interface (API) calls, the similarity matrix being generated from a term document matrix using singular value decomposition, the term document matrix including a first dimension of first entries corresponding to the plurality of computer applications and a second dimension of second entries corresponding to categories of the categorization, elements of the term document matrix having values based on a quantity of API calls in a computer application corresponding to a first entry of the first dimension, and in a category, of the categories, corresponding to a second entry of the second dimension, and at least one of the API calls corresponding to one of the categories, the similarity being based on weights for the API calls contained in the plurality of computer applications, a respective weight for a respective API call in a respective computer application being based on a quantity of API calls in the respective computer application and a quantity of computer applications, of the plurality of computer applications, that contain the respective API call; receive a selection of a first computer application of the plurality of computer applications; and provide an indication of at least one second computer application, of the plurality of computer applications, using the similarity matrix and based on the selection of the first computer application.

1. A device comprising: a processor, at least partially implemented in hardware, to: generate a similarity matrix defining a similarity between a plurality of computer applications according to a categorization of application programming interface (API) calls, the similarity matrix being generated from a term document matrix using singular value decomposition, the term document matrix including a first dimension of first entries corresponding to the plurality of computer applications and a second dimension of second entries corresponding to categories of the categorization, elements of the term document matrix having values based on a quantity of API calls in a computer application corresponding to a first entry of the first dimension, and in a category, of the categories, corresponding to a second entry of the second dimension, and at least one of the API calls corresponding to one of the categories, the similarity being based on weights for the API calls contained in the plurality of computer applications, a respective weight for a respective API call in a respective computer application being based on a quantity of API calls in the respective computer application and a quantity of computer applications, of the plurality of computer applications, that contain the respective API call; receive a selection of a first computer application of the plurality of computer applications; and provide an indication of at least one second computer application, of the plurality of computer applications, using the similarity matrix and based on the selection of the first computer application. 3. The device of claim 1 , where the processor, when generating the similarity matrix, is to: generate the similarity matrix from a plurality of vectors corresponding to the plurality of computer applications using a vector space model, the plurality of vectors including elements corresponding to the categories of the categorization, the elements including values based on a number of the API calls in source code and documentation for a computer application corresponding to a vector and in the category corresponding to one of the elements, at least one of the API calls corresponding to one of the categories.

1. A method comprising: at a computing device having one or more processors and memory storing one or more programs for execution by the one or more processors: displaying a messaging application for a first user; responsive to a determination that a message body of a first electronic message satisfies a first set of content-based clustering rules associated with a first message cluster, assigning the first electronic message to the first message cluster, which has a first plurality of electronic messages, wherein each electronic message in the first message cluster is either addressed to the first user or originates from the first user; displaying a first view of a first cluster graphic for the first message cluster, wherein the first view collectively represents the electronic messages in the first message cluster; in response to a first predefined user action, displaying a second view of the first cluster graphic, wherein the second view replaces the first view and displays the first plurality of electronic messages individually within the first message cluster; and in response to a second predefined user action, expanding one or more electronic messages of the first plurality of electronic messages inline within the first message cluster.

1. A method comprising: at a computing device having one or more processors and memory storing one or more programs for execution by the one or more processors: displaying a messaging application for a first user; responsive to a determination that a message body of a first electronic message satisfies a first set of content-based clustering rules associated with a first message cluster, assigning the first electronic message to the first message cluster, which has a first plurality of electronic messages, wherein each electronic message in the first message cluster is either addressed to the first user or originates from the first user; displaying a first view of a first cluster graphic for the first message cluster, wherein the first view collectively represents the electronic messages in the first message cluster; in response to a first predefined user action, displaying a second view of the first cluster graphic, wherein the second view replaces the first view and displays the first plurality of electronic messages individually within the first message cluster; and in response to a second predefined user action, expanding one or more electronic messages of the first plurality of electronic messages inline within the first message cluster. 6. The method of claim 1 , wherein the first electronic message further satisfies a second set of content-based clustering rules associated with a second message cluster; and the method further comprises: forgoing association of the first incoming electronic message with the second message cluster.

8. A method comprising: receiving, from a client device, a request to share content on a social network platform; in response to receiving the request, accessing a generative grammar model defining a message structure, the message structure including a plurality of lexical slots, the generative grammar model specifying: a corpus of source data to populate each lexical slot in the plurality of lexical slots; and a a grammatical constraint for each lexical slot in the plurality of lexical slots; generating, by a hardware processor, a message using the generative grammar model; verifying that the message adheres to a messaging standard of the social network platform; and causing the message to be published as an entry on the social network platform.

8. A method comprising: receiving, from a client device, a request to share content on a social network platform; in response to receiving the request, accessing a generative grammar model defining a message structure, the message structure including a plurality of lexical slots, the generative grammar model specifying: a corpus of source data to populate each lexical slot in the plurality of lexical slots; and a a grammatical constraint for each lexical slot in the plurality of lexical slots; generating, by a hardware processor, a message using the generative grammar model; verifying that the message adheres to a messaging standard of the social network platform; and causing the message to be published as an entry on the social network platform. 18. The method of claim 8 , wherein the generative grammar model corresponds to a user profile corresponding to a user of the client device from which the request to share the content is received.

1. A method comprising: receiving a search term; identifying instances of the search term in a source text; for each of the instances of the search term identified in the source text, identifying a prefix string comprising a plurality of tokens preceding the search term in the source text, and identifying a suffix string comprising a plurality of tokens subsequent to the search term in the source text; providing data to display a visualization interface that comprises the search term within a combined tree diagram comprising a prefix tree extending to a first side of the search term, and a suffix tree extending to a second side of the search term, such that the prefix tree displays, in a tree diagram format, the prefix strings for the instances of the search term identified in the source text, and the suffix tree displays, in tree diagram format, the suffix strings for the instances of the search term identified in the source text, wherein the prefix tree comprises tokens that are shared in common among the prefix strings as nodes connected to adjacent tokens by branches, and the suffix tree comprises tokens that are shared in common among the suffix strings as nodes connected to adjacent tokens by branches, wherein the branches in each of the prefix tree and the suffix tree are user-selectable in the visualization interface; and in response to receiving a user input selecting one of the branches in the prefix tree or in the suffix tree, and for each of one or more matching sequences that are connected through the selected branch, providing data to display a visual indication of a particular prefix string and a particular suffix string in the visualization interface that form a unique matching sequence of the particular prefix string, the search term, and the particular suffix string that occur together in the source text, wherein each of the one or more matching sequences forms a unique matching sequence from the source text, and wherein the visual indication comprises a unique graphical indicator applied to each unique matching sequence through the corresponding nodes in the prefix tree, the search term, and the corresponding nodes in the suffix tree for each of the unique matching sequences that comprise the search term and the selected branch.

1. A method comprising: receiving a search term; identifying instances of the search term in a source text; for each of the instances of the search term identified in the source text, identifying a prefix string comprising a plurality of tokens preceding the search term in the source text, and identifying a suffix string comprising a plurality of tokens subsequent to the search term in the source text; providing data to display a visualization interface that comprises the search term within a combined tree diagram comprising a prefix tree extending to a first side of the search term, and a suffix tree extending to a second side of the search term, such that the prefix tree displays, in a tree diagram format, the prefix strings for the instances of the search term identified in the source text, and the suffix tree displays, in tree diagram format, the suffix strings for the instances of the search term identified in the source text, wherein the prefix tree comprises tokens that are shared in common among the prefix strings as nodes connected to adjacent tokens by branches, and the suffix tree comprises tokens that are shared in common among the suffix strings as nodes connected to adjacent tokens by branches, wherein the branches in each of the prefix tree and the suffix tree are user-selectable in the visualization interface; and in response to receiving a user input selecting one of the branches in the prefix tree or in the suffix tree, and for each of one or more matching sequences that are connected through the selected branch, providing data to display a visual indication of a particular prefix string and a particular suffix string in the visualization interface that form a unique matching sequence of the particular prefix string, the search term, and the particular suffix string that occur together in the source text, wherein each of the one or more matching sequences forms a unique matching sequence from the source text, and wherein the visual indication comprises a unique graphical indicator applied to each unique matching sequence through the corresponding nodes in the prefix tree, the search term, and the corresponding nodes in the suffix tree for each of the unique matching sequences that comprise the search term and the selected branch. 4. The method of claim 1 , wherein the nodes in the prefix tree and the suffix tree are also user-selectable in the visualization interface, the method further comprising: receiving a user input selecting one of the nodes; and combining a token in the selected node with the search term into a new search term; and providing data to display an updated visualization interface that comprises the new search term within a new combined tree diagram, comprising a new prefix tree and a new suffix tree, such that the new prefix tree displays, in tree diagram format, the prefix strings for instances of the new search term in the source text, and the new suffix tree displays, in tree diagram format, the suffix strings for instances of the new search term in the source text.

1. A system for hosting data, comprising: at least one computing device in a first region of control that: receives from at least one computing device in a second region of control via at least one network, a data request applicable to at least one data set stored by the at least one computing device in the first region of control; in response to the data request, extracts a subset of results from the at least one data set based on the data request; infers from the subset of the results additional semantic information that describes the at least one data set; and forms or updates mapping information that describes an identifier of the at least one data set based on the additional semantic information.

1. A system for hosting data, comprising: at least one computing device in a first region of control that: receives from at least one computing device in a second region of control via at least one network, a data request applicable to at least one data set stored by the at least one computing device in the first region of control; in response to the data request, extracts a subset of results from the at least one data set based on the data request; infers from the subset of the results additional semantic information that describes the at least one data set; and forms or updates mapping information that describes an identifier of the at least one data set based on the additional semantic information. 6. The system according to claim 1 , wherein the at least one computing device in the first region of control extracts the subset of results returned from executing the data request.

8. A system in communication, comprising: a processor; and a computer readable storage medium including code executed by the processor to perform operations, the operations comprising: accessing document identifiers for documents including at least one value that is a member of a set of values; generating a number of posting lists associated with a first level, wherein each posting list is associated with a range of consecutive values within the set of values and includes document identifiers for documents including at least one value within the range of consecutive values associated with the posting list, and wherein each document identifier is associated with one value in the set of values included in the document identified by the document identifier; performing at least one iteration of generating posting lists for an additional level, wherein each posting list generated for the additional level is formed by merging at least two posting lists associated with a previous level, wherein each generated posting list at one additional level is associated with consecutive values in the set of values, wherein each document in the generated posting list at the additional level includes one value in the consecutive values associated with the posting list at the additional level, and wherein a new additional level and posting lists associated therewith are generated with each iteration; receiving a query on a query range of values within the set of values; determining a minimum number of posting lists associated with one or more levels having consecutive values that include the query range of values; merging the determined posting lists to form a merged posting list including document identifiers of documents including values within the query range; and returning the document identifiers in the merged posting list.

8. A system in communication, comprising: a processor; and a computer readable storage medium including code executed by the processor to perform operations, the operations comprising: accessing document identifiers for documents including at least one value that is a member of a set of values; generating a number of posting lists associated with a first level, wherein each posting list is associated with a range of consecutive values within the set of values and includes document identifiers for documents including at least one value within the range of consecutive values associated with the posting list, and wherein each document identifier is associated with one value in the set of values included in the document identified by the document identifier; performing at least one iteration of generating posting lists for an additional level, wherein each posting list generated for the additional level is formed by merging at least two posting lists associated with a previous level, wherein each generated posting list at one additional level is associated with consecutive values in the set of values, wherein each document in the generated posting list at the additional level includes one value in the consecutive values associated with the posting list at the additional level, and wherein a new additional level and posting lists associated therewith are generated with each iteration; receiving a query on a query range of values within the set of values; determining a minimum number of posting lists associated with one or more levels having consecutive values that include the query range of values; merging the determined posting lists to form a merged posting list including document identifiers of documents including values within the query range; and returning the document identifiers in the merged posting list. 15. The system of claim 8 , wherein the operations further comprise: filtering at least one of the determined posting lists at the first level in response to the determined posting lists at the first level including values outside of the query range of values to remove values not within the query range of values to form at least one filtered posting list only including values within the query range of values, wherein merging the determined posting lists comprising merging the at least one filtered posting list and determined posting lists that are not subject to filtering.

10. The non-transitory computer-readable memory device of claim 9 , where the one or more instructions that cause the one or more processors to identify the sentences comprise: one or more instructions that, when executed by the one or more processors, cause that one or more processors to: obtain the query; identify the one or more documents based, at least in part, on the query; and identify the sentences, within the one or more documents, where the sentences include the query.

10. The non-transitory computer-readable memory device of claim 9 , where the one or more instructions that cause the one or more processors to identify the sentences comprise: one or more instructions that, when executed by the one or more processors, cause that one or more processors to: obtain the query; identify the one or more documents based, at least in part, on the query; and identify the sentences, within the one or more documents, where the sentences include the query. 11. The non-transitory computer-readable memory device of claim 10 , where the one or more instructions that cause the one or more processors to identify the sentences comprise: one or more instructions that, when executed by the one or more processors, cause that one or more processors to search for documents that include synonyms of one or more words within the obtained query to identify the one or more documents.

2. The computer-implemented method of claim 1 , wherein generating predefined feedback comments includes generating the predefined feedback comment to include a name of the item.

2. The computer-implemented method of claim 1 , wherein generating predefined feedback comments includes generating the predefined feedback comment to include a name of the item. 3. The computer-implemented method of claim 2 , wherein generating predefined feedback comments further includes accessing an item table from a network-based transaction system, the item table storing a plurality of item names including the name of the item.

1. A computer-implemented method comprising: receiving, by a search system, (i) a pixel map corresponding to one or more characters that have been drawn on a display of a client device and (ii) data identifying one or more other characters that were previously recognized by the search system using one or more other pixel maps; recognizing, by the search system, the one or more characters that correspond to the pixel map based on the received pixel map and the one or more other characters; formulating, by the search system, a search that includes the one or more characters and the one or more other characters as a query term; and communicating, by the search system, (i) one or more search results for the search, (ii) data identifying the one or more characters that correspond to the received pixel map, and (iii) data identifying the one or more other characters to the client device that were previously recognized by the search system using the one or more other pixel maps.

1. A computer-implemented method comprising: receiving, by a search system, (i) a pixel map corresponding to one or more characters that have been drawn on a display of a client device and (ii) data identifying one or more other characters that were previously recognized by the search system using one or more other pixel maps; recognizing, by the search system, the one or more characters that correspond to the pixel map based on the received pixel map and the one or more other characters; formulating, by the search system, a search that includes the one or more characters and the one or more other characters as a query term; and communicating, by the search system, (i) one or more search results for the search, (ii) data identifying the one or more characters that correspond to the received pixel map, and (iii) data identifying the one or more other characters to the client device that were previously recognized by the search system using the one or more other pixel maps. 5. The method of claim 1 , wherein the search comprises an image search.

42. The system of claim 32 , wherein said processed text comprises a string of characters selected from a processed text character set, said processed text character set comprising at least one contiguous subset of the Unicode character set.

42. The system of claim 32 , wherein said processed text comprises a string of characters selected from a processed text character set, said processed text character set comprising at least one contiguous subset of the Unicode character set. 45. The system of claim 42 , wherein the at least one contiguous subset is selected from the set of Unicode characters consisting of Korean Hangul, Chinese, Japanese and Korean (CJK) Unified Ideographs, and a combination thereof.

1. A method, comprising: generating, at a master node, configuration data for each indexer of a cluster of indexers under coordination by the master node, wherein the cluster of indexers is distributed across one or more sites, wherein configuration data for a particular indexer of the cluster of indexers indicates whether the particular indexer is a primary indexer with primary responsibility for responding to search queries originating from one or more search heads, wherein each of the one or more sites comprises a plurality of indexers of the cluster, wherein each indexer is operable to store multiple subsets of searchable data, and wherein each subset of searchable data is operable to be replicated across multiple indexers at the one or more sites, and wherein, in response to a search query, each indexer is configured to use configuration data received from the master node to search associated subsets of searchable data for which it has primary responsibility; sending, to each indexer of the cluster of indexers, configuration data generated for a respective indexer, wherein the configuration data further indicates whether a particular indexer is a secondary indexer with secondary responsibility for responding to the search queries related to searchable data replicated between the primary indexer and the secondary indexer.

1. A method, comprising: generating, at a master node, configuration data for each indexer of a cluster of indexers under coordination by the master node, wherein the cluster of indexers is distributed across one or more sites, wherein configuration data for a particular indexer of the cluster of indexers indicates whether the particular indexer is a primary indexer with primary responsibility for responding to search queries originating from one or more search heads, wherein each of the one or more sites comprises a plurality of indexers of the cluster, wherein each indexer is operable to store multiple subsets of searchable data, and wherein each subset of searchable data is operable to be replicated across multiple indexers at the one or more sites, and wherein, in response to a search query, each indexer is configured to use configuration data received from the master node to search associated subsets of searchable data for which it has primary responsibility; sending, to each indexer of the cluster of indexers, configuration data generated for a respective indexer, wherein the configuration data further indicates whether a particular indexer is a secondary indexer with secondary responsibility for responding to the search queries related to searchable data replicated between the primary indexer and the secondary indexer. 2. The method of claim 1 , wherein the primary indexer responds with one or more results based on data from one or more subsets of searchable data accessible to the primary indexer.

3. The method of claim 1 , further comprising down-weighing a language model word as a function of branching size of the language model and a number of entries in embedded grammar.

3. The method of claim 1 , further comprising down-weighing a language model word as a function of branching size of the language model and a number of entries in embedded grammar. 4. The method of claim 3 , wherein a number of language model words to be down-weighed is a function of actual entries in language model paths and grammar paths.

1. A computer program product for messaging, the computer program product comprising: a computer readable storage medium and program instructions stored on the computer readable storage medium, the program instructions comprising instructions to: receive proxy recipient information from a target recipient; detect that a message is being drafted to the target recipient determine whether the target recipient is currently available without receiving a message from the target recipient; and in response to determining that the target recipient is currently unavailable, suggest a proxy recipient for the target recipient to a user.

1. A computer program product for messaging, the computer program product comprising: a computer readable storage medium and program instructions stored on the computer readable storage medium, the program instructions comprising instructions to: receive proxy recipient information from a target recipient; detect that a message is being drafted to the target recipient determine whether the target recipient is currently available without receiving a message from the target recipient; and in response to determining that the target recipient is currently unavailable, suggest a proxy recipient for the target recipient to a user. 5. The computer program product of claim 1 , wherein the proxy recipient information is provided by the user.

3. A system according to claim 2 , further comprising: a cluster scoring module to determine a score for each cluster concept by aggregating the document concept scores for each document concept in that cluster.

3. A system according to claim 2 , further comprising: a cluster scoring module to determine a score for each cluster concept by aggregating the document concept scores for each document concept in that cluster. 4. A system according to claim 3 , further comprising: a spine scoring module to determine a score for each spine concept by aggregating the cluster concept scores for each cluster associated with that spine.