Datasets:

patent

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AIPD_nlp_sentence_dataset_v2

like 1

10. An apparatus comprising: a processor; memory including computer program code; the memory and the computer program code configured to, with the processor, cause the apparatus to: receive a handwritten input character string having an unrecognized character; determine at least one character sub-string preceding the unrecognized character in the input character string; provide, by means of handwriting recognition, one or more candidate characters for the unrecognized character; identify, amongst stored character strings, one or more character strings comprising an initial character sub-string identical to the determined character sub-string; and select, based on the identified one or more character strings, one of the one or more candidate characters that is most likely to be a correct recognition of the unrecognized character, wherein if a complete character string preceding the unrecognized character in the input character string is not identical to any stored character string or an initial sub-string of any stored character string, the apparatus is caused to determine at least one character sub-string by: identifying any initial character sub-string of the input character string preceding the unrecognized character, which is identical to one of the stored character strings or to an initial character sub-string of one or more of the stored character strings, and which together with a succeeding character is not identical to any one of the stored character strings or to an initial character sub-string of any one of the stored character strings; and determining a character sub-string consisting of a terminal character sub-string of the input character string preceding the unrecognized character and succeeding any identified initial character sub-string; else the apparatus is caused to determine at least one character sub-string by: determining a character sub-string consisting of said complete character string preceding the unrecognized character in the input character string.

10. An apparatus comprising: a processor; memory including computer program code; the memory and the computer program code configured to, with the processor, cause the apparatus to: receive a handwritten input character string having an unrecognized character; determine at least one character sub-string preceding the unrecognized character in the input character string; provide, by means of handwriting recognition, one or more candidate characters for the unrecognized character; identify, amongst stored character strings, one or more character strings comprising an initial character sub-string identical to the determined character sub-string; and select, based on the identified one or more character strings, one of the one or more candidate characters that is most likely to be a correct recognition of the unrecognized character, wherein if a complete character string preceding the unrecognized character in the input character string is not identical to any stored character string or an initial sub-string of any stored character string, the apparatus is caused to determine at least one character sub-string by: identifying any initial character sub-string of the input character string preceding the unrecognized character, which is identical to one of the stored character strings or to an initial character sub-string of one or more of the stored character strings, and which together with a succeeding character is not identical to any one of the stored character strings or to an initial character sub-string of any one of the stored character strings; and determining a character sub-string consisting of a terminal character sub-string of the input character string preceding the unrecognized character and succeeding any identified initial character sub-string; else the apparatus is caused to determine at least one character sub-string by: determining a character sub-string consisting of said complete character string preceding the unrecognized character in the input character string. 15. The apparatus of claim 10 , wherein the apparatus is a mobile terminal.

4. The method of claim 1 further comprising performing initial filtering for selecting interactions to be processed.

4. The method of claim 1 further comprising performing initial filtering for selecting interactions to be processed. 5. The method of claim 4 wherein the initial filtering relates to Computer-Telephony-Integration data or to Customer-Relationship-Management data or to meta data associated with the at least one vocal interaction or the at least one non-vocal interaction.

1. A method of displaying search information implemented in a computer infrastructure having computer executable code, comprising the steps of: submitting a query having one or more search criterion; displaying a summary result of the query in a search criteria control bar (SCCB) format, wherein the SCCB format includes each of the one or more search criterion having a first active control for editing the query with a one-click operation and a second active control for editing the query with another one-click operation; initiating a submission of another query when either the first or second active control is clicked to obtain another summary result in the SCCB format reflecting results of the another query based on which active control is clicked; displaying the summary result and the another summary result in the SCCB format, wherein the one or more search criterion includes at least any one of one or more category words or phrase each delimited by a set of category delimiters and one or more keywords or phrase each delimited by a set of keyword delimiters; displaying the one or more search criterion each having an associated filter option for removing a chosen search criterion from the one or more search criterion when the another query is initiated, the associated filter option being the second active control; and removing the chosen search criterion when the associated filter option is clicked and initiating the submission of the another query using any remaining one or more search criterion causing the results of the another query to be limited to the remaining one or more search criterion.

1. A method of displaying search information implemented in a computer infrastructure having computer executable code, comprising the steps of: submitting a query having one or more search criterion; displaying a summary result of the query in a search criteria control bar (SCCB) format, wherein the SCCB format includes each of the one or more search criterion having a first active control for editing the query with a one-click operation and a second active control for editing the query with another one-click operation; initiating a submission of another query when either the first or second active control is clicked to obtain another summary result in the SCCB format reflecting results of the another query based on which active control is clicked; displaying the summary result and the another summary result in the SCCB format, wherein the one or more search criterion includes at least any one of one or more category words or phrase each delimited by a set of category delimiters and one or more keywords or phrase each delimited by a set of keyword delimiters; displaying the one or more search criterion each having an associated filter option for removing a chosen search criterion from the one or more search criterion when the another query is initiated, the associated filter option being the second active control; and removing the chosen search criterion when the associated filter option is clicked and initiating the submission of the another query using any remaining one or more search criterion causing the results of the another query to be limited to the remaining one or more search criterion. 12. The method of claim 1 further comprising limiting the query based on a user profile.

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. 9. The pronunciation variation rule extraction method according to claim 8 , wherein said controlling further includes updating said weight value, when said difference is smaller than a predetermined threshold, such that said weight value is decreased.

1. A system comprising: a microphone array configured to produce microphone audio signals; an audio beamformer configured to process the microphone audio signals to produce directional audio signals, wherein a first directional audio signal of the directional audio signals corresponds to a first direction with respect to the microphone array and wherein a second directional audio signal of the directional audio signals corresponds to a second direction with respect to the microphone array, wherein the first directional audio signal and the second directional audio signal emphasize sound from the first direction and the second direction, respectively; a speech activity detector configured to analyze one or more frequency characteristics of the first directional audio signal and the second directional audio signal to determine a first level of speech presence and a second level of speech presence occurring in the first direction and the second direction, respectively, over time; a source detector configured to analyze the first level of speech presence and the second level of speech presence occurring over a past time period to determine that an electronic source of sound is located in the first direction or the second direction; and an expression detector configured to perform actions comprising: identifying the first direction where a first occurring level of speech presence is a highest level of speech presence; determining that the first direction corresponds to a direction in which the electronic source of sound is located; identifying the second direction where a second occurring level of speech presence is a second highest level of speech presence; analyzing the first directional audio signal corresponding to the first direction to produce a first score indicating a first likelihood that a trigger expression is represented in the first directional audio signal; analyzing the second directional audio signal corresponding to the second direction to produce a second score indicating a second likelihood that the trigger expression is represented in the second directional audio signal; comparing the first score to a first threshold; comparing the second score to a second threshold, wherein the second threshold is less than the first threshold; determining that (i) the first score is greater than the first threshold or (ii) the second score is greater than the second threshold; concluding that the trigger expression has been uttered; and performing speech recognition on subsequent speech, based at least in part on the trigger expression.

1. A system comprising: a microphone array configured to produce microphone audio signals; an audio beamformer configured to process the microphone audio signals to produce directional audio signals, wherein a first directional audio signal of the directional audio signals corresponds to a first direction with respect to the microphone array and wherein a second directional audio signal of the directional audio signals corresponds to a second direction with respect to the microphone array, wherein the first directional audio signal and the second directional audio signal emphasize sound from the first direction and the second direction, respectively; a speech activity detector configured to analyze one or more frequency characteristics of the first directional audio signal and the second directional audio signal to determine a first level of speech presence and a second level of speech presence occurring in the first direction and the second direction, respectively, over time; a source detector configured to analyze the first level of speech presence and the second level of speech presence occurring over a past time period to determine that an electronic source of sound is located in the first direction or the second direction; and an expression detector configured to perform actions comprising: identifying the first direction where a first occurring level of speech presence is a highest level of speech presence; determining that the first direction corresponds to a direction in which the electronic source of sound is located; identifying the second direction where a second occurring level of speech presence is a second highest level of speech presence; analyzing the first directional audio signal corresponding to the first direction to produce a first score indicating a first likelihood that a trigger expression is represented in the first directional audio signal; analyzing the second directional audio signal corresponding to the second direction to produce a second score indicating a second likelihood that the trigger expression is represented in the second directional audio signal; comparing the first score to a first threshold; comparing the second score to a second threshold, wherein the second threshold is less than the first threshold; determining that (i) the first score is greater than the first threshold or (ii) the second score is greater than the second threshold; concluding that the trigger expression has been uttered; and performing speech recognition on subsequent speech, based at least in part on the trigger expression. 3. The system of claim 1 , wherein the source detector is further configured to determine that the electronic source of sound is located in the first direction by determining that the first level of speech presence corresponding to the first direction has exceeded a level threshold for at least a threshold amount of time during the past time period.

20. The method of claim 1, wherein the data is stored in a database, further comprising the steps of: reducing a dimensionality of the database and generating dimensionality reduction information associated with the database; and storing the dimensionality reduction information associated with the database; wherein said partitioning step is responsive to said reducing step.

20. The method of claim 1, wherein the data is stored in a database, further comprising the steps of: reducing a dimensionality of the database and generating dimensionality reduction information associated with the database; and storing the dimensionality reduction information associated with the database; wherein said partitioning step is responsive to said reducing step. 22. The method of claim 20, for performing a similarity search, comprising the steps of: reducing the dimensionality of specified data using the dimensionality reduction information associated with the database; finding the cluster to which reduced dimensionality specified data belongs, based on the clustering information; reducing the dimensionality of the reduced dimensionality specified data based on the dimensionality reduction information for an identified cluster; searching for a reduced-dimensionality version of the cluster to which the further reduced dimensionality specified data belongs; retrieving via the multidimensional index, k records most similar to the further reduced dimensionality specified data in the cluster; assessing whether other clusters can contain records closer to the specified data than the farthest of the k records retrieved; searching a closest other cluster to the specified data, in response to said assessing step; and repeating said assessing and searching for all said other clusters.

1. A method comprising: identifying, via a processor communicating with Internet resources, common task independent web-sentences based on frequently occurring phrases across multiple websites from a web domain stored in a data store; selectively removing the common task independent web-sentences from the web domain data, to yield filtered web domain data comprising domain-specific data; identifying, via the processor, predicate/argument pairs from the filtered web domain data; replacing, via the processor, the predicate/argument pairs with predicate/argument tokens; generating, via the processor, conversational utterances by merging the predicate/argument tokens with manually written conversational templates while preserving a relative frequency of the manually written conversational templates, to yield generated conversational utterances; and generating, via the processor, a web data language model using the generated conversational utterances, and providing it as an initial language model for deployment of an automated speech recognition system.

1. A method comprising: identifying, via a processor communicating with Internet resources, common task independent web-sentences based on frequently occurring phrases across multiple websites from a web domain stored in a data store; selectively removing the common task independent web-sentences from the web domain data, to yield filtered web domain data comprising domain-specific data; identifying, via the processor, predicate/argument pairs from the filtered web domain data; replacing, via the processor, the predicate/argument pairs with predicate/argument tokens; generating, via the processor, conversational utterances by merging the predicate/argument tokens with manually written conversational templates while preserving a relative frequency of the manually written conversational templates, to yield generated conversational utterances; and generating, via the processor, a web data language model using the generated conversational utterances, and providing it as an initial language model for deployment of an automated speech recognition system. 6. The method of claim 1 , wherein the manually written conversational templates can be learned from a library of utterances from spoken dialogue systems.

1. A user-interface method of incrementally providing fully qualified links to a set of relevant search engines, the method comprising: identifying a set of search engines and associating each search engine of the set with at least one descriptive category to which the subject matter of the corresponding search engine relates; providing a database containing a collection of potential full queries, each potential full query associated in said database with at least one descriptive category; receiving a partial search query entered on a keypad by a user; after each keypress received from the user, inferring a set of potential full queries intended by the user, based at least in part on the partial search query; selecting a subset of the identified search engines that are relevant to the inferred full queries based on comparing the inferred full queries with the descriptive categories associated with the search engines, wherein the selecting the subset of relevant search engines is further based on the descriptive categories associated with the provided potential full queries; and for each of the selected search engines, providing a fully qualified link designed to directly launch a search for a relevant query string using the search engine.

1. A user-interface method of incrementally providing fully qualified links to a set of relevant search engines, the method comprising: identifying a set of search engines and associating each search engine of the set with at least one descriptive category to which the subject matter of the corresponding search engine relates; providing a database containing a collection of potential full queries, each potential full query associated in said database with at least one descriptive category; receiving a partial search query entered on a keypad by a user; after each keypress received from the user, inferring a set of potential full queries intended by the user, based at least in part on the partial search query; selecting a subset of the identified search engines that are relevant to the inferred full queries based on comparing the inferred full queries with the descriptive categories associated with the search engines, wherein the selecting the subset of relevant search engines is further based on the descriptive categories associated with the provided potential full queries; and for each of the selected search engines, providing a fully qualified link designed to directly launch a search for a relevant query string using the search engine. 10. The method of claim 1 wherein the relevant query string is one of the provided query refinements.

20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device.

20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. 28. The method of claim 20 , wherein processing the text string and the contextual information comprises: identifying a search query in the text string; identifying a geographical constraint in the text string; and performing a search based at least in part on the search query and the geographical constraint; wherein transmitting the results comprises transmitting results of the search to the portable electronic device.

20. The system of claim 19 , further comprising a second computer, wherein the second computer is operative to: receive the request to access the hosted application via a web page; decrypt the credentials sent to the IP address; and render the credentials to a user via the web page whereby TS accounts are provisioned and TS sessions provides access to the hosted application without a user entering credentials.

20. The system of claim 19 , further comprising a second computer, wherein the second computer is operative to: receive the request to access the hosted application via a web page; decrypt the credentials sent to the IP address; and render the credentials to a user via the web page whereby TS accounts are provisioned and TS sessions provides access to the hosted application without a user entering credentials. 26. The method of claim 20 , further comprising detecting time parameters associated with the TS account located wherein the time parameters include at least one of the following: a TS account duration comprising a time span between provisioning the TS account and deletion of the TS account; a warning time comprising a time span between provisioning a TS account and rendering a warning to a user during a TS session; and a TS session duration comprising a time limit at which a TS session is disconnected.

1. A method performed by a processor of providing companion services to a companion device associated with a media display device, the method comprising: detecting video being displayed on the media display device; in response to detecting video being displayed, automatically identifying text contained within the video; determining, by performing pattern matching, if the identified text in the video contains one or more actionable text; if the identified text in the video contains one or more actionable text, providing access to one or more features at the companion device based on the one or more actionable text while playback of the video is being provided on the media display device, wherein providing access to the one or more features includes adding an actionable link to an actionable object list, and wherein the added actionable link is associated with the identified one or more actionable text, and wherein the added actionable link is a link to an operation, and wherein when the actionable object list contains two or more actionable links, each actionable link in the actionable object list is a link to a unique operation, and wherein the actionable object list is a running list of added actionable links that includes actionable links associated with previously identified one or more actionable text; and providing instructions to display at the companion device the added actionable links in the actionable object list based on an order in which the one or more actionable text associated with the added actionable links were identified in the video.

1. A method performed by a processor of providing companion services to a companion device associated with a media display device, the method comprising: detecting video being displayed on the media display device; in response to detecting video being displayed, automatically identifying text contained within the video; determining, by performing pattern matching, if the identified text in the video contains one or more actionable text; if the identified text in the video contains one or more actionable text, providing access to one or more features at the companion device based on the one or more actionable text while playback of the video is being provided on the media display device, wherein providing access to the one or more features includes adding an actionable link to an actionable object list, and wherein the added actionable link is associated with the identified one or more actionable text, and wherein the added actionable link is a link to an operation, and wherein when the actionable object list contains two or more actionable links, each actionable link in the actionable object list is a link to a unique operation, and wherein the actionable object list is a running list of added actionable links that includes actionable links associated with previously identified one or more actionable text; and providing instructions to display at the companion device the added actionable links in the actionable object list based on an order in which the one or more actionable text associated with the added actionable links were identified in the video. 2. The method of claim 1 , wherein providing access to one or more features comprises: providing an actionable link to create a calendar event based on the one or more actionable text.

1. A method performed by one or more devices, the method comprising: identifying, by one or more processors of the one or more devices, a plurality of documents, a first document, of the identified plurality of documents, being linked to by a second document, of the identified plurality of documents, the second document and a third document, of the identified plurality of documents, being in a set of affiliated documents; calculating, by one or more processors of the one or more devices, a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determining, by one or more processors of the one or more devices, that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assigning, by one or more processors of the one or more devices, a ranking score to the first document based on the first value calculated for the third document; and storing, by one or more processors of the one or more devices, the ranking score.

1. A method performed by one or more devices, the method comprising: identifying, by one or more processors of the one or more devices, a plurality of documents, a first document, of the identified plurality of documents, being linked to by a second document, of the identified plurality of documents, the second document and a third document, of the identified plurality of documents, being in a set of affiliated documents; calculating, by one or more processors of the one or more devices, a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determining, by one or more processors of the one or more devices, that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assigning, by one or more processors of the one or more devices, a ranking score to the first document based on the first value calculated for the third document; and storing, by one or more processors of the one or more devices, the ranking score. 2. The method of claim 1 , further comprising: sorting a group of the identified plurality of documents, including the first document, based on the ranking score; and presenting information identifying the sorted group of the identified plurality of documents to a user.

1. A computer-implemented method comprising: determining a data structure comprising a plurality of query language configuration parameters and at least two values associated with each of the plurality of query language configuration parameters; generating, based on the data structure, a first structured language query associated with a first value associated with one of the plurality of query language configuration parameters, and a second structured language query associated with a second value associated with the one of the plurality of query language configuration parameters; determining a first expected query result that is associated with the first structured language query and expected in response to the first structured language query if a data source supports a first particularity; determining a second expected query result that is associated with the second structured language query and expected in response to the second structured language query if the data source supports a second particularity rather than the first particularity; querying the data source with the first structured language query; querying the data source with the second structured language query; receiving a first query result associated with the first structured language query and a second query result associated with the second structured language query; comparing the first query result to the first expected query result that is associated with the first structured language query and expected in response to the first structured language query if the data source supports the first particularity; comparing the second query result to the second expected query result that is associated with the second structured language query and expected in response to the second structured language query if the data source supports a second particularity rather than the first particularity; determining that the first query result matches the first expected query result that is associated with the first structured language query and expected in response to the first structured language query if the data source supports the first particularity; determining that the second query result does not match the second expected query result that is associated with the second structured language query and expected in response to the second structured language query if the data source supports a second particularity rather than the first particularity; and in response to the determining that the first query result matches the first expected query result that is associated with the first structured language query and expected in response to the first structured language query if the data source supports the first particularity, adding, to a query language configuration parameter file associated with the data source, the one of the plurality of query language configuration parameters in association with the first value.

1. A computer-implemented method comprising: determining a data structure comprising a plurality of query language configuration parameters and at least two values associated with each of the plurality of query language configuration parameters; generating, based on the data structure, a first structured language query associated with a first value associated with one of the plurality of query language configuration parameters, and a second structured language query associated with a second value associated with the one of the plurality of query language configuration parameters; determining a first expected query result that is associated with the first structured language query and expected in response to the first structured language query if a data source supports a first particularity; determining a second expected query result that is associated with the second structured language query and expected in response to the second structured language query if the data source supports a second particularity rather than the first particularity; querying the data source with the first structured language query; querying the data source with the second structured language query; receiving a first query result associated with the first structured language query and a second query result associated with the second structured language query; comparing the first query result to the first expected query result that is associated with the first structured language query and expected in response to the first structured language query if the data source supports the first particularity; comparing the second query result to the second expected query result that is associated with the second structured language query and expected in response to the second structured language query if the data source supports a second particularity rather than the first particularity; determining that the first query result matches the first expected query result that is associated with the first structured language query and expected in response to the first structured language query if the data source supports the first particularity; determining that the second query result does not match the second expected query result that is associated with the second structured language query and expected in response to the second structured language query if the data source supports a second particularity rather than the first particularity; and in response to the determining that the first query result matches the first expected query result that is associated with the first structured language query and expected in response to the first structured language query if the data source supports the first particularity, adding, to a query language configuration parameter file associated with the data source, the one of the plurality of query language configuration parameters in association with the first value. 2. A method according to claim 1 , further comprising: in response to the determining that the second query result does not match the second expected query result, determining to not associate the one of the plurality of query language configuration parameters with the second value in the query language configuration parameter file associated with the data source.

10. A system for providing data based on object relevance, comprising: a memory to store executable instructions; a processor to execute the executable instructions stored in the memory, the executable instructions including: a communications interface to be displayed on at least one computing device, the communications interface configured to receive one or more query terms from a user; a ratings module in communication with the communications interface, the ratings module configured to determine a preliminary relevance of one or more objects associated with an enterprise system based on the query terms, to assign at least one rating to the one or more objects based on the preliminary relevance, to propogate the preliminary relevance among the one or more objects; and to establish an overall relevance of the one or more objects based on the at least one rating, utilizing the preliminary relevance and the propogation; a search results module in communication with the ratings module, the search results module configured to rank the one or more objects according to the overall relevance and to provide data as search results comprising the one or more objects according to the ranking to the user; and a filtering engine configured to filter the search results based on a selected, dynamically generated filter and to transmit to display the filtered search results to the at least one computing device via the communications interface.

10. A system for providing data based on object relevance, comprising: a memory to store executable instructions; a processor to execute the executable instructions stored in the memory, the executable instructions including: a communications interface to be displayed on at least one computing device, the communications interface configured to receive one or more query terms from a user; a ratings module in communication with the communications interface, the ratings module configured to determine a preliminary relevance of one or more objects associated with an enterprise system based on the query terms, to assign at least one rating to the one or more objects based on the preliminary relevance, to propogate the preliminary relevance among the one or more objects; and to establish an overall relevance of the one or more objects based on the at least one rating, utilizing the preliminary relevance and the propogation; a search results module in communication with the ratings module, the search results module configured to rank the one or more objects according to the overall relevance and to provide data as search results comprising the one or more objects according to the ranking to the user; and a filtering engine configured to filter the search results based on a selected, dynamically generated filter and to transmit to display the filtered search results to the at least one computing device via the communications interface. 11. The system recited in claim 10 , wherein the filtering engine is further configured to filter the data according to one or more virtual domains.

1. A method for double programming a multi-level-cell (MLC) in a multi-bit-cell (MBC) of a charge trapping memory, the charge trapping memory having an array of charge trapping memory cells connecting to a plurality of word lines, each word line is connected to a plurality of charge trapping memory cells, each charge trapping memory cell having a first trapping site and a second trapping site, comprising: receiving a data pattern including a plurality of programming levels; during a first programming phase, conducting a first program operation and a first program-verify operation to a plurality of charge trapping memory cells along a word line, the first program operation programming the plurality of charge trapping memory cells along the word line to first voltage program levels that are less than corresponding predetermined program voltage levels, the first program-verify operation verifying charge trapping memory cells in the plurality of charge trapping memory cells along the word line to first voltage verifying levels that are less than corresponding predetermined program-verify levels; and during a second programming phase, conducting a second programming operation and a second program-verify operation of the plurality of charge trapping memory cells along the word line, the second programming operation programming the plurality of charge trapping memory cells along the word line to second voltage programming levels that are substantially equal to the predetermined program voltage levels, the second program-verify operation verifying the plurality of charge trapping memory cells along the word line to second voltage verifying levels that substantially equal to the predetermined program-verify levels.

1. A method for double programming a multi-level-cell (MLC) in a multi-bit-cell (MBC) of a charge trapping memory, the charge trapping memory having an array of charge trapping memory cells connecting to a plurality of word lines, each word line is connected to a plurality of charge trapping memory cells, each charge trapping memory cell having a first trapping site and a second trapping site, comprising: receiving a data pattern including a plurality of programming levels; during a first programming phase, conducting a first program operation and a first program-verify operation to a plurality of charge trapping memory cells along a word line, the first program operation programming the plurality of charge trapping memory cells along the word line to first voltage program levels that are less than corresponding predetermined program voltage levels, the first program-verify operation verifying charge trapping memory cells in the plurality of charge trapping memory cells along the word line to first voltage verifying levels that are less than corresponding predetermined program-verify levels; and during a second programming phase, conducting a second programming operation and a second program-verify operation of the plurality of charge trapping memory cells along the word line, the second programming operation programming the plurality of charge trapping memory cells along the word line to second voltage programming levels that are substantially equal to the predetermined program voltage levels, the second program-verify operation verifying the plurality of charge trapping memory cells along the word line to second voltage verifying levels that substantially equal to the predetermined program-verify levels. 6. The method of claim 1 , wherein the second program and second program-verify operations during the second programming phase are conducted in a sequential order, comprising: programming one or more of the plurality of charge trapping memory cells along the word line to a first program level; verifying one or more of the plurality of charge trapping memory cells along the word line to a first program-verify level (PV 1 B); programming one or more of the plurality of charge trapping memory cells along the word line to a second program level; verifying one or more of the plurality of charge trapping memory cells along the word line to a second program-verify level (PV 2 B); programming one or more of the plurality of charge trapping memory cells along the word line to third program level; and verifying one or more of the plurality of charge trapping memory cells along the word line to a third program-verify level (PV 3 B).

10. A system comprising: one or more computers configured to perform operations comprising: receiving a collection of documents; for each document of the collection of documents: breaking the document into pieces of text, and extracting n+k-grams from each piece of text separately such that each n+k-gram does not overlap; using the extracted n+k-grams for each document as a collection of candidate phrases for a given topic; assigning weights to the candidate phrases; and generating a linear classifier using the weighted candidate phrases, wherein the linear classifier varies the weights for each phrase candidate depending on the length of a document being classified.

10. A system comprising: one or more computers configured to perform operations comprising: receiving a collection of documents; for each document of the collection of documents: breaking the document into pieces of text, and extracting n+k-grams from each piece of text separately such that each n+k-gram does not overlap; using the extracted n+k-grams for each document as a collection of candidate phrases for a given topic; assigning weights to the candidate phrases; and generating a linear classifier using the weighted candidate phrases, wherein the linear classifier varies the weights for each phrase candidate depending on the length of a document being classified. 11. The system of claim 10 , wherein breaking the document into pieces of text comprises breaking document text at each HTML structure tag in the document.

1. A software transformation system executed on one or more computing devices and configured to transform a legacy computer application into a new computer application, the software transformation system comprising: a business asset extraction sub-system configured to receive as input data representing the legacy computer application, the business asset extraction sub-system comprising: a mechanical model formation tool configured to: scan the legacy computer application to identify mechanical assets of the legacy computer application, including one or more of system interface objects, computer programs, data access points, and a physical data model configured to store data records utilized by the legacy computer application; parse the legacy computer application into identifiable segments; and during the parsing, tag mechanical assets of the legacy computer application with associated meta language identifier information; assign mechanical nodes to the tagged mechanical assets based on the meta language identifier information; linking the mechanical nodes to create a mechanical fabric representing computer-implemented operations of the legacy computer application; wherein the mechanical fabric includes a network of mechanical nodes, each mechanical node being placed at a tagged mechanical asset, and associations between the mechanical nodes; a semantic model formation tool configured to: identify as semantic assets a plurality of steps of a use case of a business process according to which a user interacts with the legacy computer application, the steps including one or more observable system interactions during which the user interacts with respective system interface objects of the mechanical fabric; parse the semantic assets; and during the parsing, tag each semantic asset with associated meta language identifier information; assign semantic nodes to the tagged semantic assets based on the associated meta language identifier information; linking the semantic asset nodes to create a semantic model representing operator-perceived meanings attached to interactions with the legacy application, wherein the semantic model includes a network of semantic nodes, each semantic node being placed at a tagged semantic asset, and associations between the semantic nodes; an ontological linking tool configured to create links between related mechanical nodes and semantic nodes, based on the meta language identifier information associated with each of the mechanical nodes and semantic nodes, at least some of the links being between mechanical nodes that represent system interface objects and semantic nodes that represent observable system interactions with corresponding system interface objects; and an asset-specific graphical generator to generate a graphical view of the links identified by the ontological linking tool as being between related mechanical nodes created by the mechanical model formation tool and semantic nodes created by the semantic model formation tool; a modernization and streamlining sub-system configured to process output of the business asset extraction sub-system to remove obsolete business rules from the collection of business rules to produce a collection of relevant business rules; and a model and standards development sub-system configured to process output of the modernization and streamlining sub-system to output a new computer application based on the collection of relevant business rules.

1. A software transformation system executed on one or more computing devices and configured to transform a legacy computer application into a new computer application, the software transformation system comprising: a business asset extraction sub-system configured to receive as input data representing the legacy computer application, the business asset extraction sub-system comprising: a mechanical model formation tool configured to: scan the legacy computer application to identify mechanical assets of the legacy computer application, including one or more of system interface objects, computer programs, data access points, and a physical data model configured to store data records utilized by the legacy computer application; parse the legacy computer application into identifiable segments; and during the parsing, tag mechanical assets of the legacy computer application with associated meta language identifier information; assign mechanical nodes to the tagged mechanical assets based on the meta language identifier information; linking the mechanical nodes to create a mechanical fabric representing computer-implemented operations of the legacy computer application; wherein the mechanical fabric includes a network of mechanical nodes, each mechanical node being placed at a tagged mechanical asset, and associations between the mechanical nodes; a semantic model formation tool configured to: identify as semantic assets a plurality of steps of a use case of a business process according to which a user interacts with the legacy computer application, the steps including one or more observable system interactions during which the user interacts with respective system interface objects of the mechanical fabric; parse the semantic assets; and during the parsing, tag each semantic asset with associated meta language identifier information; assign semantic nodes to the tagged semantic assets based on the associated meta language identifier information; linking the semantic asset nodes to create a semantic model representing operator-perceived meanings attached to interactions with the legacy application, wherein the semantic model includes a network of semantic nodes, each semantic node being placed at a tagged semantic asset, and associations between the semantic nodes; an ontological linking tool configured to create links between related mechanical nodes and semantic nodes, based on the meta language identifier information associated with each of the mechanical nodes and semantic nodes, at least some of the links being between mechanical nodes that represent system interface objects and semantic nodes that represent observable system interactions with corresponding system interface objects; and an asset-specific graphical generator to generate a graphical view of the links identified by the ontological linking tool as being between related mechanical nodes created by the mechanical model formation tool and semantic nodes created by the semantic model formation tool; a modernization and streamlining sub-system configured to process output of the business asset extraction sub-system to remove obsolete business rules from the collection of business rules to produce a collection of relevant business rules; and a model and standards development sub-system configured to process output of the modernization and streamlining sub-system to output a new computer application based on the collection of relevant business rules. 2. The software transformation system of claim 1 , wherein the mechanical fabric is generated using a programming meta-language generator.

10. A system to evaluate data efficacy across an enterprise, comprising: a processor; a display device coupled to said processor; one or more non-transitory computer memories coupled to said processor storing program instructions executable by said processor to implement a data center analytics and dashboard configured to: access a set of data sources over a communications network that comprise at least one of structured and unstructured data artifacts; index the set of data sources; generate a plurality of analytics about the data sources based on the indexing, wherein the analytics include a plurality of: a document originality analytic that evaluates originality of data within a corpus of documents; a corpus storage volume analytic that provides metrics based on a relative value of data based on facts extracted from the data sources versus facts inferred from the data sources using at least one of models, logic and rules; a data source ingest analytic that identifies growth in at least one of ingest rates and update rates; a document type analytic that uses document metadata to analyze types of documents in the corpus of documents and provide metrics depicting a number of documents of each of the types in the corpus of documents; and an analysis analytic that identifies top entity-to-entity relationships across a set of the data sources; and display, on said display device, an interactive visualization of results based on the analytics, wherein the visualization comprises at least one of: a histogram, a graph, a timeline, a panel, a list, a chart, a popup, and a table.

10. A system to evaluate data efficacy across an enterprise, comprising: a processor; a display device coupled to said processor; one or more non-transitory computer memories coupled to said processor storing program instructions executable by said processor to implement a data center analytics and dashboard configured to: access a set of data sources over a communications network that comprise at least one of structured and unstructured data artifacts; index the set of data sources; generate a plurality of analytics about the data sources based on the indexing, wherein the analytics include a plurality of: a document originality analytic that evaluates originality of data within a corpus of documents; a corpus storage volume analytic that provides metrics based on a relative value of data based on facts extracted from the data sources versus facts inferred from the data sources using at least one of models, logic and rules; a data source ingest analytic that identifies growth in at least one of ingest rates and update rates; a document type analytic that uses document metadata to analyze types of documents in the corpus of documents and provide metrics depicting a number of documents of each of the types in the corpus of documents; and an analysis analytic that identifies top entity-to-entity relationships across a set of the data sources; and display, on said display device, an interactive visualization of results based on the analytics, wherein the visualization comprises at least one of: a histogram, a graph, a timeline, a panel, a list, a chart, a popup, and a table. 17. The system of claim 10 , wherein the plurality of analytics includes an analysis analytic and said processor is further configured to: determine, using at least one of one or more models and logic, as well as entities, relationships, sentences, and derived content in the data artifacts to generate said analysis analytic; and generate statistics on the determined entities, relationships, sentences, and derived content across the data artifacts, wherein the visualization further comprises a depiction of the statistics, such as top entities, top relationships, top data artifacts based on the derived content, and top sentences.

1. A system comprising: a first computer-readable storage media having stored thereon a reference dictionary file data structure, the reference dictionary file data structure including terms parsed from a plurality of documents stored in a document repository, and terms parsed from a new document received by the system but not stored in the document repository, the plurality of documents and the new document parsed without regard to any user profile, a user profile updated based at least in part on terms from the new document included in the reference dictionary file data structure and feedback from a user regarding relevance of a document received by the user before the system determines whether the new document is relevant to any user, the user profile specifying one or more areas of interest of the user; the first computer-readable storage media having stored thereon a parsed term data structure, the parsed term data structure including a one or more parsed terms and a term selection value associated with each of the one or more parsed terms, each of the parsed terms either: present in the reference dictionary file data structure indicating at least one document indicated as relevant to the user contains the term, or present in an original user profile, at least one of the parsed terms present in an original user profile and not present in the reference dictionary file data, the term selection value used for determining whether the associated term is to be included in the undated user profile; and a second computer-readable storage media having stored thereon a document dictionary index data structure and the document repository, the document dictionary index data structure including only terms located in the plurality of documents stored in the document repository.

1. A system comprising: a first computer-readable storage media having stored thereon a reference dictionary file data structure, the reference dictionary file data structure including terms parsed from a plurality of documents stored in a document repository, and terms parsed from a new document received by the system but not stored in the document repository, the plurality of documents and the new document parsed without regard to any user profile, a user profile updated based at least in part on terms from the new document included in the reference dictionary file data structure and feedback from a user regarding relevance of a document received by the user before the system determines whether the new document is relevant to any user, the user profile specifying one or more areas of interest of the user; the first computer-readable storage media having stored thereon a parsed term data structure, the parsed term data structure including a one or more parsed terms and a term selection value associated with each of the one or more parsed terms, each of the parsed terms either: present in the reference dictionary file data structure indicating at least one document indicated as relevant to the user contains the term, or present in an original user profile, at least one of the parsed terms present in an original user profile and not present in the reference dictionary file data, the term selection value used for determining whether the associated term is to be included in the undated user profile; and a second computer-readable storage media having stored thereon a document dictionary index data structure and the document repository, the document dictionary index data structure including only terms located in the plurality of documents stored in the document repository. 4. A system as defined in claim 1 , the parsed term data structure further including an original profile indicator associated with each of the parsed terms in the parsed term data structure, each original profile indicator indicating whether a parsed term associated therewith is present in a specified user profile.

6. The method of claim 1 , wherein storing the entity-key association strings and the association value IDs in the shards includes: creating a first in-memory object in a processing system to store the entity-key association strings; creating a second in-memory object to store the association value IDs.

6. The method of claim 1 , wherein storing the entity-key association strings and the association value IDs in the shards includes: creating a first in-memory object in a processing system to store the entity-key association strings; creating a second in-memory object to store the association value IDs. 9. The method of claim 6 , wherein distributing the shards to the servers includes: splitting the first in-memory object and the second in-memory object into the shards, wherein each of the shards includes a subset of the entity-key associations from the first in-memory object and corresponding association value IDs from the second in-memory object; and loading the shards into a memory of each of the servers.

10. A content selection system, comprising: a sampler configured to sample frequency data from a plurality of content and to generate static visual representations based on the sampled frequency data; a filter configured to capture intensity differences represented in the static visual representations and to generate filtered representations of the plurality of content; an encoder configured to encode the filtered representations and to create digitized representations of the plurality of content based on the encoded filtered representations; an analyzer configured to identify characteristics within the digitized representations that correspond to a plurality of moods and to generate three-dimensional shapes that correspond to the plurality of moods; and a user interface configured to enable a user to view the three-dimensional shapes and to select content from the plurality of content based on the three-dimensional shapes.

10. A content selection system, comprising: a sampler configured to sample frequency data from a plurality of content and to generate static visual representations based on the sampled frequency data; a filter configured to capture intensity differences represented in the static visual representations and to generate filtered representations of the plurality of content; an encoder configured to encode the filtered representations and to create digitized representations of the plurality of content based on the encoded filtered representations; an analyzer configured to identify characteristics within the digitized representations that correspond to a plurality of moods and to generate three-dimensional shapes that correspond to the plurality of moods; and a user interface configured to enable a user to view the three-dimensional shapes and to select content from the plurality of content based on the three-dimensional shapes. 19. The content selection system as recited in claim 10 , wherein the plurality of content includes video that includes music.

12. A method comprising: receiving, by a virtual machine monitor of a computing device, a request to start an applet from a first virtual domain of a set of virtual domains provided by the virtual machine monitor; creating, by the virtual machine monitor, a second virtual domain for running the applet; incorporate a byte code interpreter in address space of a kernel of an operating system of the second virtual domain, the operating system of the second virtual domain, to run byte code interpreted applications comprising at least the applet using the byte code interpreter, wherein the kernel to access hardware of the computer through a platform independent interface provided by the virtual machine monitor; and starting, by the virtual machine monitor, the applet in the second virtual domain, wherein the applet runs in the operating system of the second virtual domain.

12. A method comprising: receiving, by a virtual machine monitor of a computing device, a request to start an applet from a first virtual domain of a set of virtual domains provided by the virtual machine monitor; creating, by the virtual machine monitor, a second virtual domain for running the applet; incorporate a byte code interpreter in address space of a kernel of an operating system of the second virtual domain, the operating system of the second virtual domain, to run byte code interpreted applications comprising at least the applet using the byte code interpreter, wherein the kernel to access hardware of the computer through a platform independent interface provided by the virtual machine monitor; and starting, by the virtual machine monitor, the applet in the second virtual domain, wherein the applet runs in the operating system of the second virtual domain. 14. The method of claim 12 , wherein receiving the request to start the applet comprises receiving a request to start a C# applet.

7. A computer-readable storage medium containing a program which, when executed by a processor, performs a process of creating queries querying physical data logically represented by a data abstraction model, the process comprising: receiving an abstract query including logical fields against physical data in a database, the logical fields contained in the abstract query defined by the data abstraction model; determining that the data abstraction model includes logical links associated with the logical fields contained in the abstract query, wherein the logical links define relationships between the associated logical fields and other logical fields; and then: retrieving the associated logical links; and transforming the abstract query into an executable query capable of being executed formatted for execution against the physical data, wherein the transforming is done using the data abstraction model and the retrieved associated logical links.

7. A computer-readable storage medium containing a program which, when executed by a processor, performs a process of creating queries querying physical data logically represented by a data abstraction model, the process comprising: receiving an abstract query including logical fields against physical data in a database, the logical fields contained in the abstract query defined by the data abstraction model; determining that the data abstraction model includes logical links associated with the logical fields contained in the abstract query, wherein the logical links define relationships between the associated logical fields and other logical fields; and then: retrieving the associated logical links; and transforming the abstract query into an executable query capable of being executed formatted for execution against the physical data, wherein the transforming is done using the data abstraction model and the retrieved associated logical links. 9. The computer-readable medium of claim 7 , wherein determining whether the data abstraction model includes the associated logical links comprises: determining whether one or more result fields of the abstract query are included with a category specification including a logical link.

16. The apparatus of claim 10 , wherein the at least one processor executes the instructions to identify the at least one token to be rendered with contrastive stress at least in part by: identifying at least one linking token in the text input indicating applicability of contrastive stress; and based at least in part on the at least one linking token, identifying the at least one token to be rendered with contrastive stress.

16. The apparatus of claim 10 , wherein the at least one processor executes the instructions to identify the at least one token to be rendered with contrastive stress at least in part by: identifying at least one linking token in the text input indicating applicability of contrastive stress; and based at least in part on the at least one linking token, identifying the at least one token to be rendered with contrastive stress. 17. The apparatus of claim 16 , wherein the at least one linking token comprises at least one sequence of one or more tokens selected from the group consisting of: originally, but, is now, or, and, whereas, as opposed to, as compared with, as contrasted with, and versus.

1. A computer-implemented method for developing semantic relationships between elements distilled from content of a document to generate a semantic representation of the content, the method comprising: identifying, by way of a computing device having a processor and memory, a text portion of the document; determining semantic information for a plurality of elements identified in the text portion, the semantic information including one or more of meanings of the identified elements or grammatical functions of the identified elements; identifying at least one of the identified elements as a subject of the text portion; determining a plurality of levels of association from the text portion and identifying at least one of the identified elements as a reporting act corresponding to an attitude report for each of the plurality of levels of association, the reporting act identified based on a set of rules that utilizes, in part, surrounding text, wherein the attitude report describes the subject's attitude toward a particular topic of the text portion; based on the determined semantic information for the identified elements, associating the identified elements so that each association of identified elements represents a certain semantic relationship; generating, by way of the computing device, a semantic representation that represents the associations, by way of relational elements that describe the associations, of the identified elements to one another; and indexing the semantic representation, including the identified elements and the relational elements, in an index for retrieval, the index being searchable and including pointers from the semantic representation to its associated text portion.

1. A computer-implemented method for developing semantic relationships between elements distilled from content of a document to generate a semantic representation of the content, the method comprising: identifying, by way of a computing device having a processor and memory, a text portion of the document; determining semantic information for a plurality of elements identified in the text portion, the semantic information including one or more of meanings of the identified elements or grammatical functions of the identified elements; identifying at least one of the identified elements as a subject of the text portion; determining a plurality of levels of association from the text portion and identifying at least one of the identified elements as a reporting act corresponding to an attitude report for each of the plurality of levels of association, the reporting act identified based on a set of rules that utilizes, in part, surrounding text, wherein the attitude report describes the subject's attitude toward a particular topic of the text portion; based on the determined semantic information for the identified elements, associating the identified elements so that each association of identified elements represents a certain semantic relationship; generating, by way of the computing device, a semantic representation that represents the associations, by way of relational elements that describe the associations, of the identified elements to one another; and indexing the semantic representation, including the identified elements and the relational elements, in an index for retrieval, the index being searchable and including pointers from the semantic representation to its associated text portion. 5. The method of claim 1 , further comprising: recognizing one or more entities within the text portion, wherein the one or more entities are recognized by searching a predefined list of words stored in a data store.

17. The system of claim 15 , wherein: the representation of the first actor comprises a first node; the representation of the suspicious event comprises a second node; the representation of the second actor comprises a third node; the first node and the second node are interconnected by a first edge; the second node and the third node are interconnected by a second edge.

17. The system of claim 15 , wherein: the representation of the first actor comprises a first node; the representation of the suspicious event comprises a second node; the representation of the second actor comprises a third node; the first node and the second node are interconnected by a first edge; the second node and the third node are interconnected by a second edge. 18. The system of claim 17 , wherein the adjusting module adjusts the suspiciousness score by: determining a prior probability distribution for each node in the event-correlation graph based at least in part on the suspiciousness score associated with the node for which the prior probability distribution is determined; iteratively propagating a probability among the nodes in the event-correlation graph that indicates whether the actor or suspicious event represented by the node is malicious by transmitting messages along the edges in the event-correlation graph, wherein a message transmitted by a transmitting node is generated based at least in part on the prior probability distribution of the transmitting node and messages received by the transmitting node from other nodes in the event-correlation graph during any previous iterations; adjusting the suspiciousness score associated with the node based at least in part on the probability that indicates whether the actor or suspicious event represented by the node is malicious.

10. A computer readable storage medium that is not a transient signal, the computer readable storage medium configured to store instructions that, when executed, provide for: defining in a role based access control (RBAC) store, scope data representing at least one scope wherein each scope represents a set of resources in a networked computing environment; providing in the RBAC store, role definition data defining at least one role, each role including a set of permissions that are assigned to principals in a given scope; and using the RBAC store for translating the at least one scope and the at least one enterprise role representing a role based access control (RBAC) policy to a resource authorization policy model, the RBAC policy mappable to at least one access control list (ACL) in the networked computing environment for configuring an underlying resource authorization policy.

10. A computer readable storage medium that is not a transient signal, the computer readable storage medium configured to store instructions that, when executed, provide for: defining in a role based access control (RBAC) store, scope data representing at least one scope wherein each scope represents a set of resources in a networked computing environment; providing in the RBAC store, role definition data defining at least one role, each role including a set of permissions that are assigned to principals in a given scope; and using the RBAC store for translating the at least one scope and the at least one enterprise role representing a role based access control (RBAC) policy to a resource authorization policy model, the RBAC policy mappable to at least one access control list (ACL) in the networked computing environment for configuring an underlying resource authorization policy. 11. The computer readable storage medium according to claim 10 , wherein the resource authorization policy addresses access control lists (ACEs) data structures.

1. A system comprising: computer-readable storage media having processor-executable instructions embodied therein; and a processor operatively coupled to the computer-readable storage media to execute the processor-executable instructions for implementing computer-executable components comprising: a clustering component that receives and clusters a plurality of emails, the clustering component automatically determining and creating topics for the emails by assigning key phrases extracted from the emails within one or more clusters, the topics being cohesive concepts relevant to a user associated with the emails; an organization component that utilizes the topics created from the emails to organize the emails and to also organize other documents of the user within a graphical user interface, the other documents having been stored in a data store separately from the emails and comprising at least one of word processing documents, spreadsheets, presentation files, video files, audio files or digital images; and an interface component that displays the topics defined by the clustering component and information pertaining to the organized emails and the other documents associated with the topics.

1. A system comprising: computer-readable storage media having processor-executable instructions embodied therein; and a processor operatively coupled to the computer-readable storage media to execute the processor-executable instructions for implementing computer-executable components comprising: a clustering component that receives and clusters a plurality of emails, the clustering component automatically determining and creating topics for the emails by assigning key phrases extracted from the emails within one or more clusters, the topics being cohesive concepts relevant to a user associated with the emails; an organization component that utilizes the topics created from the emails to organize the emails and to also organize other documents of the user within a graphical user interface, the other documents having been stored in a data store separately from the emails and comprising at least one of word processing documents, spreadsheets, presentation files, video files, audio files or digital images; and an interface component that displays the topics defined by the clustering component and information pertaining to the organized emails and the other documents associated with the topics. 9. The system of claim 1 , further comprising: an analysis component that reviews text in subject lines of the emails and creates a list of noun phrases; a supplement component that supplements the noun phrases with a set of words that appear in the noun phrases; and a counting component that counts a number of occurrences of the supplemented noun phrases in a body of an email.

1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule.

1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule. 7. The method according to claim 1 , further comprising: displaying on a display of said music symbol recognition apparatus the music symbol candidates of the at least one selected graph.

39. A system for managing attribute information, comprising: a data store, said data store comprises an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with a preferred language, determine whether the preferred language of a requesting user matches an installed language at the access management system, and in response to the preferred language not matching the installed language, perform an approximate language match based at least in part on a language code associated with the preferred language; the data store further comprises an entry comprising a plurality of multi-valued attributes, wherein the entry comprises a single data structure that includes the plurality of multi-valued attributes, said plurality of multi-valued attributes comprising a first multi-valued attribute having a plurality of language components and value components, each of said value components specifies a value for said first one multi-valued attribute that is associated with a corresponding language component, wherein said entry contains all available language components and value components for said multi-valued attribute; and at least one server in communication with said data store, said at least one server comprising at least one processor and code executable by said at least one processor, said processor readable code comprising: code for retrieving from the single data structure said first multi-valued attribute to generate a response to a request associated with said first multi-valued attribute, said request is associated with the preferred language, said response includes at least one first value for said first multi-valued attribute that corresponds to said preferred language.

39. A system for managing attribute information, comprising: a data store, said data store comprises an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with a preferred language, determine whether the preferred language of a requesting user matches an installed language at the access management system, and in response to the preferred language not matching the installed language, perform an approximate language match based at least in part on a language code associated with the preferred language; the data store further comprises an entry comprising a plurality of multi-valued attributes, wherein the entry comprises a single data structure that includes the plurality of multi-valued attributes, said plurality of multi-valued attributes comprising a first multi-valued attribute having a plurality of language components and value components, each of said value components specifies a value for said first one multi-valued attribute that is associated with a corresponding language component, wherein said entry contains all available language components and value components for said multi-valued attribute; and at least one server in communication with said data store, said at least one server comprising at least one processor and code executable by said at least one processor, said processor readable code comprising: code for retrieving from the single data structure said first multi-valued attribute to generate a response to a request associated with said first multi-valued attribute, said request is associated with the preferred language, said response includes at least one first value for said first multi-valued attribute that corresponds to said preferred language. 42. The system of claim 39 , wherein said processor readable code further comprises: code for reading said plurality of language components and value components for said first multi-valued attribute; and code for generating a table at said server, said table corresponds to said first multi-valued attribute, includes said plurality of language components and value components, and is indexed according to said plurality of language components.

7. A system comprising: at least one processor operable to execute: a search engine to process a search query specifying one or more keywords to identify listings satisfying the search query, each listing from the identified listings describing an item or service offered for sale and including a title and a price; a sorting engine to organize the identified listings based on a composite relevance score assigned to each listing from the identified listings, the composite relevance score derived as a sum of relevance scores respectively associated with each keyword from the one or more keywords appearing in a listing from the identified listings, each relevance score representing a customer desirability measure for a keyword in the listing, the customer desirability measure determined based on a calculated difference between a measure of customer demand and supply for the keyword; a relevance engine to derive the measure of customer demand for the keyword as the percentage of listings that i) are selected by a user over a period of time, and ii) have titles including words that match keywords specified in the search query; a keyword engine to derive the measure of supply for the keyword as the percentage of listings satisfying the search query that include the keyword; and an output module to display the organized listings.

7. A system comprising: at least one processor operable to execute: a search engine to process a search query specifying one or more keywords to identify listings satisfying the search query, each listing from the identified listings describing an item or service offered for sale and including a title and a price; a sorting engine to organize the identified listings based on a composite relevance score assigned to each listing from the identified listings, the composite relevance score derived as a sum of relevance scores respectively associated with each keyword from the one or more keywords appearing in a listing from the identified listings, each relevance score representing a customer desirability measure for a keyword in the listing, the customer desirability measure determined based on a calculated difference between a measure of customer demand and supply for the keyword; a relevance engine to derive the measure of customer demand for the keyword as the percentage of listings that i) are selected by a user over a period of time, and ii) have titles including words that match keywords specified in the search query; a keyword engine to derive the measure of supply for the keyword as the percentage of listings satisfying the search query that include the keyword; and an output module to display the organized listings. 10. The system of claim 7 , further comprising a relevance engine to derive the measure of demand for the keyword in the title of the listing as the percentage of all search queries received over a period of time that include the keyword.

11. A computer system, comprising: an input interface operable to parse a high-level language program, the high-level language program configured to run on a central processing unit, wherein the input interface is operable to identify a functional block count included in the high-level language program, wherein the functional block count is associated with a code sequence in the high-level language program; a processor operable to generate hardware acceleration logic for implementing the code sequence using the functional block count, wherein the functional block count specifies the number of functional blocks to use to implement the code sequence on a programmable chip.

11. A computer system, comprising: an input interface operable to parse a high-level language program, the high-level language program configured to run on a central processing unit, wherein the input interface is operable to identify a functional block count included in the high-level language program, wherein the functional block count is associated with a code sequence in the high-level language program; a processor operable to generate hardware acceleration logic for implementing the code sequence using the functional block count, wherein the functional block count specifies the number of functional blocks to use to implement the code sequence on a programmable chip. 16. The computer system of claim 11 , wherein generating hardware acceleration logic includes generating HDL.

4. A computer-implemented method for operating an interactive response system comprising: receiving data representing an input from a person; using a processor, automatically presenting information relating to the input to an intent analyst through a graphical analyst user interface, the information presented in the graphical analyst user interface comprising at least one of: an output produced responsive to the received data, location information corresponding to the person, historical information corresponding to the person, characteristics of the person, and prior interactions with the person; accepting an intent from the intent analyst through the analyst user interface; providing the information and the intent to a training subsystem; accepting from the training subsystem a training model used by a training automated speech recognizer (ASR), the training ASR generated responsive to the information and the intent; accepting from the training ASR statistics generated responsive to the information; and training, via the statistics, a second model used by a real-time ASR in order to improve performance thereof.

4. A computer-implemented method for operating an interactive response system comprising: receiving data representing an input from a person; using a processor, automatically presenting information relating to the input to an intent analyst through a graphical analyst user interface, the information presented in the graphical analyst user interface comprising at least one of: an output produced responsive to the received data, location information corresponding to the person, historical information corresponding to the person, characteristics of the person, and prior interactions with the person; accepting an intent from the intent analyst through the analyst user interface; providing the information and the intent to a training subsystem; accepting from the training subsystem a training model used by a training automated speech recognizer (ASR), the training ASR generated responsive to the information and the intent; accepting from the training ASR statistics generated responsive to the information; and training, via the statistics, a second model used by a real-time ASR in order to improve performance thereof. 6. The computer-implemented method of claim 4 , wherein the training comprises testing performance of the real-time ASR and continuing training responsive to the performance not exceeding a performance threshold.

14. An apparatus for identifying domain name abuse in web-based content to secure a computer, comprising: a memory comprising a rule information module having at least one rule for replacing characters to modify a first domain name; a replacement module for: converting the first domain name into a second domain name using the at least one rule, wherein the first domain name is an imitation of the second domain name and the second domain name is associated with a brand being imitated by the first domain name; identifying the brand being imitated by the first domain name that is associated with the second domain name; and classifying web-based content as fraud based at least in part on the identified brand.

14. An apparatus for identifying domain name abuse in web-based content to secure a computer, comprising: a memory comprising a rule information module having at least one rule for replacing characters to modify a first domain name; a replacement module for: converting the first domain name into a second domain name using the at least one rule, wherein the first domain name is an imitation of the second domain name and the second domain name is associated with a brand being imitated by the first domain name; identifying the brand being imitated by the first domain name that is associated with the second domain name; and classifying web-based content as fraud based at least in part on the identified brand. 18. The apparatus of claim 14 , wherein the rule information comprises a rule for removing a first character of the first domain name, wherein the removed first character is used to imitate the second domain name.

1. A computer-implemented method comprising: applying training documents to links in a current generative model that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, to determine a respective expected count for each of the links; selecting, from the links that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, a first subset of one or more links that are each associated with more than a predetermined number of sources of the training documents; for each selected link of the first subset, determining (i) a significance of the link, and (ii) a link rating for the link based on the expected count for the link and the significance; ranking the selected links of the first subset based on the link ratings; selecting a second subset of the ranked links; and generating a new generative model using only the selected links of the second subset, without using any of the links in the current generative model that were not selected for the second subset.

1. A computer-implemented method comprising: applying training documents to links in a current generative model that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, to determine a respective expected count for each of the links; selecting, from the links that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, a first subset of one or more links that are each associated with more than a predetermined number of sources of the training documents; for each selected link of the first subset, determining (i) a significance of the link, and (ii) a link rating for the link based on the expected count for the link and the significance; ranking the selected links of the first subset based on the link ratings; selecting a second subset of the ranked links; and generating a new generative model using only the selected links of the second subset, without using any of the links in the current generative model that were not selected for the second subset. 4. The method of claim 1 , wherein applying training documents to links in a current generative model that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, to determine a respective expected count for each of the links further comprises: applying training documents to prospective links in a current generative model that each connect a respective terminal node that represents a corresponding word to a respective cluster node that represents a corresponding cluster of conceptually related words, to determine a respective expected count for each of the prospective links.

1. A system comprising: a plurality of speakers; and a media device for playing a movie having a first audio content for the movie in a first language and a second audio content for the movie in a second language different than the first language, the media device including: a memory configured to store an audio application; a processor configured to execute the audio application to: obtain a first position of a first user of a first user device with respect to each of the plurality of speakers; obtain a second position of a second user of a second user device with respect to each of the plurality of speakers; play, during the playing of the movie and using first one or more of the plurality of speakers, the first audio content for the movie in the first language, based on the first position of the first user of the first user device with respect to each of the plurality of speakers; and play, during the playing of the movie and using second one or more of the plurality of speakers, the second audio content for the movie in the second language, based on the second position of the second user of the second user device with respect to each of the plurality of speakers.

1. A system comprising: a plurality of speakers; and a media device for playing a movie having a first audio content for the movie in a first language and a second audio content for the movie in a second language different than the first language, the media device including: a memory configured to store an audio application; a processor configured to execute the audio application to: obtain a first position of a first user of a first user device with respect to each of the plurality of speakers; obtain a second position of a second user of a second user device with respect to each of the plurality of speakers; play, during the playing of the movie and using first one or more of the plurality of speakers, the first audio content for the movie in the first language, based on the first position of the first user of the first user device with respect to each of the plurality of speakers; and play, during the playing of the movie and using second one or more of the plurality of speakers, the second audio content for the movie in the second language, based on the second position of the second user of the second user device with respect to each of the plurality of speakers. 9. The system of claim 1 , wherein the first audio content includes a dialog in a user selected language.

1. A computer-implemented system for identifying relevant documents for display, comprising: themes for a set of documents; an extraction module to extract noun phrases from the documents as concepts; a theme generator to group two or more of the concepts as one such theme; a frequency table that identifies each of the concepts and a frequency of occurrence of each concept within each of the documents in the set; a graph generator to generate a graph of the concepts, comprising: an x-axis of the graph defining the concepts; a y-axis of the graph defining a number of the documents that reference each concept; and a mapping module to map the concepts on the graph in order of descending number of referring documents; a cluster module to cluster the documents based on the themes; a matrix for the documents comprising an inner product of document frequency occurrences and cluster concept weightings for each theme; an identification module to identify from the matrix, documents most relevant to a particular theme; and a display to present the relevant documents.

1. A computer-implemented system for identifying relevant documents for display, comprising: themes for a set of documents; an extraction module to extract noun phrases from the documents as concepts; a theme generator to group two or more of the concepts as one such theme; a frequency table that identifies each of the concepts and a frequency of occurrence of each concept within each of the documents in the set; a graph generator to generate a graph of the concepts, comprising: an x-axis of the graph defining the concepts; a y-axis of the graph defining a number of the documents that reference each concept; and a mapping module to map the concepts on the graph in order of descending number of referring documents; a cluster module to cluster the documents based on the themes; a matrix for the documents comprising an inner product of document frequency occurrences and cluster concept weightings for each theme; an identification module to identify from the matrix, documents most relevant to a particular theme; and a display to present the relevant documents. 4. A system according to claim 1 , further comprising: a value determination module to identify a median value of the frequencies of occurrence along the x-axis; a threshold module to set edge conditions based on the frequencies of occurrence; and a selection module to select those documents with concepts that fall within the edge conditions as forming a subset of documents that include latent concepts.

11. A method for printing and interacting with a document, said method comprising the steps of: receiving, in a computer system, a request for printing said document, said document containing visible information; allocating a document identity to said document; determining coded data for said document, said coded data encoding a plurality of locations on said document and identifying said document identity; sending print data to a printer; printing the document so that the printed document includes said visible information superimposed with said coded data, said visible information and said coded data being printed at the same time by a printer connected to the computer system; interacting with the printed document using an optically imaging pen; imaging at least some of the printed coded data; generating indicating data using the sensed coded data, said indicating data identifying the document identity and a position of the pen relative to the printed document; sending the indicating to the computer system; and interpreting the indicating data using a stored page description retrievable using said document identity contained in said indicating data.

11. A method for printing and interacting with a document, said method comprising the steps of: receiving, in a computer system, a request for printing said document, said document containing visible information; allocating a document identity to said document; determining coded data for said document, said coded data encoding a plurality of locations on said document and identifying said document identity; sending print data to a printer; printing the document so that the printed document includes said visible information superimposed with said coded data, said visible information and said coded data being printed at the same time by a printer connected to the computer system; interacting with the printed document using an optically imaging pen; imaging at least some of the printed coded data; generating indicating data using the sensed coded data, said indicating data identifying the document identity and a position of the pen relative to the printed document; sending the indicating to the computer system; and interpreting the indicating data using a stored page description retrievable using said document identity contained in said indicating data. 15. The method of claim 11 , wherein said pen comprises a transceiver for communicating the indicating data to the computer system.

1. A computer readable storage device having computer readable program instructions embodied thereon for programming a processor, said instructions consisting of: a computer software application manifesting an entirely declarative system for creating a software program comprising properties for declaratively establishing relationships between data elements, said relationships comprising descriptions of logic and data, wherein said entirely declarative system comprises one or more declarative lattice structures, each respective lattice having a plurality of configurable constructs comprising: (i) one or more declarative attributes, each attribute configurable to select an internal behavior of said respective lattice; (ii) one or more declarative data access sites, each site configurable to define respective data access points for accessing lattices external to said respective lattice, and wherein said attributes and data access sites configure each said respective lattice to complete a singular computing task, and each respective lattice is configured to instantiate and execute, either alone or in relation to other lattices of said declarative system.

1. A computer readable storage device having computer readable program instructions embodied thereon for programming a processor, said instructions consisting of: a computer software application manifesting an entirely declarative system for creating a software program comprising properties for declaratively establishing relationships between data elements, said relationships comprising descriptions of logic and data, wherein said entirely declarative system comprises one or more declarative lattice structures, each respective lattice having a plurality of configurable constructs comprising: (i) one or more declarative attributes, each attribute configurable to select an internal behavior of said respective lattice; (ii) one or more declarative data access sites, each site configurable to define respective data access points for accessing lattices external to said respective lattice, and wherein said attributes and data access sites configure each said respective lattice to complete a singular computing task, and each respective lattice is configured to instantiate and execute, either alone or in relation to other lattices of said declarative system. 2. The computer readable storage device of claim 1 , wherein said one or more sites define said respective data access points for programming structures internal to said respective declarative lattice structure.

16. The apparatus as defined by claim 15, wherein said translator further identifies said predefined characters in said target language which are represented using multiple bytes.

16. The apparatus as defined by claim 15, wherein said translator further identifies said predefined characters in said target language which are represented using multiple bytes. 17. The apparatus as defined by claim 16, wherein said translator represents said predefined characters requiring multiple bytes as a string of ASCII characters, the beginning and ending of said string of ASCII characters requiring multiple bytes identified by a flag character.

9. A computer-implemented method comprising: generating a model of a business application; generating Java classes based on the model of the business application; executing, using a Java virtual machine, machine code based on the Java classes; detecting a problem in the executing machine code; generating debugging data associated with the problem; generating a model-oriented debugging view of the business application based on the model of the business application; translating the debugging data into the model-oriented debugging view; identifying a model element of the model associated with the problem based on the debugging data in the model-oriented debugging view by using a model identifier of the model and a model element identifier of the model element of the model; converting the model identifier and the model element identifier into a machine code resource identifier to generate a breakpoint in the model-oriented debugging view; translating the breakpoint in the model-oriented debugging view into the machine code according to the machine code resource identifier; and executing the machine code associated with the breakpoint to debug the business application at the breakpoint.

9. A computer-implemented method comprising: generating a model of a business application; generating Java classes based on the model of the business application; executing, using a Java virtual machine, machine code based on the Java classes; detecting a problem in the executing machine code; generating debugging data associated with the problem; generating a model-oriented debugging view of the business application based on the model of the business application; translating the debugging data into the model-oriented debugging view; identifying a model element of the model associated with the problem based on the debugging data in the model-oriented debugging view by using a model identifier of the model and a model element identifier of the model element of the model; converting the model identifier and the model element identifier into a machine code resource identifier to generate a breakpoint in the model-oriented debugging view; translating the breakpoint in the model-oriented debugging view into the machine code according to the machine code resource identifier; and executing the machine code associated with the breakpoint to debug the business application at the breakpoint. 11. A computer-implemented method in accordance with claim 9 , wherein converting the model identifier and the model element identifier into the machine code resource identifier further includes: determining a Java resource name based on the model identifier.

7. The system of claim 6 , wherein the identified additional terms are ranked based at least in part on a relationship network corresponding to the search query object.

7. The system of claim 6 , wherein the identified additional terms are ranked based at least in part on a relationship network corresponding to the search query object. 8. The system of claim 7 , wherein the scoring is further based on information included in a pre-existing knowledgebase.

1. A method, implemented by one or more processors in a computing system, for generating a multidimensional synopsis of a stream of textual data, the method comprising: accessing, by the one or more processors, a stream of textual data that includes a number of elements of textual data, each element of textual data comprising plain text content that is associated with an author and is directed to a particular subject; identifying, by the one or more processors, a first dimension and a second dimension for the stream of textual data, the first dimension including a number of concepts that each represent a subject attribute of the particular subject, the second dimension including a number of concepts that each represent an author attribute; processing, by the one or more processors, each of the number of elements of textual data to identify which of the concepts of the first and second dimension appear in the plain text content included in the element, and for each concept within the first dimension that appears in the plain text content included in the element, generating a quantitative value; and generating, by the one or more processors, the multidimensional synopsis of the stream of textual data by generating a score for each intersecting set of concepts from the corresponding quantitative values, each score representing a prevalence of the intersecting set of concepts within the stream of textual data.

1. A method, implemented by one or more processors in a computing system, for generating a multidimensional synopsis of a stream of textual data, the method comprising: accessing, by the one or more processors, a stream of textual data that includes a number of elements of textual data, each element of textual data comprising plain text content that is associated with an author and is directed to a particular subject; identifying, by the one or more processors, a first dimension and a second dimension for the stream of textual data, the first dimension including a number of concepts that each represent a subject attribute of the particular subject, the second dimension including a number of concepts that each represent an author attribute; processing, by the one or more processors, each of the number of elements of textual data to identify which of the concepts of the first and second dimension appear in the plain text content included in the element, and for each concept within the first dimension that appears in the plain text content included in the element, generating a quantitative value; and generating, by the one or more processors, the multidimensional synopsis of the stream of textual data by generating a score for each intersecting set of concepts from the corresponding quantitative values, each score representing a prevalence of the intersecting set of concepts within the stream of textual data. 7. The method of claim 1 , wherein processing each of the number of elements of textual data to identify which of the concepts of the first and second dimension appear in the plain text content included in the element comprises performing natural language processing on the number of elements of textual data.

1. A method for managing scripts carried out in a script management server which is connected to a user terminal and manages script codes, the method comprising: preparing, by the script management server, a plurality of databases including a meta database and a plurality of script databases, wherein the script management server comprises at least one computing device; designating, by the script management server, an active script database by providing a plurality of original script lists to the user terminal; and storing, by the script management server, identifiers of the user terminal and the designated active script database in the meta database, wherein the plurality of script databases are classified according to script version and each of the plurality of script databases manages the original script code and user-specific script code, and wherein the meta database manages the plurality of original script lists related to the plurality of script databases and a list of user-specific scripts, if a script code in the active script database is updated through the user terminal, updating, by the script management server, a script list and script codes of the corresponding user stored in the meta database and the designated active script database, respectively, wherein the updating a script list and script codes of the corresponding user further comprises, if the script code is updated through the user terminal, updating the script in the plurality of script databases into a script of new version for the corresponding script.

1. A method for managing scripts carried out in a script management server which is connected to a user terminal and manages script codes, the method comprising: preparing, by the script management server, a plurality of databases including a meta database and a plurality of script databases, wherein the script management server comprises at least one computing device; designating, by the script management server, an active script database by providing a plurality of original script lists to the user terminal; and storing, by the script management server, identifiers of the user terminal and the designated active script database in the meta database, wherein the plurality of script databases are classified according to script version and each of the plurality of script databases manages the original script code and user-specific script code, and wherein the meta database manages the plurality of original script lists related to the plurality of script databases and a list of user-specific scripts, if a script code in the active script database is updated through the user terminal, updating, by the script management server, a script list and script codes of the corresponding user stored in the meta database and the designated active script database, respectively, wherein the updating a script list and script codes of the corresponding user further comprises, if the script code is updated through the user terminal, updating the script in the plurality of script databases into a script of new version for the corresponding script. 11. The method of claim 1 , further comprising transmitting a script list and part of script codes of the corresponding user to the user terminal as a database backup file read by the script management server.

9. The method as set forth in claim 8 wherein the combining overall weights for a literary element is bound within each associated segment by applying a mathematical weighting function to the one or more attributes.

9. The method as set forth in claim 8 wherein the combining overall weights for a literary element is bound within each associated segment by applying a mathematical weighting function to the one or more attributes. 10. The method as set forth in claim 9 wherein the correlating and matching further comprises calculating an overall weight for a literary element within a plurality of segments by applying a mathematical weighting function to one or more segment-bound overall weights.

13. A system comprising: at least one processor; and a computer readable medium having instructions thereon, the instructions comprising: instructions to perform, by the system, based on an outcome variable selected for modeling, a cascade of a plurality of filtering operations, wherein the plurality of filtering operations comprises a determination of a first subset of a plurality of variables having a probability of non-contribution less than a first value and a determination, based on cross products of the first subset of the plurality of variables, of a second subset of the plurality of variables having a probability of non-contribution less than a second value; instructions to determine, by the system, a subset of predictor variables from among the plurality of variables and a subset of excluded variables from among the plurality of variables; instructions to generate, by the system, a sample predictive model comprising a model of the outcome variable based on variables in the subset of predictor variables; instructions to receive, by the system, a request to change the subset of predictor variables, wherein the request to change the subset of predictor variables comprises at least one of a request to add one of the subset of excluded variables to the subset of predictor variables, a request to add a new variable to the subset of predictor variables, and a request to remove a variable from the subset of predictor variables; instructions to generate, by the system, a predictive model comprising a model of the outcome variable based on the variables in the changed subset of predictor variables, wherein the changed subset of predictor variables has fewer variables than the plurality of variables such that a dimensionality of the changed subset of predictor variables is different than a dimensionality of the plurality of variables; and instructions to output, by the system, the generated predictive model.

13. A system comprising: at least one processor; and a computer readable medium having instructions thereon, the instructions comprising: instructions to perform, by the system, based on an outcome variable selected for modeling, a cascade of a plurality of filtering operations, wherein the plurality of filtering operations comprises a determination of a first subset of a plurality of variables having a probability of non-contribution less than a first value and a determination, based on cross products of the first subset of the plurality of variables, of a second subset of the plurality of variables having a probability of non-contribution less than a second value; instructions to determine, by the system, a subset of predictor variables from among the plurality of variables and a subset of excluded variables from among the plurality of variables; instructions to generate, by the system, a sample predictive model comprising a model of the outcome variable based on variables in the subset of predictor variables; instructions to receive, by the system, a request to change the subset of predictor variables, wherein the request to change the subset of predictor variables comprises at least one of a request to add one of the subset of excluded variables to the subset of predictor variables, a request to add a new variable to the subset of predictor variables, and a request to remove a variable from the subset of predictor variables; instructions to generate, by the system, a predictive model comprising a model of the outcome variable based on the variables in the changed subset of predictor variables, wherein the changed subset of predictor variables has fewer variables than the plurality of variables such that a dimensionality of the changed subset of predictor variables is different than a dimensionality of the plurality of variables; and instructions to output, by the system, the generated predictive model. 14. The system of claim 13 , the instructions further comprising: instructions to receive, by the system, a request to change a dimensionality of a dataset; wherein the instructions to generate the predictive model comprise instructions to generate, by the system, the predictive model based on the request to change the dimensionality of the dataset.

1. A multimodal system, the system comprising: a speech detection module configured to detect audio; a speech recognition module configured to accept the audio and at least one letter input, to dynamically create a reduced dictionary based on the at least one letter input, to search the reduced dictionary for a set of speech recognized words based on the detected audio, and to determine an acoustic score for each of the speech recognized words; a text prediction module configured to accept the least one letter input, to predict a set of predicted words associated with the at least one letter input and to determine a language model score for each of the predicted words; and a combine module configured to accept the set of predicted words and the set of speech recognized words and to create a set of choice words, wherein the set of choice words is based upon a dynamic weight determined for each of the speech recognized words and each of the predicted words using the respective acoustic score and language model score, wherein the set of choice words is output to aid in a determination of a subsequent user-action.

1. A multimodal system, the system comprising: a speech detection module configured to detect audio; a speech recognition module configured to accept the audio and at least one letter input, to dynamically create a reduced dictionary based on the at least one letter input, to search the reduced dictionary for a set of speech recognized words based on the detected audio, and to determine an acoustic score for each of the speech recognized words; a text prediction module configured to accept the least one letter input, to predict a set of predicted words associated with the at least one letter input and to determine a language model score for each of the predicted words; and a combine module configured to accept the set of predicted words and the set of speech recognized words and to create a set of choice words, wherein the set of choice words is based upon a dynamic weight determined for each of the speech recognized words and each of the predicted words using the respective acoustic score and language model score, wherein the set of choice words is output to aid in a determination of a subsequent user-action. 5. The multimodal system of claim 1 , further comprising an adaption module configured to determine an adaption score based on a usage pattern, and the set of choice words being further based on the adaption score.

2. The method of claim 1, wherein the identifying step comprises: generating an automaton based on the desired information; generating the composite automaton by combining a schema of the database with the automaton; and analyzing the composite automaton to identify broken paths.

2. The method of claim 1, wherein the identifying step comprises: generating an automaton based on the desired information; generating the composite automaton by combining a schema of the database with the automaton; and analyzing the composite automaton to identify broken paths. 3. The method of claim 2, further comprising selecting portions of the automaton that does not correspond to the broken paths of the composite automaton.

15. The computer program product of claim 14 , further comprising program code that is readable and executable by the processor for: dynamically adjusting a displayed appearance of the particular context-based conformed dimensional data gravity well according to how many parsed synthetic context-based objects are pulled into the particular context-based conformed dimensional data gravity well.

15. The computer program product of claim 14 , further comprising program code that is readable and executable by the processor for: dynamically adjusting a displayed appearance of the particular context-based conformed dimensional data gravity well according to how many parsed synthetic context-based objects are pulled into the particular context-based conformed dimensional data gravity well. 16. The computer program product of claim 15 , further comprising program code that is readable and executable by the processor for: further dynamically adjusting the displayed appearance of the particular context-based conformed dimensional data gravity well according to a first derivative d′(PO), where d′(PO) defines a rate of change of how many of the multiple parsed synthetic context-based objects are associated with at least one specific context object in the particular context-based conformed dimensional data gravity well, and wherein the rate of change is represented by a change to a depicted size of the specific context object.

1. A system for searching a plurality of digital works for comments, comprising: a server; a storage in electronic communication with the server; software searching, on a computer, the plurality of digital works for a reference to a first digital work; software identifying, on a computer, a first comment in proximity to the reference, the first comment a portion of the content in the one of the plurality of digital works having the reference and comprising a discussion of the first digital work; software associating the first comment and the first digital work in the storage; software searching, on a computer, the plurality of digital works for a reference delimiter not in proximity to a reference to another digital work; software identifying, on a computer, a second comment in proximity to the reference delimiter; software searching, on a computer, the plurality of digital works for a second digital work referenced by the second comment; and software associating the second comment and the second digital work in the storage; wherein the plurality of digital works are searched over a network; software identifying, on a computer, a reference point in the first web page referenced by the first comment; and software associating the first comment and the reference point in the storage, wherein the software identifying a reference point comprises: content parsing software parsing the first comment for a first set of identifiable elements; work parsing software parsing the first web page for a second set of identifiable elements; and comparison software comparing the first and second sets of identifiable elements to determine the reference point.

1. A system for searching a plurality of digital works for comments, comprising: a server; a storage in electronic communication with the server; software searching, on a computer, the plurality of digital works for a reference to a first digital work; software identifying, on a computer, a first comment in proximity to the reference, the first comment a portion of the content in the one of the plurality of digital works having the reference and comprising a discussion of the first digital work; software associating the first comment and the first digital work in the storage; software searching, on a computer, the plurality of digital works for a reference delimiter not in proximity to a reference to another digital work; software identifying, on a computer, a second comment in proximity to the reference delimiter; software searching, on a computer, the plurality of digital works for a second digital work referenced by the second comment; and software associating the second comment and the second digital work in the storage; wherein the plurality of digital works are searched over a network; software identifying, on a computer, a reference point in the first web page referenced by the first comment; and software associating the first comment and the reference point in the storage, wherein the software identifying a reference point comprises: content parsing software parsing the first comment for a first set of identifiable elements; work parsing software parsing the first web page for a second set of identifiable elements; and comparison software comparing the first and second sets of identifiable elements to determine the reference point. 7. The system of claim 1 wherein the software searching for a reference searches within a predetermined proximity to a second reference delimiter.

3. A system for controlling audio operation for data management and data rendering among a plurality of devices, the system comprising: a computer processor; a non-transitory computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions capable of: retrieving a current speech characteristic of a user and context information comprising current device-state information and current geographical coordinates of the plurality of devices; selecting a device from among said plurality of devices to be a selected device, the selection being based upon the current speech characteristic of the user and the context information, wherein the current device-state information indicates a power state of the selected device; selecting one of a plurality of predetermined audio configurations for the selected device in dependence upon the current speech characteristic of the user and the context information; setting audio operation of a data management and data rendering module to the selected predetermined audio configuration; and providing, by the data management and data rendering module, an audio presentation of synthesized data with the audio operation set to the selected predetermined audio configuration; wherein the synthesized data comprises data of disparate types that has been synthesized into data of a uniform data type, the data of disparate types comprising at least one of Really Simple Syndication (RSS) feed text, calendar information, and email text.

3. A system for controlling audio operation for data management and data rendering among a plurality of devices, the system comprising: a computer processor; a non-transitory computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions capable of: retrieving a current speech characteristic of a user and context information comprising current device-state information and current geographical coordinates of the plurality of devices; selecting a device from among said plurality of devices to be a selected device, the selection being based upon the current speech characteristic of the user and the context information, wherein the current device-state information indicates a power state of the selected device; selecting one of a plurality of predetermined audio configurations for the selected device in dependence upon the current speech characteristic of the user and the context information; setting audio operation of a data management and data rendering module to the selected predetermined audio configuration; and providing, by the data management and data rendering module, an audio presentation of synthesized data with the audio operation set to the selected predetermined audio configuration; wherein the synthesized data comprises data of disparate types that has been synthesized into data of a uniform data type, the data of disparate types comprising at least one of Really Simple Syndication (RSS) feed text, calendar information, and email text. 15. The system of claim 3 , wherein selecting one of a plurality of predetermined audio configurations in dependence upon context information includes selecting at least one predetermined audio configuration in dependence upon the current device-state information indicating the selected device has an open lid.

2. The method of claim 1 , further comprising extending the first set of tokens to create an extended first set of tokens and the second set of tokens to create an extended second set of tokens based on the received semantic knowledge.

2. The method of claim 1 , further comprising extending the first set of tokens to create an extended first set of tokens and the second set of tokens to create an extended second set of tokens based on the received semantic knowledge. 4. The method of claim 2 , further comprising assigning weight values to each token of the extended first and second sets of extended tokens, each weight representing a level of importance of a token in a corresponding string record.

12. A computer-implemented method comprising: providing, by a processor, an interface displaying at least a portion of a transcript, the interface configured to receive a command selecting one of a plurality of words of the transcript and a desired edit from a plurality of permitted edits to the transcript, wherein the command is restricted to selection of a single word, wherein the plurality of permitted edits is restricted to prevent edits to a plurality of time index markers associated with the transcript; receiving, by the processor, data via the interface selecting a word from the transcript and the desired edit; and editing, by the processor, the transcript in response to receiving the selection and the desired edit, wherein editing the transcript comprises editing only data relating to one or more of the word selected by the received selection and a word adjacent to the selected word.

12. A computer-implemented method comprising: providing, by a processor, an interface displaying at least a portion of a transcript, the interface configured to receive a command selecting one of a plurality of words of the transcript and a desired edit from a plurality of permitted edits to the transcript, wherein the command is restricted to selection of a single word, wherein the plurality of permitted edits is restricted to prevent edits to a plurality of time index markers associated with the transcript; receiving, by the processor, data via the interface selecting a word from the transcript and the desired edit; and editing, by the processor, the transcript in response to receiving the selection and the desired edit, wherein editing the transcript comprises editing only data relating to one or more of the word selected by the received selection and a word adjacent to the selected word. 17. The method of claim 12 , wherein editing the transcript comprises merging the selected word with an adjacent word by: determining respective durations of the selected word and the adjacent word; and creating a new data item comprising (i) the text of the selected word and the adjacent word combined, (ii) a time index marker corresponding to an earlier time index marker as between the selected word and the adjacent word, and (iii) an additional duration equal to the sum of the respective durations of the selected word and the adjacent word.

11. The system according to claim 10 , further comprising: a domain definition module configured to receive input for defining said domain context that said domain specific solution is to be used in; a specification definition module configured to receive input for defining said plurality of specifications, including assigning said valid range of specification values for said one or more of said plurality of specifications; and an attribute definition module configured to receive input for defining said plurality of attributes.

11. The system according to claim 10 , further comprising: a domain definition module configured to receive input for defining said domain context that said domain specific solution is to be used in; a specification definition module configured to receive input for defining said plurality of specifications, including assigning said valid range of specification values for said one or more of said plurality of specifications; and an attribute definition module configured to receive input for defining said plurality of attributes. 12. The system according to claim 11 , wherein one or more specifications of said plurality of specifications are mapped to an attribute of said plurality of attributes to form said relationship mappings.

9. The computer program product of claim 5 , wherein the method further comprises tuning the database based on the generated static SQL query before executing the source code; generating a dynamic SQL query based on the static SQL query by the ORM during execution of the source code; and executing the dynamic SQL query against the tuned database during execution of the source code.

9. The computer program product of claim 5 , wherein the method further comprises tuning the database based on the generated static SQL query before executing the source code; generating a dynamic SQL query based on the static SQL query by the ORM during execution of the source code; and executing the dynamic SQL query against the tuned database during execution of the source code. 16. The computer program product of claim 9 , wherein tuning the database comprises adding an index to a table based on the static SQL query.

9. The method of claim 7 , wherein generating the semantic stack trace comprises: recording, into a first node, a mapping of a current stack trace in response to an execution of a first instruction to construct a first element of a plurality of elements in a computer program, wherein the current stack trace is a stack trace that includes stack frames generated up to a particular point in the execution of code instructions in the computer program; storing the first node in a data structure configured for storing a plurality of nodes, wherein the first node includes a first set of stack frames associated with the execution of the first instruction to construct the first element; and incrementally updating the first node by recording, into the first node, a first updated mapping of the current stack trace in response to the execution of a first subsequent instruction that has the first element as a parameter.

9. The method of claim 7 , wherein generating the semantic stack trace comprises: recording, into a first node, a mapping of a current stack trace in response to an execution of a first instruction to construct a first element of a plurality of elements in a computer program, wherein the current stack trace is a stack trace that includes stack frames generated up to a particular point in the execution of code instructions in the computer program; storing the first node in a data structure configured for storing a plurality of nodes, wherein the first node includes a first set of stack frames associated with the execution of the first instruction to construct the first element; and incrementally updating the first node by recording, into the first node, a first updated mapping of the current stack trace in response to the execution of a first subsequent instruction that has the first element as a parameter. 10. The method of claim 9 , wherein generating the semantic stack trace further comprises: recording, into a second node, the mapping of the current stack trace in response to the execution of a second instruction to construct a second element of the plurality of elements in the computer program; storing the second node in the data structure; incrementally updating the second node by recording, into the second node, a second updated mapping of the current stack trace in response to the execution of a second subsequent instruction that has the second element as the parameter; and in response to a determination that no additional instruction for constructing an element exists in the computer program, generating a node string from the plurality of nodes that includes at least the first node and the second node.

6. A speech understanding apparatus, comprising: a speech recognition unit for recognizing an input speech to produce a speech recognition result; a sentence analysis unit for performing morpheme analysis on a sentence corresponding to the speech recognition result, recognizing and extracting additional information, and performing syntax analysis; a hierarchy describing unit for describing hierarchy of the sentence based on the additional information and results of the morpheme analysis and the syntax analysis; a class transformation unit for performing class transformation on the sentence, whose hierarchy has been described, with reference to a thesaurus/ontology and a classification rule dictionary; a semantic representation determination unit for marking optional expressions for the sentence that has undergone the class transformation, deleting meaningless expressions and the additional information, converting the sentence into its base form, and deleting morphemic tags or symbols to determine a semantic representation; a semantic representation retrieval unit for retrieving the determined semantic representation from an example-based semantic representation pattern database; and a retrieval result processing unit for selectively producing a retrieved semantic representation depending on whether or not the determined semantic representation exists in the example-based semantic representation pattern database.

6. A speech understanding apparatus, comprising: a speech recognition unit for recognizing an input speech to produce a speech recognition result; a sentence analysis unit for performing morpheme analysis on a sentence corresponding to the speech recognition result, recognizing and extracting additional information, and performing syntax analysis; a hierarchy describing unit for describing hierarchy of the sentence based on the additional information and results of the morpheme analysis and the syntax analysis; a class transformation unit for performing class transformation on the sentence, whose hierarchy has been described, with reference to a thesaurus/ontology and a classification rule dictionary; a semantic representation determination unit for marking optional expressions for the sentence that has undergone the class transformation, deleting meaningless expressions and the additional information, converting the sentence into its base form, and deleting morphemic tags or symbols to determine a semantic representation; a semantic representation retrieval unit for retrieving the determined semantic representation from an example-based semantic representation pattern database; and a retrieval result processing unit for selectively producing a retrieved semantic representation depending on whether or not the determined semantic representation exists in the example-based semantic representation pattern database. 9. The speech understanding apparatus of claim 6 , wherein the class transformation unit converts a noun into a hypernym class, converts synonyms from declinable words into a single word, assigns particles subject to phonological change due to a final consonant to the same class, and classifies numeric representations of time and amount by using automata.

1. A method, comprising: determining a relationship between a plurality of existing rules in a rule set of a rule based system used to screen incoming data of a network, wherein the relationship includes a cause interaction and an effect interaction among the existing rules; creating a representation of the relationship including the cause interaction and the effect interaction; receiving a new rule to be inserted into the rule set; inserting a further relationship between the new rule and the existing rules into the representation to create a modified representation; and determining, based on the modified representation, if a conflict is created by insertion of the new rule in the rule set.

1. A method, comprising: determining a relationship between a plurality of existing rules in a rule set of a rule based system used to screen incoming data of a network, wherein the relationship includes a cause interaction and an effect interaction among the existing rules; creating a representation of the relationship including the cause interaction and the effect interaction; receiving a new rule to be inserted into the rule set; inserting a further relationship between the new rule and the existing rules into the representation to create a modified representation; and determining, based on the modified representation, if a conflict is created by insertion of the new rule in the rule set. 4. The method of claim 1 , wherein the rule set includes a parameter used to determine when the rule set is invoked.

1. A computerized-method of searching for an element in speech related documents, the method comprising: transcribing, by a controller, a set of digital speech recordings stored in a speech recording database to a set of digital phoneme strings and including the phoneme strings in a set of digital phonetic transcriptions; reverse-indexing, by the controller, using one or more parser rules, the phonetic transcriptions according to one or more phonemes and storing the reverse-indexed transcriptions in an inverted index database including a mapping to documents such that the one or more phonemes can be used as a search key for searching in the phonetic transcriptions for a phoneme string; transcribing, by the controller, a textual search term into a set of search phoneme strings; and using, by the controller, the set of search phoneme strings to search for the textual search term in the set of phonetic transcriptions and produce a list of the documents ranked according to the match of the phoneme strings to the documents.

1. A computerized-method of searching for an element in speech related documents, the method comprising: transcribing, by a controller, a set of digital speech recordings stored in a speech recording database to a set of digital phoneme strings and including the phoneme strings in a set of digital phonetic transcriptions; reverse-indexing, by the controller, using one or more parser rules, the phonetic transcriptions according to one or more phonemes and storing the reverse-indexed transcriptions in an inverted index database including a mapping to documents such that the one or more phonemes can be used as a search key for searching in the phonetic transcriptions for a phoneme string; transcribing, by the controller, a textual search term into a set of search phoneme strings; and using, by the controller, the set of search phoneme strings to search for the textual search term in the set of phonetic transcriptions and produce a list of the documents ranked according to the match of the phoneme strings to the documents. 6. The method of claim 1 , comprising: transcribing the textual search term into a set of search phoneme strings based on a respective set of pronunciations, and simultaneously searching for the set of search phoneme strings in the set of phonetic transcriptions.

5. The method of claim 4, wherein the steps of selecting further comprise closing an electrical switching circuit uniquely associated with the desired symbol.

5. The method of claim 4, wherein the steps of selecting further comprise closing an electrical switching circuit uniquely associated with the desired symbol. 6. The method of claim 5, wherein the step of reproducing further comprises copying the desired character in reproduced form onto a media different from the displayed media.

2. The system of claim 1 , wherein the BPM handler comprises an annotator configured to annotate each of the at least some of the tasks with the corresponding requirements, to thereby provide a business process annotated model (BPAM).

2. The system of claim 1 , wherein the BPM handler comprises an annotator configured to annotate each of the at least some of the tasks with the corresponding requirements, to thereby provide a business process annotated model (BPAM). 3. The system of claim 2 , comprising a business process annotation view and graphical editor configured to display the BPM and to receive user selections of individual tasks of the BPM and associated user designations of the requirements and resources annotated thereto.

1. A method comprising: receiving from an advertiser an indication of an example resource, wherein the example resource is an example of a type of resource that the advertiser desires to target with a promotional campaign; identifying one or more query logs wherein a given entry in the query log includes a query that was received and an identification of a resource that was selected as responsive to the query; evaluating the one or more query logs to determine one or more queries including one or more query terms that resolved to the example resource; using the determined one or more queries and the query logs, identifying one or more matching resources other than the example resource that also were provided as a solution to the one or more determined queries; filtering the one or more matching resources based on one or more criteria to identify matching resources that are relevant to the advertiser, wherein filtering includes ranking the one or more matching resources based at least in part on a frequency of a respective matching resource being returned in response to the one or more queries as represented in the query logs and identifying one or more top ranked resources as leads wherein a lead can be used as a targeting criteria for the promotional campaign; and providing suggestions to the advertiser including providing the leads for targeting content for the promotional campaign.

1. A method comprising: receiving from an advertiser an indication of an example resource, wherein the example resource is an example of a type of resource that the advertiser desires to target with a promotional campaign; identifying one or more query logs wherein a given entry in the query log includes a query that was received and an identification of a resource that was selected as responsive to the query; evaluating the one or more query logs to determine one or more queries including one or more query terms that resolved to the example resource; using the determined one or more queries and the query logs, identifying one or more matching resources other than the example resource that also were provided as a solution to the one or more determined queries; filtering the one or more matching resources based on one or more criteria to identify matching resources that are relevant to the advertiser, wherein filtering includes ranking the one or more matching resources based at least in part on a frequency of a respective matching resource being returned in response to the one or more queries as represented in the query logs and identifying one or more top ranked resources as leads wherein a lead can be used as a targeting criteria for the promotional campaign; and providing suggestions to the advertiser including providing the leads for targeting content for the promotional campaign. 8. The method of claim 1 wherein filtering includes removing irrelevant businesses from the matching resources.

1. A method, comprising: obtaining an electronic document conforming to one of a plurality of print formats; parsing the electronic document according to the one of the plurality of print formats to generate an intermediate data structure conforming to an intermediate format such that the electronic document is converted to the intermediate format, wherein the intermediate format is different from the plurality of print formats; applying one or more rules to obtain data for a plurality of regions of the electronic document from the intermediate data structure; and storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure, thereby enabling a report to be generated using at least a portion of the data for the plurality of regions that has been stored or provided.

1. A method, comprising: obtaining an electronic document conforming to one of a plurality of print formats; parsing the electronic document according to the one of the plurality of print formats to generate an intermediate data structure conforming to an intermediate format such that the electronic document is converted to the intermediate format, wherein the intermediate format is different from the plurality of print formats; applying one or more rules to obtain data for a plurality of regions of the electronic document from the intermediate data structure; and storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure, thereby enabling a report to be generated using at least a portion of the data for the plurality of regions that has been stored or provided. 6. The method as recited in claim 1 , wherein storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure comprises: generating a document data structure that contains the data for the plurality of regions of the electronic document.

8. A computer program product comprising computer-readable program code to be executed by one or more processors when retrieved from a non-transitory computer-readable medium, the program code including instructions to: create a plurality of scores for each token, in a sequence of tokens from an email signature block, based on a corresponding independent probability distribution that has been previously trained for a plurality of entity types, wherein each token comprises one of a word, a punctuation symbol, and an end-of-line character, an entity being a part of one of a person name, a job title, an enterprise name, a telephone number, an email address, and a uniform resource locator, and being associated with at least one of an entity type, an entity sequence, and a set of entities; identify each entity sequence that has a total number of entities that is identical to a total number of tokens in the sequence of tokens; determine, for each of the identified entity sequences, an entity sequence score by combining corresponding scores for each token, in the sequence of tokens, that corresponds to an entity type in an identified entity sequence; identify an entity sequence from the identified entity sequences with a highest entity sequence score; and output the sequence of tokens as an identified set of entities, in the email signature block, based on the entity sequence with the highest score.

8. A computer program product comprising computer-readable program code to be executed by one or more processors when retrieved from a non-transitory computer-readable medium, the program code including instructions to: create a plurality of scores for each token, in a sequence of tokens from an email signature block, based on a corresponding independent probability distribution that has been previously trained for a plurality of entity types, wherein each token comprises one of a word, a punctuation symbol, and an end-of-line character, an entity being a part of one of a person name, a job title, an enterprise name, a telephone number, an email address, and a uniform resource locator, and being associated with at least one of an entity type, an entity sequence, and a set of entities; identify each entity sequence that has a total number of entities that is identical to a total number of tokens in the sequence of tokens; determine, for each of the identified entity sequences, an entity sequence score by combining corresponding scores for each token, in the sequence of tokens, that corresponds to an entity type in an identified entity sequence; identify an entity sequence from the identified entity sequences with a highest entity sequence score; and output the sequence of tokens as an identified set of entities, in the email signature block, based on the entity sequence with the highest score. 12. The computer program product of claim 8 , wherein identifying each entity sequence in the plurality of entity sequences which comprises the number of entities that matches the number of tokens in the sequence of tokens comprises identifying each entity sequence which excludes entities identified from a previous line of the email signature block.

1. A method performed by data processing apparatus, the method comprising: receiving a query determined to be a question query and a corresponding answer generated in response to the question query, the answer determined to be responsive to the question query so that it is to be provided to a user device as an answer to the question query, wherein each of the question query and the answer has one or more terms; in response to receiving the question query and the corresponding answer: receiving a first set of rich content items in response to a search process and based on the question query and corresponding answer and ranked according to an order; for each rich content item in the set of first rich content items, receiving data specifying rich content item labels for the rich content item; determining each rich content item having labels that match terms of the answer and terms of the question query as first rich content items; determining each rich content item having labels that match only the terms of the answer or that match only the terms of the question query as second rich content items; demoting the second rich content items in the order in the first set relative to the first rich content items in the first set so that the rich content items in the first set are ranked according to a revised order; selecting, according to the revised order, a rich content item as a selected rich content item to provide with the answer; and providing, to a user device, the answer to the question query and the selected rich content item with the answer to the question query.

1. A method performed by data processing apparatus, the method comprising: receiving a query determined to be a question query and a corresponding answer generated in response to the question query, the answer determined to be responsive to the question query so that it is to be provided to a user device as an answer to the question query, wherein each of the question query and the answer has one or more terms; in response to receiving the question query and the corresponding answer: receiving a first set of rich content items in response to a search process and based on the question query and corresponding answer and ranked according to an order; for each rich content item in the set of first rich content items, receiving data specifying rich content item labels for the rich content item; determining each rich content item having labels that match terms of the answer and terms of the question query as first rich content items; determining each rich content item having labels that match only the terms of the answer or that match only the terms of the question query as second rich content items; demoting the second rich content items in the order in the first set relative to the first rich content items in the first set so that the rich content items in the first set are ranked according to a revised order; selecting, according to the revised order, a rich content item as a selected rich content item to provide with the answer; and providing, to a user device, the answer to the question query and the selected rich content item with the answer to the question query. 2. The method of claim 1 , wherein receiving a first set of rich content items in response to a search process and based on the question query and corresponding answer comprises: generating a contextual query that includes a first element relating to the question query and a second element relating to the answer; and submitting the contextual query to a rich content search process and receiving data specifying a first set of rich content items responsive to the contextual query, the rich content items ranked according to an order that is indicative of the relevance of each rich content item to the contextual query.

1. A method for providing caller identification information by a caller's mobile phone, the method comprising the steps of: when there is a request, by a caller, for an addition of a word or phrase after an input of a call recipient's phone number, receiving, by the caller's mobile phone, an input of the word or phrase from the caller; and when the caller inputs a request for making an outgoing call, generating, by the caller's mobile phone, an outgoing call message, which includes a caller's phone number, the recipient's phone number, and an input word or phrase, and sending the generated outgoing call message to the recipient's mobile phone, wherein receiving the input of the word or phrase from the caller comprises: upon generating an identifier to request addition of the word or phrase, distinguishing the recipient's phone number and the word or phrase and adding the identifier after the recipient's phone number; and receiving the input of the word or phrase from the caller, and continuously arranging the recipient's phone number, the identifier and the word or phrase in order and displaying the recipient's phone number, the identifier and the word or phrase on a single screen of the caller's mobile phone.

1. A method for providing caller identification information by a caller's mobile phone, the method comprising the steps of: when there is a request, by a caller, for an addition of a word or phrase after an input of a call recipient's phone number, receiving, by the caller's mobile phone, an input of the word or phrase from the caller; and when the caller inputs a request for making an outgoing call, generating, by the caller's mobile phone, an outgoing call message, which includes a caller's phone number, the recipient's phone number, and an input word or phrase, and sending the generated outgoing call message to the recipient's mobile phone, wherein receiving the input of the word or phrase from the caller comprises: upon generating an identifier to request addition of the word or phrase, distinguishing the recipient's phone number and the word or phrase and adding the identifier after the recipient's phone number; and receiving the input of the word or phrase from the caller, and continuously arranging the recipient's phone number, the identifier and the word or phrase in order and displaying the recipient's phone number, the identifier and the word or phrase on a single screen of the caller's mobile phone. 7. The method according to claim 1 , wherein the identifier is a single character.

7. A computing device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: providing a plurality of user interface objects on a desktop, the plurality of user interface objects including an active application window and a first user interface object that is completely visually obscured by the active application window; providing a pointer cursor and an accessibility cursor that is distinct from the pointer cursor; while the first user interface object is completely visually obscured by the active application window, detecting a user input accessing the first user interface object with the accessibility cursor, independently of the pointer cursor; and while the accessibility cursor is accessing the first user interface object, visually revealing the first user interface element from behind the active application window.

7. A computing device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: providing a plurality of user interface objects on a desktop, the plurality of user interface objects including an active application window and a first user interface object that is completely visually obscured by the active application window; providing a pointer cursor and an accessibility cursor that is distinct from the pointer cursor; while the first user interface object is completely visually obscured by the active application window, detecting a user input accessing the first user interface object with the accessibility cursor, independently of the pointer cursor; and while the accessibility cursor is accessing the first user interface object, visually revealing the first user interface element from behind the active application window. 11. The device of claim 7 , wherein the one or more programs further include instructions for: while the accessibility cursor is accessing the first user interface object, providing an audible description of the first user interface element.

1. A method for compressing a byte stream of input data, comprising: establishing a multiple-byte buffer and sequentially transferring bytes from said byte stream into said buffer; establishing a multiple-byte first comparison window and sequentially transferring bytes from said byte stream into said first comparison window; establishing a multiple-byte second comparison window to receive some but not all of the bytes from said byte stream; comparing a byte in the buffer against the bytes in the first comparison window and the second comparison window; substituting a pointer for the compared byte in the buffer if the compared byte matches a byte in the first or second comparison window; and outputting said substituted pointer into an output stream.

1. A method for compressing a byte stream of input data, comprising: establishing a multiple-byte buffer and sequentially transferring bytes from said byte stream into said buffer; establishing a multiple-byte first comparison window and sequentially transferring bytes from said byte stream into said first comparison window; establishing a multiple-byte second comparison window to receive some but not all of the bytes from said byte stream; comparing a byte in the buffer against the bytes in the first comparison window and the second comparison window; substituting a pointer for the compared byte in the buffer if the compared byte matches a byte in the first or second comparison window; and outputting said substituted pointer into an output stream. 10. The method of claim 1, further comprising uncompressing the output stream by utilizing said pointers to locate a byte in a comparison window, and substituting said located byte for the pointer.

12. The computer program product of claim 10 , further comprising parsing the extracted respective data in the timebox to determine keywords for searching.

12. The computer program product of claim 10 , further comprising parsing the extracted respective data in the timebox to determine keywords for searching. 16. The computer program product of claim 12 , further comprising adding search results of the keywords, extracted from the timebox, to the package along with the extracted respective data.

1. A system comprising: a processor and a computer readable memory, wherein the processor retrieves and executes instructions from the computer readable memory to perform a processor-implemented method comprising; receiving a reading speed of a reader, wherein the reader is a human reader, wherein the reading speed is based on a first source; determining a summary length of a summary of a document based on the received reading speed of the reader, wherein the document is a second source that differs from the first source, wherein a first reading speed is faster than a second reading speed, wherein the first reading speed results in a first summary length of the summary and the second reading speed results in a second summary length of the summary, and wherein the first summary length is longer than the second summary length; generating a summary of the document having the determined summary length; identifying an interest of the reader; modifying the summary of the document according to the interest of the reader in order to include, in the summary of the document, content from the document that is of interest to the reader, wherein the reader has multiple interests; weighting each interest from the multiple interests based on a reading history of the reader, wherein each interest is assigned a weight based on a percentage of the reading history of the reader that is devoted to said each interest; generating a weight ratio of interests of the reader from the multiple interests based on the percentage of the reading history of the reader that is devoted to said each interest; generating components of the summary based on the weight ratio of interests of the reader; and modifying the summary of the document to match the weight ratio such that a ratio of lengths of the components of the summary matches the weight ratio of the interests of the reader.

1. A system comprising: a processor and a computer readable memory, wherein the processor retrieves and executes instructions from the computer readable memory to perform a processor-implemented method comprising; receiving a reading speed of a reader, wherein the reader is a human reader, wherein the reading speed is based on a first source; determining a summary length of a summary of a document based on the received reading speed of the reader, wherein the document is a second source that differs from the first source, wherein a first reading speed is faster than a second reading speed, wherein the first reading speed results in a first summary length of the summary and the second reading speed results in a second summary length of the summary, and wherein the first summary length is longer than the second summary length; generating a summary of the document having the determined summary length; identifying an interest of the reader; modifying the summary of the document according to the interest of the reader in order to include, in the summary of the document, content from the document that is of interest to the reader, wherein the reader has multiple interests; weighting each interest from the multiple interests based on a reading history of the reader, wherein each interest is assigned a weight based on a percentage of the reading history of the reader that is devoted to said each interest; generating a weight ratio of interests of the reader from the multiple interests based on the percentage of the reading history of the reader that is devoted to said each interest; generating components of the summary based on the weight ratio of interests of the reader; and modifying the summary of the document to match the weight ratio such that a ratio of lengths of the components of the summary matches the weight ratio of the interests of the reader. 8. The system of claim 1 , wherein the first source is an input from the reader that specifies the reading speed of the reader.

1. A method of searching for similar documents, the method comprising: accessing a first document; identifying one or more terms from a metamodel semantic network; identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises: identifying a user that created the first document; retrieving context information associated with the user; identifying business functional data associated with the context information; identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms; and selecting terms that are associated with the identified domain for the analysis; identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document; and searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the metamodel semantic network.

1. A method of searching for similar documents, the method comprising: accessing a first document; identifying one or more terms from a metamodel semantic network; identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises: identifying a user that created the first document; retrieving context information associated with the user; identifying business functional data associated with the context information; identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms; and selecting terms that are associated with the identified domain for the analysis; identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document; and searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the metamodel semantic network. 7. The method of claim 1 , wherein the metamodel semantic network includes the terms and associated concepts.

6. A system comprising: memory storing a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of the respective object, the memory also storing map information including a plurality of points of interest, where each point of interest of the plurality of points of interest is associated with a geographic coordinate; and one or more computing devices configured to: identify a 3D model of an object from a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of that respective object; determine whether a geographic coordinate of a point of interest is within the geographic area of the base polygon; when the geographic coordinate of the point of interest is within the geographic area of the base polygon, create a system tag including a search term selected based on the given point of interest; and associate the system tag with the identified 3D model of the object.

6. A system comprising: memory storing a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of the respective object, the memory also storing map information including a plurality of points of interest, where each point of interest of the plurality of points of interest is associated with a geographic coordinate; and one or more computing devices configured to: identify a 3D model of an object from a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of that respective object; determine whether a geographic coordinate of a point of interest is within the geographic area of the base polygon; when the geographic coordinate of the point of interest is within the geographic area of the base polygon, create a system tag including a search term selected based on the given point of interest; and associate the system tag with the identified 3D model of the object. 9. The computer of claim 6 , wherein the memory further stores a search index, and the one or more computing devices are further configured to store the system tag in the search index.

1. A computer-implemented method comprising: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking.

1. A computer-implemented method comprising: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking. 8. The method of claim 1 , wherein associating each cluster of search queries with a respective representative category further comprises: for each cluster: associating each search query in the cluster with one or more categories based on a respective set of result documents responsive to the search query; and associating the cluster with a respective representative category based on the category associations of the cluster's search queries.

11. The method as claimed in claim 7 , the determination of the source document to be deleted includes the document fragment referenced by the fragment object determines whether the source document to be deleted is identified in a list of referenced documents.

11. The method as claimed in claim 7 , the determination of the source document to be deleted includes the document fragment referenced by the fragment object determines whether the source document to be deleted is identified in a list of referenced documents. 12. The method as claimed in claim 11 , further comprising: (d) removing the document to be deleted from the list of referenced documents.

1. A method for management entity operations, the method comprising: parsing, by a management entity, a request to collect data about a communications system for an entity in the communications system, the parsing to produce a parsed request and dependency information related to the request; generating, by the management entity, sets of model elements in accordance with context tokens and content tokens derived from the parsed request, the content tokens including extrinsic metadata and intrinsic metadata of the parsed request, the generating the sets of model elements comprising: evaluating content of the request to collect the data to produce links between the context tokens and the content tokens; and mapping the links into a model element graph; analyzing context metadata tokens and content metadata tokens in accordance with the dependency information; analyzing the model element graph in accordance with the dependency information; modifying the model element graph for each combination of dependency and dependency type in the dependency information; generating, by the management entity, a platform-neutral description of results of the request from the model element graph derived from the sets of model elements, the platform-neutral description being independent of a protocol used by the management entity to collect the data about the communications system; executing, by the management entity, the request to collect the data as requested in accordance with the platform-neutral description; and storing, by the management entity, the data as collected.

1. A method for management entity operations, the method comprising: parsing, by a management entity, a request to collect data about a communications system for an entity in the communications system, the parsing to produce a parsed request and dependency information related to the request; generating, by the management entity, sets of model elements in accordance with context tokens and content tokens derived from the parsed request, the content tokens including extrinsic metadata and intrinsic metadata of the parsed request, the generating the sets of model elements comprising: evaluating content of the request to collect the data to produce links between the context tokens and the content tokens; and mapping the links into a model element graph; analyzing context metadata tokens and content metadata tokens in accordance with the dependency information; analyzing the model element graph in accordance with the dependency information; modifying the model element graph for each combination of dependency and dependency type in the dependency information; generating, by the management entity, a platform-neutral description of results of the request from the model element graph derived from the sets of model elements, the platform-neutral description being independent of a protocol used by the management entity to collect the data about the communications system; executing, by the management entity, the request to collect the data as requested in accordance with the platform-neutral description; and storing, by the management entity, the data as collected. 14. The method of claim 1 , further comprising optimizing the modified model element graph after each dependency and dependency type combination.

1. A method of training a handwriting recognition system to recognize handwritten characters of a particular user, comprising: (a) storing electrical representations of a plurality of prototype characters in a memory; (b) entering a string of user-generated handwritten characters on an electronic digitizing tablet; (c) generating an electrical representation of the string of handwritten characters; (d) comparing the electrical representation of the user generated string of characters with the representations of the prototype characters stored in memory; (e) displaying on the digitizing tablet, for each user generated handwritten character, a corresponding character, the corresponding character being a prototype character whose electrical representation most closely resembles the electrical representation of the particular user-generated handwritten character; (f) entering on the digitizing tablet, for each incorrectly recognized user-input character, a user-generated handwritten correction character; (g) comparing an electrical representation of the user generated handwritten correction character with the representations of the prototype characters stored in memory, excluding the electrical representation of the incorrectly returned character; (h) displaying on the digitizing tablet, for each correction character, a corresponding correction character, the corresponding correction character of a particular user-generated handwritten correction character being a prototype character whose electrical representation most closely resembles the electrical representation of the particular user-generated handwritten correction character; (i) repeating steps (f) through (h) if the corresponding correction character does not match the user generated correction character; (j) comparing the electrical representation of the misrecognized user generated handwritten character and the user generated correction character and determining whether they resemble one another within a predetermined threshold and: if so, retraining the system to recognize the misrecognized user generated character and the user generated correction character as the corresponding correction character; if not, retraining the system to recognize the user generated correction character as the corresponding correction character.

1. A method of training a handwriting recognition system to recognize handwritten characters of a particular user, comprising: (a) storing electrical representations of a plurality of prototype characters in a memory; (b) entering a string of user-generated handwritten characters on an electronic digitizing tablet; (c) generating an electrical representation of the string of handwritten characters; (d) comparing the electrical representation of the user generated string of characters with the representations of the prototype characters stored in memory; (e) displaying on the digitizing tablet, for each user generated handwritten character, a corresponding character, the corresponding character being a prototype character whose electrical representation most closely resembles the electrical representation of the particular user-generated handwritten character; (f) entering on the digitizing tablet, for each incorrectly recognized user-input character, a user-generated handwritten correction character; (g) comparing an electrical representation of the user generated handwritten correction character with the representations of the prototype characters stored in memory, excluding the electrical representation of the incorrectly returned character; (h) displaying on the digitizing tablet, for each correction character, a corresponding correction character, the corresponding correction character of a particular user-generated handwritten correction character being a prototype character whose electrical representation most closely resembles the electrical representation of the particular user-generated handwritten correction character; (i) repeating steps (f) through (h) if the corresponding correction character does not match the user generated correction character; (j) comparing the electrical representation of the misrecognized user generated handwritten character and the user generated correction character and determining whether they resemble one another within a predetermined threshold and: if so, retraining the system to recognize the misrecognized user generated character and the user generated correction character as the corresponding correction character; if not, retraining the system to recognize the user generated correction character as the corresponding correction character. 3. The method of claim 1, wherein each of the user generated handwritten characters is mapped to its corresponding character, and wherein an electrical representation of the mapping is stored in system memory.

1. A method performed by a policy and charging rules node for providing managed object support, the method comprising: determining, at a policy and charging rules node, that the policy and charging rules node should perform a policy decision; comparing a criteria portion of at least one rule of a plurality of rules to a set of context information; identifying a rule of the plurality of rules that matches the set of context information; determining that a result portion of the identified rule includes a reference to a first managed object; retrieving the first managed object based on the reference to the first managed object, wherein the first managed object is stored separately from the identified rule; and using the first managed object as at least part of a result of the policy decision.

1. A method performed by a policy and charging rules node for providing managed object support, the method comprising: determining, at a policy and charging rules node, that the policy and charging rules node should perform a policy decision; comparing a criteria portion of at least one rule of a plurality of rules to a set of context information; identifying a rule of the plurality of rules that matches the set of context information; determining that a result portion of the identified rule includes a reference to a first managed object; retrieving the first managed object based on the reference to the first managed object, wherein the first managed object is stored separately from the identified rule; and using the first managed object as at least part of a result of the policy decision. 2. The method of claim 1 , further comprising: presenting a user with a first version of a managed object; receiving, from the user, a second version of the managed object; and storing the second version of the managed object, wherein a future reference to a managed object results in using the second version of the managed object as at least part of a result of a policy decision.

1. A method for rendering a document, the method comprising: converting a plurality of resources in a document file into a plurality of files that are native to a browser; creating a style sheet based on the document file, wherein an aggregate of the plurality of files together with the style sheet are configured to cause the browser to render an appearance of the document file; and generating, based on the document file, an invisible layer to be laid on the appearance, wherein the invisible layer enables actions to be performed on the document file.

1. A method for rendering a document, the method comprising: converting a plurality of resources in a document file into a plurality of files that are native to a browser; creating a style sheet based on the document file, wherein an aggregate of the plurality of files together with the style sheet are configured to cause the browser to render an appearance of the document file; and generating, based on the document file, an invisible layer to be laid on the appearance, wherein the invisible layer enables actions to be performed on the document file. 3. The method of claim 1 , wherein the plurality of resources comprise a font, the method further comprising: extracting the font from the document file; and creating a blank variation of the font so as to enable the generation of the invisible layer, wherein glyphs within the blank variation of the font contain no outline information.

17. An apparatus for displaying driving directions, the apparatus being configured to: access data that describes at least one maneuver to be executed to traverse a route from an origin to a destination; select a portion of the accessed data that describes a particular maneuver, the maneuver including an action and a road; determine a road symbol to associate with the particular maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road involved in the particular maneuver; determine an action symbol to associate with the particular maneuver, the action symbol having substantially the same appearance as a road sign used to identify the action to be performed to execute the particular maneuver; and present both the road symbol and the action symbol to describe the particular maneuver, such that the road symbol and the action symbol describe the particular maneuver.

17. An apparatus for displaying driving directions, the apparatus being configured to: access data that describes at least one maneuver to be executed to traverse a route from an origin to a destination; select a portion of the accessed data that describes a particular maneuver, the maneuver including an action and a road; determine a road symbol to associate with the particular maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road involved in the particular maneuver; determine an action symbol to associate with the particular maneuver, the action symbol having substantially the same appearance as a road sign used to identify the action to be performed to execute the particular maneuver; and present both the road symbol and the action symbol to describe the particular maneuver, such that the road symbol and the action symbol describe the particular maneuver. 24. The apparatus of claim 17 wherein the action symbol indicates a turn angle involved in the particular maneuver.

1. An automated method for generating an image quality guide document comprising: for at least one image in a set of images undergoing image enhancement: identifying image quality-related features for the image based on enhancements being automatically applied to the image, identifying image content-related features based on content of the image, determining a content-based degradation of the image based on the identified image quality-related features and image content-related features, and retrieving a photograph shooting tip for correcting the degradation in the image, based on the determined content-based degradation; generating a thumbnail of each of the images; and generating an image quality guide document including the thumbnails for the images in the set of images in which at least one of the thumbnails is associated with a respective text description that is based on the determined content-based degradation, the text description including the shooting tip associated with the thumbnail of the image.

1. An automated method for generating an image quality guide document comprising: for at least one image in a set of images undergoing image enhancement: identifying image quality-related features for the image based on enhancements being automatically applied to the image, identifying image content-related features based on content of the image, determining a content-based degradation of the image based on the identified image quality-related features and image content-related features, and retrieving a photograph shooting tip for correcting the degradation in the image, based on the determined content-based degradation; generating a thumbnail of each of the images; and generating an image quality guide document including the thumbnails for the images in the set of images in which at least one of the thumbnails is associated with a respective text description that is based on the determined content-based degradation, the text description including the shooting tip associated with the thumbnail of the image. 2. The method of claim 1 , wherein the method further comprises retrieving a photograph shooting tip for the image based on the content-based degradation, the shooting tip comprising a suggestion for avoiding the content-based degradation in future, and wherein in the image quality guide document, the shooting tip is associated with the thumbnail of the image.

13. The method of claim 1 , wherein the first query comprises a script comprising: a gather step for identifying the first subset of the data chunks relevant to the first query and loading the first subset of the data chunks to the main memory; a sift step for executing the first query only against triples included within the first subset of the data chunks loaded to the main memory; and a clear step for freeing the main memory of one or more of the triples included within the first subset of the data chunks loaded to the main memory.

13. The method of claim 1 , wherein the first query comprises a script comprising: a gather step for identifying the first subset of the data chunks relevant to the first query and loading the first subset of the data chunks to the main memory; a sift step for executing the first query only against triples included within the first subset of the data chunks loaded to the main memory; and a clear step for freeing the main memory of one or more of the triples included within the first subset of the data chunks loaded to the main memory. 16. The method of claim 13 , further comprising: fragmenting the script into a plurality of script fragments; and sending one of the plurality of script fragments to a remote instance of the database system for execution, wherein the remote instance stores a data chunk relevant to executing the script fragment sent for execution.

67. A data processing system as set forth in claim 66, further including: means, operative in response to a termination of the second nested application program, for setting the current interaction language to a previous interaction language specified in the means for storing nested language information; and means for removing the previous interaction language from the means for storing nested language information.

67. A data processing system as set forth in claim 66, further including: means, operative in response to a termination of the second nested application program, for setting the current interaction language to a previous interaction language specified in the means for storing nested language information; and means for removing the previous interaction language from the means for storing nested language information. 68. A data processing system as set forth in claim 67 wherein the means for storing nested language information is a stack.

11. An apparatus for preventing unauthorized access to database resources, comprising: a processor; a memory; a receiving mechanism for receiving a section of programming language code to execute on a computer system, wherein the programming language code is annotated with a pragma that defines a set of database objects that the programming language code has permission to access, wherein the pragma is run-time interpreted or compilation-directed; an analysis mechanism for analyzing the pragma to determine the set of database objects; and a processing mechanism for processing the programming language code, wherein the processing mechanism is configured to: create a sandbox which includes the set of database objects defined by the pragma; execute the programming language code within the boundaries of the sandbox; determine if the programming language code is attempting to access a table database object outside of the boundaries of the sandbox; and if so, generate an exception.

11. An apparatus for preventing unauthorized access to database resources, comprising: a processor; a memory; a receiving mechanism for receiving a section of programming language code to execute on a computer system, wherein the programming language code is annotated with a pragma that defines a set of database objects that the programming language code has permission to access, wherein the pragma is run-time interpreted or compilation-directed; an analysis mechanism for analyzing the pragma to determine the set of database objects; and a processing mechanism for processing the programming language code, wherein the processing mechanism is configured to: create a sandbox which includes the set of database objects defined by the pragma; execute the programming language code within the boundaries of the sandbox; determine if the programming language code is attempting to access a table database object outside of the boundaries of the sandbox; and if so, generate an exception. 13. The apparatus of claim 11 , wherein the processing mechanism further comprises a compilation mechanism for compiling the programming language code into executable code, wherein the executable code can only access the set of database objects defined by the pragma.

1. A computer-implemented method for generating a reference set via seed documents, comprising: obtaining a collection of documents; identifying one or more seed documents related to an issue for which a reference set of documents is needed; selecting the seed documents from at least one of a current document set and a previously defined document set; comparing the seed documents to the document collection and identifying those documents similar to the seed documents as reference set candidates; applying a size threshold to the reference set candidates; and grouping the reference set candidates as the reference set when the size threshold is satisfied, wherein the reference set is reduced by identifying the reference set candidates that are closely related and common reference set candidates and by removing the closely related reference set candidates and the common reference set candidates.

1. A computer-implemented method for generating a reference set via seed documents, comprising: obtaining a collection of documents; identifying one or more seed documents related to an issue for which a reference set of documents is needed; selecting the seed documents from at least one of a current document set and a previously defined document set; comparing the seed documents to the document collection and identifying those documents similar to the seed documents as reference set candidates; applying a size threshold to the reference set candidates; and grouping the reference set candidates as the reference set when the size threshold is satisfied, wherein the reference set is reduced by identifying the reference set candidates that are closely related and common reference set candidates and by removing the closely related reference set candidates and the common reference set candidates. 5. A method according to claim 1 , further comprising: determining the seed documents, comprising: identifying a topic of the document collection; and identifying documents that are important to the topic from one of the document collection and the a further collection.

1. A computer-storage device storing computer-executable instructions that, when executed by a computing device, facilitate a method of providing one or more suggested search-engine queries related to content of a web page that is requested, the method comprising: retrieving the web page in response to a request from a client computing device to provide the web page, wherein the web page is configured to present an advertisement in an advertisement frame; identifying a suggested search-engine query to be provided together with the web page, wherein identifying the suggested search-engine query includes identifying one or more hyperlinks included on the web page, analyzing historical user metrics, or a combination thereof; creating a web-page element that includes a hyperlink that, when selected, communicates the suggested search-engine query to a search-engine server, wherein the suggested search-engine query includes a search term derived from the one or more hyperlinks or the historical user metrics; inserting the web-page element in the advertisement frame instead of the advertisement to syndicate the request to the search-engine server by way of the advertisement frame; and providing to the client computing device the web page, which includes both the web-page element having the hyperlink and the content combined together in a same web page, thereby providing the suggested search-engine query comprised of the search term.

1. A computer-storage device storing computer-executable instructions that, when executed by a computing device, facilitate a method of providing one or more suggested search-engine queries related to content of a web page that is requested, the method comprising: retrieving the web page in response to a request from a client computing device to provide the web page, wherein the web page is configured to present an advertisement in an advertisement frame; identifying a suggested search-engine query to be provided together with the web page, wherein identifying the suggested search-engine query includes identifying one or more hyperlinks included on the web page, analyzing historical user metrics, or a combination thereof; creating a web-page element that includes a hyperlink that, when selected, communicates the suggested search-engine query to a search-engine server, wherein the suggested search-engine query includes a search term derived from the one or more hyperlinks or the historical user metrics; inserting the web-page element in the advertisement frame instead of the advertisement to syndicate the request to the search-engine server by way of the advertisement frame; and providing to the client computing device the web page, which includes both the web-page element having the hyperlink and the content combined together in a same web page, thereby providing the suggested search-engine query comprised of the search term. 7. The computer-storage device of claim 1 , wherein the method further comprises analyzing historical user metrics to identify other suggested search-engine queries.

8. A system, comprising: a data processing apparatus; and a non-transitory computer readable storage medium storing instructions executable by the data processing apparatus and that upon execution cause the data processing apparatus to perform operations comprising: determining, for a native application that generates an application environment for display on a user device within the native application, the native application operating independent of a browser application that can operate on the user device, a set of environment instances of the native application, the determining comprising receiving a set of uniform resource identifiers for the native application from a publisher of the native application, each uniform resource identifier in the set of uniform resource identifiers corresponding to a corresponding environment instance in the set of environment instances; for each environment instance: determining textual data describing features of the corresponding environment instance, the textual data being data that is not rendered to be visible when the native application renders the environment instance on a user device display, the determining of textual data comprising: instantiating a virtual machine emulating an operating system of a user device; instantiating, within the virtual machine, the native application; accessing, within the virtual machine, the uniform resource identifier to which the environment instance corresponds, and in response to accessing each uniform resource identifier: generating in the virtual machine the environment instance that corresponds to the uniform resource identifier; and extracting the textual data provided to a rendering process of the native application, wherein the textual data is identified as invisible textual data for the rendering process so that the textual data is not rendered to be visible when the native application renders the environment instance on a user device display; generating, from the textual data, native application environment instance data describing content of the environment instance; and indexing the native application environment instance data for the native application in an index that is searchable by a search engine.

8. A system, comprising: a data processing apparatus; and a non-transitory computer readable storage medium storing instructions executable by the data processing apparatus and that upon execution cause the data processing apparatus to perform operations comprising: determining, for a native application that generates an application environment for display on a user device within the native application, the native application operating independent of a browser application that can operate on the user device, a set of environment instances of the native application, the determining comprising receiving a set of uniform resource identifiers for the native application from a publisher of the native application, each uniform resource identifier in the set of uniform resource identifiers corresponding to a corresponding environment instance in the set of environment instances; for each environment instance: determining textual data describing features of the corresponding environment instance, the textual data being data that is not rendered to be visible when the native application renders the environment instance on a user device display, the determining of textual data comprising: instantiating a virtual machine emulating an operating system of a user device; instantiating, within the virtual machine, the native application; accessing, within the virtual machine, the uniform resource identifier to which the environment instance corresponds, and in response to accessing each uniform resource identifier: generating in the virtual machine the environment instance that corresponds to the uniform resource identifier; and extracting the textual data provided to a rendering process of the native application, wherein the textual data is identified as invisible textual data for the rendering process so that the textual data is not rendered to be visible when the native application renders the environment instance on a user device display; generating, from the textual data, native application environment instance data describing content of the environment instance; and indexing the native application environment instance data for the native application in an index that is searchable by a search engine. 11. The system of claim 8 , wherein the operations further comprise: receiving, from a search engine, a query and data identifying one of the application environment instances as being responsive to the query based, in part, on the native application environment instance data; and generating a search result that identifies the corresponding environment instance of the native application as being responsive to the query.

3. The system of claim 1 , wherein the feature is a continuous feature.

3. The system of claim 1 , wherein the feature is a continuous feature. 5. The system of claim 3 , wherein the set of partitions for the continuous feature is defined by boundary values automatically determined during training of the speech recognition system using the training data.

12. A computer-implemented method of semantic information retrieval based on a semantic dictionary augmented with explicit rules that enable machine learning and deep contextual understanding comprising: curating in real-time and interactively semantic expressions taken from a networked database; configuring a gloss vector engine operable to generate semantic gloss vectors for data mining by unsupervised machine learning; configuring a deconstruction engine operable to identify well-formed sentences; configuring a data discovery engine operable to identify indirect communicating links; configuring a collocation engine operable to identify compound nouns; configuring a disambiguation engine operable to assign appropriate nouns given context; configuring a generic noun disambiguation engine operable to identify context shifts produced by use of generic or common nouns; configuring a pronoun disambiguation engine operable to link common nouns to proper nouns; configuring a data evaluation engine operable to identify well-formed sentences containing information of maximal semantic value; configuring a retrieval engine operable to return information of the highest semantic value for a given search term; and configuring a context targeting engine operable to display in context the specific sentence in the source article showing the query results wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus.

12. A computer-implemented method of semantic information retrieval based on a semantic dictionary augmented with explicit rules that enable machine learning and deep contextual understanding comprising: curating in real-time and interactively semantic expressions taken from a networked database; configuring a gloss vector engine operable to generate semantic gloss vectors for data mining by unsupervised machine learning; configuring a deconstruction engine operable to identify well-formed sentences; configuring a data discovery engine operable to identify indirect communicating links; configuring a collocation engine operable to identify compound nouns; configuring a disambiguation engine operable to assign appropriate nouns given context; configuring a generic noun disambiguation engine operable to identify context shifts produced by use of generic or common nouns; configuring a pronoun disambiguation engine operable to link common nouns to proper nouns; configuring a data evaluation engine operable to identify well-formed sentences containing information of maximal semantic value; configuring a retrieval engine operable to return information of the highest semantic value for a given search term; and configuring a context targeting engine operable to display in context the specific sentence in the source article showing the query results wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus. 20. The computer-based method of claim 12 further comprising: evaluating sentences; and scoring said sentences to enable selection of information of maximal semantic value from a corpus.

10. The computer-implemented method according to claim 1 , wherein the web-based document is a spreadsheet.

10. The computer-implemented method according to claim 1 , wherein the web-based document is a spreadsheet. 11. The computer-implemented method according to claim 10 , further comprising: acquiring the first data set into the data table from a database; examining data from the first data set to determine a data structure; and calculating a number of rows and columns in the data table which includes the first data set.

9. The method of claim 1 , further comprising: ranking each of the identified ideograms based on the respective calculated use-probability; and determining the first set of ideograms based on the respective rankings associated with the ideograms.

9. The method of claim 1 , further comprising: ranking each of the identified ideograms based on the respective calculated use-probability; and determining the first set of ideograms based on the respective rankings associated with the ideograms. 11. The method of claim 9 , wherein ranking each of the identified ideograms is further based on a calculated misspelling-probability that at least one of the n-grams of the received first query corresponds to a different n-gram.

22. The system of claim 21 , wherein each ranking score is determined based on at least one of a frequency, an interaction score, an endorsement score and a selection score that are specific to a respective query auto-completion.

22. The system of claim 21 , wherein each ranking score is determined based on at least one of a frequency, an interaction score, an endorsement score and a selection score that are specific to a respective query auto-completion. 24. The system of claim 22 , wherein: the frequency reflects a frequency at which the respective query auto-completion is used as a search query, the interaction score reflects user interaction with search results that had been previously generated based on the respective query auto-completion, the endorsement score reflects endorsements users have provided to search results that had been previously generated based on the respective query auto-completion, and the selection score reflects selections of the respective query auto-completion as a search query from a list of query auto-completions.

13. A system residing on a client computing device comprising computer code that, when executed by the client computing device, causes the client computing device to perform a method for illustrating where a ticket is located in an event venue, the method comprising: presenting, by a web browser of the client computing device, a filter module for allowing a user to perform a search of tickets listed for sale by a ticket service hosted by a web site; accepting, at the filter module, event criteria for at least one ticket and at least one event; accepting, at the filter module, price criteria for the at least one ticket and the at least one event; calling, by the filter module, an application programming interface of a mediator application executing in the web browser; constructing, by the mediator application, a request for filtering tickets by criteria based on the event and price criteria accepted at the filter module; sending the request for filtering tickets by criteria to the ticket service; receiving, at the mediator application, data representing a filtered ticket set meeting the event and price criteria from the ticket service; displaying, by the web browser, an interactive graphics-based event venue map illustrating a location of all sections at an event venue with at least one ticket meeting the event and price criteria, the interactive graphics-based event venue map being displayed at a size corresponding to a minimum zoom level; receiving, at the interactive graphics-based event venue map, input from the user to increase the size of the interactive graphics-based event venue map; presenting, by the interactive graphics-based event venue map, a dragger feature for allowing the user to move the interactive graphics-based event venue map if the size of the interactive graphics-based event venue map is increased from the minimum zoom level by at least a predetermined amount; accepting, at the interactive graphics-based event venue map, section selection criteria in response to the user selecting at least one section from the interactive graphics-based event venue map; calling, by the interactive graphics-based event venue map, the application programming interface of the mediator application executing in the web browser; constructing, by the mediator application, a request for retrieving tickets by section based on the section selection criteria accepted at the interactive graphics-based venue map; sending the request for retrieving tickets by section to the ticket service; receiving, from the ticket service at the mediator application, data representing tickets of the filtered ticket set that meet the section selection criteria; and displaying ticket information in a web browsing language comprising a ticket listing corresponding to the tickets of the filtered set that meet the section selection criteria, the displayed ticket information in the web browsing language allowing the user to drill down to a specific ticket in the ticket listing, causing a location of the specific ticket to be displayed in the interactive graphics-based event venue map.

13. A system residing on a client computing device comprising computer code that, when executed by the client computing device, causes the client computing device to perform a method for illustrating where a ticket is located in an event venue, the method comprising: presenting, by a web browser of the client computing device, a filter module for allowing a user to perform a search of tickets listed for sale by a ticket service hosted by a web site; accepting, at the filter module, event criteria for at least one ticket and at least one event; accepting, at the filter module, price criteria for the at least one ticket and the at least one event; calling, by the filter module, an application programming interface of a mediator application executing in the web browser; constructing, by the mediator application, a request for filtering tickets by criteria based on the event and price criteria accepted at the filter module; sending the request for filtering tickets by criteria to the ticket service; receiving, at the mediator application, data representing a filtered ticket set meeting the event and price criteria from the ticket service; displaying, by the web browser, an interactive graphics-based event venue map illustrating a location of all sections at an event venue with at least one ticket meeting the event and price criteria, the interactive graphics-based event venue map being displayed at a size corresponding to a minimum zoom level; receiving, at the interactive graphics-based event venue map, input from the user to increase the size of the interactive graphics-based event venue map; presenting, by the interactive graphics-based event venue map, a dragger feature for allowing the user to move the interactive graphics-based event venue map if the size of the interactive graphics-based event venue map is increased from the minimum zoom level by at least a predetermined amount; accepting, at the interactive graphics-based event venue map, section selection criteria in response to the user selecting at least one section from the interactive graphics-based event venue map; calling, by the interactive graphics-based event venue map, the application programming interface of the mediator application executing in the web browser; constructing, by the mediator application, a request for retrieving tickets by section based on the section selection criteria accepted at the interactive graphics-based venue map; sending the request for retrieving tickets by section to the ticket service; receiving, from the ticket service at the mediator application, data representing tickets of the filtered ticket set that meet the section selection criteria; and displaying ticket information in a web browsing language comprising a ticket listing corresponding to the tickets of the filtered set that meet the section selection criteria, the displayed ticket information in the web browsing language allowing the user to drill down to a specific ticket in the ticket listing, causing a location of the specific ticket to be displayed in the interactive graphics-based event venue map. 16. The system of claim 13 , wherein the dragger feature of the interactive graphics-based event venue map is presented if the size of the interactive graphics-based event venue map is increased from the minimum zoom level by at least 10%.

8. A computer program product stored on non-transitory computer readable storage medium, which when executed by a computer system having a memory and processor, provides product evaluation system, comprising: program instructions for identifying a set of products based on an inputted query; program instructions for collecting structured and unstructured data associated with the set of products; program instructions for generating a composite feature list from the structured and unstructured data; program instructions for generating a matrix for each identified product, wherein the matrix provides a set of features and any known limitations and benefits determined from the structured and unstructured data for each of the features; and program instructions that analyzes a usage context in view of the known limitations and benefits to evaluate compatibility of each product at a feature level, and generates interactive rankings and summaries.

8. A computer program product stored on non-transitory computer readable storage medium, which when executed by a computer system having a memory and processor, provides product evaluation system, comprising: program instructions for identifying a set of products based on an inputted query; program instructions for collecting structured and unstructured data associated with the set of products; program instructions for generating a composite feature list from the structured and unstructured data; program instructions for generating a matrix for each identified product, wherein the matrix provides a set of features and any known limitations and benefits determined from the structured and unstructured data for each of the features; and program instructions that analyzes a usage context in view of the known limitations and benefits to evaluate compatibility of each product at a feature level, and generates interactive rankings and summaries. 11. The program product of claim 8 , wherein the usage context includes a set of usage elements that are compared to the limitations and benefits to determine whether each usage element is compatible with an associated feature to generate compatibility score.

1. A method comprising: receiving a search request by at least one server computer, the search request identifying search criteria; cause, by the at least one server computer, a search of geographically referenced information using the search criteria to identify search results, the search results comprising a plurality of result items, each result item of the plurality having associated text for a display of the search results result items and having an associated location; for each result item of the plurality, the at least one server computer determining a distance of the result item from a user's location using the user's location and the result item's associated location; and causing, by the at least one server computer, the display of the search results, wherein the display of the search results comprises the text for each of the plurality of result items, and at least one appearance characteristic of the text varies for at least one result item of the search results based on the at least one result item's distance from the user's location, the result item's distance from the user's location is determined using the user's location and the at least one result item's associated location and one of the plurality of result items closest in distance to the user's location relative to other ones of the plurality of result items is displayed more prominently than the other ones of the plurality of result items, wherein the at least one appearance characteristic is selected from the group consisting of font size, font style, color, shading, three-dimensional height, associated features, and animation.

1. A method comprising: receiving a search request by at least one server computer, the search request identifying search criteria; cause, by the at least one server computer, a search of geographically referenced information using the search criteria to identify search results, the search results comprising a plurality of result items, each result item of the plurality having associated text for a display of the search results result items and having an associated location; for each result item of the plurality, the at least one server computer determining a distance of the result item from a user's location using the user's location and the result item's associated location; and causing, by the at least one server computer, the display of the search results, wherein the display of the search results comprises the text for each of the plurality of result items, and at least one appearance characteristic of the text varies for at least one result item of the search results based on the at least one result item's distance from the user's location, the result item's distance from the user's location is determined using the user's location and the at least one result item's associated location and one of the plurality of result items closest in distance to the user's location relative to other ones of the plurality of result items is displayed more prominently than the other ones of the plurality of result items, wherein the at least one appearance characteristic is selected from the group consisting of font size, font style, color, shading, three-dimensional height, associated features, and animation. 6. The method of claim 1 , wherein the at least one appearance characteristic of the text of the at least one result item of the displayed search results varies based on the at least one result item's distance from the user's location relative to at least one other result item's distance from the user's location.

1. A method for managing interactive voice response dialog between a machine comprising automatic speech recognition and a user, said method comprising the steps of: setting a mode confidence level parameter value to a first value prior to a first input from said user wherein said first input is of a speech input mode; selecting one of a plurality of audio prompts comprising speech to annunciate to the user from the machine based on said first value of said mode confidence level parameter, wherein said one of said plurality of audio prompts solicits said first input comprising a first semantic response from said user in said speech input mode; annunciating the at least one of a plurality of audio prompts to said user; receiving said first input from said user; determining a first speech recognition confidence level based on said first input; setting said mode confidence level parameter to a second value based on said first speech recognition confidence level, said second value indicating a lower level of confidence of recognition relative to said first value of said mode confidence level; selecting an another one of at least one of a plurality of audio prompts based on said mode confidence level; and annunciating to the user from the machine said another one of least one of a plurality of audio prompts comprising speech based on said second value of said mode confidence level wherein said another one of said plurality of phrases solicits said first semantic response from said user in a DTMF input mode.

1. A method for managing interactive voice response dialog between a machine comprising automatic speech recognition and a user, said method comprising the steps of: setting a mode confidence level parameter value to a first value prior to a first input from said user wherein said first input is of a speech input mode; selecting one of a plurality of audio prompts comprising speech to annunciate to the user from the machine based on said first value of said mode confidence level parameter, wherein said one of said plurality of audio prompts solicits said first input comprising a first semantic response from said user in said speech input mode; annunciating the at least one of a plurality of audio prompts to said user; receiving said first input from said user; determining a first speech recognition confidence level based on said first input; setting said mode confidence level parameter to a second value based on said first speech recognition confidence level, said second value indicating a lower level of confidence of recognition relative to said first value of said mode confidence level; selecting an another one of at least one of a plurality of audio prompts based on said mode confidence level; and annunciating to the user from the machine said another one of least one of a plurality of audio prompts comprising speech based on said second value of said mode confidence level wherein said another one of said plurality of phrases solicits said first semantic response from said user in a DTMF input mode. 7. The method of claim 1 further comprising the steps of: receiving a second input from said user in response to said another one of said plurality of audio prompts; setting said mode confidence level parameter to a third level based on said second input; and annunciating a third audio prompt to the user from the machine based on said third level of said mode confidence level parameter wherein said third audio prompt solicits input from said user in said DTMF input mode.

1. A computer-implemented information searching method, comprising the steps of: extracting one or more non-content characteristics of a document from a document set; analyzing the extracted non-content characteristics; generating an optimizing tool based on analyzing results; and optimizing a preliminary search result with the generated optimizing tool, wherein the step of optimizing includes the steps of: selecting, from the preliminary search result, a resulting document sequence having relatively high reliability; calculating a distance from each of the documents in the preliminary search results to each document of the resulting document sequence; adjusting the reliability values of the documents in the resulting document sequence; and arranging the documents in descending order of the adjusted reliability values to obtain optimized results, and wherein the distance from each of the documents in the preliminary search results to the document of the resulting document sequence equals a sum of weights of sides passed through by a directional path between two documents, the distance is infinite when there is no path between the document in the preliminary search results and the document in the resulting document sequence, the distance from one document to itself is zero, the distance L between the document in the preliminary search results and the document in the resulting document sequence is expressed by the following equation when there are plural paths between the two documents, L=1/((1/L 1 )+(1/L 2 )+ . . . +(1/LX)) where, L represents the distance between two documents, L 1 represents the distance of a path 1 , L 2 represents the distance of a path 2 , and LX represents the distance of a path X.

1. A computer-implemented information searching method, comprising the steps of: extracting one or more non-content characteristics of a document from a document set; analyzing the extracted non-content characteristics; generating an optimizing tool based on analyzing results; and optimizing a preliminary search result with the generated optimizing tool, wherein the step of optimizing includes the steps of: selecting, from the preliminary search result, a resulting document sequence having relatively high reliability; calculating a distance from each of the documents in the preliminary search results to each document of the resulting document sequence; adjusting the reliability values of the documents in the resulting document sequence; and arranging the documents in descending order of the adjusted reliability values to obtain optimized results, and wherein the distance from each of the documents in the preliminary search results to the document of the resulting document sequence equals a sum of weights of sides passed through by a directional path between two documents, the distance is infinite when there is no path between the document in the preliminary search results and the document in the resulting document sequence, the distance from one document to itself is zero, the distance L between the document in the preliminary search results and the document in the resulting document sequence is expressed by the following equation when there are plural paths between the two documents, L=1/((1/L 1 )+(1/L 2 )+ . . . +(1/LX)) where, L represents the distance between two documents, L 1 represents the distance of a path 1 , L 2 represents the distance of a path 2 , and LX represents the distance of a path X. 4. The information searching method as claimed in claim 1 , wherein the optimizing tool includes one of a classification-based optimizing tool, a time-based optimizing tool, and a document relationship-based optimizing tool.

3. The storage medium of claim 2 , further comprising instructions for applying the further term occurrence-level constraint to at least the term occurrence.

3. The storage medium of claim 2 , further comprising instructions for applying the further term occurrence-level constraint to at least the term occurrence. 4. The storage medium of claim 3 , wherein the instructions for selecting the candidate fact include instructions for selecting the candidate fact based at least in part on applying at least the further term occurrence-level constraint to the term occurrence.

21. A system comprising: a communication interface configured to receive a set of uncertain characters obtained as a result of a recognition process of a text image, the set of uncertain characters including an image of an uncertain character, a hypothesis about the uncertain character, and a confidence level associated with the hypothesis; a processor configured to: cause a display device to present to a user the image of the uncertain character from the set of uncertain characters over a text readout; receive, via the communication interface from a user input, marking data for the uncertain character; and adjust, using the received marking data, the confidence level associated with the hypothesis about the uncertain character for obtaining a confirmed hypothesis linked to the uncertain character.

21. A system comprising: a communication interface configured to receive a set of uncertain characters obtained as a result of a recognition process of a text image, the set of uncertain characters including an image of an uncertain character, a hypothesis about the uncertain character, and a confidence level associated with the hypothesis; a processor configured to: cause a display device to present to a user the image of the uncertain character from the set of uncertain characters over a text readout; receive, via the communication interface from a user input, marking data for the uncertain character; and adjust, using the received marking data, the confidence level associated with the hypothesis about the uncertain character for obtaining a confirmed hypothesis linked to the uncertain character. 24. The system of claim 21 , wherein the marking data is one of marked, unmarked, or rejected, and wherein the processor is configured to: in response to determining that the marking data is unmarked for the uncertain character, increase the confidence level of the hypothesis about the uncertain character by a first amount; and in response to determining that the marking data is rejected for the uncertain character, increase the confidence level of the hypothesis about the uncertain character by a second amount, wherein the second amount is larger than the first amount.

9. The method as claimed in claim 4 wherein said step of applying a grouping function g comprises: i. creating groupings of contexts from said initial set of contexts; ii. calculating a conditional entropy for each grouping of contexts; iii. selecting a grouping with a lowest conditional entropy; iv. reducing a size of said set of contexts by replacing elements which comprise the selected grouping with said grouping; and v. repeating steps (i)-(iv) until a size of said set of contexts equals the predetermined number of contexts.

9. The method as claimed in claim 4 wherein said step of applying a grouping function g comprises: i. creating groupings of contexts from said initial set of contexts; ii. calculating a conditional entropy for each grouping of contexts; iii. selecting a grouping with a lowest conditional entropy; iv. reducing a size of said set of contexts by replacing elements which comprise the selected grouping with said grouping; and v. repeating steps (i)-(iv) until a size of said set of contexts equals the predetermined number of contexts. 13. The method as claimed in claim 9 wherein said initial context model is a state machine context model and wherein said initial context model is used in a context-based YK compression process for compressing a sequence x=x1x2 . . . xm by parsing said sequence, and wherein the context set is chosen such that a next context from the context model is determined from the current context and a current parsed phrase.

4. The method as recited in claim 1 wherein the filtering comprises training the support vector machine classifier with a set of manually labeled couplet data resulting in a support vector machine classifier model.

4. The method as recited in claim 1 wherein the filtering comprises training the support vector machine classifier with a set of manually labeled couplet data resulting in a support vector machine classifier model. 6. The method as recited in claim 4 further comprising loading the support vector machine classifier model to the support vector machine classifier.