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6. The method of claim 4 , including comparing data indicative of a plurality of search results to data indicative of a second aspect of the user context to determine a plurality of relevance scores associated with the plurality of search results, the second aspect of the user context including data indicative of at least one task in which the user is engaged out of a plurality of possible user tasks.

6. The method of claim 4 , including comparing data indicative of a plurality of search results to data indicative of a second aspect of the user context to determine a plurality of relevance scores associated with the plurality of search results, the second aspect of the user context including data indicative of at least one task in which the user is engaged out of a plurality of possible user tasks. 10. The method of claim 6 , wherein the second aspect of the user context is based on at least one of (a) a location of the at least one predetermined word in the text being accessed by the user, (b) a style of the at least one predetermined word in the text being accessed by the user, (c) a presence of at least one specified word in the text being accessed by the user, (d) an absence of the at least one specified word in the text being accessed by the user, (e) metadata attributes of at least a portion of the text being accessed by the user, (f) a field presented by a computer application, (g) an attribute of information being presented in the computer application, (h) an element of the computer application visible to the user, (i) a document genre, (j) a document type, (k) a type associated with the computer application, (l) a method by which the user is accessing the computer application, (m) a role in an organization, (n) a type of the organization, (o) a property of the organization, (p) a stage in a task, (q) a stage in a workflow, (r) a type of task being supported by the computer application, (s) a stage in a task being executed by the computer application, (t) a pervious user behavior, (u) a topical area of interest, (v) a proportion of hyperlinked text to non-hyperlinked text, and (w) an average sentence length in the text being accessed by the user.

4. The computer implemented method of claim 1 further comprising receiving, by the computer, result pages corresponding to each of the first query and the one or more secondary queries from the search engine.

4. The computer implemented method of claim 1 further comprising receiving, by the computer, result pages corresponding to each of the first query and the one or more secondary queries from the search engine. 6. The computer implemented method of claim 4 further comprising processing, by the computer, the result pages corresponding to the one or more secondary queries by exploring one or more web-links present in the result pages corresponding to each of the one or more secondary queries.

3. The method of claim 2 , wherein: the discrete gesture recognizer has a first set of gesture recognizer states including: a gesture possible state, corresponding to an initial state of the discrete gesture recognizer; a gesture recognized state, corresponding to recognition of the respective discrete gesture; and a gesture failed state, corresponding to failure of the discrete gesture recognizer to recognize the one or more touches as the respective discrete gesture; and the continuous gesture recognizer has a second set of gesture recognizer states including: a gesture possible state; a gesture began state, corresponding to initial recognition of the respective continuous gesture; a gesture changed state, corresponding to a respective change in location of the respective touch; a gesture ended state, corresponding to completion of the respective continuous gesture; a gesture canceled state, corresponding to interruption of the recognition of the respective continuous gesture; and a gesture failed state, corresponding to failure of the continuous gesture recognizer to recognize the one or more touches as the respective continuous gesture.

3. The method of claim 2 , wherein: the discrete gesture recognizer has a first set of gesture recognizer states including: a gesture possible state, corresponding to an initial state of the discrete gesture recognizer; a gesture recognized state, corresponding to recognition of the respective discrete gesture; and a gesture failed state, corresponding to failure of the discrete gesture recognizer to recognize the one or more touches as the respective discrete gesture; and the continuous gesture recognizer has a second set of gesture recognizer states including: a gesture possible state; a gesture began state, corresponding to initial recognition of the respective continuous gesture; a gesture changed state, corresponding to a respective change in location of the respective touch; a gesture ended state, corresponding to completion of the respective continuous gesture; a gesture canceled state, corresponding to interruption of the recognition of the respective continuous gesture; and a gesture failed state, corresponding to failure of the continuous gesture recognizer to recognize the one or more touches as the respective continuous gesture. 4. The method of claim 3 , wherein the gesture recognized state and the gesture ended state have an identical gesture recognizer state value.

20. A system for the symbolic-based recognition of a handwriting input to an input surface having an output provided as a stream of coordinate data points, comprising: a data base memory storing a compilation of text-pattern pairs, said pattern of each said pair having been derived as sample features of said handwriting and including an associated sample index derived as aspects of said handwriting sample features, said text of each said pair representing at least one predetermined character glyph; a processor, responsive to said output to extract pattern test features and a corresponding test index therefrom, responsive to access said memory stored compilation and identify a said sample index corresponding with said test index, responsive to carry out a comparison of said pattern test features with said pattern sample features associated with said identified sample index, responsive in the presence of a correspondence between said pattern test and sample features to derive output signals corresponding with said text associated with said pattern sample features, said pattern symbols and test features including: a first word feature provided as a value corresponding with the word bottom location relative to the word base line of a said output representing a word, said relative word bottom being determined to be K* ((y.sub.max +line-space)/(2*line-space)) where y.sub.max is the visually lowest part of such word measured from the baseline, line-space is a selected spacing between writing lines and K is a constant, a second feature word provided as a value corresponding with the relative height of a said output representing a word, and a third word feature provided as a value corresponding with the aspect ratio of a said output representing a word, said word aspect ratio generally being determined to be K (height/diagonal) where K is a constant, height is word height, and diagonal is the square root of the height squared plus the width squared; and display means responsive to said derived output signals for effecting the publication of a said predetermined character glyph sequence of said text associated with said pattern sample features.

20. A system for the symbolic-based recognition of a handwriting input to an input surface having an output provided as a stream of coordinate data points, comprising: a data base memory storing a compilation of text-pattern pairs, said pattern of each said pair having been derived as sample features of said handwriting and including an associated sample index derived as aspects of said handwriting sample features, said text of each said pair representing at least one predetermined character glyph; a processor, responsive to said output to extract pattern test features and a corresponding test index therefrom, responsive to access said memory stored compilation and identify a said sample index corresponding with said test index, responsive to carry out a comparison of said pattern test features with said pattern sample features associated with said identified sample index, responsive in the presence of a correspondence between said pattern test and sample features to derive output signals corresponding with said text associated with said pattern sample features, said pattern symbols and test features including: a first word feature provided as a value corresponding with the word bottom location relative to the word base line of a said output representing a word, said relative word bottom being determined to be K* ((y.sub.max +line-space)/(2*line-space)) where y.sub.max is the visually lowest part of such word measured from the baseline, line-space is a selected spacing between writing lines and K is a constant, a second feature word provided as a value corresponding with the relative height of a said output representing a word, and a third word feature provided as a value corresponding with the aspect ratio of a said output representing a word, said word aspect ratio generally being determined to be K (height/diagonal) where K is a constant, height is word height, and diagonal is the square root of the height squared plus the width squared; and display means responsive to said derived output signals for effecting the publication of a said predetermined character glyph sequence of said text associated with said pattern sample features. 23. The system of claim 20 in which said pattern sample and test features include segment based features derived from each segment of each stroke defining sequence of said data points and comprising: a fourth segment feature provided as a value corresponding with the absolute inflection point x-coordinate relative to the stroke's bounding box; a fifth segment feature provided as a value corresponding with the absolute inflection point y-coordinate relative to the stroke's bounding box; a sixth segment feature provided as a value corresponding with the x curvature of a segment of a said stroke; and a seventh segment feature provided as a value corresponding with the y curvature of a segment of a said stroke.

1. An image processing method for extracting features of a document image composed of a plurality of pixels, and for determining similarity between the document image and a reference image based on the extracted features, the method comprising steps of: storing features associated with each of a plurality of the reference images in advance; generating, based on a pixel value of each pixel of the document image, a plurality of layer images having different pixel value ranges; performing a binarization process on each of the generated layer images to extract a feature point; calculating features of the document image based on the feature point extracted for each of the layer images; determining whether the calculated features corresponds to the features associated with the reference image; voting for, when the features are determined to be corresponding to each other, the reference image associated with the features for each corresponding features; determining, based on the number of votes obtained by the voting, whether the document image is similar to the reference image; determining, based on the pixel value of each pixel of the document image, whether at least a region of the document image is a text component or a pictorial component; and generating a plurality of layer images for the region determined as being a pictorial component, wherein one or more of the steps are performed using one or more processors.

1. An image processing method for extracting features of a document image composed of a plurality of pixels, and for determining similarity between the document image and a reference image based on the extracted features, the method comprising steps of: storing features associated with each of a plurality of the reference images in advance; generating, based on a pixel value of each pixel of the document image, a plurality of layer images having different pixel value ranges; performing a binarization process on each of the generated layer images to extract a feature point; calculating features of the document image based on the feature point extracted for each of the layer images; determining whether the calculated features corresponds to the features associated with the reference image; voting for, when the features are determined to be corresponding to each other, the reference image associated with the features for each corresponding features; determining, based on the number of votes obtained by the voting, whether the document image is similar to the reference image; determining, based on the pixel value of each pixel of the document image, whether at least a region of the document image is a text component or a pictorial component; and generating a plurality of layer images for the region determined as being a pictorial component, wherein one or more of the steps are performed using one or more processors. 5. The image processing method according to claim 1 , further comprising steps of: extracting, for the region determined as being a pictorial component, a feature point from the plurality of layer images; and calculating features of the document image based on the extracted feature point.

1. A non-transitory computer-readable storage medium having a computer program stored thereon for causing a suitably programmed system to process by one or more computer processors computer-program code by performing a method when the computer-program code is executed on the suitably programmed system, the method facilitating collaboration, the method comprising: processing, by the suitably programmed system, a first request from a first user terminal of a plurality of user terminals to associate a first contextual object with a data measure mapped to a multi-dimensional data model, the first contextual object comprising information received by the first user terminal from a first user of the first user terminal, the multi-dimensional data model configured for access by online analytical processing (OLAP) applications; determining, by the suitably programmed system, coordinates of a plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; storing, by the suitably programmed system, in an electronic data storage the first contextual object in association with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; receiving, by the suitably programmed system, a second request from a second user terminal of the plurality of user terminals, the second request dynamically generated based on a value of the data measure being displayed by the second user terminal to a second user of the second user terminal, the second request indicating the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure, the second request configured to identify contextual objects associated with the coordinates; determining, by the suitably programmed system, an existence of contextual objects that are associated with the coordinates indicated in the second request; retrieving, by the suitably programmed system, the first contextual object from the electronic data storage using the coordinates of the plurality of data dimensions of the multi-dimensional data model; transmitting, by the suitably programmed system, to the second user terminal an indication of the first contextual object for display by the second user terminal in juxtaposition with the value of the data measure; and transmitting, by the suitably programmed system, to the second user terminal the first contextual object.

1. A non-transitory computer-readable storage medium having a computer program stored thereon for causing a suitably programmed system to process by one or more computer processors computer-program code by performing a method when the computer-program code is executed on the suitably programmed system, the method facilitating collaboration, the method comprising: processing, by the suitably programmed system, a first request from a first user terminal of a plurality of user terminals to associate a first contextual object with a data measure mapped to a multi-dimensional data model, the first contextual object comprising information received by the first user terminal from a first user of the first user terminal, the multi-dimensional data model configured for access by online analytical processing (OLAP) applications; determining, by the suitably programmed system, coordinates of a plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; storing, by the suitably programmed system, in an electronic data storage the first contextual object in association with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; receiving, by the suitably programmed system, a second request from a second user terminal of the plurality of user terminals, the second request dynamically generated based on a value of the data measure being displayed by the second user terminal to a second user of the second user terminal, the second request indicating the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure, the second request configured to identify contextual objects associated with the coordinates; determining, by the suitably programmed system, an existence of contextual objects that are associated with the coordinates indicated in the second request; retrieving, by the suitably programmed system, the first contextual object from the electronic data storage using the coordinates of the plurality of data dimensions of the multi-dimensional data model; transmitting, by the suitably programmed system, to the second user terminal an indication of the first contextual object for display by the second user terminal in juxtaposition with the value of the data measure; and transmitting, by the suitably programmed system, to the second user terminal the first contextual object. 17. The non-transitory computer-readable storage medium of claim 1 , wherein the indication of the first contextual object comprises a parameter calculated based on the value of the data measure.

14. The system of claim 11 , wherein the at least one processor is further operable to obtain a description of the selected database object from the database, and wherein the one or more input fields are generated based at least in part on the obtained description.

14. The system of claim 11 , wherein the at least one processor is further operable to obtain a description of the selected database object from the database, and wherein the one or more input fields are generated based at least in part on the obtained description. 15. The system of claim 14 , wherein the description of the selected database object comprises one or more parameters utilized in the query for the selected database object.

1. A computer-implemented method for searching using an adaptive thesaurus, comprising: receiving a search query including a query term; retrieving, from the adaptive thesaurus, an expansion term stored in association with an index term matching the query term, wherein metadata is stored in association with the expansion term and the index term, and the metadata includes: a recall gain meeting a recall gain threshold, wherein the recall gain identifies a value of expanding the search query to another term versus a computational cost; an expansion independence meeting an expansion independence threshold; and a semantic similarity meeting a semantic similarity threshold; and expanding, using a processor, the search query using the expansion term.

1. A computer-implemented method for searching using an adaptive thesaurus, comprising: receiving a search query including a query term; retrieving, from the adaptive thesaurus, an expansion term stored in association with an index term matching the query term, wherein metadata is stored in association with the expansion term and the index term, and the metadata includes: a recall gain meeting a recall gain threshold, wherein the recall gain identifies a value of expanding the search query to another term versus a computational cost; an expansion independence meeting an expansion independence threshold; and a semantic similarity meeting a semantic similarity threshold; and expanding, using a processor, the search query using the expansion term. 5. The method of claim 1 , further comprising: displaying the expansion term to a user; and enabling the user to select the displayed expansion term for expanding the search query.

1. A relationship information expansion apparatus stored in a processor comprising: a relationship information storage unit in which a relationship information piece including two or more language expressions having a semantic relationship is stored; a similarity information storage unit in which two or more similarity information pieces each including two or more similar language expressions are stored; a candidate expanded relationship information storage unit in which a candidate expanded relationship information piece, which is the relationship information piece in which at least one language expression was replaced with a similar language expression, is stored; a candidate expanded relationship information generation unit for generating a candidate expanded relationship information piece from the relationship information piece stored in the relationship information storage unit by replacing at least one language expression in the relationship information piece with a language expression similar to the at least one language expression, using the similarity information pieces, and accumulating the candidate expanded relationship information piece in the candidate expanded relationship information storage unit; a score acquisition unit for acquiring a score that indicates a probability that the candidate expanded relationship information piece stored in the candidate expanded relationship information storage unit has a semantic relationship; and a selection unit for selecting, using the score acquired by the score acquisition unit, an expanded relationship information piece, which is a candidate expanded relationship information piece having a high score among candidate expanded relationship information pieces stored in the candidate expanded relationship information storage unit, wherein the score acquisition unit calculates a number of replacement which is performed to generate a same candidate expanded relationship information piece from relationship information pieces, and acquires a route score of the candidate expanded relationship information piece, and the route score takes a higher value as the number is higher, and wherein the score acquisition unit acquires a co-occurrence score that takes a higher score when the two or more language expressions included in the candidate expanded relationship information piece co-occur with a co-occurring language expression, which is a language expression having a high co-occurrence degree with two or more language expressions included in each relationship information piece having a semantic relationship of the same type as the semantic relationship of the relationship information piece used at the time of generation of the candidate expanded relationship information piece, than when only the two or more language expressions included in the candidate expanded relationship information piece co-occur with one another.

1. A relationship information expansion apparatus stored in a processor comprising: a relationship information storage unit in which a relationship information piece including two or more language expressions having a semantic relationship is stored; a similarity information storage unit in which two or more similarity information pieces each including two or more similar language expressions are stored; a candidate expanded relationship information storage unit in which a candidate expanded relationship information piece, which is the relationship information piece in which at least one language expression was replaced with a similar language expression, is stored; a candidate expanded relationship information generation unit for generating a candidate expanded relationship information piece from the relationship information piece stored in the relationship information storage unit by replacing at least one language expression in the relationship information piece with a language expression similar to the at least one language expression, using the similarity information pieces, and accumulating the candidate expanded relationship information piece in the candidate expanded relationship information storage unit; a score acquisition unit for acquiring a score that indicates a probability that the candidate expanded relationship information piece stored in the candidate expanded relationship information storage unit has a semantic relationship; and a selection unit for selecting, using the score acquired by the score acquisition unit, an expanded relationship information piece, which is a candidate expanded relationship information piece having a high score among candidate expanded relationship information pieces stored in the candidate expanded relationship information storage unit, wherein the score acquisition unit calculates a number of replacement which is performed to generate a same candidate expanded relationship information piece from relationship information pieces, and acquires a route score of the candidate expanded relationship information piece, and the route score takes a higher value as the number is higher, and wherein the score acquisition unit acquires a co-occurrence score that takes a higher score when the two or more language expressions included in the candidate expanded relationship information piece co-occur with a co-occurring language expression, which is a language expression having a high co-occurrence degree with two or more language expressions included in each relationship information piece having a semantic relationship of the same type as the semantic relationship of the relationship information piece used at the time of generation of the candidate expanded relationship information piece, than when only the two or more language expressions included in the candidate expanded relationship information piece co-occur with one another. 3. The relationship information expansion apparatus according to claim 1 , wherein the score acquisition unit performs machine learning in which a language expression that co-occurs with two or more language expressions included in a group of those two or more language expressions is used at least as a feature, and in which a value of the feature and existence or non-existence of a semantic relationship in the group of the two or more language expressions are used as training data, and acquires a co-occurrence score according to a probability degree, which is an output in a case where the two or more language expressions included in the candidate expanded relationship information piece are input.

7. A method for facilitating tagging of computerized data, the method comprising: operating at least one programmed processor to carry out a series of acts identified by executable instructions with which the at least one programmed processor is programmed, the series of acts comprising: detecting a selection by a user of at least one file via a computing interface having a graphical window to display information about contents of a file system, the contents comprising the at least one file; detecting one or more inputs corresponding to successive characters of a tag desired to be applied to at least one first file; activating a tagging mode for the graphical window upon detecting the user selection and the one or more inputs without requiring any user action other than the user selection and the one or more inputs corresponding to successive characters of the tag to be applied to at least one first file, wherein the graphical window includes at least one element of a user interface that, when the graphical window is in the tagging mode, displays information regarding suggested tags that may be applied to the at least one first file; and in response to activation of the tagging mode: determining at least one local suggested tag from at least one local data store of tags; retrieving a set of tags from at least one external data store of tags based on at least one characteristic of the at least one first file, the at least one external data store of tags being different from the at least one local data store of tags; determining at least one external suggested tag from the set of tags; and automatically providing, via the at least one element of the user interface of the graphical window, the at least one local suggested tag and the at least one external suggested tag to the user as the suggested tags for the at least one first file.

7. A method for facilitating tagging of computerized data, the method comprising: operating at least one programmed processor to carry out a series of acts identified by executable instructions with which the at least one programmed processor is programmed, the series of acts comprising: detecting a selection by a user of at least one file via a computing interface having a graphical window to display information about contents of a file system, the contents comprising the at least one file; detecting one or more inputs corresponding to successive characters of a tag desired to be applied to at least one first file; activating a tagging mode for the graphical window upon detecting the user selection and the one or more inputs without requiring any user action other than the user selection and the one or more inputs corresponding to successive characters of the tag to be applied to at least one first file, wherein the graphical window includes at least one element of a user interface that, when the graphical window is in the tagging mode, displays information regarding suggested tags that may be applied to the at least one first file; and in response to activation of the tagging mode: determining at least one local suggested tag from at least one local data store of tags; retrieving a set of tags from at least one external data store of tags based on at least one characteristic of the at least one first file, the at least one external data store of tags being different from the at least one local data store of tags; determining at least one external suggested tag from the set of tags; and automatically providing, via the at least one element of the user interface of the graphical window, the at least one local suggested tag and the at least one external suggested tag to the user as the suggested tags for the at least one first file. 8. The method of claim 7 further comprising: relaying an indication to the user via the computing interface, upon activation of the tagging mode, that the tagging mode is activated.

15. The computer program product of claim 13 , wherein the XML document file, the XML document descriptor file, and the test input data file are created and stored external to the test script.

15. The computer program product of claim 13 , wherein the XML document file, the XML document descriptor file, and the test input data file are created and stored external to the test script. 16. The computer program product of claim 15 , wherein the XML document file and XML document descriptor file are stored in a common repository.

9. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving, from a client device, audio data corresponding to an utterance; receiving, from the client device, marker data corresponding to a first portion of a plurality of portions of an audio presentation, the audio presentation presented by the client device contemporaneously with capture of the utterance by the client device; generating a transcription of the utterance by performing automatic speech recognition on at least a portion of the audio data; determining an action to be taken responsive to the utterance based at least partly on the transcription and the marker data; and performing the action.

9. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving, from a client device, audio data corresponding to an utterance; receiving, from the client device, marker data corresponding to a first portion of a plurality of portions of an audio presentation, the audio presentation presented by the client device contemporaneously with capture of the utterance by the client device; generating a transcription of the utterance by performing automatic speech recognition on at least a portion of the audio data; determining an action to be taken responsive to the utterance based at least partly on the transcription and the marker data; and performing the action. 10. The computer-implemented method of claim 9 , wherein at least a portion of the audio presentation is presented simultaneously with capture of at least a portion of the utterance by the client device.

15. A non-transitory computer readable storage medium storing one or more programs configured to be executed by a computing device, the one or more programs when executed cause the computing device to: identify a set of values from a plurality of facts associated with an entity, wherein the plurality of facts are stored in a fact repository, and a respective fact in the plurality of facts includes: (i) an attribute descriptive of the fact; and (ii) a value corresponding to the attribute; responsive to a search for a first value, in the set of values, included in a first fact in the plurality of facts: identify, in the plurality of facts, a second fact associated with the entity; and cause to be displayed to a user: (A) a link to the second fact, wherein: the link, when selected, invokes a search of the fact repository in accordance with one or more search parameters; and the one or more search parameters include a value corresponding to an attribute included in the second fact; and (B) information representing a confidence value associated with the second fact.

15. A non-transitory computer readable storage medium storing one or more programs configured to be executed by a computing device, the one or more programs when executed cause the computing device to: identify a set of values from a plurality of facts associated with an entity, wherein the plurality of facts are stored in a fact repository, and a respective fact in the plurality of facts includes: (i) an attribute descriptive of the fact; and (ii) a value corresponding to the attribute; responsive to a search for a first value, in the set of values, included in a first fact in the plurality of facts: identify, in the plurality of facts, a second fact associated with the entity; and cause to be displayed to a user: (A) a link to the second fact, wherein: the link, when selected, invokes a search of the fact repository in accordance with one or more search parameters; and the one or more search parameters include a value corresponding to an attribute included in the second fact; and (B) information representing a confidence value associated with the second fact. 17. The non-transitory computer readable storage medium of claim 15 , wherein the one or more programs when executed further cause the computing device to: cause to be displayed to a user, (C) an importance value associated with the second fact.

5. An interactive searching apparatus, including: one or more processors configured to execute one or more software modules, the one or more software modules including: an obtaining module configured to obtain a query from a webpage on a user device; and a generating module configured to generate intention clarification information of the query according to a history search log associated with the query and a predetermined semantic knowledge base, the intention clarification information configured to be displayed in the webpage on the user device and including at one least candidate query related to the query; wherein the generating module is further configured to: generate guiding information, the guiding information configured to be displayed in the webpage on the user device and including at least one question related to the query from the webpage on the user device; obtain first information according to a configuration template; obtain second information according to a word set configured to generate the interactive candidate; obtain one or more of the following: a hypernym of the sibling set and a hypernym of the hyponym set from the at least one word; match an interrogative set with the hypernym according to a predetermined language model; obtain an expression with a highest probability of matching; treat the expression with the highest probability of matching as the second information; obtain third information according to the query, in which the word set comprises the hyponym set and the sibling set; combine the first information, the second information and the third information to form the guiding information; segment the query into at least one word; obtain a hyponym set and/or sibling set of the at least one word according to the history search log associated with the at least one word and the semantic knowledge base; generate interactive candidates configured to clarify a query intention according to the hyponym set and/or sibling set; combine the interactive candidates to form the at one least candidate query; and wherein the semantic knowledge base comprises a plurality of words having a semantic hypernym-hyponym relationship and/or a semantic apposition relationship.

5. An interactive searching apparatus, including: one or more processors configured to execute one or more software modules, the one or more software modules including: an obtaining module configured to obtain a query from a webpage on a user device; and a generating module configured to generate intention clarification information of the query according to a history search log associated with the query and a predetermined semantic knowledge base, the intention clarification information configured to be displayed in the webpage on the user device and including at one least candidate query related to the query; wherein the generating module is further configured to: generate guiding information, the guiding information configured to be displayed in the webpage on the user device and including at least one question related to the query from the webpage on the user device; obtain first information according to a configuration template; obtain second information according to a word set configured to generate the interactive candidate; obtain one or more of the following: a hypernym of the sibling set and a hypernym of the hyponym set from the at least one word; match an interrogative set with the hypernym according to a predetermined language model; obtain an expression with a highest probability of matching; treat the expression with the highest probability of matching as the second information; obtain third information according to the query, in which the word set comprises the hyponym set and the sibling set; combine the first information, the second information and the third information to form the guiding information; segment the query into at least one word; obtain a hyponym set and/or sibling set of the at least one word according to the history search log associated with the at least one word and the semantic knowledge base; generate interactive candidates configured to clarify a query intention according to the hyponym set and/or sibling set; combine the interactive candidates to form the at one least candidate query; and wherein the semantic knowledge base comprises a plurality of words having a semantic hypernym-hyponym relationship and/or a semantic apposition relationship. 6. The method according to claim 5 , wherein the query from the webpage is an internet search query performed by a web search engine.

2. The method of claim 1 , further comprising parsing a query corresponding to the consumer command tree.

2. The method of claim 1 , further comprising parsing a query corresponding to the consumer command tree. 3. The method of claim 2 , further comprising receiving an extended structured query language (eSQL) string in the query.

15. A system, comprising: a network; a first I/O device connected to the network; a second I/O device connected to the network; a processor and a memory connected to at least one of the network, the first I/O device, and the second I/O device, wherein the memory includes computer-readable instruction which, when executed, cause: the processor to associate a word with an image; the first I/O device to display the image; the first I/O device to display the word; the first I/O device to receive an input from a first player indicative of a portion of the image to be displayed on the second I/O device to a second player, wherein the input is received after the first I/O device displays the image and the word to the first player; the second I/O device to display a portion of the image, wherein the portion of the image displayed on the second I/O device is less than all of the image, wherein the portion of the image displayed on the second I/O device is less than the image displayed to the first I/O device, and wherein the portion of the image displayed on the second I/O device is determined by the input received by the first I/O device; the second I/O device to receive an input from the second player after the portion of the image is displayed on the second I/O device, wherein the portion of the image displayed on the second I/O device is less than the image displayed on the first I/O device; and the processor to determine whether the input from the second I/O device is related to the image.

15. A system, comprising: a network; a first I/O device connected to the network; a second I/O device connected to the network; a processor and a memory connected to at least one of the network, the first I/O device, and the second I/O device, wherein the memory includes computer-readable instruction which, when executed, cause: the processor to associate a word with an image; the first I/O device to display the image; the first I/O device to display the word; the first I/O device to receive an input from a first player indicative of a portion of the image to be displayed on the second I/O device to a second player, wherein the input is received after the first I/O device displays the image and the word to the first player; the second I/O device to display a portion of the image, wherein the portion of the image displayed on the second I/O device is less than all of the image, wherein the portion of the image displayed on the second I/O device is less than the image displayed to the first I/O device, and wherein the portion of the image displayed on the second I/O device is determined by the input received by the first I/O device; the second I/O device to receive an input from the second player after the portion of the image is displayed on the second I/O device, wherein the portion of the image displayed on the second I/O device is less than the image displayed on the first I/O device; and the processor to determine whether the input from the second I/O device is related to the image. 18. The system of claim 15 , further comprising a memory including computer-readable instruction which, when executed, cause: a processor to identify an image and a corresponding input submitted at the second I/O device that were determined to be related to each other; the processor to identify additional information associated with the input and image; and the memory to store the input, the image, and the additional information associated with the input and the image.

5. The method of claim 4 , wherein applying a Gaussian mixture model includes applying a Gaussian mixture model based on a maximum likelihood estimation score.

5. The method of claim 4 , wherein applying a Gaussian mixture model includes applying a Gaussian mixture model based on a maximum likelihood estimation score. 6. The method of claim 5 and further comprising: calculating the maximum likelihood estimation score from previously classified phrasal translation pairs.

2. The method of claim 1 further comprises the steps of: deactivating the execution of said first one of said scripts by said computer system by a third one of said scripts being executed by said computer system; and controlling a third operation in said process by the execution of said second one of said scripts by said computer system in response to said first signal upon the deactivation of the execution of said first one of said scripts.

2. The method of claim 1 further comprises the steps of: deactivating the execution of said first one of said scripts by said computer system by a third one of said scripts being executed by said computer system; and controlling a third operation in said process by the execution of said second one of said scripts by said computer system in response to said first signal upon the deactivation of the execution of said first one of said scripts. 3. The method of claim 2 wherein said real-time telephone process assumes a plurality of states and each of said program scripts comprises a plurality of groups of instructions each of whose execution is determined by said computer system responding to one of the process states and one of the signals from the real-time telephone process, said executing step to control said first operation comprises the steps of responding to said first signal by said computer system's execution of one of said groups of instructions of said first one of said scripts upon said process being in one of said states; performing the control of said first operation by said computer system's execution of one of said program instructions of said group of instructions of said first one of said scripts; and said step of blocking comprises the step of stopping said computer system's execution of further groups of instructions in response to said first signal by execution of a second one of said instructions of said group of instructions of said first one of said script.

12. The non-transitory machine-readable storage medium of claim 9 , the instructions further comprising: receiving a second request from a second end-user system for registration; generating a second text-phrase; transmitting the second text-phrase to the second end-user system; and receiving a second audio signal from the second end-user system that corresponds to the second text-phrase.

12. The non-transitory machine-readable storage medium of claim 9 , the instructions further comprising: receiving a second request from a second end-user system for registration; generating a second text-phrase; transmitting the second text-phrase to the second end-user system; and receiving a second audio signal from the second end-user system that corresponds to the second text-phrase. 13. The non-transitory machine-readable storage medium of claim 12 , the instructions, when executed by the computing device, cause the computing device to perform a method further comprising: generating a second voice-template based on the second audio signal; and saving the second voice-template indexed based on an identity indicated in the second request.

1. A printing apparatus comprising: a printing engine; a print processor operatively connected to said printing engine; and a user interface operatively connected to said print processor, said user interface receiving instructions to retrieve a remote electronic document maintained within a print queue of an external server, said user interface displaying a full-printing menu option and a second printing menu option, based on said user interface receiving selection of said full-printing menu option, said printing engine printing all of said remote electronic document without pausing to print a fully printed document, and based on said user interface receiving selection of said second printing menu option: said printing engine beginning printing sample pages of said remote electronic document and pausing printing said remote electronic document to print a partially printed document, said sample pages comprising non-consecutive pages of said remote electronic document appearing at various locations within said remote electronic document; said user interface displaying an inquiry regarding whether said partially printed document is acceptable after said pausing printing; said printing engine printing a remainder of said remote electronic document based on said user interface receiving input that said partially printed document is acceptable, said remainder comprising all pages of said remote electronic document other than said sample pages; and said print processor canceling printing said remainder of said remote electronic document and resetting said print queue of said external server to indicate that said remote electronic document has not been printed, based on said user interface receiving input that said partially printed document is unacceptable.

1. A printing apparatus comprising: a printing engine; a print processor operatively connected to said printing engine; and a user interface operatively connected to said print processor, said user interface receiving instructions to retrieve a remote electronic document maintained within a print queue of an external server, said user interface displaying a full-printing menu option and a second printing menu option, based on said user interface receiving selection of said full-printing menu option, said printing engine printing all of said remote electronic document without pausing to print a fully printed document, and based on said user interface receiving selection of said second printing menu option: said printing engine beginning printing sample pages of said remote electronic document and pausing printing said remote electronic document to print a partially printed document, said sample pages comprising non-consecutive pages of said remote electronic document appearing at various locations within said remote electronic document; said user interface displaying an inquiry regarding whether said partially printed document is acceptable after said pausing printing; said printing engine printing a remainder of said remote electronic document based on said user interface receiving input that said partially printed document is acceptable, said remainder comprising all pages of said remote electronic document other than said sample pages; and said print processor canceling printing said remainder of said remote electronic document and resetting said print queue of said external server to indicate that said remote electronic document has not been printed, based on said user interface receiving input that said partially printed document is unacceptable. 4. The printing apparatus according to claim 1 , said sample pages comprising a last page of said remote electronic document.

3. The method of claim 2 , wherein determining whether the text of the delimited phrase satisfies a condition of the rule comprises determining whether a particular pattern of characters is present in the delimited phrase, the particular pattern including a delimiter character, and wherein modifying the delimited phrase comprises modifying the particular pattern of characters.

3. The method of claim 2 , wherein determining whether the text of the delimited phrase satisfies a condition of the rule comprises determining whether a particular pattern of characters is present in the delimited phrase, the particular pattern including a delimiter character, and wherein modifying the delimited phrase comprises modifying the particular pattern of characters. 5. The method of claim 3 , wherein the particular pattern of characters is specified by a regular expression.

10. A method as in claim 9 , wherein performing an editing function includes editing at least one cost function.

10. A method as in claim 9 , wherein performing an editing function includes editing at least one cost function. 11. A method as in claim 10 , wherein performing an editing function includes changing at least one or more parameters of a target-cost function.

61. The computer accessible storage medium of claim 45 , wherein each contact entry comprises historical context information indicating context information associated with the contact entry's past usage, wherein in said identifying the program instructions are executable to implement identifying one or more context appropriate contact entries from the contact entries based on the current context information and according to each entry's historical context information.

61. The computer accessible storage medium of claim 45 , wherein each contact entry comprises historical context information indicating context information associated with the contact entry's past usage, wherein in said identifying the program instructions are executable to implement identifying one or more context appropriate contact entries from the contact entries based on the current context information and according to each entry's historical context information. 64. The computer accessible storage medium of claim 61 , wherein the current context information comprises a current device identifier and the historical context information of each contact entry comprises information indicating the device that was used when each entry was historically selected and wherein in said identifying the program instructions are executable to implement identifying one or more contact entries based on each entry's historical context information and the current device identifier.

1. A mobile media consumption device comprising: a display device; one or more hardware processors; and one or more computer-readable storage devices storing processor-executable instructions that are executable by the one or more hardware processors to implement a storytelling module configured to: present a visual experience capable of telling a story, the story including an authored series of events and visual context, the authored series of events representing a storyline of the story, the visual context providing context for the storyline, the visual experience including story views and context views, the story views each having at least a portion of a respective event of the authored series of events, the context views each including at least a portion of the visual context for the storyline; display a portion of the visual experience on the display device based on a display view that is initially mapped to the portion of the visual experience; cause the display view to move across the visual experience and map to different portions of the visual experience based on a user input; determine whether the display view corresponds to a story view or a context view based on an amount of the respective event visually included within the display view; and perform one or more operations associated with a progression through the authored series of events based on the determination.

1. A mobile media consumption device comprising: a display device; one or more hardware processors; and one or more computer-readable storage devices storing processor-executable instructions that are executable by the one or more hardware processors to implement a storytelling module configured to: present a visual experience capable of telling a story, the story including an authored series of events and visual context, the authored series of events representing a storyline of the story, the visual context providing context for the storyline, the visual experience including story views and context views, the story views each having at least a portion of a respective event of the authored series of events, the context views each including at least a portion of the visual context for the storyline; display a portion of the visual experience on the display device based on a display view that is initially mapped to the portion of the visual experience; cause the display view to move across the visual experience and map to different portions of the visual experience based on a user input; determine whether the display view corresponds to a story view or a context view based on an amount of the respective event visually included within the display view; and perform one or more operations associated with a progression through the authored series of events based on the determination. 6. The mobile media consumption device as recited in claim 1 , wherein: the storytelling module is further configured to cease to progress through the authored series of events based on a determination that the display view corresponds to the context view; the progress is ceased by repeating the respective event, a set of events of which the respective event is a part, or a portion of the respective event in a loop; and the loop enables a transition from a context view to a story view to seamlessly present the story.

32. The system of claim 26 in which each vector in the set of vectors represents a corresponding user in a community, and each feature of each vector represents a preference of the corresponding user towards an object in a set of objects.

32. The system of claim 26 in which each vector in the set of vectors represents a corresponding user in a community, and each feature of each vector represents a preference of the corresponding user towards an object in a set of objects. 33. The system of claim 32 , further comprising a results tool that recommends an object to a user corresponding to the vector x based on the vector y.

9. The method of claim 1, further comprising the steps of: identifying within the selected word subgraph a third node representing a third occurrence of the second word, the third node having a word sense characterization; and determining to attribute to the first node the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a characteristic of the second occurrence of the second word.

9. The method of claim 1, further comprising the steps of: identifying within the selected word subgraph a third node representing a third occurrence of the second word, the third node having a word sense characterization; and determining to attribute to the first node the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a characteristic of the second occurrence of the second word. 11. The method of claim 9 wherein the determining step determines to attribute to the first occurrence of the second word the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a determination that the second occurrence of the second word is more closely related to the first word than is the third occurrence of the second word.

1. A semantic tagging method that outputs semantically linked tags for text content comprising: inputting the text content to a computer; by the computer, extracting nouns and noun phrases from the text content; by the computer, mapping the extracted nouns and noun phrases to terms of an ontology; by the computer, mapping the extracted nouns and noun phrases to a correct sense of the ontology terms using lexical chaining Word Sense Disambiguation (WSD) algorithms; by the computer, weighting the extracted nouns' and noun phrases' concepts from their ontological and statistical features; by the computer, extracting key-phrases from the weighted concepts; and by the computer, outputting the key-phrases as semantic tags; wherein mapping the extracted nouns and noun phrases to terms of an ontology further comprises: accessing the ontology; comparing the nouns and noun phrases with the ontology terms; and if there is an exact match, retrieving the ontology term, and if there is not an exact match, performing phrase mapping using a rule based algorithm; and wherein the phrase mapping rule based algorithm further comprises: generating two sub phrases by removing the first and last word from the noun phrases and replacing the original noun phrases with the two sub phrases; and repeating the phrase mapping until there is a match or there are no more noun phrases remaining.

1. A semantic tagging method that outputs semantically linked tags for text content comprising: inputting the text content to a computer; by the computer, extracting nouns and noun phrases from the text content; by the computer, mapping the extracted nouns and noun phrases to terms of an ontology; by the computer, mapping the extracted nouns and noun phrases to a correct sense of the ontology terms using lexical chaining Word Sense Disambiguation (WSD) algorithms; by the computer, weighting the extracted nouns' and noun phrases' concepts from their ontological and statistical features; by the computer, extracting key-phrases from the weighted concepts; and by the computer, outputting the key-phrases as semantic tags; wherein mapping the extracted nouns and noun phrases to terms of an ontology further comprises: accessing the ontology; comparing the nouns and noun phrases with the ontology terms; and if there is an exact match, retrieving the ontology term, and if there is not an exact match, performing phrase mapping using a rule based algorithm; and wherein the phrase mapping rule based algorithm further comprises: generating two sub phrases by removing the first and last word from the noun phrases and replacing the original noun phrases with the two sub phrases; and repeating the phrase mapping until there is a match or there are no more noun phrases remaining. 4. The method according to claim 1 wherein extracting nouns and noun phrases from the text content further comprises using a Natural Language Processing (NLP) Application Programming Interface (API).

14. A computing device comprising: one or more processing units; one or more computer-readable media comprising computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: identify a venue entity based upon user information associated with a user of a searching device; mine user defined data of a social network to generate a user defined suggestion associated with the venue entity, the mining comprising: extracting a set of candidate user suggestions, corresponding to the venue entity, from the social network; generating a candidate graph comprising one or more nodes connected by one more edges based upon the set of candidate user suggestions such that a first node, representing a first candidate user suggestion, is connected to a second node, representing a second candidate user suggestion, by a first edge based upon the first candidate user suggestion corresponding to the second candidate user suggestion above a correspondence threshold; generating one or more suggestion category clusters based upon the candidate graph, a first suggestion category duster comprising one or more nodes connected by at least one edge; and generating the user defined suggestion as a descriptive summary of candidate user suggestions represented by the evaluated nodes within the first suggestion category cluster; and provide the user defined suggestion to the searching device.

14. A computing device comprising: one or more processing units; one or more computer-readable media comprising computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: identify a venue entity based upon user information associated with a user of a searching device; mine user defined data of a social network to generate a user defined suggestion associated with the venue entity, the mining comprising: extracting a set of candidate user suggestions, corresponding to the venue entity, from the social network; generating a candidate graph comprising one or more nodes connected by one more edges based upon the set of candidate user suggestions such that a first node, representing a first candidate user suggestion, is connected to a second node, representing a second candidate user suggestion, by a first edge based upon the first candidate user suggestion corresponding to the second candidate user suggestion above a correspondence threshold; generating one or more suggestion category clusters based upon the candidate graph, a first suggestion category duster comprising one or more nodes connected by at least one edge; and generating the user defined suggestion as a descriptive summary of candidate user suggestions represented by the evaluated nodes within the first suggestion category cluster; and provide the user defined suggestion to the searching device. 17. The computing device of claim 14 , wherein the one or more computer-readable media comprise further computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to further: identify an image corresponding to the user defined suggestion; and provide the image together with the user defined suggestion.

1. A method of visualization of a set of objects in a computer graphic interface, comprising: defining a hierarchy of objects, the hierarchy of objects having hierarchal relationships between a plurality of objects each having associated content, a hierarchal organization of the hierarchy of objects being related to a respective content of an object and being included within the hierarchy based on satisfaction of a set of inclusion criteria; and supplementing the hierarchy with at least one additional object which does not satisfy the set of inclusion criteria, the at least one additional object being selectively placed within the hierarchy of objects based on an associated content of objects within the hierarchy of objects near the placement position of the at least the additional object and an associated content of the respective additional object.

1. A method of visualization of a set of objects in a computer graphic interface, comprising: defining a hierarchy of objects, the hierarchy of objects having hierarchal relationships between a plurality of objects each having associated content, a hierarchal organization of the hierarchy of objects being related to a respective content of an object and being included within the hierarchy based on satisfaction of a set of inclusion criteria; and supplementing the hierarchy with at least one additional object which does not satisfy the set of inclusion criteria, the at least one additional object being selectively placed within the hierarchy of objects based on an associated content of objects within the hierarchy of objects near the placement position of the at least the additional object and an associated content of the respective additional object. 18. The method according to claim 1 , wherein a subset of the set of objects of the hierarchy are presented to a user.

3. A data processing system comprising: a processor which executes a database management system (DMS) software; a memory system which stores a database system and the DMS software; a utility which when executed on said processor provides functions of: creating a number of materialized query tables (MQTs) within the database system; defining one or more database table specifications; receiving an incoming query at the database system; in response to the incoming query referencing a first subset of a set of tables, identifying an MQT with a definition query that references the set of tables, wherein said first subset includes one of: (a) a number of fact tables and a group of dimension tables; (b) a number of source tables and a group of dependent tables; and (c) a number of referencing tables and a group of referenced tables; determining when the MQT is a candidate match for the incoming query; identifying one or more candidate MQTs; selecting an optimal MQT from among the one or more candidate MQTs; when the MQT is identified as a candidate match for the incoming query, determining whether the MQT is a best match from among a number of candidate matches for the incoming query; and when the MQT is identified as the best match for the incoming query, rewriting the incoming query utilizing the MQT.

3. A data processing system comprising: a processor which executes a database management system (DMS) software; a memory system which stores a database system and the DMS software; a utility which when executed on said processor provides functions of: creating a number of materialized query tables (MQTs) within the database system; defining one or more database table specifications; receiving an incoming query at the database system; in response to the incoming query referencing a first subset of a set of tables, identifying an MQT with a definition query that references the set of tables, wherein said first subset includes one of: (a) a number of fact tables and a group of dimension tables; (b) a number of source tables and a group of dependent tables; and (c) a number of referencing tables and a group of referenced tables; determining when the MQT is a candidate match for the incoming query; identifying one or more candidate MQTs; selecting an optimal MQT from among the one or more candidate MQTs; when the MQT is identified as a candidate match for the incoming query, determining whether the MQT is a best match from among a number of candidate matches for the incoming query; and when the MQT is identified as the best match for the incoming query, rewriting the incoming query utilizing the MQT. 10. The data processing system of claim 3 , wherein said determining function further comprises the functions of: identifying a second subset of tables which are referenced by the definition query of the MQT and which second subset of tables are not referenced by the incoming query, wherein said second subset includes one of: (a) a group of dimension tables; and (b) a group of source tables; determining when a join of the one or more fact tables of the first subset and one or more dimension tables of the second subset has an equal number of rows compared with the number of rows of the one or more fact tables of the first subset; dismissing the MQT as a candidate match for the incoming query when one of: (a) a data cardinality is not maintained, such that a join of the number of fact tables of the first subset and the group of dimension tables of the second subset does not generate a resultant table that has an equal number of rows compared with a number of rows of the fact tables of the first subset and (b) a number of prerequisites are not satisfied, said prerequisites include one or more of the following qualifying conditions: (1) a physical referential integrity constraint for said join is defined; (2) an informational referential integrity constraint for said join is defined; (3) one or more physical not-null table check constraints are defined on nullable foreign key columns; and (4) one or more informational not-null table check constraints are defined on nullable foreign key columns.

14. A method for interfacing the management of layer one telecommunication resources in a carrier virtual network, wherein the management system of an accessing telecommunication network may indirectly manage layer one resources dedicated to the carrier virtual network by at least one dedicating telecommunication network having a dedicating telecommunication network management system, the method comprising: converting network information regarding layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network to messages having a predetermined format; transmitting messages having a predetermined format to the management system of an accessing telecommunication network, wherein the dedicated layer one resources of the dedicating-telecommunication network are freely accessible to the accessing telecommunication network such that the management system of the accessing telecommunication network can provision the dedicated layer one resources as if part of the accessing telecommunication network; converting messages transmitted to the management system of the accessing telecommunication network to a format useable by the accessing telecommunication network management system, the accessing telecommunication network management system: (1) maintaining information identifying the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network that is accessible by the accessing telecommunication network in a resource allocation record; (2) receiving a customer request to establish service; (3) referencing the resource allocation record to ascertain that the customer request can be satisfied by utilizing the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network that is accessible by the accessing telecommunication network, without engaging the network management system of the dedicating telecommunication network; issuing network instructions for the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network from the network management system of the accessing telecommunication network; converting the network instructions to messages having a predetermined format; transmitting messages having a predetermined format to the management system of a dedicating telecommunication network; converting the messages transmitted to the management system of the dedicating telecommunication network to network instructions to a format useable by the dedicating telecommunication network management system; and transmitting the network instructions to the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network to those layer one resources.

14. A method for interfacing the management of layer one telecommunication resources in a carrier virtual network, wherein the management system of an accessing telecommunication network may indirectly manage layer one resources dedicated to the carrier virtual network by at least one dedicating telecommunication network having a dedicating telecommunication network management system, the method comprising: converting network information regarding layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network to messages having a predetermined format; transmitting messages having a predetermined format to the management system of an accessing telecommunication network, wherein the dedicated layer one resources of the dedicating-telecommunication network are freely accessible to the accessing telecommunication network such that the management system of the accessing telecommunication network can provision the dedicated layer one resources as if part of the accessing telecommunication network; converting messages transmitted to the management system of the accessing telecommunication network to a format useable by the accessing telecommunication network management system, the accessing telecommunication network management system: (1) maintaining information identifying the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network that is accessible by the accessing telecommunication network in a resource allocation record; (2) receiving a customer request to establish service; (3) referencing the resource allocation record to ascertain that the customer request can be satisfied by utilizing the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network that is accessible by the accessing telecommunication network, without engaging the network management system of the dedicating telecommunication network; issuing network instructions for the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network from the network management system of the accessing telecommunication network; converting the network instructions to messages having a predetermined format; transmitting messages having a predetermined format to the management system of a dedicating telecommunication network; converting the messages transmitted to the management system of the dedicating telecommunication network to network instructions to a format useable by the dedicating telecommunication network management system; and transmitting the network instructions to the layer one resources of the dedicating telecommunication network dedicated to the carrier virtual network to those layer one resources. 19. The method for interfacing the management of layer one telecommunication resources of claim 14 , wherein the predetermined format of messages is ASCII text.

1. A computer-implemented method, comprising: receiving input files comprising markup language text for a graphical user interface; obtaining an application framework code; receiving web application business logic objects; organizing the application framework code and the web application business logic objects into web application source code; and binding the web application source code with the input files, the binding including compiling the input files; wherein the application framework code is configured to, at runtime, detect any change to web application screens and to re-compile the input files in response to detecting the any change.

1. A computer-implemented method, comprising: receiving input files comprising markup language text for a graphical user interface; obtaining an application framework code; receiving web application business logic objects; organizing the application framework code and the web application business logic objects into web application source code; and binding the web application source code with the input files, the binding including compiling the input files; wherein the application framework code is configured to, at runtime, detect any change to web application screens and to re-compile the input files in response to detecting the any change. 8. The computer-implemented method of claim 1 , further comprising generating an event handler code, the generating comprising: parsing the markup language text; identifying an input tag in the markup language text; identifying, in the markup language text, an attribute within the identified input tag; identifying, in the markup language text, a value corresponding to the identified attribute; and using the identified input tag, the identified attribute, and the identified value to identify a rule; and using the identified rule, the identified input tag, the identified attribute, and the identified value to create the event handler code.

9. A multi-user searchable encryption method, the method comprising: generating, at a key generation server, system parameters, a primary key, and a secondary key; receiving, at a user terminal, the primary key; encrypting, at the user terminal, data to obtain cypher text, symmetric key to obtain encrypted symmetric key, keyword to obtain encrypted keyword; generating, at the user terminal, trapdoor using the primary key for a search keyword inputted by user, and a decryption parameter using the primary key; receiving, at a proxy server, the cypher text, the encrypted keyword, the encrypted symmetric key, and the secondary key; encrypting, at the proxy server, trapdoor using the secondary key; performing, at the proxy server, a lookup for search results corresponding to the search keyword; and storing, at a database server, the cypher text at a location address and returning the location address of the cypher text to the proxy server; wherein the method further comprises at least one selected from the group consisting of (a), (b), and (c): (a) re-encrypting, at the proxy server, the encrypted symmetric key and encrypted keyword using the secondary key; (b) maintaining, at the proxy server, a table of re-encrypted symmetric keys and a table to store location address of data; and (c) receiving, at the user terminal, a decryption attribute and the cypher text.

9. A multi-user searchable encryption method, the method comprising: generating, at a key generation server, system parameters, a primary key, and a secondary key; receiving, at a user terminal, the primary key; encrypting, at the user terminal, data to obtain cypher text, symmetric key to obtain encrypted symmetric key, keyword to obtain encrypted keyword; generating, at the user terminal, trapdoor using the primary key for a search keyword inputted by user, and a decryption parameter using the primary key; receiving, at a proxy server, the cypher text, the encrypted keyword, the encrypted symmetric key, and the secondary key; encrypting, at the proxy server, trapdoor using the secondary key; performing, at the proxy server, a lookup for search results corresponding to the search keyword; and storing, at a database server, the cypher text at a location address and returning the location address of the cypher text to the proxy server; wherein the method further comprises at least one selected from the group consisting of (a), (b), and (c): (a) re-encrypting, at the proxy server, the encrypted symmetric key and encrypted keyword using the secondary key; (b) maintaining, at the proxy server, a table of re-encrypted symmetric keys and a table to store location address of data; and (c) receiving, at the user terminal, a decryption attribute and the cypher text. 17. The method of claim 9 , further comprising generating, at the user terminal, decryption keys using a decryption attribute, the primary key, and the decryption parameter.

19. A title extracting apparatus for recognizing and extracting a required partial region from a document image of a document that has been converted into image data, comprising: character region generating means for generating character regions, including black pixel connected regions composed of connected black pixels of the document image; character string region generating means for unifying one or more character regions generated by said character region generating means, and for generating character string regions including one or more character regions; and title extracting means for extracting a particular character string region of the character string regions, according to attributes of a plurality of character string regions generated by said character string region generating means, as a title region, wherein said title extracting means is adapted for extracting an underline attribute or a frame attribute as an attribute of the character string regions, assigning a number of points to each of the character string regions corresponding to the extracted underline attribute or frame attribute, a position of each character string regions, and a relative position relation between the character string regions, and treating a character string region having the greatest number of assigned points as the particular character string region.

19. A title extracting apparatus for recognizing and extracting a required partial region from a document image of a document that has been converted into image data, comprising: character region generating means for generating character regions, including black pixel connected regions composed of connected black pixels of the document image; character string region generating means for unifying one or more character regions generated by said character region generating means, and for generating character string regions including one or more character regions; and title extracting means for extracting a particular character string region of the character string regions, according to attributes of a plurality of character string regions generated by said character string region generating means, as a title region, wherein said title extracting means is adapted for extracting an underline attribute or a frame attribute as an attribute of the character string regions, assigning a number of points to each of the character string regions corresponding to the extracted underline attribute or frame attribute, a position of each character string regions, and a relative position relation between the character string regions, and treating a character string region having the greatest number of assigned points as the particular character string region. 22. The title extracting apparatus as set forth in claim 19, wherein said title extracting means is adapted for assigning predetermined points to a character string region that is disposed between and spaced apart from an upper and a lower character string region.

10. An electronic whiteboard, comprising: a memory; a touch screen interface configured to receive as first input a tag class configuration instruction identifying a metadata tag class, display a tag configuration list for the metadata tag class, receive as second input a plurality of metadata tags and associated metadata tag priorities for inclusion in the metadata tag class, wherein the metadata tags and the associated metadata tag priorities are received as handwritten characters in empty metadata tag cells and counterpart empty metadata tag priority cells within the tag configuration list, receive as third input an object tagging instruction identifying an object to be tagged with metadata, display as output a hierarchical selection menu including the metadata tag class as a selectable option on a first level and the metadata tags as selectable options on a second level, wherein the metadata tags are ordered on the second level in accordance with the metadata tag priorities, and receive as fourth input a selection from the hierarchical selection menu of one of the metadata tags, whereby the identified object is tagged with the metadata; and a processor communicatively coupled with memory and the touch screen interface configured to associate in the memory the metadata tag class with the metadata tags and the associated metadata tag priorities and generate the hierarchical selection menu using the associated metadata tag class, metadata tags and metadata tag priorities.

10. An electronic whiteboard, comprising: a memory; a touch screen interface configured to receive as first input a tag class configuration instruction identifying a metadata tag class, display a tag configuration list for the metadata tag class, receive as second input a plurality of metadata tags and associated metadata tag priorities for inclusion in the metadata tag class, wherein the metadata tags and the associated metadata tag priorities are received as handwritten characters in empty metadata tag cells and counterpart empty metadata tag priority cells within the tag configuration list, receive as third input an object tagging instruction identifying an object to be tagged with metadata, display as output a hierarchical selection menu including the metadata tag class as a selectable option on a first level and the metadata tags as selectable options on a second level, wherein the metadata tags are ordered on the second level in accordance with the metadata tag priorities, and receive as fourth input a selection from the hierarchical selection menu of one of the metadata tags, whereby the identified object is tagged with the metadata; and a processor communicatively coupled with memory and the touch screen interface configured to associate in the memory the metadata tag class with the metadata tags and the associated metadata tag priorities and generate the hierarchical selection menu using the associated metadata tag class, metadata tags and metadata tag priorities. 12. The electronic whiteboard of claim 10 , wherein the metadata tags are received as handwritten words and the metadata tag priorities are received as handwritten numbers.

3. The method of claim 1 further comprising: processing at least one of said text documents to identify a document object model and selecting at least one member of said training set using said document object model, said document object model defining a set of nodes based on objects within said text document.

3. The method of claim 1 further comprising: processing at least one of said text documents to identify a document object model and selecting at least one member of said training set using said document object model, said document object model defining a set of nodes based on objects within said text document. 6. The method of claim 3 further comprising: identifying a text object that is less than a predefined number of nodes from said image.

13. One or more computer-readable non-transitory media storing computer-executable instructions that, when executed by one or more computer systems, configure the one or more computer systems to perform operations comprising: defining a query operator based at least in part upon an interaction with a user, the interaction with the user comprising at least one of ordering a first item offered by one or more item providers, scrolling through search results of items offered by the one or more item providers, or providing feedback about the items offered by the one or more item providers; receiving, from the user, a search query for a second item, the search query including a query syntax that comprises the query operator; determining a definition by a quantitative measurement of the interaction of the user with the computer system, the definition for assisting the user in adjusting the search query by indicating instructions for translating the received query syntax into an enhanced query syntax usable by the one or more computer systems; generating a comment comprising the definition; determining a search term in the search query from the user that corresponds with the enhanced query syntax; causing the comment to be displayed with the definition; receiving an adjusted search query from the user based at least in part on the comment and the definition; obtaining updated search results for the second item based at least in part upon the adjusted search query and absent of a transformation by the computer system of the adjusted search query to obtain the updated search results, the updated search results configured to be aggregated, filtered, or ordered based at least in part on the enhanced query syntax, and the updated search results excluding at least a subset of the search results; and providing the updated search results.

13. One or more computer-readable non-transitory media storing computer-executable instructions that, when executed by one or more computer systems, configure the one or more computer systems to perform operations comprising: defining a query operator based at least in part upon an interaction with a user, the interaction with the user comprising at least one of ordering a first item offered by one or more item providers, scrolling through search results of items offered by the one or more item providers, or providing feedback about the items offered by the one or more item providers; receiving, from the user, a search query for a second item, the search query including a query syntax that comprises the query operator; determining a definition by a quantitative measurement of the interaction of the user with the computer system, the definition for assisting the user in adjusting the search query by indicating instructions for translating the received query syntax into an enhanced query syntax usable by the one or more computer systems; generating a comment comprising the definition; determining a search term in the search query from the user that corresponds with the enhanced query syntax; causing the comment to be displayed with the definition; receiving an adjusted search query from the user based at least in part on the comment and the definition; obtaining updated search results for the second item based at least in part upon the adjusted search query and absent of a transformation by the computer system of the adjusted search query to obtain the updated search results, the updated search results configured to be aggregated, filtered, or ordered based at least in part on the enhanced query syntax, and the updated search results excluding at least a subset of the search results; and providing the updated search results. 15. The one or more computer-readable non-transitory media of claim 13 , wherein the search query comprises a first term, a second term, and the query operator, wherein the search results comprises first search results associated with the first term and second search results associated with the second term, and wherein the updated search results are filtered from the first search results based on an operation associated with the query operator.

1. A computer-implemented method comprising: causing, by a server system via a network, a web browser to display (a) at least first and second content areas separately from each other on a webpage, and (b) at least a first content item at a location on the webpage other than in the first and the second content areas; receiving from the web browser, by the server system via the network, an indication of dragging, by a user of the web browser, of an element displayed on the webpage, and dropping, by the user, of the element into one of the first and the second content areas, the element selected from the group consisting of: the first content item, and a graphical element displayed in association with the first content item; if the indication is of dropping the element into the first content area, causing, by the server system, the web browser to display, in the first content area, at least a portion of a set of one or more second content items related to the first content item; and if the indication is of dropping the element into the second content area, causing, by the server system, the web browser to display, in the second content area, at least a portion of a set of one or more third content items related to the first content item.

1. A computer-implemented method comprising: causing, by a server system via a network, a web browser to display (a) at least first and second content areas separately from each other on a webpage, and (b) at least a first content item at a location on the webpage other than in the first and the second content areas; receiving from the web browser, by the server system via the network, an indication of dragging, by a user of the web browser, of an element displayed on the webpage, and dropping, by the user, of the element into one of the first and the second content areas, the element selected from the group consisting of: the first content item, and a graphical element displayed in association with the first content item; if the indication is of dropping the element into the first content area, causing, by the server system, the web browser to display, in the first content area, at least a portion of a set of one or more second content items related to the first content item; and if the indication is of dropping the element into the second content area, causing, by the server system, the web browser to display, in the second content area, at least a portion of a set of one or more third content items related to the first content item. 9. The method according to claim 1 , wherein the method further comprises, before receiving the indication of dragging and dropping, causing, by the server system, the web browser to display, in the first and the second content areas, respective content items requested from respective one or more online content sources.

23. One or more non-transitory volatile or non-volatile machine-readable storage media storing instructions which, when executed by one or more processors, cause: storing bonds that reflect relationships between searchable items; wherein the searchable items include a plurality of documents; wherein the bonds are not stored as part of the searchable items; wherein the bonds do not reflect storage location relationships between said searchable items; receiving a search request to perform a search for searchable items that are associated with a keyword, wherein the search request specifies the keyword; determining that a particular searchable item is to be the starting point of the search; responding to said search request by performing the search relative to the particular searchable item that is to be used as a starting point for said search, wherein performing the search includes at least one of: (a) ranking documents that match said search based, at least in part, on the minimum number of bonds that have to be traversed from the particular searchable item to arrive at each document, wherein the documents that match said search include a first document and a second document, wherein the minimum number of bonds that have to be traversed from said particular searchable item to arrive at said first document is different than the minimum number of bonds that have to be traversed from said particular searchable to arrive at said second document; (b) searching against documents that are within one bond of said particular searchable item; and if the number of documents, within one bond of said particular searchable item, that match the search is less than a target number, then expanding the search to documents that are within two bonds of said particular searchable item; and repeatedly expanding the search to documents that are one further bond away from the particular searchable item until at least the target number of documents that match the search have been identified; or (c) sequentially performing a series of searches relative to said particular searchable item until a predetermined maximum number of bonds from said particular searchable item has been reached, wherein the series of searches includes a first search and one or more subsequent searches, wherein each search of said one or more subsequent searches is performed against documents that are at a greater minimum number of bonds that have to be traversed from said particular searchable item than the documents that were searched in any search that preceded said search in said series.

23. One or more non-transitory volatile or non-volatile machine-readable storage media storing instructions which, when executed by one or more processors, cause: storing bonds that reflect relationships between searchable items; wherein the searchable items include a plurality of documents; wherein the bonds are not stored as part of the searchable items; wherein the bonds do not reflect storage location relationships between said searchable items; receiving a search request to perform a search for searchable items that are associated with a keyword, wherein the search request specifies the keyword; determining that a particular searchable item is to be the starting point of the search; responding to said search request by performing the search relative to the particular searchable item that is to be used as a starting point for said search, wherein performing the search includes at least one of: (a) ranking documents that match said search based, at least in part, on the minimum number of bonds that have to be traversed from the particular searchable item to arrive at each document, wherein the documents that match said search include a first document and a second document, wherein the minimum number of bonds that have to be traversed from said particular searchable item to arrive at said first document is different than the minimum number of bonds that have to be traversed from said particular searchable to arrive at said second document; (b) searching against documents that are within one bond of said particular searchable item; and if the number of documents, within one bond of said particular searchable item, that match the search is less than a target number, then expanding the search to documents that are within two bonds of said particular searchable item; and repeatedly expanding the search to documents that are one further bond away from the particular searchable item until at least the target number of documents that match the search have been identified; or (c) sequentially performing a series of searches relative to said particular searchable item until a predetermined maximum number of bonds from said particular searchable item has been reached, wherein the series of searches includes a first search and one or more subsequent searches, wherein each search of said one or more subsequent searches is performed against documents that are at a greater minimum number of bonds that have to be traversed from said particular searchable item than the documents that were searched in any search that preceded said search in said series. 32. The one or more non-transitory volatile or non-volatile machine-readable storage media of claim 23 , wherein storing bonds includes storing at least one bond that represents a relationship that is independent of where said searchable items involved in the relationship are stored.

8. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, causes the processors to perform operations, the operations comprising: transmitting, to a remote server, a verbal input; receiving, from the remote server, a digital message that comprises a symbolic representation of the verbal input; determining, based on the symbolic representation of the verbal input, an application identifier for an application that is indicated by the symbolic representation of the verbal input; launching, using the application identifier, the application that is indicated by the symbolic representation of the verbal input; transmitting, using the application and to an information provider, a query that was generated based on the symbolic representation of the verbal input; obtaining, from the information provider as a response to the query, an information result; and presenting, through an application interface, the information result.

8. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, causes the processors to perform operations, the operations comprising: transmitting, to a remote server, a verbal input; receiving, from the remote server, a digital message that comprises a symbolic representation of the verbal input; determining, based on the symbolic representation of the verbal input, an application identifier for an application that is indicated by the symbolic representation of the verbal input; launching, using the application identifier, the application that is indicated by the symbolic representation of the verbal input; transmitting, using the application and to an information provider, a query that was generated based on the symbolic representation of the verbal input; obtaining, from the information provider as a response to the query, an information result; and presenting, through an application interface, the information result. 12. The system of claim 8 , wherein presenting the information result comprises audibly presenting the information result.

18. A non-transitory computer-readable storage medium comprising computer program code for providing a video-assisted customer experience, the computer program code comprising: instructions for providing a communications link between a customer and a business representative, the communications link being facilitated by an external apparatus comprising a display, wherein the communications link comprises video such that the customer may view the business representative or a representation of the business representative on the display; instructions for utilizing speech-recognition to provide subtitles of the words spoken by the business representative viewable to the customer instructions for detecting key words spoken by the business representative, wherein the key words include a product or service provided by the business of the business representative; instructions for highlighting the detected key words spoken by the business representative, wherein highlighting further comprises integrating a selectable link to a website of the business that includes information and ordering for the product or service of the key words, wherein the product or service of the key words are financial products or services; and instructions for enabling the customer to select via the selectable link the detected key words, wherein the selection directs the user to the website of the business that includes information and ordering for the financial product or service of the key words.

18. A non-transitory computer-readable storage medium comprising computer program code for providing a video-assisted customer experience, the computer program code comprising: instructions for providing a communications link between a customer and a business representative, the communications link being facilitated by an external apparatus comprising a display, wherein the communications link comprises video such that the customer may view the business representative or a representation of the business representative on the display; instructions for utilizing speech-recognition to provide subtitles of the words spoken by the business representative viewable to the customer instructions for detecting key words spoken by the business representative, wherein the key words include a product or service provided by the business of the business representative; instructions for highlighting the detected key words spoken by the business representative, wherein highlighting further comprises integrating a selectable link to a website of the business that includes information and ordering for the product or service of the key words, wherein the product or service of the key words are financial products or services; and instructions for enabling the customer to select via the selectable link the detected key words, wherein the selection directs the user to the website of the business that includes information and ordering for the financial product or service of the key words. 25. The non-transitory computer-readable storage medium of claim 18 , wherein the speech-recognition is configured to detect key words or phrases spoken and present the detected key words as interactive words in the subtitles.

14. A system comprising one or more computers configured to perform operations comprising: receiving a query; receiving a plurality of search results responsive to the query, each search result identifying a resource responsive to the query; after receiving the plurality of search results responsive to the query, accessing an index of resources to determine, for a plurality of the identified resources, that each identified resource is associated with a respective answer box topic; determining a set of answer box topics from the respective answer box topics; analyzing each answer box topic of the set of answer box topics to identify a first answer box topic that is responsive to the query, the first answer box topic associated with a first search result of the plurality of search results; identifying a first publisher of a first resource identified by the first search result; obtaining an answer box precursor for the first answer box topic using a mapping between a plurality of answer box topics and a plurality of answer box precursors, wherein the mapping includes mapping information provided by the first publisher of the first resource; and providing the search results along with the answer box precursor for the first answer box topic, wherein the answer box precursor includes information that defines an answer box.

14. A system comprising one or more computers configured to perform operations comprising: receiving a query; receiving a plurality of search results responsive to the query, each search result identifying a resource responsive to the query; after receiving the plurality of search results responsive to the query, accessing an index of resources to determine, for a plurality of the identified resources, that each identified resource is associated with a respective answer box topic; determining a set of answer box topics from the respective answer box topics; analyzing each answer box topic of the set of answer box topics to identify a first answer box topic that is responsive to the query, the first answer box topic associated with a first search result of the plurality of search results; identifying a first publisher of a first resource identified by the first search result; obtaining an answer box precursor for the first answer box topic using a mapping between a plurality of answer box topics and a plurality of answer box precursors, wherein the mapping includes mapping information provided by the first publisher of the first resource; and providing the search results along with the answer box precursor for the first answer box topic, wherein the answer box precursor includes information that defines an answer box. 17. The system of claim 14 , the operations further comprising: identifying, by the system of one or more computers, a second answer box topic that is associated with a second search result, and wherein providing the search results along with an answer box precursor for the first answer box topic comprises selecting, by the system of one or more computers, the first answer box topic as a consequence of the first search result having a higher ranking position relative to the second search result in the plurality of search results.

5. The pen type multimedia device of claim 1 , wherein, when the handwriting comprises a geometric shape corresponding to a storage folder selection input and the text, the controller is further configured to store the image to a folder corresponding to the text.

5. The pen type multimedia device of claim 1 , wherein, when the handwriting comprises a geometric shape corresponding to a storage folder selection input and the text, the controller is further configured to store the image to a folder corresponding to the text. 6. The pen type multimedia device of claim 5 , wherein, when the folder corresponding to the text does not exist, the controller is further configured to create a folder having a name of the text, and store the image in the newly created folder.

16. A system, comprising: a memory; a processor; an extraction engine to extract a set of candidate phrases from a content stream, wherein the candidate phrases have at least two words; and an analysis engine to organize the extracted candidate phrases from the content stream based on at least one metric, assign a visual cue based on the least one metric using an average sentiment value to determine at least one property of the visual cue, and display the candidate phrases in statistical groups including the visual cues to an operator; wherein the extraction and analysis engines are implemented as a processor executing software.

16. A system, comprising: a memory; a processor; an extraction engine to extract a set of candidate phrases from a content stream, wherein the candidate phrases have at least two words; and an analysis engine to organize the extracted candidate phrases from the content stream based on at least one metric, assign a visual cue based on the least one metric using an average sentiment value to determine at least one property of the visual cue, and display the candidate phrases in statistical groups including the visual cues to an operator; wherein the extraction and analysis engines are implemented as a processor executing software. 17. The system of claim 16 , wherein the analysis engine calculates the importance of the candidate phrases by co-occurrence as a first metric, and calculates the sentiment of the candidate phrases by term-association as the second metric.

1. A method of generating a dynamic document, the method comprising: providing a web-based visual editor structured to facilitate generation of a markup language version of the dynamic document, the markup language version of the dynamic document including first data indicative of a dynamic field; converting the markup language version of the dynamic document to a stylesheet version of the dynamic document, the stylesheet version of the dynamic document including second data indicative of the dynamic field; deploying the stylesheet version of the dynamic document via a network at an application server, wherein when the stylesheet version of the dynamic document is executed by a first user, a first instance of the dynamic document is generated using data associated with the first user as a first output document, and when the stylesheet version of the dynamic document is executed by a second different user, a second different instance of the dynamic document is generated using data associated with the second user as a second output document; transmitting the first output document to a first client device of the first user from the application server; and transmitting the second output document to a second client device of the second user from the application server, wherein the markup language version of the dynamic document is displayed as an XHTML page within a web browser at a designer terminal that provides the web-based visual editor, the stylesheet version of the dynamic document is an XSL:FO file stored at the application server, and the first and second output documents are at least one of PDF and RTF files stored locally at the first and second client devices, the client devices being located remotely from the application server.

1. A method of generating a dynamic document, the method comprising: providing a web-based visual editor structured to facilitate generation of a markup language version of the dynamic document, the markup language version of the dynamic document including first data indicative of a dynamic field; converting the markup language version of the dynamic document to a stylesheet version of the dynamic document, the stylesheet version of the dynamic document including second data indicative of the dynamic field; deploying the stylesheet version of the dynamic document via a network at an application server, wherein when the stylesheet version of the dynamic document is executed by a first user, a first instance of the dynamic document is generated using data associated with the first user as a first output document, and when the stylesheet version of the dynamic document is executed by a second different user, a second different instance of the dynamic document is generated using data associated with the second user as a second output document; transmitting the first output document to a first client device of the first user from the application server; and transmitting the second output document to a second client device of the second user from the application server, wherein the markup language version of the dynamic document is displayed as an XHTML page within a web browser at a designer terminal that provides the web-based visual editor, the stylesheet version of the dynamic document is an XSL:FO file stored at the application server, and the first and second output documents are at least one of PDF and RTF files stored locally at the first and second client devices, the client devices being located remotely from the application server. 11. The method of claim 1 , wherein the data associated with the first user includes data entered by the first user.

1. A computer-implemented method for tagging place names with geographic location coordinates, the method comprising: at a server system having one or more processors and memory storing programs executed by the one or more processors to perform the method: retrieving a first fact from a fact repository, the first fact having an attribute and a value, wherein the first fact is associated with a first object, the fact repository includes a plurality of objects and a plurality of facts associated with the plurality of objects, a respective fact in the fact repository includes a respective attribute and a respective value, the respective attribute is a text string, and the attribute of the first fact and plurality of values are extracted from free text in a plurality of web documents; determining that the attribute of the first fact indicates that the value of the first fact is a potential place name; and in response to the determining: identifying a first potential place name corresponding to the value of the first fact; determining geographic location coordinates for the first potential place name, including examining frequency with which the geographic location coordinates are associated with variations of the first potential place name; and storing the determined geographic location coordinates in the fact repository, the storing including associating the determined geographic location coordinates with the first fact.

1. A computer-implemented method for tagging place names with geographic location coordinates, the method comprising: at a server system having one or more processors and memory storing programs executed by the one or more processors to perform the method: retrieving a first fact from a fact repository, the first fact having an attribute and a value, wherein the first fact is associated with a first object, the fact repository includes a plurality of objects and a plurality of facts associated with the plurality of objects, a respective fact in the fact repository includes a respective attribute and a respective value, the respective attribute is a text string, and the attribute of the first fact and plurality of values are extracted from free text in a plurality of web documents; determining that the attribute of the first fact indicates that the value of the first fact is a potential place name; and in response to the determining: identifying a first potential place name corresponding to the value of the first fact; determining geographic location coordinates for the first potential place name, including examining frequency with which the geographic location coordinates are associated with variations of the first potential place name; and storing the determined geographic location coordinates in the fact repository, the storing including associating the determined geographic location coordinates with the first fact. 6. The method of claim 1 , wherein the identifying a first potential place name comprises comparing the first potential place name with an object name associated with an identified place name in the fact repository.

19. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: generating a supplement to an article of content, the supplement including two or more sections, each section of the two or more sections corresponding to a different entity of a plurality of entities; selecting the plurality of entities based at least in part upon the content, wherein selecting the plurality of entities comprises: selecting a first entity of the plurality of entities by extracting the entity from the article of content; and based on extracted-from-article entities extracted from the content of the article, selecting a second entity from a set of related entities not found in the content of the article, that are related to constituent entities extracted from the content of the article; wherein the supplement comprises a plurality of tabs, each of the tabs configured to swap into view a different section, of the two or more sections, that corresponds to the tab, each of the tabs comprising a label identifying the different entity that corresponds to the different section; wherein each particular section of the two or more sections displays multiple search results obtained from one or more searches for a particular entity, of the plurality of entities, that corresponds to the particular section.

19. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: generating a supplement to an article of content, the supplement including two or more sections, each section of the two or more sections corresponding to a different entity of a plurality of entities; selecting the plurality of entities based at least in part upon the content, wherein selecting the plurality of entities comprises: selecting a first entity of the plurality of entities by extracting the entity from the article of content; and based on extracted-from-article entities extracted from the content of the article, selecting a second entity from a set of related entities not found in the content of the article, that are related to constituent entities extracted from the content of the article; wherein the supplement comprises a plurality of tabs, each of the tabs configured to swap into view a different section, of the two or more sections, that corresponds to the tab, each of the tabs comprising a label identifying the different entity that corresponds to the different section; wherein each particular section of the two or more sections displays multiple search results obtained from one or more searches for a particular entity, of the plurality of entities, that corresponds to the particular section. 20. The non-transitory computer-readable media of claim 19 , wherein the second entity of the set of related entities is selected based on a co-occurrence frequency of the first entity and the second entity in a corpus of articles.

1. A computer-implemented method, the method comprising: identifying, by a computing system, multiple authors that have submitted posts to a messaging system, the multiple authors including at least a first author, a second author, and a third author; determining, by the computing system, a score for the first author based on a quantity of interactions, by a first group of at least some of the multiple authors, with posts that the first author has submitted to the messaging system; determining, by the computing system, a score for the second author based on a quantity of interactions, by a second group of at least some of the multiple authors, with posts that the second author has submitted to the messaging system; determining, by the computing system, a score for the third author based on the score for the first author and the score for the second author, due to the first author and the second author having requested to subscribe to a stream of posts that the third author submits to the messaging system; receiving, at the messaging system and from a computing device, a particular post that the third author submitted to the messaging system; assigning a score to the particular post based on the score for the third author; transmitting the particular post for receipt by computing devices that are associated with authors who have requested to subscribe to the stream of posts that the third author submits to the messaging system; determining that the score for the particular post satisfies a criteria for transmission to a recipient author that has not requested to subscribe to the stream of posts that the third author submits to the messaging system; and providing the particular post for display to the recipient author.

1. A computer-implemented method, the method comprising: identifying, by a computing system, multiple authors that have submitted posts to a messaging system, the multiple authors including at least a first author, a second author, and a third author; determining, by the computing system, a score for the first author based on a quantity of interactions, by a first group of at least some of the multiple authors, with posts that the first author has submitted to the messaging system; determining, by the computing system, a score for the second author based on a quantity of interactions, by a second group of at least some of the multiple authors, with posts that the second author has submitted to the messaging system; determining, by the computing system, a score for the third author based on the score for the first author and the score for the second author, due to the first author and the second author having requested to subscribe to a stream of posts that the third author submits to the messaging system; receiving, at the messaging system and from a computing device, a particular post that the third author submitted to the messaging system; assigning a score to the particular post based on the score for the third author; transmitting the particular post for receipt by computing devices that are associated with authors who have requested to subscribe to the stream of posts that the third author submits to the messaging system; determining that the score for the particular post satisfies a criteria for transmission to a recipient author that has not requested to subscribe to the stream of posts that the third author submits to the messaging system; and providing the particular post for display to the recipient author. 11. The computer-implemented method of claim 1 , wherein determining the score for the first author is further based on the score for the third author, due to the third author having requested to subscribe to a stream of posts that the first author submits to the messaging system.

13. The non-transitory computer readable medium of claim 12 , wherein the operations further comprise: displaying in a second display area of the main window a list of one or more communities in which the selected tag has been published, wherein each of the one or more communities can be selectable or unselectable.

13. The non-transitory computer readable medium of claim 12 , wherein the operations further comprise: displaying in a second display area of the main window a list of one or more communities in which the selected tag has been published, wherein each of the one or more communities can be selectable or unselectable. 15. The non-transitory computer readable medium of claim 13 , wherein the operations further comprise displaying in a third display area of the main window a list of tags that are associated with at least one community displayed in the second display area.

5. The natural language processing system according to claim 1, which further comprises extraction means for extracting specific data from the natural language information inputted from said input means, on the basis of a result of an analysis made by said analysis means.

5. The natural language processing system according to claim 1, which further comprises extraction means for extracting specific data from the natural language information inputted from said input means, on the basis of a result of an analysis made by said analysis means. 6. The natural language processing system according to claim 5, wherein the information represents the contents of a document of a specific domain, wherein said knowledge base has knowledge of the specific domain, and wherein said extraction means refers to the knowledge of the specific domain stored in said knowledge base and extracts specific data.

11. A program product stored on a computer readable storage medium, which when executed, binds a portlet into a web portal infrastructure comprising at least a portal and a plurality of portlets, the computer readable storage medium comprising program code for: storing a portlet profile data structure, wherein the portlet profile data structure is associated with a portlet and is deployed at a portal server, and wherein the portlet profile data structure declares a portlet class and at least one portlet quality of service characteristic; storing a portlet binding policy data structure, which is associated with the portlet class and is deployed at a portal server, wherein the portlet binding policy data structure contains a set of predicates specifying the at least one portlet quality of service characteristic; processing of an incoming request for a portlet, comprising: determining the portlet class of the requested portlet; selecting all stored portlet profile data structures for the portlet class of the requested portlet; and selecting the portlet binding policy data structure associated with the requested portlet; performing a cross-checking of the set of predicates of the selected binding policy data structure against the portlet quality of service characteristics of the selected portlet profile data structures, wherein the cross-checking seeks optimal adherence to the selected binding policy data structure; selecting an optimal portlet out of the selected portlets in response to the cross-checking; and invoking the optimal portlet for rendering in response to the incoming request.

11. A program product stored on a computer readable storage medium, which when executed, binds a portlet into a web portal infrastructure comprising at least a portal and a plurality of portlets, the computer readable storage medium comprising program code for: storing a portlet profile data structure, wherein the portlet profile data structure is associated with a portlet and is deployed at a portal server, and wherein the portlet profile data structure declares a portlet class and at least one portlet quality of service characteristic; storing a portlet binding policy data structure, which is associated with the portlet class and is deployed at a portal server, wherein the portlet binding policy data structure contains a set of predicates specifying the at least one portlet quality of service characteristic; processing of an incoming request for a portlet, comprising: determining the portlet class of the requested portlet; selecting all stored portlet profile data structures for the portlet class of the requested portlet; and selecting the portlet binding policy data structure associated with the requested portlet; performing a cross-checking of the set of predicates of the selected binding policy data structure against the portlet quality of service characteristics of the selected portlet profile data structures, wherein the cross-checking seeks optimal adherence to the selected binding policy data structure; selecting an optimal portlet out of the selected portlets in response to the cross-checking; and invoking the optimal portlet for rendering in response to the incoming request. 12. The program product according to claim 11 , wherein the set of predicates specifies an acceptable range for the at least one portlet quality of service characteristic.

1. A computer-implemented method of defining a lexical database ontology comprising: accessing a lexical database comprising a plurality of concepts individually including a plurality of different words; accessing a corpus of documents; using a processor, identifying occurrences of the words in the documents of the corpus; using the processor, counting a plurality of frequency counts for the concepts, wherein the counting includes incrementing the frequency counts of the concepts using the identifying of the occurrences of the words of the respective concepts in the documents; using the processor, analyzing the frequency counts; using the processor, selecting a plurality of the concepts as event classes of a lexical database ontology using the analyzing, wherein the event classes of the lexical database ontology are usable to disambiguate textual content; and wherein each concept includes a sense of a word lemma, and wherein the counting for one of the concepts comprises incrementing the frequency count of the one concept, for each occurrence of the word lemma in the documents of the corpus which is included in the one concept, by 1/n where n is the total number of concepts which include a sense of the world lemma.

1. A computer-implemented method of defining a lexical database ontology comprising: accessing a lexical database comprising a plurality of concepts individually including a plurality of different words; accessing a corpus of documents; using a processor, identifying occurrences of the words in the documents of the corpus; using the processor, counting a plurality of frequency counts for the concepts, wherein the counting includes incrementing the frequency counts of the concepts using the identifying of the occurrences of the words of the respective concepts in the documents; using the processor, analyzing the frequency counts; using the processor, selecting a plurality of the concepts as event classes of a lexical database ontology using the analyzing, wherein the event classes of the lexical database ontology are usable to disambiguate textual content; and wherein each concept includes a sense of a word lemma, and wherein the counting for one of the concepts comprises incrementing the frequency count of the one concept, for each occurrence of the word lemma in the documents of the corpus which is included in the one concept, by 1/n where n is the total number of concepts which include a sense of the world lemma. 6. The method of claim 1 wherein the incrementing comprises incrementing the frequency counts of concepts which are hypernyms of concepts whose frequency counts have been incremented.

8. The method of providing the game as in claim 5 further comprising providing PGO enhancements with variable performance characteristics in first group activities where the activity module also requires a predetermined performance characteristic PGO enhancement produced by first group activities to successfully complete a second group activity.

8. The method of providing the game as in claim 5 further comprising providing PGO enhancements with variable performance characteristics in first group activities where the activity module also requires a predetermined performance characteristic PGO enhancement produced by first group activities to successfully complete a second group activity. 9. The method of providing the game as in claim 8 further comprising enabling a character object exchange arranged such that characters exchange PGO's, PGO enhancements, and PGO enhancements with variable performance characteristics whereby the required object is obtained by exchange.

15. A system comprising: one or more computers and one or more storage devices storing instructions which are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a gesture from a user, wherein the gesture is a touch input; configuring a microphone system based on the gesture received from the user to be more sensitive in the direction of the user that the gesture was received from based only on the direction from which the gesture was received; and receiving a first acoustic input from the direction of the user.

15. A system comprising: one or more computers and one or more storage devices storing instructions which are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a gesture from a user, wherein the gesture is a touch input; configuring a microphone system based on the gesture received from the user to be more sensitive in the direction of the user that the gesture was received from based only on the direction from which the gesture was received; and receiving a first acoustic input from the direction of the user. 20. The method of claim 15 , wherein the instructions further cause the one or more computers to perform operations comprising: increasing the sensitivity of at least one microphone by using at least one selected from the group of: electronic steering and mechanical steering when configuring a microphone system based on the gesture from the user.

1. A method for modifying a File Open dialog to enable searching for a file, comprising: writing a namespace extension to organize a file system into a tree-structured hierarchy of files and folders; building a customized shell view within a File Open dialog box based on the namespace extension by implementing a Component Object Model (COM) interface to display or perform an operation on contents of said customized shell via a user input device; providing a channel of communication between a view object and said File Open dialog via a second COM interface; providing a channel of communication between said File Open dialog and said customized shell view via a third COM interface; hosting a Shell browser via a fourth COM interface; receiving a user search input within the customized File Open dialog box; searching for a file indicated by the user search input; and displaying at least one search result within the customized File Open dialog box via a user output device.

1. A method for modifying a File Open dialog to enable searching for a file, comprising: writing a namespace extension to organize a file system into a tree-structured hierarchy of files and folders; building a customized shell view within a File Open dialog box based on the namespace extension by implementing a Component Object Model (COM) interface to display or perform an operation on contents of said customized shell via a user input device; providing a channel of communication between a view object and said File Open dialog via a second COM interface; providing a channel of communication between said File Open dialog and said customized shell view via a third COM interface; hosting a Shell browser via a fourth COM interface; receiving a user search input within the customized File Open dialog box; searching for a file indicated by the user search input; and displaying at least one search result within the customized File Open dialog box via a user output device. 4. The method of claim 1 , further comprising: enabling a user to drag and drop the at least one search result from the customized File Open dialog box.

9. A method for automatic natural language translation of embedded text regions in images during information transfer, the method comprising: a computer receiving in a clipboard buffer a copy of one or more user-selected image elements from within a source computer file responsive to user operation of a cut-and-paste command; the computer receiving a user-supplied isolation rule defining one or more types of image elements to be isolated; the computer examining the one or more image elements in the clipboard buffer against the isolation rule; the computer, responsive to the one or more image elements meeting the isolation rule, transferring the one or more image elements from the clipboard buffer to an isolation store, and disabling pasting of the one or more image elements into a destination computer file; the computer automatically recognizing text within the one or more image elements in the isolation store; the computer identifying a source language by determining a natural language in which the recognized text is expressed; the computer comparing a user preference by determining if the natural language of the recognized text matches a user-specified destination natural language; the computer performing automatic natural language translation of the recognized text into the user-specified destination natural language; the computer rendering text image data for the translated text; the computer overlaying the text within the one or more image elements stored in the isolation store with the rendered image data; and the computer pasting of the one or more image elements from the isolation store to one or more user-designated destination points within the destination computer file.

9. A method for automatic natural language translation of embedded text regions in images during information transfer, the method comprising: a computer receiving in a clipboard buffer a copy of one or more user-selected image elements from within a source computer file responsive to user operation of a cut-and-paste command; the computer receiving a user-supplied isolation rule defining one or more types of image elements to be isolated; the computer examining the one or more image elements in the clipboard buffer against the isolation rule; the computer, responsive to the one or more image elements meeting the isolation rule, transferring the one or more image elements from the clipboard buffer to an isolation store, and disabling pasting of the one or more image elements into a destination computer file; the computer automatically recognizing text within the one or more image elements in the isolation store; the computer identifying a source language by determining a natural language in which the recognized text is expressed; the computer comparing a user preference by determining if the natural language of the recognized text matches a user-specified destination natural language; the computer performing automatic natural language translation of the recognized text into the user-specified destination natural language; the computer rendering text image data for the translated text; the computer overlaying the text within the one or more image elements stored in the isolation store with the rendered image data; and the computer pasting of the one or more image elements from the isolation store to one or more user-designated destination points within the destination computer file. 11. The method as set forth in claim 9 wherein the Optical Character Recognition said comprises extracting strings of encoded text.

37. A mobile device comprises: a display; a processor; a memory coupled to the processor storing a computer program product that configures the processor to: retrieve from a queue in a computer storage on the device, sets of visual items of playable content, where the queue is organized by linked data structures of data types of components of information feeds that were parsed into the sets of the visual items of playable content from components of the information feeds into corresponding code functions and data elements to provide corresponding datasets, and which corresponding code functions and data elements are loaded into a player window of a player engine to render the corresponding datasets into a corresponding one or ones of the visual items of playable content, with the retrieved visual items displayed in a sequence for a time period that is regularly repeated until a user interaction or a new set is retrieved by the processor; and render the retrieved one or more sets of visual items on a display device with the rendition of the retrieved visual items in the one or more sets rendered with a title parsed from a feed title in the information feed, a banner parsed from a feed image, and a description of the information feed; and display the visual items in a sequence for a predetermined number of seconds receive a signal that pauses playback of the sequence; receive an assertion of a user interaction tool from a set of user interaction tools that enable a user to interact with the paused sequence to apply a respective operation to one of the visual items of playable content in the paused sequence; produce new content from the application of the user interaction tool; associate the produced new content with the corresponding visual item of playable content; and store the new content in the computing storage.

37. A mobile device comprises: a display; a processor; a memory coupled to the processor storing a computer program product that configures the processor to: retrieve from a queue in a computer storage on the device, sets of visual items of playable content, where the queue is organized by linked data structures of data types of components of information feeds that were parsed into the sets of the visual items of playable content from components of the information feeds into corresponding code functions and data elements to provide corresponding datasets, and which corresponding code functions and data elements are loaded into a player window of a player engine to render the corresponding datasets into a corresponding one or ones of the visual items of playable content, with the retrieved visual items displayed in a sequence for a time period that is regularly repeated until a user interaction or a new set is retrieved by the processor; and render the retrieved one or more sets of visual items on a display device with the rendition of the retrieved visual items in the one or more sets rendered with a title parsed from a feed title in the information feed, a banner parsed from a feed image, and a description of the information feed; and display the visual items in a sequence for a predetermined number of seconds receive a signal that pauses playback of the sequence; receive an assertion of a user interaction tool from a set of user interaction tools that enable a user to interact with the paused sequence to apply a respective operation to one of the visual items of playable content in the paused sequence; produce new content from the application of the user interaction tool; associate the produced new content with the corresponding visual item of playable content; and store the new content in the computing storage. 38. The mobile device of claim 37 , wherein the processor is configured to: repeatedly display the sequence of the visual items for the predetermined number of seconds.

1. A method of identifying non-functional email addresses in an email list, the method comprising: determining, by a processor, a distribution of domain names within a list of email addresses, wherein the list of email addresses comprises a plurality of domain names, wherein each domain name of the plurality of domain names are each associated with one or more email addresses, wherein the distribution of domain names comprises a correlation between each domain name present in the list and a number of email addresses containing the respective domain name; selecting a first portion of the plurality of domain names based on the distribution, wherein a remaining portion of the plurality of domain names comprises a portion of the plurality of domain names that are not within the first portion; sending, by a processor, a domain name lookup request to one or more domain name servers for each domain name in the first portion of the plurality of domain names; determining that at least one domain name of the first portion of the plurality of domain names fails a domain name lookup based on sending the domain name lookup request; adding the at least one domain name that fails the domain name lookup to a non-functional domain name list; generating, by a processor, an error expansion list using one or more domain names in the first portion of the plurality of domain names, wherein the error expansion list comprises a plurality of error domain names that are based on at least one of typographical errors or misspellings of the one or more domain names in the first portion of the plurality of domain names; comparing the domain names in the list with each of the error domain names in the error expansion list; determining that one or more of the domain names in the list match one or more of the error domain names; adding the one or more of the domain names in the list that match one or more of the error domain names to the non-functional domain name list; comparing the non-functional domain name list with the list of email addresses; determining that one or more of the email addresses in the list have domain names matching domain names on the non-functional domain name list; marking each of the one or more email addresses in the list that match the domain names on the non-functional domain name list as non-functional; and sending, by a server, an electronic message to one or more of the email addresses in the list that are not marked as non-functional without triggering a spam filtering service, wherein the electronic message is received at an electronic device.

1. A method of identifying non-functional email addresses in an email list, the method comprising: determining, by a processor, a distribution of domain names within a list of email addresses, wherein the list of email addresses comprises a plurality of domain names, wherein each domain name of the plurality of domain names are each associated with one or more email addresses, wherein the distribution of domain names comprises a correlation between each domain name present in the list and a number of email addresses containing the respective domain name; selecting a first portion of the plurality of domain names based on the distribution, wherein a remaining portion of the plurality of domain names comprises a portion of the plurality of domain names that are not within the first portion; sending, by a processor, a domain name lookup request to one or more domain name servers for each domain name in the first portion of the plurality of domain names; determining that at least one domain name of the first portion of the plurality of domain names fails a domain name lookup based on sending the domain name lookup request; adding the at least one domain name that fails the domain name lookup to a non-functional domain name list; generating, by a processor, an error expansion list using one or more domain names in the first portion of the plurality of domain names, wherein the error expansion list comprises a plurality of error domain names that are based on at least one of typographical errors or misspellings of the one or more domain names in the first portion of the plurality of domain names; comparing the domain names in the list with each of the error domain names in the error expansion list; determining that one or more of the domain names in the list match one or more of the error domain names; adding the one or more of the domain names in the list that match one or more of the error domain names to the non-functional domain name list; comparing the non-functional domain name list with the list of email addresses; determining that one or more of the email addresses in the list have domain names matching domain names on the non-functional domain name list; marking each of the one or more email addresses in the list that match the domain names on the non-functional domain name list as non-functional; and sending, by a server, an electronic message to one or more of the email addresses in the list that are not marked as non-functional without triggering a spam filtering service, wherein the electronic message is received at an electronic device. 5. The method of claim 1 , further comprising: determining a plurality of text strings; comparing the plurality of text strings to the domain names in the remaining portion of the plurality of domain names; determining that one or more of the domain names in the plurality of domain names contain one or more of the plurality of text strings; adding the one or more of the domain names that contain one or more of the plurality of text strings to the non-functional domain name list.

13. A non-transitory computer-readable medium having stored thereon executable instructions that, in response to execution, cause a computing system to perform operations, the operations comprising: receiving an industrial application and associated metadata from a first client device, the industrial application comprising at least one of programming code for an industrial controller or a human-machine interface graphic, and the metadata specifying at least an industry type and a type of industrial process to which the industrial application pertains; indexing the industrial application in an application library in accordance with the metadata, the application library residing on a cloud platform and classifying the industrial application according to hierarchical categories of a storage schema comprising at least the industry type and the type of industrial process specified by the metadata; receiving browsing input from a second client device; identifying a subset of industrial applications stored in the application library based on the browsing input, wherein the browsing input progressively narrows the subset of the industrial applications based on a selected industry type and a selected type of industrial process identified by the browsing input; displaying identification information for the subset of industrial applications; and provisioning a selected industrial application of the subset of industrial applications to a memory location associated with the second client device.

13. A non-transitory computer-readable medium having stored thereon executable instructions that, in response to execution, cause a computing system to perform operations, the operations comprising: receiving an industrial application and associated metadata from a first client device, the industrial application comprising at least one of programming code for an industrial controller or a human-machine interface graphic, and the metadata specifying at least an industry type and a type of industrial process to which the industrial application pertains; indexing the industrial application in an application library in accordance with the metadata, the application library residing on a cloud platform and classifying the industrial application according to hierarchical categories of a storage schema comprising at least the industry type and the type of industrial process specified by the metadata; receiving browsing input from a second client device; identifying a subset of industrial applications stored in the application library based on the browsing input, wherein the browsing input progressively narrows the subset of the industrial applications based on a selected industry type and a selected type of industrial process identified by the browsing input; displaying identification information for the subset of industrial applications; and provisioning a selected industrial application of the subset of industrial applications to a memory location associated with the second client device. 14. The non-transitory computer-readable medium of claim 13 , wherein the provisioning comprises allowing the second client device to execute the selected industrial application using a set of cloud resources assigned to an industrial enterprise.

34. The non-transitory computer readable storage medium of claim 32 , wherein the second gesture is a swipe gesture.

34. The non-transitory computer readable storage medium of claim 32 , wherein the second gesture is a swipe gesture. 35. The non-transitory computer readable storage medium of claim 34 , wherein the second gesture is an upward swipe gesture and the scroll is a one-dimensional vertical scroll.

1. A method for refining a process model, comprising: mining a process model from a set of execution traces; determining whether the process model is too dense or too sparse; learning a predictive model from the execution traces to predict an outcome; modifying the predictive model with a processor, comprising: making the predictive model more specific if it is determined that the process model is too dense; and making the predictive model more general if it is determined that the process model is too sparse; and mining a refined process model from updated traces based on attributes present in the modified predictive model.

1. A method for refining a process model, comprising: mining a process model from a set of execution traces; determining whether the process model is too dense or too sparse; learning a predictive model from the execution traces to predict an outcome; modifying the predictive model with a processor, comprising: making the predictive model more specific if it is determined that the process model is too dense; and making the predictive model more general if it is determined that the process model is too sparse; and mining a refined process model from updated traces based on attributes present in the modified predictive model. 10. The method of claim 1 , further comprising repeating said steps of determining, learning, modifying, and mining a refined process model until the step of determining determines that the process model is neither too sparse nor too dense.

11. The method of claim 10 , wherein the priority value is determined based on an impact-metric of the first text string, wherein the impact-metric measures an importance of the first text string.

11. The method of claim 10 , wherein the priority value is determined based on an impact-metric of the first text string, wherein the impact-metric measures an importance of the first text string. 13. The method of claim 11 , wherein the impact-metric of the first text string is based on an estimate of the number of distinct users for whom a translation of the first text string is to be published, the estimate being based on a sample of a plurality of text strings or their associated translations that have been published to a subset of users.

16. A system comprising: an electronic data store configured to store a plurality of acoustic models; and one or more computer processors implemented in hardware and in communication with the electronic data store, the one or more computer processors configured to at least: receive a first signal comprising first speech; generate first speech recognition results using the first signal and an acoustic model of the plurality of acoustic models, wherein the first speech recognition results comprise a textual transcription of the first speech; and subsequent to generating the first speech recognition results: determine a first confidence value associated with the first speech recognition results; generate a first updated acoustic model based at least in part on the first confidence value associated with the first speech recognition results; generate second speech recognition results using a second signal and the first updated acoustic model, wherein the second speech recognition results comprise a textual transcription of second speech in the second signal; determine a second confidence value associated with the second speech recognition results; determine that the first speech recognition results were generated outside a window; and generate a second updated acoustic model based at least in part on the second confidence value.

16. A system comprising: an electronic data store configured to store a plurality of acoustic models; and one or more computer processors implemented in hardware and in communication with the electronic data store, the one or more computer processors configured to at least: receive a first signal comprising first speech; generate first speech recognition results using the first signal and an acoustic model of the plurality of acoustic models, wherein the first speech recognition results comprise a textual transcription of the first speech; and subsequent to generating the first speech recognition results: determine a first confidence value associated with the first speech recognition results; generate a first updated acoustic model based at least in part on the first confidence value associated with the first speech recognition results; generate second speech recognition results using a second signal and the first updated acoustic model, wherein the second speech recognition results comprise a textual transcription of second speech in the second signal; determine a second confidence value associated with the second speech recognition results; determine that the first speech recognition results were generated outside a window; and generate a second updated acoustic model based at least in part on the second confidence value. 24. The system of claim 16 , wherein the one or more computer processors are configured to determine the first confidence value based at least in part on at least one of: a level of background noise; a volume of the first speech included in the first signal; a duration of the first speech included in the first signal; or probability scores associated with the first textual transcription of the first signal.

1. In a computing environment comprising an application executing on a computer system that includes one or more processors, wherein the application hosts documents, a method of facilitating application level add-in to add document level controls, the method comprising: the computer system creating an enhanced native control object by wrapping a native control object with a wrapper that defines one or more extension methods, the one or more extension methods being configured to be called by an application level add-in to add and remove document level controls from the native control object for documents opened or created in the application, the application level add-in being configured to act under a first root object corresponding to an add-in class; the computer system determining, by the application level add-in, that a particular document has been opened or created in the application; the computer system determining, by the application level add-in, a class of documents for which document level controls should be added; the computer system determining, by the application level add-in, that the particular document that has been opened or created is in the class of documents; based on determining that the particular document is in the class of documents, the computer system determining, by the application level add-in, and that a particular document level control is to be added to the particular document; the computer system adding, by the application level add-in, the particular document level control to the particular document by calling the one or more extension methods of the enhanced native control object, the document level control being configured to act under a different second root object representing the particular document; the computer system monitoring, by the application level add-in, the particular document to determine when the particular document is closed; and upon the application level add-in determining that the particular document has been closed, the application level add-in removing the particular document level control to prevent the particular document level control from further executing by calling the one or more extension methods of the enhanced native control object.

1. In a computing environment comprising an application executing on a computer system that includes one or more processors, wherein the application hosts documents, a method of facilitating application level add-in to add document level controls, the method comprising: the computer system creating an enhanced native control object by wrapping a native control object with a wrapper that defines one or more extension methods, the one or more extension methods being configured to be called by an application level add-in to add and remove document level controls from the native control object for documents opened or created in the application, the application level add-in being configured to act under a first root object corresponding to an add-in class; the computer system determining, by the application level add-in, that a particular document has been opened or created in the application; the computer system determining, by the application level add-in, a class of documents for which document level controls should be added; the computer system determining, by the application level add-in, that the particular document that has been opened or created is in the class of documents; based on determining that the particular document is in the class of documents, the computer system determining, by the application level add-in, and that a particular document level control is to be added to the particular document; the computer system adding, by the application level add-in, the particular document level control to the particular document by calling the one or more extension methods of the enhanced native control object, the document level control being configured to act under a different second root object representing the particular document; the computer system monitoring, by the application level add-in, the particular document to determine when the particular document is closed; and upon the application level add-in determining that the particular document has been closed, the application level add-in removing the particular document level control to prevent the particular document level control from further executing by calling the one or more extension methods of the enhanced native control object. 7. The method of claim 1 , wherein adding the particular document level control to the particular document comprises wrapping a native control to allow the native control to be implemented as a document level control based on interaction with the application wide add-in.

7. A computer program product, comprising one or more computer readable hardware storage devices having computer readable program instructions stored therein, said program instructions executable by one or more processors of a computer system to implement a method for enhanced local commoning optimization of compilation of a program, said method comprising: performing, by the one or more processors, commoning of volatiles within an extended block for a particular memory model associated with a particular programming language, using a two pass approach by: determining, by the one or more processors, within a first pass, where in the program to evaluate volatile expressions that can be commoned; and commoning, by the one or more processors, in a second pass, all remaining expressions that are not volatile expressions.

7. A computer program product, comprising one or more computer readable hardware storage devices having computer readable program instructions stored therein, said program instructions executable by one or more processors of a computer system to implement a method for enhanced local commoning optimization of compilation of a program, said method comprising: performing, by the one or more processors, commoning of volatiles within an extended block for a particular memory model associated with a particular programming language, using a two pass approach by: determining, by the one or more processors, within a first pass, where in the program to evaluate volatile expressions that can be commoned; and commoning, by the one or more processors, in a second pass, all remaining expressions that are not volatile expressions. 12. The computer program product of claim 7 , wherein the particular memory model associated with the particular programming language is selected from a group consisting of a managed runtime language, a scripting environment language, and a procedural language.

1. A method of converting and transmitting audio information, comprising: receiving spoken audio input; converting the received spoken audio input into digital data that is representative of the received spoken audio input, wherein converting the received spoken audio input into digital data comprises creating a stream of digital data pockets, each digital data packet having a payload of data representative of a portion of the received spoken audio input; generating a textual representation of the received spoken audio input; inserting portions of the textual representation of the received spoken audio input into one or more headers of the digital data packets; and transmitting corresponding portions of the digital data and the textual representation to a destination device at substantially the same time.

1. A method of converting and transmitting audio information, comprising: receiving spoken audio input; converting the received spoken audio input into digital data that is representative of the received spoken audio input, wherein converting the received spoken audio input into digital data comprises creating a stream of digital data pockets, each digital data packet having a payload of data representative of a portion of the received spoken audio input; generating a textual representation of the received spoken audio input; inserting portions of the textual representation of the received spoken audio input into one or more headers of the digital data packets; and transmitting corresponding portions of the digital data and the textual representation to a destination device at substantially the same time. 2. The method of claim 1 , wherein converting the received spoken audio input into digital data comprises using a CODEC to convert the received spoken audio input into digital data packets.

8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs.

8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs. 11. The system of claim 8 , wherein the selected top level flow controller interacts independent of an associated decision model.

1. A method of creating a pool of images available for display, the method comprising: generating a pre-determined number N of numbers; encoding an instruction in a markup language document, the instruction identifying a utility program to include the pre-determined N numbers and be executed by one or more hardware-based processors to dynamically select N images for insertion into the markup language document; automatically invoking the utility program when the instruction is processed; automatically selecting the N images from all available images using the N numbers, each selected image having at least one predefined data parameter associated with an item represented in that selected image; and placing the N images in the markup language document at one or more respective locations defined in the instruction, the N images to be displayed on one or more web pages.

1. A method of creating a pool of images available for display, the method comprising: generating a pre-determined number N of numbers; encoding an instruction in a markup language document, the instruction identifying a utility program to include the pre-determined N numbers and be executed by one or more hardware-based processors to dynamically select N images for insertion into the markup language document; automatically invoking the utility program when the instruction is processed; automatically selecting the N images from all available images using the N numbers, each selected image having at least one predefined data parameter associated with an item represented in that selected image; and placing the N images in the markup language document at one or more respective locations defined in the instruction, the N images to be displayed on one or more web pages. 3. The method of claim 1 , wherein the selecting the N images for the pool of images includes: obtaining filtering criteria; identifying an image from the all available images based on the filtering criteria; and adding the identified image to the pool of images.

26. The method of claim 25 , wherein the generating of a score for a structure having an aggregate comprises calculating (a) a deviation score of the search expression, and (b) for each sub-expression of the search expression, a density and a relevance center of the sub-expression, for the aggregate, the calculating being performed using at least relevance geometry of the aggregate, one or more deviation scores of the search expression of each child of the aggregate, and a density of each sub-expression of the search expression for each child of the aggregate.

26. The method of claim 25 , wherein the generating of a score for a structure having an aggregate comprises calculating (a) a deviation score of the search expression, and (b) for each sub-expression of the search expression, a density and a relevance center of the sub-expression, for the aggregate, the calculating being performed using at least relevance geometry of the aggregate, one or more deviation scores of the search expression of each child of the aggregate, and a density of each sub-expression of the search expression for each child of the aggregate. 33. The method of claim 26 , wherein the generating of a score for a structure having an aggregate comprises calculating a relevance center of matches for the search expression for the aggregate by calculating (Σ 1≦i≦n (A i *v i *p i ))/(Σ 1≦i≦n (A i *v i )), where n is a number of children of the aggregate, A i is the relevance size of the i-th child of the aggregate, v i is the relevance value for the search expression assigned to the i-th child of the aggregate, p i is a position of the relevance center for the search expression for the i-th child of the aggregate in a space corresponding to the aggregate.

13. An article of manufacture, embodying logic to perform a method of mining a collection of data, comprising: a user interface for: receiving a collection of data, the collection of data comprising key words, wherein the key words comprise coherent character strings; visually displaying statistical information; and presenting a distribution of differences of unique concepts; and a processor embodying logic for: converting the collection of data into labeled data by grouping various types of data into a same format and assigning a label indicating a category of item contents, such that the labeled data is in analyzable condition for concept extraction, and wherein the labeled data comprises the label and a clause comprising the item contents; assigning a category to the key words, wherein the category references a concept so that the key words can be handled as concepts with a meaning; separating the clauses into pairs comprising an independent word and an attached word; assigning categories to the separated clauses using syntactic patterns and a category dictionary; generating, by syntactic analysis, a syntactic tree of a sentence comprising the separated clauses; receiving a syntactically analyzed sentence as input, identifying mutually dependent relationships between or among the categorized words, within each of the clauses; grouping the identified mutually dependent relationships into groups of related mutually dependent relationships; extracting the key words with mutually dependent relationships in the same sentence as labeled data with concepts, wherein the step of extracting key words comprises using a mutually dependent relationship extraction rule comprising a string of categories of arbitrary length to be extracted; and searching for the unique concepts, the unique concept being a concept whose statistical characteristic is distinguished beyond a threshold with the set to which it belongs; creating and keeping the statistical information.

13. An article of manufacture, embodying logic to perform a method of mining a collection of data, comprising: a user interface for: receiving a collection of data, the collection of data comprising key words, wherein the key words comprise coherent character strings; visually displaying statistical information; and presenting a distribution of differences of unique concepts; and a processor embodying logic for: converting the collection of data into labeled data by grouping various types of data into a same format and assigning a label indicating a category of item contents, such that the labeled data is in analyzable condition for concept extraction, and wherein the labeled data comprises the label and a clause comprising the item contents; assigning a category to the key words, wherein the category references a concept so that the key words can be handled as concepts with a meaning; separating the clauses into pairs comprising an independent word and an attached word; assigning categories to the separated clauses using syntactic patterns and a category dictionary; generating, by syntactic analysis, a syntactic tree of a sentence comprising the separated clauses; receiving a syntactically analyzed sentence as input, identifying mutually dependent relationships between or among the categorized words, within each of the clauses; grouping the identified mutually dependent relationships into groups of related mutually dependent relationships; extracting the key words with mutually dependent relationships in the same sentence as labeled data with concepts, wherein the step of extracting key words comprises using a mutually dependent relationship extraction rule comprising a string of categories of arbitrary length to be extracted; and searching for the unique concepts, the unique concept being a concept whose statistical characteristic is distinguished beyond a threshold with the set to which it belongs; creating and keeping the statistical information. 14. The article of manufacture of claim 13 wherein converting comprises conversion of the received collection of data into the same format, wherein the received collection of data is made up of various data formats.

1. An apparatus comprising: a stack of word line layers comprising word lines for a three-dimensional non-volatile memory array, the stack of word line layers comprising a plurality of tiers; a plurality of word line switch transistors for transferring word line bias voltages to the word lines; a plurality of word line contact regions for coupling the word line switch transistors to the word lines, a word line contact region comprising a stepped structure for a tier of the word line layers, wherein a level region separates a word line contact region for a first tier from a word line contact region for a second tier; and a plurality of connectors coupling the word line switch transistors to the word lines, the connectors comprising vertical conductors, wherein connectors for a single word line contact region comprise vertical conductors disposed within the single word line contact region, at a first side of the single word line contact region, and at a second side of the single word line contact region.

1. An apparatus comprising: a stack of word line layers comprising word lines for a three-dimensional non-volatile memory array, the stack of word line layers comprising a plurality of tiers; a plurality of word line switch transistors for transferring word line bias voltages to the word lines; a plurality of word line contact regions for coupling the word line switch transistors to the word lines, a word line contact region comprising a stepped structure for a tier of the word line layers, wherein a level region separates a word line contact region for a first tier from a word line contact region for a second tier; and a plurality of connectors coupling the word line switch transistors to the word lines, the connectors comprising vertical conductors, wherein connectors for a single word line contact region comprise vertical conductors disposed within the single word line contact region, at a first side of the single word line contact region, and at a second side of the single word line contact region. 9. The apparatus of claim 1 , wherein the plurality of word line contact regions comprises three or more word line contact regions separated by level regions.

1. A method implemented in a computer infrastructure having computer executable code tangibly embodied in a computer readable storage medium having programming instructions configured to: receive an input text which comprises an unstructured message in a first dialect and a second dialect of at least one language at a first computing device; identify the unstructured message as inappropriate language in the first dialect and appropriate language in the second dialect of the at least one language; process the input text according to a string-structure similarity measure which compares each word of the input text to a predefined dictionary to indicate whether there is a similarity in meaning; and generate an evaluation score for each word of the input text at the first computing device and send the evaluation score to another computing device, wherein the evaluation score for each word of the input text is based on the string-structure similarity measure between each word of the input text and the predefined dictionary, and the evaluation score corresponds to a degree that the unstructured message of the input text comprises the inappropriate language in the first dialect with respect to the appropriate language in the second dialect of the at least one language.

1. A method implemented in a computer infrastructure having computer executable code tangibly embodied in a computer readable storage medium having programming instructions configured to: receive an input text which comprises an unstructured message in a first dialect and a second dialect of at least one language at a first computing device; identify the unstructured message as inappropriate language in the first dialect and appropriate language in the second dialect of the at least one language; process the input text according to a string-structure similarity measure which compares each word of the input text to a predefined dictionary to indicate whether there is a similarity in meaning; and generate an evaluation score for each word of the input text at the first computing device and send the evaluation score to another computing device, wherein the evaluation score for each word of the input text is based on the string-structure similarity measure between each word of the input text and the predefined dictionary, and the evaluation score corresponds to a degree that the unstructured message of the input text comprises the inappropriate language in the first dialect with respect to the appropriate language in the second dialect of the at least one language. 8. The method of claim 1 , wherein the predefined dictionary comprises a plurality of dialects which correspond to the at least one language.

7. The method of claim 5 , wherein the recognizing the type of network access used by the user to submit the text string query comprises: recognizing an industry-specific internet content adaptation protocol content associated with the text string query, wherein the industry-specific internet content adaptation protocol content is associated with users having the predominant occupational identity.

7. The method of claim 5 , wherein the recognizing the type of network access used by the user to submit the text string query comprises: recognizing an industry-specific internet content adaptation protocol content associated with the text string query, wherein the industry-specific internet content adaptation protocol content is associated with users having the predominant occupational identity. 8. The method of claim 7 , wherein the step of displaying the primary set of search results, the secondary set of search results and the set of peripheral knowledge articles to the user in the different, respective tabbed sheets that are nested on top of one another in a web-based interface dashboard comprises: displaying a list of the primary set of results to the user in a primary tabbed sheet of the nested tabbed sheets; listing the secondary set of search results in a secondary tabbed sheet of the nested tabbed sheets, wherein the list of the secondary set of search results is nested behind the primary tabbed sheet and not visible to the user unless selected by the user; and listing the set of peripheral search results in a peripheral tabbed sheet of the nested tabbed sheets, wherein the list of the set of peripheral search results is nested behind the primary and secondary tabbed sheets and not visible to the user unless selected by the user; and wherein selection of one of the secondary tabbed sheet and the peripheral tabbed sheet by the user via a graphical user interface cursor routine causes a display of the list of results of the selected one of the secondary tabbed sheet and the peripheral tabbed sheet in a tabbed sheet display above each of other unselected ones of the primary tabbed sheet, the secondary tabbed sheet and the peripheral tabbed sheet.

6. The system of claim 1 , where the data includes key words describing the first image.

6. The system of claim 1 , where the data includes key words describing the first image. 7. The system of claim 6 , where Beta uses the key words to aid finding a/the preferences of an owner of Beta.

18. The machine-readable storage device of claim, wherein the operations further comprise: obtaining a language preference by the query originator; and determining the second language based on the language preference.

18. The machine-readable storage device of claim, wherein the operations further comprise: obtaining a language preference by the query originator; and determining the second language based on the language preference. 19. The machine-readable storage device of claim 18 , wherein the language preference is based on a language preference setting related to search results from the query originator.

1. A method in a computer system for determining an operand for an operator during data entry of the nodes of an intentional program tree, the method comprising: receiving a sequence of tokens, each token indicating a computational construct corresponding to a node of the intentional program tree; when receiving an indication of a selection of a subtree of the intentional program tree, selecting the indicated subtree; and when receiving an indication of a next token to be appended to the sequence of tokens, when a subtree is currently selected, identifying the selected subtree as an operand of the operator represented by the next token; when a subtree is not currently selected, identifying according to predefined rules of operator precedence an operand of the operator represented by the next token; and adding a node to the intentional program tree indicating the operator represented by the next token and indicating the identified operand whereby predefined rules of operator precedence may be overridden by selection of a subtree.

1. A method in a computer system for determining an operand for an operator during data entry of the nodes of an intentional program tree, the method comprising: receiving a sequence of tokens, each token indicating a computational construct corresponding to a node of the intentional program tree; when receiving an indication of a selection of a subtree of the intentional program tree, selecting the indicated subtree; and when receiving an indication of a next token to be appended to the sequence of tokens, when a subtree is currently selected, identifying the selected subtree as an operand of the operator represented by the next token; when a subtree is not currently selected, identifying according to predefined rules of operator precedence an operand of the operator represented by the next token; and adding a node to the intentional program tree indicating the operator represented by the next token and indicating the identified operand whereby predefined rules of operator precedence may be overridden by selection of a subtree. 3. The method of claim 1 wherein the operator is a binary operator and the identified operand is a left operand.

1. In a health care enterprise, a computerized provider order entry system for receiving one or more search terms from a health care provider and finding an order for providing a medication or medical service related to the one or more search terms, comprising: a repository including a plurality of records identifying a corresponding plurality of medications or medical services available for order, a record of an individual medication or medical service available for order including a plurality of related text terms describing order related parameters, including terms identifying a treatment and at least one of: (a) a diagnosis code associated with the medication or medical service available for order, (b) a medical condition associated with the medication or medical service available for order, and (c) a medical problem associated with the medication or medical service available for order; a search processor for searching said plurality of records to find candidate medications or medical services available for order corresponding to the one or more health care provider entered search terms by: determining a relative frequency of occurrence of respective ones of the one or more search terms in the related text terms of corresponding records of candidate medications or medical services available for order; summing data representing the relative frequency of occurrence of the respective ones of the one or more search terms to provide data representing a summed relative frequency of the one or more search terms in corresponding records of candidate medications or medical services available for order; identifying and prioritizing candidate medications or medical services available for order in response to the summed relative frequency of occurrence of said health care provider entered search terms in corresponding records of said candidate medications or medical services available for order; and ranking said identified and prioritized candidate medications or medical services available for order in response to a relative frequency of ordering of said identified and prioritized candidate medications or medical services available for use by health care providers; wherein said search processor alters search result ranking based on voting mechanisms for said medications or medical services available for order, said voting achieved by at least one of (a) selection of an item for order in normal use and (b) manual adjustment of priority weighting of that item for order; and an output processor for providing search result data representing said ranked, identified and prioritized candidate medications or medical services.

1. In a health care enterprise, a computerized provider order entry system for receiving one or more search terms from a health care provider and finding an order for providing a medication or medical service related to the one or more search terms, comprising: a repository including a plurality of records identifying a corresponding plurality of medications or medical services available for order, a record of an individual medication or medical service available for order including a plurality of related text terms describing order related parameters, including terms identifying a treatment and at least one of: (a) a diagnosis code associated with the medication or medical service available for order, (b) a medical condition associated with the medication or medical service available for order, and (c) a medical problem associated with the medication or medical service available for order; a search processor for searching said plurality of records to find candidate medications or medical services available for order corresponding to the one or more health care provider entered search terms by: determining a relative frequency of occurrence of respective ones of the one or more search terms in the related text terms of corresponding records of candidate medications or medical services available for order; summing data representing the relative frequency of occurrence of the respective ones of the one or more search terms to provide data representing a summed relative frequency of the one or more search terms in corresponding records of candidate medications or medical services available for order; identifying and prioritizing candidate medications or medical services available for order in response to the summed relative frequency of occurrence of said health care provider entered search terms in corresponding records of said candidate medications or medical services available for order; and ranking said identified and prioritized candidate medications or medical services available for order in response to a relative frequency of ordering of said identified and prioritized candidate medications or medical services available for use by health care providers; wherein said search processor alters search result ranking based on voting mechanisms for said medications or medical services available for order, said voting achieved by at least one of (a) selection of an item for order in normal use and (b) manual adjustment of priority weighting of that item for order; and an output processor for providing search result data representing said ranked, identified and prioritized candidate medications or medical services. 6. A system according to claim 1 , wherein said search processor identifies and prioritizes individual candidate medications or medical services available for order proportional to a number of occurrences of said user entered search term relative to a total number of terms in a corresponding record of an individual candidate item for order.

24. A non-transitory computer-readable storage medium storing executable computer instructions that, when executed by a processor, cause the processor to perform steps comprising: generating a preview document of a native document comprising a preview code including table elements corresponding to fields in the native document, the native document stored on a client device, the generating comprising: generating field dimensions for the fields in the native document; generating a field mapping of fields in the native document to table elements in the preview code; generating a formula listing designating, for each formula of a set of formulas in the native document, one or more fields associated with the formula in the native document; and displaying the preview document on a display by executing the preview code; generating an updated preview document in response to a change to the native document; swapping the updated preview document with the displayed preview document; and applying a current user interaction context to the swapped updated preview document.

24. A non-transitory computer-readable storage medium storing executable computer instructions that, when executed by a processor, cause the processor to perform steps comprising: generating a preview document of a native document comprising a preview code including table elements corresponding to fields in the native document, the native document stored on a client device, the generating comprising: generating field dimensions for the fields in the native document; generating a field mapping of fields in the native document to table elements in the preview code; generating a formula listing designating, for each formula of a set of formulas in the native document, one or more fields associated with the formula in the native document; and displaying the preview document on a display by executing the preview code; generating an updated preview document in response to a change to the native document; swapping the updated preview document with the displayed preview document; and applying a current user interaction context to the swapped updated preview document. 26. The non-transitory computer-readable storage medium of claim 24 , wherein the executable computer instructions is further configured to cause the processor to: receive a modification of a table element from the user; determine a target field associated with the modification using the field mapping; and modify the target field in the native document with the modification.

10. An image processing system configured to process a medical image data set for a patient, comprising: a memory configured to store a medical image data set; and a processor configured to apply a first classifier to the medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a plaque region and configured to pass the identified subset to a second classifier and to apply the second classifier to the first subset the second classifier having a specificity configured to confirm the presence, or absence, of the plaque region in one or more portions of the first subset, wherein the plaque region is selected from an occlusive plague region and a vulnerable plague region, and wherein each of the first classifier and the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, the processor further configured to apply a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, pass the identified second subset to a fourth classifier and further apply the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region, wherein each of the third classifier and the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, wherein the second specified distinctive region is a different type of region than the plaque region.

10. An image processing system configured to process a medical image data set for a patient, comprising: a memory configured to store a medical image data set; and a processor configured to apply a first classifier to the medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a plaque region and configured to pass the identified subset to a second classifier and to apply the second classifier to the first subset the second classifier having a specificity configured to confirm the presence, or absence, of the plaque region in one or more portions of the first subset, wherein the plaque region is selected from an occlusive plague region and a vulnerable plague region, and wherein each of the first classifier and the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, the processor further configured to apply a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, pass the identified second subset to a fourth classifier and further apply the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region, wherein each of the third classifier and the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, wherein the second specified distinctive region is a different type of region than the plaque region. 14. The image processing system of claim 10 , wherein the processor is further configured to format the medical image data set for display with a visual indication of the location of the distinctive region in the medical image data set.

3. The method of claim 1 wherein the profile constructing step includes the steps of detecting the frequency distribution of the energy of the utterance for a plurality of time intervals within the duration of a single phoneme, and deriving at least a pair of sweep spectra representing the change in energy present in the phoneme from one frequency to another as a function of time for a plurality of frequency distributions, and wherein the difference profile generating step includes generating a pair of difference profiles for substantially each pair of significant phonemes by subtracting the respective sweep spectra of each significant phoneme from the respective sweep spectrum of each other significant phoneme.

3. The method of claim 1 wherein the profile constructing step includes the steps of detecting the frequency distribution of the energy of the utterance for a plurality of time intervals within the duration of a single phoneme, and deriving at least a pair of sweep spectra representing the change in energy present in the phoneme from one frequency to another as a function of time for a plurality of frequency distributions, and wherein the difference profile generating step includes generating a pair of difference profiles for substantially each pair of significant phonemes by subtracting the respective sweep spectra of each significant phoneme from the respective sweep spectrum of each other significant phoneme. 5. The method of claim 3 wherein the sweep spectra deriving step includes deriving a short time constant sweep spectrum having a first time constant, and deriving a long time constant sweep spectrum having a time constant longer than the first time constant.

1. A system for determining popularity of an individual, comprising: a database, the database configured to provide rankings of several individuals; a client computer; an information server for providing information of the individual, the information comprising qualitative data and quantitative data; and a popularity profiling server operably connected to the database, the client computer, and the information server, the popularity profiling server configured to receive, from the information server, the information, analyze a quantitative data portion of the information, analyze a qualitative data portion of the information using sentiment analysis, the sentiment analysis by natural language parsing to separate the qualitative data into parts of speech, calculate an initial set of scores for the popularity of the individual based on the analysis of the quantitative data portion and the qualitative data portion of the information, update a ranking for the popularity of the individual in the database based on the initial set of scores, determine, after waiting a predetermined amount of time, whether new data has been updated to the information on the information server, the predetermined amount of time entered by a client on the client computer, and if new data has been updated, calculate an updated set of scores for the information based on the new data, and update the ranking for the popularity of the individual on the database.

1. A system for determining popularity of an individual, comprising: a database, the database configured to provide rankings of several individuals; a client computer; an information server for providing information of the individual, the information comprising qualitative data and quantitative data; and a popularity profiling server operably connected to the database, the client computer, and the information server, the popularity profiling server configured to receive, from the information server, the information, analyze a quantitative data portion of the information, analyze a qualitative data portion of the information using sentiment analysis, the sentiment analysis by natural language parsing to separate the qualitative data into parts of speech, calculate an initial set of scores for the popularity of the individual based on the analysis of the quantitative data portion and the qualitative data portion of the information, update a ranking for the popularity of the individual in the database based on the initial set of scores, determine, after waiting a predetermined amount of time, whether new data has been updated to the information on the information server, the predetermined amount of time entered by a client on the client computer, and if new data has been updated, calculate an updated set of scores for the information based on the new data, and update the ranking for the popularity of the individual on the database. 2. The system of claim 1 , wherein the popularity profiling server is further configured to receive a request for a current ranking of the individual using an identifier from a remote third party application, retrieve from the database the current ranking of the individual using the identifier, and transmit the current ranking to the remote third party application, the current ranking representing a ranked order of the individual based on a comparison of the individual's current sets of scores to other individuals' current sets of scores.

12. The method for organizing digital images of claim 8 , further comprising: determining an associated classification for each of the digital images based on the probability that a block vocabulary and a word vocabulary apply.

12. The method for organizing digital images of claim 8 , further comprising: determining an associated classification for each of the digital images based on the probability that a block vocabulary and a word vocabulary apply. 13. The method for organizing digital images of claim 12 , further comprising: retrieving digital images searched by a query tag using the block vectors associated with the probability that the block vocabulary and the word vocabulary apply.

36. A search engine as claimed in claim 35 , wherein said comparing is executed from the upper level of the tree structure to the lower level, with paths in the structure being selected on the basis of the comparison between the vectors.

36. A search engine as claimed in claim 35 , wherein said comparing is executed from the upper level of the tree structure to the lower level, with paths in the structure being selected on the basis of the comparison between the vectors. 37. A search engine as claimed in claim 36 , wherein said index network obtains the product of said query vector and the text vector of the nodes of a level of said structure, and obtains said product for nodes of a succeeding level of said structure which are connected to nodes for which the product has exceeded a predetermined threshold.

10. A system for providing advertisements that are associated with actors, comprising user equipment that is configured to: access a collection of media information, wherein the media information comprises a plurality of advertisements; receive user input requesting advertisements associated with an actor, wherein the user input comprises a search expression that includes a name of the actor; generate based on the user input a plurality of search terms that are associated with the actor, wherein one of the search terms is different from the name of the actor; search the collection of media information to identify advertisements that are associated with the search terms; and generate a display based on the identified advertisements.

10. A system for providing advertisements that are associated with actors, comprising user equipment that is configured to: access a collection of media information, wherein the media information comprises a plurality of advertisements; receive user input requesting advertisements associated with an actor, wherein the user input comprises a search expression that includes a name of the actor; generate based on the user input a plurality of search terms that are associated with the actor, wherein one of the search terms is different from the name of the actor; search the collection of media information to identify advertisements that are associated with the search terms; and generate a display based on the identified advertisements. 11. The system of claim 10 wherein the media information further comprises at least one of media program listings, media programming information, celebrity information, photos, videos, audio clips and articles.

10. A system in accordance with claim 9 , wherein said at least one business information system module further includes at least one customer relationship management module and said second information is derived from said at least one enterprise resource planning module or said at least one customer relationship management module.

10. A system in accordance with claim 9 , wherein said at least one business information system module further includes at least one customer relationship management module and said second information is derived from said at least one enterprise resource planning module or said at least one customer relationship management module. 11. A method in accordance with claim 10 , wherein said at least one customer relationship management module is hosted by an application service provider.

4. The system of claim 1 , in which the model defines a relationship between (i) users in each of one or more classes and (ii) estimated consumption of resources by such users during execution of the application.

4. The system of claim 1 , in which the model defines a relationship between (i) users in each of one or more classes and (ii) estimated consumption of resources by such users during execution of the application. 6. The system of claim 4 , in which the model defines quotas for usage of the application and/or one or more components thereof in production mode by users in each of one or more classes.

18. The computer system of claim 11 , wherein the instructions further comprise: receiving a deployment request to deploy a deployable package on the cloud computing platform; according to a set of rules, parsing the received deployable package to search for a file including documentation content, the set of rules includes rules for specifying a predetermined type of the file, a predetermined location at the deployable package specifying where to search for the file, and a predetermined naming convention; upon determining that the file including the documentation content is included in the deployable package, extract the file including the documentation content from the deployable package; and store the extracted file including the documentation content in the documentation repository.

18. The computer system of claim 11 , wherein the instructions further comprise: receiving a deployment request to deploy a deployable package on the cloud computing platform; according to a set of rules, parsing the received deployable package to search for a file including documentation content, the set of rules includes rules for specifying a predetermined type of the file, a predetermined location at the deployable package specifying where to search for the file, and a predetermined naming convention; upon determining that the file including the documentation content is included in the deployable package, extract the file including the documentation content from the deployable package; and store the extracted file including the documentation content in the documentation repository. 19. The computer system of claim 18 , wherein the instructions further comprises: upon receiving the deployment request, determining whether the deployment request is associated with an authorized account for authorized software associated with the deployment package; upon determining that the deployment request is associated with the authorized account for the authorized software, verifying credentials provided with the deployment request; and authorizing the deployment upon the verified credentials.

8. A non-transitory computer readable storage medium storing executable program instructions, which, when executed by an electronic device with one or more processors, memory, and a touch-sensitive display, cause the electronic device to: receive data relating to device movement and data relating to device orientation; receive a touch input on the touch-sensitive display; process the received data relating to device movement and the received data relating to device orientation to determine whether the electronic device is in one of a first or second state based on the received data relating to device movement and the received data relating to device orientation, wherein the first state occurs when a user is looking at the electronic device; if it is determined that the electronic device is in the first state, process the touch input as an intentional touch input; if it is determined that the electronic device is in the second state, process the touch input as an unintentional touch input; and in response to detecting a first change in the received data relating to device movement and the received data relating to device orientation, determine that the device has changed from the second state to the first state.

8. A non-transitory computer readable storage medium storing executable program instructions, which, when executed by an electronic device with one or more processors, memory, and a touch-sensitive display, cause the electronic device to: receive data relating to device movement and data relating to device orientation; receive a touch input on the touch-sensitive display; process the received data relating to device movement and the received data relating to device orientation to determine whether the electronic device is in one of a first or second state based on the received data relating to device movement and the received data relating to device orientation, wherein the first state occurs when a user is looking at the electronic device; if it is determined that the electronic device is in the first state, process the touch input as an intentional touch input; if it is determined that the electronic device is in the second state, process the touch input as an unintentional touch input; and in response to detecting a first change in the received data relating to device movement and the received data relating to device orientation, determine that the device has changed from the second state to the first state. 10. The non-transitory computer readable storage medium of claim 8 , wherein the data relating to device movement is received from an accelerometer.

19. A system, comprising: at least one processor and at least one associated memory; a query processor that executes on the at least one processor and receives the query, wherein the query applies one or more qualitative search terms to an attribute of data items in a set of data items; and while executing the query, the query processor processes each data item in the set of data items by, extracting an attribute value from the data item, using a concept-mapping to determine a compatibility index for the attribute value, wherein the concept-mapping associates each attribute value with a numerical compatibility index that indicates a compatibility between the attribute value and the one or more qualitative search terms, wherein the concept mapping is represented using an array containing X and Y coordinate pairs describing a shape of a concept-mapping function, wherein using the concept-mapping to determine the compatibility index includes using the attribute value to perform a lookup in the array to retrieve the compatibility index, and using the compatibility index as a factor in determining whether to include the data item in a set of query results; and wherein when the query includes multiple qualitative search terms, the query processor, determines compatibility indices for the multiple qualitative search terms for each data item, combines the determined compatibility indices into an aggregate compatibility index for each data item, wherein combining the determined compatibility indices involves one of computing an average for the multiple compatibility indices, and computing a weighted average for the multiple compatibility indices based on an ordering of associated qualitative search terms in the query, and determines whether to include each data item in the set of query results based on whether the aggregate compatibility index for the data item meets or exceeds a threshold.

19. A system, comprising: at least one processor and at least one associated memory; a query processor that executes on the at least one processor and receives the query, wherein the query applies one or more qualitative search terms to an attribute of data items in a set of data items; and while executing the query, the query processor processes each data item in the set of data items by, extracting an attribute value from the data item, using a concept-mapping to determine a compatibility index for the attribute value, wherein the concept-mapping associates each attribute value with a numerical compatibility index that indicates a compatibility between the attribute value and the one or more qualitative search terms, wherein the concept mapping is represented using an array containing X and Y coordinate pairs describing a shape of a concept-mapping function, wherein using the concept-mapping to determine the compatibility index includes using the attribute value to perform a lookup in the array to retrieve the compatibility index, and using the compatibility index as a factor in determining whether to include the data item in a set of query results; and wherein when the query includes multiple qualitative search terms, the query processor, determines compatibility indices for the multiple qualitative search terms for each data item, combines the determined compatibility indices into an aggregate compatibility index for each data item, wherein combining the determined compatibility indices involves one of computing an average for the multiple compatibility indices, and computing a weighted average for the multiple compatibility indices based on an ordering of associated qualitative search terms in the query, and determines whether to include each data item in the set of query results based on whether the aggregate compatibility index for the data item meets or exceeds a threshold. 21. The system of claim 19 , wherein the concept-mapping is a class-specific concept-mapping; and wherein prior to using the concept-mapping, the query processor is configured to select the concept-mapping based on class information obtained from one or more fields in the set of data items.

10. An information processing system for software debugging, the system comprising: data storage for storing inputs, the inputs comprising: an interface configured for accessing at least a portion of a program exhibiting faulty behavior, a failing input sequence from the at least a portion of the program, a behavioral model of the at least a portion of the program, and mutation operators; a processor configured for performing steps of: executing the failing input sequence stepwise in parallel on both the behavioral model and the at least a portion of the program; validating, after each execution, an expected behavior of the at least a portion of the program by executing test sequences constructed from the behavioral model, wherein the test sequences comprise model states and transitions; performing model mutation using mutation operators, for creating a hypothesis of faulty program behaviors; verifying each faulty program behavior in the hypothesis using the model mutators; and assigning a score to each faulty behavior, wherein the score comprises a percentage of executions of confirming sequences that match the faulty program behavior; and ranking the scores for producing a ranked list of diagnoses, wherein the diagnoses correspond to the mutation operators; and an input/output subsystem for interacting with a user of the system.

10. An information processing system for software debugging, the system comprising: data storage for storing inputs, the inputs comprising: an interface configured for accessing at least a portion of a program exhibiting faulty behavior, a failing input sequence from the at least a portion of the program, a behavioral model of the at least a portion of the program, and mutation operators; a processor configured for performing steps of: executing the failing input sequence stepwise in parallel on both the behavioral model and the at least a portion of the program; validating, after each execution, an expected behavior of the at least a portion of the program by executing test sequences constructed from the behavioral model, wherein the test sequences comprise model states and transitions; performing model mutation using mutation operators, for creating a hypothesis of faulty program behaviors; verifying each faulty program behavior in the hypothesis using the model mutators; and assigning a score to each faulty behavior, wherein the score comprises a percentage of executions of confirming sequences that match the faulty program behavior; and ranking the scores for producing a ranked list of diagnoses, wherein the diagnoses correspond to the mutation operators; and an input/output subsystem for interacting with a user of the system. 15. The system of claim 10 wherein the input/output subsystem comprises a network interface.

16. A system for analyzing electronic messages for phishing detection, comprising: one or more recipient's/recipient organization's email servers; one or more sender's email clients; one or more recipient's email clients; Intranet or Internet; a database; and one or more anti-phishing servers coupled to the database, and further the one or more anti-phishing servers coupled to the one or more recipient's/recipient's organization's email servers, the one or more sender's email clients, and/or the one or more recipient's email clients via Internet or Intranet, wherein the email client plugin module attaches to one or more recipient's email clients and wherein the anti-phishing server comprises: a processor; and a memory coupled to the processor, wherein the memory comprising a anti-phishing module, wherein the anti-phishing module comprises an import module, an analysis and data warehouse module, a mail handler module, an organizational analysis module, an outbound mail relay module, a configuration and management module that are configured to: receiving an email message from one or more sender/sender organizations by one or more recipients/recipient's organization via the mail handler module; obtaining email characteristics by parsing the received email message based on a set of predetermined email characteristics by the analysis and data warehouse module; comparing the email characteristics of the received email message with email characteristics associated with the recipient/recipient organization and/or that sender/sender organization by the analysis and data warehouse module; and declaring the received email message by the recipient/recipient organization as a phishing electronic message based on the outcome of the comparison by the analysis and data warehouse module; wherein the email characteristics are selected from the group consisting of network path used to reach a recipient/recipient organization, geography associated with IP address, email client software used by the sender/sender organization, email client software version used by the sender/sender organization, date, day of week, time, time period of the email, time zone of the sender/sender organization, presence and details of digital signatures in the email, meta data present in header portion of the email, character set used in content of the email, format of the email, email length and subject length, character case of the email, character case of the subject, style of introduction at the top of the email, style and content of the sender/sender organization's signature in the body of the email, other recipient/recipient organizations included in the email, to, and copy circulated (cc'd) email addresses, sender/sender organizations name, sender/sender organizations from and reply to email address, senders organization name, senders domain name, sender's organization's Domain Name Service (DNS) settings including SPF records, sender organization's mail server information, including server ip address, sender/sender organization server network path, sender/sender organization email server software and software version, DKIM signature, spam scoring from spam software, message ID, volume of email sent by the sender/sender organization, volume of email sent by sender's organization, volume of email received by the recipient, volume of email received by recipient organization, details associated with URLs or attachments in the email, whether the recipient/recipient organization has responded to this specific email, and number of interactions between sender and recipient associated with the email and the like; and wherein the configuration and management module allows an administrator to select desired email characteristics to be included in the set of characteristics used for comparing the characteristics of the received email message and to assign a weight of how much each characteristic should influence the likelihood that a new message is a phishing message.

16. A system for analyzing electronic messages for phishing detection, comprising: one or more recipient's/recipient organization's email servers; one or more sender's email clients; one or more recipient's email clients; Intranet or Internet; a database; and one or more anti-phishing servers coupled to the database, and further the one or more anti-phishing servers coupled to the one or more recipient's/recipient's organization's email servers, the one or more sender's email clients, and/or the one or more recipient's email clients via Internet or Intranet, wherein the email client plugin module attaches to one or more recipient's email clients and wherein the anti-phishing server comprises: a processor; and a memory coupled to the processor, wherein the memory comprising a anti-phishing module, wherein the anti-phishing module comprises an import module, an analysis and data warehouse module, a mail handler module, an organizational analysis module, an outbound mail relay module, a configuration and management module that are configured to: receiving an email message from one or more sender/sender organizations by one or more recipients/recipient's organization via the mail handler module; obtaining email characteristics by parsing the received email message based on a set of predetermined email characteristics by the analysis and data warehouse module; comparing the email characteristics of the received email message with email characteristics associated with the recipient/recipient organization and/or that sender/sender organization by the analysis and data warehouse module; and declaring the received email message by the recipient/recipient organization as a phishing electronic message based on the outcome of the comparison by the analysis and data warehouse module; wherein the email characteristics are selected from the group consisting of network path used to reach a recipient/recipient organization, geography associated with IP address, email client software used by the sender/sender organization, email client software version used by the sender/sender organization, date, day of week, time, time period of the email, time zone of the sender/sender organization, presence and details of digital signatures in the email, meta data present in header portion of the email, character set used in content of the email, format of the email, email length and subject length, character case of the email, character case of the subject, style of introduction at the top of the email, style and content of the sender/sender organization's signature in the body of the email, other recipient/recipient organizations included in the email, to, and copy circulated (cc'd) email addresses, sender/sender organizations name, sender/sender organizations from and reply to email address, senders organization name, senders domain name, sender's organization's Domain Name Service (DNS) settings including SPF records, sender organization's mail server information, including server ip address, sender/sender organization server network path, sender/sender organization email server software and software version, DKIM signature, spam scoring from spam software, message ID, volume of email sent by the sender/sender organization, volume of email sent by sender's organization, volume of email received by the recipient, volume of email received by recipient organization, details associated with URLs or attachments in the email, whether the recipient/recipient organization has responded to this specific email, and number of interactions between sender and recipient associated with the email and the like; and wherein the configuration and management module allows an administrator to select desired email characteristics to be included in the set of characteristics used for comparing the characteristics of the received email message and to assign a weight of how much each characteristic should influence the likelihood that a new message is a phishing message. 25. The system of claim 16 , wherein the organization analysis module monitors changing patterns of outbound emails to determine whether an email client has been compromised and the sender/sender organization is sending a phishing email.

14. One or more computer-readable non-transitory storage media embodying software that is operable when executed by one or more computing devices to: derive a concept matrix from a plurality of sample documents using singular value decomposition of a term-document matrix, the concept matrix identifying a latent pattern of word usage in the plurality of sample documents around a concept; derive concept terms by extracting significant terms from search text and inferring relevant terms therefrom using the concept matrix; and generate a first query for a first index of a first search engine and a second query for a second index of a second search engine, the first and second queries comprising at least one of the derived concept terms.

14. One or more computer-readable non-transitory storage media embodying software that is operable when executed by one or more computing devices to: derive a concept matrix from a plurality of sample documents using singular value decomposition of a term-document matrix, the concept matrix identifying a latent pattern of word usage in the plurality of sample documents around a concept; derive concept terms by extracting significant terms from search text and inferring relevant terms therefrom using the concept matrix; and generate a first query for a first index of a first search engine and a second query for a second index of a second search engine, the first and second queries comprising at least one of the derived concept terms. 17. The media of claim 14 , the software further operable when executed by the one or more computing devices to cluster concept terms in synonym groups with an operator therebetween.

8. A non-transitory machine-readable storage medium having stored thereon program code executable by a computer system, the program code comprising: code that causes the computer system to associate a first plurality of tags with documents in an enterprise; code that cause the computer system to create a tag for a document in the enterprise by: retrieving a first term associated with the document, wherein the first term corresponds to a location of the document or to metadata associated with the document; and applying a translation rule to convert the first term into a second term used in the tag; code that causes the computer system to associate a second plurality of tags with individuals in the enterprise; code that causes the computer system to receive a search query including a first tag; code that causes the computer system to determine a list of documents based on the search query, the list of documents including one or more documents in the enterprise that are associated with the first tag; code that causes the computer system to determine a list of experts based on the search query and the list of documents, the list of experts including one or more individuals in the enterprise that are associated with the first tag and one or more individuals in the enterprise that are knowledgeable about subject matter described in one or more documents in the list of documents; and code that causes the computer system to generate a user interface including the list of documents and the list of experts, wherein a rank value is determined for each document in the list of documents at least partially based on tags that define knowledge encapsulated by the content of each document, wherein the tags are linked with documents by content users, wherein each document in the list of documents is ordered according to its rank value, wherein one or more coefficients are calculated for the one or more documents using tags, wherein the rank value for the document is calculated using the one or more coefficients; wherein an expert rank value is determined for each expert in the list of experts at least partially based on tags applied to the experts by content users in the enterprise and one or more connections between the expert and other individuals in the enterprise, and wherein the experts in the list of experts are ordered according to their expert rank values.

8. A non-transitory machine-readable storage medium having stored thereon program code executable by a computer system, the program code comprising: code that causes the computer system to associate a first plurality of tags with documents in an enterprise; code that cause the computer system to create a tag for a document in the enterprise by: retrieving a first term associated with the document, wherein the first term corresponds to a location of the document or to metadata associated with the document; and applying a translation rule to convert the first term into a second term used in the tag; code that causes the computer system to associate a second plurality of tags with individuals in the enterprise; code that causes the computer system to receive a search query including a first tag; code that causes the computer system to determine a list of documents based on the search query, the list of documents including one or more documents in the enterprise that are associated with the first tag; code that causes the computer system to determine a list of experts based on the search query and the list of documents, the list of experts including one or more individuals in the enterprise that are associated with the first tag and one or more individuals in the enterprise that are knowledgeable about subject matter described in one or more documents in the list of documents; and code that causes the computer system to generate a user interface including the list of documents and the list of experts, wherein a rank value is determined for each document in the list of documents at least partially based on tags that define knowledge encapsulated by the content of each document, wherein the tags are linked with documents by content users, wherein each document in the list of documents is ordered according to its rank value, wherein one or more coefficients are calculated for the one or more documents using tags, wherein the rank value for the document is calculated using the one or more coefficients; wherein an expert rank value is determined for each expert in the list of experts at least partially based on tags applied to the experts by content users in the enterprise and one or more connections between the expert and other individuals in the enterprise, and wherein the experts in the list of experts are ordered according to their expert rank values. 14. The non-transitory machine-readable storage medium of claim 8 wherein the rank value for each expert in the list of experts is calculated based on one or more tags associated with the expert.

1. A contextual conversion platform for implementation on a computing device configured to process content of a target for use with a text-to-speech engine, said contextual conversion platform comprising: a processing module for generating a spoken content input in response to the target, the processing module comprising, a first filter module for identifying a context identifier in the target, and a second filter module for delineating portions of the target comprising one or more target terms; and a repository in communication with the processing module, the repository having entries that are organized according to a prioritized scheme, the entries comprising a substitution unit with an identified unit respecting the target terms in the delineated portions and a replacement unit corresponding to the identified unit, wherein the prioritized scheme assigns a position for the identified unit amongst a plurality of tables in the repository, wherein the position amongst the tables is assigned based on a specificity characteristic that describes a relative inclusivity of the substitution unit as compared to other substitution units in the plurality of tables, wherein the position defines a level of priority for the identified unit, wherein the level of priority changes as between the tables, and wherein the processing module replaces the identified unit in the delineated portions with the replacement unit in accordance with the level of priority to form the spoken content input.

1. A contextual conversion platform for implementation on a computing device configured to process content of a target for use with a text-to-speech engine, said contextual conversion platform comprising: a processing module for generating a spoken content input in response to the target, the processing module comprising, a first filter module for identifying a context identifier in the target, and a second filter module for delineating portions of the target comprising one or more target terms; and a repository in communication with the processing module, the repository having entries that are organized according to a prioritized scheme, the entries comprising a substitution unit with an identified unit respecting the target terms in the delineated portions and a replacement unit corresponding to the identified unit, wherein the prioritized scheme assigns a position for the identified unit amongst a plurality of tables in the repository, wherein the position amongst the tables is assigned based on a specificity characteristic that describes a relative inclusivity of the substitution unit as compared to other substitution units in the plurality of tables, wherein the position defines a level of priority for the identified unit, wherein the level of priority changes as between the tables, and wherein the processing module replaces the identified unit in the delineated portions with the replacement unit in accordance with the level of priority to form the spoken content input. 4. A contextual conversion platform according to claim 1 wherein the identified unit comprises one or more variants of the target terms.

1. A computer-implemented method for interpreting geographical search queries, comprising: receiving a geographical search query from a client computer; obtaining, by one or more processors, a plurality of geographical search queries, each of the plurality of geographical search queries having a plurality of terms; determining, by the one or more processors, a plurality of query templates based on the plurality of geographical search queries, each of the plurality of query templates including an arrangement of several geographic term types determined from the plurality of terms, wherein at least some of the plurality of query templates have different arrangements of geographic term types for different locales; determining, by the one or more processors, probability distributions for the query templates corresponding to different locales; and providing, by the one or more processors, the plurality of query templates as a plurality of interpretation candidates for interpreting the geographical search query using a probability distribution corresponding to a locale from which the geographical search query was received.

1. A computer-implemented method for interpreting geographical search queries, comprising: receiving a geographical search query from a client computer; obtaining, by one or more processors, a plurality of geographical search queries, each of the plurality of geographical search queries having a plurality of terms; determining, by the one or more processors, a plurality of query templates based on the plurality of geographical search queries, each of the plurality of query templates including an arrangement of several geographic term types determined from the plurality of terms, wherein at least some of the plurality of query templates have different arrangements of geographic term types for different locales; determining, by the one or more processors, probability distributions for the query templates corresponding to different locales; and providing, by the one or more processors, the plurality of query templates as a plurality of interpretation candidates for interpreting the geographical search query using a probability distribution corresponding to a locale from which the geographical search query was received. 5. The computer-implemented method of claim 1 , wherein the several geographic term types comprise two or more of: a number of an address, a route, a locality, a type of entity, a province, a state, and a country.

20. A computer-implemented system for automatically modifying text displayed on a graphical user interface by detecting offensive words in a string of words transmitted over a computer network, comprising: one or more data processors; a computer-readable memory encoded with a computer database instructions for commanding the data processors to execute steps including: receiving and storing in a computer database, using one or more processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving a string of words, using the one or more processors, wherein a candidate word is selected from the string of words; calculating, for each respective offensive word in the plurality of offensive words, using the one or more processors, a distance between the candidate word and the respective offensive word, the distance between the candidate word and the respective offensive word being a value on a scale having more than two possible values; calculating a plurality of offensiveness scores for the candidate word using the one or more processors, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein a particular offensiveness score is based on a product of two terms, a first of the two terms being based on the calculated distance between the candidate word and a particular offensive word, and a second of the two terms being based on the severity score of the particular offensive word; determining, using the one or more processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value; and when the candidate word is determined to be an offender word, adjusting the candidate word, as stored in a computer-readable memory, prior to display of the adjusted candidate word on a graphical user interface.

20. A computer-implemented system for automatically modifying text displayed on a graphical user interface by detecting offensive words in a string of words transmitted over a computer network, comprising: one or more data processors; a computer-readable memory encoded with a computer database instructions for commanding the data processors to execute steps including: receiving and storing in a computer database, using one or more processors, a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving a string of words, using the one or more processors, wherein a candidate word is selected from the string of words; calculating, for each respective offensive word in the plurality of offensive words, using the one or more processors, a distance between the candidate word and the respective offensive word, the distance between the candidate word and the respective offensive word being a value on a scale having more than two possible values; calculating a plurality of offensiveness scores for the candidate word using the one or more processors, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein a particular offensiveness score is based on a product of two terms, a first of the two terms being based on the calculated distance between the candidate word and a particular offensive word, and a second of the two terms being based on the severity score of the particular offensive word; determining, using the one or more processors, whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value; and when the candidate word is determined to be an offender word, adjusting the candidate word, as stored in a computer-readable memory, prior to display of the adjusted candidate word on a graphical user interface. 38. The system of claim 20 , wherein the highest offensiveness score is one of: a smallest value offensiveness score calculated in comparing each of the plurality of offensive words with the candidate word, or a largest value offensiveness score calculated in comparing each of the plurality of offensive words with the candidate word.

7. The system of claim 1 , wherein said indicating data comprises digital ink including a plurality of pen positions.

7. The system of claim 1 , wherein said indicating data comprises digital ink including a plurality of pen positions. 8. The system of claim 7 , wherein said computer system is configured for interpreting said digital ink as a handwritten annotation of said document.

5. A two-tier system for converting an audio input, comprising words made up of various sounds in a spoken sequence, into a visible form, comprising a sequence of corresponding phonemes, said system comprising: first means for breaking down the spoken sequence of sounds into syllabits, each syllabit comprising a group of classes of sounds; second means for grouping the syllabits into syllabit groups, each syllabit group defining corresponding possible words; third means for providing, for each of said possible words corresponding to each syllabit group, a respective skeletal sequence of phonemes comprising a corresponding grouping of phonemes; fourth means for determining, for each distinctive syllabit group, the phonemes occurring therein so as to develop an input sequence of phonemes for each syllabit group; fifth means for comparing the input sequence of phonemes for each syllabit group with the respective skeletal sequences of phonemes of each of the corresponding possible words so as to determine, with reference to the phonemes in each grouping of phonemes, which possible word has a skeletal sequence of phonemes which contains, in a given sequence, phonemes all of which are found, in said given sequence, in the input sequence of phonemes, thereby identifying each of said words of said audio input; and sixth means for providing said identified words of said audio input in said visible form.

5. A two-tier system for converting an audio input, comprising words made up of various sounds in a spoken sequence, into a visible form, comprising a sequence of corresponding phonemes, said system comprising: first means for breaking down the spoken sequence of sounds into syllabits, each syllabit comprising a group of classes of sounds; second means for grouping the syllabits into syllabit groups, each syllabit group defining corresponding possible words; third means for providing, for each of said possible words corresponding to each syllabit group, a respective skeletal sequence of phonemes comprising a corresponding grouping of phonemes; fourth means for determining, for each distinctive syllabit group, the phonemes occurring therein so as to develop an input sequence of phonemes for each syllabit group; fifth means for comparing the input sequence of phonemes for each syllabit group with the respective skeletal sequences of phonemes of each of the corresponding possible words so as to determine, with reference to the phonemes in each grouping of phonemes, which possible word has a skeletal sequence of phonemes which contains, in a given sequence, phonemes all of which are found, in said given sequence, in the input sequence of phonemes, thereby identifying each of said words of said audio input; and sixth means for providing said identified words of said audio input in said visible form. 6. The system of claim 5, wherein said first means comprises at least one transducer for receiving and processing said audio input, and issuing identification outputs, vowel identification circuitry for receiving and processing said audio input to determine which of said various sounds comprise vowels, and issuing corresponding vowel identification outputs, an input synchronizer for receiving and synchronizing said identification outputs of said at least one transducer and said vowel identification outputs of said vowel identification circuitry, and providing phoneme identification outputs, and a processor responsive to said phoneme identification outputs for breaking down the spoken sequence of sounds into syllabits.

1. A computer implemented method of automatically generating and storing a data structure for displaying a Unified Modeling Language (UML) model of behavior of a network of computing devices, said behavior dependent on location of said computing devices, comprising: creating a UML model comprising a plurality of line charts arranged in parallel to a time indicating axis; displaying said UML model in a graphical user interface (GUI) displayed on a screen; setting a plurality of values along each of said line charts; wherein each one of said values indicative of a computer action; adding to said displayed UML model a plurality of connectors, each one of said plurality of connectors connects a pair of line charts selected from said plurality of line charts, each one of said plurality of connectors is indicative of a message transmitted between two entities represented by respective said pair; wherein a distance between each two line charts of said plurality of line charts in said UML model maps a geographical distance therebetween; and wherein said distance and said value and said plurality of connectors are editable according to at least one user input indicative of a selection of an area of said displayed UML model.

1. A computer implemented method of automatically generating and storing a data structure for displaying a Unified Modeling Language (UML) model of behavior of a network of computing devices, said behavior dependent on location of said computing devices, comprising: creating a UML model comprising a plurality of line charts arranged in parallel to a time indicating axis; displaying said UML model in a graphical user interface (GUI) displayed on a screen; setting a plurality of values along each of said line charts; wherein each one of said values indicative of a computer action; adding to said displayed UML model a plurality of connectors, each one of said plurality of connectors connects a pair of line charts selected from said plurality of line charts, each one of said plurality of connectors is indicative of a message transmitted between two entities represented by respective said pair; wherein a distance between each two line charts of said plurality of line charts in said UML model maps a geographical distance therebetween; and wherein said distance and said value and said plurality of connectors are editable according to at least one user input indicative of a selection of an area of said displayed UML model. 2. The method of claim 1 , wherein each one of said plurality of line charts models said behavior of a corresponding computing device from said network of computing devices.

21. The computer-useable storage medium of claim 15 , wherein assigning a matching score comprises processing the search score based on a similarity definition for approximation.

21. The computer-useable storage medium of claim 15 , wherein assigning a matching score comprises processing the search score based on a similarity definition for approximation. 25. The computer-useable storage medium of claim 21 , wherein processing for approximation comprises normalizing a term frequency-inverse document frequency score based on a frequency of the problem description information of the new problem being included in problem description information of previously diagnosed problem sets.