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13. A monitoring terminal, comprising: an processor, a transmitter, a receiver, and a discovery unit; wherein the processor is configured to acquire a code word broadcast by a first terminal at a 3GPP network layer in a home public land mobile network (HPLMN), wherein the code word is allocated to the first terminal by a first proximity service (ProSe) entity, and the first ProSe entity is a ProSe entity in the HPLMN; the transmitter is configured to send a first message to a receiving ProSe entity at the 3GPP network layer in the HPLMN when the code word matches a prestored code word, wherein the first message carries the code word and a first application identity, the first application identity is an application identity of a first application, and the receiving ProSe entity is a ProSe entity in an HPLMN of the monitoring terminal; the receiver is configured to receive a second message sent by the receiving ProSe entity at the 3GPP network layer in the HPLMN, wherein the second message carries a application user identity, the application user identity is an application user identity that is allocated to a first application user by a first application server, the first application user is a user of the first application of the first terminal, and the first application server is an application server of the first application; and the discovery unit is configured to discover the first application user according to the application user identity at the 3GPP network layer in the HPLMN, wherein the transmitter is further configured to: when the code word matches the prestored code word, and before the processor acquires the code word broadcast by the first terminal, send a third message to the receiving ProSe entity, wherein the third message carries first information, a fourth identity, and the first application identity, wherein the first information comprises a third identity or a sixth identity, the third identity is a temporary terminal identity that is allocated to the monitoring terminal by the receiving ProSe entity, the sixth identity is a terminal identity of the monitoring terminal, the fourth identity is an application user identity that is allocated to a second application user by the first application server, and the second application user is a user of the first application of the monitoring terminal; and wherein the receiver is further configured to receive a fourth message sent by the receiving ProSe entity, wherein the fourth message carries the code word.

13. A monitoring terminal, comprising: an processor, a transmitter, a receiver, and a discovery unit; wherein the processor is configured to acquire a code word broadcast by a first terminal at a 3GPP network layer in a home public land mobile network (HPLMN), wherein the code word is allocated to the first terminal by a first proximity service (ProSe) entity, and the first ProSe entity is a ProSe entity in the HPLMN; the transmitter is configured to send a first message to a receiving ProSe entity at the 3GPP network layer in the HPLMN when the code word matches a prestored code word, wherein the first message carries the code word and a first application identity, the first application identity is an application identity of a first application, and the receiving ProSe entity is a ProSe entity in an HPLMN of the monitoring terminal; the receiver is configured to receive a second message sent by the receiving ProSe entity at the 3GPP network layer in the HPLMN, wherein the second message carries a application user identity, the application user identity is an application user identity that is allocated to a first application user by a first application server, the first application user is a user of the first application of the first terminal, and the first application server is an application server of the first application; and the discovery unit is configured to discover the first application user according to the application user identity at the 3GPP network layer in the HPLMN, wherein the transmitter is further configured to: when the code word matches the prestored code word, and before the processor acquires the code word broadcast by the first terminal, send a third message to the receiving ProSe entity, wherein the third message carries first information, a fourth identity, and the first application identity, wherein the first information comprises a third identity or a sixth identity, the third identity is a temporary terminal identity that is allocated to the monitoring terminal by the receiving ProSe entity, the sixth identity is a terminal identity of the monitoring terminal, the fourth identity is an application user identity that is allocated to a second application user by the first application server, and the second application user is a user of the first application of the monitoring terminal; and wherein the receiver is further configured to receive a fourth message sent by the receiving ProSe entity, wherein the fourth message carries the code word. 14. The monitoring terminal according to claim 13 , wherein: the transmitter is further configured to send a third message to the receiving ProSe entity when the code word matches the prestored code word and before the processor acquires the code word broadcast by the first terminal, wherein the third message carries a third identity and the first application identity, and the third identity is a temporary terminal identity that is allocated to the monitoring terminal by the receiving ProSe entity; and the receiver is further configured to receive a fourth message sent by the receiving ProSe entity, wherein the fourth message carries the code word.

1. A method comprising: using a computer for receiving design data related to layout of an integrated circuit (IC); extracting information from the design data; performing analysis on the extracted information; enabling design-for-manufacturing (DFM) and design-enabled-manufacturing (DEM) aware manufacturing (collectively DFM-DEM) applications using information stored in a knowledge database, wherein the knowledge database stores information related to DFM and DEM for facilitating DFM-DEM aware manufacturing; and updating the knowledge database with new information learned from at least the extracted information and the analysis.

1. A method comprising: using a computer for receiving design data related to layout of an integrated circuit (IC); extracting information from the design data; performing analysis on the extracted information; enabling design-for-manufacturing (DFM) and design-enabled-manufacturing (DEM) aware manufacturing (collectively DFM-DEM) applications using information stored in a knowledge database, wherein the knowledge database stores information related to DFM and DEM for facilitating DFM-DEM aware manufacturing; and updating the knowledge database with new information learned from at least the extracted information and the analysis. 14. The method of claim 1 , further comprising: generating a report on one or more results from the extracting.

1. A method for establishing paraphrasing data for a machine translation system comprising: selecting a paraphrasing target sentence through application of an object language model to a translated sentence that is obtained by machine-translating a source language sentence; extracting, from a corpus DB for the source language, paraphrasing candidates that can be paraphrased with the selected paraphrasing target sentence; performing machine translation with respect to the extracted paraphrasing candidates; selecting a final paraphrasing candidate from the extracted paraphrasing candidates by applying the object language model to a result of the machine translation with respect to the extracted paraphrasing candidates; and confirming a paraphrasing relationship of the paraphrasing target sentence and the selected final paraphrasing candidate as paraphrasing lexical patterns using a bilingual corpus and storing the paraphrasing lexical patterns in a paraphrasing DB.

1. A method for establishing paraphrasing data for a machine translation system comprising: selecting a paraphrasing target sentence through application of an object language model to a translated sentence that is obtained by machine-translating a source language sentence; extracting, from a corpus DB for the source language, paraphrasing candidates that can be paraphrased with the selected paraphrasing target sentence; performing machine translation with respect to the extracted paraphrasing candidates; selecting a final paraphrasing candidate from the extracted paraphrasing candidates by applying the object language model to a result of the machine translation with respect to the extracted paraphrasing candidates; and confirming a paraphrasing relationship of the paraphrasing target sentence and the selected final paraphrasing candidate as paraphrasing lexical patterns using a bilingual corpus and storing the paraphrasing lexical patterns in a paraphrasing DB. 8. The method for establishing paraphrasing data for a machine translation system of claim 1 , wherein in the selecting the final paraphrasing candidate, the object language model is an n-gram based object language mode.

1. A system for build script generation for software projects and applications, comprising: a computer server; a developer interface, deployed on the computer server, that allows a software developer to specify a project or application input file as an input into the system; a plurality of script generators, deployed on the computer server, wherein at least one of the plurality of script generators is applied to the input file to generate an interim build script for the project or application; a plurality of generator customizers, deployed on the computer server, wherein at least one of the plurality of generator customizers modifies the interim build script; and an output interface, deployed on the computer server, that outputs the interim build script as a build script, as modified by the generator customizers, for subsequent use in building the project or application; wherein each of the plurality of script generators directly reads the input file to independently determine its applicability to the input file, and if the script generator is applicable the script generator then assists in generating the interim build script, otherwise the script generator abstains from the script generation, wherein the determining applicability of the script generator does not involve invoking the script generator; and wherein the applicability of each of the script generators is first determined, and the determined applicable script generators are invoked to assist in generating the interim build script.

1. A system for build script generation for software projects and applications, comprising: a computer server; a developer interface, deployed on the computer server, that allows a software developer to specify a project or application input file as an input into the system; a plurality of script generators, deployed on the computer server, wherein at least one of the plurality of script generators is applied to the input file to generate an interim build script for the project or application; a plurality of generator customizers, deployed on the computer server, wherein at least one of the plurality of generator customizers modifies the interim build script; and an output interface, deployed on the computer server, that outputs the interim build script as a build script, as modified by the generator customizers, for subsequent use in building the project or application; wherein each of the plurality of script generators directly reads the input file to independently determine its applicability to the input file, and if the script generator is applicable the script generator then assists in generating the interim build script, otherwise the script generator abstains from the script generation, wherein the determining applicability of the script generator does not involve invoking the script generator; and wherein the applicability of each of the script generators is first determined, and the determined applicable script generators are invoked to assist in generating the interim build script. 2. The system of claim 1 , wherein the developer interface is a command line interface.

1. A method for expanding a size of a field associated with a plurality of variables present in a source code of at least one software application, the method comprising processor implemented steps of: receiving said source code in at least one source language; parsing said source code to generate an abstract syntax tree (AST), wherein the AST comprises relation amongst the plurality of variables, and wherein the relation is stored in a repository; identifying a first set of seed variables from the plurality of variables, wherein the first set of seed variables is identified based on, a) matching of a pattern pertaining to the field received from a user with patterns of fields associated with the plurality of variables, or b) one or more files, one or more database fields, or one or more screen fields; performing multi-level impact analysis on the first set of seed variables in order to identify a second set of seed variables, wherein performing the multi-level impact analysis further comprises excluding one or more seed variables from the second set of seed variables, wherein the one or more seed variables indicative of non-impacted variables, and wherein the exclusion of the non-impacted variables facilitates in reduction of the false positives; generating an analysis report comprising the first set of seed variables and the second set of seed variables, wherein the analysis report facilitates to further exclude at least one seed variable from the first set of seed variables or the second set of seed variables in order to derive a set of impacted variables, thereby further facilitating to reduce the false positives; and expanding the size of a field associated with each seed variable of the set of impacted variables.

1. A method for expanding a size of a field associated with a plurality of variables present in a source code of at least one software application, the method comprising processor implemented steps of: receiving said source code in at least one source language; parsing said source code to generate an abstract syntax tree (AST), wherein the AST comprises relation amongst the plurality of variables, and wherein the relation is stored in a repository; identifying a first set of seed variables from the plurality of variables, wherein the first set of seed variables is identified based on, a) matching of a pattern pertaining to the field received from a user with patterns of fields associated with the plurality of variables, or b) one or more files, one or more database fields, or one or more screen fields; performing multi-level impact analysis on the first set of seed variables in order to identify a second set of seed variables, wherein performing the multi-level impact analysis further comprises excluding one or more seed variables from the second set of seed variables, wherein the one or more seed variables indicative of non-impacted variables, and wherein the exclusion of the non-impacted variables facilitates in reduction of the false positives; generating an analysis report comprising the first set of seed variables and the second set of seed variables, wherein the analysis report facilitates to further exclude at least one seed variable from the first set of seed variables or the second set of seed variables in order to derive a set of impacted variables, thereby further facilitating to reduce the false positives; and expanding the size of a field associated with each seed variable of the set of impacted variables. 10. The method of claim 1 , wherein the final set of seed variables are expanded based on a specified target data type, length, size and memory allocated.

1. A digital storage medium having an index data structure for one or more data objects encoded thereon, the index data structure comprising: a) a plurality of index keys for uniquely identifying potential context nodes in a data object, each index key being associated with one or more potential context nodes, the index key having a label that provides semantic content to a user; and b) one or more routing tables associated with each index key, the one or more routing tables comprising at least 5 path references selected from a preceding peer-to-peer graph, a following peer-to-peer graph, an ancestor peer-to-peer graph, and descendent peer-to-peer graph.

1. A digital storage medium having an index data structure for one or more data objects encoded thereon, the index data structure comprising: a) a plurality of index keys for uniquely identifying potential context nodes in a data object, each index key being associated with one or more potential context nodes, the index key having a label that provides semantic content to a user; and b) one or more routing tables associated with each index key, the one or more routing tables comprising at least 5 path references selected from a preceding peer-to-peer graph, a following peer-to-peer graph, an ancestor peer-to-peer graph, and descendent peer-to-peer graph. 5. The digital storage medium of claim 1 wherein the one or more routing tables comprising at least 10 path references.

12. The computer program product in accordance with claim 1 , wherein the model element of the second model element type includes one or more property fields, wherein the computer-executable instructions are further structured such that the computing system further performs an act of automatically populating at least one of the one or more property fields based on property values of the model element of the first model element type.

12. The computer program product in accordance with claim 1 , wherein the model element of the second model element type includes one or more property fields, wherein the computer-executable instructions are further structured such that the computing system further performs an act of automatically populating at least one of the one or more property fields based on property values of the model element of the first model element type. 14. The computer program product in accordance with claim 12 , wherein the act of automatically populating comprises the following: an act of access a property value of the model element of the first model element type; an act of transforming the property value of the model element of the first model element type into a different property value; and an act of providing the transformed property value into a property field of the Model element of the second model element type.

35. The bowling system of claim 34 , wherein the interactive display is a plurality of web pages including at least one of: a home page, a theme page, a party experience page, a party package page, an explanation page and a registration page.

35. The bowling system of claim 34 , wherein the interactive display is a plurality of web pages including at least one of: a home page, a theme page, a party experience page, a party package page, an explanation page and a registration page. 40. The bowling system of claim 35 , wherein the explanation page explains concepts behind the party kit using the one or more animated characters displayed by the automated bowling scoring system.

1. A computer-implemented method for eliciting command variants from crowd users to train a natural language processing system, the method being implemented in a computer system having one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, cause the computer system to perform the method, the method comprising: identifying a computer recognized command to be processed by a computer; generating at least a first task, wherein the first task includes command creation instructions that prompt a user to input a variant of the computer recognized command; transmitting the first task to a plurality of users via a network; receiving, from at least a first user among the plurality of users, a first user-defined variant of the computer recognized command; receiving, from at least a second user among the plurality of users, a second user-defined variant of the computer recognized command; storing the first user-defined variant and the second user-defined variant in association with the computer recognized command; generating at least a second task, wherein the second task includes command review instructions that prompt a given user to verify the first user-defined variant; transmitting the second task to a second plurality of users via the network; receiving, from at least a second user among the second plurality of users, a verification of the first user-defined variant; and training the natural language processing system to recognize variants of the computer recognized command based on the verified first user-defined variant and the second user-defined variant.

1. A computer-implemented method for eliciting command variants from crowd users to train a natural language processing system, the method being implemented in a computer system having one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, cause the computer system to perform the method, the method comprising: identifying a computer recognized command to be processed by a computer; generating at least a first task, wherein the first task includes command creation instructions that prompt a user to input a variant of the computer recognized command; transmitting the first task to a plurality of users via a network; receiving, from at least a first user among the plurality of users, a first user-defined variant of the computer recognized command; receiving, from at least a second user among the plurality of users, a second user-defined variant of the computer recognized command; storing the first user-defined variant and the second user-defined variant in association with the computer recognized command; generating at least a second task, wherein the second task includes command review instructions that prompt a given user to verify the first user-defined variant; transmitting the second task to a second plurality of users via the network; receiving, from at least a second user among the second plurality of users, a verification of the first user-defined variant; and training the natural language processing system to recognize variants of the computer recognized command based on the verified first user-defined variant and the second user-defined variant. 3. The method of claim 1 , wherein the first task configures the first application to periodically display a non-machine readable caption on the first application.

1. A system comprising: a computer connected to a computer readable memory, a non-transitory computer readable storage medium, and to the Internet; first program instructions for receiving a search term; second program instructions for receiving a designation of a character in the search term as a set character; third program instructions for automatically designating, responsive to receiving the designation, all other characters in the search term as a plurality of companion characters so that the set character will be considered only for a context that the set character provides to the plurality of companion characters and will not itself be translated; fourth program instructions for searching a translation dictionary for a plurality of translation results in accordance with the context that the set character provides to the plurality of companion characters; and fifth program instructions for displaying the plurality of translation results in a display connected to the computer; wherein the first through the fifth program instructions are stored in the non-transitory computer readable storage medium for running via the computer readable memory.

1. A system comprising: a computer connected to a computer readable memory, a non-transitory computer readable storage medium, and to the Internet; first program instructions for receiving a search term; second program instructions for receiving a designation of a character in the search term as a set character; third program instructions for automatically designating, responsive to receiving the designation, all other characters in the search term as a plurality of companion characters so that the set character will be considered only for a context that the set character provides to the plurality of companion characters and will not itself be translated; fourth program instructions for searching a translation dictionary for a plurality of translation results in accordance with the context that the set character provides to the plurality of companion characters; and fifth program instructions for displaying the plurality of translation results in a display connected to the computer; wherein the first through the fifth program instructions are stored in the non-transitory computer readable storage medium for running via the computer readable memory. 13. The system of claim 1 wherein the first through the eighth program instructions normalize a plurality of weights across a plurality of search engines.

1. A computer-implemented method executed using one or more processors, the method comprising: receiving a search query from a user, receiving search results responsive to the search query; providing search results for display to the user; receiving one or more user interactions associated with the search results; generating a search interaction score based on the one or more user interactions; determining that the search interaction score exceeds a threshold search interaction score; receiving a reminder event relating to the search query, wherein the reminder event is prompted by an occurrence other than re-submission of the search query by the user; and in response to determining that the search interaction score exceeds the threshold search interaction score and the reminder event, providing a notification to the user relating to the search query, wherein the notification invites the user to re-engage the search query and the search results, wherein the one or more user interactions associated with the search results are selected from a group including a selection of, an endorsement of, a sharing of, and a comment on an entry in the search results, and wherein the occurrence prompting the reminder event corresponds to one or more subsequent search queries, related to or matching the search query, reaching a threshold level of popularity.

1. A computer-implemented method executed using one or more processors, the method comprising: receiving a search query from a user, receiving search results responsive to the search query; providing search results for display to the user; receiving one or more user interactions associated with the search results; generating a search interaction score based on the one or more user interactions; determining that the search interaction score exceeds a threshold search interaction score; receiving a reminder event relating to the search query, wherein the reminder event is prompted by an occurrence other than re-submission of the search query by the user; and in response to determining that the search interaction score exceeds the threshold search interaction score and the reminder event, providing a notification to the user relating to the search query, wherein the notification invites the user to re-engage the search query and the search results, wherein the one or more user interactions associated with the search results are selected from a group including a selection of, an endorsement of, a sharing of, and a comment on an entry in the search results, and wherein the occurrence prompting the reminder event corresponds to one or more subsequent search queries, related to or matching the search query, reaching a threshold level of popularity. 8. The method of claim 1 , wherein the threshold search interaction score is unique to the user.

30. A non-transitory computer-readable medium having computer executable instructions stored thereon that, when executed, cause a processor to perform a method comprising: a) generating a capability domain, by the processor, having a plurality of entity roles within a predetermined degree of separation, the predetermined degree of separation being dependent on an activity trust level of a relationship a first entity is seeking to establish with the second entity; b) generating an activity trust domain, by the processor, having a plurality of levels of trust; and c) generating a respective business process of a plurality of business processes being associated with one or more combinations of a respective role of the plurality of roles and a respective trust level of the plurality of trust levels, wherein the data structure is indexed by the capability domain and the activity trust domain to obtain a corresponding business process.

30. A non-transitory computer-readable medium having computer executable instructions stored thereon that, when executed, cause a processor to perform a method comprising: a) generating a capability domain, by the processor, having a plurality of entity roles within a predetermined degree of separation, the predetermined degree of separation being dependent on an activity trust level of a relationship a first entity is seeking to establish with the second entity; b) generating an activity trust domain, by the processor, having a plurality of levels of trust; and c) generating a respective business process of a plurality of business processes being associated with one or more combinations of a respective role of the plurality of roles and a respective trust level of the plurality of trust levels, wherein the data structure is indexed by the capability domain and the activity trust domain to obtain a corresponding business process. 32. The computer-readable medium having stored thereon a data structure according to claim 30 , wherein each respective level of trust in the plurality of levels of trust defines a respective degree of trust between one entity and another entity.

9. A system for conducting matching transactions in accordance with claim 8 , said authentication system being further configured to: update the genuine matching score distribution with at least one genuine matching score generated during a matching transaction; and update the imposter matching score distribution with at least one imposter matching score generated during the matching transaction.

9. A system for conducting matching transactions in accordance with claim 8 , said authentication system being further configured to: update the genuine matching score distribution with at least one genuine matching score generated during a matching transaction; and update the imposter matching score distribution with at least one imposter matching score generated during the matching transaction. 10. A system for conducting matching transactions in accordance with claim 9 , said authentication system being further configured to calculate an equal error rate when the maximum genuine matching score is at least equal to the minimum imposter matching score.

1. A method performed by one or more computers, the method comprising: receiving a first search query from a user device, wherein the first search query has been determined to relate to a first entity of a first entity type, and wherein a plurality of second entities of a second entity type have a predetermined relationship with the first entity; determining a respective ranking score for each second entity of the plurality of second entities of the second entity type, the determining comprising: determining a frequency of occurrence of authoritative resources for the second entity of the second entity type in search results for previously submitted search queries, each authoritative resource for the second entity being a resource whose occurrence in the search results for the previously submitted search queries has been determined to be an indicator that the received search query is directed to the second entity; and determining the respective ranking score for the second entity based at least in part on the frequency; ordering the second entities of the second entity type according to the ranking scores; receiving search results for the first search query provided by a search engine, wherein each of the search results identifies a respective resource; and transmitting the search results and information identifying each of the plurality of second entities of the second entity type to the user device as part of a response to the first search query, wherein, when presented on the user device, the information identifies each of the plurality of second entities in an order that matches the ordering.

1. A method performed by one or more computers, the method comprising: receiving a first search query from a user device, wherein the first search query has been determined to relate to a first entity of a first entity type, and wherein a plurality of second entities of a second entity type have a predetermined relationship with the first entity; determining a respective ranking score for each second entity of the plurality of second entities of the second entity type, the determining comprising: determining a frequency of occurrence of authoritative resources for the second entity of the second entity type in search results for previously submitted search queries, each authoritative resource for the second entity being a resource whose occurrence in the search results for the previously submitted search queries has been determined to be an indicator that the received search query is directed to the second entity; and determining the respective ranking score for the second entity based at least in part on the frequency; ordering the second entities of the second entity type according to the ranking scores; receiving search results for the first search query provided by a search engine, wherein each of the search results identifies a respective resource; and transmitting the search results and information identifying each of the plurality of second entities of the second entity type to the user device as part of a response to the first search query, wherein, when presented on the user device, the information identifies each of the plurality of second entities in an order that matches the ordering. 5. The method of claim 1 , further comprising: accessing data that indicates that two or more of the second entities of the second entity type are members of a set of entities that has a specified order; and adjusting the ordering of the two or more second entities of the second entity type to match the specified order.

10. The electronic device of claim 9 , wherein the first source is a second sandbox.

10. The electronic device of claim 9 , wherein the first source is a second sandbox. 16. The electronic device of claim 10 , wherein obtaining the second search results comprises obtaining search results from an application associated with the first lockable sandbox.

13. A computer program product comprising a non-transitory computer readable storage medium storing computer readable program code, which when executed by a computer, causes the computer to: integrate a set of standardization functions into database engines to allow access to standardization of data via database queries executed in the database engines against databases; store a plurality of standardization tables; with an extract module, extract data before a transform portion of an extract, transform, and load process by issuing a first database query from the database queries to a first database engine of the database engines and a second database query from the database queries to a second database engine of the database engines, wherein the first database query includes a first standardization function, and wherein the second database query includes a second standardization function; with the first database engine, determine a first context included in the first standardization function; and invoke the first standardization function within the first database engine to convert a first data value having the first context using a first standard value and a first standardization table from the plurality of standardization tables that includes a context column for the first context; with the second database engine, determining determine a second context using metadata values by: identifying the metadata values of a column name and a database schema; mapping the metadata values to the second context using a lookup table; and identifying a second standardization table from the plurality of standardization tables based on the second context, wherein the second standardization table does not include any context column; and invoke the second standardization function within the second database engine to convert a second data value having the second context using a second standard value and the second standardization table; and provide cleansed data in the databases before another transform portion of another extract, transform, and load process by storing the converted first data value and the converted second data value.

13. A computer program product comprising a non-transitory computer readable storage medium storing computer readable program code, which when executed by a computer, causes the computer to: integrate a set of standardization functions into database engines to allow access to standardization of data via database queries executed in the database engines against databases; store a plurality of standardization tables; with an extract module, extract data before a transform portion of an extract, transform, and load process by issuing a first database query from the database queries to a first database engine of the database engines and a second database query from the database queries to a second database engine of the database engines, wherein the first database query includes a first standardization function, and wherein the second database query includes a second standardization function; with the first database engine, determine a first context included in the first standardization function; and invoke the first standardization function within the first database engine to convert a first data value having the first context using a first standard value and a first standardization table from the plurality of standardization tables that includes a context column for the first context; with the second database engine, determining determine a second context using metadata values by: identifying the metadata values of a column name and a database schema; mapping the metadata values to the second context using a lookup table; and identifying a second standardization table from the plurality of standardization tables based on the second context, wherein the second standardization table does not include any context column; and invoke the second standardization function within the second database engine to convert a second data value having the second context using a second standard value and the second standardization table; and provide cleansed data in the databases before another transform portion of another extract, transform, and load process by storing the converted first data value and the converted second data value. 16. The computer program product of claim 13 , wherein, when determining the second context, the computer readable program code further causes the computer to: access the metadata values describing the second data value; and determine the second context with the metadata values.

15. A computer-implemented method for performing a location search, comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a location search query; identifying geographical features that satisfy the location search query; ranking the identified geographical features in accordance with a score that is based, at least in part, on proximity of the geographical features to a geographical viewport region of a client system, to produce a set of ranked geographical features; and providing results, in accordance with the ranked geographical features, that identify at least one geographic feature corresponding to the at least one of the ranked geographical features.

15. A computer-implemented method for performing a location search, comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a location search query; identifying geographical features that satisfy the location search query; ranking the identified geographical features in accordance with a score that is based, at least in part, on proximity of the geographical features to a geographical viewport region of a client system, to produce a set of ranked geographical features; and providing results, in accordance with the ranked geographical features, that identify at least one geographic feature corresponding to the at least one of the ranked geographical features. 18. The method of claim 15 , wherein the geographical viewport region comprises a circular geographical region that encompasses a rectangular geographical region displayed on the client system.

12. One or more devices, comprising: means for identifying a group of comments; means for determining that a first comment, of the group of comments, does not include a plurality of links pointing to a plurality of different documents; means for removing the first comment from the group of comments based on the first comment not including the plurality of links pointing to the plurality of different documents; means for identifying a second comment that includes: a first link pointing to a first document, and a second link pointing to a second document that is different than the first document; means for identifying one or more factors associated with the first link, the one or more factors associated with the first link including at least one of: a click through rate associated with the first link, explicit user feedback regarding the first link, a length of an address associated with the first link, a measure of popularity associated with the first document, or a comparison of a topic associated with the second comment and a topic associated with the first document; means for identifying one or more factors associated with the second link, the one or more factors associated with the second link including at least one of: a click through rate associated with the second link, explicit user feedback regarding the second link, a length of an address associated with the second link, a measure of popularity associated with the second document, or a comparison of the topic associated with the second comment and a topic associated with the second document; means for assigning a score to the first link based on the one or more factors associated with the first link; means for assigning a score to the second link based on the one or more factors associated with the second link; means for associating the second comment with one of the first document or the second document based on the score assigned to the first link and the score assigned to the second link, the second comment being associated with the first document when the score assigned to the first link is greater than the score assigned to the second link, and the second comment being associated with the second document when the score assigned to the second link is greater than the score assigned to the first link; and means for providing information regarding the second comment to a client device for presentation in connection with presentation of the first document or the second document, the information regarding the second comment being provided in connection with the first document when the second comment is associated with the first document, and the information regarding the second comment being provided in connection with the second document when the second comment is associated with the second document.

12. One or more devices, comprising: means for identifying a group of comments; means for determining that a first comment, of the group of comments, does not include a plurality of links pointing to a plurality of different documents; means for removing the first comment from the group of comments based on the first comment not including the plurality of links pointing to the plurality of different documents; means for identifying a second comment that includes: a first link pointing to a first document, and a second link pointing to a second document that is different than the first document; means for identifying one or more factors associated with the first link, the one or more factors associated with the first link including at least one of: a click through rate associated with the first link, explicit user feedback regarding the first link, a length of an address associated with the first link, a measure of popularity associated with the first document, or a comparison of a topic associated with the second comment and a topic associated with the first document; means for identifying one or more factors associated with the second link, the one or more factors associated with the second link including at least one of: a click through rate associated with the second link, explicit user feedback regarding the second link, a length of an address associated with the second link, a measure of popularity associated with the second document, or a comparison of the topic associated with the second comment and a topic associated with the second document; means for assigning a score to the first link based on the one or more factors associated with the first link; means for assigning a score to the second link based on the one or more factors associated with the second link; means for associating the second comment with one of the first document or the second document based on the score assigned to the first link and the score assigned to the second link, the second comment being associated with the first document when the score assigned to the first link is greater than the score assigned to the second link, and the second comment being associated with the second document when the score assigned to the second link is greater than the score assigned to the first link; and means for providing information regarding the second comment to a client device for presentation in connection with presentation of the first document or the second document, the information regarding the second comment being provided in connection with the first document when the second comment is associated with the first document, and the information regarding the second comment being provided in connection with the second document when the second comment is associated with the second document. 14. The one or more devices of claim 12 , where the second comment is associated with the first document, the method further comprising: means for identifying a plurality of comments associated with the first document, where the second comment is one of the plurality of comments; and means for selecting one or more of the plurality of comments to present in connection with the presentation of the first document.

1. A machine implemented method, comprising; accessing narrative data, the narrative data comprising a plurality of sequence of words, each sequence of words including a verb and being arranged in a sentence pattern; reading a semiotic square function data table for each verb in the sequence of words, each semiotic square function data table classifies at least one verb in each sentence pattern as a functional type and includes one or more words in a semiotic square relationship to the verb classified, the functional type applying a symmetrical relationship between a first actor and a second actor in the narrative data; accessing a set of event rules, each event rule containing an association of a verb and functional type to an event record; parsing each sentence which includes a verb matching a functional type to match sentence subjects and objects to an event rule selected from the set of event rules; storing data from each subject and object in a sentence as an event record; and displaying an analysis of the narrative data on a user perceptible device to a user relative to a common story theme based on a sequence of event records.

1. A machine implemented method, comprising; accessing narrative data, the narrative data comprising a plurality of sequence of words, each sequence of words including a verb and being arranged in a sentence pattern; reading a semiotic square function data table for each verb in the sequence of words, each semiotic square function data table classifies at least one verb in each sentence pattern as a functional type and includes one or more words in a semiotic square relationship to the verb classified, the functional type applying a symmetrical relationship between a first actor and a second actor in the narrative data; accessing a set of event rules, each event rule containing an association of a verb and functional type to an event record; parsing each sentence which includes a verb matching a functional type to match sentence subjects and objects to an event rule selected from the set of event rules; storing data from each subject and object in a sentence as an event record; and displaying an analysis of the narrative data on a user perceptible device to a user relative to a common story theme based on a sequence of event records. 2. The machine implemented method of claim 1 , wherein the semiotic square function data table includes a MAKE function type, a TRANSFORMATION type, a TRANSFER type, and a TRANSACTION type.

1. A method for interpreting a user request, the method comprising: receiving, by a processor, an initial user request from a user; interpreting, by the processor, the initial user request, where the processor fails to fully interpret the initial user request due to a presence of at least one un-interpretable expression in the initial user request wherein the interpreting comprises: identifying an abstracted version of a previous user request that matches the initial user request, wherein at least one attribute value in the abstracted version of the previous request has been replaced with a variable; and replacing the variable with an attribute defined in the initial user request to produce a modified version of the initial user request; and generating, by the processor, at least one alternative request in a context of the initial user request, the at least one alternative request being phrased in a manner that the processor can successfully interpret and that satisfies a combination of semantic constraints, syntactic constraints, and contextual constraints relating to the initial user request, wherein the generating comprises: retrieving a modified version of the previous user request that is stored with the abstracted version of the previous user request; and adapting the modified version of the initial user request in accordance with the modified version of the previous user request to produce the at least one alternative request, where the modified version of the previous user request has been fully interpreted by the processor.

1. A method for interpreting a user request, the method comprising: receiving, by a processor, an initial user request from a user; interpreting, by the processor, the initial user request, where the processor fails to fully interpret the initial user request due to a presence of at least one un-interpretable expression in the initial user request wherein the interpreting comprises: identifying an abstracted version of a previous user request that matches the initial user request, wherein at least one attribute value in the abstracted version of the previous request has been replaced with a variable; and replacing the variable with an attribute defined in the initial user request to produce a modified version of the initial user request; and generating, by the processor, at least one alternative request in a context of the initial user request, the at least one alternative request being phrased in a manner that the processor can successfully interpret and that satisfies a combination of semantic constraints, syntactic constraints, and contextual constraints relating to the initial user request, wherein the generating comprises: retrieving a modified version of the previous user request that is stored with the abstracted version of the previous user request; and adapting the modified version of the initial user request in accordance with the modified version of the previous user request to produce the at least one alternative request, where the modified version of the previous user request has been fully interpreted by the processor. 14. The method of claim 1 , wherein the semantic constraints, syntactic constraints, and contextual constraints are each applied to the initial user request in its entirety.

1. A system comprising: one or more computers configured to perform operations comprising: receiving a plurality of test queries; generating, for each test query, a first group of resources corresponding to a first automated resource selection process and a second group of resources corresponding to a second automated resource selection process, the generating comprising, for each test query: identifying a plurality of resources responsive to the test query, determining, for each resource in the plurality of resources, whether the first automated resource selection process would classify the resource as to-be-indexed or not-to-be-indexed, and then selecting all resources classified as to-be-indexed as the first group of resources, and determining, for each resource in the plurality of resources, whether the second automated resource selection process would classify the resource as to-be-indexed or not-to-be-indexed, and then selecting all resources classified as to-be-indexed as the second group of resources, wherein the determination whether the first automated resource selection process would classify a particular resource as to-be-indexed or not-to-be-indexed is made independently of the determination whether the second automated resource selection process would classify that particular resource as to-be-indexed or not-to-be-indexed.

1. A system comprising: one or more computers configured to perform operations comprising: receiving a plurality of test queries; generating, for each test query, a first group of resources corresponding to a first automated resource selection process and a second group of resources corresponding to a second automated resource selection process, the generating comprising, for each test query: identifying a plurality of resources responsive to the test query, determining, for each resource in the plurality of resources, whether the first automated resource selection process would classify the resource as to-be-indexed or not-to-be-indexed, and then selecting all resources classified as to-be-indexed as the first group of resources, and determining, for each resource in the plurality of resources, whether the second automated resource selection process would classify the resource as to-be-indexed or not-to-be-indexed, and then selecting all resources classified as to-be-indexed as the second group of resources, wherein the determination whether the first automated resource selection process would classify a particular resource as to-be-indexed or not-to-be-indexed is made independently of the determination whether the second automated resource selection process would classify that particular resource as to-be-indexed or not-to-be-indexed. 6. The system of claim 1 , wherein, for at least one of the test queries in the plurality of test queries, the first group of resources is different from the second group of resources.

10. The method of claim 8 , in which the transformations are performed upon the data comprising at least one of characters, words and phrases contained in the plurality of sections.

10. The method of claim 8 , in which the transformations are performed upon the data comprising at least one of characters, words and phrases contained in the plurality of sections. 11. The method of claim 10 , in which the transformations create at least one of acronyms and abbreviations for at least one of the characters, words, and phrases.

1. A computer program product, comprising: a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions readable by a processing circuit to cause the processing circuit to perform a method of determining a crowd behavior, the method comprising: collecting, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make; generating a graph of the audible expressions as the audible expressions are collected from the individuals, wherein the graph comprises nodes that represent tokens and edges that represent temporal precedence in the audible expressions; determining a crowd behavior by performing a graphical text analysis on the graph; and outputting an indication of the crowd behavior to trigger a crowd control measure, wherein the crowd behavior comprises a risk metric, and wherein the crowd control measure is triggered when the risk metric is above a threshold.

1. A computer program product, comprising: a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions readable by a processing circuit to cause the processing circuit to perform a method of determining a crowd behavior, the method comprising: collecting, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make; generating a graph of the audible expressions as the audible expressions are collected from the individuals, wherein the graph comprises nodes that represent tokens and edges that represent temporal precedence in the audible expressions; determining a crowd behavior by performing a graphical text analysis on the graph; and outputting an indication of the crowd behavior to trigger a crowd control measure, wherein the crowd behavior comprises a risk metric, and wherein the crowd control measure is triggered when the risk metric is above a threshold. 4. The computer program product of claim 1 , wherein the crowd control measure is for assisting the crowd in minimizing a risk the crowd behavior has.

1. An apparatus comprising: a handwriting input device that receives input stroke data; a processor; and a memory that stores code executable by the processor to: identify a handwritten character from the stroke data; determine a deviation between the stroke data corresponding to the handwritten character and a reference character corresponding to the handwritten character; map the handwritten character to a font character of a user-specific font set based on the stroke data deviation; and create a file storing a character encoding corresponding to the font character of a user-specific font set.

1. An apparatus comprising: a handwriting input device that receives input stroke data; a processor; and a memory that stores code executable by the processor to: identify a handwritten character from the stroke data; determine a deviation between the stroke data corresponding to the handwritten character and a reference character corresponding to the handwritten character; map the handwritten character to a font character of a user-specific font set based on the stroke data deviation; and create a file storing a character encoding corresponding to the font character of a user-specific font set. 10. The apparatus of claim 1 , wherein the handwriting input device comprises an input device selected from the group consisting of: a touchscreen, a touch panel, a digitizer, a digital pen, a scanner, an imager, and a digital camera.

19. A system outputting audio content and displaying textual content, the system comprising: a data store; and a processor in communication with the data store, the processor operative to: generate audio content based at least in part on textual content; cause output of the generated audio content; cause presentation of the textual content; obtain an input pointer referencing a position within the textual content being presented; during advancement of the output pointer, determine, independent of the obtained input pointer, a position in the textual content corresponding to the current output position of the generated audio content; determine a segment of textual content based at least in part on a difference between the determined position within the textual content and the position within the textual content referenced by the input pointer; determine a length of the segment of textual content; and modify an attribute associated with the output of the generated audio content based at least in part on the determined length of the segment of textual content.

19. A system outputting audio content and displaying textual content, the system comprising: a data store; and a processor in communication with the data store, the processor operative to: generate audio content based at least in part on textual content; cause output of the generated audio content; cause presentation of the textual content; obtain an input pointer referencing a position within the textual content being presented; during advancement of the output pointer, determine, independent of the obtained input pointer, a position in the textual content corresponding to the current output position of the generated audio content; determine a segment of textual content based at least in part on a difference between the determined position within the textual content and the position within the textual content referenced by the input pointer; determine a length of the segment of textual content; and modify an attribute associated with the output of the generated audio content based at least in part on the determined length of the segment of textual content. 23. The system of claim 19 , wherein modifying an attribute associated with the output of the generated audio content based at least in part on the determined length of the segment of textual content includes modifying the attribute if the determined length satisfies a threshold value.

1. A system for providing reference items as a suggestion for classifying uncoded electronically stored information items, comprising: a set of reference electronically stored information items each associated with one of a plurality of classification codes and a visual representation of that classification code comprising at least one of a shape and a symbol, wherein the visual representation of each of the classification codes is different from the visual representations of the remaining classification codes; a set of uncoded electronically stored information items each associated with a visual representation different from the visual representations of the classification codes; a processor to execute modules, comprising: a clustering module to combine one or more of the coded reference electronically stored information items with the set of the uncoded electronically stored information items and to group the combined uncoded electronically stored information items and one or more coded reference electronically stored information items into clusters; and a display to visually depict relationships between the uncoded electronically stored information items and the one or more coded reference electronically stored information items in at least one of the clusters as suggestions for classifying the uncoded electronically stored information items in that cluster by displaying the visual representation associated with each of the coded reference electronically stored information items in that cluster and the visual representation associated with each of the uncoded electronically stored information items in that cluster.

1. A system for providing reference items as a suggestion for classifying uncoded electronically stored information items, comprising: a set of reference electronically stored information items each associated with one of a plurality of classification codes and a visual representation of that classification code comprising at least one of a shape and a symbol, wherein the visual representation of each of the classification codes is different from the visual representations of the remaining classification codes; a set of uncoded electronically stored information items each associated with a visual representation different from the visual representations of the classification codes; a processor to execute modules, comprising: a clustering module to combine one or more of the coded reference electronically stored information items with the set of the uncoded electronically stored information items and to group the combined uncoded electronically stored information items and one or more coded reference electronically stored information items into clusters; and a display to visually depict relationships between the uncoded electronically stored information items and the one or more coded reference electronically stored information items in at least one of the clusters as suggestions for classifying the uncoded electronically stored information items in that cluster by displaying the visual representation associated with each of the coded reference electronically stored information items in that cluster and the visual representation associated with each of the uncoded electronically stored information items in that cluster. 3. A system according to claim 1 , wherein the clusters are generated based on a similarity metric comprising forming a score vector for each uncoded electronically stored information item in the portion and each coded electronically stored information item in the reference set and calculating the similarity metric by comparing the score vectors for one of the uncoded electronically stored information items and one of the coded electronically stored information items in the reference set as an inner product.

2. A system, comprising: using at least one hardware processor to perform: accessing input data comprising: training data comprising a first plurality of data records, each of the first plurality of data records having numeric data values at least for first and second variables in a plurality of variables; and a second plurality of data records comprising at least a first not fully specified data record that does not include a first numeric data value for the first variable in the plurality of variables; generating, using the training data, a representation of a relationship between the first variable and at least the second variable in the plurality of variables; and obtaining, by the computer system and using the generated representation, at least the first numeric data value for the first variable in the first not fully specified data record.

2. A system, comprising: using at least one hardware processor to perform: accessing input data comprising: training data comprising a first plurality of data records, each of the first plurality of data records having numeric data values at least for first and second variables in a plurality of variables; and a second plurality of data records comprising at least a first not fully specified data record that does not include a first numeric data value for the first variable in the plurality of variables; generating, using the training data, a representation of a relationship between the first variable and at least the second variable in the plurality of variables; and obtaining, by the computer system and using the generated representation, at least the first numeric data value for the first variable in the first not fully specified data record. 13. The system of claim 2 , further comprising: identifying, by the computer system, the first not fully specified data record in the second plurality of data records.

1. A tangible computer-readable storage medium including computer program code to be executed by a processor, the computer program code, when executed, implementing a content-based healthcare location management system comprising: a correlation services manager to receive a location correlation identifier for a clinical application, and correlate the location correlation identifier with a location instance identifier based on an ontology, wherein the ontology is represented in a directed acyclic graph navigable to identify the ontology for a location, wherein the directed acyclic graph includes a plurality of available ontologies for selection of a location relationship, wherein the plurality of available ontologies includes an “is a” ontology and an “is part of” ontology, wherein the location instance identifier identifies an internal instance of the location correlation identifier to provide location information according to a location schema; a location services manager to update a location map using the location instance identifier, the location services manager to store the location instance identifier in a location relationship object based on at least one location relationship associated with the location instance identifier; and a frame manager to utilize the location relationship object to configure one or more content items forming the clinical application based on the location and the at least one location relationship identified in the location relationship object.

1. A tangible computer-readable storage medium including computer program code to be executed by a processor, the computer program code, when executed, implementing a content-based healthcare location management system comprising: a correlation services manager to receive a location correlation identifier for a clinical application, and correlate the location correlation identifier with a location instance identifier based on an ontology, wherein the ontology is represented in a directed acyclic graph navigable to identify the ontology for a location, wherein the directed acyclic graph includes a plurality of available ontologies for selection of a location relationship, wherein the plurality of available ontologies includes an “is a” ontology and an “is part of” ontology, wherein the location instance identifier identifies an internal instance of the location correlation identifier to provide location information according to a location schema; a location services manager to update a location map using the location instance identifier, the location services manager to store the location instance identifier in a location relationship object based on at least one location relationship associated with the location instance identifier; and a frame manager to utilize the location relationship object to configure one or more content items forming the clinical application based on the location and the at least one location relationship identified in the location relationship object. 2. The computer-readable storage medium of claim 1 , wherein allowed relationships are determined by a terminology definition provided by the ontology.

10. The system of claim 1 further comprising: said computer to form a transport object; said computer to generate code indicating said modifications to said selected portion of said text; and said computer to dispose said transport object containing said code within a transport medium.

10. The system of claim 1 further comprising: said computer to form a transport object; said computer to generate code indicating said modifications to said selected portion of said text; and said computer to dispose said transport object containing said code within a transport medium. 16. The system of claim 10 wherein said transport medium comprises Telnet.

15. One or more non-transitory computer readable media comprising computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform a method comprising: receiving a set of identity information supplied by a subject; querying one or more public or private databases with at least a portion of the set of identity information; receiving, in response to the querying, independent information, wherein the independent information is not received from the subject; responsive to receiving the independent information, producing, with the one or more processors, one or more identity proofing queries, wherein at least a portion of the one or more identity proofing queries is based on identity information derived from the independent information; receiving, in response to sending the one or more identity proofing queries, at least one query response; comparing with the one or more processors, the one or more proofing queries and the at least one query response; determining, by querying one or more watchlists with a combination of the identity information and the received independent information, whether the combination matches information in the one or more watchlists; and initiating, based at least in part on the comparing and the determining, one or more of authentication enrollment of the subject and multi-factor authentication of the subject.

15. One or more non-transitory computer readable media comprising computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform a method comprising: receiving a set of identity information supplied by a subject; querying one or more public or private databases with at least a portion of the set of identity information; receiving, in response to the querying, independent information, wherein the independent information is not received from the subject; responsive to receiving the independent information, producing, with the one or more processors, one or more identity proofing queries, wherein at least a portion of the one or more identity proofing queries is based on identity information derived from the independent information; receiving, in response to sending the one or more identity proofing queries, at least one query response; comparing with the one or more processors, the one or more proofing queries and the at least one query response; determining, by querying one or more watchlists with a combination of the identity information and the received independent information, whether the combination matches information in the one or more watchlists; and initiating, based at least in part on the comparing and the determining, one or more of authentication enrollment of the subject and multi-factor authentication of the subject. 19. The non-transitory computer readable of claim 15 , further comprising capturing biometric information, wherein capturing biometric information comprises one or more of: fingerprint image capture, voiceprint audio capture, facial feature image capture, and iris image capture.

1. A system for presenting facts, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions to: receive search results from a fact repository responsive to a search query submitted to the fact repository by a user, wherein the search results include objects from the fact repository, wherein a respective object has associated facts, wherein a respective fact includes an attribute field indicating an attribute, a value field describing the indicated attribute, and a confidence level field that indicates the likelihood that the fact is correct, and wherein the objects in the fact repository are created by: extracting facts from web documents; determining, through fact induction, entities with which the extracted facts are associated, wherein a respective entity is represented by a respective object in the fact repository; storing the extracted facts in the fact repository; and associating the stored extracted facts with the objects corresponding to the determined entities; present the search results to a user in a user interface, wherein the user interface allows the user to select one or more objects to be graphed in the user interface; receive a user-selection of a set of objects to be graphed from the user, wherein the set of objects is selected from the search results; determine that at least one object in the set of objects is associated with at least one value of at least one fact that describes a geographic location; generate a geographic map based on the at least one value of the at least one fact and maps of geographic regions stored on the system; present via the user interface the geographic map; and plot a visual indicator of the at least one object on the geographic map at a location corresponding to the value of the at least one fact of the at least one object.

1. A system for presenting facts, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions to: receive search results from a fact repository responsive to a search query submitted to the fact repository by a user, wherein the search results include objects from the fact repository, wherein a respective object has associated facts, wherein a respective fact includes an attribute field indicating an attribute, a value field describing the indicated attribute, and a confidence level field that indicates the likelihood that the fact is correct, and wherein the objects in the fact repository are created by: extracting facts from web documents; determining, through fact induction, entities with which the extracted facts are associated, wherein a respective entity is represented by a respective object in the fact repository; storing the extracted facts in the fact repository; and associating the stored extracted facts with the objects corresponding to the determined entities; present the search results to a user in a user interface, wherein the user interface allows the user to select one or more objects to be graphed in the user interface; receive a user-selection of a set of objects to be graphed from the user, wherein the set of objects is selected from the search results; determine that at least one object in the set of objects is associated with at least one value of at least one fact that describes a geographic location; generate a geographic map based on the at least one value of the at least one fact and maps of geographic regions stored on the system; present via the user interface the geographic map; and plot a visual indicator of the at least one object on the geographic map at a location corresponding to the value of the at least one fact of the at least one object. 7. The system of claim 1 , including: instructions to determine a commonality of the attributes of the objects in the set; wherein the instructions to present via the user interface a representation of one or more identified facts of the objects in the set having values describing geographic locations include instructions to present representations of facts responsive to the attributes' commonality.

2. The method of claim 1 , wherein the media content is media guidance data related to a media program.

2. The method of claim 1 , wherein the media content is media guidance data related to a media program. 3. The method of claim 2 , wherein the media program is a first media program, the method further comprising generating for display the media guidance data related to the first media program in the alternate language simultaneously with media guidance data related to a second media program in the preferred language.

14. A system to process at least one document image comprising a plurality of text rows and a plurality of characters, each text row having at least one character, the system comprising: at least one processor; and a plurality of modules to execute on the at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; a classification system to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine one or more classes for the text rows based on the physical structures of the text rows as defined by the columns of the character blocks in each text row, each class comprising one or more particular text rows having a similar physical structure; and a pattern matching system to: determine a corresponding binary average row for each of the one or more classes, wherein each corresponding binary average row comprises binary values specifying whether a particular column position in the corresponding average row comprises a character block or a white space; determine an average row matrix for each class based on the corresponding binary average row, wherein each average row vector correspond to one particular class; interpolate the average row matrix for each class to generate corresponding interpolation matrix data; determine a correlation value between the corresponding interpolation matrix data for at least two selected classes of text rows; compare the correlation value to a threshold correlation value; and group the at least two selected classes of text rows into a first combined class when the correlation value is greater than the threshold correlation value.

14. A system to process at least one document image comprising a plurality of text rows and a plurality of characters, each text row having at least one character, the system comprising: at least one processor; and a plurality of modules to execute on the at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; a classification system to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine one or more classes for the text rows based on the physical structures of the text rows as defined by the columns of the character blocks in each text row, each class comprising one or more particular text rows having a similar physical structure; and a pattern matching system to: determine a corresponding binary average row for each of the one or more classes, wherein each corresponding binary average row comprises binary values specifying whether a particular column position in the corresponding average row comprises a character block or a white space; determine an average row matrix for each class based on the corresponding binary average row, wherein each average row vector correspond to one particular class; interpolate the average row matrix for each class to generate corresponding interpolation matrix data; determine a correlation value between the corresponding interpolation matrix data for at least two selected classes of text rows; compare the correlation value to a threshold correlation value; and group the at least two selected classes of text rows into a first combined class when the correlation value is greater than the threshold correlation value. 15. The system of claim 14 wherein the pattern matching system is further configured to: determine a distance between binary average rows for the at least two selected classes of text rows when the correlation value is less than the threshold correlation value; compare the distance to a threshold distance; and group the at least two selected classes of text rows into the first combined class when the distance is less than the threshold distance.

61. A computer system for processing a stored document, comprising: a document index input device including a scanner to scan a coversheet having a document index to provide an image of the document index; a marked check box locator, coupled to the document input index device, to identify at least one action from a plurality of actions set forth in the image by identifying a location of a ark in an action indication area on the image, wherein the plurality of actions includes printing, faxing, sending by electronic mail, and grouping, wherein the action indication area is associated with the plurality of actions, to identify a location on the document index image of at least one indication area having a mark therein, the at least one indication area being associated with at least one document out of a plurality of document set forth in the image; a document identifier, coupled to the marked check box locator, to identify the at least one document from the plurality of document set forth in the image based on the location of the at least one indication area having the mark therein, wherein the at least one action and the at least one document are identified by scanning the coversheet; and a document processor, coupled to the document identifier, to perform the at least one action identified from the plurality of action presented on the document index on the at least one document identified from the plurality of documents presented on the document index.

61. A computer system for processing a stored document, comprising: a document index input device including a scanner to scan a coversheet having a document index to provide an image of the document index; a marked check box locator, coupled to the document input index device, to identify at least one action from a plurality of actions set forth in the image by identifying a location of a ark in an action indication area on the image, wherein the plurality of actions includes printing, faxing, sending by electronic mail, and grouping, wherein the action indication area is associated with the plurality of actions, to identify a location on the document index image of at least one indication area having a mark therein, the at least one indication area being associated with at least one document out of a plurality of document set forth in the image; a document identifier, coupled to the marked check box locator, to identify the at least one document from the plurality of document set forth in the image based on the location of the at least one indication area having the mark therein, wherein the at least one action and the at least one document are identified by scanning the coversheet; and a document processor, coupled to the document identifier, to perform the at least one action identified from the plurality of action presented on the document index on the at least one document identified from the plurality of documents presented on the document index. 71. The computer system of claim 61 , wherein the document index comprises a plurality of representations of documents, and wherein the document locator identifies at least one document based on the location of the at least one indication area by identifying the at least one document corresponding to a document representation indicated by the mark in the at least one indication area overlapping a portion of at least one document image representation.

34. A method comprising: specifying a class network having a class, wherein a membership function defines whether an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; receiving pixel values obtained from a digital image; receiving metadata relating to the digital image; and executing the class network and the process hierarchy on a computer that implements the data network by selectively linking a plurality of objects to the pixel values and to the metadata according to the class network and the process hierarchy, wherein the process step is linked to the metadata.

34. A method comprising: specifying a class network having a class, wherein a membership function defines whether an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; receiving pixel values obtained from a digital image; receiving metadata relating to the digital image; and executing the class network and the process hierarchy on a computer that implements the data network by selectively linking a plurality of objects to the pixel values and to the metadata according to the class network and the process hierarchy, wherein the process step is linked to the metadata. 36. The method of claim 34 , wherein the object of the data network belongs to the class and is linked to pixel values that depict a micro-calcification in a human breast.

1. A search engine implemented within a computer device, comprising: a component to receive a user search query; a document locator to identify documents responsive to the user search query; and a decision component to: rank the identified documents, calculate a click-through rate associated with each of the identified documents, and associate, with a link to a particular one of the identified documents, a thumbnail representation of the particular document in response to calculating that the click through rate associated with the particular document is higher, by at least a threshold amount, than the click through rates associated with all other ones of the identified documents.

1. A search engine implemented within a computer device, comprising: a component to receive a user search query; a document locator to identify documents responsive to the user search query; and a decision component to: rank the identified documents, calculate a click-through rate associated with each of the identified documents, and associate, with a link to a particular one of the identified documents, a thumbnail representation of the particular document in response to calculating that the click through rate associated with the particular document is higher, by at least a threshold amount, than the click through rates associated with all other ones of the identified documents. 8. The search engine of claim 1 , where the click through rate associated with the particular document is based on a ratio of a number of times users have selected the particular document responsive to the search query to a number of times the search query has been received at the search engine.

1. A method of generating a response to a text-based natural language message, comprising: identifying a sentence in the text-based natural language message; identifying an input clause in the sentence; comparing the input clause to a previously received clause, the previously received clause being correlated with a previously generated response message; and generating an output response message based on the previously generated response message, the output response message being derived from a plurality of previously generated response clauses.

1. A method of generating a response to a text-based natural language message, comprising: identifying a sentence in the text-based natural language message; identifying an input clause in the sentence; comparing the input clause to a previously received clause, the previously received clause being correlated with a previously generated response message; and generating an output response message based on the previously generated response message, the output response message being derived from a plurality of previously generated response clauses. 3. A method according to claim 1 , further comprising parsing the input clause, thereby defining a relationship between words in the input clause.

14. The one or more Non-transitory machine-readable media of claim 13 , wherein detecting the state comprises reading variables periodically from storage locations associated with the apparatus.

14. The one or more Non-transitory machine-readable media of claim 13 , wherein detecting the state comprises reading variables periodically from storage locations associated with the apparatus. 15. The one or more Non-transitory machine-readable media of claim 14 , wherein the storage locations comprise register locations corresponding to hardware associated with the apparatus.

27. A computer-implemented method comprising: enabling, using a computing device, secure information transfer between a web browser's scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, said enabling the at least one object to be returned cross-domain enabling return of a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine.

27. A computer-implemented method comprising: enabling, using a computing device, secure information transfer between a web browser's scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, said enabling the at least one object to be returned cross-domain enabling return of a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 34. The computer-implemented method of claim 27 , wherein the scripting engine comprises a JavaScript engine.

37. The system of claim 36 , wherein the one or more time trend statistics include a quality of result difference between two of the quality of result statistics.

37. The system of claim 36 , wherein the one or more time trend statistics include a quality of result difference between two of the quality of result statistics. 38. The system of claim 37 , further programmed to perform operations comprising verifying that the quality of result difference satisfies a statistically significant threshold before generating the first modified quality of result statistic.

2. The system of claim 1 , wherein the end devices generate one or more common language messages based on user input and send the one or more common language messages to one or more of the managers via the bus.

2. The system of claim 1 , wherein the end devices generate one or more common language messages based on user input and send the one or more common language messages to one or more of the managers via the bus. 3. The system of claim 2 , wherein the managers receive the common language messages from the end devices via the bus and to translate the common language messages to content of the media types of the servers with which the manager is connected.

21. A computer-implemented method of playing back evolution of a segment of an electronic document, comprising: presenting an electronic document; retrieving a revision history associated with the electronic document; presenting a graphical control, the graphical control allowing to select a graphical region within a visible portion of the electronic document; selecting the graphical region; choosing a first and a second reference points from the revision history, wherein the first and the second reference points are applicable to the chosen graphical region; determining revision points between the first and the second reference points; traversing the determined revision points and generating a graphical representation of the electronic document at each revision point; constructing an animation sequence comprised of the graphical representation of the electronic document at each revision point, wherein the animation sequence is created separately from the document; and displaying the animation sequence as animation-sequence-playback.

21. A computer-implemented method of playing back evolution of a segment of an electronic document, comprising: presenting an electronic document; retrieving a revision history associated with the electronic document; presenting a graphical control, the graphical control allowing to select a graphical region within a visible portion of the electronic document; selecting the graphical region; choosing a first and a second reference points from the revision history, wherein the first and the second reference points are applicable to the chosen graphical region; determining revision points between the first and the second reference points; traversing the determined revision points and generating a graphical representation of the electronic document at each revision point; constructing an animation sequence comprised of the graphical representation of the electronic document at each revision point, wherein the animation sequence is created separately from the document; and displaying the animation sequence as animation-sequence-playback. 32. The method of claim 21 , wherein the step of choosing the graphical region of the document further comprises: presenting the graphical control overlaying the document; receiving user input to manipulate the position and dimensions of the graphical control; choosing the segment of the document such that it corresponds to the position and dimensions of the graphical control.

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. 4. The method of claim 2 , the transforming including eliminating at least one of a type constructor or a nesting construct from the query.

114. The system of claim 110 , wherein the search criteria comprises a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase and a required term of experience.

114. The system of claim 110 , wherein the search criteria comprises a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase and a required term of experience. 118. The system of claim 114 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for at least one of said at least one job requirement, the required skill or experience-related phrase or at least one implying phrase of the required skill or experience-related phrase, and wherein the term of experience for the required skill or experience-related phrase or said at least one implying phrase of the required skill or experience-related phrase is greater than or equal to the required term of experience.

1. A method comprising: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions; generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions; wherein the method is performed by one or more computers.

1. A method comprising: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions; generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions; wherein the method is performed by one or more computers. 8. The method of claim 1 , further comprising: for each temporary path expression of the one or more temporary path expressions, generating a first tree of nodes, wherein each node in the first tree corresponds to an element in said each temporary path expression; and for each subsetted path expression of the one or more subsetted path expressions, generating a second tree of nodes, wherein each node in the second tree corresponds to an element in said each subsetted path expression; wherein determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by the path-subsetted XML index includes determining whether each first tree is equivalent to one of the second trees.

8. The computer-implemented method of claim 5 , the attribute comprising context information associated with the conversation.

8. The computer-implemented method of claim 5 , the attribute comprising context information associated with the conversation. 9. The computer-implemented method of claim 8 , the context information comprising at least one of identification of a meeting participant, meeting agenda, meeting subject matter, meeting date, meeting time, or meeting location.

1. A computer-implemented method for speaker recognition comprising: determining a speaker recognition score based on a received audio input; generating a speech to noise ratio based on the received audio input; generating a noise type label corresponding to the received audio input; determining a selected adaptive speaker recognition threshold from a plurality of adaptive speaker recognition thresholds based on the speech to noise ratio, the noise type label, and a target false accept rate corresponding to the received audio input, wherein each of the plurality of adaptive speaker recognition thresholds is associated with a particular noise type label, a particular speech to noise ratio, and a particular target false accept rate, and wherein each of the plurality of adaptive speaker recognition thresholds provides a threshold corresponding to a lowest target false reject rate for the particular noise type label, the particular speech to noise ratio, and the particular target false accept rate; and performing speaker recognition for the received audio input based on a comparison of the speaker recognition score to the selected adaptive speaker recognition threshold.

1. A computer-implemented method for speaker recognition comprising: determining a speaker recognition score based on a received audio input; generating a speech to noise ratio based on the received audio input; generating a noise type label corresponding to the received audio input; determining a selected adaptive speaker recognition threshold from a plurality of adaptive speaker recognition thresholds based on the speech to noise ratio, the noise type label, and a target false accept rate corresponding to the received audio input, wherein each of the plurality of adaptive speaker recognition thresholds is associated with a particular noise type label, a particular speech to noise ratio, and a particular target false accept rate, and wherein each of the plurality of adaptive speaker recognition thresholds provides a threshold corresponding to a lowest target false reject rate for the particular noise type label, the particular speech to noise ratio, and the particular target false accept rate; and performing speaker recognition for the received audio input based on a comparison of the speaker recognition score to the selected adaptive speaker recognition threshold. 7. The method of claim 1 , further comprising: determining a second speaker recognition score based on the received audio input, wherein determining the speaker recognition score comprises applying a first speaker model corresponding to a first user and determining the second speaker recognition score comprises applying a second speaker model corresponding to a second user, wherein the first and second speaker models are different, and wherein performing the speaker recognition comprises a second comparison of the second speaker recognition score to the selected adaptive speaker recognition threshold.

14. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: extracting a first set of tokens from a Uniform Resource Locator (URL), wherein the extracting comprises: i. splitting the URL by predefined separators; and ii. removing numerical characters; determining a similarity between the first set of tokens and each of a multiple set of tokens extracted from multiple other URLs; and associating the search query with a cluster, wherein the associating is based at least in part on the similarities between the first set of tokens and each of the multiple set of tokens extracted from the other URLs.

14. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: extracting a first set of tokens from a Uniform Resource Locator (URL), wherein the extracting comprises: i. splitting the URL by predefined separators; and ii. removing numerical characters; determining a similarity between the first set of tokens and each of a multiple set of tokens extracted from multiple other URLs; and associating the search query with a cluster, wherein the associating is based at least in part on the similarities between the first set of tokens and each of the multiple set of tokens extracted from the other URLs. 16. One or more computer-readable media as recited in claim 14 , wherein the extracting further comprises merging identical tokens.

10. A computer-readable storage medium that stores instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: a SQL/XML compiler rewriting a XQuery query that includes a XQuery function to generate a rewritten query, wherein said XQuery query applies XML data to said XQuery function, wherein rewriting said XQuery query includes: during compile time, said SQL/XML compiler determining that said XML data is dynamically typed; and in response to determining that said XML data is dynamically typed, said SQL/XML compiler replacing said XQuery function with an SQL polymorphic function that is able to handle a range of XML data types and performs type checking when computed at run time, said rewritten query applying said XML data to said SQL polymorphic function and typing said XML data as XMLType.

10. A computer-readable storage medium that stores instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: a SQL/XML compiler rewriting a XQuery query that includes a XQuery function to generate a rewritten query, wherein said XQuery query applies XML data to said XQuery function, wherein rewriting said XQuery query includes: during compile time, said SQL/XML compiler determining that said XML data is dynamically typed; and in response to determining that said XML data is dynamically typed, said SQL/XML compiler replacing said XQuery function with an SQL polymorphic function that is able to handle a range of XML data types and performs type checking when computed at run time, said rewritten query applying said XML data to said SQL polymorphic function and typing said XML data as XMLType. 15. The computer-readable storage medium of claim 10 , wherein the XQuery function is an XQuery order-by construct in a FLWOR expression.

1. A translation device comprising: a region extracting unit that extracts a character region and a separate region from image data showing an image including characters, the separate region having structural elements different from structural elements of the character region; a character recognition unit that recognizes characters in the region that is determined to be the character region by the region extracting unit; a specifying unit that specifies a caption region from within the character region, the caption region being a region having a predetermined positional relationship with the separate region, the caption region having a size that satisfies a predetermined condition; an associating unit that extracts, from a result of character recognition performed by the character recognition unit, a character string included in the caption region specified by the specifying unit, and that associates the character string with the character region from which the character string is extracted and the separate region; a translating unit that translates to another language the resulting recognized characters; and a pasting unit that, based on the association between the character string and the other character region, pastes the resulting translation that includes the character string onto the same page as the separate region that is associated with the character string.

1. A translation device comprising: a region extracting unit that extracts a character region and a separate region from image data showing an image including characters, the separate region having structural elements different from structural elements of the character region; a character recognition unit that recognizes characters in the region that is determined to be the character region by the region extracting unit; a specifying unit that specifies a caption region from within the character region, the caption region being a region having a predetermined positional relationship with the separate region, the caption region having a size that satisfies a predetermined condition; an associating unit that extracts, from a result of character recognition performed by the character recognition unit, a character string included in the caption region specified by the specifying unit, and that associates the character string with the character region from which the character string is extracted and the separate region; a translating unit that translates to another language the resulting recognized characters; and a pasting unit that, based on the association between the character string and the other character region, pastes the resulting translation that includes the character string onto the same page as the separate region that is associated with the character string. 2. The translation device according to claim 1 , wherein the separate region is a graphic region and the character string is a diagram number; and wherein the diagram number corresponding to the graphic region is associated with the diagram number in the character region.

12. A non-transitory computer program embodied on a computer readable medium for generating a searchable knowledge base for a plurality of items in a choice set, each of said items having an associated set of attributes including at least one subjective attribute, comprising: instructions for harvesting information relevant to each of said items and an age of said harvested information from the Internet; instructions for extracting a set of normalized representations from a corresponding set of statements in one or more texts of said harvested information; instructions for analyzing the normalized representations to derive a set of scores for each attribute in said associated set of attributes for each of said items; instructions for aggregating said derived scores, for said each attribute in said associated set of attributes, by assigning a weight to each of the scores based on at least the age of said harvested information; and instructions for incorporating attributes in said associated set of attributes and their corresponding aggregated scores, for each of said items, into said searchable knowledge base for said choice set, wherein a computer processor is utilized to automatically perform each of said instructions, the incorporating including: annotating a first statement harvested for a first item of the plurality of items with a first set of attributes and a corresponding first set of scores to generate a first annotation, the first set of attributes associated with the first item and determined based on an analysis of text in the first statement, the first statement being one of multiple statements harvested for the first item, the first annotation being one of multiple annotations in the searchable knowledge base, the first annotation including a link to the first statement, and indexing the annotations in the searchable knowledge base to facilitate retrieval of a statement of the statements that corresponds to an input attribute.

12. A non-transitory computer program embodied on a computer readable medium for generating a searchable knowledge base for a plurality of items in a choice set, each of said items having an associated set of attributes including at least one subjective attribute, comprising: instructions for harvesting information relevant to each of said items and an age of said harvested information from the Internet; instructions for extracting a set of normalized representations from a corresponding set of statements in one or more texts of said harvested information; instructions for analyzing the normalized representations to derive a set of scores for each attribute in said associated set of attributes for each of said items; instructions for aggregating said derived scores, for said each attribute in said associated set of attributes, by assigning a weight to each of the scores based on at least the age of said harvested information; and instructions for incorporating attributes in said associated set of attributes and their corresponding aggregated scores, for each of said items, into said searchable knowledge base for said choice set, wherein a computer processor is utilized to automatically perform each of said instructions, the incorporating including: annotating a first statement harvested for a first item of the plurality of items with a first set of attributes and a corresponding first set of scores to generate a first annotation, the first set of attributes associated with the first item and determined based on an analysis of text in the first statement, the first statement being one of multiple statements harvested for the first item, the first annotation being one of multiple annotations in the searchable knowledge base, the first annotation including a link to the first statement, and indexing the annotations in the searchable knowledge base to facilitate retrieval of a statement of the statements that corresponds to an input attribute. 13. A computer program as recited in claim 12 , further comprising instructions for extracting texts of said harvested information by automated voice recognition, wherein said harvested information includes audio information.

1. A computer implemented method of obtaining personal ads, the method comprising: performing a first search, using at least one computing device, of personal ads to identify a first personals ad; performing an affinity search, using the at least one computing device, based on the first personals ad identified in the first search to identify one or more second personals ads having an affinity to the first personals ad, wherein the affinity search comprises calculating an affinity score between the first personals ad and each of the second personals ads, wherein the affinity score of each of the second personals ads relates to the number of occurrences of an action taken by a plurality of users with respect to the first personals ad and the respective second personals ad, and wherein the affinity search does not identify personals ads having an affinity score with the first personal ad below a predefined threshold; and prioritizing, using the at least one computing device, the identified second personals ads based upon its respective affinity score with the first personals ad.

1. A computer implemented method of obtaining personal ads, the method comprising: performing a first search, using at least one computing device, of personal ads to identify a first personals ad; performing an affinity search, using the at least one computing device, based on the first personals ad identified in the first search to identify one or more second personals ads having an affinity to the first personals ad, wherein the affinity search comprises calculating an affinity score between the first personals ad and each of the second personals ads, wherein the affinity score of each of the second personals ads relates to the number of occurrences of an action taken by a plurality of users with respect to the first personals ad and the respective second personals ad, and wherein the affinity search does not identify personals ads having an affinity score with the first personal ad below a predefined threshold; and prioritizing, using the at least one computing device, the identified second personals ads based upon its respective affinity score with the first personals ad. 7. The method of claim 1 , wherein the one or more second personal ads were not identified by the first search.

16. A computer program product to process an electronic document, the computer program product comprising: a computer usable storage medium having computer usable program code embodied therein, the computer usable storage medium comprising: computer usable program code configured to perform a programmatic analysis to determine all required portions of an input document to produce an output document; computer usable program code configured to generate an executable transformer to produce the output document from the input document; and computer usable program code configured to produce the output document by transforming any streamable parts of the input document directly to corresponding parts of the output document without extraneous intermediate buffering.

16. A computer program product to process an electronic document, the computer program product comprising: a computer usable storage medium having computer usable program code embodied therein, the computer usable storage medium comprising: computer usable program code configured to perform a programmatic analysis to determine all required portions of an input document to produce an output document; computer usable program code configured to generate an executable transformer to produce the output document from the input document; and computer usable program code configured to produce the output document by transforming any streamable parts of the input document directly to corresponding parts of the output document without extraneous intermediate buffering. 19. The computer program product of claim 16 , wherein the computer usable medium further comprises: computer usable program code configured to build-up an optimized document model from any non-streamable parts of the input document; and computer usable program code configured to process the built-up optimized document model in the executable transformer to complete the output document.

3. The method according to claim 2 , wherein the modifying the created packet filter rule context according to the message for modifying the packet filter rule context sent by the MGC comprises one of: adding, modifying or deleting a filter rule carried in the packet filter rule context according to the message for modifying the packet filter rule context sent by the MGC.

3. The method according to claim 2 , wherein the modifying the created packet filter rule context according to the message for modifying the packet filter rule context sent by the MGC comprises one of: adding, modifying or deleting a filter rule carried in the packet filter rule context according to the message for modifying the packet filter rule context sent by the MGC. 6. The method according to claim 3 , wherein: the packet filter rule context comprises a termination, and a termination property of the termination comprise the filter rule.

6. A method for training acoustic model, comprising: a training respective speech unit in a speech database to generate an acoustic model, the speech unit includes acoustic parameters and context labels; for context combination, performing a decision tree clustering process to generate the acoustic model with a decision tree; determining fuzzy data in the speech database based on the acoustic model with the decision tree; generating the fuzzy context feature labels for the fuzzy data; and cluster training the speech database based on the fuzzy context feature labels to generate the acoustic model with the fuzzy decision tree, using a device selected from the group consisting of a computer and a logic circuit.

6. A method for training acoustic model, comprising: a training respective speech unit in a speech database to generate an acoustic model, the speech unit includes acoustic parameters and context labels; for context combination, performing a decision tree clustering process to generate the acoustic model with a decision tree; determining fuzzy data in the speech database based on the acoustic model with the decision tree; generating the fuzzy context feature labels for the fuzzy data; and cluster training the speech database based on the fuzzy context feature labels to generate the acoustic model with the fuzzy decision tree, using a device selected from the group consisting of a computer and a logic circuit. 10. The method according to claim 6 , wherein the step of cluster training based on the fuzzy context feature labels further comprises one of: training a training set including the fuzzy data based on the fuzzy context feature labels and a predefined fuzzy question set to generate the acoustic model with the fuzzy decision tree; and re-training the respective speech unit in the speech database based on a question set and context feature labels, wherein the question set further includes a predefined fuzzy question set, and the context feature labels of the fuzzy data in the speech database are the fuzzy context feature labels.

26. A method of operating a computerized information retrieval system where information is retrieved from a database containing documents in response to user queries, the method comprising: receiving a natural language query specifying information to be retrieved; extracting terms that appear in the query; detecting words that indicate that a given term is required to be in a retrieved document; if a word that indicates a mandatory term is detected, determining which of the terms are indicated to be mandatory; generating an alternative representation of the query that includes both the terms that are indicated to be mandatory and the terms that are not indicated to be mandatory, the alternative representation including a logical representation wherein the mandatory terms are logically connected to the query terms using an AND fuzzy Boolean operator; matching the alternative representation of the query against the database by determining a measure of relevance for each document; providing a set of documents that satisfy a retrieval criterion; and within the set of documents, so provided, segregating those documents that satisfy the mandatory portion of the query from those documents that do not satisfy the mandatory portion of the query.

26. A method of operating a computerized information retrieval system where information is retrieved from a database containing documents in response to user queries, the method comprising: receiving a natural language query specifying information to be retrieved; extracting terms that appear in the query; detecting words that indicate that a given term is required to be in a retrieved document; if a word that indicates a mandatory term is detected, determining which of the terms are indicated to be mandatory; generating an alternative representation of the query that includes both the terms that are indicated to be mandatory and the terms that are not indicated to be mandatory, the alternative representation including a logical representation wherein the mandatory terms are logically connected to the query terms using an AND fuzzy Boolean operator; matching the alternative representation of the query against the database by determining a measure of relevance for each document; providing a set of documents that satisfy a retrieval criterion; and within the set of documents, so provided, segregating those documents that satisfy the mandatory portion of the query from those documents that do not satisfy the mandatory portion of the query. 27. The method of claim 26, and further comprising the steps, performed before said matching step, of: displaying query information to the user indicating the terms that are interpreted by the system to be mandatory; receiving user input responsive to the display of such query information; and in response to such user input, if any, modifying the alternative representation of the query to reflect such user input.

6. The method of claim 1 , wherein the search query comprises search keywords, each keyword being associated with one negative or one positive operator, the step of transforming the search query in the query matrix comprising several rows comprises the following steps: expressing the search query in disjunctive normal form, as disjunction of conjunctive clauses, separating in each conjunctive clause the keywords associated with a positive operator from the keywords associated with a negative operator, transforming in each conjunctive clause: each search keyword associated with a positive operator in a vector, called positive vector, in the span of the orthonormal basis; each search keyword associated with a negative operator in a vector, called negative vector, in the span of the orthonormal basis; and determining the search query as a matrix where each row of the query matrix corresponds to one conjunctive clause and each row is a vector based on the positive and negative vectors, each row comprising a first sum in which the positive vectors are gathered and a second sum in which the negative vectors are gathered.

6. The method of claim 1 , wherein the search query comprises search keywords, each keyword being associated with one negative or one positive operator, the step of transforming the search query in the query matrix comprising several rows comprises the following steps: expressing the search query in disjunctive normal form, as disjunction of conjunctive clauses, separating in each conjunctive clause the keywords associated with a positive operator from the keywords associated with a negative operator, transforming in each conjunctive clause: each search keyword associated with a positive operator in a vector, called positive vector, in the span of the orthonormal basis; each search keyword associated with a negative operator in a vector, called negative vector, in the span of the orthonormal basis; and determining the search query as a matrix where each row of the query matrix corresponds to one conjunctive clause and each row is a vector based on the positive and negative vectors, each row comprising a first sum in which the positive vectors are gathered and a second sum in which the negative vectors are gathered. 9. The method of claim 6 , wherein each row of the query matrix further comprises a common vector corresponding to a common keyword which has been added to all the documents.

1. A method comprising: providing, to a client device associated with a first user of a plurality of users of a social networking system, a user interface for display to the first user; receiving from the first user, via the client device, a check-in at a location associated with a page in the social networking system, wherein the page is a social networking system page about at least one of a product, a business, a location, and a topic of interest, and wherein the page is a node in a social graph of the social networking system; responsive to receiving the check-in, providing a user interface element for receiving a tip associated with the page; receiving, via the client device, a tip from the first user that is associated with the page; identifying a plurality of tips, including the received tip, that are associated with the page, the plurality of tips shared by one or more of the plurality of users of the social networking system; receiving, via a second client device, a request from a second user of the plurality of users to display one or more of the plurality of tips associated with the page, wherein each tip is associated with privacy criteria that identify users having permission to view that tip; determining that the second user meets privacy criteria associated with a set of candidate tips of the plurality of tips; selecting, by a computer processor, one or more tips, including the received tip, from the set of candidate tips to display to the second user based in part on the second user meeting the privacy criteria associated with the received tip and a relevancy score associated with the received tip, the relevancy score providing a likelihood the second user will view the received tip and is based in part on a number of interactions between the second user and the first user within the social networking system; and responsive to the selecting, providing the page to the second client device, the page displaying the selected one or more tips.

1. A method comprising: providing, to a client device associated with a first user of a plurality of users of a social networking system, a user interface for display to the first user; receiving from the first user, via the client device, a check-in at a location associated with a page in the social networking system, wherein the page is a social networking system page about at least one of a product, a business, a location, and a topic of interest, and wherein the page is a node in a social graph of the social networking system; responsive to receiving the check-in, providing a user interface element for receiving a tip associated with the page; receiving, via the client device, a tip from the first user that is associated with the page; identifying a plurality of tips, including the received tip, that are associated with the page, the plurality of tips shared by one or more of the plurality of users of the social networking system; receiving, via a second client device, a request from a second user of the plurality of users to display one or more of the plurality of tips associated with the page, wherein each tip is associated with privacy criteria that identify users having permission to view that tip; determining that the second user meets privacy criteria associated with a set of candidate tips of the plurality of tips; selecting, by a computer processor, one or more tips, including the received tip, from the set of candidate tips to display to the second user based in part on the second user meeting the privacy criteria associated with the received tip and a relevancy score associated with the received tip, the relevancy score providing a likelihood the second user will view the received tip and is based in part on a number of interactions between the second user and the first user within the social networking system; and responsive to the selecting, providing the page to the second client device, the page displaying the selected one or more tips. 8. The method of claim 1 , wherein privacy criteria associated with the received tip is provided by the first user, the privacy criteria identifying users of the social networking system having permission to view the received tip when the received tip is provided.

1. A system for gesture recognition by a computing device, the system comprising: one or more processors; a memory coupled to the one or more processors; a touch-sensitive display coupled to the one or more processors; a virtual keyboard module configured to display a virtual keyboard on the touch-sensitive display and to receive a continuous stroke input by a user on the virtual keyboard, wherein the continuous stroke comprises a start-point and an end-point; a recognition module configured to obtain a most probable candidate word corresponding to the continuous stroke input by a user on the virtual keyboard; and a candidate display module configured to display, over the virtual keyboard, one or more characters representing the most probable candidate word, wherein a representation of the most probable candidate word is displayed at a particular location selected based at least in part on the continuous stroke end-point.

1. A system for gesture recognition by a computing device, the system comprising: one or more processors; a memory coupled to the one or more processors; a touch-sensitive display coupled to the one or more processors; a virtual keyboard module configured to display a virtual keyboard on the touch-sensitive display and to receive a continuous stroke input by a user on the virtual keyboard, wherein the continuous stroke comprises a start-point and an end-point; a recognition module configured to obtain a most probable candidate word corresponding to the continuous stroke input by a user on the virtual keyboard; and a candidate display module configured to display, over the virtual keyboard, one or more characters representing the most probable candidate word, wherein a representation of the most probable candidate word is displayed at a particular location selected based at least in part on the continuous stroke end-point. 3. The system of claim 1 further comprising a concatenation module configured to: automatically recognize that the most probable candidate word is part of a stem or compound word created from one or more previously entered words; and replace the previously entered one or more words with the recognized stem or compound word.

25. The system of claim 24 further comprising a bus that interconnects the main processor, the processing device, the data store of unstructured data, and the RDBMS.

25. The system of claim 24 further comprising a bus that interconnects the main processor, the processing device, the data store of unstructured data, and the RDBMS. 27. The system of claim 25 further comprising a network interface connected to the bus, the network interface being in communication with a computer network in which a SQL-enabled client application resides, the SQL-enabled client application being configured to formulate the query in response to user input and communicate the query to the SQL-enabled API via the network interface.

9. A method for retrieving information from databases, said databases being structured or unstructured, said databases being homogeneous or heterogeneous, wherein retrieval is performed through visual queries on dynamic taxonomies, said dynamic taxonomies being an organization of concepts that ranges from a most general concept to a most specific concept, said concepts and their organization being called an intension, items in said databases being classified under one or more concepts, said items and their classification being called an extension, said method comprising, given an initial current subset of interest: using a computer for providing a reduced taxonomy for the current subset of interest; using the computer for refining the current subset of interest of said reduced taxonomy with the combination of one or more taxonomy concepts through Boolean operations; and using the computer for iteratively repeating said steps of providing a reduced taxonomy for the current subset of interest to further refine said retrieval and of refining the current subset of interest, wherein: said initial subset of interest includes all the items in the extension of the dynamic taxonomy or a subset of them; said reduced taxonomy being derived from said taxonomy by using the computer for pruning concepts under which no item in said current subset of interest is classified; said step of pruning concepts includes eliminating from the taxonomy all the concepts under which no item in the current subset of interest is classified, or preventing said concepts from being displayed, or preventing said concepts from being selected in order to refine interest sets; said step of providing a reduced taxonomy either reports only the concepts belonging to the reduced taxonomy or, for each such concept also reports how many items in the current interest set are classified under the concept; said intension is organized as a hierarchy of concepts or as a directed acyclic graph of concepts, thereby allowing a concept to have multiple fathers; in said extension, there exists at least one item such that said item is classified under at least two different concepts such that each of said two concepts is neither an ancestor nor a descendant of the other concept in the intension.

9. A method for retrieving information from databases, said databases being structured or unstructured, said databases being homogeneous or heterogeneous, wherein retrieval is performed through visual queries on dynamic taxonomies, said dynamic taxonomies being an organization of concepts that ranges from a most general concept to a most specific concept, said concepts and their organization being called an intension, items in said databases being classified under one or more concepts, said items and their classification being called an extension, said method comprising, given an initial current subset of interest: using a computer for providing a reduced taxonomy for the current subset of interest; using the computer for refining the current subset of interest of said reduced taxonomy with the combination of one or more taxonomy concepts through Boolean operations; and using the computer for iteratively repeating said steps of providing a reduced taxonomy for the current subset of interest to further refine said retrieval and of refining the current subset of interest, wherein: said initial subset of interest includes all the items in the extension of the dynamic taxonomy or a subset of them; said reduced taxonomy being derived from said taxonomy by using the computer for pruning concepts under which no item in said current subset of interest is classified; said step of pruning concepts includes eliminating from the taxonomy all the concepts under which no item in the current subset of interest is classified, or preventing said concepts from being displayed, or preventing said concepts from being selected in order to refine interest sets; said step of providing a reduced taxonomy either reports only the concepts belonging to the reduced taxonomy or, for each such concept also reports how many items in the current interest set are classified under the concept; said intension is organized as a hierarchy of concepts or as a directed acyclic graph of concepts, thereby allowing a concept to have multiple fathers; in said extension, there exists at least one item such that said item is classified under at least two different concepts such that each of said two concepts is neither an ancestor nor a descendant of the other concept in the intension. 41. The method of claim 9 where one or more concepts represent a tag cloud, said tag cloud having as descendants all or parts of the terms or phrases that are derived from the items, each tag cloud and each of descendants is used as a dynamic taxonomy concept to define a subset of interest possibly in combination with other clouds or concepts or querying methods, each tag cloud and each of descendants is used as a dynamic taxonomy concept to summarize a subset of interest.

1. A computer-implemented method comprising steps of: from a workload set, identifying a plurality of database query language statements for automatic tuning, wherein the workload set comprises database query language statements and current performance data for the database query language statements; executing each database query language statement from said plurality of query language statements against a database; collecting new performance data from said executing each database query language statement, said collecting comprising measuring resource usage by said executing each database query language statement; detecting that conditions in said database that affect executing said plurality of database query language statements changed based at least in part on comparison of the new performance data with the current performance data; in response to the detecting, tuning a subset of database query language statements from said plurality of database query language statements, said subset of database query language statements comprising a database query language statement from said plurality of database query language statements, wherein the new performance data is different from the current performance data for the database query language statement; wherein the tuning the subset of database query language statements comprises generating a plurality of tuning recommendations for execution of the subset of database query language statements; testing the plurality of tuning recommendations against said database, wherein the testing the plurality of tuning recommendations comprises, for each tuning recommendation of said plurality of tuning recommendations: executing a respective database query language statement from said subset of database query language statements with said each tuning recommendation enabled; measuring resource usage by said executing the respective database query language statement with said each tuning recommendation enabled, wherein the resource usage comprises processor time or buffer gets; and measuring benefits based on performance improvement of said executing the respective database query language statement with said each tuning recommendation enabled; based on the testing, determining a subset of said plurality of tuning recommendations resulted in performance improvement that meets a specific set of criteria; implementing the subset of said plurality of tuning recommendations; and wherein the steps are automatically performed by one or more computing devices.

1. A computer-implemented method comprising steps of: from a workload set, identifying a plurality of database query language statements for automatic tuning, wherein the workload set comprises database query language statements and current performance data for the database query language statements; executing each database query language statement from said plurality of query language statements against a database; collecting new performance data from said executing each database query language statement, said collecting comprising measuring resource usage by said executing each database query language statement; detecting that conditions in said database that affect executing said plurality of database query language statements changed based at least in part on comparison of the new performance data with the current performance data; in response to the detecting, tuning a subset of database query language statements from said plurality of database query language statements, said subset of database query language statements comprising a database query language statement from said plurality of database query language statements, wherein the new performance data is different from the current performance data for the database query language statement; wherein the tuning the subset of database query language statements comprises generating a plurality of tuning recommendations for execution of the subset of database query language statements; testing the plurality of tuning recommendations against said database, wherein the testing the plurality of tuning recommendations comprises, for each tuning recommendation of said plurality of tuning recommendations: executing a respective database query language statement from said subset of database query language statements with said each tuning recommendation enabled; measuring resource usage by said executing the respective database query language statement with said each tuning recommendation enabled, wherein the resource usage comprises processor time or buffer gets; and measuring benefits based on performance improvement of said executing the respective database query language statement with said each tuning recommendation enabled; based on the testing, determining a subset of said plurality of tuning recommendations resulted in performance improvement that meets a specific set of criteria; implementing the subset of said plurality of tuning recommendations; and wherein the steps are automatically performed by one or more computing devices. 13. The computer-implemented method of claim 1 , wherein the resource usage comprises both processor time and buffer gets.

1. Vocabulary building playing cards comprising a deck having a multiplicity of cards, each card displaying symbolic indicia defining a suit designation, there being 4 suits in said deck, each suit having a prescribed number of different value denominaions, the value denominations of each suit being the same as each other suit, at least some of said cards being vocabulary cards having a vocabulary word thereon, each of said vocabulary cards displaying indicia comprising a correct definition and a plurality of incorrect definitions of the respective vocabulary word, indicia defining a different value denomination on each vocabulary card adjacent each correct and each incorrect definition, the value denomination of each vocabulary card being that corresponding to the correct definition of the vocabulary word.

1. Vocabulary building playing cards comprising a deck having a multiplicity of cards, each card displaying symbolic indicia defining a suit designation, there being 4 suits in said deck, each suit having a prescribed number of different value denominaions, the value denominations of each suit being the same as each other suit, at least some of said cards being vocabulary cards having a vocabulary word thereon, each of said vocabulary cards displaying indicia comprising a correct definition and a plurality of incorrect definitions of the respective vocabulary word, indicia defining a different value denomination on each vocabulary card adjacent each correct and each incorrect definition, the value denomination of each vocabulary card being that corresponding to the correct definition of the vocabulary word. 3. Vocabulary building playing cards as recited in claim 1 wherein each vocabulary card has a different vocabulary word thereon.

1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device.

1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device. 2. The method of claim 1 , wherein receiving the narrative content further comprises transmitting a user selection of the interactive audiobook from a plurality of interactive audiobooks and receiving the selected interactive audiobook.

12. A system for processing queries of an XML document, the system comprising: a tokenizer configured to generate a plurality of tokens based on the contents of the XML document; a processor configured to: receive at least one query expression, wherein the at least one query expression comprises one or more components, and wherein each of the components comprises at least one symbol; generate at least one index and a data structure, wherein the generated data structure is indicative of hierarchical relationships between the one or more components of the received at least one query expression, the generated data structure further defining respective lists of the one or more components having corresponding symbols and the index comprising a plurality of entries with at least one of the entries for each symbol of the received at least one query expression and wherein the generated at least one index relates each symbol of the received at least one query expression in a corresponding one of the entries to a corresponding component in the respective lists defined by the generated data structure; generate a plurality of tokens based on contents of the XML document; identify one or more tokens that matches at least one symbol by comparing the plurality of tokens with the generated at least one index; for each of the identified one or more tokens: retrieving a respective list of matching components corresponding to the matched at least one symbol of the generated structure and marking each matching component of the respective list of matching components; and output data indicative of a match to the received at least one query expression subsequent to marking each of the components of the received at least one query expression.

12. A system for processing queries of an XML document, the system comprising: a tokenizer configured to generate a plurality of tokens based on the contents of the XML document; a processor configured to: receive at least one query expression, wherein the at least one query expression comprises one or more components, and wherein each of the components comprises at least one symbol; generate at least one index and a data structure, wherein the generated data structure is indicative of hierarchical relationships between the one or more components of the received at least one query expression, the generated data structure further defining respective lists of the one or more components having corresponding symbols and the index comprising a plurality of entries with at least one of the entries for each symbol of the received at least one query expression and wherein the generated at least one index relates each symbol of the received at least one query expression in a corresponding one of the entries to a corresponding component in the respective lists defined by the generated data structure; generate a plurality of tokens based on contents of the XML document; identify one or more tokens that matches at least one symbol by comparing the plurality of tokens with the generated at least one index; for each of the identified one or more tokens: retrieving a respective list of matching components corresponding to the matched at least one symbol of the generated structure and marking each matching component of the respective list of matching components; and output data indicative of a match to the received at least one query expression subsequent to marking each of the components of the received at least one query expression. 20. The system of claim 12 , wherein the at least one query expression comprises a plurality of XML queries and wherein the processor is configured to process the plurality of XML queries concurrently.

1. A method comprising: receiving, using one or more processors, a search query; identifying, using the one or more processors, a plurality of entities referred to in the search query, wherein each of the entities is associated with an entity ID uniquely assigned to the particular entity; generating, using the search query, a search query graph that comprises: a) the search query; b) for each of the plurality of entities, the entity ID uniquely assigned to the particular entity; c) for each of the plurality of entities, one or more properties of the particular entity, wherein the one or more properties comprise one or more other entities; and d) one or more relationship connections between the plurality of entities and the one or more properties; based on the search query, identifying one or more candidate content selection criteria graphs from a database using the search query, wherein each of the candidate content selection criteria graphs relates to one or more of the identified entities referred to in the search query, wherein the one or more candidate content selection criteria graphs are associated with one or more content items; identifying, from the one or more candidate content selection criteria graphs, a particular content selection criteria graph that matches the search query graph based, at least in part, on a similarity between the one or more entities, one or more properties, and one or more relationship connections of the search query graph and the particular content selection criteria graph, wherein identifying a particular content selection criteria graph comprises comparing entity confidence scores of the search query graph with threshold confidence scores of the one or more candidate content selection criteria graphs; identifying content items associated with the particular content selection criteria graph that are distributed using the particular content selection criteria graph; and providing, for display on a computing device that submitted the search query, one or more of the identified content items.

1. A method comprising: receiving, using one or more processors, a search query; identifying, using the one or more processors, a plurality of entities referred to in the search query, wherein each of the entities is associated with an entity ID uniquely assigned to the particular entity; generating, using the search query, a search query graph that comprises: a) the search query; b) for each of the plurality of entities, the entity ID uniquely assigned to the particular entity; c) for each of the plurality of entities, one or more properties of the particular entity, wherein the one or more properties comprise one or more other entities; and d) one or more relationship connections between the plurality of entities and the one or more properties; based on the search query, identifying one or more candidate content selection criteria graphs from a database using the search query, wherein each of the candidate content selection criteria graphs relates to one or more of the identified entities referred to in the search query, wherein the one or more candidate content selection criteria graphs are associated with one or more content items; identifying, from the one or more candidate content selection criteria graphs, a particular content selection criteria graph that matches the search query graph based, at least in part, on a similarity between the one or more entities, one or more properties, and one or more relationship connections of the search query graph and the particular content selection criteria graph, wherein identifying a particular content selection criteria graph comprises comparing entity confidence scores of the search query graph with threshold confidence scores of the one or more candidate content selection criteria graphs; identifying content items associated with the particular content selection criteria graph that are distributed using the particular content selection criteria graph; and providing, for display on a computing device that submitted the search query, one or more of the identified content items. 6. The method of claim 1 , wherein generating the search query graph comprises accessing a data structure having entity information and identifying one or more properties of the plurality of entities from the entity information.

1. A computer system for identifying flee-text documents, the system comprising: a knowledge source storing in a knowledge database a plurality of concepts formed based on one or more words from a predefined vocabulary set, the knowledge source maintaining a plurality of relationship links wherein each relationship link defines a relationship between a first semantic grouping of the concepts and a second semantic grouping of the concepts; an input receiving an input query including an original query concept and at least one scenario identifier, the at least one scenario identifier being associated with at least one of the relationship links; a database of flee-text documents, wherein each document is indexed via one or more indexing concepts formed based on one or more words from the predefined vocabulary set; one or more processors coupled to the input, each of the one or more processors being operable to execute one or more computer instructions which: generate the indexing concepts for the free-text documents based on the one or more words from the predefined vocabulary set, wherein the program instructions which generate the indexing concepts include computer instructions for: maintaining a plurality of data structures mapping each of the plurality of concepts in the knowledge source to all words appearing in the concept; receiving a particular one of the free-text documents; identifying based on the plurality of data structures the one or more of the plurality of concepts in the knowledge source mapped to a set of words appearing in the particular one of the free-text documents; and returning the one or more identified concepts as candidate index concepts for the particular one of the free-text documents; automatically generate an expanded input query including both the original query concept and one or more additional query concepts, the one or more additional query concepts being selected from one or more first particular semantic groupings of the concepts in the knowledge source that have a specific relationship link with a second particular semantic grouping of the concepts containing the original query concept, the specific relationship link being identified by the at least one scenario identifier, wherein the computer instructions which automatically generate the expanded input query further include computer instructions which: filter candidate expansion concepts not included in the one or more first particular semantic groupings of the concepts in the knowledge source; and return the one or more additional query concepts based on the filtering; compare the expanded input query with the indexing concepts for the free-text documents; and return one or more of the free-text documents that satisfy the expanded input query based on the comparison.

1. A computer system for identifying flee-text documents, the system comprising: a knowledge source storing in a knowledge database a plurality of concepts formed based on one or more words from a predefined vocabulary set, the knowledge source maintaining a plurality of relationship links wherein each relationship link defines a relationship between a first semantic grouping of the concepts and a second semantic grouping of the concepts; an input receiving an input query including an original query concept and at least one scenario identifier, the at least one scenario identifier being associated with at least one of the relationship links; a database of flee-text documents, wherein each document is indexed via one or more indexing concepts formed based on one or more words from the predefined vocabulary set; one or more processors coupled to the input, each of the one or more processors being operable to execute one or more computer instructions which: generate the indexing concepts for the free-text documents based on the one or more words from the predefined vocabulary set, wherein the program instructions which generate the indexing concepts include computer instructions for: maintaining a plurality of data structures mapping each of the plurality of concepts in the knowledge source to all words appearing in the concept; receiving a particular one of the free-text documents; identifying based on the plurality of data structures the one or more of the plurality of concepts in the knowledge source mapped to a set of words appearing in the particular one of the free-text documents; and returning the one or more identified concepts as candidate index concepts for the particular one of the free-text documents; automatically generate an expanded input query including both the original query concept and one or more additional query concepts, the one or more additional query concepts being selected from one or more first particular semantic groupings of the concepts in the knowledge source that have a specific relationship link with a second particular semantic grouping of the concepts containing the original query concept, the specific relationship link being identified by the at least one scenario identifier, wherein the computer instructions which automatically generate the expanded input query further include computer instructions which: filter candidate expansion concepts not included in the one or more first particular semantic groupings of the concepts in the knowledge source; and return the one or more additional query concepts based on the filtering; compare the expanded input query with the indexing concepts for the free-text documents; and return one or more of the free-text documents that satisfy the expanded input query based on the comparison. 3. The system of claim 1 , wherein the processor is further operable to execute computer instructions which filter the candidate index concepts based on a filter selected from a group consisting of symbol type filter, term length filter, coverage filter, subset filter, range filter, and semantic filter.

9. The data processing system of claim 8 , where in executing the instructions to place the contents of the include file in-line within the parsed information, the processing unit executes instructions to expand a substitution tag associated with the contents of the include file within the parsed information.

9. The data processing system of claim 8 , where in executing the instructions to place the contents of the include file in-line within the parsed information, the processing unit executes instructions to expand a substitution tag associated with the contents of the include file within the parsed information. 10. The data processing system of claim 9 , where in executing the instructions to place the contents of the include file in-line within the parsed information and to expand the substitution tag, the processing unit executes instructions to place the contents of the include file and the expanded substitution tag within a <style> element within the parsed information.

2. The interaction system according to claim 1 , wherein an amount of video frame images in the multimedia material is plural.

2. The interaction system according to claim 1 , wherein an amount of video frame images in the multimedia material is plural. 3. The interaction system according to claim 2 , wherein the comment comprises an annotated behavior done by the user who is watching the multimedia material, an annotated time, which corresponds to the timestamp that the annotated behavior is done in duration of playing the multimedia material, said annotated position, or a combination thereof.

1. A method of enabling disambiguation of an input into a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a memory having a plurality of objects stored therein, the plurality of objects including a plurality of language objects, the input apparatus including a plurality of input members, each of at least a portion of the input members of the plurality of input members having a plurality of linguistic elements assigned thereto, the method comprising: receiving on the handheld electronic device data including one or more language objects; identifying, from among the one or more language objects, one or more proper language objects that have an upper case character as a first character; determining that one or more of the identified proper language objects includes the same characters as one of the plurality of language objects stored in the memory, wherein the plurality of language objects stored in the memory include a non-upper case character as the first character; storing the identified one or more proper language objects in the memory; detecting an ambiguous input including a number of input member actuations of a number of the input members, wherein at least one of the input members has a plurality of linguistic elements assigned thereto; identifying one or more of the stored proper language objects that corresponds with the ambiguous input; and outputting at least a portion of the one or more stored proper language objects as a proposed disambiguation of the ambiguous input.

1. A method of enabling disambiguation of an input into a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a memory having a plurality of objects stored therein, the plurality of objects including a plurality of language objects, the input apparatus including a plurality of input members, each of at least a portion of the input members of the plurality of input members having a plurality of linguistic elements assigned thereto, the method comprising: receiving on the handheld electronic device data including one or more language objects; identifying, from among the one or more language objects, one or more proper language objects that have an upper case character as a first character; determining that one or more of the identified proper language objects includes the same characters as one of the plurality of language objects stored in the memory, wherein the plurality of language objects stored in the memory include a non-upper case character as the first character; storing the identified one or more proper language objects in the memory; detecting an ambiguous input including a number of input member actuations of a number of the input members, wherein at least one of the input members has a plurality of linguistic elements assigned thereto; identifying one or more of the stored proper language objects that corresponds with the ambiguous input; and outputting at least a portion of the one or more stored proper language objects as a proposed disambiguation of the ambiguous input. 2. The method of claim 1 , further comprising: identifying as a proper language object a language object that is a proper noun.

23. An apparatus according to claim 8, wherein the at least one desired inputted character is displayed distinguishably from other inputted characters.

23. An apparatus according to claim 8, wherein the at least one desired inputted character is displayed distinguishably from other inputted characters. 24. An apparatus according to claim 23, wherein the parameters comprise information for modifying inputted characters.

16. The method of claim 14 wherein encrypting the captured information includes encrypting the captured information using a public/private key pair.

16. The method of claim 14 wherein encrypting the captured information includes encrypting the captured information using a public/private key pair. 22. The method of claim 16 wherein the public/private key pair includes information identifying the scanner.

1. A multimodal control device comprising for each modality type, a browser for interpreting content in accordance with modality type and performing interaction with a user, wherein content containing an input focus item currently subject to input is generated from document data having a plurality of data input items, which are stored in a storage unit, said content being within a data input item range in accordance with the characteristics of each modality, and output to each browser, the multimodal control device comprising: a computer executing moving input currently subject to input in the document data and managing the moved input item currently subject to input as an input focus item, in response to receiving a processing request from the browser; referring to a content granularity definition file which stores a correspondency between the modality types and the data input item range of content to be generated in the modality; specifying a data input item range containing the input focus item from the document data, according to the referred content granularity definition file; generating content containing the specified data input item range; and transmitting the generated content containing the specified data input item range to a browser corresponding to the modality to display the generated content.

1. A multimodal control device comprising for each modality type, a browser for interpreting content in accordance with modality type and performing interaction with a user, wherein content containing an input focus item currently subject to input is generated from document data having a plurality of data input items, which are stored in a storage unit, said content being within a data input item range in accordance with the characteristics of each modality, and output to each browser, the multimodal control device comprising: a computer executing moving input currently subject to input in the document data and managing the moved input item currently subject to input as an input focus item, in response to receiving a processing request from the browser; referring to a content granularity definition file which stores a correspondency between the modality types and the data input item range of content to be generated in the modality; specifying a data input item range containing the input focus item from the document data, according to the referred content granularity definition file; generating content containing the specified data input item range; and transmitting the generated content containing the specified data input item range to a browser corresponding to the modality to display the generated content. 8. The multimodal control device according to claim 1 , wherein the document data comprises a definition file in which content corresponding to modality type is defined for each data input item, wherein the content generating, in accordance with modality type and input focus item, reads content for each modality corresponding to the relevant data input item from the definition file.

1. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; and generating a heat map for the video file, wherein the heat map comprises a graphical display which indicates offset locations of words within the video file with the highest rankings, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words.

1. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; and generating a heat map for the video file, wherein the heat map comprises a graphical display which indicates offset locations of words within the video file with the highest rankings, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. 6. The computer-implemented method of generating automated tags for the video file as in claim 1 , further comprising: establishing a top concepts threshold value; determining that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associating information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file.

1. A computer-implemented method comprising: receiving data including (i) audio data that encodes a spoken natural language query, and (ii) environmental audio data; obtaining a transcription of the spoken natural language query; determining a particular content type associated with one or more keywords in the transcription; providing at least a portion of the environmental audio data to a content recognition engine; and identifying a content item that (i) has been output by the content recognition engine, and (ii) matches the particular content type associated with the one or more keywords in the transcription.

1. A computer-implemented method comprising: receiving data including (i) audio data that encodes a spoken natural language query, and (ii) environmental audio data; obtaining a transcription of the spoken natural language query; determining a particular content type associated with one or more keywords in the transcription; providing at least a portion of the environmental audio data to a content recognition engine; and identifying a content item that (i) has been output by the content recognition engine, and (ii) matches the particular content type associated with the one or more keywords in the transcription. 7. The computer-implemented method of claim 1 , wherein determining the particular content type further includes identifying the one or more keywords using one or more databases that, for each of multiple content types, maps at least one of the keywords to at least one of the multiple content types.

7. A system comprising: a first non-transitory computer-readable storage medium having stored thereon computer executable program code which, when executed on a computer system, causes the computer system to perform steps including, generate a Service Adaptation Definition Language (SADL) definition for each of a plurality of business entity types, the SADL definition being based on an intermediate representation of each of the plurality of business entities, and publish the SADL definition as service of a SADL engine, and a second non-transitory computer-readable storage medium having stored thereon computer executable program code which, when executed on a computer system, causes the computer system to perform steps comprising: discover the SADL definition, and display, on a user interface, a representation of the SADL definition, the user interface configured to enable selection of two or more business entity types each associated with a different model layer framework, the user interface also configured to enable definition of a new user interface using the first and second business entity types, wherein the new user interface works with the different model layer frameworks of the two or more business entity types.

7. A system comprising: a first non-transitory computer-readable storage medium having stored thereon computer executable program code which, when executed on a computer system, causes the computer system to perform steps including, generate a Service Adaptation Definition Language (SADL) definition for each of a plurality of business entity types, the SADL definition being based on an intermediate representation of each of the plurality of business entities, and publish the SADL definition as service of a SADL engine, and a second non-transitory computer-readable storage medium having stored thereon computer executable program code which, when executed on a computer system, causes the computer system to perform steps comprising: discover the SADL definition, and display, on a user interface, a representation of the SADL definition, the user interface configured to enable selection of two or more business entity types each associated with a different model layer framework, the user interface also configured to enable definition of a new user interface using the first and second business entity types, wherein the new user interface works with the different model layer frameworks of the two or more business entity types. 8. The system of claim 7 , wherein the SADL definition is programming language independent of a model layer framework.

8. The method of claim 1 , further comprising before the receiving: detecting executable content within the at least one network of an enterprise with the at least one of a plurality of collection agents disposed within the at least one network of the enterprise; copying the executable content; and distributing the executable content copies to the central analysis server.

8. The method of claim 1 , further comprising before the receiving: detecting executable content within the at least one network of an enterprise with the at least one of a plurality of collection agents disposed within the at least one network of the enterprise; copying the executable content; and distributing the executable content copies to the central analysis server. 12. The method of claim 8 , wherein the collection agent resides at a strategic point in the enterprise infrastructure, the strategic point being selected from the group consisting of: a network edge, a major subnet division, and a router.

13. A computer system, comprising: a memory subsystem; and a processor coupled to the memory subsystem, wherein the memory subsystem stores code that when executed by the processor causes the processor to: receive input that corresponds to a selected portion of an image that is included within a document, wherein the input includes location coordinates for the selected portion of the image in the document, and wherein the location coordinates provide a location portion that identifies a location of the selected portion of the image within the document; and create search enriched metadata for the document, wherein the search enriched metadata includes a text portion that provides one or more search terms that are associated with the selected portion of the image and the location portion.

13. A computer system, comprising: a memory subsystem; and a processor coupled to the memory subsystem, wherein the memory subsystem stores code that when executed by the processor causes the processor to: receive input that corresponds to a selected portion of an image that is included within a document, wherein the input includes location coordinates for the selected portion of the image in the document, and wherein the location coordinates provide a location portion that identifies a location of the selected portion of the image within the document; and create search enriched metadata for the document, wherein the search enriched metadata includes a text portion that provides one or more search terms that are associated with the selected portion of the image and the location portion. 15. The computer system claim 13 , wherein the memory subsystem stores additional code that when executed by the processor causes to processor to: store the search enriched metadata in a header that is associated with or part of the document or the image.

18. A computer program product tangibly stored on a computer readable hardware storage device, the computer program product comprising instructions for causing a computer processor device to: receive one or more text inputs corresponding to transaction requests; analyze the text inputs using natural language processing to build added information from the one or more transaction requests; provide added information based on results of analyzing the transaction requests by the natural language processing, search a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response to trigger a facility to present additional information about the key concept; build by a conversational engine, a conversation based on the transaction requests and key concept; statistically analyze the information stored in a database to derive useful market data based on the added information; track interactions with the user; store information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generate voice-synthesized follow-up responses in accordance with the transaction requests through an avatar, with the voice-synthesized, follow-up responses based on information stored in the database, including the statistically analyzed added information regarding the transactions; receive subsequent text inputs from the user in response to the voice-synthesized, follow-up responses; and analyze the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take with respect to the user; and cause the determined action to occur.

18. A computer program product tangibly stored on a computer readable hardware storage device, the computer program product comprising instructions for causing a computer processor device to: receive one or more text inputs corresponding to transaction requests; analyze the text inputs using natural language processing to build added information from the one or more transaction requests; provide added information based on results of analyzing the transaction requests by the natural language processing, search a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response to trigger a facility to present additional information about the key concept; build by a conversational engine, a conversation based on the transaction requests and key concept; statistically analyze the information stored in a database to derive useful market data based on the added information; track interactions with the user; store information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generate voice-synthesized follow-up responses in accordance with the transaction requests through an avatar, with the voice-synthesized, follow-up responses based on information stored in the database, including the statistically analyzed added information regarding the transactions; receive subsequent text inputs from the user in response to the voice-synthesized, follow-up responses; and analyze the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take with respect to the user; and cause the determined action to occur. 20. The computer program product of claim 18 wherein one of the transactions is a request as to order status for an order being tracked in the database.

28. The method of claim 18 , wherein the input communication is routed based on the task-type classification decision.

28. The method of claim 18 , wherein the input communication is routed based on the task-type classification decision. 29. The method of claim 28 , wherein a task objective is performed after the input communication is routed.

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

6. A method, implemented at least partially by a handheld electronic book reader device, the method comprising: under control of one or more systems of the handheld electronic book reader device configured with executable instructions, generating a searchable item index of terms in an electronic item; and generating a searchable master index of terms in the electronic item and other electronic items in a collection of electronic items stored in memory of the handheld electronic book reader device, wherein the master index comprises a list of terms used in electronic items in the collection and, for each term, a reference to one or more item index entries for the respective term, and wherein each reference to an item index entry comprises an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item. 13. The method of claim 6 , wherein the master index of terms is organized alphabetically.

21. A system, comprising: one or more processors; and a computer-readable storage device coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for providing an explanatory electronic document, the operations comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in a knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string.

21. A system, comprising: one or more processors; and a computer-readable storage device coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for providing an explanatory electronic document, the operations comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in a knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string. 22. The system of claim 21 , wherein semantic user profile association comprises: determining respective scores for each peer user profile in the superset of peer user profiles based on the user profile and the knowledge graph; and including a peer user profile in the set of peer user profiles based on the respective score.

9. A system for scoring likelihood of success of revised queries suggested for an original query, comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: maintaining log files of user clicks on results provided in response to the revised queries suggested for the original query, the log files including data representing features associated with the original query and the revised queries, and a respective feature value for each feature; selecting a condition, wherein the condition specifies one or more feature values for a corresponding one or more features; selecting the revised queries that, for a particular feature, are associated with a feature value that matches one or more of the feature values specified by the condition for the particular feature; collecting click data for the selected revised queries from the log files, the click data including click length data, wherein a long click on a result for a particular revised query in the log files is taken as indicating a success of the particular revised query; analyzing the click data for the selected revised queries to determine a weight for the condition; formulating a rule, wherein the rule includes the condition and the weight; and adding the rule to a predictive model, wherein the model includes a set of rules that contribute to a prediction of a respective likelihood of success for the revised queries.

9. A system for scoring likelihood of success of revised queries suggested for an original query, comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: maintaining log files of user clicks on results provided in response to the revised queries suggested for the original query, the log files including data representing features associated with the original query and the revised queries, and a respective feature value for each feature; selecting a condition, wherein the condition specifies one or more feature values for a corresponding one or more features; selecting the revised queries that, for a particular feature, are associated with a feature value that matches one or more of the feature values specified by the condition for the particular feature; collecting click data for the selected revised queries from the log files, the click data including click length data, wherein a long click on a result for a particular revised query in the log files is taken as indicating a success of the particular revised query; analyzing the click data for the selected revised queries to determine a weight for the condition; formulating a rule, wherein the rule includes the condition and the weight; and adding the rule to a predictive model, wherein the model includes a set of rules that contribute to a prediction of a respective likelihood of success for the revised queries. 10. The system of claim 9 , wherein the operations further comprise: applying the original query and the revised queries to the predictive model to obtain confidence measures for the revised queries based on the respective likelihood of success.

1. A method comprising the computer-implemented steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages.

1. A method comprising the computer-implemented steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages. 4. The method of claim 1 , wherein the step of said XML processor generating said one or more messages includes generating said one or more messages that are transmitted in an output stream.

9. The method of claim 1 , further comprising: enabling a user to include a reference to an operand of extended representation in the source code; generating a token corresponding to the operand of extended representation; and processing the token to generate a node corresponding to the operand of extended representation.

9. The method of claim 1 , further comprising: enabling a user to include a reference to an operand of extended representation in the source code; generating a token corresponding to the operand of extended representation; and processing the token to generate a node corresponding to the operand of extended representation. 10. The method of claim 9 , wherein the operand of extended representation comprises one of an image, video, and audio segment.

5. The method of claim 3 , wherein using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence comprises: maintaining normalized dominance thresholds, there being one normalized dominance threshold corresponding to each first text sequence cognitive motivation orientation weight score in one-to-one correspondence; identifying as dominant for the first text sequence each cognitive motivation orientation for which the corresponding normalized first text sequence cognitive motivation orientation weight score exceeds a corresponding normalized dominance threshold; and identifying as non-dominant for the first text sequence each cognitive motivation orientation for which the corresponding first text sequence cognitive motivation orientation weight score does not exceed the corresponding normalized dominance threshold.

5. The method of claim 3 , wherein using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence comprises: maintaining normalized dominance thresholds, there being one normalized dominance threshold corresponding to each first text sequence cognitive motivation orientation weight score in one-to-one correspondence; identifying as dominant for the first text sequence each cognitive motivation orientation for which the corresponding normalized first text sequence cognitive motivation orientation weight score exceeds a corresponding normalized dominance threshold; and identifying as non-dominant for the first text sequence each cognitive motivation orientation for which the corresponding first text sequence cognitive motivation orientation weight score does not exceed the corresponding normalized dominance threshold. 6. The method of claim 5 , wherein: using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence further comprises: ranking the first text sequence cognitive motivation orientations, the ranking being according to a difference between each normalized first text sequence cognitive motivation orientation weight score and its respective corresponding normalized dominance threshold, to thereby obtain ranked normalized first text sequence cognitive motivation orientation weight scores; wherein: the first dominant cognitive motivation orientation set comprises m or fewer cognitive motivation orientations, where m is a positive integer; and wherein where m or more cognitive motivation orientations are identified as dominant for the first text sequence, the first dominant cognitive motivation orientation set comprises the m most highly ranked cognitive motivation orientations.

1. A computer-implemented user interface method of presenting results of a search customized using content preferences learned about a user, the method comprising: receiving a user input action for interacting with an application on a user device; in response to receiving the user input action, sending query information to a search engine, the query information including user information, the user information including (i) context information describing an environment in which the user input action was received, the context information adapted into a syntax understandable by the search engine, and (ii) a user signature representing content preferences learned about the user; generating customized search results by receiving a set of search results and auxiliary information from the search engine in response to sending the query information, the auxiliary information including information describing attributes of each search result of the set of search results that led to each search result being chosen by the search engine; ordering the set of search results based at least in part on the auxiliary information; and presenting, to the user, the ordered set of search results customized using the content preferences learned about the user.

1. A computer-implemented user interface method of presenting results of a search customized using content preferences learned about a user, the method comprising: receiving a user input action for interacting with an application on a user device; in response to receiving the user input action, sending query information to a search engine, the query information including user information, the user information including (i) context information describing an environment in which the user input action was received, the context information adapted into a syntax understandable by the search engine, and (ii) a user signature representing content preferences learned about the user; generating customized search results by receiving a set of search results and auxiliary information from the search engine in response to sending the query information, the auxiliary information including information describing attributes of each search result of the set of search results that led to each search result being chosen by the search engine; ordering the set of search results based at least in part on the auxiliary information; and presenting, to the user, the ordered set of search results customized using the content preferences learned about the user. 10. The method of claim 1 , wherein the search engine includes a recommendation engine, the recommendation engine recommending search results based on at least a portion of the user information.

1. A method of converting a regression test script of an automated testing tool into a function, said method comprising: receiving said regression test script comprising at least one object, wherein said object describes at least one action initiated by said regression test script to test a software application; inserting a physical description related to said object into said regression test script, said physical description copied from an external GUI map; assigning a variable name to said physical description; compiling said regression test script comprising said object and said physical description referenced by the variable name to generate said function such that a regression test is subsequently performed according to said regression test script by invoking said function and does not require the external GUI map; storing said function in a centralized library accessible by a plurality of users allowing said function to be shared between different regression tests and reused for said subsequent regression test, wherein the function comprises the regression test script and is executed to implement the regression test script; and testing the software application by invoking the stored function, wherein the stored function performs the regressive test without the external GUI map.

1. A method of converting a regression test script of an automated testing tool into a function, said method comprising: receiving said regression test script comprising at least one object, wherein said object describes at least one action initiated by said regression test script to test a software application; inserting a physical description related to said object into said regression test script, said physical description copied from an external GUI map; assigning a variable name to said physical description; compiling said regression test script comprising said object and said physical description referenced by the variable name to generate said function such that a regression test is subsequently performed according to said regression test script by invoking said function and does not require the external GUI map; storing said function in a centralized library accessible by a plurality of users allowing said function to be shared between different regression tests and reused for said subsequent regression test, wherein the function comprises the regression test script and is executed to implement the regression test script; and testing the software application by invoking the stored function, wherein the stored function performs the regressive test without the external GUI map. 6. The method as recited in claim 1 further comprising: declaring said variable name in said regression test script.

22. A portable computing device, comprising: a user interface having a plurality of user interface controls and a menu having a list of navigation icons, each of which corresponds to a navigation command for assisting the user in navigating the plurality of media items; a communications port for receiving audio prompts and media items from the host system, the audio prompts describing at least one of the user interface controls or one of the media items; a user interface control module that receives user touch events from the user interface, wherein if a user touch event on one of the navigation icons is received, the user interface control module is designed to navigate the plurality of menu items and to play an audibilized navigation command associated with the navigation on which the user touch event is received, wherein the playing is performed only during the touch event, wherein if the user decides not to select the associated navigation icon, then the user terminates the touch event prior to the completion of the playing of the audibilized navigation command, and if the user decides to select the navigation icon associated with the audibilized navigation command, then a selection user input event is received at the navigated to navigation icon that causes the portable computing device to execute the navigation command; a memory that stores the audio prompts and media items.

22. A portable computing device, comprising: a user interface having a plurality of user interface controls and a menu having a list of navigation icons, each of which corresponds to a navigation command for assisting the user in navigating the plurality of media items; a communications port for receiving audio prompts and media items from the host system, the audio prompts describing at least one of the user interface controls or one of the media items; a user interface control module that receives user touch events from the user interface, wherein if a user touch event on one of the navigation icons is received, the user interface control module is designed to navigate the plurality of menu items and to play an audibilized navigation command associated with the navigation on which the user touch event is received, wherein the playing is performed only during the touch event, wherein if the user decides not to select the associated navigation icon, then the user terminates the touch event prior to the completion of the playing of the audibilized navigation command, and if the user decides to select the navigation icon associated with the audibilized navigation command, then a selection user input event is received at the navigated to navigation icon that causes the portable computing device to execute the navigation command; a memory that stores the audio prompts and media items. 23. A portable computing device as recited in claim 22 , wherein the portable computing device is one of: a media player, a mobile phone or a personal digital assistant.

13. The method as recited in claim 12 , wherein parsing includes and reformatting the contract text document to eliminate less relevant information to permit comparison with the pattern matrices and contract data tags.

13. The method as recited in claim 12 , wherein parsing includes and reformatting the contract text document to eliminate less relevant information to permit comparison with the pattern matrices and contract data tags. 14. The method as recited in claim 13 , wherein reformatting includes reformatting the contract text document by inserting formatting bookmarks.

29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a search engine server, including instructions configured to cause a data processing apparatus to: detect a request for a search for search results, wherein the request for the search includes topic data describing a search topic, and wherein the request does not include a request for an agent; perform a search for information associated with the search topic; determine a search result, wherein the search result includes the information associated with the search topic; process, by the search engine server, status data stored remotely within an agent search server, wherein the search engine server operates remotely from the agent search server and communicates with the agent search server over a network, wherein the status data corresponds to one or more active relevant agents, wherein the one or more active relevant agents are associated with one or more real-time interaction options, wherein agents are active or inactive, and wherein agents are relevant or irrelevant to the search topic; generate an agent search request using the topic data, wherein the agent search request is separate from the request for the search and includes the topic data describing the search topic, wherein the agent search request is used to determine the one or more active relevant agents associated with the search topic, and wherein agents are determined to be relevant by matching the search topic with a topic included in one or more profiles of the one or more active relevant agents; use the status data to determine whether to associate a real-time interactive element with the search result; associate a real-time interactive element with the search result, wherein the real-time interactive element is separate from the search result, and wherein the real-time interactive element is displayed concurrently with the search result; and detect data corresponding to a selection of the real-time interactive element associated with the search result, wherein the real-time interactive element is associated with one or more agents based on the status data, wherein the selection of the real-time interactive element facilitates a real-time interaction option among two or more devices, and wherein at least one device is associated with an active relevant agent associated with the search topic.

29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a search engine server, including instructions configured to cause a data processing apparatus to: detect a request for a search for search results, wherein the request for the search includes topic data describing a search topic, and wherein the request does not include a request for an agent; perform a search for information associated with the search topic; determine a search result, wherein the search result includes the information associated with the search topic; process, by the search engine server, status data stored remotely within an agent search server, wherein the search engine server operates remotely from the agent search server and communicates with the agent search server over a network, wherein the status data corresponds to one or more active relevant agents, wherein the one or more active relevant agents are associated with one or more real-time interaction options, wherein agents are active or inactive, and wherein agents are relevant or irrelevant to the search topic; generate an agent search request using the topic data, wherein the agent search request is separate from the request for the search and includes the topic data describing the search topic, wherein the agent search request is used to determine the one or more active relevant agents associated with the search topic, and wherein agents are determined to be relevant by matching the search topic with a topic included in one or more profiles of the one or more active relevant agents; use the status data to determine whether to associate a real-time interactive element with the search result; associate a real-time interactive element with the search result, wherein the real-time interactive element is separate from the search result, and wherein the real-time interactive element is displayed concurrently with the search result; and detect data corresponding to a selection of the real-time interactive element associated with the search result, wherein the real-time interactive element is associated with one or more agents based on the status data, wherein the selection of the real-time interactive element facilitates a real-time interaction option among two or more devices, and wherein at least one device is associated with an active relevant agent associated with the search topic. 31. The computer-program product of claim 29 , wherein the status data is active or inactive, wherein the status data is active when a relevant agent associated with the topic data is active, and wherein the status data is inactive when a relevant agent associated with the topic data is inactive.

19. A system for generating a structured query language (SQL) script based on a template, the system comprises: memory operable to store a data model, a plurality of instructions, and a plurality of template strings and the data model comprising a plurality of objects; and one or more processors operable to: select one object from the plurality of objects in the data model; automatically select, without user input, at least one first instruction based, at least in part, on a type of the selected object; select a first template string based on the selected at least one first instruction; select a second object from the plurality of objects in the data model; select at least one second instruction based, at least in part, on a type of the second object; select a second template string based on the selected at least one second instruction; automatically, and without user input, sort and concatenate the template strings from the selected objects in an order identified by the first and second instructions and based on the types of the first and second objects; and automatically generate at least a portion of the SQL script based on the sorted and concatenated first and second template strings in the order identified by the first and second instructions.

19. A system for generating a structured query language (SQL) script based on a template, the system comprises: memory operable to store a data model, a plurality of instructions, and a plurality of template strings and the data model comprising a plurality of objects; and one or more processors operable to: select one object from the plurality of objects in the data model; automatically select, without user input, at least one first instruction based, at least in part, on a type of the selected object; select a first template string based on the selected at least one first instruction; select a second object from the plurality of objects in the data model; select at least one second instruction based, at least in part, on a type of the second object; select a second template string based on the selected at least one second instruction; automatically, and without user input, sort and concatenate the template strings from the selected objects in an order identified by the first and second instructions and based on the types of the first and second objects; and automatically generate at least a portion of the SQL script based on the sorted and concatenated first and second template strings in the order identified by the first and second instructions. 21. The system of claim 19 , the one or more processors further operable to select the data model from a plurality of data models.

6. A system for compiling data, comprising at least one computer device that performs a method, comprising: receiving an input query in a first language; translating the input query to a nested relational algebra (NRA) in the form of a first intermediate representation (IR), wherein the first IR comprises a high-level functional language including algebraic operators; implementing a set of algorithms of the algebraic operators to compile at least some of the first IR into a second IR, wherein the second IR comprises a hybrid language which utilizes a data-flow language and a set of lower-level extensions, and wherein the second IR is optimized by utilizing a set of specific optimizations targeting a part of the second IR that was compiled from a set of algebraic operators of the first IR, wherein the first IR is optimized by utilizing a set of functional optimizations on a set of non-algebra portions of the first IR, wherein the second IR is further optimized by utilizing a set of data-flow optimizations; and compiling at least one of: the first IR and the second IR, into a low-level code.

6. A system for compiling data, comprising at least one computer device that performs a method, comprising: receiving an input query in a first language; translating the input query to a nested relational algebra (NRA) in the form of a first intermediate representation (IR), wherein the first IR comprises a high-level functional language including algebraic operators; implementing a set of algorithms of the algebraic operators to compile at least some of the first IR into a second IR, wherein the second IR comprises a hybrid language which utilizes a data-flow language and a set of lower-level extensions, and wherein the second IR is optimized by utilizing a set of specific optimizations targeting a part of the second IR that was compiled from a set of algebraic operators of the first IR, wherein the first IR is optimized by utilizing a set of functional optimizations on a set of non-algebra portions of the first IR, wherein the second IR is further optimized by utilizing a set of data-flow optimizations; and compiling at least one of: the first IR and the second IR, into a low-level code. 10. The system of claim 6 , the method further comprising: wherein the low-level code is selected from a group comprising: assembly code, virtual machine code, and virtual machine code instructions.

9. A control method in a document reading apparatus having a conveying unit configured to convey a document, a reading unit configured to read an image of the document conveyed by the conveying unit, and a detecting unit configured to detect multi-feed of the document conveyed by the conveying unit, the control method comprising: making a setting indicating whether, based on the detecting unit detecting multi-feed of the document, conveyance of the document by the conveying unit is to stop; stopping conveyance of the document by the conveying unit in a case where the made setting indicates that, in response to the detecting unit detecting multi-feed of the document, the conveyance of the document by the conveying unit is to stop; and displaying a screen, wherein, in a case where the made setting indicates that, in response to the detecting unit detecting multi-feed of the document, the conveyance of the document by the conveying unit is to stop, displaying includes displaying a screen for receiving, from a user, an instruction not to stop conveyance of the document by the conveying unit, even in a case where the detecting unit detects multi-feed of the document.

9. A control method in a document reading apparatus having a conveying unit configured to convey a document, a reading unit configured to read an image of the document conveyed by the conveying unit, and a detecting unit configured to detect multi-feed of the document conveyed by the conveying unit, the control method comprising: making a setting indicating whether, based on the detecting unit detecting multi-feed of the document, conveyance of the document by the conveying unit is to stop; stopping conveyance of the document by the conveying unit in a case where the made setting indicates that, in response to the detecting unit detecting multi-feed of the document, the conveyance of the document by the conveying unit is to stop; and displaying a screen, wherein, in a case where the made setting indicates that, in response to the detecting unit detecting multi-feed of the document, the conveyance of the document by the conveying unit is to stop, displaying includes displaying a screen for receiving, from a user, an instruction not to stop conveyance of the document by the conveying unit, even in a case where the detecting unit detects multi-feed of the document. 10. The control method according to claim 9 , further comprising receiving, via a receiving unit from the user through the displayed screen, the instruction not to stop conveyance of the document by the conveying unit, even in the case where the detecting unit detects multi-feed of the document, wherein, in a case where the receiving unit has received the instruction, stopping includes not stopping the conveyance of the document by the conveying unit, even in the case where the detecting unit detects multi-feed of the document, and wherein, in a case where the receiving unit has not received the instruction, stopping includes stopping the conveyance of the document by the conveying unit in the case where the detecting unit detects multi-feed of the document.

9. Non-transitory physical computer storage comprising computer-executable instructions that, when executed by one or more processors, direct a computing system to perform a method for accessing variables in an application, the method comprising: accessing application source code associated with an application; parsing the application source code to identify a set of variables, the parsing comprising distinguishing variables from other programming constructs; for each variable from the set of variables: determining a variable type of the variable; in response to determining that the variable type is a complex variable, parsing the complex variable; in response to determining that the variable is associated with a database, resolving a variable name and determining whether the variable exists in a data dictionary associated with the database; determining metadata associated with the variable based, at least in part, on the variable type; providing an identity of the variable and the metadata for the variable to a user interface thereby enabling a user to access the variable; accessing test code for the application source code; identifying, for each variable from the set of variables, an expected variable type for the variable based on the test code; determining whether the variable type of each variable matches the expected variable type for the variable; in response to determining that the variable type of each variable matches the expected variable type for the variable, executing the test code for the application source code; and in response to determining that the variable type of each variable does not match the expected variable type for the variable; identifying modifications to the test code; regenerating test code with the identified modifications; and executing the regenerated test code.

9. Non-transitory physical computer storage comprising computer-executable instructions that, when executed by one or more processors, direct a computing system to perform a method for accessing variables in an application, the method comprising: accessing application source code associated with an application; parsing the application source code to identify a set of variables, the parsing comprising distinguishing variables from other programming constructs; for each variable from the set of variables: determining a variable type of the variable; in response to determining that the variable type is a complex variable, parsing the complex variable; in response to determining that the variable is associated with a database, resolving a variable name and determining whether the variable exists in a data dictionary associated with the database; determining metadata associated with the variable based, at least in part, on the variable type; providing an identity of the variable and the metadata for the variable to a user interface thereby enabling a user to access the variable; accessing test code for the application source code; identifying, for each variable from the set of variables, an expected variable type for the variable based on the test code; determining whether the variable type of each variable matches the expected variable type for the variable; in response to determining that the variable type of each variable matches the expected variable type for the variable, executing the test code for the application source code; and in response to determining that the variable type of each variable does not match the expected variable type for the variable; identifying modifications to the test code; regenerating test code with the identified modifications; and executing the regenerated test code. 14. The non-transitory physical computer storage of claim 9 , wherein the data dictionary specifies each variable defined at the database.

5. The computer implemented method of claim 1 , further comprising: automatically removing the bookmark from the first selected page and continuing to display the second selected page in response to a second predefined gesture other than the first predefined gesture.

5. The computer implemented method of claim 1 , further comprising: automatically removing the bookmark from the first selected page and continuing to display the second selected page in response to a second predefined gesture other than the first predefined gesture. 6. The computer implemented method of claim 5 , wherein the second predefined gesture comprises: a swipe leading to the removal of the first finger from the touchscreen.

15. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving voice input from a user and processing the voice input using natural language processing to produce a textual representation, the textual representation including a plurality of words; identifying, from the textual representation, an actionable intent from among a plurality of actionable intents recognizable by the electronic device, the actionable intents corresponding to tasks that can be performed by the electronic device; identifying a keyword in the textual representation; determining whether one or more words adjacent to the keyword correspond to a textual identifier of a collection of textual identifiers; and wherein, responsive to the identified actionable intent and a determination that the one or more adjacent words correspond to a properly formatted textual identifier, the digital assistant replaces the keyword and the one or more adjacent words with the textual identifier, wherein the textual identifier is a known hashtag or a username, wherein, if the textual identifier is a known hashtag, the collection includes hashtags that were previously identified by a social network, wherein if the textual identifier is a username the collection is a set of usernames that are registered in the social network.

15. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving voice input from a user and processing the voice input using natural language processing to produce a textual representation, the textual representation including a plurality of words; identifying, from the textual representation, an actionable intent from among a plurality of actionable intents recognizable by the electronic device, the actionable intents corresponding to tasks that can be performed by the electronic device; identifying a keyword in the textual representation; determining whether one or more words adjacent to the keyword correspond to a textual identifier of a collection of textual identifiers; and wherein, responsive to the identified actionable intent and a determination that the one or more adjacent words correspond to a properly formatted textual identifier, the digital assistant replaces the keyword and the one or more adjacent words with the textual identifier, wherein the textual identifier is a known hashtag or a username, wherein, if the textual identifier is a known hashtag, the collection includes hashtags that were previously identified by a social network, wherein if the textual identifier is a username the collection is a set of usernames that are registered in the social network. 19. The electronic device of claim 15 , wherein the textual identifier is a concatenation of a symbol and the one or more adjacent words without interstitial spaces.

16. The method of claim 1 , further comprising, based on the identified type, determining a ranking scheme for use in determining the respective rank score for the document associated with the respective geographic feature.

16. The method of claim 1 , further comprising, based on the identified type, determining a ranking scheme for use in determining the respective rank score for the document associated with the respective geographic feature. 17. The method of claim 16 wherein the ranking scheme comprises at least one of area based ranking, density based ranking, aggregate based ranking, visual prominence ranking, transportation network ranking, or network based ranking.

5. The method of claim 1 , wherein the remaining portion of the client device display includes a window corresponding to the window with the active text caret.

5. The method of claim 1 , wherein the remaining portion of the client device display includes a window corresponding to the window with the active text caret. 8. The method of claim 5 , wherein the instructions for automatic adjustment concern further changing size of the text within the corresponding window.

1. A non-transitory computer readable medium encoded with instructions executable by a processor of a computing system for performing vector comparison in natural language processing, the instructions comprising instructions for: receiving a target vector and a source vector, the target vector including a first target vector dimension comprising a first word or phrase and a second target vector dimension comprising a second word or phrase; determining a first number of possible magnitudes that are assignable to the first target vector dimension, wherein the magnitudes comprise weights; determining a number of possible features associated with the source vector; assigning a magnitude from the first number of possible magnitudes to the first target vector dimension based on a first feature of the determined number of possible features associated with the source vector; determining a second number of magnitudes that are assignable to the second target vector dimension, wherein the magnitudes comprise weights; assigning a magnitude from the second number of magnitudes to the second target vector dimension based on a second feature of the determined number of features associated with the source vector.

1. A non-transitory computer readable medium encoded with instructions executable by a processor of a computing system for performing vector comparison in natural language processing, the instructions comprising instructions for: receiving a target vector and a source vector, the target vector including a first target vector dimension comprising a first word or phrase and a second target vector dimension comprising a second word or phrase; determining a first number of possible magnitudes that are assignable to the first target vector dimension, wherein the magnitudes comprise weights; determining a number of possible features associated with the source vector; assigning a magnitude from the first number of possible magnitudes to the first target vector dimension based on a first feature of the determined number of possible features associated with the source vector; determining a second number of magnitudes that are assignable to the second target vector dimension, wherein the magnitudes comprise weights; assigning a magnitude from the second number of magnitudes to the second target vector dimension based on a second feature of the determined number of features associated with the source vector. 7. The non-transitory computer readable medium of claim 1 , wherein assigning a magnitude from the number of magnitudes assigned to the target vector dimension based on a feature of the determined number of features associated with the source vector comprises: assigning a magnitude from the number of magnitudes based on a magnitude associated with the feature.