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13. The computer-readable storage medium of claim 11 , wherein the seed input information indicates excluding a method associated with the network service identifier or limiting the execution of the network service identifier to one or more methods associated with the network service identifier.

13. The computer-readable storage medium of claim 11 , wherein the seed input information indicates excluding a method associated with the network service identifier or limiting the execution of the network service identifier to one or more methods associated with the network service identifier. 14. The computer-readable storage medium of claim 13 , further comprising executing the network service identifier utilizing the input information to generate the result information based at least in part on the seed input information.

24. The method of claim 22 , in which the manner associated with the first person includes one or more of a manner of speaking by the first person, a manner of rendering the song by the first person or a gesture used by the first person.

24. The method of claim 22 , in which the manner associated with the first person includes one or more of a manner of speaking by the first person, a manner of rendering the song by the first person or a gesture used by the first person. 25. The method of claim 24 , in which the manner of speaking includes one or more of voice of the first person, an accent of the first person, or a tone of voice of the first person.

12. A method for refining a content recommendation made by a user, the method comprising: receiving, through a user interface of a social network application installed on a user device, an indication that a user recommended content displayed in a web browser on the user device, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the web browser, retrieving candidate annotations that describe characteristics of each of the plurality of different content components; updating the user interface presented at the user device with a request for the user to select at least one of the candidate annotations for at least one of the plurality of content components; receiving, through the social network application, a user selection of at least one of the candidate annotations as an annotation for at least one of the plurality of content components; and distributing through a social network the user recommended content with the selected at least one candidate annotation at a presentation location corresponding to the at least one content component of the recommended content.

12. A method for refining a content recommendation made by a user, the method comprising: receiving, through a user interface of a social network application installed on a user device, an indication that a user recommended content displayed in a web browser on the user device, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the web browser, retrieving candidate annotations that describe characteristics of each of the plurality of different content components; updating the user interface presented at the user device with a request for the user to select at least one of the candidate annotations for at least one of the plurality of content components; receiving, through the social network application, a user selection of at least one of the candidate annotations as an annotation for at least one of the plurality of content components; and distributing through a social network the user recommended content with the selected at least one candidate annotation at a presentation location corresponding to the at least one content component of the recommended content. 14. The method of claim 12 , wherein determining that the recommendation made by the user applies to a specific one or more of the plurality of content components of the recommended content includes: determining, from a component reference table stored for the recommended content, one or more content components of the recommended content mapped to the at least one action performed by the user.

13. A computing system comprising memory storing computer executable instructions that cause the computing system to perform a method, the method comprising: indexing source code, the indexing comprising creating index records for a plurality of code elements , wherein the index records for the plurality of code elements comprise structure fields and structure values that correspond to the structure fields; parsing the source code to identify a class or method in the source code; receiving a code structure query comprising at least one field-value expression, wherein the at least one field-value expression comprises a field term and a value term; identifying one or more of the index records that conform to the code structure query, wherein the identified one or more of the index records comprise structure fields and structure values that correspond to the at least one field-value expression, wherein the field term corresponds to field identifiers of the structure fields and the value term corresponds to the structure values; sending a list of code structure query results that correspond to the identified one or more of the index records that conform to the code structure query; receiving one or more selections from the list of code structure query results; based on the one or more selections from the list of code structure query results, receiving a code hierarchy, wherein the code hierarchy comprises a list of dependencies identified from an index record for the one or more selections from the list of code structure query results; wherein indexing the source code further comprises generating formatted source code, wherein the formatted source code comprises HTML that displays a first code element of the source code when rendered in a web browser, wherein the formatted source code comprises at least one hyperlink corresponding to a second code element referenced in the source code of the first code element, wherein the second code element corresponds to the class that is referenced in or the method that is called by the first code element, wherein the hyperlink corresponds to a use of the second code element in the first code element; and sending formatted source code corresponding to the one or more selections from the list of code structure query results.

13. A computing system comprising memory storing computer executable instructions that cause the computing system to perform a method, the method comprising: indexing source code, the indexing comprising creating index records for a plurality of code elements , wherein the index records for the plurality of code elements comprise structure fields and structure values that correspond to the structure fields; parsing the source code to identify a class or method in the source code; receiving a code structure query comprising at least one field-value expression, wherein the at least one field-value expression comprises a field term and a value term; identifying one or more of the index records that conform to the code structure query, wherein the identified one or more of the index records comprise structure fields and structure values that correspond to the at least one field-value expression, wherein the field term corresponds to field identifiers of the structure fields and the value term corresponds to the structure values; sending a list of code structure query results that correspond to the identified one or more of the index records that conform to the code structure query; receiving one or more selections from the list of code structure query results; based on the one or more selections from the list of code structure query results, receiving a code hierarchy, wherein the code hierarchy comprises a list of dependencies identified from an index record for the one or more selections from the list of code structure query results; wherein indexing the source code further comprises generating formatted source code, wherein the formatted source code comprises HTML that displays a first code element of the source code when rendered in a web browser, wherein the formatted source code comprises at least one hyperlink corresponding to a second code element referenced in the source code of the first code element, wherein the second code element corresponds to the class that is referenced in or the method that is called by the first code element, wherein the hyperlink corresponds to a use of the second code element in the first code element; and sending formatted source code corresponding to the one or more selections from the list of code structure query results. 16. The computing system of claim 13 , wherein the code structure query further comprises one or more Boolean operators that operate on the at least one field-value expression.

9. A system for stemming terms using behavioral data, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the system to: capture behavioral data for a plurality of users with respect to a plurality of terms; obtain a rule set for stemming in a language, the language including the plurality of terms; obtain a word to be stemmed; in response to determining that only one rule of the rule set is to be used to stem the obtained word, stemming the obtained word using only one rule; or in response to determining that more than one rule of the rule set is to be used in stemming the obtained word: determine a set of forms of the obtained word; determine an output set of forms corresponding to the set of forms, wherein each rule of the more than one rule corresponds to one of the forms in the output set of forms, determine, based at least in part upon the captured behavioral data, a relative measurement value of each form in the set of output forms, and select, based at least in part upon the relative measurement values, at least one form in the output set of forms to be used as a stem for the obtained word.

9. A system for stemming terms using behavioral data, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the system to: capture behavioral data for a plurality of users with respect to a plurality of terms; obtain a rule set for stemming in a language, the language including the plurality of terms; obtain a word to be stemmed; in response to determining that only one rule of the rule set is to be used to stem the obtained word, stemming the obtained word using only one rule; or in response to determining that more than one rule of the rule set is to be used in stemming the obtained word: determine a set of forms of the obtained word; determine an output set of forms corresponding to the set of forms, wherein each rule of the more than one rule corresponds to one of the forms in the output set of forms, determine, based at least in part upon the captured behavioral data, a relative measurement value of each form in the set of output forms, and select, based at least in part upon the relative measurement values, at least one form in the output set of forms to be used as a stem for the obtained word. 10. The system of claim 9 , wherein the word to be stemmed is obtained from a data store storing the behavioral data.

1. A method for creating extensible computer applications with a user interface, by cascading sets of retrieval, computation and update requirement specifications to facilitate repetition, decision and execution control logics, without user input of natural, procedural and programming language and without generating any source codes and executable computers programs; said extensible computer application is composed of unlimited levels of components and sub-components; each component is consists of one or more sets of requirement specifications previously created; newly created components consists of multiple existing components are useable to create higher level components; said method for building applications with no limitation in size and complexity; said method provides database product independent Web based access of databases on the Internet preforming the following steps: a. creating a database dictionary/directory in the form of a two way hierarchical structure with a keyword index for describing existing or new databases tables, columns, and data values; b. creating new databases on the Internet; c. keyword scan by the user in said dictionary to identify available keywords; d. searching said directory by keywords to establish entry points to the directory; e. browsing said directory upward or downward by the user from the said entry points to identify information of interest step by step; f. creating retrieval and computation requirement specifications by the user during the directory browsing process; g. creating update and deletion requirement specifications for existing information and addition of new information during the directory browsing process; h. saving, restoring said requirement specifications by name and submitting said requirement specifications to be executed by the computing engine; i. cascading previously saved requirement specifications as components and sub-components to create a newly named requirement specification which can itself be saved as a component or executed; j. specification of said retrieval/update requirements, repetition and decision control logic from said databases during the directory browsing comprise user: selecting one or more tables from said databases; selecting one or more columns and/or column group from said tables; selecting of one or more data values and/or data value groups and/or data value ranges from said columns; selecting common columns from said selected tables, and criterion for the purpose of integrating multiple tables into a single table; said criterion must be based on the selecting of equal, not equal, greater, smaller, greater or equal, smaller or equal values of the selected common columns; selecting sort columns and/or sort order; selecting group-by columns and/or group-by order from said selected tables; k. specification of said computation requirements, decision and execution control logic from said databases during the directory browsing comprise user: selecting one or more tables from said databases; selecting one or more columns and/or column groups from said tables; selecting one or more data values and/or data value ranges and/or data value groups from said tables; selecting group-by columns and/or group-by order; specifying column aggregation operations; specifying row aggregation operations; creating column algebraic and/or logical expressions known as column formulas in said tables; creating row algebraic and/or logical expressions known as row formulas in said tables; l. operands of said row and column formulas can be expressed symbolically in terms of names or name combinations in said dictionary/directory, operand can also be constants and functions provided by the Web application server; said operand can refer to specific data element, specific row or column in the same or different tables; naming scheme of said operands with specific rules provide a method to address data element, row and column of said tables: said operand can also be the name of a row or column formula defined previously; said row formulas, logical expressions and/or aggregations are automatically applied to all the columns of the row unless restricted by other specification of computation requirements; said column formulas, logical expressions and/or aggregations are automatically applied to all the rows of the column unless restricted by other specification of computation requirements; said sets of retrieval/update and computation requirement specifications can be saved and restored with a given name; said operand can also be the name of a set of requirement specifications saved previously, in which case the requirement specifications will be executed upon submission; said formulas and logical expressions can also be expressed in terms of built-in functions provided by the computing engine with said operands as arguments of said functions to facilitate execution control logics; m. said naming scheme used to name operands in row and column formulas are defined as follows: data elements in any table can be named in the form of X.A.B.C.D; said name addresses the data items of column B in the rows of table A in database X with the value of column C equals D; if said name represents more than one data items, it will be used as an operand of an aggregate or built-in function; if X is omitted in the name, X is defaulted to be the database currently selected: if A is omitted, A is defaulted to be the table currently selected; if B is omitted in the name, expressed as A.C.D of database X, said name references all the rows in table A with the value of column C equal D; if C and D are omitted in the name, expressed as A.B of database X, said name references all the data items in column B of table A; if A, C and D are omitted in the name of an operand, said name references all the data items of column B of the table currently selected; if A, B and C are omitted in the name of an operand, said name references all the rows with data value of the first column of the table currently selected equals D; all names of column and row formulas defined within the same set of requirement specification are unique; all names of requirement specifications saved are unique.

1. A method for creating extensible computer applications with a user interface, by cascading sets of retrieval, computation and update requirement specifications to facilitate repetition, decision and execution control logics, without user input of natural, procedural and programming language and without generating any source codes and executable computers programs; said extensible computer application is composed of unlimited levels of components and sub-components; each component is consists of one or more sets of requirement specifications previously created; newly created components consists of multiple existing components are useable to create higher level components; said method for building applications with no limitation in size and complexity; said method provides database product independent Web based access of databases on the Internet preforming the following steps: a. creating a database dictionary/directory in the form of a two way hierarchical structure with a keyword index for describing existing or new databases tables, columns, and data values; b. creating new databases on the Internet; c. keyword scan by the user in said dictionary to identify available keywords; d. searching said directory by keywords to establish entry points to the directory; e. browsing said directory upward or downward by the user from the said entry points to identify information of interest step by step; f. creating retrieval and computation requirement specifications by the user during the directory browsing process; g. creating update and deletion requirement specifications for existing information and addition of new information during the directory browsing process; h. saving, restoring said requirement specifications by name and submitting said requirement specifications to be executed by the computing engine; i. cascading previously saved requirement specifications as components and sub-components to create a newly named requirement specification which can itself be saved as a component or executed; j. specification of said retrieval/update requirements, repetition and decision control logic from said databases during the directory browsing comprise user: selecting one or more tables from said databases; selecting one or more columns and/or column group from said tables; selecting of one or more data values and/or data value groups and/or data value ranges from said columns; selecting common columns from said selected tables, and criterion for the purpose of integrating multiple tables into a single table; said criterion must be based on the selecting of equal, not equal, greater, smaller, greater or equal, smaller or equal values of the selected common columns; selecting sort columns and/or sort order; selecting group-by columns and/or group-by order from said selected tables; k. specification of said computation requirements, decision and execution control logic from said databases during the directory browsing comprise user: selecting one or more tables from said databases; selecting one or more columns and/or column groups from said tables; selecting one or more data values and/or data value ranges and/or data value groups from said tables; selecting group-by columns and/or group-by order; specifying column aggregation operations; specifying row aggregation operations; creating column algebraic and/or logical expressions known as column formulas in said tables; creating row algebraic and/or logical expressions known as row formulas in said tables; l. operands of said row and column formulas can be expressed symbolically in terms of names or name combinations in said dictionary/directory, operand can also be constants and functions provided by the Web application server; said operand can refer to specific data element, specific row or column in the same or different tables; naming scheme of said operands with specific rules provide a method to address data element, row and column of said tables: said operand can also be the name of a row or column formula defined previously; said row formulas, logical expressions and/or aggregations are automatically applied to all the columns of the row unless restricted by other specification of computation requirements; said column formulas, logical expressions and/or aggregations are automatically applied to all the rows of the column unless restricted by other specification of computation requirements; said sets of retrieval/update and computation requirement specifications can be saved and restored with a given name; said operand can also be the name of a set of requirement specifications saved previously, in which case the requirement specifications will be executed upon submission; said formulas and logical expressions can also be expressed in terms of built-in functions provided by the computing engine with said operands as arguments of said functions to facilitate execution control logics; m. said naming scheme used to name operands in row and column formulas are defined as follows: data elements in any table can be named in the form of X.A.B.C.D; said name addresses the data items of column B in the rows of table A in database X with the value of column C equals D; if said name represents more than one data items, it will be used as an operand of an aggregate or built-in function; if X is omitted in the name, X is defaulted to be the database currently selected: if A is omitted, A is defaulted to be the table currently selected; if B is omitted in the name, expressed as A.C.D of database X, said name references all the rows in table A with the value of column C equal D; if C and D are omitted in the name, expressed as A.B of database X, said name references all the data items in column B of table A; if A, C and D are omitted in the name of an operand, said name references all the data items of column B of the table currently selected; if A, B and C are omitted in the name of an operand, said name references all the rows with data value of the first column of the table currently selected equals D; all names of column and row formulas defined within the same set of requirement specification are unique; all names of requirement specifications saved are unique. 6. The method of claim 1 , wherein said dictionary/directory facilities searching by user input of keywords, the results of the search comprising all the paths leading from the relevant nodes in said hierarchical structure, which may be data values or data value groups, columns or column groups, tables or table groups, databases or database groups, to the root of said directory.

29. A computerized apparatus for spotting an at least one call interaction out of a multiplicity of call interactions in which a target speaker participates, the apparatus comprising: a training computerized component configured for generating a multiplicity of speaker models based on a multiplicity of speaker speech samples from the at least one call interaction; and a speaker spotting computerized component configured for matching the target speaker speech sample with speaker models of the multiplicity of speaker models to determine a target speaker model, determining a score for each call interaction of the multiplicity of call interactions according to a comparison between the target speaker model and the multiplicity of speaker models, and based on scores that are higher than a predetermined threshold, determining call interactions, of the multiplicity of call interactions, and in which the at least one target speaker participates.

29. A computerized apparatus for spotting an at least one call interaction out of a multiplicity of call interactions in which a target speaker participates, the apparatus comprising: a training computerized component configured for generating a multiplicity of speaker models based on a multiplicity of speaker speech samples from the at least one call interaction; and a speaker spotting computerized component configured for matching the target speaker speech sample with speaker models of the multiplicity of speaker models to determine a target speaker model, determining a score for each call interaction of the multiplicity of call interactions according to a comparison between the target speaker model and the multiplicity of speaker models, and based on scores that are higher than a predetermined threshold, determining call interactions, of the multiplicity of call interactions, and in which the at least one target speaker participates. 32. The apparatus of claim 29 wherein the training component comprises a speaker speech pre-processor module to pre-process an at least one speaker speech sample and an at least one speech feature vector; and an extraction module to extract the at least one speech feature vectors from the pre-processed at least one speaker speech sample.

6. A. computerized .system of identifying a wine entity from text in a digital image of a wine menu comprising: a processor configured to execute instructions; a memory including instructions when executed on the processor, causes the processor to perform operations that: obtains a digital image from a mobile device, wherein the digital image comprises a digital photograph of a physical text, wherein at least a portion of the physical text is related to a pre-defined topic, wherein the digital image comprises a digital photograph of the wine menu, and Wherein the pre-defined topic comprises a wine-related topic; converts the digital photograph of the physical text to a text in a computer-readable format; provides a word dictionary, wherein the word dictionary comprises a set of words related to the pre-defined topic; matches a set of words of the text to similar words in the set of words in the word dictionary; identifies a word cluster in the text, wherein each word in the word cluster is associated with a category of a single entity, wherein the single entity is a member of a class of entities demarcated by the pre-defined topic, wherein the class of entities demarcated by the pre-defined topic comprises a set of wine items, and wherein a set of categories of the wine item comprises a wine varietal, a wine producer and a wine vintage; searches a database comprising; a list of members of the class of entities demarcated by the pre-defined topic for one or more entities matching one or more of word-category associations of the word cluster; receives a user instruction that identifies the word cluster; returns a sorted list of the one or more entities matching the one or more of word-category associations of the word cluster, wherein in the list is ranked based on the number of matches between the word-category associations of the word cluster for each entity in the list; and implement a linear n-gram scanning processes to convert a set of character strings of each word in the set of words of the text to words related to the pre-defined topic according to a statistical algorithm.

6. A. computerized .system of identifying a wine entity from text in a digital image of a wine menu comprising: a processor configured to execute instructions; a memory including instructions when executed on the processor, causes the processor to perform operations that: obtains a digital image from a mobile device, wherein the digital image comprises a digital photograph of a physical text, wherein at least a portion of the physical text is related to a pre-defined topic, wherein the digital image comprises a digital photograph of the wine menu, and Wherein the pre-defined topic comprises a wine-related topic; converts the digital photograph of the physical text to a text in a computer-readable format; provides a word dictionary, wherein the word dictionary comprises a set of words related to the pre-defined topic; matches a set of words of the text to similar words in the set of words in the word dictionary; identifies a word cluster in the text, wherein each word in the word cluster is associated with a category of a single entity, wherein the single entity is a member of a class of entities demarcated by the pre-defined topic, wherein the class of entities demarcated by the pre-defined topic comprises a set of wine items, and wherein a set of categories of the wine item comprises a wine varietal, a wine producer and a wine vintage; searches a database comprising; a list of members of the class of entities demarcated by the pre-defined topic for one or more entities matching one or more of word-category associations of the word cluster; receives a user instruction that identifies the word cluster; returns a sorted list of the one or more entities matching the one or more of word-category associations of the word cluster, wherein in the list is ranked based on the number of matches between the word-category associations of the word cluster for each entity in the list; and implement a linear n-gram scanning processes to convert a set of character strings of each word in the set of words of the text to words related to the pre-defined topic according to a statistical algorithm. 7. The computerized system of claim 6 , wherein the digital image is obtained with a digital camera system in the mobile device of a user.

1. A method comprising: when in an instructional environment, training of a dynamic string analysis handler of a string analysis module to effectively handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application, wherein the dynamic string analysis handler is operating in a training mode, wherein an effectiveness of the dynamic string analysis handler is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; upon completion of the training, synthesizing a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon interactions between the dynamic string analysis handler and client application when handling the subset of string queries during training, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and when in the operational environment, dynamically handling of the plurality of string queries having the plurality of contextual metadata received from the client application in accordance with the string analysis algorithm selection policy by the dynamic string analysis handler, wherein the dynamic string analysis handler is operating in a production mode, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined.

1. A method comprising: when in an instructional environment, training of a dynamic string analysis handler of a string analysis module to effectively handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application, wherein the dynamic string analysis handler is operating in a training mode, wherein an effectiveness of the dynamic string analysis handler is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; upon completion of the training, synthesizing a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon interactions between the dynamic string analysis handler and client application when handling the subset of string queries during training, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and when in the operational environment, dynamically handling of the plurality of string queries having the plurality of contextual metadata received from the client application in accordance with the string analysis algorithm selection policy by the dynamic string analysis handler, wherein the dynamic string analysis handler is operating in a production mode, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined. 7. The method of claim 1 , wherein the dynamic handling of the plurality of string queries in the operational environment further comprises: receiving a query request from the client application, wherein said query request comprises a string query from the plurality of string queries and the plurality of contextual metadata associated with the string query; assessing the plurality of contextual metadata of the string query; using the string analysis algorithm selection policy, dynamically selecting the string analysis algorithm that best addresses the string query; executing the dynamically-selected string analysis algorithm for the string query; and conveying results of the execution of the dynamically-selected string analysis algorithm to the client application.

19. The method of claim 14 , further comprising executing the output module to provide output to the user in the form of a graphical representation, wherein the content of the graphical representation is determined by the user input character string.

19. The method of claim 14 , further comprising executing the output module to provide output to the user in the form of a graphical representation, wherein the content of the graphical representation is determined by the user input character string. 21. The method of claim 19 further comprising using a hash function to translate user input into a symbolic representation.

11. The method of claim 1 , further comprising supplying one or both of a confidence measure and a ranking associated with the identified concepts.

11. The method of claim 1 , further comprising supplying one or both of a confidence measure and a ranking associated with the identified concepts. 12. The method of claim 11 , wherein one or both of the confidence measure and the ranking can vary with time of the one or more digital video frames.

8. A system comprising: a processor; a transceiver; data storage; and program instructions in the data storage that, upon execution the processor, cause the system to train an automatic speech recognition (ASR) system with sample utterance-to-text-string mappings, wherein the sample utterance-to-text-string mappings are selected from a corpus of utterance-to-text-string mappings based on a first compressed word frequency and a second compressed word frequency, wherein the first compressed word frequency was determined by raising a first uncompressed word frequency to a power, wherein the power is greater than or equal to 0 and less than 1, wherein the second compressed word frequency was determined by raising a second uncompressed word frequency to the power, and wherein at least one of the first compressed word frequency and the first uncompressed word frequency was received by the system via the transceiver.

8. A system comprising: a processor; a transceiver; data storage; and program instructions in the data storage that, upon execution the processor, cause the system to train an automatic speech recognition (ASR) system with sample utterance-to-text-string mappings, wherein the sample utterance-to-text-string mappings are selected from a corpus of utterance-to-text-string mappings based on a first compressed word frequency and a second compressed word frequency, wherein the first compressed word frequency was determined by raising a first uncompressed word frequency to a power, wherein the power is greater than or equal to 0 and less than 1, wherein the second compressed word frequency was determined by raising a second uncompressed word frequency to the power, and wherein at least one of the first compressed word frequency and the first uncompressed word frequency was received by the system via the transceiver. 9. The system of claim 8 , wherein at least one of the second compressed word frequency and the second uncompressed word frequency was received by the system via the transceiver.

1. A computer-implemented method, comprising: generating, by a computing system, declarative script models with services using a Data Notation Architecture (DNA), wherein the DNA provides a structure to identify and modify data schemas; creating instructions on how corresponding target application code is to be generated, by the computing system, using a Resolution Notation Architecture (RNA), wherein a given RNA file categorically qualifies and defines how DNA base pairs are resolved in the corresponding target application code; and generating rendered code and markup files for a corresponding target application as a part of a Genetic layer to be executed by a computing system associated with the corresponding target application using the RNA to create precompiled RNA.

1. A computer-implemented method, comprising: generating, by a computing system, declarative script models with services using a Data Notation Architecture (DNA), wherein the DNA provides a structure to identify and modify data schemas; creating instructions on how corresponding target application code is to be generated, by the computing system, using a Resolution Notation Architecture (RNA), wherein a given RNA file categorically qualifies and defines how DNA base pairs are resolved in the corresponding target application code; and generating rendered code and markup files for a corresponding target application as a part of a Genetic layer to be executed by a computing system associated with the corresponding target application using the RNA to create precompiled RNA. 6. The computer-implemented method of claim 1 , wherein a DNA layer file is created for each successive layer, and each DNA layer comprises a plurality of DNA files that are representative variations of a given data entity.

13. A non-transitory computer-readable storage medium containing one or more markup language documents for being rendered by a web browser application executing on a computer system, the one or more markup language documents comprising: a hierarchical structure of nodes representing elements of a markup language document and edges connecting the nodes, wherein: a subset of nodes mapped to node types and a root node connected with other nodes via paths comprising nodes and edges; and a specification comprising a mapping from sets of node types to sets of handlers, wherein each set of node types specified in the mapping is mapped to a set of handlers; instructions to a web browser application executing on a computer system for executing handlers in response to an event, the instructions for causing the computer system to: receive a user input associated with a selected node; identify a set of node types encountered in a path connecting the root node with the selected node; identify a set of handlers mapped to the identified set of node types based on the mapping; and execute the handlers in the identified set of handlers.

13. A non-transitory computer-readable storage medium containing one or more markup language documents for being rendered by a web browser application executing on a computer system, the one or more markup language documents comprising: a hierarchical structure of nodes representing elements of a markup language document and edges connecting the nodes, wherein: a subset of nodes mapped to node types and a root node connected with other nodes via paths comprising nodes and edges; and a specification comprising a mapping from sets of node types to sets of handlers, wherein each set of node types specified in the mapping is mapped to a set of handlers; instructions to a web browser application executing on a computer system for executing handlers in response to an event, the instructions for causing the computer system to: receive a user input associated with a selected node; identify a set of node types encountered in a path connecting the root node with the selected node; identify a set of handlers mapped to the identified set of node types based on the mapping; and execute the handlers in the identified set of handlers. 14. The non-transitory computer readable storage medium of claim 13 , wherein the hierarchical structure further comprises: metadata associated with nodes, wherein the metadata distinguishes instances of nodes belonging to a same node type.

3. The robot of claim 2 , further comprising a robot behavior database for mapping a plurality of recognized behaviors of said partner which will be detected by said fist analyzer to a plurality of predetermined robot behaviors, wherein the referenced entry indicates an expected state of said people, and wherein said processor compares a recognized state of said people currently detected by said second analyzer to the expected state of the referenced entry for a match or mismatch and determines said behavior of the robot according to the referenced portion of said scenario if there is a match between said recognized and expected states and according to one of said predetermined robot behaviors of said database corresponding to a recognized behavior of said partner currently detected by said first analyzer if there is a mismatch between said recognized and expected states.

3. The robot of claim 2 , further comprising a robot behavior database for mapping a plurality of recognized behaviors of said partner which will be detected by said fist analyzer to a plurality of predetermined robot behaviors, wherein the referenced entry indicates an expected state of said people, and wherein said processor compares a recognized state of said people currently detected by said second analyzer to the expected state of the referenced entry for a match or mismatch and determines said behavior of the robot according to the referenced portion of said scenario if there is a match between said recognized and expected states and according to one of said predetermined robot behaviors of said database corresponding to a recognized behavior of said partner currently detected by said first analyzer if there is a mismatch between said recognized and expected states. 6. The robot of claim 3 , wherein each of said entries of said scenario memory indicates which one of said partner and said robot has the right to speak, wherein said database further maps a plurality of recognized states of said people which will be detected by said second analyzer to said plurality of predetermined robot behaviors, wherein said processor determines said behavior of said robot according to one of said predetermined robot behaviors corresponding to a recognized behavior of said partner currently detected by said first analyzer if the referenced entry indicates that said partner has the right to speak and according to one of said predetermined robot behaviors corresponding to a recognized state of said people currently detected by said second analyzer if the referenced entry indicates that said robot has the right to speak.

1. A method for automatically processing electronic information messages, comprising: automatically via a software module receiving an electronic information message on a network device with one or more processors via a communications network from a source network device with one or more processors; automatically via the software module parsing the electronic information message to identify one or more keywords in the electronic information message, wherein the identified one or more keywords include keywords include advertising keywords stored in a database, non-advertising keywords such as public interest keywords and keywords dynamically generated using information theory to decide relevant keywords; automatically via the software module mapping a selected single identified keyword into a plurality of related keywords, or mapping a plurality of selected identified keywords into a single keyword before submitting the one or more queries to one or more search engines; automatically via the software module submitting the identified one or more keywords from the network device to the one or more search engines as one or more search engine queries via the communications network, wherein the one or more search engines include one or more publicly available search engines and one or more privately available search engines; automatically via the software module receiving query results from the one or more search engines; automatically via the software module selecting one or more electronic links from the one or more query results, wherein the one or more electronic links are selected based on pre-determined conditions, wherein one of the pre-determine conditions includes fee agreements with advertisers and wherein the electronic links include electronic links for linking directly to another information site on the communications network, for initiating a static search engine query and for initiating a dynamic search engine query; automatically via the software module adding the one or more selected electronic links to the electronic message creating a modified electronic information message, thereby allowing additional electronic information to be accessed from the modified electronic information message based on information content of the electronic information message, wherein a same selected electronic link is added to repeating occurrences of an identified keyword and wherein different selected electronic links are added to repeating occurrences of the identified keyword.

1. A method for automatically processing electronic information messages, comprising: automatically via a software module receiving an electronic information message on a network device with one or more processors via a communications network from a source network device with one or more processors; automatically via the software module parsing the electronic information message to identify one or more keywords in the electronic information message, wherein the identified one or more keywords include keywords include advertising keywords stored in a database, non-advertising keywords such as public interest keywords and keywords dynamically generated using information theory to decide relevant keywords; automatically via the software module mapping a selected single identified keyword into a plurality of related keywords, or mapping a plurality of selected identified keywords into a single keyword before submitting the one or more queries to one or more search engines; automatically via the software module submitting the identified one or more keywords from the network device to the one or more search engines as one or more search engine queries via the communications network, wherein the one or more search engines include one or more publicly available search engines and one or more privately available search engines; automatically via the software module receiving query results from the one or more search engines; automatically via the software module selecting one or more electronic links from the one or more query results, wherein the one or more electronic links are selected based on pre-determined conditions, wherein one of the pre-determine conditions includes fee agreements with advertisers and wherein the electronic links include electronic links for linking directly to another information site on the communications network, for initiating a static search engine query and for initiating a dynamic search engine query; automatically via the software module adding the one or more selected electronic links to the electronic message creating a modified electronic information message, thereby allowing additional electronic information to be accessed from the modified electronic information message based on information content of the electronic information message, wherein a same selected electronic link is added to repeating occurrences of an identified keyword and wherein different selected electronic links are added to repeating occurrences of the identified keyword. 16. The method of claim 1 wherein the network device is a server device.

18. The non-transitory computer-readable storage device of claim 13 , wherein the target entry is a character string comprising letters of a pre-selected alphabet, wherein the plurality of potential distractors comprises the pre-selected alphabet, and wherein the step of selecting at least one distractor comprises iteratively selecting for each character of the character string every letter of the pre-selected alphabet that is acoustically dissimilar to a particular character of the character string.

18. The non-transitory computer-readable storage device of claim 13 , wherein the target entry is a character string comprising letters of a pre-selected alphabet, wherein the plurality of potential distractors comprises the pre-selected alphabet, and wherein the step of selecting at least one distractor comprises iteratively selecting for each character of the character string every letter of the pre-selected alphabet that is acoustically dissimilar to a particular character of the character string. 19. The non-transitory computer-readable storage device of claim 18 , wherein the step of generating a speech recognition grammar comprises generating for each character of the character string a corresponding pool of distractors that comprises each letter of the pre-selected alphabet that is acoustically dissimilar to the corresponding character.

1. A system for displaying unified model (UM) data in a UM visualization, comprising: a weighting system for assigning weights to UM elements; a clustering system for clustering the weighted UM elements into clusters, the weighting system further assigning weights to the clusters; and a visualization system for displaying the weighted clusters and the weighted UM elements in the weighted clusters within a conceptual framework; wherein a size of each weighted UM element displayed within the conceptual framework is proportional to the weight assigned to the weighted UM element, and wherein a size of each weighted cluster displayed within the conceptual framework is proportional to the weight assigned to the weighted cluster.

1. A system for displaying unified model (UM) data in a UM visualization, comprising: a weighting system for assigning weights to UM elements; a clustering system for clustering the weighted UM elements into clusters, the weighting system further assigning weights to the clusters; and a visualization system for displaying the weighted clusters and the weighted UM elements in the weighted clusters within a conceptual framework; wherein a size of each weighted UM element displayed within the conceptual framework is proportional to the weight assigned to the weighted UM element, and wherein a size of each weighted cluster displayed within the conceptual framework is proportional to the weight assigned to the weighted cluster. 2. The system of claim 1 , wherein the weighting system determines weights manually based on user input.

1. A Non-Transitory machine-readable medium storing a set of machine-readable instructions executable by the machine to implement a configuration management database (CMDB) comprising: a plurality of statements, wherein the statements comprise: a configuration item wherein the configuration item comprises a first item identifying a resource, a second item identifying an object, wherein the statements are made in a markup language; an ontology wherein the ontology comprises a set of defined constraints and relationships for the configuration item; a subset of instructions wherein the subset of instructions requests changing the CMDB by substituting configuration items; an inference service wherein the inference service uses the markup language and one or more constraints included in the ontology to infer relationships not explicitly defined between the plurality of statements; wherein the CMDB defines an actual state of an information system and a desired state of the information system, and the actual state and the desired state are comparable to reveal inconsistencies therebetween; and wherein the inference service analyzes the inconsistencies to create one or more rules for applying the requested substitution to the CMDB.

1. A Non-Transitory machine-readable medium storing a set of machine-readable instructions executable by the machine to implement a configuration management database (CMDB) comprising: a plurality of statements, wherein the statements comprise: a configuration item wherein the configuration item comprises a first item identifying a resource, a second item identifying an object, wherein the statements are made in a markup language; an ontology wherein the ontology comprises a set of defined constraints and relationships for the configuration item; a subset of instructions wherein the subset of instructions requests changing the CMDB by substituting configuration items; an inference service wherein the inference service uses the markup language and one or more constraints included in the ontology to infer relationships not explicitly defined between the plurality of statements; wherein the CMDB defines an actual state of an information system and a desired state of the information system, and the actual state and the desired state are comparable to reveal inconsistencies therebetween; and wherein the inference service analyzes the inconsistencies to create one or more rules for applying the requested substitution to the CMDB. 2. The Non-Transitory machine-readable medium as claimed in claim 1 , wherein the plurality of statements comprise a plurality of Resource Description Framework (RDF) statements.

1. A method for detecting automatically generated malicious domain names in a network, comprising: identifying a plurality of domain name service (DNS) queries in the network, wherein the plurality of DNS queries share a common attribute; analyzing, using a central processing unit (CPU) of a computer, the plurality of DNS queries to identify a plurality of alphanumeric elements embedded in a set of domain names associated with the plurality of DNS queries; analyzing, using the CPU, the plurality of alphanumeric elements to determine a distribution metric of the set domain names; and generating an alert of domain fluxing based on the distribution metric according to a pre-determined criterion.

1. A method for detecting automatically generated malicious domain names in a network, comprising: identifying a plurality of domain name service (DNS) queries in the network, wherein the plurality of DNS queries share a common attribute; analyzing, using a central processing unit (CPU) of a computer, the plurality of DNS queries to identify a plurality of alphanumeric elements embedded in a set of domain names associated with the plurality of DNS queries; analyzing, using the CPU, the plurality of alphanumeric elements to determine a distribution metric of the set domain names; and generating an alert of domain fluxing based on the distribution metric according to a pre-determined criterion. 3. The method of claim 1 , wherein the common attribute comprises a top level domain name corresponding to the plurality of DNS queries.

1. A system for an autonomous vehicle comprising: two or more microphones mounted to the autonomous vehicle; a controller executing a pre-processor programmed to detect audio features in two or more audio streams from the two or more microphones; a collision avoidance module programmed to classify the audio features and a direction to a source thereof, and, if the class for the sound source is a vehicle, invoke obstacle avoidance with respect to the direction; wherein the collision avoidance module is further programmed to: classify the audio features by inputting the audio features into a machine learning model; and wherein the machine-learning model outputs a confidence value indicating a probability that the audio features correspond to a vehicle.

1. A system for an autonomous vehicle comprising: two or more microphones mounted to the autonomous vehicle; a controller executing a pre-processor programmed to detect audio features in two or more audio streams from the two or more microphones; a collision avoidance module programmed to classify the audio features and a direction to a source thereof, and, if the class for the sound source is a vehicle, invoke obstacle avoidance with respect to the direction; wherein the collision avoidance module is further programmed to: classify the audio features by inputting the audio features into a machine learning model; and wherein the machine-learning model outputs a confidence value indicating a probability that the audio features correspond to a vehicle. 8. The system of claim 1 , wherein the collision avoidance module is further programmed to detect the direction to the source of the audio features by evaluating a time difference between the audio features.

13. A system, comprising: a processor; and a memory including instructions that, when executed by the processor, cause the processor to: segment information; determine a language type for the segmented information; search a language dictionary for synonyms of the contents of each information segment in at least one language type; and store the synonyms and contents of each information segment.

13. A system, comprising: a processor; and a memory including instructions that, when executed by the processor, cause the processor to: segment information; determine a language type for the segmented information; search a language dictionary for synonyms of the contents of each information segment in at least one language type; and store the synonyms and contents of each information segment. 16. The system of claim 13 , wherein the memory device further includes instructions that, when executed by the processor, cause the processor to: remove punctuation from each information segment; and further segment the information segment into at least one additional segment where punctuation is removed.

8. A requirement acquiring method, comprising the steps of: a) arranging components of a development on a screen of a computer terminal; b) specifying, for each of the arranged components, an attribute information relating to data and procedure to be held by said component; c) designating a procedure call sequence between the components by selecting a procedure from a list of procedures held by the component, and representing an arrow line between said arranged components holding said selected procedure on said screen; d) generating a scenario including component data and procedure call sequence data on the basis of said attribute information and said selected procedure call sequence; and e) successively displaying a procedure call sequence with arrow lines between components on said screen of said computer terminal in accordance with said generated procedure call sequence data.

8. A requirement acquiring method, comprising the steps of: a) arranging components of a development on a screen of a computer terminal; b) specifying, for each of the arranged components, an attribute information relating to data and procedure to be held by said component; c) designating a procedure call sequence between the components by selecting a procedure from a list of procedures held by the component, and representing an arrow line between said arranged components holding said selected procedure on said screen; d) generating a scenario including component data and procedure call sequence data on the basis of said attribute information and said selected procedure call sequence; and e) successively displaying a procedure call sequence with arrow lines between components on said screen of said computer terminal in accordance with said generated procedure call sequence data. 11. A requirement acquiring method according to claim 8, wherein said step c) comprises specifying a data item name and a value corresponding to said data item held by said component holding said selected procedure, and specifying a data item name held by another component in which said value is to be set, wherein said step d) comprises generating substitution data to provide said value corresponding to said specified data item into said data item held by said another component, and generating data of component on the basis of said component holding said selected procedure and said another component, and wherein said step e) comprises the steps of: displaying an arrow line from the data item held by said specified component to the data item held by said another component, and displaying the value corresponding to said specified data item, in accordance with said procedure call sequence data; and displaying a connection line between an arrow line of said procedure call sequence holding said data of component and said component.

8. A conversational speech analysis method in a conversational speech analyzing system having a first microphone, a second microphone, a first sensor, a second sensor, and a computer connected to the first microphone, the second microphone, the first sensor, and the second sensor, the method comprising: a first step, including using the first microphone and the second microphone to capture speech data in a vicinity of a meeting, and storing the speech data in the memory of the computer; a second step, including using the first sensor to capture first sensor information in the vicinity of the meeting, and using the second sensor to capture second sensor information in the vicinity of the meeting, and to store the first and second sensor information in the memory of a computer; and a third step, including using the computer to classify the speech data captured from the first microphone as first speech frames when speech is detected, and to classify the speech data captured from the first microphone as first nonspeech frames when speech is not detected; a fourth step, including using the computer to divide the first sensor information based on the first speech frames and the first nonspeech frames, and to divide the second sensor information also based on the first speech frames and the first nonspeech frames; and a fifth step, including using the computer to evaluate an interest level of a person in the meeting by comparing characteristics of the second sensor information divided based on the first speech frames to characteristics of the second sensor information divided based on the first nonspeech frames.

8. A conversational speech analysis method in a conversational speech analyzing system having a first microphone, a second microphone, a first sensor, a second sensor, and a computer connected to the first microphone, the second microphone, the first sensor, and the second sensor, the method comprising: a first step, including using the first microphone and the second microphone to capture speech data in a vicinity of a meeting, and storing the speech data in the memory of the computer; a second step, including using the first sensor to capture first sensor information in the vicinity of the meeting, and using the second sensor to capture second sensor information in the vicinity of the meeting, and to store the first and second sensor information in the memory of a computer; and a third step, including using the computer to classify the speech data captured from the first microphone as first speech frames when speech is detected, and to classify the speech data captured from the first microphone as first nonspeech frames when speech is not detected; a fourth step, including using the computer to divide the first sensor information based on the first speech frames and the first nonspeech frames, and to divide the second sensor information also based on the first speech frames and the first nonspeech frames; and a fifth step, including using the computer to evaluate an interest level of a person in the meeting by comparing characteristics of the second sensor information divided based on the first speech frames to characteristics of the second sensor information divided based on the first nonspeech frames. 9. The conversational speech analysis method according to claim 8 , wherein in the third step, the computer matches data pertaining to one of the persons in a vicinity of at least one of the first sensor and the second sensor with at least one of first sensor information captured from the first sensor and second sensor information captured from the second sensor, and stores the result; and wherein the computer matches an interest level in the meeting with the data pertaining to the person matched to at least one of first sensor information and second sensor information, and stores the result.

12. A modulus encoder according to claim 8, further comprising means for adaptively determining the value of b in response to the values of said moduli.

12. A modulus encoder according to claim 8, further comprising means for adaptively determining the value of b in response to the values of said moduli. 14. A modulus encoder according to claim 12, wherein: said processing means is capable of performing division operations with a divisor having a maximum length of N bits and with a dividend having a maximum length of P bits; said means for adaptively determining is configured to determine the value of b in accordance with the following relationship: 1.ltoreq.b.ltoreq.P-max [log.sub.2 M.sub.i ], .A-inverted.i; N.gtoreq.max[log.sub.2 M.sub.i ], .A-inverted.i; and M.sub.i represents said number of moduli.

19. A computer-implemented method of evaluating an electronic mail message based on probabilistic analysis, comprising: training a probabilistic filter using first properties of one or more first network resource identifiers obtained from a whitelist; wherein at least one of the first properties is obtained from any of: information obtained from DNS queries based, at least in part, on the one or more first work resource identifiers; server software information; or information obtained from “whois” queries based, at least in part, on information contained in the network resource identifier; training the probabilistic filter using second properties of one or more second network resource identifiers obtained from a blocklist; testing third properties of a third network resource identifier using the probabilistic filter, resulting in creating a probability output; adding the third network resource identifier to the blocklist when the probability output is greater than a specified threshold.

19. A computer-implemented method of evaluating an electronic mail message based on probabilistic analysis, comprising: training a probabilistic filter using first properties of one or more first network resource identifiers obtained from a whitelist; wherein at least one of the first properties is obtained from any of: information obtained from DNS queries based, at least in part, on the one or more first work resource identifiers; server software information; or information obtained from “whois” queries based, at least in part, on information contained in the network resource identifier; training the probabilistic filter using second properties of one or more second network resource identifiers obtained from a blocklist; testing third properties of a third network resource identifier using the probabilistic filter, resulting in creating a probability output; adding the third network resource identifier to the blocklist when the probability output is greater than a specified threshold. 21. The invention of claim 19 , further comprising: extracting a domain name portion of the third network resource identifier; retrieving one or more MX records for the domain name portion from a domain name system (DNS) server; retrieving network address records for each mail exchange that is identified in the one or more MX records; determining an average reputation score for the network address records; adding the third network resource identifier to the blocklist when the average reputation score is less than a specified threshold.

4. The method of claim 1 , wherein selecting one or more shape models of the object comprises: computing probability distributions of the shape models of the object; and estimating likelihood of each shape model to be selected as a reference shape model of the object.

4. The method of claim 1 , wherein selecting one or more shape models of the object comprises: computing probability distributions of the shape models of the object; and estimating likelihood of each shape model to be selected as a reference shape model of the object. 5. The method of claim 4 , further comprising: re-computing the probability distribution of each shape model based on the appearance features contained in a corresponding appearance model.

4. The method of claim 1 , wherein the external knowledge source includes a directory with name data and during the analyzing of the plurality of interpretations, the at least one processor compares at least one information item in the plurality of information items from each of the plurality of interpretations with the name data directory to determine if any invalid name combinations are present in the at least one information item.

4. The method of claim 1 , wherein the external knowledge source includes a directory with name data and during the analyzing of the plurality of interpretations, the at least one processor compares at least one information item in the plurality of information items from each of the plurality of interpretations with the name data directory to determine if any invalid name combinations are present in the at least one information item. 6. The method of claim 4 , further including deleting the at least one information item because the at least one informational item was an invalid name combination.

9. The method of claim 5, wherein the step of providing a cognitive profile further comprises testing the learner using presentations having different cognitive styles and determining the cognitive profile using the cognitive index associated with the cognitive style that resulted in the greatest comprehension by the learner of the content presented during testing, and wherein the method further comprises the step of aggregating information about a large number of learners' cognitive profiles.

9. The method of claim 5, wherein the step of providing a cognitive profile further comprises testing the learner using presentations having different cognitive styles and determining the cognitive profile using the cognitive index associated with the cognitive style that resulted in the greatest comprehension by the learner of the content presented during testing, and wherein the method further comprises the step of aggregating information about a large number of learners' cognitive profiles. 10. The method of claim 9, further comprising the step of developing new presentations having a cognitive style that is selected based upon the aggregate information.

5. A method for enabling virtual universe users to find and engage subject matter experts within an expected context of a virtual universe, comprising: an avatar of a user engaging a conduit texture presented within a graphic environment of a virtual universe by physically contacting an object on the conduit texture that is tagged with a tag relevant to a query search term, the engaging indicating the query search term; in response to the engaging the texture, automatically searching a data storage in communication with the conduit texture for a tag relevant to the query search term, identifying and locating a subject matter expert tagged with the relevant tag, and teleporting one of the user avatar and the subject matter expert avatar to an other of the user avatar and the subject matter expert avatar; and the located subject matter expert communicating directly with the user avatar via a subject matter expert avatar, the communicating entirely within an expected role context of the user avatar and the subject matter expert avatar within the virtual universe, the communicating without the user directly engaging a resource outside of the virtual universe and without requiring the user to engage in a communication interface outside of the virtual universe.

5. A method for enabling virtual universe users to find and engage subject matter experts within an expected context of a virtual universe, comprising: an avatar of a user engaging a conduit texture presented within a graphic environment of a virtual universe by physically contacting an object on the conduit texture that is tagged with a tag relevant to a query search term, the engaging indicating the query search term; in response to the engaging the texture, automatically searching a data storage in communication with the conduit texture for a tag relevant to the query search term, identifying and locating a subject matter expert tagged with the relevant tag, and teleporting one of the user avatar and the subject matter expert avatar to an other of the user avatar and the subject matter expert avatar; and the located subject matter expert communicating directly with the user avatar via a subject matter expert avatar, the communicating entirely within an expected role context of the user avatar and the subject matter expert avatar within the virtual universe, the communicating without the user directly engaging a resource outside of the virtual universe and without requiring the user to engage in a communication interface outside of the virtual universe. 6. The method of claim 5 , further comprising: prompting the user to input subject matter expert search terms comprising the query search term in a text input field in response to the user avatar engaging the conduit texture presented within the graphic environment of the virtual universe.

41. An electronic device, comprising: one or more processors; memory; 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 audio input; determining whether the audio input includes music; determining whether the audio input includes speech; responsive to determining that the audio input includes music, generating an acoustic fingerprint representing a portion of the audio input that includes music; and responsive to determining that the audio input includes speech rather than music, identifying an end-point of a speech utterance of the audio input.

41. An electronic device, comprising: one or more processors; memory; 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 audio input; determining whether the audio input includes music; determining whether the audio input includes speech; responsive to determining that the audio input includes music, generating an acoustic fingerprint representing a portion of the audio input that includes music; and responsive to determining that the audio input includes speech rather than music, identifying an end-point of a speech utterance of the audio input. 57. The device according to claim 41 , wherein receiving the audio input begins in response to receiving a signal to begin receiving the audio input, and wherein the one or more programs further including instructions for: in response to determining that the audio input includes neither speech nor music for a predetermined duration, ceasing to receive the audio input.

7. A method performed by at least one hardware processor executing computer-readable instructions stored on at least one computer-readable storage device, the method comprising: receiving a sibling request to access a combined hierarchical ontology, the combined hierarchical ontology comprising first concepts and corresponding first codes associated with the first concepts by a first terminology and second concepts associated with second codes by a second terminology, wherein the sibling request identifies a specified first concept that is on a particular level of the combined hierarchical ontology and the sibling request specifies a number of levels to traverse the combined hierarchical ontology, the number of levels being greater than one; traversing the combined hierarchical ontology the number of levels specified by the sibling request to identify a common ancestor shared by the specified first concept and a corresponding second concept, wherein the corresponding second concept has a different meaning than the specified first concept and is also on the particular level of the combined hierarchical ontology with the specified first concept; and responding to the sibling request with the corresponding second concept that shares the common ancestor with the specified first concept.

7. A method performed by at least one hardware processor executing computer-readable instructions stored on at least one computer-readable storage device, the method comprising: receiving a sibling request to access a combined hierarchical ontology, the combined hierarchical ontology comprising first concepts and corresponding first codes associated with the first concepts by a first terminology and second concepts associated with second codes by a second terminology, wherein the sibling request identifies a specified first concept that is on a particular level of the combined hierarchical ontology and the sibling request specifies a number of levels to traverse the combined hierarchical ontology, the number of levels being greater than one; traversing the combined hierarchical ontology the number of levels specified by the sibling request to identify a common ancestor shared by the specified first concept and a corresponding second concept, wherein the corresponding second concept has a different meaning than the specified first concept and is also on the particular level of the combined hierarchical ontology with the specified first concept; and responding to the sibling request with the corresponding second concept that shares the common ancestor with the specified first concept. 15. The method of claim 7 , wherein the combined hierarchical ontology has at least one level that is lower than the particular level.

15. Apparatus as defined by claim 14 wherein said means for time normalizing divides each training word and the command word into a predetermined number of time slots of substantially equal duration.

15. Apparatus as defined by claim 14 wherein said means for time normalizing divides each training word and the command word into a predetermined number of time slots of substantially equal duration. 16. Apparatus as defined by claim 15 further comprising means responsive to said correlation figure and supplementary correlation figure for generating an occurrence indication indicative of the training word which corresponds most closely to the command word.

1. A method for document classification, comprising: embedding n-grams from an input text in a latent space; embedding the input text in the latent space based on the embedded n-grams and weighting the n-grams according to a non-linear function q j = 1 Q ⁢ ∑ k = 1 K ⁢ sigmoid ⁡ ( a k · j N + b k ) , using a mixture model on a relative position of the n-grams in the input text, where a k and b k are parameters to be learned, Q = ∑ j = 1 N ⁢ q j and K specify a number of mixture quantities, sigmoid (•) is a non-linear transfer function, q j is the weight associated with a j th n-gram, j signifies the position of an n-gram in the input text, and N is the position of a final n-gram in the input text; classifying the document along one or more axes using a processor; and adjusting weights used to weight the n-grams based on the output of the classifying step.

1. A method for document classification, comprising: embedding n-grams from an input text in a latent space; embedding the input text in the latent space based on the embedded n-grams and weighting the n-grams according to a non-linear function q j = 1 Q ⁢ ∑ k = 1 K ⁢ sigmoid ⁡ ( a k · j N + b k ) , using a mixture model on a relative position of the n-grams in the input text, where a k and b k are parameters to be learned, Q = ∑ j = 1 N ⁢ q j and K specify a number of mixture quantities, sigmoid (•) is a non-linear transfer function, q j is the weight associated with a j th n-gram, j signifies the position of an n-gram in the input text, and N is the position of a final n-gram in the input text; classifying the document along one or more axes using a processor; and adjusting weights used to weight the n-grams based on the output of the classifying step. 7. The method of claim 1 , wherein weights for each n-gram are learned by optimizing over a set of training documents with known class labels.

1. A computer-implemented method for generating at least one index over XML documents in an XML database configured to operate in a computing system that includes at least one processor, the method comprising: executing, via the at least one processor, at least one indexing function defined in the XQuery language, each said indexing function being configured to accept an XML document as input and to return at least one computed result; storing each said computed result from the at least one indexing function as a key of the corresponding index; and storing a reference to the input XML document as a value of the index, wherein the at least one indexing function returns at least one XML substructure, and further comprising mapping each of the at least one XML substructures onto a tuple of type values and wherein each of the tuples is stored as a key of the index.

1. A computer-implemented method for generating at least one index over XML documents in an XML database configured to operate in a computing system that includes at least one processor, the method comprising: executing, via the at least one processor, at least one indexing function defined in the XQuery language, each said indexing function being configured to accept an XML document as input and to return at least one computed result; storing each said computed result from the at least one indexing function as a key of the corresponding index; and storing a reference to the input XML document as a value of the index, wherein the at least one indexing function returns at least one XML substructure, and further comprising mapping each of the at least one XML substructures onto a tuple of type values and wherein each of the tuples is stored as a key of the index. 7. The method of claim 1 , further comprising optimizing an XQuery that comprises at least one call of an indexing function by scanning the corresponding index of the indexing function when processing the XQuery.

22. A computer system comprising: a memory: one or more processors; an event management component, executed by the one or more processors, configured to— determine various audience intensity and/or emotional engagements at corresponding points during an event, wherein each audience intensity and/or emotional engagement is based on one or more audience member actions; and an administrative component, executed by the one or more processors, configured to— select one of the various audience intensity and/or emotional engagements based on the selected audience intensity and/or emotional engagement being at or above a pre-determined level; determine, based on the selected audience intensity and/or emotional engagement, a type of content to send; and select a content item corresponding to the determined type of content, wherein the content item is based on the selected audience intensity and/or emotional engagement; and an interface configured to send the selected content item to one or more of the audience members.

22. A computer system comprising: a memory: one or more processors; an event management component, executed by the one or more processors, configured to— determine various audience intensity and/or emotional engagements at corresponding points during an event, wherein each audience intensity and/or emotional engagement is based on one or more audience member actions; and an administrative component, executed by the one or more processors, configured to— select one of the various audience intensity and/or emotional engagements based on the selected audience intensity and/or emotional engagement being at or above a pre-determined level; determine, based on the selected audience intensity and/or emotional engagement, a type of content to send; and select a content item corresponding to the determined type of content, wherein the content item is based on the selected audience intensity and/or emotional engagement; and an interface configured to send the selected content item to one or more of the audience members. 24. The system of claim 22 wherein the type of content is an offer for a product and/or an offer for a service.

11. A non-transitory computer readable storage medium having a computer-executable container, the container comprising: a container for encapsulating operative components in a predetermined electronic file format to define an interactive document, the container including a compressed portion for storing predetermined portions of selected operative components; the operative components comprising: one or more content components of the interactive document for representing document contents including text, graphics, controls, sounds; an interaction orchestration component operative to display, from among an array of orchestration subcomponents, at least some of the orchestration subcomponents as a user document interaction interface within the interactive document, each orchestration subcomponent being configured to provide variability in a type, a quantity, and a source of the content components; a control component for controlling, as a function of user characteristics including at least one of an identity, a title, or a role, user access to predetermined content components of the interactive document and user access regarding which, if any, of predetermined interaction orchestration component subcomponents within the interactive document are accessible to a user; and instance data within the interactive document, the instance data comprising predetermined information obtained during one or more of the following: interaction between a user and operations of the interaction orchestration component; data retrieval from an enterprise database controlled by the interaction orchestration component; data retrieved from an external database as a function of a predetermined data retrieval component; and data retrieved from an asynchronous information source.

11. A non-transitory computer readable storage medium having a computer-executable container, the container comprising: a container for encapsulating operative components in a predetermined electronic file format to define an interactive document, the container including a compressed portion for storing predetermined portions of selected operative components; the operative components comprising: one or more content components of the interactive document for representing document contents including text, graphics, controls, sounds; an interaction orchestration component operative to display, from among an array of orchestration subcomponents, at least some of the orchestration subcomponents as a user document interaction interface within the interactive document, each orchestration subcomponent being configured to provide variability in a type, a quantity, and a source of the content components; a control component for controlling, as a function of user characteristics including at least one of an identity, a title, or a role, user access to predetermined content components of the interactive document and user access regarding which, if any, of predetermined interaction orchestration component subcomponents within the interactive document are accessible to a user; and instance data within the interactive document, the instance data comprising predetermined information obtained during one or more of the following: interaction between a user and operations of the interaction orchestration component; data retrieval from an enterprise database controlled by the interaction orchestration component; data retrieved from an external database as a function of a predetermined data retrieval component; and data retrieved from an asynchronous information source. 21. The non-transitory computer readable storage medium of claim 11 , wherein the instance data component comprises specific information obtained from user interaction with the interactive document during a document interaction session with a user.

8. A system comprising one or more computing devices configured to: select a first geographic entity of a plurality of distinct geographic entities; identify a plurality of distinct geographic sub-entities, each distinct geographic sub-entity having a geographic containment relationship with the first geographic entity, the plurality of distinct geographic sub-entities including: a first distinct geographic sub-entity that is both (i) visually represented by at least one landmark corresponding to the first distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of a plurality of pre-stored navigation experiences that is unique to the first distinct geographic sub-entity, and a second distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark corresponding to the second distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the second distinct geographic sub-entity, wherein each pre-stored navigation experience in the plurality of pre-stored navigation experiences corresponds to a given geographic entity and comprises a sequence of images and transitions between the images that produces a tour of at least one landmark associated with the given geographic entity; filter the plurality of distinct geographic sub-entities to remove at least one distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the at least one distinct geographic sub-entity, the at least one distinct geographic sub-entity including the second geographic sub-entity; determine a ranking order of the filtered plurality of distinct geographic sub-entities based at least in part on one or more characteristics of each distinct geographic sub-entity in the filtered plurality of distinct geographic sub-entities; select a subset of at least two distinct geographic sub-entities based on the ranking order; and generate a semantic image navigation experience for the first geographic entity based on at least the pre-stored navigation experiences associated with the subset of at least two distinct geographic sub-entities by: automatically selecting a plurality of images from each pre-stored navigation experience of the subset of at least two distinct geographic sub-entities, and including the plurality of selected images in the semantic image navigation experience as a sequence of images based on the ranking order.

8. A system comprising one or more computing devices configured to: select a first geographic entity of a plurality of distinct geographic entities; identify a plurality of distinct geographic sub-entities, each distinct geographic sub-entity having a geographic containment relationship with the first geographic entity, the plurality of distinct geographic sub-entities including: a first distinct geographic sub-entity that is both (i) visually represented by at least one landmark corresponding to the first distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of a plurality of pre-stored navigation experiences that is unique to the first distinct geographic sub-entity, and a second distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark corresponding to the second distinct geographic sub-entity and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the second distinct geographic sub-entity, wherein each pre-stored navigation experience in the plurality of pre-stored navigation experiences corresponds to a given geographic entity and comprises a sequence of images and transitions between the images that produces a tour of at least one landmark associated with the given geographic entity; filter the plurality of distinct geographic sub-entities to remove at least one distinct geographic sub-entity that is not at least one of (i) visually represented by at least one landmark and (ii) associated with a pre-stored navigation experience of the plurality of pre-stored navigation experiences that is unique to the at least one distinct geographic sub-entity, the at least one distinct geographic sub-entity including the second geographic sub-entity; determine a ranking order of the filtered plurality of distinct geographic sub-entities based at least in part on one or more characteristics of each distinct geographic sub-entity in the filtered plurality of distinct geographic sub-entities; select a subset of at least two distinct geographic sub-entities based on the ranking order; and generate a semantic image navigation experience for the first geographic entity based on at least the pre-stored navigation experiences associated with the subset of at least two distinct geographic sub-entities by: automatically selecting a plurality of images from each pre-stored navigation experience of the subset of at least two distinct geographic sub-entities, and including the plurality of selected images in the semantic image navigation experience as a sequence of images based on the ranking order. 12. The system of claim 8 , wherein the one or more computing devices are further configured to generate the semantic image navigation experience by including information about each distinct geographic sub-entity in the subset of at least two distinct geographic sub-entities.

8. A computer system comprising: at least one processor; a communications medium coupled with the processor; a system memory in communication with the processor via the communication medium, the system memory configured to store programmed computer code, which when executed by the processor, causes the processor to perform operations comprising: receiving inputs from user interface framework of an application that implements the user interface framework when at least one text string is to be displayed in a display element of the user interface, the inputs comprising the text string, an amount of available space in the display element, and an identification of the language of the text string; receiving linguistic pre-analysis results from outside the user interface framework; executing a text reduction algorithm on the text string based upon the linguistic pre-analysis results, wherein executing the text reduction algorithm comprises calculating one or more of entropy, confusion, and style deviation of the short forms of the text string; identifying one or more short forms of the text string that fit within the available space of the display element based on executing the text reduction algorithm; and communicating the identified short forms of the text string to the application or framework for display in the display element of the user interface framework.

8. A computer system comprising: at least one processor; a communications medium coupled with the processor; a system memory in communication with the processor via the communication medium, the system memory configured to store programmed computer code, which when executed by the processor, causes the processor to perform operations comprising: receiving inputs from user interface framework of an application that implements the user interface framework when at least one text string is to be displayed in a display element of the user interface, the inputs comprising the text string, an amount of available space in the display element, and an identification of the language of the text string; receiving linguistic pre-analysis results from outside the user interface framework; executing a text reduction algorithm on the text string based upon the linguistic pre-analysis results, wherein executing the text reduction algorithm comprises calculating one or more of entropy, confusion, and style deviation of the short forms of the text string; identifying one or more short forms of the text string that fit within the available space of the display element based on executing the text reduction algorithm; and communicating the identified short forms of the text string to the application or framework for display in the display element of the user interface framework. 19. The system of claim 8 wherein calculating the entropy of the one or more short forms of the text string comprises: assigning a total meaningfulness value to the text string; determining a contribution of each character of the text string to the total meaningfulness value; and calculating how much meaning is subtracted when one or more characters are removed from the text string based on determining the contribution of the removed characters to the total meaningfulness value.

2. The method of claim 1 , wherein at least one constraint for preserving referential integrity specified by the constraint specification is based on dependence of values for a field of the second dataset on values for a field of the first dataset.

2. The method of claim 1 , wherein at least one constraint for preserving referential integrity specified by the constraint specification is based on dependence of values for a field of the second dataset on values for a field of the first dataset. 5. The method of claim 2 , wherein determining the processing order for the multiple datasets includes determining that the first dataset occurs before the second dataset in the processing order based on the dependence of values for the field of the second dataset on values for the field of the first dataset.

15. The computer readable storage medium of claim 14 , wherein the method further comprises: generating at least one organic query suggestion that is based on at least one previous query submitted by one or more previous users; and presenting said at least one organic query suggestion along with at least one synthetic query suggestion.

15. The computer readable storage medium of claim 14 , wherein the method further comprises: generating at least one organic query suggestion that is based on at least one previous query submitted by one or more previous users; and presenting said at least one organic query suggestion along with at least one synthetic query suggestion. 17. The computer readable storage medium of claim 15 , wherein the method further comprises presenting said at least one organic query suggestion along with said at least one synthetic query suggestion without distinguishing said at least one organic query suggestion from said at least one synthetic query suggestion.

16. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing-devices, cause performance of: generating an index mapping data objects to terms associated with the data objects; generating a graph describing hierarchical relationships between each of the data objects; receiving a search request comprising a plurality of search terms; based on the index, calculating multiple candidate sets of data objects by, for each particular term in the plurality of search terms, identifying a particular candidate set of data objects that are mapped to the particular term; calculating priority scores for at least the data objects in the candidate sets based at least in part on one or more of: a link analysis of the graph; or metadata describing structural constraints upon the data objects; based on the graph, identifying one or more search result subgraphs, wherein each particular subgraph of the one or more search result subgraphs is a hierarchy of data objects that comprises, for each particular term, at least one data object mapped to the particular term in the index; wherein identifying the one or more search result subgraphs comprises investigating the hierarchical relationships described by the graph, in an order that is based on the priority scores, to locate at least one ancestor object that, for each particular candidate set, is the same as, or an ancestor of, at least one member object of that particular candidate set; providing information indicating the one or more search result subgraphs in response to the search request.

16. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing-devices, cause performance of: generating an index mapping data objects to terms associated with the data objects; generating a graph describing hierarchical relationships between each of the data objects; receiving a search request comprising a plurality of search terms; based on the index, calculating multiple candidate sets of data objects by, for each particular term in the plurality of search terms, identifying a particular candidate set of data objects that are mapped to the particular term; calculating priority scores for at least the data objects in the candidate sets based at least in part on one or more of: a link analysis of the graph; or metadata describing structural constraints upon the data objects; based on the graph, identifying one or more search result subgraphs, wherein each particular subgraph of the one or more search result subgraphs is a hierarchy of data objects that comprises, for each particular term, at least one data object mapped to the particular term in the index; wherein identifying the one or more search result subgraphs comprises investigating the hierarchical relationships described by the graph, in an order that is based on the priority scores, to locate at least one ancestor object that, for each particular candidate set, is the same as, or an ancestor of, at least one member object of that particular candidate set; providing information indicating the one or more search result subgraphs in response to the search request. 19. The one or more non-transitory computer-readable media of claim 16 , wherein the data objects are normalized and the search request is unstructured.

2. The document collaboration system of claim 1 , wherein the processor generates information that is used to display the document adjacent to at least one of the first edit and the second edit.

2. The document collaboration system of claim 1 , wherein the processor generates information that is used to display the document adjacent to at least one of the first edit and the second edit. 3. The document collaboration system of claim 2 , wherein the processor generates the information such that it does not include the second edit based on the identification of a user requesting to view the document.

1. An autonomous wearable computing device comprising: a first glove having fingers and a second glove having fingers, said first glove being adapted to fit the left hand of a user, said first glove having a first portion on a palm side and a second portion on a back side, said second glove being adapted to fit the right hand of said user, said second glove having a third portion on a palm side and a fourth portion on a back side, said first glove having a first set of indicia mounted on said first portion thereof and a second set of indicia mounted on said second portion thereof, said second glove having a third set of indicia mounted on said third portion thereof, and a fourth set of indicia mounted on said fourth portion thereof; first keys mounted within the first portion of said first glove in association with each indicium of said first set of indicia, said first keys corresponding to the keys of a keyboard of arbitrary format and content to be struck by the fingers of the left hand, said first keys having indicia mounted thereon, said indicia mounted on said first keys identifying the letters, numbers, or symbols associated to said first keys; second keys mounted within the third portion of said second glove in association with each indicium of said third set of indicia, said second keys corresponding to the keys of said keyboard to be struck by the fingers of the right hand, said second keys having indicia mounted thereon, said indicia mounted on said second keys identifying the letters, numbers, or symbols associated to said second keys; the positions of said first set of indicia and said second set of indicia being mirror images of each other, said second set of indicia thereby corresponding to said first keys of said first glove, and providing said user with a representation of said first keys; the positions of said third set of indicia and said fourth set of indicia being mirror images of each other, said fourth set of indicia thereby corresponding to said second keys of said second glove, and providing said user with a representation of said second keys; a first microprocessor connected to said first keys of said first glove with a first set of interconnections, said first set of interconnections being embedded within said first glove; a second microprocessor connected to said second keys of said second glove with a second set of interconnections, said second set of interconnections being embedded within said second glove; said first microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said first glove to be struck by the fingers of the left hand, said second glove microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said second glove to be struck by the fingers of the right hand; said first microprocessor monitoring the flow of data input through the keys of said first glove, said second microprocessor monitoring the flow of data input through the keys of said second glove; a first set of external input/output ports mounted within said first glove, a second set of external input/output ports mounted within said second glove; said first and second sets of ports allowing said gloves to be interfaced with any processing unit that can be interfaced with a conventional keyboard; first means for enabling said gloves to transmit and receive information to and from any data processing unit that can be interfaced with said gloves, and allowing said user to easily interpret the information that is transmitted or received; second means for providing said gloves with autonomous computing capabilities.

1. An autonomous wearable computing device comprising: a first glove having fingers and a second glove having fingers, said first glove being adapted to fit the left hand of a user, said first glove having a first portion on a palm side and a second portion on a back side, said second glove being adapted to fit the right hand of said user, said second glove having a third portion on a palm side and a fourth portion on a back side, said first glove having a first set of indicia mounted on said first portion thereof and a second set of indicia mounted on said second portion thereof, said second glove having a third set of indicia mounted on said third portion thereof, and a fourth set of indicia mounted on said fourth portion thereof; first keys mounted within the first portion of said first glove in association with each indicium of said first set of indicia, said first keys corresponding to the keys of a keyboard of arbitrary format and content to be struck by the fingers of the left hand, said first keys having indicia mounted thereon, said indicia mounted on said first keys identifying the letters, numbers, or symbols associated to said first keys; second keys mounted within the third portion of said second glove in association with each indicium of said third set of indicia, said second keys corresponding to the keys of said keyboard to be struck by the fingers of the right hand, said second keys having indicia mounted thereon, said indicia mounted on said second keys identifying the letters, numbers, or symbols associated to said second keys; the positions of said first set of indicia and said second set of indicia being mirror images of each other, said second set of indicia thereby corresponding to said first keys of said first glove, and providing said user with a representation of said first keys; the positions of said third set of indicia and said fourth set of indicia being mirror images of each other, said fourth set of indicia thereby corresponding to said second keys of said second glove, and providing said user with a representation of said second keys; a first microprocessor connected to said first keys of said first glove with a first set of interconnections, said first set of interconnections being embedded within said first glove; a second microprocessor connected to said second keys of said second glove with a second set of interconnections, said second set of interconnections being embedded within said second glove; said first microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said first glove to be struck by the fingers of the left hand, said second glove microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said second glove to be struck by the fingers of the right hand; said first microprocessor monitoring the flow of data input through the keys of said first glove, said second microprocessor monitoring the flow of data input through the keys of said second glove; a first set of external input/output ports mounted within said first glove, a second set of external input/output ports mounted within said second glove; said first and second sets of ports allowing said gloves to be interfaced with any processing unit that can be interfaced with a conventional keyboard; first means for enabling said gloves to transmit and receive information to and from any data processing unit that can be interfaced with said gloves, and allowing said user to easily interpret the information that is transmitted or received; second means for providing said gloves with autonomous computing capabilities. 5. The autonomous wearable computing device as claimed in claim 1 wherein a first means comprise: a first interface connecting a first internal data processing unit to a first audio-based mini output display, and a second interface connecting a second internal data processing unit to a second audio-based mini output display; said audio-based output displays being mounted within the glove and connected into a headset through said first and second external ports, said headset allowing said user to hear the information transmitted to and received by said gloves.

41. The system of claim 1 , wherein the processor implements the first processing node and the second processing node for denying the relevant network access or activity by intercepting the relevant network access or activity.

41. The system of claim 1 , wherein the processor implements the first processing node and the second processing node for denying the relevant network access or activity by intercepting the relevant network access or activity. 42. The system of claim 41 , wherein the processor implements the first processing node and the second processing node for intercepting to occur at a same time the live-data flow is in active transmission between the endpoints of the network before an event is finalized.

10. A computer readable medium encoded with a computer program for distinguishing between text strokes and non-text strokes in digital ink, the computer process comprising: detecting a stroke in the digital ink; generating a classification model based on at least one stroke feature of the stroke, wherein the model defines a posterior probability that the stroke is a text stroke; labeling the stroke as a text stroke or a non-text stroke based on the posterior probability; dividing the stroke into fragments at points corresponding to local maxima in the curvature of the stroke; and detecting the at least one stroke feature of the stroke as a total absolute curvature of the largest fragment of the stroke in the digital ink.

10. A computer readable medium encoded with a computer program for distinguishing between text strokes and non-text strokes in digital ink, the computer process comprising: detecting a stroke in the digital ink; generating a classification model based on at least one stroke feature of the stroke, wherein the model defines a posterior probability that the stroke is a text stroke; labeling the stroke as a text stroke or a non-text stroke based on the posterior probability; dividing the stroke into fragments at points corresponding to local maxima in the curvature of the stroke; and detecting the at least one stroke feature of the stroke as a total absolute curvature of the largest fragment of the stroke in the digital ink. 17. The computer readable medium of claim 10 wherein the computer process further comprises: dividing the stroke into fragments at points corresponding to local maxima in the curvature of the stroke; and detecting the at least one stroke feature of the stroke as a direction of the largest fragment of the stroke in the digital ink.

28. The computer readable medium of claim 27 , wherein said performing a data transformation comprises automatically transforming said data change into a transformation script of a transformation language for implementation by said join engine peer.

28. The computer readable medium of claim 27 , wherein said performing a data transformation comprises automatically transforming said data change into a transformation script of a transformation language for implementation by said join engine peer. 29. The computer readable medium of claim 28 , wherein said transformation language is compliant with XSLT syntax.

14. A method as in claim 13 , further comprising setting a state of at least one page table entry bit for indicating, on a code page by code page basis, whether the code page is partitioned into said first and second sections for storing instruction words and at least one instruction word extension, or whether the code page is comprised instead of a single section storing only instruction words.

14. A method as in claim 13 , further comprising setting a state of at least one page table entry bit for indicating, on a code page by code page basis, whether the code page is partitioned into said first and second sections for storing instruction words and at least one instruction word extension, or whether the code page is comprised instead of a single section storing only instruction words. 15. A method as in claim 14 , further comprising outputting said at least one page table entry bit from a translation lookaside buffer (TLB).

5. A system comprising: an electronic data store configured to store item association information that associates a portion of each of a plurality of digital content items with a content characteristic; and a computing device, comprising a physical processor and memory, that is in communication with the electronic data store, the computing device configured to: receive context information associated with a current context of a user, wherein the context information includes at least one of a current location of the user or a current activity of the user; determine a context attribute associated with the current context of the user based at least in part on the context information; determine a content characteristic that is identified in stored context-to-characteristic association information as being associated with the context attribute, wherein the content characteristic is not the current location of the user and the content characteristic is not the current activity of the user; determine a recommended portion of a digital content item, selected from among the plurality of digital content items, to be consumed in the current context, wherein the recommended portion of the digital content item is determined based at least in part on a determination that content association information indicates that the content characteristic that is identified in the stored context-to-characteristic association information as being associated with the context attribute is also associated with the recommended portion of the digital content item; and cause presentation of an option whose selection enables the user to access at least the recommended portion of the digital content item.

5. A system comprising: an electronic data store configured to store item association information that associates a portion of each of a plurality of digital content items with a content characteristic; and a computing device, comprising a physical processor and memory, that is in communication with the electronic data store, the computing device configured to: receive context information associated with a current context of a user, wherein the context information includes at least one of a current location of the user or a current activity of the user; determine a context attribute associated with the current context of the user based at least in part on the context information; determine a content characteristic that is identified in stored context-to-characteristic association information as being associated with the context attribute, wherein the content characteristic is not the current location of the user and the content characteristic is not the current activity of the user; determine a recommended portion of a digital content item, selected from among the plurality of digital content items, to be consumed in the current context, wherein the recommended portion of the digital content item is determined based at least in part on a determination that content association information indicates that the content characteristic that is identified in the stored context-to-characteristic association information as being associated with the context attribute is also associated with the recommended portion of the digital content item; and cause presentation of an option whose selection enables the user to access at least the recommended portion of the digital content item. 9. The system of claim 5 , wherein the context-to-characteristic association information indicates that content associated with the content characteristic is appropriate to be consumed in a context associated with the context attribute.

41. The apparatus of claim 39 , wherein the query is generated by a user.

41. The apparatus of claim 39 , wherein the query is generated by a user. 42. The apparatus of claim 41 , wherein translating the query comprises: searching a cache of a set of recent popular queries for a cached query that is substantially similar to the query received from the user, providing the one or more of the cached queries to the user for selection by the user; and in response to a user input selecting one of the cached queries, translating the received query into the selected query.

23. The method of claim 17 wherein the disabling act comprises the act of determining whether to enable access based on a privilege associated with the user, the privilege indicating information about electronic learning for that user.

23. The method of claim 17 wherein the disabling act comprises the act of determining whether to enable access based on a privilege associated with the user, the privilege indicating information about electronic learning for that user. 25. The method of claim 23 wherein the privilege associated with the user indicates whether the user may access a group of business intelligence objects based on the user's electronic learning history.

1. A messaging system for use in a network, the messaging system comprising: a plurality of network entities which include both publishing entities and subscribing entities, the publishing entities publishing content of which the subscribing entities have need, wherein information embedded within the published content defines a data hierarchy for the published content exchanged between the publishing entities and subscribing entities; wherein the data hierarchy defines at least a child tier and a parent tier, where the child tier contains a plurality of published content contributed by a plurality of said publishing entities; and wherein the data hierarchy determines virtual connections formed between the plurality of network entities in response to publication and subscription requests exchanged between the entities, such that the virtual connections established between network entities form a hierarchy corresponding to the data hierarchy, whereby subscription by one of said subscribing entities to the parent tier of the data hierarchy results in the subscribing entity receiving all of said plurality of published content in the child tier; wherein the data hierarchy comprises a plurality of child-tiered data elements that each correspond to a portion of data that forms a parent-tiered data element; wherein different entities publish different ones of the child-tiered data elements; wherein responsive to a subscribing entity's subscription to the parent-tiered data element, the subscribing entity receives the plurality of child-tiered data elements via the virtual connections.

1. A messaging system for use in a network, the messaging system comprising: a plurality of network entities which include both publishing entities and subscribing entities, the publishing entities publishing content of which the subscribing entities have need, wherein information embedded within the published content defines a data hierarchy for the published content exchanged between the publishing entities and subscribing entities; wherein the data hierarchy defines at least a child tier and a parent tier, where the child tier contains a plurality of published content contributed by a plurality of said publishing entities; and wherein the data hierarchy determines virtual connections formed between the plurality of network entities in response to publication and subscription requests exchanged between the entities, such that the virtual connections established between network entities form a hierarchy corresponding to the data hierarchy, whereby subscription by one of said subscribing entities to the parent tier of the data hierarchy results in the subscribing entity receiving all of said plurality of published content in the child tier; wherein the data hierarchy comprises a plurality of child-tiered data elements that each correspond to a portion of data that forms a parent-tiered data element; wherein different entities publish different ones of the child-tiered data elements; wherein responsive to a subscribing entity's subscription to the parent-tiered data element, the subscribing entity receives the plurality of child-tiered data elements via the virtual connections. 22. The system of claim 1 wherein said plurality of network entities comprise entities of a communication network monitoring system.

1. A computer program product for refining a search result, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable/executable by a processor to perform a method comprising: accepting, by the processor, a first search query comprising one or more keywords; generating, by the processor, a first search result comprising a plurality of first search result members according to the first search query; accepting, by the processor, a refinement command from a user selecting a plurality of undesired first search result members; determining, by the processor, a singular scope for the selected plurality of undesired first search result members; generating, by the processor, a second search result from the determined singular scope, the second search result comprising second search result members inferred from the determined singular scope, and wherein the generating of the second search result comprises: determining which of the one or more keywords in the first search query is related to the selected undesired search result members; determining a contextual annotation for each of the determined one or more keywords in the first search query; and generating the second search result from the determined one or more keywords and the determined contextual annotation of each of the determined one or more keywords; automatically refining, by the processor, the first search result using the second search result, wherein the refining comprises subtracting the second search result from the first search result; and providing, by the processor, the automatically refined search result.

1. A computer program product for refining a search result, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable/executable by a processor to perform a method comprising: accepting, by the processor, a first search query comprising one or more keywords; generating, by the processor, a first search result comprising a plurality of first search result members according to the first search query; accepting, by the processor, a refinement command from a user selecting a plurality of undesired first search result members; determining, by the processor, a singular scope for the selected plurality of undesired first search result members; generating, by the processor, a second search result from the determined singular scope, the second search result comprising second search result members inferred from the determined singular scope, and wherein the generating of the second search result comprises: determining which of the one or more keywords in the first search query is related to the selected undesired search result members; determining a contextual annotation for each of the determined one or more keywords in the first search query; and generating the second search result from the determined one or more keywords and the determined contextual annotation of each of the determined one or more keywords; automatically refining, by the processor, the first search result using the second search result, wherein the refining comprises subtracting the second search result from the first search result; and providing, by the processor, the automatically refined search result. 3. The computer program product of claim 1 , wherein automatically refining the first search result comprises: excluding the second search result members from the first search result members.

16. A system for performing an electronic search of a database, said system comprising: a processor; and a memory coupled to the processor; wherein the memory has a set of computer readable instructions stored therein, that when executed by the processor, cause the processor to: (i) process user input acquired through user interaction with an icon selection tool to define at least two selected graphical icons from a set of graphical icons in the database; (ii) process user input to define a search weighting preference for each of the at least two selected graphical icons; (iii) process the at least two selected graphical icons to generate a ranked item list for each of the at least two selected graphical icons based on metadata, wherein the ranked item lists each comprise: items having an associated numerical ranking relative to other items in the ranked item list, wherein the metadata include seed products associated with corresponding graphical icons; (iv) process the search weighting preferences and the ranked item lists for the at least two selected graphical icons to generate a weighted ranked item list for each of the at least two selected graphical icons, the weighted ranked item lists being generated by applying each of the search weighting preferences to the numerical rankings of the items in the ranked item list, and wherein the seed products are weighted, using the keywords and combined into a single ranked list for each corresponding graphical icon, wherein the single ranked list is also used to generate the ranked item list; (v) generate a combined ranked item list by processing the weighted ranked item lists for the at least two selected graphical icons and grouping the items from each of the weighted rank item lists into the combined ranked item list.

16. A system for performing an electronic search of a database, said system comprising: a processor; and a memory coupled to the processor; wherein the memory has a set of computer readable instructions stored therein, that when executed by the processor, cause the processor to: (i) process user input acquired through user interaction with an icon selection tool to define at least two selected graphical icons from a set of graphical icons in the database; (ii) process user input to define a search weighting preference for each of the at least two selected graphical icons; (iii) process the at least two selected graphical icons to generate a ranked item list for each of the at least two selected graphical icons based on metadata, wherein the ranked item lists each comprise: items having an associated numerical ranking relative to other items in the ranked item list, wherein the metadata include seed products associated with corresponding graphical icons; (iv) process the search weighting preferences and the ranked item lists for the at least two selected graphical icons to generate a weighted ranked item list for each of the at least two selected graphical icons, the weighted ranked item lists being generated by applying each of the search weighting preferences to the numerical rankings of the items in the ranked item list, and wherein the seed products are weighted, using the keywords and combined into a single ranked list for each corresponding graphical icon, wherein the single ranked list is also used to generate the ranked item list; (v) generate a combined ranked item list by processing the weighted ranked item lists for the at least two selected graphical icons and grouping the items from each of the weighted rank item lists into the combined ranked item list. 29. The system of claim 16 , wherein the metadata comprises keywords.

21. A non-transitory computer readable medium wherein program instruction means are recorded on said medium for instructing a processor to present an organization structure, comprising: first program instruction means for providing a database of names of individuals in an organization, each of said individual names having an associated manager name and a profile, and presenting a view of the names of individuals on a display to a user; second program instruction means for receiving, from the user, a selection of a first and a second individual from said organization; third program instruction means for constructing automatically, in response to the selection, a view showing names of those in a manager chain of said first and second individuals, every name in the manager chain being a name of at least one of the first individual, the second individual or a manager of either of the first or second individual up to the point where there is a common manager, and then a single manager chain to at least one manager at a higher level than the common manager in said organization, wherein the single manager chain showing only manager names above the common manager, wherein the constructing is configured to construct the view from any first and second individual in said organization regardless of whether the first and second individual share a common immediate manager; fourth program instruction means for appending a nesting control indicator to the names in said view; and fifth program instruction means for displaying said view on the display to the user, wherein the view allows the user to: access said profile by selecting a name in said view, and expand said view by selecting said nesting control indicator, wherein the profile is displayed in proximity to the respective name in the view, and wherein the profile includes at least: a job title and a work location; and wherein all of said program instruction means are recorded on said medium.

21. A non-transitory computer readable medium wherein program instruction means are recorded on said medium for instructing a processor to present an organization structure, comprising: first program instruction means for providing a database of names of individuals in an organization, each of said individual names having an associated manager name and a profile, and presenting a view of the names of individuals on a display to a user; second program instruction means for receiving, from the user, a selection of a first and a second individual from said organization; third program instruction means for constructing automatically, in response to the selection, a view showing names of those in a manager chain of said first and second individuals, every name in the manager chain being a name of at least one of the first individual, the second individual or a manager of either of the first or second individual up to the point where there is a common manager, and then a single manager chain to at least one manager at a higher level than the common manager in said organization, wherein the single manager chain showing only manager names above the common manager, wherein the constructing is configured to construct the view from any first and second individual in said organization regardless of whether the first and second individual share a common immediate manager; fourth program instruction means for appending a nesting control indicator to the names in said view; and fifth program instruction means for displaying said view on the display to the user, wherein the view allows the user to: access said profile by selecting a name in said view, and expand said view by selecting said nesting control indicator, wherein the profile is displayed in proximity to the respective name in the view, and wherein the profile includes at least: a job title and a work location; and wherein all of said program instruction means are recorded on said medium. 22. The non-transitory computer readable medium of claim 21 , further comprising: sixth program instruction means for providing people awareness data for each of said individuals in said organization; wherein the fourth program instruction further comprises means for appending an indicator of said people awareness data to the names in said view; and wherein the fifth program instruction means for displaying said view on the display wherein the view further allows a user to initiate a communication with an individual by selecting said people awareness indicator.

1. A method implemented on a computer for segmenting an input image into line segments and word segments, the input image being a binary image containing text, the method comprising: (a) horizontally down sampling the input image using a first down-sampling ratio; (b) detecting connected regions in the down-sampled image obtained in step (a); (c) identifying horizontally neighboring connected regions that belong to same lines to form line lists containing such horizontally neighboring connected regions; (d) segmenting the input image into a plurality of line segments of the input image, each line segment of the input image being a region of the input image that corresponds to a bounding box in the down-sampled image containing all connected regions in a corresponding line list obtained in step (c); and for each of the line segments of the input image obtained in step (d), (e) horizontally down sampling the line segment of the input image using a second down-sampling ratio; (f) detecting connected regions in the down-sampled line segment obtained in step (e); and (g) segmenting the line segment of the input image into word segments at one or more word segmentation positions using the connected regions obtained in step (f), wherein the word segmentation positions are a subset of positions corresponding to locations in gaps between the connected regions in the down-sampled line segment of step (e) that have been detected in step (f), wherein the second down-sampling ratio is smaller than the first down-sampling ratio.

1. A method implemented on a computer for segmenting an input image into line segments and word segments, the input image being a binary image containing text, the method comprising: (a) horizontally down sampling the input image using a first down-sampling ratio; (b) detecting connected regions in the down-sampled image obtained in step (a); (c) identifying horizontally neighboring connected regions that belong to same lines to form line lists containing such horizontally neighboring connected regions; (d) segmenting the input image into a plurality of line segments of the input image, each line segment of the input image being a region of the input image that corresponds to a bounding box in the down-sampled image containing all connected regions in a corresponding line list obtained in step (c); and for each of the line segments of the input image obtained in step (d), (e) horizontally down sampling the line segment of the input image using a second down-sampling ratio; (f) detecting connected regions in the down-sampled line segment obtained in step (e); and (g) segmenting the line segment of the input image into word segments at one or more word segmentation positions using the connected regions obtained in step (f), wherein the word segmentation positions are a subset of positions corresponding to locations in gaps between the connected regions in the down-sampled line segment of step (e) that have been detected in step (f), wherein the second down-sampling ratio is smaller than the first down-sampling ratio. 2. The method of claim 1 , wherein the first down-sampling ratio is calculated from the input image, and the second down-sampling ratio for each line segment is calculated from the line segment.

1. A method, implemented by an information handling system, that copies records between tables in a relational database, the method comprising: receiving a Structured Query Language (SQL) table COPY statement, wherein the COPY statement is devoid of an INSERT clause and identifies a source table and a target table; retrieving a plurality of column names from a metadata corresponding to the source table; and generating an SQL statement, based upon the COPY statement, that includes an INSERT INTO clause pertaining to the target table and a SELECT clause pertaining to the source table, wherein the INSERT INTO clause includes a set of target column names corresponding to the plurality of column names, and wherein the SELECT clause includes a set of corresponding source column names.

1. A method, implemented by an information handling system, that copies records between tables in a relational database, the method comprising: receiving a Structured Query Language (SQL) table COPY statement, wherein the COPY statement is devoid of an INSERT clause and identifies a source table and a target table; retrieving a plurality of column names from a metadata corresponding to the source table; and generating an SQL statement, based upon the COPY statement, that includes an INSERT INTO clause pertaining to the target table and a SELECT clause pertaining to the source table, wherein the INSERT INTO clause includes a set of target column names corresponding to the plurality of column names, and wherein the SELECT clause includes a set of corresponding source column names. 2. The method of claim 1 , wherein the COPY statement further identifies a SET clause, the method further comprising: receiving a SET clause predicate corresponding to the identified SET clause, wherein the SET clause predicate includes a name element and an expression element; comparing the name element to the set of source column names; in response to the name element matching one of the source column names, replacing the matching source column name in the SELECT clause with the expression element; and in response to the name element failing to match one of the source column names: adding the name element to the set of target names included in the INSERT INTO clause; and adding the expression element to the set of source names included in the SELECT clause, wherein placement of the expression element within the SELECT clause matches placement of the name element in the INSERT INTO clause.

1. A device, comprising: an image acquisition unit configured to acquire a first image; a transmission unit configured to transmit first information associated with the first image and an assistance information to a server, the server being associated with a first feature quantity dictionary; a receiving unit configured to receive a second feature quantity dictionary from the server in response to the transmission, the second feature quantity dictionary comprising less information than the first feature quantity dictionary; and an identification unit configured to identify an object within the first image using the second feature quantity dictionary, wherein the second feature quantity dictionary is a filtered version of the first feature quantity dictionary that is stored on the server, and the second feature quantity dictionary represents a subset of the first feature quantity dictionary and contains only selected contents of the first feature quantity dictionary having a highest relation to the first information and satisfying a threshold criteria, wherein an amount of contents that is selected from the first feature quantity dictionary as the subset forming the second feature quantity dictionary is based on a capability or processing ability of the device, and the amount of contents selected is determined and set based on a capability information contained in the assistance information transmitted from the transmission unit to the server, and wherein the image acquisition unit, the transmission unit, the receiving unit, and the identification unit are each implemented via at least one processor.

1. A device, comprising: an image acquisition unit configured to acquire a first image; a transmission unit configured to transmit first information associated with the first image and an assistance information to a server, the server being associated with a first feature quantity dictionary; a receiving unit configured to receive a second feature quantity dictionary from the server in response to the transmission, the second feature quantity dictionary comprising less information than the first feature quantity dictionary; and an identification unit configured to identify an object within the first image using the second feature quantity dictionary, wherein the second feature quantity dictionary is a filtered version of the first feature quantity dictionary that is stored on the server, and the second feature quantity dictionary represents a subset of the first feature quantity dictionary and contains only selected contents of the first feature quantity dictionary having a highest relation to the first information and satisfying a threshold criteria, wherein an amount of contents that is selected from the first feature quantity dictionary as the subset forming the second feature quantity dictionary is based on a capability or processing ability of the device, and the amount of contents selected is determined and set based on a capability information contained in the assistance information transmitted from the transmission unit to the server, and wherein the image acquisition unit, the transmission unit, the receiving unit, and the identification unit are each implemented via at least one processor. 7. The device of claim 1 , wherein the transmitting unit is further configured to transmit, to the server, second information associated with the first image, the second information comprising at least one geographic position associated with the first image.

4. The method of claim 1 wherein decoding of the first coded portion produces a first image result, and decoding of the modified first arithmetically coded portion produces a modified first image result that is different from the first image result.

4. The method of claim 1 wherein decoding of the first coded portion produces a first image result, and decoding of the modified first arithmetically coded portion produces a modified first image result that is different from the first image result. 5. The method of claim 4 wherein determining the modified first arithmetically coded portion comprises determining a modified first arithmetically coded portion for which the modified first image result has a difference from the first image result that is (1) imperceptible, from a viewer's standpoint, and (2) detectable by a processing device.

11. The system of claim 7 , the operations further comprising assigning a multiplier value to each image in the subset of training images, the multiplier value being greater than one.

11. The system of claim 7 , the operations further comprising assigning a multiplier value to each image in the subset of training images, the multiplier value being greater than one. 12. The system of claim 11 , wherein generating a re-trained image relevance model comprises generating the re-trained image relevance model based on the visual features for the subset of training images and the assigned multiplier value.

9. The method of claim 1 , further comprising: monitoring the social network input dictionary to determine if one or more terms in the social network input dictionary have a current usage metric that meets a threshold indicative of declining use of the term in communications within the digital social network; and reducing a relative priority of the one or more terms in the social network input dictionary if the current usage metric meets the threshold.

9. The method of claim 1 , further comprising: monitoring the social network input dictionary to determine if one or more terms in the social network input dictionary have a current usage metric that meets a threshold indicative of declining use of the term in communications within the digital social network; and reducing a relative priority of the one or more terms in the social network input dictionary if the current usage metric meets the threshold. 10. The method of claim 9 , further comprising: determining if the usage metric or relative priority of the one or more terms in the social network input dictionary meet criteria for removal of the one or more terms from the social network input dictionary; and deleting an entry in the social network input dictionary associated with the one or more terms if an associated usage metric or relative priority of the one or more terms meet the criteria for removal.

4. The method of claim 1 , wherein the displayable objects correspond to functions of the plurality of applications of the mobile device that are accessible by way of different icons of the first user interface.

4. The method of claim 1 , wherein the displayable objects correspond to functions of the plurality of applications of the mobile device that are accessible by way of different icons of the first user interface. 5. The method of claim 4 , wherein the functions of the plurality of applications of the mobile device comprise at least two of device settings, voice communications, text communications, streaming video, Internet access, music, shopping, games, banking, stocks, navigation, weather, or local news.

12. The method of claim 11 , wherein allowing the teacher to select one of the learners comprises: displaying a list of the audio messages in an audio message queue; and allowing the teacher to browse and select one of the audio messages in the audio message queue.

12. The method of claim 11 , wherein allowing the teacher to select one of the learners comprises: displaying a list of the audio messages in an audio message queue; and allowing the teacher to browse and select one of the audio messages in the audio message queue. 13. The method of claim 12 , further comprising: allowing the teacher to send a private text message to the selected learner.

1. A method of selecting an advertisement associated with a geographic location, comprising: receiving, using one or more processors, a request from a remote computer, the request identifying the geographic location from location signals associated with the remote computer, the location signals determined at the remote computer using an antenna for receiving location signals and associated software for determining the position of the remote computer based on the received location signals; determining, using the one or more processors, a listing associated with the geographic location and the request; determining, using the one or more processors, a number of previous users that selected the listing associated with the geographic location in response to the previous users providing a first search term; when the number of previous users exceeds a predetermined threshold, selecting, using the one or more processors, the first search term as one or more search terms associated with the geographic location; when the number of previous users does not exceed the predetermined threshold, determining, using the one or more processors, a number of listing categories associated with the geographic location; when the number of listing categories falls below a given threshold, selecting, using the one or more processors, the listing categories as the one or more search terms associated with the geographic location; when the number of listing categories does not fall below the given threshold, determining, using the one or more processors and without user input, a point of interest that is associated with the geographic location and selecting a title of the point of interest as the one or more search terms associated with the geographic location; determining, using the one or more processors, an advertisement based at least in part on the one or more search terms associated with the geographic location; and transmitting, using the one or more processors, the advertisement to an electronic display of the remote computer for display to the user in response to the request.

1. A method of selecting an advertisement associated with a geographic location, comprising: receiving, using one or more processors, a request from a remote computer, the request identifying the geographic location from location signals associated with the remote computer, the location signals determined at the remote computer using an antenna for receiving location signals and associated software for determining the position of the remote computer based on the received location signals; determining, using the one or more processors, a listing associated with the geographic location and the request; determining, using the one or more processors, a number of previous users that selected the listing associated with the geographic location in response to the previous users providing a first search term; when the number of previous users exceeds a predetermined threshold, selecting, using the one or more processors, the first search term as one or more search terms associated with the geographic location; when the number of previous users does not exceed the predetermined threshold, determining, using the one or more processors, a number of listing categories associated with the geographic location; when the number of listing categories falls below a given threshold, selecting, using the one or more processors, the listing categories as the one or more search terms associated with the geographic location; when the number of listing categories does not fall below the given threshold, determining, using the one or more processors and without user input, a point of interest that is associated with the geographic location and selecting a title of the point of interest as the one or more search terms associated with the geographic location; determining, using the one or more processors, an advertisement based at least in part on the one or more search terms associated with the geographic location; and transmitting, using the one or more processors, the advertisement to an electronic display of the remote computer for display to the user in response to the request. 4. The method of claim 1 , wherein the antenna for receiving location signals at the remote computer comprises one or more of an antenna associated with a GPS receiver or a cell phone antenna.

1. A method of enabling input on an electronic device having stored therein a plurality of objects that comprise a number of raw inputs, a number of characters, and a number of segments, each raw input having one or more of the characters associated therewith, each segment comprising a plurality of the characters, the method comprising: receiving a string of reference characters; obtaining the raw inputs with which the reference characters are associated; generating a proposed character interpretation of the obtained raw inputs; determining that at least a portion of the proposed character interpretation and a corresponding at least portion of the string of reference characters differ; and responsive to the determining, storing the at least portion of the string of reference characters as an object of the plurality of objects.

1. A method of enabling input on an electronic device having stored therein a plurality of objects that comprise a number of raw inputs, a number of characters, and a number of segments, each raw input having one or more of the characters associated therewith, each segment comprising a plurality of the characters, the method comprising: receiving a string of reference characters; obtaining the raw inputs with which the reference characters are associated; generating a proposed character interpretation of the obtained raw inputs; determining that at least a portion of the proposed character interpretation and a corresponding at least portion of the string of reference characters differ; and responsive to the determining, storing the at least portion of the string of reference characters as an object of the plurality of objects. 6. The method of claim 1 wherein the plurality of objects further comprise a number of candidates and a number of combination objects, each combination object comprising a segment plus one of a character and a segment, and wherein the number of segments comprise a number of generic segments and a number of learned segments, and further comprising consulting one or more of the number of raw inputs, the number of characters, the number of combination objects, the number of generic segments, the number of learned segments, and the number of candidates in the generating of the proposed character interpretation.

8. A message correlation method comprising: determining, by a processor, whether there are two or more outstanding queries to which a response from a user to any of the outstanding queries that includes no context would render the response uncorrelatable to one of the outstanding queries; and Correlating, by the processor, a keyword associated with a response to an outstanding query, wherein, when there is a conflict where the keyword is used in at least two of the two or more outstanding queries or the keyword is not used in the two or more outstanding queries, a supplemental query is sent to the user requesting clarification.

8. A message correlation method comprising: determining, by a processor, whether there are two or more outstanding queries to which a response from a user to any of the outstanding queries that includes no context would render the response uncorrelatable to one of the outstanding queries; and Correlating, by the processor, a keyword associated with a response to an outstanding query, wherein, when there is a conflict where the keyword is used in at least two of the two or more outstanding queries or the keyword is not used in the two or more outstanding queries, a supplemental query is sent to the user requesting clarification. 13. The method of claim 8 , wherein one or more of an end user, an end user device and a keyword management module select the keyword.

24. A computer system according to claim 23 wherein to compute a relevance for a single merchant location relative to a set of merchant locations within the transaction data, said computer system is programmed to: extract relevant features from a plurality of merchant locations grouped into sets to generate a document for each set; collect the generated documents within a dictionary; form a sparse matrix utilizing the dictionary whereby the relevance of each field value and tokenized field value in the generated documents is computed, utilizing the extracted relevant features based on at least one of a term frequency and an inverse document frequency; and join a matrix of merchant location level weights to a matrix of merchant group weights based on field types and field values within the sparse matrix.

24. A computer system according to claim 23 wherein to compute a relevance for a single merchant location relative to a set of merchant locations within the transaction data, said computer system is programmed to: extract relevant features from a plurality of merchant locations grouped into sets to generate a document for each set; collect the generated documents within a dictionary; form a sparse matrix utilizing the dictionary whereby the relevance of each field value and tokenized field value in the generated documents is computed, utilizing the extracted relevant features based on at least one of a term frequency and an inverse document frequency; and join a matrix of merchant location level weights to a matrix of merchant group weights based on field types and field values within the sparse matrix. 26. A computer system according to claim 24 wherein said computer system is programmed to utilize a sum of the merchant location level weights and the merchant group weights within a relevance engine to determine the relevance of each merchant location to each set of merchant locations; and output the set of merchant locations with the highest relevance as a prediction.

1. A computer-implemented method for searching business objects data sources, the method comprising: providing a plurality of computer-readable master tables, each computer-readable master table associated with a respective business objects data source of a plurality of business objects data sources, each business objects data source stores a plurality of data items; receiving a search query including one or more query terms, each query term represents first metadata included in metadata associated with a plurality of business objects data sources identifying, for each query term, one or more business objects data sources that are associated with the first metadata by searching a plurality of computer-searchable index documents, each computer-searchable index document references the metadata; identifying, for each query term, the metadata associated with the identified one or more business objects data sources by searching the plurality of computer-readable master tables, wherein the identified metadata associated with the identified one or more business objects data sources includes the first metadata and additional metadata associated with the identified one or more business objects data sources; searching the identified one or more business objects data sources for data items that satisfy the identified metadata; and providing representations of the data items and identified metadata in response to receiving the search query.

1. A computer-implemented method for searching business objects data sources, the method comprising: providing a plurality of computer-readable master tables, each computer-readable master table associated with a respective business objects data source of a plurality of business objects data sources, each business objects data source stores a plurality of data items; receiving a search query including one or more query terms, each query term represents first metadata included in metadata associated with a plurality of business objects data sources identifying, for each query term, one or more business objects data sources that are associated with the first metadata by searching a plurality of computer-searchable index documents, each computer-searchable index document references the metadata; identifying, for each query term, the metadata associated with the identified one or more business objects data sources by searching the plurality of computer-readable master tables, wherein the identified metadata associated with the identified one or more business objects data sources includes the first metadata and additional metadata associated with the identified one or more business objects data sources; searching the identified one or more business objects data sources for data items that satisfy the identified metadata; and providing representations of the data items and identified metadata in response to receiving the search query. 5. The method of claim 1 , wherein searching one or more business objects data sources to identify data items of the plurality of data items stored in each of the searched one or more business objects data sources for data items that satisfy the identified metadata comprises identifying a plurality of tuples, each tuple including a first metadata portion and a second metadata portion, each of which satisfies the respective query term.

1. An article comprising: a computer readable storage medium having stored thereon executable instructions that in response to being executed by one or more processors of a client-side computerized device operatively enable the one or more processors to: access information from an application layer interface; access a first parameter that is related to content, and a second parameter that identifies a linked set of documents; and in response to an input received through a single selectable feature of a user interface indicating a desire to advance to a next location within the linked set of documents that includes an instance of the content related to the first parameter: for a currently open document if the content is present in the currently open document, setting the next location to correspond to at least a portion of the currently open document in which the content is present; if the content is not present in the currently open document, identifying a next document within the linked set of documents in which the content is present, and setting the next location to correspond to at least a portion of the next document in which the content is present; and initiate display of the next location via a computer display monitor.

1. An article comprising: a computer readable storage medium having stored thereon executable instructions that in response to being executed by one or more processors of a client-side computerized device operatively enable the one or more processors to: access information from an application layer interface; access a first parameter that is related to content, and a second parameter that identifies a linked set of documents; and in response to an input received through a single selectable feature of a user interface indicating a desire to advance to a next location within the linked set of documents that includes an instance of the content related to the first parameter: for a currently open document if the content is present in the currently open document, setting the next location to correspond to at least a portion of the currently open document in which the content is present; if the content is not present in the currently open document, identifying a next document within the linked set of documents in which the content is present, and setting the next location to correspond to at least a portion of the next document in which the content is present; and initiate display of the next location via a computer display monitor. 2. The article of claim 1 , wherein at least one of the first parameter and/or second parameter are accessed via a user interface that comprises an interactive menu.

10. The method of claim 8 , wherein each of at least a subset of the identified potential matches is between a respective pair of elements including the actual element of the first document and the expected element of the second document.

10. The method of claim 8 , wherein each of at least a subset of the identified potential matches is between a respective pair of elements including the actual element of the first document and the expected element of the second document. 12. The method of claim 10 , further comprising, in response to a determination that there is at least one difference between the respective pair of elements, invoking a custom asserter to determine whether the at least one difference is significant as defined based at least in part by the custom rules of the custom asserter when the custom asserter is specified by the user.

1. Apparatus for recognizing selected speech based on acoustic models, the apparatus comprising: a processor responsive to selected data representing a sample of the selected speech for modifying the acoustic models; and a mechanism for defining a hierarchical structure which includes a plurality of levels, each level having one or more nodes thereon, each level in the structure arranged higher than every other level having a smaller number of nodes thereon than the other level, each node being associated with a probability measure which is determined based on at least the selected data, each node on each level having two or more nodes thereon being connected to a node on a second level higher than the level having two or more nodes thereon, the probability measure associated with each node on each level having two or more nodes thereon being a function of at least the probability measure associated with the node connected thereto on the second level, the acoustic models being modified based on at least the probability measure associated with each node on a selected level.

1. Apparatus for recognizing selected speech based on acoustic models, the apparatus comprising: a processor responsive to selected data representing a sample of the selected speech for modifying the acoustic models; and a mechanism for defining a hierarchical structure which includes a plurality of levels, each level having one or more nodes thereon, each level in the structure arranged higher than every other level having a smaller number of nodes thereon than the other level, each node being associated with a probability measure which is determined based on at least the selected data, each node on each level having two or more nodes thereon being connected to a node on a second level higher than the level having two or more nodes thereon, the probability measure associated with each node on each level having two or more nodes thereon being a function of at least the probability measure associated with the node connected thereto on the second level, the acoustic models being modified based on at least the probability measure associated with each node on a selected level. 4. The apparatus of claim 1 wherein the probability measure associated with each node is determined based also on second data representing a sample of at least second speech.

8. The system of claim 4 , wherein a data structure representing the directed graph is stored in a memory accessible by the first computing device.

8. The system of claim 4 , wherein a data structure representing the directed graph is stored in a memory accessible by the first computing device. 9. The system of claim 8 , wherein the data structure comprises the complexity information.

8. A speech recognition system comprising: a microphone configured to receive a speech signal; a frame constructor configured to create a plurality of frames from the speech signal; a feature extractor configured to produced feature vectors from the frames; and a decoder configured to: expand a search network based on a frame; determine a best hypothesis in the search network; modify a default beam threshold to produce a modified beam threshold, wherein modifying a default beam threshold further comprises modifying the default beam threshold based on at least one selected from a group consisting of: a time the frame is received, a speed with which the search network is increasing in size, and a number of active phones, wherein the default beam threshold is increased by an empirically determined amount if an acceleration of the speed with which the search network is increasing in size for the frame exceeds an empirically determined amount; and prune the search network using the modified beam threshold and the best hypothesis.

8. A speech recognition system comprising: a microphone configured to receive a speech signal; a frame constructor configured to create a plurality of frames from the speech signal; a feature extractor configured to produced feature vectors from the frames; and a decoder configured to: expand a search network based on a frame; determine a best hypothesis in the search network; modify a default beam threshold to produce a modified beam threshold, wherein modifying a default beam threshold further comprises modifying the default beam threshold based on at least one selected from a group consisting of: a time the frame is received, a speed with which the search network is increasing in size, and a number of active phones, wherein the default beam threshold is increased by an empirically determined amount if an acceleration of the speed with which the search network is increasing in size for the frame exceeds an empirically determined amount; and prune the search network using the modified beam threshold and the best hypothesis. 9. The speech recognition system of claim 8 , wherein the time the frame is received is used to increase the default beam threshold for a predetermined number of frames.

9. A system for producing search results, comprising: memory; one or more processors; and one or more programs, stored in the memory and executed by the one or more processors, the one or more programs including instructions for: receiving a search request associated with a user from the client system, the search request having one or more search terms; obtaining a user profile corresponding to the user, wherein the user profile is generated based in part on the user's prior computing activities, comprising one or more of browsing, searching, and messaging; obtaining search results for the search request; generating a personalized snippet for at least one of the search results in accordance with the obtained user profile, the snippet comprising a text portion of the search result chosen based on at least one or more search terms and one or more terms of the obtained user profile; and transmitting the search results and personalized snippet to the client system for display, wherein the generating includes identifying content associated with one of the search results, determining a profile similarity score for a term in the content, and generating a snippet based at least in part on the term when the profile similarity score is above a threshold, and wherein determining the profile similarity score includes identifying a respective term profile associated with the at least one term and determining a similarity between the profile information associated with the user profile and the respective term profile.

9. A system for producing search results, comprising: memory; one or more processors; and one or more programs, stored in the memory and executed by the one or more processors, the one or more programs including instructions for: receiving a search request associated with a user from the client system, the search request having one or more search terms; obtaining a user profile corresponding to the user, wherein the user profile is generated based in part on the user's prior computing activities, comprising one or more of browsing, searching, and messaging; obtaining search results for the search request; generating a personalized snippet for at least one of the search results in accordance with the obtained user profile, the snippet comprising a text portion of the search result chosen based on at least one or more search terms and one or more terms of the obtained user profile; and transmitting the search results and personalized snippet to the client system for display, wherein the generating includes identifying content associated with one of the search results, determining a profile similarity score for a term in the content, and generating a snippet based at least in part on the term when the profile similarity score is above a threshold, and wherein determining the profile similarity score includes identifying a respective term profile associated with the at least one term and determining a similarity between the profile information associated with the user profile and the respective term profile. 12. The system of claim 9 , wherein the profile information associated with the user profile and information associated with the respective term profile are each represented as a plurality of profile categories and respective weights.

1. A method for incrementally and multi-dimensionally adjusting prose style comprising: creating a database of sets of phrase synonyms within a data processing environment wherein a phrase is defined as a character string including one or more words, numbers, abbreviations or combinations thereof, and wherein set of phrase synonyms is defined as a set of phrases in which there is at least one phrase in the set for which all other phrases in the set can be substituted in prose usage without causing significant changes in the meaning of the prose or grammatical errors in the prose; assigning rankings and/or values to phrases in the database for each phrase's ranking and/or value with respect to a dimension of prose style, for at least two different dimensions of prose style; receiving input prose selected by a user via an interface between the user and a computer selected from a group consisting of: direct entry of prose by means of a physical or virtual keyboard, keypad, touchpad, or touch screen; importing prose from a file, document, or website; highlighting or identifying a portion of prose using a cursor; voice, speech, or gesture recognition; and selection of a file, document, or website in response to a search request; receiving a style adjustment preference from a user for multiple dimensions of prose style through a multi-dimensional style-adjusting interface having multiple dimensions of prose style each assigned to an incrementally adjustable control between the user and the computer selected from one or more control elements in a group consisting of: virtual or physical slider bar; virtual or physical buttons, keyboard, keypad, or touch screen; virtual or physical dials or knobs; popup menu, drop down menu, or other virtual menu; data entry box, line, or space; mouse and/or cursor movement; voice or speech recognition; and gesture or posture recognition; and making adjustments to the style of the input prose within a data processing environment according to the style adjustment preference specified by the user through the multi-dimensional style-adjusting interface, wherein style adjustments are done (a) searching for phrases in the input prose that are in the database of phrase synonyms and (b) replacing the phrases in the input prose with intra-set phrase synonyms from the database with higher rankings and/or values in a dimension of style for which the user has indicated an increased preference through the multi-dimensional style-adjusting interface and/or replacing the phrases in the input prose with intra-set phrase synonyms from the database with lower rankings and/or values in a dimension of style for which the user has indicated a decreased preference through the multi-dimensional style-adjusting interface.

1. A method for incrementally and multi-dimensionally adjusting prose style comprising: creating a database of sets of phrase synonyms within a data processing environment wherein a phrase is defined as a character string including one or more words, numbers, abbreviations or combinations thereof, and wherein set of phrase synonyms is defined as a set of phrases in which there is at least one phrase in the set for which all other phrases in the set can be substituted in prose usage without causing significant changes in the meaning of the prose or grammatical errors in the prose; assigning rankings and/or values to phrases in the database for each phrase's ranking and/or value with respect to a dimension of prose style, for at least two different dimensions of prose style; receiving input prose selected by a user via an interface between the user and a computer selected from a group consisting of: direct entry of prose by means of a physical or virtual keyboard, keypad, touchpad, or touch screen; importing prose from a file, document, or website; highlighting or identifying a portion of prose using a cursor; voice, speech, or gesture recognition; and selection of a file, document, or website in response to a search request; receiving a style adjustment preference from a user for multiple dimensions of prose style through a multi-dimensional style-adjusting interface having multiple dimensions of prose style each assigned to an incrementally adjustable control between the user and the computer selected from one or more control elements in a group consisting of: virtual or physical slider bar; virtual or physical buttons, keyboard, keypad, or touch screen; virtual or physical dials or knobs; popup menu, drop down menu, or other virtual menu; data entry box, line, or space; mouse and/or cursor movement; voice or speech recognition; and gesture or posture recognition; and making adjustments to the style of the input prose within a data processing environment according to the style adjustment preference specified by the user through the multi-dimensional style-adjusting interface, wherein style adjustments are done (a) searching for phrases in the input prose that are in the database of phrase synonyms and (b) replacing the phrases in the input prose with intra-set phrase synonyms from the database with higher rankings and/or values in a dimension of style for which the user has indicated an increased preference through the multi-dimensional style-adjusting interface and/or replacing the phrases in the input prose with intra-set phrase synonyms from the database with lower rankings and/or values in a dimension of style for which the user has indicated a decreased preference through the multi-dimensional style-adjusting interface. 7. The method of claim 1 wherein at least one dimension of prose style is selected from the group consisting of: use of alliteration; and use of humor.

25. The system of claim 19 , wherein determining the short-term category of interest comprises determining the short-term category of interest based on, at least, user specific information.

25. The system of claim 19 , wherein determining the short-term category of interest comprises determining the short-term category of interest based on, at least, user specific information. 26. The system of claim 25 , wherein the user specific information includes at least one of demographic information of the user and location information of the user.

1. A computer-implemented method to authenticate a user through a triple factor authentication in one step, the method comprising: intercepting, by a gateway, an access request sent to a network address of a resource server from a user using a user device the access request comprising a unique user record identifier; identifying a specific user device used by the user to send the access request based on a cookie or an identifier stored in the specific user device by the gateway; selecting a voice biometrics record of the user recorded using the specific user device used by the user to send the access request from among a plurality of voice biometrics records stored for the user during an enrollment period; placing a call to the user device based on information from the cookie or the identifier; sending, to the user device, a challenge message prompting the user to respond by voice, wherein the challenge message corresponds to the selected voice biometrics record; receiving, from the user device, a voice sample of the user; comparing the voice sample of the user against the selected voice biometrics record; converting the voice sample into a speech-to-text phrase; and comparing the speech-to-text phrase against a stored secret text phrase to verify the speech-to-text phrase matches the stored secret text phrase.

1. A computer-implemented method to authenticate a user through a triple factor authentication in one step, the method comprising: intercepting, by a gateway, an access request sent to a network address of a resource server from a user using a user device the access request comprising a unique user record identifier; identifying a specific user device used by the user to send the access request based on a cookie or an identifier stored in the specific user device by the gateway; selecting a voice biometrics record of the user recorded using the specific user device used by the user to send the access request from among a plurality of voice biometrics records stored for the user during an enrollment period; placing a call to the user device based on information from the cookie or the identifier; sending, to the user device, a challenge message prompting the user to respond by voice, wherein the challenge message corresponds to the selected voice biometrics record; receiving, from the user device, a voice sample of the user; comparing the voice sample of the user against the selected voice biometrics record; converting the voice sample into a speech-to-text phrase; and comparing the speech-to-text phrase against a stored secret text phrase to verify the speech-to-text phrase matches the stored secret text phrase. 15. The computer-implemented method of claim 1 , wherein sending the challenge message comprises providing a text message for display on the user device.

8. A system for automating a process of querying a relational database using at least one of an object and a relational persistent query service, the system comprising: a partition; a cache area; a processor; a network accessible by at least one user, wherein the network is coupled to the partition; and a relational database, the relational database being coupled to the partition, the partition and the cache area being coupled to the processor, the processor being programmed to: receive a request from a user via the partition for information from the relational database; translate the received request to at least one of an object and a relational persistent query; determine if a class associated with a table name already exists in a directory and perform a pre-fetch for one or more table columns on the relational database and create classes and other related files for the query using the table names and the table columns upon determining the class associated with the table name does not already exist in a directory; parse the query to determine table names, attributes and attribute types; generate at least one set of related files based on the parsed query; update at least one configuration file for use by at least one of an object and a relational persistent query service; and execute at least one of an object and a relational persistent query service based on the at least one of an object and a relational persistent query, wherein the at least one of an object and a relational persistent query service is operable to receive the translated query, retrieve at least one result stored in at least one of the cache area or the relational database based on at least one of the translated query and the generated at least one set of related files, and transmit the results to the user.

8. A system for automating a process of querying a relational database using at least one of an object and a relational persistent query service, the system comprising: a partition; a cache area; a processor; a network accessible by at least one user, wherein the network is coupled to the partition; and a relational database, the relational database being coupled to the partition, the partition and the cache area being coupled to the processor, the processor being programmed to: receive a request from a user via the partition for information from the relational database; translate the received request to at least one of an object and a relational persistent query; determine if a class associated with a table name already exists in a directory and perform a pre-fetch for one or more table columns on the relational database and create classes and other related files for the query using the table names and the table columns upon determining the class associated with the table name does not already exist in a directory; parse the query to determine table names, attributes and attribute types; generate at least one set of related files based on the parsed query; update at least one configuration file for use by at least one of an object and a relational persistent query service; and execute at least one of an object and a relational persistent query service based on the at least one of an object and a relational persistent query, wherein the at least one of an object and a relational persistent query service is operable to receive the translated query, retrieve at least one result stored in at least one of the cache area or the relational database based on at least one of the translated query and the generated at least one set of related files, and transmit the results to the user. 12. The system according to claim 8 wherein upon determining the class associated with the table name does not already exist in a directory, the processor further programmed to: generate class variables and functions; generate at least one mapping file that includes information consistent with information related to the mapping files, including identification numbers and tables with class properties; generate a cache configuration file that includes information consistent with the configuration of the cache, including a default cache size, store location, life span, and idle time; and add one or more default properties into the at least one updated configuration file and mapped out classes.

32. The product summary generator of claim 22 , wherein the selected alternative product is selected from a product category of a class of peer products.

32. The product summary generator of claim 22 , wherein the selected alternative product is selected from a product category of a class of peer products. 33. The product summary generator of claim 32 , wherein characteristics of peer products in the class of peer products cause a change in a scalarization range of the existing attribute value of the selected product, thereby introducing a new assertion based upon a changed relative position of the selected product in the peer class.

1. A method for associating documents with searchable metadata, the method comprising: receiving as input at least one text document; and operating at least one programmed processor to perform acts of creating metadata to be associated with the at least one text document, the metadata comprising at least one text keyword, the creating comprising extracting a set of one or more data elements from text of the at least one text document, the set of one or more data elements comprising at least one keyword that appears in the text of the at least one text document; normalizing said set of data elements to create a set of normalized data elements, wherein the normalizing comprises, for a first keyword of the at least one keyword, determining at least one other keyword similar to the first keyword, the at least one other keyword not being a keyword appearing in the text of the at least one text document, and adding the at least one other keyword to the set of normalized data elements; identifying at least one previously-validated keyword that is associated as metadata with at least one previously-stored text document, the at least one previously-stored text document not being one of the at least one text document, the at least one previously-validated keyword not being in the set of normalized data elements; merging said set of normalized data elements with the at least one previously-validated keyword to form a preliminary set of data elements; presenting said preliminary set of data elements for review by a user; and receiving user input validating a validated set of data elements; and in response to the user input validating the validated set of data elements, storing the at least one text document and storing the validated set of data elements as the metadata, the metadata being associated with the at least one text document such that the at least one text document may be located through a search for any data element included in the validated set of data elements.

1. A method for associating documents with searchable metadata, the method comprising: receiving as input at least one text document; and operating at least one programmed processor to perform acts of creating metadata to be associated with the at least one text document, the metadata comprising at least one text keyword, the creating comprising extracting a set of one or more data elements from text of the at least one text document, the set of one or more data elements comprising at least one keyword that appears in the text of the at least one text document; normalizing said set of data elements to create a set of normalized data elements, wherein the normalizing comprises, for a first keyword of the at least one keyword, determining at least one other keyword similar to the first keyword, the at least one other keyword not being a keyword appearing in the text of the at least one text document, and adding the at least one other keyword to the set of normalized data elements; identifying at least one previously-validated keyword that is associated as metadata with at least one previously-stored text document, the at least one previously-stored text document not being one of the at least one text document, the at least one previously-validated keyword not being in the set of normalized data elements; merging said set of normalized data elements with the at least one previously-validated keyword to form a preliminary set of data elements; presenting said preliminary set of data elements for review by a user; and receiving user input validating a validated set of data elements; and in response to the user input validating the validated set of data elements, storing the at least one text document and storing the validated set of data elements as the metadata, the metadata being associated with the at least one text document such that the at least one text document may be located through a search for any data element included in the validated set of data elements. 18. The method according to claim 1 , wherein the creating further comprises: in response to the user input, identifying the preliminary set of data elements as the validated set of data elements.

1. A method in a web browser on a data processing system for processing a document, the method comprising: receiving a first web document including formatting information used to display the first web document; receiving a request to present a selected portion of the first web document; identifying formatting information associated with the selected portion of the first web document; creating in the web browser a second web document including the selected portion and the formatting information associated with the selected portion, in response to receiving the request, wherein the first web document and the second web document are markup language documents; responsive to a request to change a font attribute of the selected portion, inserting virtual font indicators before and after text within the selected portion; and responsive to a request to identify a page break in the selected portion, inserting at least one virtual page break indicator within the selected portion, wherein identifying the page break in the selected portion comprises identifying a location of the page break based on page setup information, document formatting information, and document content.

1. A method in a web browser on a data processing system for processing a document, the method comprising: receiving a first web document including formatting information used to display the first web document; receiving a request to present a selected portion of the first web document; identifying formatting information associated with the selected portion of the first web document; creating in the web browser a second web document including the selected portion and the formatting information associated with the selected portion, in response to receiving the request, wherein the first web document and the second web document are markup language documents; responsive to a request to change a font attribute of the selected portion, inserting virtual font indicators before and after text within the selected portion; and responsive to a request to identify a page break in the selected portion, inserting at least one virtual page break indicator within the selected portion, wherein identifying the page break in the selected portion comprises identifying a location of the page break based on page setup information, document formatting information, and document content. 2. The method of claim 1 , further comprising sending the second web document to an output device.

1. A method for presenting a search result in response to a current search term, comprising: determining a pre-established first model corresponding to preselected user information and including historical user search data; identifying a selected historical search term in the historical user search data that corresponds with the current search term; identifying a selected historical selection result in the historical user search data that corresponds with the identified historical search term; determining the search result based upon the identified historical selection result, said determining the search result comprising determining an online recommendation result based upon the identified historical selection result; processing the online recommendation result to generate a generated recommendation result; and presenting the generated recommendation result, wherein said processing comprises: calculating a literal association degree between the online recommendation result and the current search term according to a logistic regression process such that the online recommendation result has the literal association degree that is greater than a preselected third threshold value; calculating a semantic association degree between the online recommendation result and the current search term according to a gradient boost decision tree such that the online recommendation result has the semantic association degree that is greater than a preselected fourth threshold value; or a combination thereof.

1. A method for presenting a search result in response to a current search term, comprising: determining a pre-established first model corresponding to preselected user information and including historical user search data; identifying a selected historical search term in the historical user search data that corresponds with the current search term; identifying a selected historical selection result in the historical user search data that corresponds with the identified historical search term; determining the search result based upon the identified historical selection result, said determining the search result comprising determining an online recommendation result based upon the identified historical selection result; processing the online recommendation result to generate a generated recommendation result; and presenting the generated recommendation result, wherein said processing comprises: calculating a literal association degree between the online recommendation result and the current search term according to a logistic regression process such that the online recommendation result has the literal association degree that is greater than a preselected third threshold value; calculating a semantic association degree between the online recommendation result and the current search term according to a gradient boost decision tree such that the online recommendation result has the semantic association degree that is greater than a preselected fourth threshold value; or a combination thereof. 9. The method of claim 1 , wherein said calculating the literal association degree comprises calculating the literal association degree according to a logistic regression model trained by a logistic regression algorithm, wherein the logistic regression algorithm trains the logistic regression model by using the pre-established first model as training data and taking a click-through rate as an optimization objective.

1. A method for optimizing a federated database management system having a federated database server and a plurality of data source servers comprising the steps of: a) determining schema and metadata configurations of the data source servers; b) enumerating available resources; c) enumerating security and confidentiality requirements; d) calculating an optimal federated database management system design based on the schema and metadata, the enumerated available resources, and the enumerated security and confidentiality requirements, wherein said calculating includes: (i) modeling a cost in terms of available resources consumed by each strategy of a plurality of strategies while executing a query with said federated database management system; (ii) determining whether operations associated with said query should be performed by said federated database server or one of said data source servers; (iii) determining the optimal order of said operations associated with said query; e) designing an optimal federated database management system, wherein said designing includes: (i) selecting the strategy having the lowest cost for executing said query; (ii) in response to determining that said operations associated with said query should be performed by said federated database server, selecting said federated database server to perform said operations according to said optimal order; (ii) in response to determining that said operations associated with said query should be performed by one of said data source servers, selecting said data source server to perform said operations according to said optimal order; and f) providing functionality for user input including user heuristics and data inputs.

1. A method for optimizing a federated database management system having a federated database server and a plurality of data source servers comprising the steps of: a) determining schema and metadata configurations of the data source servers; b) enumerating available resources; c) enumerating security and confidentiality requirements; d) calculating an optimal federated database management system design based on the schema and metadata, the enumerated available resources, and the enumerated security and confidentiality requirements, wherein said calculating includes: (i) modeling a cost in terms of available resources consumed by each strategy of a plurality of strategies while executing a query with said federated database management system; (ii) determining whether operations associated with said query should be performed by said federated database server or one of said data source servers; (iii) determining the optimal order of said operations associated with said query; e) designing an optimal federated database management system, wherein said designing includes: (i) selecting the strategy having the lowest cost for executing said query; (ii) in response to determining that said operations associated with said query should be performed by said federated database server, selecting said federated database server to perform said operations according to said optimal order; (ii) in response to determining that said operations associated with said query should be performed by one of said data source servers, selecting said data source server to perform said operations according to said optimal order; and f) providing functionality for user input including user heuristics and data inputs. 4. The method of claim 1 comprising designing the optimal federated database management system using one or more of an entity unification scheme, conformal dimensions, an aggregation scheme, unified metadata, and a unified data model.

19. A computer-accessible storage medium storing instructions, wherein the instructions are computer-executable to: identify a result set including one or more of a plurality of online content sources, wherein each of the included one or more online content sources satisfies a keyword query including one or more keywords; for a given one of the online content sources included in said result set, identify and generate corresponding representations of one or more aggregate paths including said given online content source, wherein each of the one or more aggregate paths includes one or more navigation paths among said plurality of online content sources, wherein each of the one or more navigation paths is indicative of an access request by one or more users that originates from a corresponding originating one of said online content sources to access a corresponding destination one of said online content sources, wherein each such access request indicated by a navigation path occurs prior to generation of representations of said one or more aggregate paths, wherein a representation of a given one of said one or more aggregate paths is indicative of multiple ones of said online content sources; detect a selection of a particular online content source from one of said identified aggregate paths, wherein prior to said detecting, said particular online content source does not satisfy said keyword query; and in response to detecting said selection of said particular online content source, associate said one or more keywords included in said keyword query with said particular online content source, such that after said one or more keywords are associated with said particular online content source, said particular online content source satisfies said keyword query.

19. A computer-accessible storage medium storing instructions, wherein the instructions are computer-executable to: identify a result set including one or more of a plurality of online content sources, wherein each of the included one or more online content sources satisfies a keyword query including one or more keywords; for a given one of the online content sources included in said result set, identify and generate corresponding representations of one or more aggregate paths including said given online content source, wherein each of the one or more aggregate paths includes one or more navigation paths among said plurality of online content sources, wherein each of the one or more navigation paths is indicative of an access request by one or more users that originates from a corresponding originating one of said online content sources to access a corresponding destination one of said online content sources, wherein each such access request indicated by a navigation path occurs prior to generation of representations of said one or more aggregate paths, wherein a representation of a given one of said one or more aggregate paths is indicative of multiple ones of said online content sources; detect a selection of a particular online content source from one of said identified aggregate paths, wherein prior to said detecting, said particular online content source does not satisfy said keyword query; and in response to detecting said selection of said particular online content source, associate said one or more keywords included in said keyword query with said particular online content source, such that after said one or more keywords are associated with said particular online content source, said particular online content source satisfies said keyword query. 34. The computer-accessible medium as recited in claim 19 , wherein said keyword query is extracted from a content source with which a user is interacting.

13. The system of claim 12 , wherein identifying one or more characteristics of the content surrounding the advertisement placement area includes identifying font characteristics of the content surrounding the advertisement placement area.

13. The system of claim 12 , wherein identifying one or more characteristics of the content surrounding the advertisement placement area includes identifying font characteristics of the content surrounding the advertisement placement area. 14. The system of claim 13 , wherein identifying font characteristics associated with the content surrounding the advertisement placement area includes identifying a dominant font used within the content surrounding the advertisement placement area.

5. A computer program on a computer readable medium, for execution by a computer for requiring a predetermined level of template completeness when publishing information on products and services within a content management system (CMS), the computer program comprising: a code segment for storing in a database a plurality of objects arranged in a content taxonomy, wherein the content taxonomy comprises a plurality of object groups, a plurality of object types, a plurality of objects, and a plurality of articles, wherein each object group comprises a plurality of object types sharing a first commonality, wherein each object type comprises a plurality of objects sharing a second commonality, and wherein each of the objects comprises a plurality of articles that together provide information about an associated object; a code segment for providing a plurality of CMS templates wherein each template is associated with one of the plurality of articles and describes a format and layout thereof a code segment for defining a CMS template set chosen from the plurality of CMS templates, the CMS template set used to describe information for a type of products or services wherein application of the templates for generating new articles provides each of the objects of the same object type with the same CMS template set as the other objects of the same object type, including the same set of articles with the same format and layout; a code segment for creating a new object in the content taxonomy, including a record generation code segment for generating a record of the new object in the database unit, a selection code segment for determining the object group and the object type of the new object, an identification code segment for, based on the determined object group and object type, identifying the CMS template set associated therewith, the identified CMS template set defining the number and type of articles requiring completion for the new object, and an article generation code segment for automatically generating said number and type of articles; a code segment for receiving pieces of content for the articles in the CMS templates from multiple users, each of said articles being assigned to one of the multiple users for providing said content, including creating a task identifier that links each of said articles to the associated user, controlling a workflow for article completion for the new object, and displaying an indicator representing an article requiring completion to the associated user; a code segment for determining if the received pieces of content satisfy a predetermined criteria establishing CMS publication readiness; a code segment for prohibiting CMS publication until the predetermined criteria is satisfied; a code segment for receiving a publication request from the CMS publisher after the predetermined criteria is satisfied; and a code segment for automatically publishing (after receiving the publication request) the pieces of content and corresponding CMS templates to the CMS without further interaction from the CMS publisher.

5. A computer program on a computer readable medium, for execution by a computer for requiring a predetermined level of template completeness when publishing information on products and services within a content management system (CMS), the computer program comprising: a code segment for storing in a database a plurality of objects arranged in a content taxonomy, wherein the content taxonomy comprises a plurality of object groups, a plurality of object types, a plurality of objects, and a plurality of articles, wherein each object group comprises a plurality of object types sharing a first commonality, wherein each object type comprises a plurality of objects sharing a second commonality, and wherein each of the objects comprises a plurality of articles that together provide information about an associated object; a code segment for providing a plurality of CMS templates wherein each template is associated with one of the plurality of articles and describes a format and layout thereof a code segment for defining a CMS template set chosen from the plurality of CMS templates, the CMS template set used to describe information for a type of products or services wherein application of the templates for generating new articles provides each of the objects of the same object type with the same CMS template set as the other objects of the same object type, including the same set of articles with the same format and layout; a code segment for creating a new object in the content taxonomy, including a record generation code segment for generating a record of the new object in the database unit, a selection code segment for determining the object group and the object type of the new object, an identification code segment for, based on the determined object group and object type, identifying the CMS template set associated therewith, the identified CMS template set defining the number and type of articles requiring completion for the new object, and an article generation code segment for automatically generating said number and type of articles; a code segment for receiving pieces of content for the articles in the CMS templates from multiple users, each of said articles being assigned to one of the multiple users for providing said content, including creating a task identifier that links each of said articles to the associated user, controlling a workflow for article completion for the new object, and displaying an indicator representing an article requiring completion to the associated user; a code segment for determining if the received pieces of content satisfy a predetermined criteria establishing CMS publication readiness; a code segment for prohibiting CMS publication until the predetermined criteria is satisfied; a code segment for receiving a publication request from the CMS publisher after the predetermined criteria is satisfied; and a code segment for automatically publishing (after receiving the publication request) the pieces of content and corresponding CMS templates to the CMS without further interaction from the CMS publisher. 6. The computer program from claim 5 , wherein the received publication request is via a single click with a computer mouse.

11. A computer program product, comprising: a computer readable storage medium having program code embodied therewith, the program code executable by a computer to cause the computer to: initiate, by the computer, a new document notification process in response to receipt of a new document, the new document notification process comprising: evaluating enhanced metadata of the new document via a relationship analyzing process to produce a priority list defining a likelihood of possible access, wherein the enhanced metadata includes a set of keywords and/or references from the new document; and store, by the computer, the new document in a storage tier of a hierarchical storage environment according to the priority list; receive a request to access the new document; accessing the new document; triggering and/or implementing a second document access notification process in response to the request, the second document access notification process comprising: determining documents that are related to the new document based on the enhanced metadata and the priority list; and placing the related documents in a highest level storage tier of the hierarchical storage environment.

11. A computer program product, comprising: a computer readable storage medium having program code embodied therewith, the program code executable by a computer to cause the computer to: initiate, by the computer, a new document notification process in response to receipt of a new document, the new document notification process comprising: evaluating enhanced metadata of the new document via a relationship analyzing process to produce a priority list defining a likelihood of possible access, wherein the enhanced metadata includes a set of keywords and/or references from the new document; and store, by the computer, the new document in a storage tier of a hierarchical storage environment according to the priority list; receive a request to access the new document; accessing the new document; triggering and/or implementing a second document access notification process in response to the request, the second document access notification process comprising: determining documents that are related to the new document based on the enhanced metadata and the priority list; and placing the related documents in a highest level storage tier of the hierarchical storage environment. 12. The computer program product according to claim 11 , wherein the program code is executable by the computer to cause the computer to scan the new document for the set of keywords and/or references, and creating the enhanced metadata.

7. The business information system of claim 1 , the electronic mail server further configured to transmit the electronic mail message responsive to a receipt by the interface server of an alert request from the user.

7. The business information system of claim 1 , the electronic mail server further configured to transmit the electronic mail message responsive to a receipt by the interface server of an alert request from the user. 8. The business information system of claim 7 , wherein the alert request comprises an electronic mail message sent from the electronic mail account of the user.

1. A system comprising: a data processing apparatus with one or more processors; and a computer-readable memory in data communication with the data processing apparatus and storing instructions executable by the one or more processors and upon such execution cause the data processing apparatus to perform operations comprising: receiving a first graphical document; comparing graphical content of the first graphical document to graphical content of a second graphical document; flagging the first graphical document based on the comparison; providing the flagged first graphical document to one or more evaluator terminals for rating information; and approving or disapproving the flagged first graphical document based on the rating information received from the one or more evaluator terminals.

1. A system comprising: a data processing apparatus with one or more processors; and a computer-readable memory in data communication with the data processing apparatus and storing instructions executable by the one or more processors and upon such execution cause the data processing apparatus to perform operations comprising: receiving a first graphical document; comparing graphical content of the first graphical document to graphical content of a second graphical document; flagging the first graphical document based on the comparison; providing the flagged first graphical document to one or more evaluator terminals for rating information; and approving or disapproving the flagged first graphical document based on the rating information received from the one or more evaluator terminals. 2. The system of claim 1 , wherein the instructions cause the data processing apparatus to flag the first graphical document if the second graphical document contains material identified as objectionable and the graphical content of the first graphical document is substantially identical to the graphical content of the second graphical document.

9. A non-transitory medium storing processor-executable program code, the program code executable by a processor to: determine a first metamodel conforming to a first meta-metamodel supporting metamodel class inheritance at the first metamodel level; identify one or more segments of an aggregation-free tree of nodes of the first metamodel; identify a lowest-level node of one of the one or more segments; identify all higher-level nodes of the one of the one or more segments; and consolidate attributes of each of the identified nodes of the one of the one or more segments into a node of a second metamodel conforming to a second meta-metamodel.

9. A non-transitory medium storing processor-executable program code, the program code executable by a processor to: determine a first metamodel conforming to a first meta-metamodel supporting metamodel class inheritance at the first metamodel level; identify one or more segments of an aggregation-free tree of nodes of the first metamodel; identify a lowest-level node of one of the one or more segments; identify all higher-level nodes of the one of the one or more segments; and consolidate attributes of each of the identified nodes of the one of the one or more segments into a node of a second metamodel conforming to a second meta-metamodel. 10. The medium according to claim 9 , wherein the second meta-metamodel does not support metamodel class inheritance at the second metamodel level.

12. A system for providing information, comprising: a network interface device to communicatively couple to a communication network; one or more processors configured to: receive a natural language query; determine an answer to the natural language query; format one or more electronic messages that include: the answer, and metadata corresponding to the answer, the metadata separate from the answer and including information to enable construction by a computing device, using the metadata, of a syntactically correct natural language sentence or statement that recites and/or describes the answer, wherein the information to enable construction comprises information (i) indicating how the natural language query was interpreted in determining the answer and (ii) not included in the query; and cause the network interface device to transmit the one or more electronic messages via the communication network.

12. A system for providing information, comprising: a network interface device to communicatively couple to a communication network; one or more processors configured to: receive a natural language query; determine an answer to the natural language query; format one or more electronic messages that include: the answer, and metadata corresponding to the answer, the metadata separate from the answer and including information to enable construction by a computing device, using the metadata, of a syntactically correct natural language sentence or statement that recites and/or describes the answer, wherein the information to enable construction comprises information (i) indicating how the natural language query was interpreted in determining the answer and (ii) not included in the query; and cause the network interface device to transmit the one or more electronic messages via the communication network. 13. The system of claim 12 , wherein the metadata includes information to enable construction by the computing device, using the metadata, of the sentence or statement so that the sentence or statement further rephrases the query.

1. A system for search with autosuggest, comprising: a processor configured to: determine a plurality of potential query suggestions for a partially entered query string; merge a plurality of categories associated with a merchant web site into a merged category, comprising to: determine a first weight for a first category based on a first query count associated with the first category; determine a second weight for a second category based on a second query count associated with the second category, the plurality of categories including the first category and the second category; and merge the first category and the second category into a single merged category, the single merged category being associated with the merged category, wherein the merging of the first category and the second category comprises to: aggregate the first weight and the second weight to obtain a merged weight, the merged weight being associated with the merged category; and automatically suggest a plurality of queries based on a query count for each of the queries, wherein at least one of the automatically suggested plurality of queries corresponds to the merged category; and a memory coupled to the processor and configured to provide the processor with instructions.

1. A system for search with autosuggest, comprising: a processor configured to: determine a plurality of potential query suggestions for a partially entered query string; merge a plurality of categories associated with a merchant web site into a merged category, comprising to: determine a first weight for a first category based on a first query count associated with the first category; determine a second weight for a second category based on a second query count associated with the second category, the plurality of categories including the first category and the second category; and merge the first category and the second category into a single merged category, the single merged category being associated with the merged category, wherein the merging of the first category and the second category comprises to: aggregate the first weight and the second weight to obtain a merged weight, the merged weight being associated with the merged category; and automatically suggest a plurality of queries based on a query count for each of the queries, wherein at least one of the automatically suggested plurality of queries corresponds to the merged category; and a memory coupled to the processor and configured to provide the processor with instructions. 7. The system recited in claim 1 , wherein the processor is further configured to: determine that the partially entered query string is associated with product or category of a merchant web site.

1. A method of generating and using voice characteristic profiles, the method comprising: receiving, at a computing device, information communicated between a first caller's device and a second caller's device during a communication; analyzing the information communicated by the first caller's device; identifying a set of sound components from the information communicated by the first caller's device; determining a first language characteristic for the information communicated by the first caller's device, by matching a subset of the set of sound components with a threshold number of pre-defined sound components associated with the first language characteristic; and using the first language characteristic to enhance the communication between the first caller's device and the second caller's device.

1. A method of generating and using voice characteristic profiles, the method comprising: receiving, at a computing device, information communicated between a first caller's device and a second caller's device during a communication; analyzing the information communicated by the first caller's device; identifying a set of sound components from the information communicated by the first caller's device; determining a first language characteristic for the information communicated by the first caller's device, by matching a subset of the set of sound components with a threshold number of pre-defined sound components associated with the first language characteristic; and using the first language characteristic to enhance the communication between the first caller's device and the second caller's device. 9. The method of claim 1 , wherein the first language characteristic is an age demographic.

1. A computer-implemented method on a client device, comprising: while receiving one or more first characters in a sequence of characters being entered into an input field of an interactive user interface of the client device and before the sequence of characters has been completely entered, performing by the client device: parsing the one or more first characters using a first string parsing pattern associated with a first model to generate first parsed input, the first model specifying a first string presentation format, wherein parsing includes: identifying an error indicating that the one or more first characters cannot be parsed by the first string parsing pattern associated with the first model; presenting the first parsed input in the interactive user interface formatted according to the first string presentation format; in response to identifying the error: presenting information identifying the error in the interactive user interface, the information including a message specifying the error, and sending a request to identify a second model to a server, wherein the request includes the one or more first characters; receiving, from the server and based on the request, a second model, the second model being different from the first model and associated with a second string parsing pattern and a second string presentation format, wherein the second model is a software component that contains information and processing instructions required to achieve a functionality on the client device and the second model being configured to address the error indicating that the one or more first characters cannot be parsed by the first string parsing pattern associated with the first model; parsing one or more second characters using the second string parsing pattern to generate second parsed input, the second characters including the one or more first characters and zero or more characters entered subsequent to the one or more first characters, wherein the second string parsing pattern is different from the first string parsing pattern; and presenting the second parsed input in the interactive user interface formatted according to the second string presentation format.

1. A computer-implemented method on a client device, comprising: while receiving one or more first characters in a sequence of characters being entered into an input field of an interactive user interface of the client device and before the sequence of characters has been completely entered, performing by the client device: parsing the one or more first characters using a first string parsing pattern associated with a first model to generate first parsed input, the first model specifying a first string presentation format, wherein parsing includes: identifying an error indicating that the one or more first characters cannot be parsed by the first string parsing pattern associated with the first model; presenting the first parsed input in the interactive user interface formatted according to the first string presentation format; in response to identifying the error: presenting information identifying the error in the interactive user interface, the information including a message specifying the error, and sending a request to identify a second model to a server, wherein the request includes the one or more first characters; receiving, from the server and based on the request, a second model, the second model being different from the first model and associated with a second string parsing pattern and a second string presentation format, wherein the second model is a software component that contains information and processing instructions required to achieve a functionality on the client device and the second model being configured to address the error indicating that the one or more first characters cannot be parsed by the first string parsing pattern associated with the first model; parsing one or more second characters using the second string parsing pattern to generate second parsed input, the second characters including the one or more first characters and zero or more characters entered subsequent to the one or more first characters, wherein the second string parsing pattern is different from the first string parsing pattern; and presenting the second parsed input in the interactive user interface formatted according to the second string presentation format. 2. The method of claim 1 , wherein the second model is an email model, and wherein presenting the second parsed input in the interactive user interface comprises: determining respective values for one or more email input fields from the one or more characters and the email model; formatting an email message with the respective values for the one or more email input fields; updating the interactive user interface to an interface that is configured for composing an email message; and presenting the formatted email message in the updated interactive user interface.

1. A non-transitory computer-readable recording medium storing therein an information searching program that causes a computer to execute a process, the process comprising: receiving one or a plurality of search keywords used for searching from a plurality of data items; specifying a first group of data items utilizing a character appearance map stored in a storage, wherein each of the first group of data items includes all characters constituting the one or a plurality of search keywords, the character appearance map indicating whether each character included in the plurality of data items is included in the plurality of data items, respectively; and searching the one or plurality of search keywords for the first group of data items, wherein the specifying specifies a second group of data items that each include a head character of the one or the plurality of search keywords, based on a head character appearance map stored in the storage, the head character appearance map indicating whether each character in the head character appearance map is included as a head character respectively in the plurality of data items, wherein the specifying also specifies a fourth group of data items from the second group of data items that include both each head character and each tail character of the one or plurality of search keywords, based on a tail character appearance map indicating whether each character in the tail character appearance map is included as a head character respectively in the plurality of data items, wherein the searching searches the one or plurality of search keywords utilizing the second group of data items, and wherein the searching also searches the one or plurality of search keywords utilizing the fourth group of data items.

1. A non-transitory computer-readable recording medium storing therein an information searching program that causes a computer to execute a process, the process comprising: receiving one or a plurality of search keywords used for searching from a plurality of data items; specifying a first group of data items utilizing a character appearance map stored in a storage, wherein each of the first group of data items includes all characters constituting the one or a plurality of search keywords, the character appearance map indicating whether each character included in the plurality of data items is included in the plurality of data items, respectively; and searching the one or plurality of search keywords for the first group of data items, wherein the specifying specifies a second group of data items that each include a head character of the one or the plurality of search keywords, based on a head character appearance map stored in the storage, the head character appearance map indicating whether each character in the head character appearance map is included as a head character respectively in the plurality of data items, wherein the specifying also specifies a fourth group of data items from the second group of data items that include both each head character and each tail character of the one or plurality of search keywords, based on a tail character appearance map indicating whether each character in the tail character appearance map is included as a head character respectively in the plurality of data items, wherein the searching searches the one or plurality of search keywords utilizing the second group of data items, and wherein the searching also searches the one or plurality of search keywords utilizing the fourth group of data items. 2. The non-transitory computer-readable recording medium according to claim 1 , wherein: the specifying specifies the first group of data items from the second group of data items based on the character appearance map, and the searching searches the one or plurality of search keywords utilizing the first group of data items.

15. A non-transitory computer readable medium encoded with logic, the logic when executed operable to: receive a search query generated by a user; determine a type of expansion to apply to the search query; automatically generate a plurality of different expanded search queries according to the determined expansion type without intervention from the user; execute a separate search on each one of the plurality of different expanded search queries to retrieve search results; and provide the search results of the separate searches on each of the plurality of different expanded search queries for presentation to the user in a plurality of different modules, wherein each module comprises search results for one of the expanded search queries.

15. A non-transitory computer readable medium encoded with logic, the logic when executed operable to: receive a search query generated by a user; determine a type of expansion to apply to the search query; automatically generate a plurality of different expanded search queries according to the determined expansion type without intervention from the user; execute a separate search on each one of the plurality of different expanded search queries to retrieve search results; and provide the search results of the separate searches on each of the plurality of different expanded search queries for presentation to the user in a plurality of different modules, wherein each module comprises search results for one of the expanded search queries. 18. The computer readable medium of claim 15 , further operable to graphically display the search results on a graphical user interface.

2. The method of claim 1 , wherein submitting a translation to the main software product build environment includes moving the translation from a staging release to a permanent release.

2. The method of claim 1 , wherein submitting a translation to the main software product build environment includes moving the translation from a staging release to a permanent release. 3. The method of claim 2 , wherein the staging release contains translations submitted from a translator prior to the translations being accepted into the permanent release.

33. A method performed by one or more server devices, the method comprising: identifying, by a processor of the one or more server devices, a document that is relevant to a search term, the document comprising structural elements, where the structural elements comprise the document, a set of parts of the document, and a set of pages of the document; identifying, by a processor of the one or more server devices, a tree representation of the document, where the pages of the document correspond to leaf nodes, the parts of the document correspond to higher level nodes, and the document corresponds to a root node; assigning, by a processor of the one or more server devices, scores to the leaf nodes based on whether the leaf nodes contain occurrences of the search term; determining, by a processor of the one or more server devices, scores for the higher level nodes based on the scores of associated ones of the leaf nodes; determining, by a processor of the one or more server devices, a score for the root node based on the scores of the higher level nodes; providing, by a processor of the one or more server devices, a threshold, where the threshold is based on at least one of: a number of pages associated with one of the leaf nodes, a number of pages associated with one of the higher level nodes, or a number of pages associated with the root node; selecting, by a processor of the one or more server devices, one of the leaf nodes, one of the higher level nodes, or the root node, as a selected node, based on the scores and the threshold; and providing, by a processor of the one or more server devices, information relating to the selected node.

33. A method performed by one or more server devices, the method comprising: identifying, by a processor of the one or more server devices, a document that is relevant to a search term, the document comprising structural elements, where the structural elements comprise the document, a set of parts of the document, and a set of pages of the document; identifying, by a processor of the one or more server devices, a tree representation of the document, where the pages of the document correspond to leaf nodes, the parts of the document correspond to higher level nodes, and the document corresponds to a root node; assigning, by a processor of the one or more server devices, scores to the leaf nodes based on whether the leaf nodes contain occurrences of the search term; determining, by a processor of the one or more server devices, scores for the higher level nodes based on the scores of associated ones of the leaf nodes; determining, by a processor of the one or more server devices, a score for the root node based on the scores of the higher level nodes; providing, by a processor of the one or more server devices, a threshold, where the threshold is based on at least one of: a number of pages associated with one of the leaf nodes, a number of pages associated with one of the higher level nodes, or a number of pages associated with the root node; selecting, by a processor of the one or more server devices, one of the leaf nodes, one of the higher level nodes, or the root node, as a selected node, based on the scores and the threshold; and providing, by a processor of the one or more server devices, information relating to the selected node. 38. The method of claim 33 , where the information related to the selected node is a title page of the document when the document is the selected node.

19. At a computer system, a method for ranking tables for inclusion in a response to a search query including one or more keywords, the method comprising: accessing a list of candidate tables for inclusion in a search query response, the list of candidate tables having been previously filtered from a compiled list of tables, each candidate table filtered by having an approximate ranking score meeting a score threshold to be considered a candidate table; for each candidate table: generating a hit matrix for the candidate table, including for any of the one or more keywords contained in the candidate table: determining that one or more fields in one or more parts of the candidate table contain a hit for the keyword and, for each of the one or more fields, computing a location of the keyword hit within the field; accessing table features for the candidate table from a feature index; generating a hit matrix overlay for the candidate table by overlaying the hit matrix with the accessed table features to distinguish keyword hits in different semantic locations inside the candidate table, overlaying the hit matrix including mapping keyword hit locations into logical regions of the candidate table; computing one or more dynamic features of the candidate table from the hit matrix overlay; and generating a ranking score for the candidate table at least from the one or more dynamic features.

19. At a computer system, a method for ranking tables for inclusion in a response to a search query including one or more keywords, the method comprising: accessing a list of candidate tables for inclusion in a search query response, the list of candidate tables having been previously filtered from a compiled list of tables, each candidate table filtered by having an approximate ranking score meeting a score threshold to be considered a candidate table; for each candidate table: generating a hit matrix for the candidate table, including for any of the one or more keywords contained in the candidate table: determining that one or more fields in one or more parts of the candidate table contain a hit for the keyword and, for each of the one or more fields, computing a location of the keyword hit within the field; accessing table features for the candidate table from a feature index; generating a hit matrix overlay for the candidate table by overlaying the hit matrix with the accessed table features to distinguish keyword hits in different semantic locations inside the candidate table, overlaying the hit matrix including mapping keyword hit locations into logical regions of the candidate table; computing one or more dynamic features of the candidate table from the hit matrix overlay; and generating a ranking score for the candidate table at least from the one or more dynamic features. 20. The method of claim 19 , wherein accessing a list of tables that are candidate tables for inclusion in a search query response comprises accessing a list of web tables.

1. An image forming apparatus comprising: a scan apparatus to scan a document received by the image forming apparatus; a text/image separation apparatus to separate the scanned document into a text area and an image area, and to separate texts in the text area into symbols based on pixel data of the separated text area, where the text/image separation unit compares at least one pixel of the pixel data in the separated text area with a plurality of neighboring pixels to determine and separate individual symbols of the text area; an index determination apparatus to extract one or more properties of the separated symbols and to compare the extracted symbol properties with one or more index thresholds that are set as an average value of preset symbol properties calculated based on a variation of the preset symbol properties, thereby determining whether text including the symbols is an index object; and an index page creation apparatus to create an index page including the text determined as the index object and information about a page including the text, wherein the index determination apparatus determines the symbols as index-object symbols, groups the index-object symbols, and determines the texts comprising the groups of the index-object symbols as objects in the index, when the extracted symbol properties are greater than the index thresholds.

1. An image forming apparatus comprising: a scan apparatus to scan a document received by the image forming apparatus; a text/image separation apparatus to separate the scanned document into a text area and an image area, and to separate texts in the text area into symbols based on pixel data of the separated text area, where the text/image separation unit compares at least one pixel of the pixel data in the separated text area with a plurality of neighboring pixels to determine and separate individual symbols of the text area; an index determination apparatus to extract one or more properties of the separated symbols and to compare the extracted symbol properties with one or more index thresholds that are set as an average value of preset symbol properties calculated based on a variation of the preset symbol properties, thereby determining whether text including the symbols is an index object; and an index page creation apparatus to create an index page including the text determined as the index object and information about a page including the text, wherein the index determination apparatus determines the symbols as index-object symbols, groups the index-object symbols, and determines the texts comprising the groups of the index-object symbols as objects in the index, when the extracted symbol properties are greater than the index thresholds. 2. The image forming apparatus of claim 1 , wherein the extracted symbol properties comprise one or more of a symbol width, a symbol height, and a stroke width.