Datasets:

patent

/

AIPD_nlp_sentence_dataset_v2

like 1

1. A method executed by a processor for optimizing execution of dynamic language code, the method comprising: identifying a first dynamic language function call during runtime, the function call including argument values for one or more arguments of the function; calculating a type signature for the one or more argument values of the function; determining if a function associated with the type signature is stored in a cache; looking up the function in the cache when the function associated with the type signature is stored in the cache; and dynamically calling the function associated with the type signature when the function for the type signature is not stored in the cache.

1. A method executed by a processor for optimizing execution of dynamic language code, the method comprising: identifying a first dynamic language function call during runtime, the function call including argument values for one or more arguments of the function; calculating a type signature for the one or more argument values of the function; determining if a function associated with the type signature is stored in a cache; looking up the function in the cache when the function associated with the type signature is stored in the cache; and dynamically calling the function associated with the type signature when the function for the type signature is not stored in the cache. 12. The method of claim 1 , wherein the type signature includes a single bit string.

1. A method for fulfilling an Internet search request for information related to a user's search term, the method steps comprising: (a) accepting a search term from the user; (b) automatically selecting a plurality of search Views having dynamically computed degrees of relevance to the search term, wherein the relevance is determined utilizing at least one relevancy criterion, wherein each View comprises a unique combination of data presentation, processing widgets, and preselected data sources from which search results are obtained for the View; (c) displaying the plurality of search Views to the user; (d) accepting user selection of a View; (e) obtaining search results based on the search term by utilizing an instruction set for the selected View; and (f) displaying the search results within the selected View to the user.

1. A method for fulfilling an Internet search request for information related to a user's search term, the method steps comprising: (a) accepting a search term from the user; (b) automatically selecting a plurality of search Views having dynamically computed degrees of relevance to the search term, wherein the relevance is determined utilizing at least one relevancy criterion, wherein each View comprises a unique combination of data presentation, processing widgets, and preselected data sources from which search results are obtained for the View; (c) displaying the plurality of search Views to the user; (d) accepting user selection of a View; (e) obtaining search results based on the search term by utilizing an instruction set for the selected View; and (f) displaying the search results within the selected View to the user. 4. The method of claim 1 , the method steps further comprising: (a)(1) obtaining at least one pre-search result from at least one data source; (a)(2) loading the Web page represented by the at least one pre-search result URL into a browser instance; (a)(3) obtaining at least one screenshot of the Web page; and (a)(4) retaining the at least one screenshot for subsequent retrieval.

65. The method as recited in claim 49 , further comprising extracting additional content from the image of the document.

65. The method as recited in claim 49 , further comprising extracting additional content from the image of the document. 66. The method as recited in claim 65 , wherein extracting the additional content comprises template-based extraction.

7. The method of claim 1 , wherein the supplemental content includes an audition sequence associated with the rendered document.

7. The method of claim 1 , wherein the supplemental content includes an audition sequence associated with the rendered document. 8. The method of claim 7 , wherein the audio sequence includes a pronunciation of one or more words of the rendered document.

1. A method for optimizing a query by a database system in a multi-tenant database system, the method comprising: receiving a query request with a query predicate to filter data returned in response to the query request, wherein the query predicate comprises a formula; accessing an index generated to correspond to one tenant of the multi-tenant database system; preprocessing the formula in the query predicate based upon the generated index for the tenant to create a transformed query request, wherein the preprocessing includes: applying the generated index to a database field referenced in the formula, and replacing at least one reference to a database field within the formula with a reference to a second database field based upon the generated index; optimizing the query request using the transformed query request; receiving a query request with a reference to a first database field in the query predicate, wherein the first database field comprises the formula in the query predicate, wherein the formula comprises a reference to a second database field; and transforming the query request to a transformed query request by replacing the reference to the first database field within the query request with at least one reference to the second database field.

1. A method for optimizing a query by a database system in a multi-tenant database system, the method comprising: receiving a query request with a query predicate to filter data returned in response to the query request, wherein the query predicate comprises a formula; accessing an index generated to correspond to one tenant of the multi-tenant database system; preprocessing the formula in the query predicate based upon the generated index for the tenant to create a transformed query request, wherein the preprocessing includes: applying the generated index to a database field referenced in the formula, and replacing at least one reference to a database field within the formula with a reference to a second database field based upon the generated index; optimizing the query request using the transformed query request; receiving a query request with a reference to a first database field in the query predicate, wherein the first database field comprises the formula in the query predicate, wherein the formula comprises a reference to a second database field; and transforming the query request to a transformed query request by replacing the reference to the first database field within the query request with at least one reference to the second database field. 4. The method for optimizing a query in a database system of claim 1 , wherein the formula has a nested formula and the formula is flattened during preprocessing.

1. A computer implemented method, comprising: recording in a memory input data having delimited strings; recording in the memory a region-matching transducer defining one or more patterns of one or more sequences of delimited strings, with at least one of the patterns defined in the region-matching transducer having an arrangement of a plurality of class-matching networks; the plurality of class-matching networks defining a combination of two or more entity classes from one or both of part-of-speech classes and application-specific classes; the region-matching transducer (i) having, for each of the one or more patterns, an arc that leads from a penultimate state with a transition label that identifies the entity class of the pattern, and (ii) sharing states between patterns leading to a penultimate state when segments of delimited strings making up two or more patterns overlap; applying the region-matching transducer recorded in the memory to the input data with an apply-stage replacement method, which apply-stage replacement method follows a longest match principle for identifying one or more patterns in the region-matching transducer that match one or more sequences of delimited strings in the input data; at least one of the matching sequences of delimited strings satisfying at least one pattern in the region-matching transducer defined by an arrangement of a plurality of class-matching networks, wherein the input data is not labeled with morphological tags when applying the region-matching transducer to the input data; and recording in the memory, in response to said applying, the one or more sequences of delimited strings in the input data matching the one or more patterns in the region-matching transducer.

1. A computer implemented method, comprising: recording in a memory input data having delimited strings; recording in the memory a region-matching transducer defining one or more patterns of one or more sequences of delimited strings, with at least one of the patterns defined in the region-matching transducer having an arrangement of a plurality of class-matching networks; the plurality of class-matching networks defining a combination of two or more entity classes from one or both of part-of-speech classes and application-specific classes; the region-matching transducer (i) having, for each of the one or more patterns, an arc that leads from a penultimate state with a transition label that identifies the entity class of the pattern, and (ii) sharing states between patterns leading to a penultimate state when segments of delimited strings making up two or more patterns overlap; applying the region-matching transducer recorded in the memory to the input data with an apply-stage replacement method, which apply-stage replacement method follows a longest match principle for identifying one or more patterns in the region-matching transducer that match one or more sequences of delimited strings in the input data; at least one of the matching sequences of delimited strings satisfying at least one pattern in the region-matching transducer defined by an arrangement of a plurality of class-matching networks, wherein the input data is not labeled with morphological tags when applying the region-matching transducer to the input data; and recording in the memory, in response to said applying, the one or more sequences of delimited strings in the input data matching the one or more patterns in the region-matching transducer. 8. The method according to claim 1 , wherein the input data recorded in the memory, in response to said applying, is recorded in the memory with one or more labels identifying the one or more sequences of delimited strings in the input data matching the one or more patterns in the region-matching transducer.

11. A server device, comprising: a memory device storing computer-executable instructions; and one or more processors to execute the computer-executable instructions, to: generate a list of relevant documents based on individual search terms of a search query; identify a subset of documents that are most relevant documents, to the search query, from the list of relevant documents; form a plurality of multiword substrings of the search query, each of the plurality of multiword substrings including at least two words; detect, for each of the plurality of multiword substrings, actual occurrences of the multiword substring in the subset of documents; calculate, for each of the plurality of multiword substrings generated from the search query, a value that indicates a fraction of the relevant documents in which an actual occurrence of the each substring is detected; identify, based on the detected actual occurrences of each of the plurality of multiword substrings, that words of at least one of the plurality of multiword substrings, when taken together, form a single compound unit, when identifying that words of at least one of the multiword substrings, when taken together, form a single compound unit, the one or more processors are to: determine that the calculated value associated with the at least one of the plurality of multiword substrings exceeds a threshold value associated with compound units; and identify a set of documents, the set of documents being identified based on the identified at least one of the plurality of multiword substrings.

11. A server device, comprising: a memory device storing computer-executable instructions; and one or more processors to execute the computer-executable instructions, to: generate a list of relevant documents based on individual search terms of a search query; identify a subset of documents that are most relevant documents, to the search query, from the list of relevant documents; form a plurality of multiword substrings of the search query, each of the plurality of multiword substrings including at least two words; detect, for each of the plurality of multiword substrings, actual occurrences of the multiword substring in the subset of documents; calculate, for each of the plurality of multiword substrings generated from the search query, a value that indicates a fraction of the relevant documents in which an actual occurrence of the each substring is detected; identify, based on the detected actual occurrences of each of the plurality of multiword substrings, that words of at least one of the plurality of multiword substrings, when taken together, form a single compound unit, when identifying that words of at least one of the multiword substrings, when taken together, form a single compound unit, the one or more processors are to: determine that the calculated value associated with the at least one of the plurality of multiword substrings exceeds a threshold value associated with compound units; and identify a set of documents, the set of documents being identified based on the identified at least one of the plurality of multiword substrings. 12. The server device of claim 11 , where the one or more processors are further to: refine the set of documents based on the identified at least one of the plurality of multiword substrings, where when identifying the set of documents, the one or more processors are to identify the set of documents based on the refining.

1. A method, comprising: creating two or more sets of field searchable, time stamped event records from raw data stored in at least one data store, wherein each set of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records comprises field searchable, time stamped event records having time stamps that fall within a time range, the time range different than time ranges associated with other sets of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records, wherein each field searchable, time stamped event record in the two or more sets of field searchable, time stamped event records includes a portion of the raw data and is associated with a time stamp derived from the raw data, wherein the raw data reflects activity in an information technology environment; generating a summarization table for each set of field searchable, time stamped event records in the two or more sets of field searchable, time stamped event records that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more field searchable, time stamped event records in the set of field searchable, time stamped event records; and for each field value, includes a posting value to the one or more field searchable, time stamped event records in the set of field searchable, time stamped event records that contain the field value for the associated field; storing the summarization table for each set of field searchable, time stamped event records among the two or more sets of time stamped field searchable event records; selecting a stored summarization table based on a received query that includes search criteria for evaluating field values for one or more fields; using the search criteria to evaluate field values for one or more fields in the selected summarization table to generate a query result; and wherein the query result reflects an aspect of activity in the information technology environment.

1. A method, comprising: creating two or more sets of field searchable, time stamped event records from raw data stored in at least one data store, wherein each set of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records comprises field searchable, time stamped event records having time stamps that fall within a time range, the time range different than time ranges associated with other sets of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records, wherein each field searchable, time stamped event record in the two or more sets of field searchable, time stamped event records includes a portion of the raw data and is associated with a time stamp derived from the raw data, wherein the raw data reflects activity in an information technology environment; generating a summarization table for each set of field searchable, time stamped event records in the two or more sets of field searchable, time stamped event records that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more field searchable, time stamped event records in the set of field searchable, time stamped event records; and for each field value, includes a posting value to the one or more field searchable, time stamped event records in the set of field searchable, time stamped event records that contain the field value for the associated field; storing the summarization table for each set of field searchable, time stamped event records among the two or more sets of time stamped field searchable event records; selecting a stored summarization table based on a received query that includes search criteria for evaluating field values for one or more fields; using the search criteria to evaluate field values for one or more fields in the selected summarization table to generate a query result; and wherein the query result reflects an aspect of activity in the information technology environment. 12. The method of claim 1 , wherein the raw data includes log data.

21. A computer program product for implementing within a computer system a method for dynamically generating a graphical memorabilia project, the computer program product comprising: a computer-readable, non-transitory, medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing a process comprising: receiving user input relating to a selection of: multiple dynamic page layout templates comprising a first dynamic page layout template and a second dynamic page layout template that each comprise a first well of a first well type and multiple wells of a second well type, wherein a location of the first well of the first well type and locations of the wells of the second well type are fixed with respect to their corresponding template, wherein the first well type will accept an image while preventing one or more background design elements from being disposed therein, wherein each of the one or more background design elements comprises a virtual design that is configured to resemble a decorative element placed in a physical memorabilia project, wherein each of the wells of the second well type will each accept an individual background design element while preventing the image from being disposed therein, wherein the wells of the second well type are divided into well classes, and wherein wells of the second well type that are of the same well class are governed by similar pre-determined rules, such that a change to one of the wells that is of the second well type and of a first well class will cause a similar change to another well of the second well type and of the first well class; a first image to be placed in the first well; and multiple pieces of the one or more background design elements to be placed in the wells of the second well type.

21. A computer program product for implementing within a computer system a method for dynamically generating a graphical memorabilia project, the computer program product comprising: a computer-readable, non-transitory, medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing a process comprising: receiving user input relating to a selection of: multiple dynamic page layout templates comprising a first dynamic page layout template and a second dynamic page layout template that each comprise a first well of a first well type and multiple wells of a second well type, wherein a location of the first well of the first well type and locations of the wells of the second well type are fixed with respect to their corresponding template, wherein the first well type will accept an image while preventing one or more background design elements from being disposed therein, wherein each of the one or more background design elements comprises a virtual design that is configured to resemble a decorative element placed in a physical memorabilia project, wherein each of the wells of the second well type will each accept an individual background design element while preventing the image from being disposed therein, wherein the wells of the second well type are divided into well classes, and wherein wells of the second well type that are of the same well class are governed by similar pre-determined rules, such that a change to one of the wells that is of the second well type and of a first well class will cause a similar change to another well of the second well type and of the first well class; a first image to be placed in the first well; and multiple pieces of the one or more background design elements to be placed in the wells of the second well type. 22. The computer program product of claim 21 , wherein computer program code means is further comprised of executable code for automatically receiving and retaining the image in a first orientation when the template is rotated about its center by 90 degrees and 180 degrees.

12. A communication system, comprising: a communication processor that establishes a communication, wherein the communication includes an audio communication with a plurality of communication devices, receives a plurality of audio streams from the plurality of communication devices, wherein the plurality of audio streams comprises speech of a plurality of users, and transmits a plurality of text streams to at least one communication device involved in the communication; and a translator that translates speech from the plurality of audio streams from the plurality of communication devices into the plurality of text streams, wherein the plurality of text streams are in different languages, and filters a specific translated word, in a specific language, from a specific user of the plurality of users, in a specific one of the plurality of text steams based on a user definable list.

12. A communication system, comprising: a communication processor that establishes a communication, wherein the communication includes an audio communication with a plurality of communication devices, receives a plurality of audio streams from the plurality of communication devices, wherein the plurality of audio streams comprises speech of a plurality of users, and transmits a plurality of text streams to at least one communication device involved in the communication; and a translator that translates speech from the plurality of audio streams from the plurality of communication devices into the plurality of text streams, wherein the plurality of text streams are in different languages, and filters a specific translated word, in a specific language, from a specific user of the plurality of users, in a specific one of the plurality of text steams based on a user definable list. 13. The communication system of claim 12 , wherein each of the plurality of text streams are transmitted individually as a plurality of separate packets, wherein each of the plurality of separate packets contains a corresponding language identifier field.

12. The non-transitory data processing system-readable medium of claim 11 , wherein presentation of the editing copy comprises display of the editing copy, and presentation of the at least one user interface element comprises presentation of the at least one user interface element in a position substantially adjacent to its corresponding content portion, at least some of the at least one user interface elements being displayed between sequential content portions of the plurality of content portions.

12. The non-transitory data processing system-readable medium of claim 11 , wherein presentation of the editing copy comprises display of the editing copy, and presentation of the at least one user interface element comprises presentation of the at least one user interface element in a position substantially adjacent to its corresponding content portion, at least some of the at least one user interface elements being displayed between sequential content portions of the plurality of content portions. 13. The non-transitory data processing system-readable medium of claim 12 , wherein generating the editing copy of the document further comprises converting the received electronic version of the document from a first format to a second format adapted for rendering with the embedded code; and wherein receiving the electronic version of the document generating the editing copy of the document, and transmitting the editing copy of the document are carried out for a plurality of documents received by the data processing system, each of the plurality of documents being received comprising a distinct presentation template for use in presentation of the document.

11. A non-transitory computer-readable medium containing computer-executable instructions to automatically generate a custom JavaServer Faces (JSF) component, the instructions operable when executed by one or more computers to effectuate operations comprising: receiving annotated source code that defines a component class for the custom JSF component of a JSF application, the annotated source code being Java code of a Java class that defines behavior of a user interface element in a web page, the custom JSF component being callable by a custom tag in a markup language document at least in part defining the web page, the annotated source code including a Java annotation designated by an @ symbol prefix corresponding to a renderer; and creating the custom JSF component, at least in part, by: identifying the annotation in the received source code; and in response to identifying the annotation, automatically generating a default decode method of the renderer that interprets inputs related to the custom JSF component and associating the renderer with the custom JSF component in a faces-config.xml file of the JSF application without manually adding a reference to the custom JSF component to the faces-config.xml file of the JSF application.

11. A non-transitory computer-readable medium containing computer-executable instructions to automatically generate a custom JavaServer Faces (JSF) component, the instructions operable when executed by one or more computers to effectuate operations comprising: receiving annotated source code that defines a component class for the custom JSF component of a JSF application, the annotated source code being Java code of a Java class that defines behavior of a user interface element in a web page, the custom JSF component being callable by a custom tag in a markup language document at least in part defining the web page, the annotated source code including a Java annotation designated by an @ symbol prefix corresponding to a renderer; and creating the custom JSF component, at least in part, by: identifying the annotation in the received source code; and in response to identifying the annotation, automatically generating a default decode method of the renderer that interprets inputs related to the custom JSF component and associating the renderer with the custom JSF component in a faces-config.xml file of the JSF application without manually adding a reference to the custom JSF component to the faces-config.xml file of the JSF application. 14. The computer-readable medium of claim 11 , wherein the source code comprises another annotation corresponding to a renderer, and wherein automatically generating the custom JSF component comprises automatically associating the renderer with the custom JSF component in response to identifying the other annotation in the annotated source code.

1. A computer implemented method for selecting external corpora to integrate into primary internet search engine results in response to a query, comprising: receiving a query, at least one server computer, from a client computer over a network; storing an offline model probability in memory; processing said query by: computing a first probabilistic estimate of relevance of external corpora to said query from offline query-related data from said offline model probability; combining said offline query-related data with user feedback data to determine a second probabilistic estimate of relevance of said external corpora to said query; selecting said external corpora to integrate into a response to said query based on said second probabilistic estimate of relevance of said external corpora to said query; and transmitting over said network, for display on said client computer search results for said query that include said external corpora selected.

1. A computer implemented method for selecting external corpora to integrate into primary internet search engine results in response to a query, comprising: receiving a query, at least one server computer, from a client computer over a network; storing an offline model probability in memory; processing said query by: computing a first probabilistic estimate of relevance of external corpora to said query from offline query-related data from said offline model probability; combining said offline query-related data with user feedback data to determine a second probabilistic estimate of relevance of said external corpora to said query; selecting said external corpora to integrate into a response to said query based on said second probabilistic estimate of relevance of said external corpora to said query; and transmitting over said network, for display on said client computer search results for said query that include said external corpora selected. 3. The method of claim 1 , further comprises computing said offline model by: a) gathering data from query and corpus features; b) gathering data from query log features; c) gathering data from query string features; and d) from elements a-c, forming an initial offline estimate of the probability of relevance of each said external corpora to said first query.

2. A control device for evaluating a reed in a jet loom, comprising: information generating means for detecting a last released timing and a last arrival timing of a weft to be inserted and generating the timing informations corresponding thereto; and judging means for evaluating a reed by obtaining, on the basis of both said timing informations outputted from said information generating means, the extent of dispersion of the last released timing and the extent of dispersion of the last arrival timing, and then evaluating the reed on the basis of both said obtained extents.

2. A control device for evaluating a reed in a jet loom, comprising: information generating means for detecting a last released timing and a last arrival timing of a weft to be inserted and generating the timing informations corresponding thereto; and judging means for evaluating a reed by obtaining, on the basis of both said timing informations outputted from said information generating means, the extent of dispersion of the last released timing and the extent of dispersion of the last arrival timing, and then evaluating the reed on the basis of both said obtained extents. 3. A control device according to claim 2, wherein said judging means evaluate said reed on the basis of both said obtained extents and the subpressure for weft inserting.

1. A computer-executable method for searching related documents, the method comprising: receiving a source document; searching for related documents based on semantic entities extracted from the source document; receiving user-adjusted search criteria from a user, wherein the user-adjusted search criteria include a user-adjusted entity-extraction sensitivity, and wherein the user-adjusted entity-extraction sensitivity indicates a number of semantic entities that are to be extracted from the source document; and updating search results of related documents based on the user-adjusted search criteria, wherein the user-adjusted search criteria include the number of semantic entities that are extracted from the source document.

1. A computer-executable method for searching related documents, the method comprising: receiving a source document; searching for related documents based on semantic entities extracted from the source document; receiving user-adjusted search criteria from a user, wherein the user-adjusted search criteria include a user-adjusted entity-extraction sensitivity, and wherein the user-adjusted entity-extraction sensitivity indicates a number of semantic entities that are to be extracted from the source document; and updating search results of related documents based on the user-adjusted search criteria, wherein the user-adjusted search criteria include the number of semantic entities that are extracted from the source document. 7. The method of claim 1 , wherein the searching of related documents involves calculating similarity levels of other documents in relation to the source document.

11. The character input prediction apparatus according to claim 1 , further comprising: a second operation input unit configured to obtain information of a second character input operation that is performed by the user using the character key layout display; a second indication movement detection unit configured to detect a second indication position and a second indication direction in the character key layout display from the information of the second character input operation, the second indication position showing a position of the second character input operation, and the second indication direction showing a movement direction of the second character input operation; a second filter generation unit configured to determine a second character range in the character key layout display using the second indication position, the second indication direction, and the character key layout, the second character range being located in the second indication direction with the second indication position as the base point; and a filter synthesis unit configured to extract a third character range that is included in both the first character range and the second character range, wherein the dictionary search unit is configured to search the plurality of candidate character strings included in the dictionary, for the predictive character string that includes any character included in the third character range.

11. The character input prediction apparatus according to claim 1 , further comprising: a second operation input unit configured to obtain information of a second character input operation that is performed by the user using the character key layout display; a second indication movement detection unit configured to detect a second indication position and a second indication direction in the character key layout display from the information of the second character input operation, the second indication position showing a position of the second character input operation, and the second indication direction showing a movement direction of the second character input operation; a second filter generation unit configured to determine a second character range in the character key layout display using the second indication position, the second indication direction, and the character key layout, the second character range being located in the second indication direction with the second indication position as the base point; and a filter synthesis unit configured to extract a third character range that is included in both the first character range and the second character range, wherein the dictionary search unit is configured to search the plurality of candidate character strings included in the dictionary, for the predictive character string that includes any character included in the third character range. 12. The character input prediction apparatus according to claim 11 , wherein the filter synthesis unit is further configured to determine, as the third character range, a range that is included in the first character range and is located in a direction toward the first indication position with the second indication position as the base point, in the case where the position of the first character input operation moves and a movement amount of the position of the second character input operation is equal to or less than a predetermined threshold.

1. A method of controlling access of a speaker to one of a service and a facility, the method comprising the steps of: (a) receiving first spoken utterances of the speaker, the first spoken utterances containing indicia of the speaker; (b) decoding the first spoken utterances; (c) accessing a database corresponding to the decoded first spoken utterances, the database containing information attributable to a speaker candidate having indicia substantially similar to the speaker; (d) querying the speaker with at least one question based on the information contained in the accessed database; (e) receiving second spoken utterances of the speaker, the second spoken utterances being representative of at least one answer to the at least one question; (f) decoding the second spoken utterances; (g) verifying the accuracy of the decoded answer against the information contained in the accessed database serving as the basis for the question; (h) taking a voice sample from the utterances of the speaker and processing the voice sample against an acoustic model attributable to the speaker candidate; (i) generating a score corresponding to the accuracy of the decoded answer and the closeness of the match between the voice sample and the model; and (j) comparing the score to a predetermined threshold value and if the score is one of substantially equivalent to and above the threshold value, then permitting speaker access to one of the service and the facility.

1. A method of controlling access of a speaker to one of a service and a facility, the method comprising the steps of: (a) receiving first spoken utterances of the speaker, the first spoken utterances containing indicia of the speaker; (b) decoding the first spoken utterances; (c) accessing a database corresponding to the decoded first spoken utterances, the database containing information attributable to a speaker candidate having indicia substantially similar to the speaker; (d) querying the speaker with at least one question based on the information contained in the accessed database; (e) receiving second spoken utterances of the speaker, the second spoken utterances being representative of at least one answer to the at least one question; (f) decoding the second spoken utterances; (g) verifying the accuracy of the decoded answer against the information contained in the accessed database serving as the basis for the question; (h) taking a voice sample from the utterances of the speaker and processing the voice sample against an acoustic model attributable to the speaker candidate; (i) generating a score corresponding to the accuracy of the decoded answer and the closeness of the match between the voice sample and the model; and (j) comparing the score to a predetermined threshold value and if the score is one of substantially equivalent to and above the threshold value, then permitting speaker access to one of the service and the facility. 8. The method of claim 1, wherein at least a portion of the information contained in the database is derived from decoded spoken utterances provided by the speaker.

1. A focus assessment method for determining a focus classification for a workpiece feature image, the focus classification usable to determine whether the image is sufficiently focused, such that a machine vision inspection system may perform useful machine vision inspection operations on the workpiece feature image, the method comprising: using the machine vision inspection system to perform the steps comprising: (a) acquiring a first image of a workpiece feature for which an image focus classification is to be determined; (b) determining a plurality of focus classification features based on the first image, the focus classification features being abstract features included in a multi-parameter feature vector; and (c) determining the focus classification based on processing the determined plurality of focus classification features using at least one classifier, wherein: the at least one classifier comprises at least a first respective classifier that operates on a first respective plurality of classification features; the focus assessment method does not require the acquisition of an additional image of the workpiece feature that is differently focused than the first image; at least the first respective classifier is trained on at least a first respective set of training images; the set of training images comprises respective images of a plurality of different workpieces, wherein the respective images include in-focus images and out-of-focus images; and the respective images are assigned a respective desired focus classification prior to training the respective classifier.

1. A focus assessment method for determining a focus classification for a workpiece feature image, the focus classification usable to determine whether the image is sufficiently focused, such that a machine vision inspection system may perform useful machine vision inspection operations on the workpiece feature image, the method comprising: using the machine vision inspection system to perform the steps comprising: (a) acquiring a first image of a workpiece feature for which an image focus classification is to be determined; (b) determining a plurality of focus classification features based on the first image, the focus classification features being abstract features included in a multi-parameter feature vector; and (c) determining the focus classification based on processing the determined plurality of focus classification features using at least one classifier, wherein: the at least one classifier comprises at least a first respective classifier that operates on a first respective plurality of classification features; the focus assessment method does not require the acquisition of an additional image of the workpiece feature that is differently focused than the first image; at least the first respective classifier is trained on at least a first respective set of training images; the set of training images comprises respective images of a plurality of different workpieces, wherein the respective images include in-focus images and out-of-focus images; and the respective images are assigned a respective desired focus classification prior to training the respective classifier. 6. The method of claim 1 , wherein the plurality of focus classification features comprises at least one edge strength type of focus classification feature.

1. A non-transitory machine readable storage medium comprising a plurality of instructions for determining suggested content that, in response to being executed on a computing device, cause the computing device to: evaluate data that represents a plurality of personality and psychological characteristics of a human user, the data being obtained from a user information system, and the personality and psychological characteristics being relevant to an attainment of an overall health goal for the human user; evaluate data that represents a plurality of behaviors and actions of the human user, the data being obtained from the user information system, and the behaviors and actions being relevant to the attainment of the overall health goal for the human user; select a candidate set of context-sensitive content suggestions for the human user, the context-sensitive content suggestions being selected from a content information system, and the context-sensitive content suggestions indicating respective suggested actions for performance by the human user that assist the attainment of the overall health goal for the human user; filter the candidate set of context-sensitive content suggestions for the human user, based on matching the candidate set to the behaviors and actions of the human user, and matching the candidate set to the personality and psychological characteristics of the human user; prioritize a selected content suggestion from the candidate set of context-sensitive content suggestions for presentation to the human user, based on matching the selected content suggestion to the behavior and actions of the human user, and matching the selected content suggestion to a current state of the human user; and transmit data indicating the selected content suggestion, to cause display of the selected content suggestion to the human user in a graphical user interface of an electronic device.

1. A non-transitory machine readable storage medium comprising a plurality of instructions for determining suggested content that, in response to being executed on a computing device, cause the computing device to: evaluate data that represents a plurality of personality and psychological characteristics of a human user, the data being obtained from a user information system, and the personality and psychological characteristics being relevant to an attainment of an overall health goal for the human user; evaluate data that represents a plurality of behaviors and actions of the human user, the data being obtained from the user information system, and the behaviors and actions being relevant to the attainment of the overall health goal for the human user; select a candidate set of context-sensitive content suggestions for the human user, the context-sensitive content suggestions being selected from a content information system, and the context-sensitive content suggestions indicating respective suggested actions for performance by the human user that assist the attainment of the overall health goal for the human user; filter the candidate set of context-sensitive content suggestions for the human user, based on matching the candidate set to the behaviors and actions of the human user, and matching the candidate set to the personality and psychological characteristics of the human user; prioritize a selected content suggestion from the candidate set of context-sensitive content suggestions for presentation to the human user, based on matching the selected content suggestion to the behavior and actions of the human user, and matching the selected content suggestion to a current state of the human user; and transmit data indicating the selected content suggestion, to cause display of the selected content suggestion to the human user in a graphical user interface of an electronic device. 10. The machine readable storage medium of claim 1 , wherein the overall health goal for the human user relates to: a scheduled administration of medicine, a chronic illness health condition, a long term care health condition, or a physical therapy treatment.

1. A method for contextual management, the method comprising: performing a first process repeatedly, wherein the first process includes: (i) extracting content information corresponding to a new or modified content item from a collection of digital content items to be distributed in a plurality of locations on a network, (ii) normalizing the new or modified content item corresponding to the extracted content information, (iii) sending the normalized content item to a data warehouse, which is a local storage for managing a normalized content item, and (iv) registering keywords extracted from the new or modified content item to the data warehouse; performing a second process repeatedly, wherein the second process includes: (i) examining a new content item of the data warehouse, (ii) generating an index from content information of the new content item, and (iii) updating an index database using the generated index, receiving a query from a computing device, wherein the query is automatically generated by a client program of the computing device in response to a user's operations for an application; determining a context of the user associated with the received query; generating an enhanced query by using a registered keyword corresponding to the contents of the query according to the reception of the query; performing a search based on the context of the user and contents of the enhanced query generated by using the registered keyword; generating a recommendation according to a result of the search and an index in the index database; and returning the generated recommendation to the client program of the computing device.

1. A method for contextual management, the method comprising: performing a first process repeatedly, wherein the first process includes: (i) extracting content information corresponding to a new or modified content item from a collection of digital content items to be distributed in a plurality of locations on a network, (ii) normalizing the new or modified content item corresponding to the extracted content information, (iii) sending the normalized content item to a data warehouse, which is a local storage for managing a normalized content item, and (iv) registering keywords extracted from the new or modified content item to the data warehouse; performing a second process repeatedly, wherein the second process includes: (i) examining a new content item of the data warehouse, (ii) generating an index from content information of the new content item, and (iii) updating an index database using the generated index, receiving a query from a computing device, wherein the query is automatically generated by a client program of the computing device in response to a user's operations for an application; determining a context of the user associated with the received query; generating an enhanced query by using a registered keyword corresponding to the contents of the query according to the reception of the query; performing a search based on the context of the user and contents of the enhanced query generated by using the registered keyword; generating a recommendation according to a result of the search and an index in the index database; and returning the generated recommendation to the client program of the computing device. 9. The method of claim 1 , further comprising: filtering the generated recommendation based on access permissions of the received query.

18. In a medical implant assembly having at least two bone anchors cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) an anchor member having an inner aperture slidingly receiving a discrete inner core, the core extending from the anchor member along a central axis of the connecting member, the core being surrounded by a remainder of the connecting member and in one of spaced and slidable relation thereto; b) at least one elastic spacer, the core being slidingly received in the spacer along the axis, the spacer being positioned between the at least two bone anchors; c) at least one inelastic sleeve, the core being slidingly received within the sleeve along the axis, the sleeve being in engagement with at least one of the bone anchors; and d) an over-molded elastomer surrounding the spacer and attached to the anchor member and the sleeve.

18. In a medical implant assembly having at least two bone anchors cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) an anchor member having an inner aperture slidingly receiving a discrete inner core, the core extending from the anchor member along a central axis of the connecting member, the core being surrounded by a remainder of the connecting member and in one of spaced and slidable relation thereto; b) at least one elastic spacer, the core being slidingly received in the spacer along the axis, the spacer being positioned between the at least two bone anchors; c) at least one inelastic sleeve, the core being slidingly received within the sleeve along the axis, the sleeve being in engagement with at least one of the bone anchors; and d) an over-molded elastomer surrounding the spacer and attached to the anchor member and the sleeve. 20. The improvement of claim 18 wherein the over-molded elastomer further comprises reinforcement strands.

36. In a computer network, a computer system for implementing a method for maintaining an acceptable use policy the computer system comprising: a machine capable of executing instructions embodied as software; and a plurality of software portions comprising one of said software portions is configured to receive input from a user selecting a subject matter category for use in monitoring logged network data containing language elements; one of said software portions is configured to test the language elements of the network data for the presence of at least one preselected criterion, wherein the preselected criterion is defined by a user, comprises two or more subject matter categories each comprising regular expressions, with a first portion of said regular expressions assigned weights with negative values and a second portion of said regular expressions assigned weights with positive values, wherein the language elements of the network data are tested for the presence of the at least one preselected criterion and wherein said testing first tests the language elements of the network data for the presence of the negative valued regular expressions to facilitate avoidance of false hits; one of said software portions is configured to maintain a sum of values associated with said regular expressions found within at least one subject matter category as each regular expression is found by said testing by adding the value of the found regular expression to the sum of values; and one of said software portions is configured to store the network data for subsequent action selected from the group consisting of reporting, viewing, downloading and deleting when the sum of values associated with said regular expressions within a category meets or exceeds a positive threshold value selected based on user input.

36. In a computer network, a computer system for implementing a method for maintaining an acceptable use policy the computer system comprising: a machine capable of executing instructions embodied as software; and a plurality of software portions comprising one of said software portions is configured to receive input from a user selecting a subject matter category for use in monitoring logged network data containing language elements; one of said software portions is configured to test the language elements of the network data for the presence of at least one preselected criterion, wherein the preselected criterion is defined by a user, comprises two or more subject matter categories each comprising regular expressions, with a first portion of said regular expressions assigned weights with negative values and a second portion of said regular expressions assigned weights with positive values, wherein the language elements of the network data are tested for the presence of the at least one preselected criterion and wherein said testing first tests the language elements of the network data for the presence of the negative valued regular expressions to facilitate avoidance of false hits; one of said software portions is configured to maintain a sum of values associated with said regular expressions found within at least one subject matter category as each regular expression is found by said testing by adding the value of the found regular expression to the sum of values; and one of said software portions is configured to store the network data for subsequent action selected from the group consisting of reporting, viewing, downloading and deleting when the sum of values associated with said regular expressions within a category meets or exceeds a positive threshold value selected based on user input. 39. The method of claim 36 , further comprising a software portion configured to output a report relating to the presence of predetermined expressions whose sum meets or exceeds the threshold value of a category.

58. A database system according to claim 55, further comprising: a remote device, comprising a second random access memory, a non-volatile memory, a second input device, a second output device, a second processor and a second bus for coupling the second random access memory, the non-volatile memory, the second input device, the second output device and the second processor, for accessing data in the database image at a location separate from that of the computer system; a copy of the record information table and translation table, stored in the non-volatile memory; and a communications channel connecting the remote device to the computer system.

58. A database system according to claim 55, further comprising: a remote device, comprising a second random access memory, a non-volatile memory, a second input device, a second output device, a second processor and a second bus for coupling the second random access memory, the non-volatile memory, the second input device, the second output device and the second processor, for accessing data in the database image at a location separate from that of the computer system; a copy of the record information table and translation table, stored in the non-volatile memory; and a communications channel connecting the remote device to the computer system. 59. A database system according to claim 58, wherein a partial copy of the database image is stored in the nonvolatile memory.

1. A non-transitory computer-readable storage medium comprising instructions configured for execution by a computing device, to cause the computing device to perform operations, comprising: receiving a query associated with a user, the query comprising an intersection criteria, the intersection criteria comprising a specified location and a specified timeframe; generating an intersection space responsive to the query by: accessing a plurality of stories, each story submitted by a submitter and comprising one or more content items and having respective intersection metadata, the intersection metadata of each story comprising a location and a timeframe pertaining to the story, selecting stories for inclusion in the intersection space that each have intersection metadata corresponding to the location and the timeframe of the intersection criteria, accessing timeframe-dependent access controls provided by respective submitters that submitted the selected stories; filtering the selected stories based on the timeframe-dependent access controls, such that each remaining selected story in the intersection space is associated with one or more timeframes the user is authorized to access based on the corresponding timeframe-dependent access controls; and displaying the intersection space to the user on a display device, the display comprising indicators of one or more of the filtered stories selected for inclusion in the intersection space.

1. A non-transitory computer-readable storage medium comprising instructions configured for execution by a computing device, to cause the computing device to perform operations, comprising: receiving a query associated with a user, the query comprising an intersection criteria, the intersection criteria comprising a specified location and a specified timeframe; generating an intersection space responsive to the query by: accessing a plurality of stories, each story submitted by a submitter and comprising one or more content items and having respective intersection metadata, the intersection metadata of each story comprising a location and a timeframe pertaining to the story, selecting stories for inclusion in the intersection space that each have intersection metadata corresponding to the location and the timeframe of the intersection criteria, accessing timeframe-dependent access controls provided by respective submitters that submitted the selected stories; filtering the selected stories based on the timeframe-dependent access controls, such that each remaining selected story in the intersection space is associated with one or more timeframes the user is authorized to access based on the corresponding timeframe-dependent access controls; and displaying the intersection space to the user on a display device, the display comprising indicators of one or more of the filtered stories selected for inclusion in the intersection space. 5. The non-transitory computer-readable storage medium of claim 1 , wherein the location of the intersection criteria corresponds to a virtual location.

12. An apparatus, comprising: at least one processor; and a storage module having stored therein machine executable instructions, that when executed by the at least one processor, cause the apparatus to: determine one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer, wherein said determining the one or more mood metrics for a chat stage of the real-time textual conversation, by the processor, further comprises determining an overall mood for the chat stage based on a polarity based approach by: assigning polarity labels to features present in the chat stage; assigning polarity strength scores for the polarity labels assigned to the features present in the chat stage; calculating weighted polarity scores for the features based on aggregation of the polarity labels and the polarity strength scores to determine the overall mood for the chat stage; and determining the overall mood based on a subjectivity-based approach by removing terms classified as objective from the real-time textual conversation prior to assigning the polarity labels and the polarity strength scores; track changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation between the agent and the customer; and determine at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics; and an input-output (I/O) module; wherein the at least one processor is further configured to cause the apparatus to perform the at least one action by enabling the I/O module to any of: displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation; displaying information associated with the at least one action to a supervisor monitoring the real-time textual conversation and causing the I/O module to provide the information associated with the at least one action to the agent engaged in the real-time textual conversation based on an input received from the supervisor so as to enable the agent to perform the at least one action thereby causing a target outcome of the real-time textual conversation; monitoring an agent engagement score associated with the two or more chat stages of the real-time textual conversation; storing the real-time textual conversation with a timestamp of the real-time textual conversation; and displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation.

12. An apparatus, comprising: at least one processor; and a storage module having stored therein machine executable instructions, that when executed by the at least one processor, cause the apparatus to: determine one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer, wherein said determining the one or more mood metrics for a chat stage of the real-time textual conversation, by the processor, further comprises determining an overall mood for the chat stage based on a polarity based approach by: assigning polarity labels to features present in the chat stage; assigning polarity strength scores for the polarity labels assigned to the features present in the chat stage; calculating weighted polarity scores for the features based on aggregation of the polarity labels and the polarity strength scores to determine the overall mood for the chat stage; and determining the overall mood based on a subjectivity-based approach by removing terms classified as objective from the real-time textual conversation prior to assigning the polarity labels and the polarity strength scores; track changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation between the agent and the customer; and determine at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics; and an input-output (I/O) module; wherein the at least one processor is further configured to cause the apparatus to perform the at least one action by enabling the I/O module to any of: displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation; displaying information associated with the at least one action to a supervisor monitoring the real-time textual conversation and causing the I/O module to provide the information associated with the at least one action to the agent engaged in the real-time textual conversation based on an input received from the supervisor so as to enable the agent to perform the at least one action thereby causing a target outcome of the real-time textual conversation; monitoring an agent engagement score associated with the two or more chat stages of the real-time textual conversation; storing the real-time textual conversation with a timestamp of the real-time textual conversation; and displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation. 25. The apparatus of claim 12 , wherein the apparatus is further configured to determining an overall mood for a chat stage of the real-time textual conversation based on a supervised text classification approach.

1. A computer-based recommendation system for generating recommendations of unique items, the recommendation system comprising: one or more computer readable storage devices configured to store: a plurality of computer executable instructions; an items information database containing data relating to a plurality of unique items; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to: receive an input from a user that comprises user-expressed preferences associated with the plurality of unique items; calculate a customization score for each unique item in the plurality of unique items, the customization score at least partially based on at least one customization attribute associated with that unique item; calculate a condition score for each unique item in the plurality of unique items, the condition score at least partially based on at least one condition attribute associated with that unique item; generate a dissimilarity penalty for each unique item in the plurality of unique items by combining the customization score and the condition score for that unique item, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between the unique item and the user-expressed preferences; and generate a recommendation of unique items by ranking at least a portion of the plurality of the unique items based at least partially on the calculated dissimilarity penalties.

1. A computer-based recommendation system for generating recommendations of unique items, the recommendation system comprising: one or more computer readable storage devices configured to store: a plurality of computer executable instructions; an items information database containing data relating to a plurality of unique items; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to: receive an input from a user that comprises user-expressed preferences associated with the plurality of unique items; calculate a customization score for each unique item in the plurality of unique items, the customization score at least partially based on at least one customization attribute associated with that unique item; calculate a condition score for each unique item in the plurality of unique items, the condition score at least partially based on at least one condition attribute associated with that unique item; generate a dissimilarity penalty for each unique item in the plurality of unique items by combining the customization score and the condition score for that unique item, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between the unique item and the user-expressed preferences; and generate a recommendation of unique items by ranking at least a portion of the plurality of the unique items based at least partially on the calculated dissimilarity penalties. 3. The computer-based recommendation system of claim 1 , wherein the unique items comprise one of the following types of items: used automobiles, existing homes, real estate, household goods, customized electronics, customized goods.

2. A method as recited in claim 1 , wherein the series of user input selections comprises a partial data input, and wherein the additional input selection is determined by: comparing, by the computer, the partial data input to a plurality of grammar rules that identify valid inputs; identifying by the computer, based on the comparing, a set of grammar rules that match the partial data input; assigning a score to each of the grammar rules by the computer, the score indicating how closely the grammar rule matches the partial data input; and selecting by the computer, as the additional input selection, the grammar rule with a highest score.

2. A method as recited in claim 1 , wherein the series of user input selections comprises a partial data input, and wherein the additional input selection is determined by: comparing, by the computer, the partial data input to a plurality of grammar rules that identify valid inputs; identifying by the computer, based on the comparing, a set of grammar rules that match the partial data input; assigning a score to each of the grammar rules by the computer, the score indicating how closely the grammar rule matches the partial data input; and selecting by the computer, as the additional input selection, the grammar rule with a highest score. 7. A method as recited in claim 2 , wherein the plurality of grammar rules includes a set of grammar rules that were previously accepted by the user to complete a previous partial data input.

1. A method of generating characters of an Ethiopic alphabet using key presses inputted on a device keyboard, comprising: receiving at the device keyboard a first keystroke, wherein the device keyboard is a QWERTY keyboard or a Dvorac keyboard; in response to receiving the first keystroke, starting a first timer, designating a first character a first contingent character, and rendering the first contingent character prior to the first timer expiring; if the first timer expires, accepting the first contingent character; if a second keystroke is received at the device keyboard prior to the first timer expiring, determining if the second keystroke is associated with one of a number of predetermined specifier keys associated with the first keystroke; if the second keystroke received prior to the first timer expiring is not one of the predetermined specifier keys, accepting the first contingent character and rendering a second character; if the second keystroke received prior to the first timer expiring is one of the predetermined specifier keys, removing the first character and rendering a third character; if the second keystroke is an order modifying keystroke, providing a second order group of characters and starting a second timer; if a third keystroke is received at the device keyboard prior to the second timer expiring, determining if the third keystroke is associated with one of a number of predetermined specifier keys associated with the first keystroke; if the third keystroke received prior to the second timer expiring is not one of the predetermined specifier keys, accepting the first contingent character and rendering a fourth character; and if the third keystroke received prior to the second timer expiring is one of the predetermined specifier keys, removing the first character and rendering a fifth character.

1. A method of generating characters of an Ethiopic alphabet using key presses inputted on a device keyboard, comprising: receiving at the device keyboard a first keystroke, wherein the device keyboard is a QWERTY keyboard or a Dvorac keyboard; in response to receiving the first keystroke, starting a first timer, designating a first character a first contingent character, and rendering the first contingent character prior to the first timer expiring; if the first timer expires, accepting the first contingent character; if a second keystroke is received at the device keyboard prior to the first timer expiring, determining if the second keystroke is associated with one of a number of predetermined specifier keys associated with the first keystroke; if the second keystroke received prior to the first timer expiring is not one of the predetermined specifier keys, accepting the first contingent character and rendering a second character; if the second keystroke received prior to the first timer expiring is one of the predetermined specifier keys, removing the first character and rendering a third character; if the second keystroke is an order modifying keystroke, providing a second order group of characters and starting a second timer; if a third keystroke is received at the device keyboard prior to the second timer expiring, determining if the third keystroke is associated with one of a number of predetermined specifier keys associated with the first keystroke; if the third keystroke received prior to the second timer expiring is not one of the predetermined specifier keys, accepting the first contingent character and rendering a fourth character; and if the third keystroke received prior to the second timer expiring is one of the predetermined specifier keys, removing the first character and rendering a fifth character. 10. The method of claim 1 , wherein rendering the first character, the second character, the third character, the fourth character and the fifth character includes referencing a Unicode font library.

1. A method for analyzing cohorts to answer a question in a question answering system, the method comprising the steps of: identifying the cohorts for a person in the question, wherein the cohorts are persons meeting a threshold of similar attributes to the person of the question and available in a corpus of data to answer the question; extracting answers and evidence from data of the cohorts; combining and ranking the extracted answers and evidence from the cohorts; using the combined and ranked answers and evidence to gather statistically significant evidence; and answering the question with the gathered statistically significant evidence.

1. A method for analyzing cohorts to answer a question in a question answering system, the method comprising the steps of: identifying the cohorts for a person in the question, wherein the cohorts are persons meeting a threshold of similar attributes to the person of the question and available in a corpus of data to answer the question; extracting answers and evidence from data of the cohorts; combining and ranking the extracted answers and evidence from the cohorts; using the combined and ranked answers and evidence to gather statistically significant evidence; and answering the question with the gathered statistically significant evidence. 7. The method of claim 1 wherein the attributes include age, race and symptoms.

11. A computer program product comprising machine-readable instructions, stored on non-transitory computer-readable storage media, for causing a computing device, including a processor and system memory, to perform the steps of: a) creating a probabilistic model of a paragraph of text, parameterized by inter-word spacing; and b) running an inference on the model to find a sequence of line-breaks that maximize the joint probability of line break positions with minimum deviation of inter-word spacing from an ideal value, by performing a max-product belief propagation operation.

11. A computer program product comprising machine-readable instructions, stored on non-transitory computer-readable storage media, for causing a computing device, including a processor and system memory, to perform the steps of: a) creating a probabilistic model of a paragraph of text, parameterized by inter-word spacing; and b) running an inference on the model to find a sequence of line-breaks that maximize the joint probability of line break positions with minimum deviation of inter-word spacing from an ideal value, by performing a max-product belief propagation operation. 13. A computer program product in accordance with claim 11 , wherein performing max-product belief propagation operation determines the maximum joint probability of line break locations with minimum deviation of inter-word spacing from the ideal value.

1. A method for comparing a query object and a set of database objects comprising: providing quantized representations of database objects which have each been transformed with a quantized embedding function which is the composition of a real-valued embedding function and a quantization function which embeds the representations in a quantized embedding space composed of quantized values; transforming the query object to a representation comprising a vector of k dimensions in a real-valued embedding space using the real-valued embedding function; computing a set of query-independent expected values comprising computing, for each of the k dimensions, a first average expected value in the real-valued embedding space for a first sample of database objects having a first of the quantized values in the quantized embedding space and a second average expected value in the real-valued embedding space for a second sample of database objects having a second of the quantized values in the quantized embedding space for the dimension; storing a set of computed query-dependent estimated distance values for the query object, based on the distance from the transformed query object to the computed set of query-independent expected values; and computing a comparison measure between the query object and each of the quantized database object representations based on the stored query-dependent estimated distance values; and outputting data based on the comparison computation.

1. A method for comparing a query object and a set of database objects comprising: providing quantized representations of database objects which have each been transformed with a quantized embedding function which is the composition of a real-valued embedding function and a quantization function which embeds the representations in a quantized embedding space composed of quantized values; transforming the query object to a representation comprising a vector of k dimensions in a real-valued embedding space using the real-valued embedding function; computing a set of query-independent expected values comprising computing, for each of the k dimensions, a first average expected value in the real-valued embedding space for a first sample of database objects having a first of the quantized values in the quantized embedding space and a second average expected value in the real-valued embedding space for a second sample of database objects having a second of the quantized values in the quantized embedding space for the dimension; storing a set of computed query-dependent estimated distance values for the query object, based on the distance from the transformed query object to the computed set of query-independent expected values; and computing a comparison measure between the query object and each of the quantized database object representations based on the stored query-dependent estimated distance values; and outputting data based on the comparison computation. 4. The method of claim 1 , wherein the storing of the set of computed query-dependent expected distance values comprises computing the set of query-dependent expected distances as a function of the set of query-independent expected values and transformed query object.

10. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors, cause the one or more processors to: generate a speech segment from one or more text strings describing or identifying a media asset having audio data distinct from the generated speech segment; obtain user input requesting a variation in speech delivery accompanying the media asset; in response to the user input, customize the speech segment by modifying selected portions of the speech segment at a server device, wherein the customizing further comprises: automatically detecting one or more repeated portions in the speech segment; and automatically modifying the speech segment by performing one or more of: (1) omitting at least one of the repeated portions from the speech segment, (2) using faster speech patterns for at least one of the repeated portions, (3) shortening breaks between words in at least one of the repeated portions, and (4) truncating one or more phrases in at least one of the repeated portions; and provide the customized speech segment from the server device to a user device for playback with the media asset.

10. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors, cause the one or more processors to: generate a speech segment from one or more text strings describing or identifying a media asset having audio data distinct from the generated speech segment; obtain user input requesting a variation in speech delivery accompanying the media asset; in response to the user input, customize the speech segment by modifying selected portions of the speech segment at a server device, wherein the customizing further comprises: automatically detecting one or more repeated portions in the speech segment; and automatically modifying the speech segment by performing one or more of: (1) omitting at least one of the repeated portions from the speech segment, (2) using faster speech patterns for at least one of the repeated portions, (3) shortening breaks between words in at least one of the repeated portions, and (4) truncating one or more phrases in at least one of the repeated portions; and provide the customized speech segment from the server device to a user device for playback with the media asset. 17. The computer-readable storage medium of claim 10 , wherein the instructions further cause the one or more processors to: detect user input fast forwarding or skipping playback of at least a first speech segment previously delivered to the user device; and in response to the detecting, customize speech delivery for a second speech segment to be delivered from the client device to the user device.

1. A method for consolidating a glyph of a font, comprising: normalizing a first contour in the glyph and a second contour in the glyph to generate a first normalized contour and a second normalized contour; comparing the first normalized contour to the second normalized contour, comprising at least one of comparing a first number of points of the first normalized contour to a second number of points of the second normalized contour, comparing a first position of points of the first normalized contour to a second position of points of the second normalized contour or comparing a first order of points of the first normalized contour to a second order of points of the second normalized contour; based upon the comparing, determining that the first normalized contour and the second normalized contour comprise at least one of a same number of points, a same position of points or a same order of points indicating that the first contour and the second contour correspond to a common contour; and based upon the determining, replacing the first contour with a first reference to a common simple glyph for the common contour and replacing the second contour with a second reference to the common simple glyph to consolidate the glyph.

1. A method for consolidating a glyph of a font, comprising: normalizing a first contour in the glyph and a second contour in the glyph to generate a first normalized contour and a second normalized contour; comparing the first normalized contour to the second normalized contour, comprising at least one of comparing a first number of points of the first normalized contour to a second number of points of the second normalized contour, comparing a first position of points of the first normalized contour to a second position of points of the second normalized contour or comparing a first order of points of the first normalized contour to a second order of points of the second normalized contour; based upon the comparing, determining that the first normalized contour and the second normalized contour comprise at least one of a same number of points, a same position of points or a same order of points indicating that the first contour and the second contour correspond to a common contour; and based upon the determining, replacing the first contour with a first reference to a common simple glyph for the common contour and replacing the second contour with a second reference to the common simple glyph to consolidate the glyph. 12. The method of claim 1 , comprising creating a complex glyph comprising: a reference to one or more transformations for the common simple glyph.

18. An automatic music composing apparatus comprising: a storage device which stores reference melody data sets each of which represents a reference melody fragment and melody generation data sets each of which contains melody specifying data of an amount for a piece of music so as to be used for generating a melody to constitute a musical piece, each said reference melody fragment being a melody fragment which correspondingly typifies each said melody generation data set; a supply device for supplying melody data which defines a desired melody fragment; a detector which compares said supplied melody data supplied by said supply device with the reference melody data set stored in said storage device and detects unequal conditions between said supplied melody data and said stored reference characteristics data set to deliver unequalness data indicating said unequal conditions; a read out device which reads out said melody generation data set stored in said storage device; a melody generator which generates melody data representing a musical piece based on the melody generation data set as read out from said storage device; and an adjuster which adjusts said melody data generated by said melody generator in accordance with said unequalness data from said detector.

18. An automatic music composing apparatus comprising: a storage device which stores reference melody data sets each of which represents a reference melody fragment and melody generation data sets each of which contains melody specifying data of an amount for a piece of music so as to be used for generating a melody to constitute a musical piece, each said reference melody fragment being a melody fragment which correspondingly typifies each said melody generation data set; a supply device for supplying melody data which defines a desired melody fragment; a detector which compares said supplied melody data supplied by said supply device with the reference melody data set stored in said storage device and detects unequal conditions between said supplied melody data and said stored reference characteristics data set to deliver unequalness data indicating said unequal conditions; a read out device which reads out said melody generation data set stored in said storage device; a melody generator which generates melody data representing a musical piece based on the melody generation data set as read out from said storage device; and an adjuster which adjusts said melody data generated by said melody generator in accordance with said unequalness data from said detector. 20. An automatic music composing apparatus according to claim 18, wherein said supply device is to supply first melody data representing a melody fragment for a partial section of a musical piece to be composed, and said melody generator generates second melody data for the remaining sections of said musical piece to be composed and combines said first melody data and said second melody data to generate a melody data set representing an amount of melody to constitute a musical piece.

1. A computer-implemented method comprising: receiving, by a search system, from a user a search query comprising keywords; using at least one association graph comprising keywords, identifying, by the search system, one or more suggested replacement keywords for one or more of the keywords of the search query; presenting the suggested replacement keywords to the user; responsively to a selection of one of the suggested replacement keywords by the user, substituting, by the search system, the selected suggested replacement keyword for the corresponding one of the keywords of the search query, to generate a refined search query; and presenting search results to the user responsively to the refined search query, wherein identifying the one or more suggested replacement keywords comprises: designating, by the search system, one or more of the keywords of the search query as anchor keywords, and the remaining keywords of the search query as non-anchor keywords; and identifying, by the search system, the one or more suggested replacement keywords for one or more of the non-anchor keywords and not for any of the anchor keywords.

1. A computer-implemented method comprising: receiving, by a search system, from a user a search query comprising keywords; using at least one association graph comprising keywords, identifying, by the search system, one or more suggested replacement keywords for one or more of the keywords of the search query; presenting the suggested replacement keywords to the user; responsively to a selection of one of the suggested replacement keywords by the user, substituting, by the search system, the selected suggested replacement keyword for the corresponding one of the keywords of the search query, to generate a refined search query; and presenting search results to the user responsively to the refined search query, wherein identifying the one or more suggested replacement keywords comprises: designating, by the search system, one or more of the keywords of the search query as anchor keywords, and the remaining keywords of the search query as non-anchor keywords; and identifying, by the search system, the one or more suggested replacement keywords for one or more of the non-anchor keywords and not for any of the anchor keywords. 7. The method according to claim 1 , wherein the at least one association graph comprises a topic association graph (TAG) that represents interactions of previous search queries of a plurality of users including the user, conducted within a single topic, with respective search result documents presented to the users in response to the previous search queries.

11. A computer-implemented method, comprising: receiving a first set of phrase terms for a first phrase at a computing device within a phrase detection system, the first phrase terms being in first ordinal positions and the first set of phrase terms having a first cardinality, and the phrase terms are indicative of data leakage; receiving a second set of phrase terms for a second phrase at the phrase detection system, the second phrase terms being in second ordinal positions and the second set of phrase terms having a second cardinality that is greater than the first cardinality; generating a set of first hashes for each of the phrase terms by the phrase detection system; generating concatenated hashes from the first hashes by the phrase detection system, the concatenated hashes including a concatenation of the first hashes for the first set of phrase terms according to the first ordinal positions, a concatenation of the first hashes for the second set of phrase terms according to the second ordinal positions, concatenations of proper subsets of the set of first hashes in the first set according to the first ordinal positions, and concatenations of proper subsets of the set of first hashes in the second set according to the second ordinal positions; using the first set of hashes and the concatenated hashes for phrase detection by the phrase detection system in content with noise terms intermixed between phrase terms in the content, wherein the noise terms comprise terms, words and other data that when hashed do not match one of the first set of hashes, and wherein the noise terms are ignored in the phrase detection; receiving content, the content including content terms in third ordinal positions; generating a set of second hashes, the set of second hashes includes a second hash for each of the content terms; selecting the second hashes according to an increasing order of the third ordinal positions and the sub-phrase scores; comparing the selected second hashes of the content terms to the concatenated hashes and the first hashes; and determining a phrase detection of one of the first phrase and second phrase has occurred if selected second hashes match at least one comparison to the concatenated hashes or first hashes; wherein selecting the second hashes according to the increasing order of the third ordinal positions comprises: comparing the cardinality of the set of second hashes to the first cardinality; selecting the set of second hashes when the cardinality of the set of second hashes is equal to the first cardinality; and selecting the set of the second hashes and selecting proper subsets of the set of second hashes according to the second ordinal positions of the content terms and the sub-phrase scores when the cardinality of the set of second hashes is greater than the first cardinality.

11. A computer-implemented method, comprising: receiving a first set of phrase terms for a first phrase at a computing device within a phrase detection system, the first phrase terms being in first ordinal positions and the first set of phrase terms having a first cardinality, and the phrase terms are indicative of data leakage; receiving a second set of phrase terms for a second phrase at the phrase detection system, the second phrase terms being in second ordinal positions and the second set of phrase terms having a second cardinality that is greater than the first cardinality; generating a set of first hashes for each of the phrase terms by the phrase detection system; generating concatenated hashes from the first hashes by the phrase detection system, the concatenated hashes including a concatenation of the first hashes for the first set of phrase terms according to the first ordinal positions, a concatenation of the first hashes for the second set of phrase terms according to the second ordinal positions, concatenations of proper subsets of the set of first hashes in the first set according to the first ordinal positions, and concatenations of proper subsets of the set of first hashes in the second set according to the second ordinal positions; using the first set of hashes and the concatenated hashes for phrase detection by the phrase detection system in content with noise terms intermixed between phrase terms in the content, wherein the noise terms comprise terms, words and other data that when hashed do not match one of the first set of hashes, and wherein the noise terms are ignored in the phrase detection; receiving content, the content including content terms in third ordinal positions; generating a set of second hashes, the set of second hashes includes a second hash for each of the content terms; selecting the second hashes according to an increasing order of the third ordinal positions and the sub-phrase scores; comparing the selected second hashes of the content terms to the concatenated hashes and the first hashes; and determining a phrase detection of one of the first phrase and second phrase has occurred if selected second hashes match at least one comparison to the concatenated hashes or first hashes; wherein selecting the second hashes according to the increasing order of the third ordinal positions comprises: comparing the cardinality of the set of second hashes to the first cardinality; selecting the set of second hashes when the cardinality of the set of second hashes is equal to the first cardinality; and selecting the set of the second hashes and selecting proper subsets of the set of second hashes according to the second ordinal positions of the content terms and the sub-phrase scores when the cardinality of the set of second hashes is greater than the first cardinality. 16. The method of claim 11 , further comprising: receiving content, the content including content terms in third ordinal positions; generating a set of second hashes, the set of second hashes includes a second hash for each of the content terms; selecting the second hashes according to an increasing order of the third ordinal positions; comparing the selected second hashes of the content terms to the concatenated hashes and the first hashes; and determining a phrase detection of one of the first phrase and second phrase has occurred if selected second hashes match at least one comparison to the concatenated hashes or first hashes.

1. A computer-implemented method comprising: identifying, by a browser assistant, a set of one or more context uniform resource identifiers; receiving, by the browser assistant, a set of one or more referenced uniform resource identifiers that are referenced by a search results page provided by a search engine; for each referenced uniform resource identifier, determining, by the browser assistant, a relatedness score based on an extent to which the referenced uniform resource identifier is related to one or more of the context uniform resource identifiers; selecting, by the browser assistant, a subset of the referenced uniform resource identifiers for presentation based on the relatedness scores; and providing, by the browser assistant, the subset of the referenced uniform resource identifiers for presentation as a web page in a browser window.

1. A computer-implemented method comprising: identifying, by a browser assistant, a set of one or more context uniform resource identifiers; receiving, by the browser assistant, a set of one or more referenced uniform resource identifiers that are referenced by a search results page provided by a search engine; for each referenced uniform resource identifier, determining, by the browser assistant, a relatedness score based on an extent to which the referenced uniform resource identifier is related to one or more of the context uniform resource identifiers; selecting, by the browser assistant, a subset of the referenced uniform resource identifiers for presentation based on the relatedness scores; and providing, by the browser assistant, the subset of the referenced uniform resource identifiers for presentation as a web page in a browser window. 2. The method of claim 1 , the method further comprising: identifying, by the browser assistant, a particular uniform resource identifier associated with a current browsing session; identifying, by the browser assistant, one or more other uniform resource identifiers that are related to the particular uniform resource identifier associated with the current browsing session; and adding, by the browser assistant, the one or more other uniform resource identifiers to the set of one or more context uniform resource identifiers.

1. A method comprising: receiving, by a media processor, prior to entering a screensaver mode of operation, a search criteria identifying a requested subject matter, wherein the search criteria is based on a last user-initiated search query to a web-based search engine; entering, by the media processor, the screensaver mode of operation; in response to entering the screensaver mode, automatically transmitting, by the media processor, the search criteria identifying the requested subject matter to a web browser; receiving, by the media processor, a set of uniform resource locators from the web browser based upon the search criteria; sequentially presenting, by the media processor at a display device during the screensaver mode, only image content referenced by the set of uniform resource locators that correspond to image files; receiving, by the media processor during the screensaver mode, user input from a first input device of the media processor during a presentation of a first image associated with a first uniform resource locator of the set of uniform resource locators; in response to receiving the user input from the first input device, presenting, by the media processor during the screensaver mode, a user-selectable region comprising a selectable element superimposed on the first image, wherein the user-selectable region includes a selectable graphical element superimposed on a graphical interface for presenting the first image; detecting, by the media processor during the screensaver mode, a selection of a first element of the selectable element; causing, by the media processor during the screensaver mode, a defined action responsive to the selection of the first element, wherein the defined action causes a storage of the first image referenced by the first uniform resource locator in a memory device as stored content and generation of an e-mail message having an attachment with content referenced by a link associated with the first image; and in response to receiving the user input from a second input device, ceasing, by the media processor, the presenting of the image content at the first image.

1. A method comprising: receiving, by a media processor, prior to entering a screensaver mode of operation, a search criteria identifying a requested subject matter, wherein the search criteria is based on a last user-initiated search query to a web-based search engine; entering, by the media processor, the screensaver mode of operation; in response to entering the screensaver mode, automatically transmitting, by the media processor, the search criteria identifying the requested subject matter to a web browser; receiving, by the media processor, a set of uniform resource locators from the web browser based upon the search criteria; sequentially presenting, by the media processor at a display device during the screensaver mode, only image content referenced by the set of uniform resource locators that correspond to image files; receiving, by the media processor during the screensaver mode, user input from a first input device of the media processor during a presentation of a first image associated with a first uniform resource locator of the set of uniform resource locators; in response to receiving the user input from the first input device, presenting, by the media processor during the screensaver mode, a user-selectable region comprising a selectable element superimposed on the first image, wherein the user-selectable region includes a selectable graphical element superimposed on a graphical interface for presenting the first image; detecting, by the media processor during the screensaver mode, a selection of a first element of the selectable element; causing, by the media processor during the screensaver mode, a defined action responsive to the selection of the first element, wherein the defined action causes a storage of the first image referenced by the first uniform resource locator in a memory device as stored content and generation of an e-mail message having an attachment with content referenced by a link associated with the first image; and in response to receiving the user input from a second input device, ceasing, by the media processor, the presenting of the image content at the first image. 10. The method of claim 1 , wherein the defined action causes an exiting of the screensaver mode and an opening of a website page within a browser referenced by the first uniform resource locator associated with the first image.

1. A computer implemented method for composing a target keyphrase to be searched, wherein the target keyphrase comprises a plurality of keywords, the computer implemented method comprising: receiving, in a search bar, one or more textual characters following at least one previously existing keyword; providing a plurality of keyword results associated only with the one or more textual characters irrespective of the at least one previously existing keyword; receiving a selection input for selecting a keyword result from amongst the plurality of keyword results associated only with the one or more textual characters irrespective of the at least one previously existing keyword; and word by word composing the target keyphrase by appending the selected keyword result associated only with the one or more textual characters irrespective of the at least one previously existing keyword to the at least one previously existing keyword in the search bar without launching search.

1. A computer implemented method for composing a target keyphrase to be searched, wherein the target keyphrase comprises a plurality of keywords, the computer implemented method comprising: receiving, in a search bar, one or more textual characters following at least one previously existing keyword; providing a plurality of keyword results associated only with the one or more textual characters irrespective of the at least one previously existing keyword; receiving a selection input for selecting a keyword result from amongst the plurality of keyword results associated only with the one or more textual characters irrespective of the at least one previously existing keyword; and word by word composing the target keyphrase by appending the selected keyword result associated only with the one or more textual characters irrespective of the at least one previously existing keyword to the at least one previously existing keyword in the search bar without launching search. 5. The computer implemented method as claimed in claim 1 , wherein the providing is based on the at least one previously existing keyword.

1. A note management system, the system comprising: a device, comprising a sensor configured to generate a first image comprising a first visual representation of a scene having a plurality of physical notes, each of the physical notes comprising a separate physical object having a general boundary and recognizable content thereon; and a processing unit comprising: a note recognition module configured to receive, from the sensor, first image data associated with the first image and process the first image data, automatically identify one or more marks associated with one or more of the plurality of physical notes in the first image, determine a location associated with the one or more marks, and use the location to control the sensor to generate a second image comprising a second visual representation of the scene, wherein the second image comprises a zoomed-in image of one or more notes of the plurality of physical notes, the note recognition module further configured to determine the general boundary of one of the plurality of physical notes from the visual representation, a note authentication module configured to authenticate the one of the plurality of physical notes, a note extraction module configured to extract, in response to determining that the one of the plurality of physical notes is authenticated, the recognizable content of the one of the plurality of physical notes from the visual representation based on the determined general boundary of the one of the plurality of physical notes, and a note labeling module configured to label a digital note representing the one of the plurality of physical notes with a category.

1. A note management system, the system comprising: a device, comprising a sensor configured to generate a first image comprising a first visual representation of a scene having a plurality of physical notes, each of the physical notes comprising a separate physical object having a general boundary and recognizable content thereon; and a processing unit comprising: a note recognition module configured to receive, from the sensor, first image data associated with the first image and process the first image data, automatically identify one or more marks associated with one or more of the plurality of physical notes in the first image, determine a location associated with the one or more marks, and use the location to control the sensor to generate a second image comprising a second visual representation of the scene, wherein the second image comprises a zoomed-in image of one or more notes of the plurality of physical notes, the note recognition module further configured to determine the general boundary of one of the plurality of physical notes from the visual representation, a note authentication module configured to authenticate the one of the plurality of physical notes, a note extraction module configured to extract, in response to determining that the one of the plurality of physical notes is authenticated, the recognizable content of the one of the plurality of physical notes from the visual representation based on the determined general boundary of the one of the plurality of physical notes, and a note labeling module configured to label a digital note representing the one of the plurality of physical notes with a category. 9. The note management system of claim 1 , wherein the note labeling module is configured to label the digital note based on extracted content and historical data.

8. A non-transitory computer readable storage medium storing a computer program having a set of instructions which, when executed by a computer apparatus, cause the computer apparatus to perform a method of producing a set of tags for an input audiovisual file, the set of tags indicating values of attributes of an audiovisual work of defined type represented by said audiovisual file, the method comprising the steps of: issuing, to a user, a prompt for manual assignment of tags to said input audiovisual file; inputting, as an initial estimate of the values of the respective attributes of the audiovisual work represented by said audiovisual file, data representative of the tags assigned to said input audiovisual file by the user in response to said prompt; automatically applying a set of one or more correlation functions to the attribute-value estimates of said initial estimate, to produce a set of revised estimates; assigning a respective confidence measure to each attribute value of said revised estimates; and outputting the final result of the applying step as the set of tags for said input audiovisual file; wherein the correlation functions applied in said applying step are functions embodying the correlations holding between known attribute-values of a set of training examples, said training examples being audiovisual works of said defined type corresponding to manually-tagged audiovisual files, and wherein the correlation-function application step is applied iteratively, said correlation functions are applied only to attribute-values estimates associated with a confidence measure whose value exceeds a threshold, and said confidence measure is set to a maximum value for attribute values provided by the user as the initial estimate to ensure that said attribute values provided by the user as the initial estimate are not changed.

8. A non-transitory computer readable storage medium storing a computer program having a set of instructions which, when executed by a computer apparatus, cause the computer apparatus to perform a method of producing a set of tags for an input audiovisual file, the set of tags indicating values of attributes of an audiovisual work of defined type represented by said audiovisual file, the method comprising the steps of: issuing, to a user, a prompt for manual assignment of tags to said input audiovisual file; inputting, as an initial estimate of the values of the respective attributes of the audiovisual work represented by said audiovisual file, data representative of the tags assigned to said input audiovisual file by the user in response to said prompt; automatically applying a set of one or more correlation functions to the attribute-value estimates of said initial estimate, to produce a set of revised estimates; assigning a respective confidence measure to each attribute value of said revised estimates; and outputting the final result of the applying step as the set of tags for said input audiovisual file; wherein the correlation functions applied in said applying step are functions embodying the correlations holding between known attribute-values of a set of training examples, said training examples being audiovisual works of said defined type corresponding to manually-tagged audiovisual files, and wherein the correlation-function application step is applied iteratively, said correlation functions are applied only to attribute-values estimates associated with a confidence measure whose value exceeds a threshold, and said confidence measure is set to a maximum value for attribute values provided by the user as the initial estimate to ensure that said attribute values provided by the user as the initial estimate are not changed. 12. The computer readable medium according to claim 8 , wherein said prompt-issuing step employs a user interface adapted to prompt said user to input tags for an audiovisual file and said user interface is adapted to indicate to the user which kind of tags should be input.

10. The system according to claim 9 further comprising a maintenance processor, coupled to the first term repository, for initiating an update of said second term repository.

10. The system according to claim 9 further comprising a maintenance processor, coupled to the first term repository, for initiating an update of said second term repository. 12. The system according to claim 10 wherein the update is initiated automatically in response to satisfaction of a predetermined criterion.

2. The method of claim 1 , wherein the event alert is issued by a calendar application, and the context data is a text string associated with a previously created calendar event stored by the calendar application.

2. The method of claim 1 , wherein the event alert is issued by a calendar application, and the context data is a text string associated with a previously created calendar event stored by the calendar application. 3. The method of claim 2 , wherein the context data includes a name of a person associated with the calendar event.

46. The method recited in claim 45 wherein the step of determining changes in the color signal includes the step of comparing a function of the color signal with the average of the color signal and determining the time intervals when the function of the color signal exceeds the average of the color signal and the time intervals when the function of the color signal is less than the average of the color signal to extract the feature string.

46. The method recited in claim 45 wherein the step of determining changes in the color signal includes the step of comparing a function of the color signal with the average of the color signal and determining the time intervals when the function of the color signal exceeds the average of the color signal and the time intervals when the function of the color signal is less than the average of the color signal to extract the feature string. 47. The method recited in claim 46 wherein the function of the color signal and the average of the color signal is determined for only a single line of the frame.

1. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: use a model to represent a system of annotators of a Question and Answer (QA) system pipeline, wherein the model represents each annotator in the system of annotators as a node having one or more performance parameters for indicating a performance of an execution of an annotator corresponding to the node, wherein each annotator in the system of annotators is a program that takes a portion of unstructured input text, extracts structured information from the portion of the unstructured input text, and generates annotations or metadata that are attached by the annotator to a source of the unstructured input text, wherein, for each node in the model, the one or more performance parameters corresponding to the node comprise an arrival rate parameter and a service rate parameter of the annotator associated with the node, wherein the arrival rate parameter indicates a number of jobs arriving in the node per second, and wherein the service rate parameter indicates a number of jobs being serviced by the node per second; determine, for each annotator in a set of annotators of the system of annotators, an effective response time for the annotator based on the one or more performance parameters; calculate a pre-execution start interval for a first annotator based on an effective response time of a second annotator, wherein execution of the first annotator is sequentially after execution of the second annotator; and schedule execution of pre-execution operations associated with the first annotator based on the calculated pre-execution start interval for the first annotator.

1. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: use a model to represent a system of annotators of a Question and Answer (QA) system pipeline, wherein the model represents each annotator in the system of annotators as a node having one or more performance parameters for indicating a performance of an execution of an annotator corresponding to the node, wherein each annotator in the system of annotators is a program that takes a portion of unstructured input text, extracts structured information from the portion of the unstructured input text, and generates annotations or metadata that are attached by the annotator to a source of the unstructured input text, wherein, for each node in the model, the one or more performance parameters corresponding to the node comprise an arrival rate parameter and a service rate parameter of the annotator associated with the node, wherein the arrival rate parameter indicates a number of jobs arriving in the node per second, and wherein the service rate parameter indicates a number of jobs being serviced by the node per second; determine, for each annotator in a set of annotators of the system of annotators, an effective response time for the annotator based on the one or more performance parameters; calculate a pre-execution start interval for a first annotator based on an effective response time of a second annotator, wherein execution of the first annotator is sequentially after execution of the second annotator; and schedule execution of pre-execution operations associated with the first annotator based on the calculated pre-execution start interval for the first annotator. 6. The computer program product of claim 1 , wherein the scheduling generates a scheduling data structure, and wherein the computer readable program further causes the computing device to: receive a job for processing by the QA system pipeline; select a set of annotators in the system of annotators to execute the job, the set of annotators comprising the first annotator and the second annotator; schedule the set of annotators, including the pre-execution operation of the first annotator, based on the scheduling data structure; and process the job based on the scheduling of the set of annotators.

1. In a computer system for executing a program comprising a plurality of methods compiled into bytecode for interpretation at runtime by a runtime interpreter, a method for improving runtime execution of said program comprising: creating a compiled code slot in memory which is associated with a particular method, said compiled code slot for storing a pointer to a memory address; initializing the compiled code slot to store a pointer to a handler, said handler for invoking compilation of said particular method; upon first invocation of the particular method, invoking said handler for performing substeps comprising: (i) compiling said particular method into a compiled method comprising native machine code for a target microprocessor, including mapping bytecode for a method being called into native machine code for execution by a target microprocessor, (ii) storing in the compiled code slot a pointer to said compiled method, including generating a machine code call instruction for transferring execution of the program to said compiled method that is located at a memory address pointed to by the pointer stored in said compiled code slot, so that the particular method can be accessed by a method which is itself compiled into native machine code for the target microprocessor, and (iii) executing said particular method by executing the compiled method comprising native machine code for the target microprocessor; and upon subsequent invocation of the particular method by a method which is itself compiled into native machine code for the target microprocessor, executing said particular method by executing the compiled method which is pointed to by the pointer stored in the compiled code slot for said particular method.

1. In a computer system for executing a program comprising a plurality of methods compiled into bytecode for interpretation at runtime by a runtime interpreter, a method for improving runtime execution of said program comprising: creating a compiled code slot in memory which is associated with a particular method, said compiled code slot for storing a pointer to a memory address; initializing the compiled code slot to store a pointer to a handler, said handler for invoking compilation of said particular method; upon first invocation of the particular method, invoking said handler for performing substeps comprising: (i) compiling said particular method into a compiled method comprising native machine code for a target microprocessor, including mapping bytecode for a method being called into native machine code for execution by a target microprocessor, (ii) storing in the compiled code slot a pointer to said compiled method, including generating a machine code call instruction for transferring execution of the program to said compiled method that is located at a memory address pointed to by the pointer stored in said compiled code slot, so that the particular method can be accessed by a method which is itself compiled into native machine code for the target microprocessor, and (iii) executing said particular method by executing the compiled method comprising native machine code for the target microprocessor; and upon subsequent invocation of the particular method by a method which is itself compiled into native machine code for the target microprocessor, executing said particular method by executing the compiled method which is pointed to by the pointer stored in the compiled code slot for said particular method. 10. The method of claim 1, wherein compiling said particular method comprises: allocating a memory block and compiling said particular method as a true compiled method stored at said memory block.

1. A method of sequence recognition, comprising the steps of: receiving an input sequence; converting the input sequence to an input sequence SSM Sequence Model (SSM) Matrix; comparing the input sequence SSM Matrix to a plurality of known SSM Matrices representing a plurality of known sequences; matching the input sequence to the known sequence based on the step of comparing.

1. A method of sequence recognition, comprising the steps of: receiving an input sequence; converting the input sequence to an input sequence SSM Sequence Model (SSM) Matrix; comparing the input sequence SSM Matrix to a plurality of known SSM Matrices representing a plurality of known sequences; matching the input sequence to the known sequence based on the step of comparing. 5. The method of claim 1 , wherein the step of comparing comprises the step of calculating a distance between the input sequence SSM Matrix and each of the known SSM Matrices, and wherein the step of matching comprises the step of selecting at least one known sequence corresponding to the known SSM Matrix having the smallest distance from the step of calculating.

12. The terminal according to claim 11 , wherein the computer processor is further configured to execute the instructions to: obtain a preset audio stream training sample; and establish the original voiceprint feature model according to the preset audio stream training sample.

12. The terminal according to claim 11 , wherein the computer processor is further configured to execute the instructions to: obtain a preset audio stream training sample; and establish the original voiceprint feature model according to the preset audio stream training sample. 18. The terminal according to claim 12 , wherein the computer processor is further configured to execute the instructions to: obtain a matching degree between the audio stream of each speaker of the at least one speaker and the original voiceprint feature model according to the audio stream of each speaker of the at least one speaker and the original voiceprint feature model; and select an audio stream corresponding to a matching degree that is the highest and is greater than a preset matching threshold as the successfully matched audio stream.

12. A non-transitory computer-readable storage medium including instructions that, when executed by a processor, cause the processor to perform the steps of: receiving via a first namespace a source language text string from an application, wherein the first namespace is associated with a first subset of a set of target languages; determining that a translated text string that includes a translation in a first target language of the source language text string is not available for use by the application, wherein the first target language is included in the set of target languages but not included in the first subset; transmitting the source language text string to a translation service for translation; receiving the translated text string from the translation service; merging the translated text string into a second namespace, wherein the second namespace is associated with the set of target languages; and causing the translated text string to be available for use by the application via the second namespace.

12. A non-transitory computer-readable storage medium including instructions that, when executed by a processor, cause the processor to perform the steps of: receiving via a first namespace a source language text string from an application, wherein the first namespace is associated with a first subset of a set of target languages; determining that a translated text string that includes a translation in a first target language of the source language text string is not available for use by the application, wherein the first target language is included in the set of target languages but not included in the first subset; transmitting the source language text string to a translation service for translation; receiving the translated text string from the translation service; merging the translated text string into a second namespace, wherein the second namespace is associated with the set of target languages; and causing the translated text string to be available for use by the application via the second namespace. 18. The non-transitory computer-readable storage medium of claim 12 , wherein determining that the translated text string is not available for use by the application comprises receiving the source language text string as part of a request to translate the source language text string into the first target language.

14. A tangible non-transitory machine-readable medium that provides executable instructions, which, when executed by a computing system, cause the computing system to perform a method comprising: receiving invoice adjustment information in a first application-specific data object format from a first processing system of a plurality of processing systems, wherein each processing system of the plurality of processing systems comprises an application, and wherein the invoice adjustment information is received at a communications transport layer; receiving, at the communications transport layer, configuration information relating to the processing systems, wherein the configuration information is configured to be received via a communications protocol adapter; and translating the invoice adjustment information into a common invoice adjustment data object format, wherein the translating comprises accessing a first storing unit configured to store transformation information, accessing a second storing unit, wherein the second storing unit stores at least one business process, and executing the business process in response to a predefined event, and the common invoice adjustment data object format comprises at least one relationship data element, wherein the relationship data element specifies at least one relationship between a plurality of entities, the relationship data element comprises a plurality of elements, a first element of the plurality of elements corresponds to a first entity of the plurality of entities, a second element of the plurality of elements corresponds to a second entity of the plurality of entities, at least one custom data element, wherein the custom data element facilitates customization of the common invoice adjustment data object format, an identification data element, an invoice adjustment base data element, a billing data element, a status data element, and a list of invoice adjustment line item details data element.

14. A tangible non-transitory machine-readable medium that provides executable instructions, which, when executed by a computing system, cause the computing system to perform a method comprising: receiving invoice adjustment information in a first application-specific data object format from a first processing system of a plurality of processing systems, wherein each processing system of the plurality of processing systems comprises an application, and wherein the invoice adjustment information is received at a communications transport layer; receiving, at the communications transport layer, configuration information relating to the processing systems, wherein the configuration information is configured to be received via a communications protocol adapter; and translating the invoice adjustment information into a common invoice adjustment data object format, wherein the translating comprises accessing a first storing unit configured to store transformation information, accessing a second storing unit, wherein the second storing unit stores at least one business process, and executing the business process in response to a predefined event, and the common invoice adjustment data object format comprises at least one relationship data element, wherein the relationship data element specifies at least one relationship between a plurality of entities, the relationship data element comprises a plurality of elements, a first element of the plurality of elements corresponds to a first entity of the plurality of entities, a second element of the plurality of elements corresponds to a second entity of the plurality of entities, at least one custom data element, wherein the custom data element facilitates customization of the common invoice adjustment data object format, an identification data element, an invoice adjustment base data element, a billing data element, a status data element, and a list of invoice adjustment line item details data element. 15. The tangible non-transitory machine-readable medium of claim 14 wherein the method further comprises: inter-exchanging invoice adjustment information in the common invoice adjustment data object format between two or more of the plurality of processing systems.

19. The method of decoding according to any one of claims 12 to 15 , wherein in order to debinarize at least one syntactic element, depending on values of the already decoded bits of the syntactic element, two or more independent methods of debinarization are used; at least two context elements are calculated with the use of binarized values obtained by various methods of binarization; and/or at least one context element is calculated by a current ordinal number of the decoded bit in a binarized string from which the current syntactic element is debinarized.

19. The method of decoding according to any one of claims 12 to 15 , wherein in order to debinarize at least one syntactic element, depending on values of the already decoded bits of the syntactic element, two or more independent methods of debinarization are used; at least two context elements are calculated with the use of binarized values obtained by various methods of binarization; and/or at least one context element is calculated by a current ordinal number of the decoded bit in a binarized string from which the current syntactic element is debinarized. 22. The method of decoding according to any claim 19 , wherein in order to debinarize and decode values of the syntactic elements with a sign, decoding of a zero attribute by the unary method, or decoding of a sign attribute by the unary method, or decoding of an absolute value of the syntactic element by the unary method or the Huffman method is used, provided that said value is not equal to zero and does not exceed, in absolute value, a predefined value; or decoding of absolute values which are greater than a predefined value by the Elias gamma code method or the Golomb exponential code method is used, and a change of the sign of the decoded value in accordance with the decoded sign attribute is used to restore the sign of the current syntactic element being not equal to zero.

8. A method for delivering author specific content, comprising: crawling open content across the multiple online resources; identifying content in any of the multiple online resources that appears to have been generated by a specific identified author; determining whether the content is from an online resource that is trusted, based on a trust policy; authenticating that the author who allegedly generated the content is the author of the content if the online resource is not trusted under the trust policy; delivering to a subscribing user, via an activity stream, an indication of the content identified as being by the specific identified author from the multiple online resources; and storing an author database that stores an identification of a first author along with a string provided by a content site having content generated by the first author, the string identifying a key that encrypts the first author's identification and the Universal Resource Locator (URL) of the content site.

8. A method for delivering author specific content, comprising: crawling open content across the multiple online resources; identifying content in any of the multiple online resources that appears to have been generated by a specific identified author; determining whether the content is from an online resource that is trusted, based on a trust policy; authenticating that the author who allegedly generated the content is the author of the content if the online resource is not trusted under the trust policy; delivering to a subscribing user, via an activity stream, an indication of the content identified as being by the specific identified author from the multiple online resources; and storing an author database that stores an identification of a first author along with a string provided by a content site having content generated by the first author, the string identifying a key that encrypts the first author's identification and the Universal Resource Locator (URL) of the content site. 12. The method of claim 8 , wherein authenticating that the apparent author is the author of the content includes using a digital signature to authenticate the content as being generated by the specific identified author.

10. One or more non-transitory computer-readable media storing executable instructions that, when executed by a processor, cause a device to: receive a sequence of speech features that characterize an unknown speech input, the sequence of speech features including speech portions and non-speech portions; determine, using voice activity detection (VAD), the speech portions of the sequence of speech features; determine a mean C 0 value for the sequence of speech features, wherein C 0 comprises an average log-energy of a given speech frame of the sequence of speech features, normalize selected speech features of the sequence of speech features using a plurality of different feature normalizing functions including a first function used only for the speech portions and a second function used only for the non-speech portions, wherein the first function normalizes the C 0 by subtracting a max C 0 that is estimated at a start of an utterance including the given speech frame and subsequently updated throughout the utterance; and combine the normalized selected speech features to produce a sequence of mixed normalized speech features for automatic speech recognition of the speech portions of the sequence of speech features.

10. One or more non-transitory computer-readable media storing executable instructions that, when executed by a processor, cause a device to: receive a sequence of speech features that characterize an unknown speech input, the sequence of speech features including speech portions and non-speech portions; determine, using voice activity detection (VAD), the speech portions of the sequence of speech features; determine a mean C 0 value for the sequence of speech features, wherein C 0 comprises an average log-energy of a given speech frame of the sequence of speech features, normalize selected speech features of the sequence of speech features using a plurality of different feature normalizing functions including a first function used only for the speech portions and a second function used only for the non-speech portions, wherein the first function normalizes the C 0 by subtracting a max C 0 that is estimated at a start of an utterance including the given speech frame and subsequently updated throughout the utterance; and combine the normalized selected speech features to produce a sequence of mixed normalized speech features for automatic speech recognition of the speech portions of the sequence of speech features. 14. The non-transitory computer-readable media of claim 10 , wherein at least one feature normalizing function of the plurality of different feature normalizing functions is a maximum normalizing function.

8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprise a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query.

8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprise a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query. 15. The system of claim 8 , wherein the elements of data for the rich result comprise a snippet of the book or a summary of the book.

15. The computer program product of claim 12 , where the computer readable program code when executed on the computer further causes the computer to: determine that at least one of the encoded text string representations of the received source code exists as the stored source code fragment in the repository based upon identification of a matching pattern of an encoded text string representation of a stored source code fragment in the repository; and where, in causing the computer to output the indication, in response to the real-time comparison, of each portion of the received source code determined to already exist as the stored source code fragment in the repository, the computer readable program code when executed on the computer causes the computer to: highlight, within a software developer kit (SDK) as a potential area of code re-use, each portion of the received source code indicated to already exist as the stored source code fragment in the repository based upon the indication of the matching pattern.

15. The computer program product of claim 12 , where the computer readable program code when executed on the computer further causes the computer to: determine that at least one of the encoded text string representations of the received source code exists as the stored source code fragment in the repository based upon identification of a matching pattern of an encoded text string representation of a stored source code fragment in the repository; and where, in causing the computer to output the indication, in response to the real-time comparison, of each portion of the received source code determined to already exist as the stored source code fragment in the repository, the computer readable program code when executed on the computer causes the computer to: highlight, within a software developer kit (SDK) as a potential area of code re-use, each portion of the received source code indicated to already exist as the stored source code fragment in the repository based upon the indication of the matching pattern. 17. The computer program product of claim 15 , where the computer readable program code when executed on the computer further causes the computer to: prompt a user within the SDK to allow the user to import the stored source code fragment indicated to already exist in the repository; import the stored source code fragment indicated to already exist in the repository in response to a user indication to import the stored source code fragment; and replace at least one portion of the received source code with the imported source code fragment.

12. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining an input image; processing the input image using a deep convolutional neural network to generate an alternative representation for the input image, wherein: (i) the deep convolutional neural network includes a plurality of core neural network layers that are each defined by a respective set of parameters having current values that were determined by training a second neural network having the plurality of core neural network layers on a plurality of training images, and (ii) the second neural network was trained in part by processing, with an output layer of the second neural network and for each training image, an output of a last core neural network layer of the plurality of core neural network layers to generate, for each of a plurality of object categories, a respective score that represents a predicted likelihood that the training image contains an image of an object from the object category; and processing the alternative representation for the input image using a third neural network to generate a sequence of a plurality of words in a target natural language that describes the input image.

12. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining an input image; processing the input image using a deep convolutional neural network to generate an alternative representation for the input image, wherein: (i) the deep convolutional neural network includes a plurality of core neural network layers that are each defined by a respective set of parameters having current values that were determined by training a second neural network having the plurality of core neural network layers on a plurality of training images, and (ii) the second neural network was trained in part by processing, with an output layer of the second neural network and for each training image, an output of a last core neural network layer of the plurality of core neural network layers to generate, for each of a plurality of object categories, a respective score that represents a predicted likelihood that the training image contains an image of an object from the object category; and processing the alternative representation for the input image using a third neural network to generate a sequence of a plurality of words in a target natural language that describes the input image. 14. The system of claim 12 , wherein the third neural network is a long-short term memory (LSTM) neural network.

10. The apparatus claim 9 , further comprising: means for receiving a user selection of one or more of the plurality of keys; means for determining a text algorithm that has been selected for data entry; and means for outputting one or more characters or words based on the user selection and the text algorithm.

10. The apparatus claim 9 , further comprising: means for receiving a user selection of one or more of the plurality of keys; means for determining a text algorithm that has been selected for data entry; and means for outputting one or more characters or words based on the user selection and the text algorithm. 11. The apparatus of claim 10 , wherein the text algorithm is one of a multi-tap text entry algorithm or a predictive text entry algorithm.

1. A system to facilitate conducting a social choice survey of members of an online community associated with a computer network, the system comprising: a computer accessible to the computer network, the computer defining a social choice administrator server, the social choice administrator server having a memory coupled to a processor; operational instructions stored in the memory of the social choice administrator server that, when executed by the processor of the social choice administrator server, cause the social choice administrator server to selectively perform the operations of: generate a first user interface on a computer display associated with a survey administrator, prompt the survey administrator with the first user interface to define the social choice survey, receive the social choice survey defined by the survey administrator with the first user interface, prompt the survey administrator with the first user interface to define a group of participants from the members of the online community on a social media website to participate in the social choice survey, receive the group of participants defined by the survey administrator with the first user interface, generate a second user interface on a computer display associated with each of the participants on the social media website the second user interface providing an interactive portion to receive a participant's response to the social choice survey, receive and register each of the participants' responses to the social choice survey collected with the second user interface, prompt the survey administrator to view and to select a progress of the social choice survey, in response to the selection of the progress of the social choice survey, generate a display of the progress of the social choice survey on the social media website that includes at least one of a list of participants who have participated in the social choice survey and a list of participants who have not participated in the social choice survey, amalgamate the participants' responses to the social choice survey to thereby determine a result of the social choice survey, and show the result of the social choice survey on a computer display of the survey administrator.

1. A system to facilitate conducting a social choice survey of members of an online community associated with a computer network, the system comprising: a computer accessible to the computer network, the computer defining a social choice administrator server, the social choice administrator server having a memory coupled to a processor; operational instructions stored in the memory of the social choice administrator server that, when executed by the processor of the social choice administrator server, cause the social choice administrator server to selectively perform the operations of: generate a first user interface on a computer display associated with a survey administrator, prompt the survey administrator with the first user interface to define the social choice survey, receive the social choice survey defined by the survey administrator with the first user interface, prompt the survey administrator with the first user interface to define a group of participants from the members of the online community on a social media website to participate in the social choice survey, receive the group of participants defined by the survey administrator with the first user interface, generate a second user interface on a computer display associated with each of the participants on the social media website the second user interface providing an interactive portion to receive a participant's response to the social choice survey, receive and register each of the participants' responses to the social choice survey collected with the second user interface, prompt the survey administrator to view and to select a progress of the social choice survey, in response to the selection of the progress of the social choice survey, generate a display of the progress of the social choice survey on the social media website that includes at least one of a list of participants who have participated in the social choice survey and a list of participants who have not participated in the social choice survey, amalgamate the participants' responses to the social choice survey to thereby determine a result of the social choice survey, and show the result of the social choice survey on a computer display of the survey administrator. 7. The system of claim 1 , wherein the interactive portion of the second user interface comprises virtual buttons.

10. A system for converting and transmitting audio information, comprising: an audio input receiving unit that receives spoken audio input; a first conversion unit that converts the received spoken audio input into audio digital data that is representative of the received spoken audio input; an audio digital data packet generation unit that generates a stream of audio digital data packets that contain the audio digital data; a textual representation conversion unit that generates a textual representation of the received spoken audio input; a textual digital data packet generation unit that generates a stream of textual digital data packets that contain the generated textual representation of the received spoken audio input; and a transmission unit that transmits the stream of audio digital data packets and the stream of textual digital data packets to a destination device; wherein at least one of the audio digital data packets and/or the textual digital data packets include information that indicates which audio digital data packets and digital data packets contain data relating to the same portions of the received spoken audio input.

10. A system for converting and transmitting audio information, comprising: an audio input receiving unit that receives spoken audio input; a first conversion unit that converts the received spoken audio input into audio digital data that is representative of the received spoken audio input; an audio digital data packet generation unit that generates a stream of audio digital data packets that contain the audio digital data; a textual representation conversion unit that generates a textual representation of the received spoken audio input; a textual digital data packet generation unit that generates a stream of textual digital data packets that contain the generated textual representation of the received spoken audio input; and a transmission unit that transmits the stream of audio digital data packets and the stream of textual digital data packets to a destination device; wherein at least one of the audio digital data packets and/or the textual digital data packets include information that indicates which audio digital data packets and digital data packets contain data relating to the same portions of the received spoken audio input. 14. The system of claim 10 , wherein first conversion unit uses a CODEC to convert the received spoken audio input into audio digital data.

32. A method to enable improved analysis and use of sociological data, the method of comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; depicting communications between a plurality of actors using communication lines between the actors; and enabling graphical queries based on selecting the communication lines between actors.

32. A method to enable improved analysis and use of sociological data, the method of comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; depicting communications between a plurality of actors using communication lines between the actors; and enabling graphical queries based on selecting the communication lines between actors. 35. The method of claim 32 , further comprising: enabling a user to access documents associated with a communication line via the communications graph.

26. A computer program product comprising computer-executable instructions tangibly stored on a computer-readable medium, the instructions comprising: instructions to: identify a document including a first coding having a first feature encoding a first concept, the first coding being associated with a first code and first data; render the first data to have a visual characteristic that is based on the first feature, without rendering the first code; receive a first indication from a user of whether the rendering is accurate; and identify, based on the first indication received from the user, a verification status of the first coding, wherein the verification status of the first coding indicates whether the first data represents the first concept, the instructions to identify comprising instructions to: identify a verification status of the first coding indicating that the first coding is accurate if the first indication indicates that the rendering is accurate; and identify a verification status of the first coding indicating that the first coding is inaccurate otherwise; and modify the first feature of the first coding if the verification status of the first coding indicates that the first coding is inaccurate.

26. A computer program product comprising computer-executable instructions tangibly stored on a computer-readable medium, the instructions comprising: instructions to: identify a document including a first coding having a first feature encoding a first concept, the first coding being associated with a first code and first data; render the first data to have a visual characteristic that is based on the first feature, without rendering the first code; receive a first indication from a user of whether the rendering is accurate; and identify, based on the first indication received from the user, a verification status of the first coding, wherein the verification status of the first coding indicates whether the first data represents the first concept, the instructions to identify comprising instructions to: identify a verification status of the first coding indicating that the first coding is accurate if the first indication indicates that the rendering is accurate; and identify a verification status of the first coding indicating that the first coding is inaccurate otherwise; and modify the first feature of the first coding if the verification status of the first coding indicates that the first coding is inaccurate. 29. The computer program product of claim 26 , wherein the computer-executable instructions further comprise instructions to: store, in the document, a record of the verification status of the first coding.

3. The system of claim 1 , further comprising: a deployable agent, deployable by the server, comprising a data source configured to provide a pipeline for data to travel; and a runtime object configured to receive and process data that travels through the pipeline, wherein the data is text-based data.

3. The system of claim 1 , further comprising: a deployable agent, deployable by the server, comprising a data source configured to provide a pipeline for data to travel; and a runtime object configured to receive and process data that travels through the pipeline, wherein the data is text-based data. 4. The system of claim 3 , wherein the deployable agent is an active agent configured to interact with a data origination entity.

19. The system of claim 18 , wherein the overall score for a selected n-gram, of the one or more n-grams, is based on a combination of: a frequency score indicating a frequency the selected n-gram appears in the low scoring content items, the user score corresponding to the low scoring content items the selected n-gram appears in, and a confidence factor for the selected n-gram.

19. The system of claim 18 , wherein the overall score for a selected n-gram, of the one or more n-grams, is based on a combination of: a frequency score indicating a frequency the selected n-gram appears in the low scoring content items, the user score corresponding to the low scoring content items the selected n-gram appears in, and a confidence factor for the selected n-gram. 20. The system of claim 19 , wherein the confidence factor for the selected n-gram is based on one or more of: a determination of how well the selected n-gram conforms to an identified set of grammatical rules; how rare portions of the selected n-gram are in an identified language corpus; how users of a social media system have reacted to or interacted with one or more of the content items the selected n-gram was taken from; or any combination thereof.

50. The method of claim 49 , wherein the method further comprises: responsive to the closing, deleting from the data structure the respective one of the first and second grammars.

50. The method of claim 49 , wherein the method further comprises: responsive to the closing, deleting from the data structure the respective one of the first and second grammars. 51. The method of claim 50 , wherein the data displayed in the determined one of the first and second display windows is a subset of data received in response to a request for a third web page, the request transmitted in response to the voice command, and the data received in response to the data request includes a third grammar, the method further comprising: updating the data structure to include a reference to the third grammar in association with the determined one of the first and second display windows.

9. A computer-implemented method comprising: transmitting, by a computing device to a server system, a search query that includes multiple search query terms; receiving, by the computing device from the server system, a list of search results that identify a plurality of documents that the server system determined are relevant to the search query terms; receiving, by the computing device, first user input selecting a first search result from the list of search results, the selection of the first search result including a selection of a link that is associated with a first document rather than a sub-page of the first document; transmitting, by the computing device to the server system, an indication of the first search result as having been selected by a user of the computing device, so as to cause the server system to: divide the first document from the plurality of documents that corresponds to the first search result into multiple sub-pages, determine a score for each of the multiple sub-pages based at least on presence of the search query terms in the sub-pages, identify a first sub-page that is determined to be most relevant to the search query from among the sub-pages based on the scores for the sub-pages, and identify a second sub-page that is determined to be next most relevant to the search query from among the sub-pages based on the scores for the sub-pages; presenting, by the computing device to a user of the computing device, the first sub-page; displaying by the computing device as part of the first sub-page a control for replacing the display of the first sub-page with a display of the second sub-page upon user selection of the control; receiving, by the computing device, second user input that requests navigation from the first sub-page to the next most relevant sub-page, wherein user selection of the control causes the received second user input; and presenting, by the computing device to a user of the computing device in response to receiving the second user input, the second sub-page.

9. A computer-implemented method comprising: transmitting, by a computing device to a server system, a search query that includes multiple search query terms; receiving, by the computing device from the server system, a list of search results that identify a plurality of documents that the server system determined are relevant to the search query terms; receiving, by the computing device, first user input selecting a first search result from the list of search results, the selection of the first search result including a selection of a link that is associated with a first document rather than a sub-page of the first document; transmitting, by the computing device to the server system, an indication of the first search result as having been selected by a user of the computing device, so as to cause the server system to: divide the first document from the plurality of documents that corresponds to the first search result into multiple sub-pages, determine a score for each of the multiple sub-pages based at least on presence of the search query terms in the sub-pages, identify a first sub-page that is determined to be most relevant to the search query from among the sub-pages based on the scores for the sub-pages, and identify a second sub-page that is determined to be next most relevant to the search query from among the sub-pages based on the scores for the sub-pages; presenting, by the computing device to a user of the computing device, the first sub-page; displaying by the computing device as part of the first sub-page a control for replacing the display of the first sub-page with a display of the second sub-page upon user selection of the control; receiving, by the computing device, second user input that requests navigation from the first sub-page to the next most relevant sub-page, wherein user selection of the control causes the received second user input; and presenting, by the computing device to a user of the computing device in response to receiving the second user input, the second sub-page. 12. The computer-implemented method of claim 9 , wherein determining the score for each of the multiple sub-pages includes: determining that a first search query term of the search query terms is located in a predetermined location in the first document, and causing presence of the first search query term in the sub-pages to less-significantly influence the scores that are determined for the sub-pages than presence in the sub-pages of other of the search query terms that are not located in the predetermined location in the first document.

3. The method of claim 1 , wherein the unique industrial sector of each dataset was collected using a corresponding industry specific spoken dialog system of the plurality of industry specific spoken dialog systems.

3. The method of claim 1 , wherein the unique industrial sector of each dataset was collected using a corresponding industry specific spoken dialog system of the plurality of industry specific spoken dialog systems. 4. The method of claim 3 , wherein the corresponding industry specific spoken dialog system and the unique industrial sector share a common task domain.

17. One or more computing devices according to claim 16 , wherein the selecting further comprises: determining that the given resource text string is related to the set of the historical resource text strings; and selecting one or more of the historical resource text strings in the set based on the scores.

17. One or more computing devices according to claim 16 , wherein the selecting further comprises: determining that the given resource text string is related to the set of the historical resource text strings; and selecting one or more of the historical resource text strings in the set based on the scores. 18. One or more computing devices according to claim 17 , the process further comprising applying a topic model to generate sets of topically related sets of the historical resource strings, the sets including the set.

7. A non-transitory machine-readable medium storing instructions executed by a processing resource to: receive a document having data descriptive of components of an event associated with an insurance claim; construct, responsive to receiving the data, a hierarchical data structure based on the received data, wherein a first portion of the hierarchical data structure comprises a number of automatically populated structural elements common to all insurance events, and a second portion of the hierarchical data structure comprises a number of automatically populated structural elements corresponding the components of the event described by the data; associate portions of the data with particular structural elements of the number of automatically populated structural elements corresponding to the components of the event described by the data; and create an electronic file folder hierarchy that corresponds to the structural elements populating the hierarchical data structure.

7. A non-transitory machine-readable medium storing instructions executed by a processing resource to: receive a document having data descriptive of components of an event associated with an insurance claim; construct, responsive to receiving the data, a hierarchical data structure based on the received data, wherein a first portion of the hierarchical data structure comprises a number of automatically populated structural elements common to all insurance events, and a second portion of the hierarchical data structure comprises a number of automatically populated structural elements corresponding the components of the event described by the data; associate portions of the data with particular structural elements of the number of automatically populated structural elements corresponding to the components of the event described by the data; and create an electronic file folder hierarchy that corresponds to the structural elements populating the hierarchical data structure. 12. The medium of claim 7 , further comprising instructions executed by the processing resource to: receive data descriptive of an additional component of the event, the additional component being different from a plurality of previously received components of the event; add at least one structural element to the hierarchical data structure responsive to receiving the data descriptive of the additional component; and add at least one electronic file folder to the electronic file folder hierarchy, each of the at least one added electronic file folder corresponding to an added structural element.

10. The computer-implemented method of claim 9 , further comprising assessing which query plan of the plurality of query plans answers the query in a least amount of time.

10. The computer-implemented method of claim 9 , further comprising assessing which query plan of the plurality of query plans answers the query in a least amount of time. 11. The computer-implemented method of claim 10 , wherein the assessing includes using cost-based optimization to determine a most efficient query plan.

13. A computer-implemented method comprising: determining, at a language layer of a query language architecture, a query syntax of a received query and a definition of a result set for the query; checking, at a compiler layer of the query language architecture, semantics of the received query, the compiler layer supporting a single data model usable on multiple application layers of a multi-layer business software architecture; reading, from a data dictionary in a persistent layer of a database from which query results are to be returned, a field expression corresponding to the result set; building, by the compiler layer, the field expression into a query statement; executing, at a runtime layer of the query language architecture, the query including the query statement; and returning results to the query per the result set based on execution of the query on the database.

13. A computer-implemented method comprising: determining, at a language layer of a query language architecture, a query syntax of a received query and a definition of a result set for the query; checking, at a compiler layer of the query language architecture, semantics of the received query, the compiler layer supporting a single data model usable on multiple application layers of a multi-layer business software architecture; reading, from a data dictionary in a persistent layer of a database from which query results are to be returned, a field expression corresponding to the result set; building, by the compiler layer, the field expression into a query statement; executing, at a runtime layer of the query language architecture, the query including the query statement; and returning results to the query per the result set based on execution of the query on the database. 14. A computer-implemented method as in claim 13 , wherein the query language architecture is implemented in a business software programming language as part of a business software architecture.

1. A method of automatic speech recognition to convert speech signal into text using one or more processors comprising: A) segmenting the speech signal into pitch-synchronous frames, wherein for voiced sections each said frame is a single pitch period; B) for each frame, equalizing the two ends of the waveform using an ends-matching program; C) generating an amplitude spectrum of each said frame using Fourier analysis; D) transforming each said amplitude spectrum into a timbre vector using Laguerre functions; E) performing acoustic decoding to find a list of most likely phonemes or sub-phoneme units for each said timbre vector by comparing with a timbre vector database; F) decoding the sequence of the list of the most likely phonemes or sub-phoneme units using a language-model database to find out the most likely text; wherein the segmenting of the speech-signal is based on an analysis of the speech signals using an asymmetric window which includes: a) conducting, for a speaker, a test to find the best size of the asymmetric window; b) convoluting the speech-signal with the said asymmetric window to form a profile function; c) picking up the maxima in the said profile function as segmentation points; d) extending the segmentation points to unvoiced sections.

1. A method of automatic speech recognition to convert speech signal into text using one or more processors comprising: A) segmenting the speech signal into pitch-synchronous frames, wherein for voiced sections each said frame is a single pitch period; B) for each frame, equalizing the two ends of the waveform using an ends-matching program; C) generating an amplitude spectrum of each said frame using Fourier analysis; D) transforming each said amplitude spectrum into a timbre vector using Laguerre functions; E) performing acoustic decoding to find a list of most likely phonemes or sub-phoneme units for each said timbre vector by comparing with a timbre vector database; F) decoding the sequence of the list of the most likely phonemes or sub-phoneme units using a language-model database to find out the most likely text; wherein the segmenting of the speech-signal is based on an analysis of the speech signals using an asymmetric window which includes: a) conducting, for a speaker, a test to find the best size of the asymmetric window; b) convoluting the speech-signal with the said asymmetric window to form a profile function; c) picking up the maxima in the said profile function as segmentation points; d) extending the segmentation points to unvoiced sections. 4. The method in claim 1 , wherein the acoustic decoding comprises distinguishing different unvoiced consonants by computing a timbre distance between each said timbre vector and the timbre vectors of different unvoiced consonants in the timbre vector database.

1. A method for creating a stored query for remotely accessing information comprising: receiving, at said computer, a selection of a query type, wherein said query type corresponds to a query template; receiving, at said computer, a query field and query criteria, wherein said query criteria is selected from an input list having a profile and stored at said computer; creating, at said computer, said query field, said query criteria, and said query type into a Structured Query Language (SQL) statement; executing, by said computer, said SQL statement to add said query field and said query criteria to said query template; creating, by said computer, said stored query based on said query template, wherein said stored query is stored in a query database; executing, by said computer, said stored query to create a first file; categorizing, at said computer, said first file such that it is available to a pre-determined group of users; placing, by said computer, said first file in a location accessible to said pre-determined group of users, communicating, by said computer, with an intermediary device, wherein said intermediary device: remotely obtains access data including location information and authentication credentials, wherein said access data is used to locate and at least one of: grant and deny access to said secure system, using a device of one of said pre-determined group of users; transmits said access data to said secure system; receives a validation of said access data from said secure system; and, allows said access to said secure system; and performing, by said computer, an analysis of said query database, wherein said analysis is based on performance data resulting from execution of said stored query on a database, and wherein said analysis determines at least one of: database fields that are queried least often and database fields that are queried most often.

1. A method for creating a stored query for remotely accessing information comprising: receiving, at said computer, a selection of a query type, wherein said query type corresponds to a query template; receiving, at said computer, a query field and query criteria, wherein said query criteria is selected from an input list having a profile and stored at said computer; creating, at said computer, said query field, said query criteria, and said query type into a Structured Query Language (SQL) statement; executing, by said computer, said SQL statement to add said query field and said query criteria to said query template; creating, by said computer, said stored query based on said query template, wherein said stored query is stored in a query database; executing, by said computer, said stored query to create a first file; categorizing, at said computer, said first file such that it is available to a pre-determined group of users; placing, by said computer, said first file in a location accessible to said pre-determined group of users, communicating, by said computer, with an intermediary device, wherein said intermediary device: remotely obtains access data including location information and authentication credentials, wherein said access data is used to locate and at least one of: grant and deny access to said secure system, using a device of one of said pre-determined group of users; transmits said access data to said secure system; receives a validation of said access data from said secure system; and, allows said access to said secure system; and performing, by said computer, an analysis of said query database, wherein said analysis is based on performance data resulting from execution of said stored query on a database, and wherein said analysis determines at least one of: database fields that are queried least often and database fields that are queried most often. 13. The method of claim 1 , wherein access to said first file is based on a type of device.

17. The at least one device of claim 16 , further comprising: instructions for implementing the service on a virtual machine.

17. The at least one device of claim 16 , further comprising: instructions for implementing the service on a virtual machine. 18. The at least one device of claim 17 , wherein the virtual machine is reloaded after every predetermined period of time.

1. A computer-implemented method for determining a decision point in real-time for a data stream from a conversation, the method comprising: receiving, by a computing device, streaming conversational data; and determining, by said computing device, when to classify the streaming conversational data into one of thematic categories and labels from a predefined set, using a measure of certainty, by performing certainty calculations at a plurality of time instances during the conversation and by selecting a decision point in response to the certainty calculations, the decision point being based on accumulated conversational data available at different ones of the plurality of time instances.

1. A computer-implemented method for determining a decision point in real-time for a data stream from a conversation, the method comprising: receiving, by a computing device, streaming conversational data; and determining, by said computing device, when to classify the streaming conversational data into one of thematic categories and labels from a predefined set, using a measure of certainty, by performing certainty calculations at a plurality of time instances during the conversation and by selecting a decision point in response to the certainty calculations, the decision point being based on accumulated conversational data available at different ones of the plurality of time instances. 10. The method in accordance with claim 1 , wherein the conversation is a call center conversation, and wherein the method further comprises taking automated action, by said computing device, at the selected decision point.

3. A method for utterance verification adapted to verify a recognized vocabulary, wherein the recognized vocabulary is obtained by performing speech recognition on a feature vector sequence according to an acoustic model and model vocabulary database, wherein the feature vector sequence comprises feature vectors of a plurality of frames, wherein the acoustic model and model vocabulary database comprises a plurality of model vocabularies, wherein each of the model vocabularies comprises a plurality of states, and wherein the method for utterance verification comprises: calculating an overall maximum reference score according to a log-likelihood score obtained from speech recognition, wherein the log-likelihood score obtained from speech recognition is calculated by taking a logarithm on a value of a probability of one of the feature vectors of the frames conditioned on one of the states of each model vocabulary, and wherein the overall maximum reference score is a summation of the maximum value of log-likelihood scores of the feature vector of each frame conditioned on each state of each of the model vocabularies; calculating a second verification score according to an optimal path score output during the speech recognition and the overall maximum reference score; and comparing the second verification score with a second predetermined threshold value, so as to reject or accept the recognized vocabulary.

3. A method for utterance verification adapted to verify a recognized vocabulary, wherein the recognized vocabulary is obtained by performing speech recognition on a feature vector sequence according to an acoustic model and model vocabulary database, wherein the feature vector sequence comprises feature vectors of a plurality of frames, wherein the acoustic model and model vocabulary database comprises a plurality of model vocabularies, wherein each of the model vocabularies comprises a plurality of states, and wherein the method for utterance verification comprises: calculating an overall maximum reference score according to a log-likelihood score obtained from speech recognition, wherein the log-likelihood score obtained from speech recognition is calculated by taking a logarithm on a value of a probability of one of the feature vectors of the frames conditioned on one of the states of each model vocabulary, and wherein the overall maximum reference score is a summation of the maximum value of log-likelihood scores of the feature vector of each frame conditioned on each state of each of the model vocabularies; calculating a second verification score according to an optimal path score output during the speech recognition and the overall maximum reference score; and comparing the second verification score with a second predetermined threshold value, so as to reject or accept the recognized vocabulary. 5. The method for utterance verification as claimed in claim 3 further comprising: calculating a garbage score according to a garbage model, wherein the garbage score is obtained by taking a logarithm on a value of a probability of one of the feature vectors conditioned on a state of the garbage model; calculating a third verification score according to the optimal path score, the garbage score and the overall maximum reference score; and comparing the third verification score with a third predetermined threshold value, so as to reject or accept the recognized vocabulary.

8. A system for creating a list of trustworthy DNS resolvers comprising: a processing system comprising one or more processors; a communications port for receiving communications from networked devices and for transmitting communications to the networked devices; and a memory storing instructions that, when executed by the processing system, cause the processing system to perform operations comprising: building, at a computer, a resolver profile for a resolver that is operable to send queries to a domain name server, wherein the resolver profile is based on one or more of a top-talker status of the resolver, a normalcy of distribution of domain names queried, or a continuity of distribution of query type, a RD (Recursion Desired bit status, and information related to query traffic at one or more nodes in a distributed domain name server topology; determining that the resolver is trustworthy by applying a policy to the resolver profile; and adding, by the computer, the resolver to a list of trustworthy resolvers based on the determining that the resolver is trustworthy.

8. A system for creating a list of trustworthy DNS resolvers comprising: a processing system comprising one or more processors; a communications port for receiving communications from networked devices and for transmitting communications to the networked devices; and a memory storing instructions that, when executed by the processing system, cause the processing system to perform operations comprising: building, at a computer, a resolver profile for a resolver that is operable to send queries to a domain name server, wherein the resolver profile is based on one or more of a top-talker status of the resolver, a normalcy of distribution of domain names queried, or a continuity of distribution of query type, a RD (Recursion Desired bit status, and information related to query traffic at one or more nodes in a distributed domain name server topology; determining that the resolver is trustworthy by applying a policy to the resolver profile; and adding, by the computer, the resolver to a list of trustworthy resolvers based on the determining that the resolver is trustworthy. 13. The system of claim 8 , wherein: the resolver profile comprises an array including one element for each profile feature; and the elements comprise binary values indicating that profile features are either normal or abnormal.

1. A method of automatically sorting sports related news stories by their temporal characteristics using a computing system comprising: a) identifying a first sporting event; wherein said first sporting event is assigned by the computing system to a plurality of different event status states each representing a different temporal period within a temporal sequence defined for such first sporting event; b) analyzing a first electronic document describing said first sporting event with the computing system to identify first content snippets determinative of a first status state of said sporting event relative to completion and/or resolution; c) analyzing a second electronic document with second content snippets describing a second status state for said first sporting event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status of said sporting event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status; wherein changes in corresponding content snippets relating to completion and/or resolution of such first sporting event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and said second electronic document.

1. A method of automatically sorting sports related news stories by their temporal characteristics using a computing system comprising: a) identifying a first sporting event; wherein said first sporting event is assigned by the computing system to a plurality of different event status states each representing a different temporal period within a temporal sequence defined for such first sporting event; b) analyzing a first electronic document describing said first sporting event with the computing system to identify first content snippets determinative of a first status state of said sporting event relative to completion and/or resolution; c) analyzing a second electronic document with second content snippets describing a second status state for said first sporting event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status of said sporting event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status; wherein changes in corresponding content snippets relating to completion and/or resolution of such first sporting event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and said second electronic document. 10. The method of claim 1 further including a step: verifying said second state for the first sporting event by computing a prevalence rate for content identifying such second state in a set of benchmark sites and confirming said prevalence rate is within a particular range.

40. The non-transitory computer readable memory device of claim 27 , provides, via the network interface and the network, the first query to the at least one social network media data source.

40. The non-transitory computer readable memory device of claim 27 , provides, via the network interface and the network, the first query to the at least one social network media data source. 41. The computer readable memory device of claim 40 , wherein the at least one result includes at least one location of the geographic context region; and wherein the computer system further provides the at least one location of the geographic context region to the user via the map.

12. A system to identify compounding relationships between suggested edits in an electronic document, comprising: a processor; a memory operatively connected to the processor, wherein the memory stores instructions that cause the processor to: receive a set of one or more first edits and a second edit to the electronic document; receive an acceptance of the second edit from an editor of the electronic document; filter the set of one or more first edits to remove deletions in the electronic document and include insertions and modifications in the electronic document, to obtain at least a subset of the one or more first edits; identify a shared position of the subset of one or more first edits and the second edit in the electronic document; determine the subset of one or more first edits and second edit have compounding relationships based at least in part on the identification, by determining that the subset of one or more first edits are required to be accepted in order for the second edit to be accepted; and in response to determining that the subset of one or more first edits and the second have compounding relationships, automatically accept the subset of one or more first edits in response to receiving the acceptance of the second edit.

12. A system to identify compounding relationships between suggested edits in an electronic document, comprising: a processor; a memory operatively connected to the processor, wherein the memory stores instructions that cause the processor to: receive a set of one or more first edits and a second edit to the electronic document; receive an acceptance of the second edit from an editor of the electronic document; filter the set of one or more first edits to remove deletions in the electronic document and include insertions and modifications in the electronic document, to obtain at least a subset of the one or more first edits; identify a shared position of the subset of one or more first edits and the second edit in the electronic document; determine the subset of one or more first edits and second edit have compounding relationships based at least in part on the identification, by determining that the subset of one or more first edits are required to be accepted in order for the second edit to be accepted; and in response to determining that the subset of one or more first edits and the second have compounding relationships, automatically accept the subset of one or more first edits in response to receiving the acceptance of the second edit. 15. The system of claim 12 , further comprising a user interface to display the subset of one or more first edits and second edit and an indicator of the compound relationships to a user of the electronic document.

2. The method of claim 1 wherein the plurality of search results are calculated according to one or more relationships between one or more of the plurality of common attributes shared by the one or more of the plurality of potential search terms and the one or more of the plurality of search terms.

2. The method of claim 1 wherein the plurality of search results are calculated according to one or more relationships between one or more of the plurality of common attributes shared by the one or more of the plurality of potential search terms and the one or more of the plurality of search terms. 3. The method of claim 2 wherein the one or more relationships are established using a cluster analysis.

1. An adaptation method for a speech system of a vehicle, comprising: receiving, by a processor, a first set of speech data recorded during a defined speech window, wherein the defined speech window begins once a system prompt has completed and ends at a predetermined time after the defined speech window begins; receiving, by a processor, a second set of speech data, wherein the second set of speech data comprises data recorded during the defined speech window and at least one of data recorded before the defined speech window and data recorded after the defined speech window; determining, by the processor, a speech pace based on the second set of speech data; determining, by the processor, a user model based on the speech pace; and generating, by the processor, adaptation parameters for processing the first set of speech data by at least one of a speech recognition system and a dialog manager based on the user model.

1. An adaptation method for a speech system of a vehicle, comprising: receiving, by a processor, a first set of speech data recorded during a defined speech window, wherein the defined speech window begins once a system prompt has completed and ends at a predetermined time after the defined speech window begins; receiving, by a processor, a second set of speech data, wherein the second set of speech data comprises data recorded during the defined speech window and at least one of data recorded before the defined speech window and data recorded after the defined speech window; determining, by the processor, a speech pace based on the second set of speech data; determining, by the processor, a user model based on the speech pace; and generating, by the processor, adaptation parameters for processing the first set of speech data by at least one of a speech recognition system and a dialog manager based on the user model. 2. The method of claim 1 , wherein the determining the speech pace comprises dividing the speech data into speech sections and non-speech sections and wherein the determining the speech pace is based on a timing of the speech sections and the non-speech sections.

2. A method in accordance with claim 1 , wherein: the ideal spacing distances and the current spacing distances in the respective template document and user document are determined between each pair of dimensionally-adjacent user-content components which are adjacent along one dimension.

2. A method in accordance with claim 1 , wherein: the ideal spacing distances and the current spacing distances in the respective template document and user document are determined between each pair of dimensionally-adjacent user-content components which are adjacent along one dimension. 3. The method of claim 2 , wherein the at least one user-content component comprises a text component.

1. A multi-function search box for display on a screen, comprising: a text input control to provide text input functionality, wherein the text input control suggests a complete word based on a partially entered word as a user continues entering characters of the user entered word, and a dropdown display area under and adjacent to the text input control, wherein the dropdown display area is opened upon detected entry in the text input control, the dropdown display area is divided into a first display area and a second display area, wherein, the first display area is oriented under the text input control to display a list of words, every word in the list of words is a suggestion for completing the user entered word; and the second display area coupled to and oriented under the first display area to display a list of contextually related options for a selected word in the list of words, wherein one or more of the contextually related options are generated without applying phrase matching criteria to the selected word, wherein a first displayed character of one or more of the contextually related options is exclusive of a first entered character of the user entered word, wherein the first or second display area is configured to receive a selection that is detected, wherein the detected selection is configured to trigger presentation of a page module including an interactive media space in a word page without generating links to external websites, wherein the page module is contextually related to the detected selection, wherein the multi-function search box is generated by a processor.

1. A multi-function search box for display on a screen, comprising: a text input control to provide text input functionality, wherein the text input control suggests a complete word based on a partially entered word as a user continues entering characters of the user entered word, and a dropdown display area under and adjacent to the text input control, wherein the dropdown display area is opened upon detected entry in the text input control, the dropdown display area is divided into a first display area and a second display area, wherein, the first display area is oriented under the text input control to display a list of words, every word in the list of words is a suggestion for completing the user entered word; and the second display area coupled to and oriented under the first display area to display a list of contextually related options for a selected word in the list of words, wherein one or more of the contextually related options are generated without applying phrase matching criteria to the selected word, wherein a first displayed character of one or more of the contextually related options is exclusive of a first entered character of the user entered word, wherein the first or second display area is configured to receive a selection that is detected, wherein the detected selection is configured to trigger presentation of a page module including an interactive media space in a word page without generating links to external websites, wherein the page module is contextually related to the detected selection, wherein the multi-function search box is generated by a processor. 16. The multi-function search box as recited in claim 1 , wherein the page module is capable of including a presentation of audio, video, text, and picture, wherein the page module includes an additional word that when selected results in a display of an additional word page, wherein the additional word page includes one or more additional page modules and is other than an external website, wherein the word page is other than an external website and is a web page, wherein the additional word page is a web page.

19. A computer-implemented method for executing a workflow, the method comprising the steps of: developing a Petri net domain model comprising a set of objects comprising a token object, a place object, an arc object, a transition object, and one or more trigger objects, wherein (a) each object represents a particular type of element of a Petri net model and (b) the one or more trigger objects represent triggering a transition object based at least in part on stimuli external to the workflow engine; reading source code representing a particular workflow by executing a workflow engine residing on a computing device, wherein the source code indicates elements of the particular workflow and connectors between elements of the particular workflow to sequence the elements of the particular workflow; loading the particular workflow into memory by mapping each element of the particular workflow to one or more objects of the set of objects and by mapping each connector of the particular workflow to one or more objects of the set of objects based on rules governing the Petri net model; and executing the particular workflow loaded into the memory by using the workflow engine, wherein the workflow engine further comprises one or more abstraction layer components comprising a transition layer from the Petri net domain model to an operating system, the abstraction layer configured to delegate one or more tasks associated with elements of the particular workflow of the Petri net domain to the operating system, via the transition layer, the delegated tasks to be performed by the operating system.

19. A computer-implemented method for executing a workflow, the method comprising the steps of: developing a Petri net domain model comprising a set of objects comprising a token object, a place object, an arc object, a transition object, and one or more trigger objects, wherein (a) each object represents a particular type of element of a Petri net model and (b) the one or more trigger objects represent triggering a transition object based at least in part on stimuli external to the workflow engine; reading source code representing a particular workflow by executing a workflow engine residing on a computing device, wherein the source code indicates elements of the particular workflow and connectors between elements of the particular workflow to sequence the elements of the particular workflow; loading the particular workflow into memory by mapping each element of the particular workflow to one or more objects of the set of objects and by mapping each connector of the particular workflow to one or more objects of the set of objects based on rules governing the Petri net model; and executing the particular workflow loaded into the memory by using the workflow engine, wherein the workflow engine further comprises one or more abstraction layer components comprising a transition layer from the Petri net domain model to an operating system, the abstraction layer configured to delegate one or more tasks associated with elements of the particular workflow of the Petri net domain to the operating system, via the transition layer, the delegated tasks to be performed by the operating system. 25. The method of claim 19 wherein delegate comprises the workflow engine passing one or more delegate components comprising one or more pointers to source code for one or more tasks associated with one or more elements of the particular workflow to the operating system so that the operating system can use the one or more pointers to access the source code to execute the source code to perform the one or more tasks.

1. A computer-implemented method, the method comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client.

1. A computer-implemented method, the method comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client. 4. The method of claim 1 wherein processing each provided input data by the respective predictive model includes determining one or more predictions based on the input data.

19. The method of claim 15 , wherein the conversion of the intermediate logical subquery into the semantic subquery by the one or more query processors comprises: identifying a surface form that corresponds to the intermediate logical subquery; retrieving interpretations for the surface form from a disambiguation table in the database; and selecting, from the retrieved interpretations, a highest-scoring interpretation that is compatible with query variables of the intermediate logical subquery, the highest-scoring interpretation characterizing the semantic subquery.

19. The method of claim 15 , wherein the conversion of the intermediate logical subquery into the semantic subquery by the one or more query processors comprises: identifying a surface form that corresponds to the intermediate logical subquery; retrieving interpretations for the surface form from a disambiguation table in the database; and selecting, from the retrieved interpretations, a highest-scoring interpretation that is compatible with query variables of the intermediate logical subquery, the highest-scoring interpretation characterizing the semantic subquery. 20. The method of claim 19 , wherein the disambiguation table is generated by: identifying patterns for each semantic frame, aliases for each entity, and words for each noun or adjective sense as surface forms; generating surface forms for each interpreted semantic fact by combining the surface forms for the semantic frame of the fact with the surface forms of one or more frame elements; and assigning scores to interpretations for each surface form.

1. A method for disambiguating an ambiguous entity in a search query based on a gaze of a user, the method comprising: monitoring, using control circuitry, at a current time, a gaze of a user during playback of a media asset, wherein monitoring the gaze of the user comprises monitoring a vertical degree of an eye of the user, a horizontal degree of the eye of the user, and a position of the eye of the user relative to a display screen displaying the media asset; determining a size of the display screen displaying the media asset; calculating, based on the position, the size, the vertical degree, and the horizontal degree, a first area of the display screen corresponding to the gaze of the user; storing, in memory, a data structure indicating the first area and the current time; receiving, using the control circuitry, a search query from the user at the current time; determining that the search query includes an ambiguous entity; and based on determining that the search query includes the ambiguous entity: retrieving, from the memory, the data structure; determining a frame of the media asset that correspond to the current time; retrieving, from a database, metadata relating to the frame of the media asset corresponding to the current time, the metadata including a first location of a first entity in the frame, a second location of a second entity in the frame, and a third location of a third entity in the frame; extracting, from the data structure, the first area corresponding to the current time; extracting from the metadata, the first location of the first entity in the frame and the second location of the second entity in the frame; determining that the first area overlaps with the first location of the first entity and the second location of the second entity; based on determining that the first area overlaps with the first location of the first entity and the second location of the second entity: receiving, using the control circuitry, data indicative of a second area from a user device of a second user, wherein the second area was calculated based on a gaze of the second user at the current time; and determining that the second area overlaps with the location of the first entity; based on determining that the second area overlaps with the location of the first entity, generating for display a first prompt for additional input, wherein the first prompt for additional input indicates the first entity as a first potential disambiguation of the ambiguous entity in the search query; subsequent to generating for display the first prompt for additional input, receiving a negative input from the user, wherein the negative input indicates that the first entity is an incorrect disambiguation of the ambiguous entity in the search query; based on receiving the negative input: expanding the first area to a third area of the display screen, wherein the third area is larger than the first area; extracting, from the metadata, the third location of the third entity in the frame; determining that the third area overlaps with the third location of the third entity; and based on determining that the third area overlaps with the third location, generating for display a second prompt for additional input, wherein the second prompt for additional input indicates the third entity as a second potential disambiguation of the ambiguous entity in the search query.

1. A method for disambiguating an ambiguous entity in a search query based on a gaze of a user, the method comprising: monitoring, using control circuitry, at a current time, a gaze of a user during playback of a media asset, wherein monitoring the gaze of the user comprises monitoring a vertical degree of an eye of the user, a horizontal degree of the eye of the user, and a position of the eye of the user relative to a display screen displaying the media asset; determining a size of the display screen displaying the media asset; calculating, based on the position, the size, the vertical degree, and the horizontal degree, a first area of the display screen corresponding to the gaze of the user; storing, in memory, a data structure indicating the first area and the current time; receiving, using the control circuitry, a search query from the user at the current time; determining that the search query includes an ambiguous entity; and based on determining that the search query includes the ambiguous entity: retrieving, from the memory, the data structure; determining a frame of the media asset that correspond to the current time; retrieving, from a database, metadata relating to the frame of the media asset corresponding to the current time, the metadata including a first location of a first entity in the frame, a second location of a second entity in the frame, and a third location of a third entity in the frame; extracting, from the data structure, the first area corresponding to the current time; extracting from the metadata, the first location of the first entity in the frame and the second location of the second entity in the frame; determining that the first area overlaps with the first location of the first entity and the second location of the second entity; based on determining that the first area overlaps with the first location of the first entity and the second location of the second entity: receiving, using the control circuitry, data indicative of a second area from a user device of a second user, wherein the second area was calculated based on a gaze of the second user at the current time; and determining that the second area overlaps with the location of the first entity; based on determining that the second area overlaps with the location of the first entity, generating for display a first prompt for additional input, wherein the first prompt for additional input indicates the first entity as a first potential disambiguation of the ambiguous entity in the search query; subsequent to generating for display the first prompt for additional input, receiving a negative input from the user, wherein the negative input indicates that the first entity is an incorrect disambiguation of the ambiguous entity in the search query; based on receiving the negative input: expanding the first area to a third area of the display screen, wherein the third area is larger than the first area; extracting, from the metadata, the third location of the third entity in the frame; determining that the third area overlaps with the third location of the third entity; and based on determining that the third area overlaps with the third location, generating for display a second prompt for additional input, wherein the second prompt for additional input indicates the third entity as a second potential disambiguation of the ambiguous entity in the search query. 9. The method of claim 1 , wherein the metadata further includes a fourth location of a fourth entity in the frame, and wherein the search query includes a pronoun, the method further comprising: extracting from the metadata the fourth location of the fourth entity in the frame; determining that the first area overlaps with the fourth location of the fourth entity; based on determining that the first area overlaps with the fourth location and the first location: retrieving, using control circuitry, from the database, metadata associating the pronoun with a characteristic of a characteristic type; retrieving, from the database, metadata about the first entity and metadata about the fourth entity; determining, based on the metadata about the first entity and the metadata about the fourth entity, that the first entity is associated with the characteristic and the fourth entity is associated with a different characteristic of the characteristic type; and wherein generating for display the first prompt for additional input is further based on determining that the first entity is associated with the characteristic and the fourth entity is associated with the different characteristic.

17. The method of claim 13 , wherein the profile information further includes the user's connections' tag affinities and wherein selecting questions based on tags related to the selected topic further comprises selecting questions based on tags corresponding to the user's connections' tag affinities.

17. The method of claim 13 , wherein the profile information further includes the user's connections' tag affinities and wherein selecting questions based on tags related to the selected topic further comprises selecting questions based on tags corresponding to the user's connections' tag affinities. 18. The method of claim 17 , wherein for each of the questions, determining a score further comprises: for each of the questions, determining a score for the question by combining the user's tag affinities for the tags associated with the question and the user's connections' tag affinities for the tags associated with the question.

16. The method of claim 15 , wherein the selecting further comprising preserving an order the pre-selected number of sentences follow in the digital text.

16. The method of claim 15 , wherein the selecting further comprising preserving an order the pre-selected number of sentences follow in the digital text. 17. The computer-implemented method of claim 16 , further comprising, prior to the acquiring the indication of the digital text to be processed, acquiring an indication of the pre-selected number of sentences and wherein the selecting the pre-selected number of sentences from the plurality of sentences based on their respective sentence meaning value comprises: (i) selecting a first subset of the pre-selected number of sentences from a first portion of the digital text and (ii) selecting a second subset of the pre-selected number of sentences from a second portion of the digital text.

1. A method comprising: opening a file definition that defines a template including executable instructions and at least one query associated with the template, wherein the executable instructions include at least one call instruction that calls at least one other template including executable instructions and wherein the executable instructions of the template and the at least one query are in a format and with a language of a source database; extracting data with the at least one query from the source database in the form of sets of records; and generating an XML document for each record comprising data derived from the data of the corresponding record by: executing the executable instructions of the template during an execution stage for each record of the set of records; calling the at least one other template when the at least one call instruction is executed among the executable instructions of the template during the execution stage, and executing the executable instructions of the at least one other template called by the at least one call instruction during the execution stage for each record of the set of records, wherein executing the executable instructions of the template during an execution stage for each record of the set of records comprises: constructing a name for at least one XML document, creating a target file for the at least one XML document, creating a root element which is assigned a function of a current element, and processing a root template calling any other template of a plurality of templates.

1. A method comprising: opening a file definition that defines a template including executable instructions and at least one query associated with the template, wherein the executable instructions include at least one call instruction that calls at least one other template including executable instructions and wherein the executable instructions of the template and the at least one query are in a format and with a language of a source database; extracting data with the at least one query from the source database in the form of sets of records; and generating an XML document for each record comprising data derived from the data of the corresponding record by: executing the executable instructions of the template during an execution stage for each record of the set of records; calling the at least one other template when the at least one call instruction is executed among the executable instructions of the template during the execution stage, and executing the executable instructions of the at least one other template called by the at least one call instruction during the execution stage for each record of the set of records, wherein executing the executable instructions of the template during an execution stage for each record of the set of records comprises: constructing a name for at least one XML document, creating a target file for the at least one XML document, creating a root element which is assigned a function of a current element, and processing a root template calling any other template of a plurality of templates. 3. The method of claim 1 , wherein executing the instructions of the template during the execution stage for each record of the set of records comprises: creating a new child element of the, root element and assigning the function of the current element to the new child element; creating a new attribute for the new child element; and closing the new child element including reassigning the function of the current element to the, root element.

1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving geotagged audio signals that correspond to environmental audio recorded by multiple mobile devices in multiple geographic locations, receiving an audio signal that corresponds to an utterance recorded by a particular mobile device, determining a particular geographic location associated with the particular mobile device, generating a noise model for the particular geographic location using a subset of the geotagged audio signals, and performing noise compensation on the audio signal that corresponds to the utterance using the noise model that has been generated for the particular geographic location.

1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving geotagged audio signals that correspond to environmental audio recorded by multiple mobile devices in multiple geographic locations, receiving an audio signal that corresponds to an utterance recorded by a particular mobile device, determining a particular geographic location associated with the particular mobile device, generating a noise model for the particular geographic location using a subset of the geotagged audio signals, and performing noise compensation on the audio signal that corresponds to the utterance using the noise model that has been generated for the particular geographic location. 11. The system of claim 1 , wherein determining the particular geographic location further comprises determining a past geographic location or a default geographic location associated with the device.

15. The non-transitory computer-readable storage medium of claim 13 , wherein responsive to the non-standard payee name being a normalized payee name, the method further comprises: determining whether a user-defined payee name which meets specified criteria is associated with the normalized payee name; responsive to the user-defined payee name being associated with the normalized payee name, determining whether a normalized payee name which meets specified criteria is associated with the determined user-defined payee name; responsive to the normalized payee name that meets specified criteria being associated with the determined user-defined payee name, determining whether the determined user-defined payee name substantially matches the determined normalized payee name; and if so, determining that the determined user-defined payee name is associated with the standard payee name; and otherwise, using the determined normalized payee name to recursively search through the plurality of non-standard payee names which are associated with the standard payee name to determine whether the non-standard payee name is associated with the standard payee name.

15. The non-transitory computer-readable storage medium of claim 13 , wherein responsive to the non-standard payee name being a normalized payee name, the method further comprises: determining whether a user-defined payee name which meets specified criteria is associated with the normalized payee name; responsive to the user-defined payee name being associated with the normalized payee name, determining whether a normalized payee name which meets specified criteria is associated with the determined user-defined payee name; responsive to the normalized payee name that meets specified criteria being associated with the determined user-defined payee name, determining whether the determined user-defined payee name substantially matches the determined normalized payee name; and if so, determining that the determined user-defined payee name is associated with the standard payee name; and otherwise, using the determined normalized payee name to recursively search through the plurality of non-standard payee names which are associated with the standard payee name to determine whether the non-standard payee name is associated with the standard payee name. 18. The non-transitory computer-readable storage medium of claim 15 , wherein responsive to a normalized payee name which meets the specified criteria not being associated with the determined user-defined payee name, the method further comprises using the determined user-defined payee name to recursively search through the plurality of non-standard payee names which are associated with a standard payee name to determine whether the non-standard payee name is associated with the standard payee name.

40. The system of claim 37 , wherein the relevancy scoring module comprises instructions associated with two or more relevancy algorithms that are executed by the processor to determine one or more of the following relevancy scores: occurrence count score; intro proximity score; first and last occurrence range score; and gap deviation score.

40. The system of claim 37 , wherein the relevancy scoring module comprises instructions associated with two or more relevancy algorithms that are executed by the processor to determine one or more of the following relevancy scores: occurrence count score; intro proximity score; first and last occurrence range score; and gap deviation score. 41. The system of claim 40 , wherein the two or more relevancy algorithms are from the group consisting of: determining a number representing a number of times the term is mentioned in the document; determining a number representing a proximity of a first occurrence of the term to the beginning of the document; determining a number representing a proximity of a first occurrence of the term to a last occurrence of the term within the document; and determining a number representing overall changes in a rate of occurrences of the term throughout the document.

1. A non-transitory article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising: analyzing input from at least one environmental sensor to identify context information pertaining to a user situation; forecasting a subsequent cognitive task of the user in the user situation based on the context information and use of a learned model; determining a combination of two or more words to be communicated by the user in anticipation of the user communicating said combination of two or more words, wherein the determining is based on the forecasted subsequent cognitive task, the context information and information learned from at least one previous user situation; computing a confidence value to represent a level of certainty in the combination of two or more words to be communicated by the user in connection with the forecasted subsequent cognitive task; updating the confidence value at a specified interval until the confidence value reaches a threshold value; and providing a prompt to the user, wherein said prompt contains the combination of two or more words to be communicated by the user, upon the confidence value reaching the threshold value.

1. A non-transitory article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising: analyzing input from at least one environmental sensor to identify context information pertaining to a user situation; forecasting a subsequent cognitive task of the user in the user situation based on the context information and use of a learned model; determining a combination of two or more words to be communicated by the user in anticipation of the user communicating said combination of two or more words, wherein the determining is based on the forecasted subsequent cognitive task, the context information and information learned from at least one previous user situation; computing a confidence value to represent a level of certainty in the combination of two or more words to be communicated by the user in connection with the forecasted subsequent cognitive task; updating the confidence value at a specified interval until the confidence value reaches a threshold value; and providing a prompt to the user, wherein said prompt contains the combination of two or more words to be communicated by the user, upon the confidence value reaching the threshold value. 11. The article of manufacture of claim 1 , wherein said forecasting comprises performing an analysis of at least one word combination or word association of the user.

14. A computing device including a speech-enabled application installed thereon, the computing device comprising: at least one storage device configured to store at least one data structure including information describing a plurality of natural language understanding (NLU) results and corresponding ASR output used to generate the plurality of NW results; an input interface configured to receive first audio comprising speech from a user of the computing device; an automatic speech recognition (ASR) engine configured to: detect based, at least in part, on a threshold time for endpointing, an end of speech in the first audio; and generate a first ASR result based, at least in part, on a portion of the first audio prior to the detected end of speech; and at least one processor programmed to: determine whether a valid action can be performed by the speech-enabled application using the first ASR result; instruct the ASR engine to process second audio when it is determined that a valid action cannot be performed by the speech-enabled application using the first ASR result; determine whether to add the first ASR result and a corresponding NLU result generated using the first ASK result to the at least one data structure stored on the at least one storage device; and add the first ASR result and the corresponding NLU result generated using the first ASR result to the at least one data structure stored on the at least one storage device in response to determining that the first ASK result and the corresponding NLU result should be added.

14. A computing device including a speech-enabled application installed thereon, the computing device comprising: at least one storage device configured to store at least one data structure including information describing a plurality of natural language understanding (NLU) results and corresponding ASR output used to generate the plurality of NW results; an input interface configured to receive first audio comprising speech from a user of the computing device; an automatic speech recognition (ASR) engine configured to: detect based, at least in part, on a threshold time for endpointing, an end of speech in the first audio; and generate a first ASR result based, at least in part, on a portion of the first audio prior to the detected end of speech; and at least one processor programmed to: determine whether a valid action can be performed by the speech-enabled application using the first ASR result; instruct the ASR engine to process second audio when it is determined that a valid action cannot be performed by the speech-enabled application using the first ASR result; determine whether to add the first ASR result and a corresponding NLU result generated using the first ASK result to the at least one data structure stored on the at least one storage device; and add the first ASR result and the corresponding NLU result generated using the first ASR result to the at least one data structure stored on the at least one storage device in response to determining that the first ASK result and the corresponding NLU result should be added. 16. The computing device of claim 14 , wherein the input interface is further configured to receive third audio including speech from the user of the computing device, wherein the ASR engine is further configured to generate a second ASR result based, at least in pall, on at least a portion of the third audio, and wherein the processor is further programmed to: identify an ASR output stored in the at least one data structure corresponding to the second ASR result; and submit the NLU result corresponding to the identified ASR output stored in the at least one data structure to the speech-enabled application to enable the speech-enabled application to perform an action based on the submitted NLU result.

1. A method of automatically translating a requested Web page from a first language to a second language, wherein the requested web page is stored within a server remotely located from a client requesting the Web page and wherein the requested Web page is configured to be displayed in a first language by the requesting client, the method comprising the steps of: transmitting a request for the Web page from the client to the server via a communications network, wherein the Web page request comprises a universal resource locator that identifies a path to the Web page on the server, and wherein at least a portion of the universal resource locator is associated with a translating environment; identifying a translating environment associated with the transmitted universal resource locator; selecting the identified translating environment from a plurality of translating environments; and translating the requested Web page from the first language to the second language using the selected translating environment prior to serving the requested Web page to the requesting client.

1. A method of automatically translating a requested Web page from a first language to a second language, wherein the requested web page is stored within a server remotely located from a client requesting the Web page and wherein the requested Web page is configured to be displayed in a first language by the requesting client, the method comprising the steps of: transmitting a request for the Web page from the client to the server via a communications network, wherein the Web page request comprises a universal resource locator that identifies a path to the Web page on the server, and wherein at least a portion of the universal resource locator is associated with a translating environment; identifying a translating environment associated with the transmitted universal resource locator; selecting the identified translating environment from a plurality of translating environments; and translating the requested Web page from the first language to the second language using the selected translating environment prior to serving the requested Web page to the requesting client. 2. A method according to claim 1 wherein the at least one portion of the universal resource locator associated with the translating environment comprises at least one character string.

9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a web site relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and transcriptions of the predetermined number of utterances.

9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a web site relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and transcriptions of the predetermined number of utterances. 15. The system of claim 9 , wherein the predetermined number of utterances are randomly selected.

1. A method for analyzing ambiguities in language for natural language processing, said method comprising: an input device receiving a first sentence or phrase from a source; wherein a vocabulary database stores words or phrases; wherein a language grammar template database stores language grammar templates; an analyzer module segmenting said first sentence or phrase, using words or phrases obtained from said vocabulary database and language grammar templates obtained from said language grammar template database; said analyzer module parsing said first sentence or phrase into one or more sentence or phrase components; said analyzer module determining Z-valuation for said one or more sentence or phrase components as a value of an attribute for said one or more sentence or phrase components; wherein said Z-valuation for said one or more sentence or phrase components are based on one or more parameters with unsharp class boundary or fuzzy membership function; said analyzer module processing language ambiguities in said first sentence or phrase for natural language processing, using said Z-valuation for said one or more sentence or phrase components.

1. A method for analyzing ambiguities in language for natural language processing, said method comprising: an input device receiving a first sentence or phrase from a source; wherein a vocabulary database stores words or phrases; wherein a language grammar template database stores language grammar templates; an analyzer module segmenting said first sentence or phrase, using words or phrases obtained from said vocabulary database and language grammar templates obtained from said language grammar template database; said analyzer module parsing said first sentence or phrase into one or more sentence or phrase components; said analyzer module determining Z-valuation for said one or more sentence or phrase components as a value of an attribute for said one or more sentence or phrase components; wherein said Z-valuation for said one or more sentence or phrase components are based on one or more parameters with unsharp class boundary or fuzzy membership function; said analyzer module processing language ambiguities in said first sentence or phrase for natural language processing, using said Z-valuation for said one or more sentence or phrase components. 14. The method for analyzing ambiguities in language for natural language processing as recited in claim 1 , wherein said method comprises: replacing neighboring keys for spelling correction.

1. An information retrieval system, the system comprising: at least one database storing a plurality of documents; and a server coupled to the at least one database, the server comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving a query, the query including a first term, from a requesting application presented by a client access device, the requesting application having a plurality of subject areas, the query associated with a subject area of the plurality of subject areas; selecting a taxonomy that is associated with the subject area of the query, the plurality of subject areas being related to different taxonomies; refining the query based on the taxonomy selected to include a second term in the query; and processing the query as refined against the at least one database to return a search result including at least one document to the client device.

1. An information retrieval system, the system comprising: at least one database storing a plurality of documents; and a server coupled to the at least one database, the server comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving a query, the query including a first term, from a requesting application presented by a client access device, the requesting application having a plurality of subject areas, the query associated with a subject area of the plurality of subject areas; selecting a taxonomy that is associated with the subject area of the query, the plurality of subject areas being related to different taxonomies; refining the query based on the taxonomy selected to include a second term in the query; and processing the query as refined against the at least one database to return a search result including at least one document to the client device. 6. The system of claim 1 , wherein operations further comprise refining the query by including a broader topic based on the taxonomy selected.

1. A computer-implemented method, the method comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client.

1. A computer-implemented method, the method comprising: obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model; executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices; processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client. 2. The method of claim 1 wherein a portion of the execution of the at least two scripts occurs at a same time.