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11. A system including a processor comprising: a query-to-data format converter that receives a first query with a first query data format and a second query with a second query data format and generates a common metadata based query object by converting the first query and the second query into a common metadata format that includes first metadata for the first query, second metadata for the second query, first data associated with the first query, and second data associated with the second query, the first query data format being distinct from the second query data format; wherein the metadata includes a condition value for a condition in the query; a query executor that extracts, with the processor, the first metadata and the second metadata from the common metadata based query object, generates a first application specific query based on the first metadata and a first application to which the first query is intended, and generates a second application specific query based on the second metadata and a second application to which the second query is intended; and wherein the application is configured for a specific enterprise information system. | 11. A system including a processor comprising: a query-to-data format converter that receives a first query with a first query data format and a second query with a second query data format and generates a common metadata based query object by converting the first query and the second query into a common metadata format that includes first metadata for the first query, second metadata for the second query, first data associated with the first query, and second data associated with the second query, the first query data format being distinct from the second query data format; wherein the metadata includes a condition value for a condition in the query; a query executor that extracts, with the processor, the first metadata and the second metadata from the common metadata based query object, generates a first application specific query based on the first metadata and a first application to which the first query is intended, and generates a second application specific query based on the second metadata and a second application to which the second query is intended; and wherein the application is configured for a specific enterprise information system. 14. The system of claim 11 , wherein the metadata includes a condition type for a condition in the query. | 0.673529 |
1. An apparatus for bi-directional sign language/speech translation in real time comprising: a processor; and a non-transitory computer readable medium storing program instructions, when executed, causing the processor to: analyze a used pattern of sign language by a user in view of current surrounding environment information of the user to generate sign category information via a pattern analyzer; recognize a speech externally made through a microphone via a speech-sign outputter and output a sign corresponding to the speech via a display of the speech-sign outputter; and recognize a sign sensed through a camera via a sign-speech outputter and output a speech corresponding to the sign via a speaker of the sign-speech outputter, wherein the pattern analyzer transmits the sign category information to the speech-sign outputter to output a text or a sign corresponding to the sign category information via the display or to the sign-speech outputter to output a speech corresponding to the sign category information via the speaker, wherein the pattern analyzer comprises a sign category keyword comparator configured to compare the sign category information with the sign corresponding to the speech or the speech corresponding to the sign to determine whether the sign category information is correct, and wherein the sign category keyword comparator transmits a signal related to whether the sign category information is correct to the speech-sign outputter or the sign-speech outputter to block the text, the sign, or the speech corresponding to the sign category information. | 1. An apparatus for bi-directional sign language/speech translation in real time comprising: a processor; and a non-transitory computer readable medium storing program instructions, when executed, causing the processor to: analyze a used pattern of sign language by a user in view of current surrounding environment information of the user to generate sign category information via a pattern analyzer; recognize a speech externally made through a microphone via a speech-sign outputter and output a sign corresponding to the speech via a display of the speech-sign outputter; and recognize a sign sensed through a camera via a sign-speech outputter and output a speech corresponding to the sign via a speaker of the sign-speech outputter, wherein the pattern analyzer transmits the sign category information to the speech-sign outputter to output a text or a sign corresponding to the sign category information via the display or to the sign-speech outputter to output a speech corresponding to the sign category information via the speaker, wherein the pattern analyzer comprises a sign category keyword comparator configured to compare the sign category information with the sign corresponding to the speech or the speech corresponding to the sign to determine whether the sign category information is correct, and wherein the sign category keyword comparator transmits a signal related to whether the sign category information is correct to the speech-sign outputter or the sign-speech outputter to block the text, the sign, or the speech corresponding to the sign category information. 2. The apparatus for bi-directional sign language/speech translation in real time of claim 1 , wherein the speech-sign outputter comprises: a speech recognizer configured to recognize the speech; an index generator configured to generate a sign index to translate into a sign corresponding to the recognized speech; and a sign outputter configured to output the sign corresponding to the recognized speech based on the generated sign index. | 0.504249 |
1. A method comprising: detecting, via a microphone of an electronic device, an audible speech stream; converting the audible speech stream to text; detecting speech loss in the audible speech stream indicating an inability to complete a thought associated with the audible speech stream; generating a query in response to the detecting the speech loss, wherein the query includes at least a portion of the text; searching a catalog on the electronic device using the query to find related catalog data, wherein the catalog includes one or more of text strings, images, contact information, and global positioning system information associated with the electronic device; and presenting the related catalog data. | 1. A method comprising: detecting, via a microphone of an electronic device, an audible speech stream; converting the audible speech stream to text; detecting speech loss in the audible speech stream indicating an inability to complete a thought associated with the audible speech stream; generating a query in response to the detecting the speech loss, wherein the query includes at least a portion of the text; searching a catalog on the electronic device using the query to find related catalog data, wherein the catalog includes one or more of text strings, images, contact information, and global positioning system information associated with the electronic device; and presenting the related catalog data. 8. The method of claim 1 , further comprising distinguishing a user's input from other speakers having conversations within the vicinity of the user, wherein the audible speech stream includes the user's input. | 0.75522 |
5. An electronic computing device comprising a computer processor and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, cause the electronic computing device to carry out the steps of: receiving a visual cue, said visual cue including visual media of a target, the visual media comprising a digital graphic image, the target comprising an object depicted in the image, the visual cue comprising a characteristic of the target; extracting visual cue identification data from the visual cue, including performing at least one of an image recognition operation and an object recognition operation; determining from the extracted visual cue identification data a list of words representing the target; storing the list of words representing the target; updating a probable words dictionary to include the list of words; and assigning a priority weighting factor to each word determined from the visual cue identification data extracted from the object depicted in the image and added to the probable word dictionary, wherein the priority weighting factor indicates that each word added to the probable word dictionary is given a higher priority than existing words in the probable word dictionary that were not determined from the visual cue identification data extracted from the object depicted in the image. | 5. An electronic computing device comprising a computer processor and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, cause the electronic computing device to carry out the steps of: receiving a visual cue, said visual cue including visual media of a target, the visual media comprising a digital graphic image, the target comprising an object depicted in the image, the visual cue comprising a characteristic of the target; extracting visual cue identification data from the visual cue, including performing at least one of an image recognition operation and an object recognition operation; determining from the extracted visual cue identification data a list of words representing the target; storing the list of words representing the target; updating a probable words dictionary to include the list of words; and assigning a priority weighting factor to each word determined from the visual cue identification data extracted from the object depicted in the image and added to the probable word dictionary, wherein the priority weighting factor indicates that each word added to the probable word dictionary is given a higher priority than existing words in the probable word dictionary that were not determined from the visual cue identification data extracted from the object depicted in the image. 7. The electronic computing device of claim 5 , wherein updating the probable words dictionary comprises: determining whether each word in the list of words is present in the probable words dictionary; and for each word not found in the probable words dictionary, adding the word to the probable words dictionary. | 0.5 |
1. A method for providing emotionally relevant content to users, comprising: receiving, from a first user, a user emotion label for content; labeling the content based upon the user emotion label to create labeled content; defining an emotional transition trigger for a second user comprising defining a timeout trigger for a first emotional content type; and responsive to a triggering of the emotional transition trigger comprising the second user consuming content of the first emotional content type for a threshold amount of time corresponding to the timeout trigger, providing the labeled content to the second user based upon the labeled content having a second emotional content type different than the first emotional content type. | 1. A method for providing emotionally relevant content to users, comprising: receiving, from a first user, a user emotion label for content; labeling the content based upon the user emotion label to create labeled content; defining an emotional transition trigger for a second user comprising defining a timeout trigger for a first emotional content type; and responsive to a triggering of the emotional transition trigger comprising the second user consuming content of the first emotional content type for a threshold amount of time corresponding to the timeout trigger, providing the labeled content to the second user based upon the labeled content having a second emotional content type different than the first emotional content type. 6. The method of claim 1 , the defining an emotional transition trigger comprising defining a user input pattern as the emotional transition trigger, and the providing the labeled content comprising responsive to user input of the second user corresponding to the user input pattern, providing the labeled content. | 0.611635 |
6. A method for performing queries on stored data in a Hadoop™ distributed computing cluster system, the method comprising: configuring a plurality of data nodes forming a peer-to-peer network for the queries received from a client, each data node of the plurality of data nodes functioning as a peer in the peer-to-peer network and being capable of interacting with components of the Hadoop™ cluster, each peer having an instance of a query engine running in memory; and configuring each instance of the query engine to include: a query planner that parses a query from the client and selectively creates query fragments based on an availability of converted data at the data node, the converted data corresponding to data associated with the query, wherein the converted data is the data associated with the query converted from an original format into a target format that is specified by a schema, and wherein the query is processed by whichever data node that receives the query; a query coordinator that distributes the query fragments among the plurality of data nodes; and a query execution engine that: transforms whichever local data that corresponds to a format for which the query fragments are created into in-memory tuples based on the schema; and executes the query fragments on the in-memory tuples to obtain intermediate results from other data nodes that receive the query fragments and to aggregate the intermediate results for the client. | 6. A method for performing queries on stored data in a Hadoop™ distributed computing cluster system, the method comprising: configuring a plurality of data nodes forming a peer-to-peer network for the queries received from a client, each data node of the plurality of data nodes functioning as a peer in the peer-to-peer network and being capable of interacting with components of the Hadoop™ cluster, each peer having an instance of a query engine running in memory; and configuring each instance of the query engine to include: a query planner that parses a query from the client and selectively creates query fragments based on an availability of converted data at the data node, the converted data corresponding to data associated with the query, wherein the converted data is the data associated with the query converted from an original format into a target format that is specified by a schema, and wherein the query is processed by whichever data node that receives the query; a query coordinator that distributes the query fragments among the plurality of data nodes; and a query execution engine that: transforms whichever local data that corresponds to a format for which the query fragments are created into in-memory tuples based on the schema; and executes the query fragments on the in-memory tuples to obtain intermediate results from other data nodes that receive the query fragments and to aggregate the intermediate results for the client. 7. The method of claim 6 , wherein the target format is a columnar format. | 0.841102 |
17. The system of claim 15 , wherein the extracted document pattern comprises a specific word that is shared by both the first documents that were retrieved by submitting the lexicon terms to the search engine and the second documents that the query log does not indicate were retrieved by submitting the lexicon terms to the search engine. | 17. The system of claim 15 , wherein the extracted document pattern comprises a specific word that is shared by both the first documents that were retrieved by submitting the lexicon terms to the search engine and the second documents that the query log does not indicate were retrieved by submitting the lexicon terms to the search engine. 19. The system of claim 17 , wherein the particular query domain relates to locations, the lexicon term identifies a first location, and the new lexicon term that is added to the lexicon identifies a second location. | 0.857898 |
14. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform a method comprising: receiving an utterance; transcribing the utterance; determining whether the utterance transcription contains grammar that is statistically common; determining whether the utterance transcription contains grammar that is statistically uncommon; receiving a translation of the utterance; determining at least one difference between the transcribed utterance and the translated utterance; sorting the at least one determined difference; and reporting the at least one determined difference, wherein the determining whether the utterance transcription contains grammar that is statistically common and the determining whether the utterance transcription contains grammar that is statistically uncommon are separate determinations performed for the utterance transcription. | 14. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform a method comprising: receiving an utterance; transcribing the utterance; determining whether the utterance transcription contains grammar that is statistically common; determining whether the utterance transcription contains grammar that is statistically uncommon; receiving a translation of the utterance; determining at least one difference between the transcribed utterance and the translated utterance; sorting the at least one determined difference; and reporting the at least one determined difference, wherein the determining whether the utterance transcription contains grammar that is statistically common and the determining whether the utterance transcription contains grammar that is statistically uncommon are separate determinations performed for the utterance transcription. 16. The computer readable medium of claim 14 , the instructions further configured to cause the processor perform a method comprising: receiving a report of a correct acceptance of the transcription from a translator. | 0.536254 |
8. A computer program product for transforming historical data collected in response to one or more triggering events, in order to classify textual values, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to access a plurality of textual values from historical transaction data; computer readable program code configured to remove undesired characters from the plurality of textual values; computer readable program code configured to implement a clustering algorithm to the plurality of textual values to identify one or more distinct patterns within the plurality of textual values, wherein the clustering algorithm comprises: a primary process coding the plurality of textual values into one or more phonetic components, thereby reducing the plurality of textual values into a combination of consonant sounds, wherein identifying the one or more distinct patterns within the plurality of textual values comprises comparing pronunciations and phonetics of the plurality of textual values; and a secondary process for identifying and classifying, based on an Internet search, one or more of the plurality of textual values unable to be classified by the primary process; computer readable program code configured to create one or more clusters by grouping the plurality of textual values based, respectively, on the one or more distinct patterns output by the primary process and the Internet search of the secondary process; computer readable program code configured to apply a similarity gauge to the textual values of each of the clusters to determine similarity or dissimilarity among the textual values of each cluster; computer readable program code configured to filter the textual values of each cluster to determine which textual values belong in each cluster and which textual values do not belong in each cluster, wherein the textual values that belong are cluster values; computer readable program code configured to pass the cluster values for each cluster to a reference table; computer readable program code configured to store the cluster values for each cluster in the reference table for future access; and computer readable program code configured to, in response to a need for classification of a future set of textual values, access the reference table and lookup the future set of textual values in the reference table to determine whether any of the future set of textual values are cluster values. | 8. A computer program product for transforming historical data collected in response to one or more triggering events, in order to classify textual values, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to access a plurality of textual values from historical transaction data; computer readable program code configured to remove undesired characters from the plurality of textual values; computer readable program code configured to implement a clustering algorithm to the plurality of textual values to identify one or more distinct patterns within the plurality of textual values, wherein the clustering algorithm comprises: a primary process coding the plurality of textual values into one or more phonetic components, thereby reducing the plurality of textual values into a combination of consonant sounds, wherein identifying the one or more distinct patterns within the plurality of textual values comprises comparing pronunciations and phonetics of the plurality of textual values; and a secondary process for identifying and classifying, based on an Internet search, one or more of the plurality of textual values unable to be classified by the primary process; computer readable program code configured to create one or more clusters by grouping the plurality of textual values based, respectively, on the one or more distinct patterns output by the primary process and the Internet search of the secondary process; computer readable program code configured to apply a similarity gauge to the textual values of each of the clusters to determine similarity or dissimilarity among the textual values of each cluster; computer readable program code configured to filter the textual values of each cluster to determine which textual values belong in each cluster and which textual values do not belong in each cluster, wherein the textual values that belong are cluster values; computer readable program code configured to pass the cluster values for each cluster to a reference table; computer readable program code configured to store the cluster values for each cluster in the reference table for future access; and computer readable program code configured to, in response to a need for classification of a future set of textual values, access the reference table and lookup the future set of textual values in the reference table to determine whether any of the future set of textual values are cluster values. 11. The computer program product of claim 8 , the computer readable program code comprising: computer readable program code configured to connect the textual values that belong in each cluster; and computer readable program code configured to remove the textual values that do not belong in each cluster. | 0.52333 |
15. A user interface, produced by, and defined on, a computing device, comprising: at least one table residing within a document, the table having multiple cells; at least one free floating field inline with text in the document, the free floating field containing a formula that references a cell in the table, wherein the free floating field is integrated into the text, and wherein selecting and applying formatting to the text applies the formatting to the free floating field; and the formula in the free floating field being automatically recalculated upon modification of the cell in the table; and a second free floating field residing inline with the text in the document, the second free floating field created in response to a selection of at least a portion of the text in the document, and the second free floating field configured to contain the selected portion of text. | 15. A user interface, produced by, and defined on, a computing device, comprising: at least one table residing within a document, the table having multiple cells; at least one free floating field inline with text in the document, the free floating field containing a formula that references a cell in the table, wherein the free floating field is integrated into the text, and wherein selecting and applying formatting to the text applies the formatting to the free floating field; and the formula in the free floating field being automatically recalculated upon modification of the cell in the table; and a second free floating field residing inline with the text in the document, the second free floating field created in response to a selection of at least a portion of the text in the document, and the second free floating field configured to contain the selected portion of text. 20. The user interface of claim 15 , further comprising multiple tables and multiple free floating fields, at least one of the tables and free floating fields containing a formula that references at least one other of the tables and free floating fields. | 0.504569 |
1. A method of generating a customized document about a product, the method comprising: a) providing a user with a document manager input interface on a computer, the input interface including a definition manager module, an electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) on the computer, defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module, wherein the document definition comprises at least one of (i) organization of sections of the customized document, (ii) maintenance codes specific to the product, and (iii) page formatting information; c) on the computer, creating the customized document from the document definition using the definition manager module; d) on the computer, storing the customized document in a relational database; e) on the computer, editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) on the computer, deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) on the computer, modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) on the computer, establishing effectivity associations, using the effectivity interface module, for a given component of the product, and thereby defining a manner in which a change to the given component is propagated throughout the customized document; i) in response to the user making the change to the given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, (iv) the customized data provided by the electronic library manager module, and (v) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document. | 1. A method of generating a customized document about a product, the method comprising: a) providing a user with a document manager input interface on a computer, the input interface including a definition manager module, an electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) on the computer, defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module, wherein the document definition comprises at least one of (i) organization of sections of the customized document, (ii) maintenance codes specific to the product, and (iii) page formatting information; c) on the computer, creating the customized document from the document definition using the definition manager module; d) on the computer, storing the customized document in a relational database; e) on the computer, editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) on the computer, deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) on the computer, modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) on the computer, establishing effectivity associations, using the effectivity interface module, for a given component of the product, and thereby defining a manner in which a change to the given component is propagated throughout the customized document; i) in response to the user making the change to the given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, (iv) the customized data provided by the electronic library manager module, and (v) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document. 5. The method of claim 1 , further comprising: cross-referencing one of the predefined data elements or revised data elements to one or more other documents. | 0.549637 |
1. A system for recommending keywords, comprising: one or more processors configured to: receive a set of product information including a product title; extract and parse the product title into a set of parsed elements; find a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored predetermined mappings between parsed data and keywords; determine a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords, wherein to determine the plurality of composite correlation scores includes to determine a first composite correlation score associated with a first candidate keyword of the plurality of candidate keywords, wherein to determine the first composite correlation score associated with the first candidate keyword includes to determine an industry index value associated with the first candidate keyword, including to: determine a first similarity value between one or more industries associated with the first candidate keyword and one or more industries associated with sets of product information that are relevant to the first candidate keyword; determine a second similarity value between the one or more industries associated with the first candidate keyword and one or more industries of one or more seller users associated with the sets of product information that are relevant to the first candidate keyword; and determine the industry index value associated with the first candidate keyword based at least in part on a combination of the first similarity value and the second similarity value; and sort at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and select a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list; and one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions. | 1. A system for recommending keywords, comprising: one or more processors configured to: receive a set of product information including a product title; extract and parse the product title into a set of parsed elements; find a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored predetermined mappings between parsed data and keywords; determine a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords, wherein to determine the plurality of composite correlation scores includes to determine a first composite correlation score associated with a first candidate keyword of the plurality of candidate keywords, wherein to determine the first composite correlation score associated with the first candidate keyword includes to determine an industry index value associated with the first candidate keyword, including to: determine a first similarity value between one or more industries associated with the first candidate keyword and one or more industries associated with sets of product information that are relevant to the first candidate keyword; determine a second similarity value between the one or more industries associated with the first candidate keyword and one or more industries of one or more seller users associated with the sets of product information that are relevant to the first candidate keyword; and determine the industry index value associated with the first candidate keyword based at least in part on a combination of the first similarity value and the second similarity value; and sort at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and select a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list; and one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions. 9. The system of claim 1 , wherein the one or more processors are further configured to receive an update to the set of product information, the update being based at least in part on the set of one or more keywords. | 0.747967 |
8. A system for providing top concepts for a video file, the system comprising: a storage memory; and a processor in communication with the storage memory, wherein the storage memory includes sets of instructions which, when executed by the processor, cause the processor to: receive a list of candidate tags for a video file; receive a transcript of audio associated with the video file; rank the list of candidate tags for the video file based on a plurality of ranking factors; filter candidate tags from the list of candidate tags which rank below a threshold value; present the filtered list of candidate tags in a user interface; receive a selection of one or more of the filtered list of candidate tags; receive one or more additional tags; based on the selected one or more of the filtered list of candidate tags and the evaluate the transcript and the one or more additional tags, evaluating the transcript and producing an updated list of candidate tags for the video file; establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file. | 8. A system for providing top concepts for a video file, the system comprising: a storage memory; and a processor in communication with the storage memory, wherein the storage memory includes sets of instructions which, when executed by the processor, cause the processor to: receive a list of candidate tags for a video file; receive a transcript of audio associated with the video file; rank the list of candidate tags for the video file based on a plurality of ranking factors; filter candidate tags from the list of candidate tags which rank below a threshold value; present the filtered list of candidate tags in a user interface; receive a selection of one or more of the filtered list of candidate tags; receive one or more additional tags; based on the selected one or more of the filtered list of candidate tags and the evaluate the transcript and the one or more additional tags, evaluating the transcript and producing an updated list of candidate tags for the video file; establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file. 10. The system for providing top concepts for a video file as in claim 8 , wherein the sets of instructions when further executed by the processor cause the processor to based on the top concepts, determine hot spots in the video file where the top concepts are predominant. | 0.690737 |
11. The system of claim 1 , wherein the luminaire further comprises a processor that executes the interpreter module and is coupled to provide the operating parameters to the drive circuit to thereby control time variation of the relative intensities of the light output from the light channels. | 11. The system of claim 1 , wherein the luminaire further comprises a processor that executes the interpreter module and is coupled to provide the operating parameters to the drive circuit to thereby control time variation of the relative intensities of the light output from the light channels. 12. The system of claim 11 , wherein the processor provides the operating parameters to the drive circuit at a fixed rate while the light channels produce light. | 0.818482 |
17. A method for tracking an individual within a monitored area comprising the following steps: a) forming a first reference facial image signature related to the individual according to a first methodology: b) forming a second reference facial image signature related to the individual according to a second methodology which is different from the first methodology; c) obtaining a current image and a set of subsequent images of the monitored area; d) locating a current facial image of the individual in the current image; e) extracting a first current facial image signature from the current facial image by use of the first methodology; f) comparing the first current facial image signature with the first reference facial image signature to generate a first score; g) extracting a second current facial image signature from the current facial image by use of the second methodology; h) comparing the second current facial image signature with the second reference facial image signature to generate a second score; i) identifying the individual from the first and second scores; and, j) tracking the identified individual from the current image through at least some of the subsequent images. | 17. A method for tracking an individual within a monitored area comprising the following steps: a) forming a first reference facial image signature related to the individual according to a first methodology: b) forming a second reference facial image signature related to the individual according to a second methodology which is different from the first methodology; c) obtaining a current image and a set of subsequent images of the monitored area; d) locating a current facial image of the individual in the current image; e) extracting a first current facial image signature from the current facial image by use of the first methodology; f) comparing the first current facial image signature with the first reference facial image signature to generate a first score; g) extracting a second current facial image signature from the current facial image by use of the second methodology; h) comparing the second current facial image signature with the second reference facial image signature to generate a second score; i) identifying the individual from the first and second scores; and, j) tracking the identified individual from the current image through at least some of the subsequent images. 19. The method of claim 17 wherein the step of forming a second reference facial image signature related to the individual according to a second methodology comprises the step of forming a reference Eigenface signature, wherein the step of extracting a second current facial image signature from the current facial image by use of the second methodology comprises the step of extracting a current image Eigenface signature, and wherein the step of comparing the second current facial image signature with the second reference facial image signature to generate a second score comprises the step of comparing the current image Eigenface signature to the reference Eigenface signature. | 0.613957 |
10. The method of claim 1 , wherein at least one term of the search results is selected from a list of a plurality of suggested terms. | 10. The method of claim 1 , wherein at least one term of the search results is selected from a list of a plurality of suggested terms. 12. The method of claim 10 , wherein the suggested terms are hierarchically ranked in order of a relevance value. | 0.986583 |
1. A computer system implemented method for deploying data science transformations from a development computing environment into a production computing environment, comprising: receiving, with one or more first computing systems, first transformation data representing one or more first transformations defined in a first programming language, the one or more first transformations operable on one or more operands to generate one or more results, wherein the one or more first computing systems are a development computing environment; receiving second transformation data representing one or more second transformations defined in a second programming language, the one or more second transformations operable on the one or more operands to generate the one or more results, wherein each of the one or more second transformations defined in the second programming language mirrors a corresponding one of the one or more first transformations defined in the first programming language, further wherein the second transformation data includes one or more configuration parameters for configuring physical and/or virtual resources to execute one or more transformations; associating the first transformation data with the second transformation data in a transformations data structure to associate the one or more first transformations with the one or more second transformations; storing the transformations data structure to one or more sections of memory associated with the one or more computing systems; receiving macro-transformation data representing a macro-transformation in the first programming language, the macro-transformation being a combination of multiple ones of the one or more first transformations that are logically connected to receive operand data for the macro-transformation and are logically connected to provide output data from the macro-transformation; compiling the first programming language macro-transformation data to generate executable code for the macro-transformation in the second programming language to enable deployment of the macro-transformation into one or more second computing systems while preserving a relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation, wherein compiling the macro-transformation data at least partially includes accessing contents of the transformations data structure that is stored in the one or more sections of memory; and deploying the executable code to the one or more second computing systems to enable the one or more second computing systems to interpret and execute the macro-transformation in the second programming language to provide services to a plurality of users that is at least partially based on a functionality of the macro-transformation, wherein the one or more second computing systems are the production environment. | 1. A computer system implemented method for deploying data science transformations from a development computing environment into a production computing environment, comprising: receiving, with one or more first computing systems, first transformation data representing one or more first transformations defined in a first programming language, the one or more first transformations operable on one or more operands to generate one or more results, wherein the one or more first computing systems are a development computing environment; receiving second transformation data representing one or more second transformations defined in a second programming language, the one or more second transformations operable on the one or more operands to generate the one or more results, wherein each of the one or more second transformations defined in the second programming language mirrors a corresponding one of the one or more first transformations defined in the first programming language, further wherein the second transformation data includes one or more configuration parameters for configuring physical and/or virtual resources to execute one or more transformations; associating the first transformation data with the second transformation data in a transformations data structure to associate the one or more first transformations with the one or more second transformations; storing the transformations data structure to one or more sections of memory associated with the one or more computing systems; receiving macro-transformation data representing a macro-transformation in the first programming language, the macro-transformation being a combination of multiple ones of the one or more first transformations that are logically connected to receive operand data for the macro-transformation and are logically connected to provide output data from the macro-transformation; compiling the first programming language macro-transformation data to generate executable code for the macro-transformation in the second programming language to enable deployment of the macro-transformation into one or more second computing systems while preserving a relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation, wherein compiling the macro-transformation data at least partially includes accessing contents of the transformations data structure that is stored in the one or more sections of memory; and deploying the executable code to the one or more second computing systems to enable the one or more second computing systems to interpret and execute the macro-transformation in the second programming language to provide services to a plurality of users that is at least partially based on a functionality of the macro-transformation, wherein the one or more second computing systems are the production environment. 7. The computer system implemented method of claim 1 , wherein the relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation includes conditional transitions between the multiple ones of the one or more first transformations. | 0.590582 |
1. A method for processing speech, comprising: semantically parsing a received natural language speech input with respect to a plurality of predetermined command grammars in an automated speech processing system; determining with at least one automated processor: if the parsed natural language speech input unambiguously corresponds to a command and comprises information that permits context-dependent statistically reliable processing with respect to completeness, then processing the command and exiting said determining; if the received natural language speech input ambiguously corresponds to a single command or does not comprise information that permits context-dependent statistically reliable processing with respect to completeness, then prompting a user for further natural language speech input to reduce ambiguity or increase completeness, in dependence on a relationship of previously received natural language speech input and at least one command grammar of the plurality of predetermined command grammars, reparsing the further natural language speech input in conjunction with previously parsed natural language speech input, and iterating said determining; and if an abort, fail or cancel condition is present in the natural language speech input; generating a signal by the at least one automated processor in dependence on said determining. | 1. A method for processing speech, comprising: semantically parsing a received natural language speech input with respect to a plurality of predetermined command grammars in an automated speech processing system; determining with at least one automated processor: if the parsed natural language speech input unambiguously corresponds to a command and comprises information that permits context-dependent statistically reliable processing with respect to completeness, then processing the command and exiting said determining; if the received natural language speech input ambiguously corresponds to a single command or does not comprise information that permits context-dependent statistically reliable processing with respect to completeness, then prompting a user for further natural language speech input to reduce ambiguity or increase completeness, in dependence on a relationship of previously received natural language speech input and at least one command grammar of the plurality of predetermined command grammars, reparsing the further natural language speech input in conjunction with previously parsed natural language speech input, and iterating said determining; and if an abort, fail or cancel condition is present in the natural language speech input; generating a signal by the at least one automated processor in dependence on said determining. 7. The method according to claim 1 , wherein said determining is responsive to at least one non-linguistic user input. | 0.626471 |
8. A non-transitory, computer accessible memory medium storing program instructions for modifying a search engine, wherein the program instructions are executable by one or more processors to: create a search engine for a website, wherein said creating the search engine comprises creating search information for a plurality of webpages of the website, wherein the search information specifies a first set of information for each webpage; provide a search-customization user interface for modifying a ranking function of the search engine for the website, wherein the search-customization user interface specifies one or more first ranking factors; after the user inserts one or more first custom tags into source code of at least one webpage of the website, update the search information to include information related to the one or more custom tags, wherein the one or more custom tags are dedicated for customizing the search engine of the web site; provide the search-customization user interface for modifying the ranking function of the search engine for the web site, wherein, in addition to the one or more first ranking factors, the search-customization user interface specifies one or more additional ranking factors corresponding to the one or more first custom tags, wherein each additional ranking factor is added to the search-customization user interface for a respective first custom tag inserted into the source code; receive first user input from the user, wherein the first user input specifies modifying a relative weight of a first additional ranking factor of the one or more additional ranking factors; automatically modify the ranking function of the search engine to use the relative weight of the first additional ranking factor based on the first user input; after automatically modifying the ranking function of the search engine to use the relative weight of the first additional ranking factor, receive a search query for the website; and provide a plurality of search results using the ranking function. | 8. A non-transitory, computer accessible memory medium storing program instructions for modifying a search engine, wherein the program instructions are executable by one or more processors to: create a search engine for a website, wherein said creating the search engine comprises creating search information for a plurality of webpages of the website, wherein the search information specifies a first set of information for each webpage; provide a search-customization user interface for modifying a ranking function of the search engine for the website, wherein the search-customization user interface specifies one or more first ranking factors; after the user inserts one or more first custom tags into source code of at least one webpage of the website, update the search information to include information related to the one or more custom tags, wherein the one or more custom tags are dedicated for customizing the search engine of the web site; provide the search-customization user interface for modifying the ranking function of the search engine for the web site, wherein, in addition to the one or more first ranking factors, the search-customization user interface specifies one or more additional ranking factors corresponding to the one or more first custom tags, wherein each additional ranking factor is added to the search-customization user interface for a respective first custom tag inserted into the source code; receive first user input from the user, wherein the first user input specifies modifying a relative weight of a first additional ranking factor of the one or more additional ranking factors; automatically modify the ranking function of the search engine to use the relative weight of the first additional ranking factor based on the first user input; after automatically modifying the ranking function of the search engine to use the relative weight of the first additional ranking factor, receive a search query for the website; and provide a plurality of search results using the ranking function. 12. The non-transitory, computer accessible memory medium of claim 8 , wherein the first one or more custom tags comprise a tag associated with social endorsements on one or more social networks. | 0.541893 |
1. A method comprising: receiving, by at least one computing device, a defect record associated with a defect; predicting a recommended plain language phrase or word based on a user input from a user and how many times within a predetermined time period a plain language phrase or word has been previously selected in response to the user input being included in a plain language dictionary; predicting the recommended plain language phrase or word based on a synonym of the user input from the user and how many times within the predetermined time period the plain language phrase or word has been selected in response to the user input not being included in the plain language dictionary; providing the recommended plain language phrase or word to classify the defect record; receiving, by the at least one computing device, the recommended plain language phrase or word to describe a type of testing from the user; mapping, by the at least one computing device, the recommended plain language phrase or word to a taxonomy; and classifying, by the at least one computing device, how the defect was at least one of detected and resolved using the taxonomy. | 1. A method comprising: receiving, by at least one computing device, a defect record associated with a defect; predicting a recommended plain language phrase or word based on a user input from a user and how many times within a predetermined time period a plain language phrase or word has been previously selected in response to the user input being included in a plain language dictionary; predicting the recommended plain language phrase or word based on a synonym of the user input from the user and how many times within the predetermined time period the plain language phrase or word has been selected in response to the user input not being included in the plain language dictionary; providing the recommended plain language phrase or word to classify the defect record; receiving, by the at least one computing device, the recommended plain language phrase or word to describe a type of testing from the user; mapping, by the at least one computing device, the recommended plain language phrase or word to a taxonomy; and classifying, by the at least one computing device, how the defect was at least one of detected and resolved using the taxonomy. 2. The method of claim 1 , further comprising: providing information regarding the defect record to the user; and generating the defect record with the recommended plain language phrase or word based on receiving the recommended plain language phrase or word. | 0.614667 |
1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method being implemented by a computer system comprising one or more processors executing one or more computer program instructions that, when executed, perform the method, the method comprising: causing an executable program associated with an ontology to be run, wherein the ontology comprises information indicating attributes for a set of applications; obtaining a domain-specific ontology, wherein the domain-specific ontology is within a domain of interest; obtaining an instance of the ontology, wherein the ontology instance is derived from the domain-specific ontology and comprises information indicating attributes for an application of the set of applications that is within the domain of interest; assigning a freeze to the ontology that disables further modification to the ontology; extracting axiom information from the frozen ontology; using the axiom information to generate a set of logic rules; using the set of logic rules to transform the ontology instance to generate application metadata for the executable program, wherein the application metadata defines one or more functionalities of the application; using the set of logic rules to validate the ontology instance, wherein the application metadata becomes read-only after the validation; and providing the application metadata as input to the executable program, wherein the application metadata, at least in part, causes the one or more functionalities of the application to be made available via the executable program, the executable program executing the one or more functionalities of the application using the definitions of the one or more functionalities in the application metadata, the executable program comprising a set of runtime rules that do not alter the application metadata. | 1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method being implemented by a computer system comprising one or more processors executing one or more computer program instructions that, when executed, perform the method, the method comprising: causing an executable program associated with an ontology to be run, wherein the ontology comprises information indicating attributes for a set of applications; obtaining a domain-specific ontology, wherein the domain-specific ontology is within a domain of interest; obtaining an instance of the ontology, wherein the ontology instance is derived from the domain-specific ontology and comprises information indicating attributes for an application of the set of applications that is within the domain of interest; assigning a freeze to the ontology that disables further modification to the ontology; extracting axiom information from the frozen ontology; using the axiom information to generate a set of logic rules; using the set of logic rules to transform the ontology instance to generate application metadata for the executable program, wherein the application metadata defines one or more functionalities of the application; using the set of logic rules to validate the ontology instance, wherein the application metadata becomes read-only after the validation; and providing the application metadata as input to the executable program, wherein the application metadata, at least in part, causes the one or more functionalities of the application to be made available via the executable program, the executable program executing the one or more functionalities of the application using the definitions of the one or more functionalities in the application metadata, the executable program comprising a set of runtime rules that do not alter the application metadata. 3. The method of claim 1 , wherein the one or more functionalities are made available via the executable program without recompiling the executable program. | 0.631034 |
15. A computer program product embodied in a non-transitory computer readable medium, the non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor, causes the processor to execute a set of acts to implement inserting rules-driven paragraphs into user-designated locations in a document after structural revisions, the set of acts comprising: receiving a set of document construction rules; generating a candidate document at least by instantiating, at a computer aided module stored in computer memory, the candidate document as an instance of a document template and further by positioning a plurality of document components at respective locations in the instance of the document template prior to application of the set of document construction rules that evaluates whether one or more conditions are to be fulfilled, the document template comprising the a plurality of document components, and at least one of the plurality of plurality of document components being a conditional document component associated with at least one document construction rule of the set of document construction rules; forming a document graph for the candidate document based at least in part on the document template, the document graph having a plurality of nodes that represent the plurality of document components and comprise respective document component labels and visibility flags; and applying at least some of the set of document construction rules to the candidate document at least by traversing and annotating the document graph after the candidate document and the document graph are generated; forming a mapping data structure, separate from the document graph, and mapping from the respective document component labels to the respective locations of the plurality of nodes within the document graph with the mapping data structure; and generating a final document from the candidate document at least by rendering the conditional document component in the plurality of document components visible when a first visibility flag of the first conditional document is set to visible and rendering the conditional document component invisible when the first visibility flag of the first conditional document is set to invisible. | 15. A computer program product embodied in a non-transitory computer readable medium, the non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor, causes the processor to execute a set of acts to implement inserting rules-driven paragraphs into user-designated locations in a document after structural revisions, the set of acts comprising: receiving a set of document construction rules; generating a candidate document at least by instantiating, at a computer aided module stored in computer memory, the candidate document as an instance of a document template and further by positioning a plurality of document components at respective locations in the instance of the document template prior to application of the set of document construction rules that evaluates whether one or more conditions are to be fulfilled, the document template comprising the a plurality of document components, and at least one of the plurality of plurality of document components being a conditional document component associated with at least one document construction rule of the set of document construction rules; forming a document graph for the candidate document based at least in part on the document template, the document graph having a plurality of nodes that represent the plurality of document components and comprise respective document component labels and visibility flags; and applying at least some of the set of document construction rules to the candidate document at least by traversing and annotating the document graph after the candidate document and the document graph are generated; forming a mapping data structure, separate from the document graph, and mapping from the respective document component labels to the respective locations of the plurality of nodes within the document graph with the mapping data structure; and generating a final document from the candidate document at least by rendering the conditional document component in the plurality of document components visible when a first visibility flag of the first conditional document is set to visible and rendering the conditional document component invisible when the first visibility flag of the first conditional document is set to invisible. 19. The computer program product of claim 15 , the set of acts further comprising traversing the document graph to output a document instance, the traversing comprising outputting a document component when a corresponding visibility flag is in a first state, and not outputting the document component when the corresponding visibility flag is in a second state. | 0.92527 |
16. An article of manufacture comprising: a non-transitory tangible computer-readable storage medium; and a plurality of programming instructions stored on the storage medium and configured to program an apparatus, in response to execution of the instructions, to: receive a plurality of execution results corresponding to a plurality of query language expressions, the plurality of query language expressions being concurrently executed against a document, and the receiving being contemporaneous with interleaved production of the plurality of execution results; create a plurality of result handles correspondingly associated with the plurality of query language expressions; store at least a first received portion of one of the plurality of execution results in one of the plurality of result handles associated with a corresponding one of the plurality of query language expressions, wherein said storing is contemporaneous with further production of at least a second portion of the one of the plurality of execution results; and upon receiving the second portion of the one of the execution results, and in response to a determination of insufficient space for the second received portion, reserving a new memory block, on the computing device, setting a most recently reserved memory block to point to the new memory block, thereby creating a linked list of reserved memory blocks associated with the one of the plurality of results handles, and store the second portion of one of the plurality of execution results in the new memory block; and store metadata associated with the corresponding one of the plurality of query language expressions and references to the linked list of reserved memory blocks in the one of the plurality of result handles wherein said metadata includes at least an indication of whether result items of the corresponding one of the plurality of query language expressions are homogenous or heterogeneous. | 16. An article of manufacture comprising: a non-transitory tangible computer-readable storage medium; and a plurality of programming instructions stored on the storage medium and configured to program an apparatus, in response to execution of the instructions, to: receive a plurality of execution results corresponding to a plurality of query language expressions, the plurality of query language expressions being concurrently executed against a document, and the receiving being contemporaneous with interleaved production of the plurality of execution results; create a plurality of result handles correspondingly associated with the plurality of query language expressions; store at least a first received portion of one of the plurality of execution results in one of the plurality of result handles associated with a corresponding one of the plurality of query language expressions, wherein said storing is contemporaneous with further production of at least a second portion of the one of the plurality of execution results; and upon receiving the second portion of the one of the execution results, and in response to a determination of insufficient space for the second received portion, reserving a new memory block, on the computing device, setting a most recently reserved memory block to point to the new memory block, thereby creating a linked list of reserved memory blocks associated with the one of the plurality of results handles, and store the second portion of one of the plurality of execution results in the new memory block; and store metadata associated with the corresponding one of the plurality of query language expressions and references to the linked list of reserved memory blocks in the one of the plurality of result handles wherein said metadata includes at least an indication of whether result items of the corresponding one of the plurality of query language expressions are homogenous or heterogeneous. 17. The article of claim 16 , wherein the programming instructions are further configured to cause the apparatus, in response to execution of the programming instructions, to: reclaim the at least one of the plurality of memory blocks individually in response to at least one of the plurality of query language expressions being associated with another result lifetime, and add the reclaimed memory blocks to a list of reclaimed memory blocks. | 0.566756 |
3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. | 3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. 29. The method of claim 3 , further comprising, prior to (C): (D) granting an authorized auditor access to the centralized storage location. | 0.690363 |
11. The method of claim 1 , comprising: determining that a first member of the member network other than the first user has endorsed a particular article in the second plurality of articles, wherein the plurality of article identifiers includes an identifier for the particular article; determining, from among a plurality of different types or degrees of associations between the members in the member network, a particular type or degree of an association in the member network between the first user and the first member; and ranking articles that correspond with the plurality of article identifiers using the particular type or degree of the association in the member network between the first member and the first user, wherein responding to the first search query with the plurality of article identifiers comprises formatting a response in an arrangement that corresponds to the ranking of the articles using the particular type or degree of the association in the member network between the first member and the first user. | 11. The method of claim 1 , comprising: determining that a first member of the member network other than the first user has endorsed a particular article in the second plurality of articles, wherein the plurality of article identifiers includes an identifier for the particular article; determining, from among a plurality of different types or degrees of associations between the members in the member network, a particular type or degree of an association in the member network between the first user and the first member; and ranking articles that correspond with the plurality of article identifiers using the particular type or degree of the association in the member network between the first member and the first user, wherein responding to the first search query with the plurality of article identifiers comprises formatting a response in an arrangement that corresponds to the ranking of the articles using the particular type or degree of the association in the member network between the first member and the first user. 15. The method of claim 11 , comprising: determining a level of the particular type of association in the member network between the first user and the first member, the level indicating a relative strength of the particular type of association between the first user and the first member; and ranking the articles in the plurality of articles using the level of the particular type of association in the member network between the first user and the first member. | 0.80364 |
13. A system, comprising: one or more processors; a memory coupled to the one or more processors, wherein the memory stores program instructions executable by the one or more processors to implement: a compiler receiving source code for a computer program; the compiler determining that the source code includes an assignment context associating a variable with a value, the assignment context having: a declaration expression introducing the variable, wherein the declaration expression specifies a part of a type for the variable and does not specify another part of the type for the variable, wherein: the type for the variable is a parameterized type; the part of the type specified in the declaration expression comprises a ground type; the part of the type not specified in the declaration expression comprises one or more type arguments for the parameterized type; and an initialization expression whose evaluation will result in the value, wherein a type of the initialization expression is a parameterized type corresponding to a given ground type and one or more type arguments; the compiler inferring the type for the variable based at least on the specified part of the type in the parameterized type in the declaration expression and on the parameterized type of the initialization expression, wherein to infer the type for the variable, the compiler: identifies a generic type corresponding to the parameterized type of the initialization expression; identifies a generic supertype of the identified generic type, wherein the identified generic supertype has the same ground type as a ground type indicated by the part of the type for the variable introduced in the declaration expression; and infers a parameterized type for the variable by parameterizing the generic supertype with one or more type arguments of the parameterized type of the initialization expression; in response to said inferring, the compiler binding the variable to the inferred type; and the compiler compiling the source code into an executable version of the computer program, wherein the compiling is dependent on the binding of the variable to the inferred type. | 13. A system, comprising: one or more processors; a memory coupled to the one or more processors, wherein the memory stores program instructions executable by the one or more processors to implement: a compiler receiving source code for a computer program; the compiler determining that the source code includes an assignment context associating a variable with a value, the assignment context having: a declaration expression introducing the variable, wherein the declaration expression specifies a part of a type for the variable and does not specify another part of the type for the variable, wherein: the type for the variable is a parameterized type; the part of the type specified in the declaration expression comprises a ground type; the part of the type not specified in the declaration expression comprises one or more type arguments for the parameterized type; and an initialization expression whose evaluation will result in the value, wherein a type of the initialization expression is a parameterized type corresponding to a given ground type and one or more type arguments; the compiler inferring the type for the variable based at least on the specified part of the type in the parameterized type in the declaration expression and on the parameterized type of the initialization expression, wherein to infer the type for the variable, the compiler: identifies a generic type corresponding to the parameterized type of the initialization expression; identifies a generic supertype of the identified generic type, wherein the identified generic supertype has the same ground type as a ground type indicated by the part of the type for the variable introduced in the declaration expression; and infers a parameterized type for the variable by parameterizing the generic supertype with one or more type arguments of the parameterized type of the initialization expression; in response to said inferring, the compiler binding the variable to the inferred type; and the compiler compiling the source code into an executable version of the computer program, wherein the compiling is dependent on the binding of the variable to the inferred type. 15. The system of claim 13 , wherein the declaration expression includes an indication of a request for the compiler to infer the type for the variable. | 0.689655 |
24. A computer-readable storage medium having executable instructions to cause a processor to perform a method comprising: displaying a set of markup language template objects, the set comprising default and user-defined markup language template objects; generating a markup language object from multiple selected markup language template objects; modifying a property value in response to input data, the property value associated with the selected markup language template object; and regenerating the markup language object using the modified property value. | 24. A computer-readable storage medium having executable instructions to cause a processor to perform a method comprising: displaying a set of markup language template objects, the set comprising default and user-defined markup language template objects; generating a markup language object from multiple selected markup language template objects; modifying a property value in response to input data, the property value associated with the selected markup language template object; and regenerating the markup language object using the modified property value. 25. The computer-readable storage medium of claim 24 , wherein the default and user defined markup language template objects are displayed separately. | 0.534901 |
7. A method for specifying a new Online Analytical Processing (OLAP) cube from an OLAP cube template, the method comprising: determining, by a computer system, the OLAP cube template; retrieving a corresponding template metadata file, the template metadata file including metadata defining the structure of the OLAP cube template; receiving rules for data access, storing the rules, and determining, based on the rules, whether a user has access to a dimension or a level in the dimension in the new OLAP cube, and the rules specify modifiable aspects of dimensions of the new OLAP cube, wherein the rules include a rule specifying that predetermined levels of the dimension must stay grouped in a view; creating a base metadata file from the template metadata file; generating viable options for modifying metadata in the base metadata file to define the new OLAP cube, wherein the viable options for modifying metadata in the base metadata file conforms with the rules; presenting the viable options to the user; receiving input from the user indicating a modification to the metadata in the base metadata file based on the presented viable options; and storing the modified base metadata file as a new metadata file defining the new OLAP cube. | 7. A method for specifying a new Online Analytical Processing (OLAP) cube from an OLAP cube template, the method comprising: determining, by a computer system, the OLAP cube template; retrieving a corresponding template metadata file, the template metadata file including metadata defining the structure of the OLAP cube template; receiving rules for data access, storing the rules, and determining, based on the rules, whether a user has access to a dimension or a level in the dimension in the new OLAP cube, and the rules specify modifiable aspects of dimensions of the new OLAP cube, wherein the rules include a rule specifying that predetermined levels of the dimension must stay grouped in a view; creating a base metadata file from the template metadata file; generating viable options for modifying metadata in the base metadata file to define the new OLAP cube, wherein the viable options for modifying metadata in the base metadata file conforms with the rules; presenting the viable options to the user; receiving input from the user indicating a modification to the metadata in the base metadata file based on the presented viable options; and storing the modified base metadata file as a new metadata file defining the new OLAP cube. 10. The method of claim 7 , further comprising: performing subsequent operations on the new OLAP cube. | 0.921254 |
6. The text messaging system of claim 1 , wherein the abbreviation personality library includes a plurality of message destinations associated with a group of members, and an abbreviation library based on preferences of the group members. | 6. The text messaging system of claim 1 , wherein the abbreviation personality library includes a plurality of message destinations associated with a group of members, and an abbreviation library based on preferences of the group members. 7. The text messaging system of claim 6 , wherein the abbreviation personality library includes abbreviations to be avoided for at least one message recipient. | 0.894737 |
8. A method implemented on a machine that provides multilingual capabilities for text based chat rooms, comprising: receiving, by one or more servers, a message from a first client; ascertaining that the message is written in a first language; temporarily persisting, using the one or more servers, the message in a first queue such that the message is monitored periodically to be dispatched for translation, the first queue being specific to the first language; translating, using the one or more servers, the first language of the message into a second language; and supplying, using the one or more servers, the message in the second language to a second queue for subsequent delivery to a second client, the second queue being specific to the second language. | 8. A method implemented on a machine that provides multilingual capabilities for text based chat rooms, comprising: receiving, by one or more servers, a message from a first client; ascertaining that the message is written in a first language; temporarily persisting, using the one or more servers, the message in a first queue such that the message is monitored periodically to be dispatched for translation, the first queue being specific to the first language; translating, using the one or more servers, the first language of the message into a second language; and supplying, using the one or more servers, the message in the second language to a second queue for subsequent delivery to a second client, the second queue being specific to the second language. 9. The method of claim 8 , further comprising awaiting a request from the second client prior to releasing the message in the second language stored in the second queue to the second client, the message in the second language displayed on the second client in the second language. | 0.602437 |
1. A data processing method comprising: receiving, at a server computer, an electronic document comprising a plurality of unknown-language data elements each associated with one or more types; based on a document schema of the document, selecting one or more unknown-language data elements from the plurality of unknown-language data elements; assigning to each of the one or more unknown-language data elements a corresponding weight value based on a respective type of the unknown-language data element; comparing the one or more unknown-language data elements with a plurality of known-language data elements that are associated with the document schema; based on the comparing, determining a number of unknown-language data elements in the one or more unknown-language data elements that matched any in a subset of the plurality of known-language data elements, wherein the subset of known-language data elements corresponds to a particular language; based on the number of unknown-language data elements in the one or more unknown-language data elements that matched to the subset of known-language data elements and based on the corresponding weight value assigned to each unknown-language data element in the number of unknown-language data elements, determining a language confidence level value specifying a level of machine confidence that the document is expressed in the particular language; based on the language confidence level value for the particular language exceeding a language threshold value, automatically processing the document using the particular language. | 1. A data processing method comprising: receiving, at a server computer, an electronic document comprising a plurality of unknown-language data elements each associated with one or more types; based on a document schema of the document, selecting one or more unknown-language data elements from the plurality of unknown-language data elements; assigning to each of the one or more unknown-language data elements a corresponding weight value based on a respective type of the unknown-language data element; comparing the one or more unknown-language data elements with a plurality of known-language data elements that are associated with the document schema; based on the comparing, determining a number of unknown-language data elements in the one or more unknown-language data elements that matched any in a subset of the plurality of known-language data elements, wherein the subset of known-language data elements corresponds to a particular language; based on the number of unknown-language data elements in the one or more unknown-language data elements that matched to the subset of known-language data elements and based on the corresponding weight value assigned to each unknown-language data element in the number of unknown-language data elements, determining a language confidence level value specifying a level of machine confidence that the document is expressed in the particular language; based on the language confidence level value for the particular language exceeding a language threshold value, automatically processing the document using the particular language. 6. The method of claim 1 , further comprising: storing the plurality of known-language data elements associated with the document schema of the document in a data store in a plurality of language sets of known-language data elements, each set of known-language data elements corresponding to a supported language in a plurality of supported languages that includes the particular language; comparing the one or more unknown-language data elements with one or more known-language data elements in said each set of known-language data elements to determine corresponding number of unknown-language data elements that matched for the corresponding supported language. | 0.595957 |
15. The method of claim 13 , wherein said selecting search template comprises presenting each of said plurality of search templates with a user provided ranking. | 15. The method of claim 13 , wherein said selecting search template comprises presenting each of said plurality of search templates with a user provided ranking. 16. The method of claim 15 , wherein said plurality of search templates are presented in descending order according to said user provided ranking. | 0.953715 |
7. A semantic sensing system comprising: a first sensing entity and a second sensing entity; a semantic engine coupled with the first sensing entity and the second sensing entity; a memory associated with the semantic engine, the memory storing a plurality of semantics; the memory further storing a plurality of rules comprising: a first semantic inference rule associating data from the first sensing entity with a first semantic; a second semantic inference rule associating data from the second sensing entity with a second semantic; a third semantic inference rule for a composite semantic indicating that the composite semantic is a combination of the first and the second semantic; a plurality of access control rules, each of the plurality of access control rules associating at least one time interval and at least one semantic from among the plurality of semantics stored in the memory with an access control action; the semantic engine being configured to interpret the plurality of rules; the semantic engine further being configured to perform the access control action by: inferring the first semantic based on an input from the first sensing entity at a first time and the first semantic inference rule; inferring the second semantic based on an input from the second sensing entity at a second time and the second semantic inference rule, wherein the second semantic is further inferred based on an external input; inferring the composite semantic based on the first and the second semantics and the third semantic inference rule; identifying a first access control rule from among the plurality of access control rules applicable to the composite semantic and performing the access control action associated with the first access control rule. | 7. A semantic sensing system comprising: a first sensing entity and a second sensing entity; a semantic engine coupled with the first sensing entity and the second sensing entity; a memory associated with the semantic engine, the memory storing a plurality of semantics; the memory further storing a plurality of rules comprising: a first semantic inference rule associating data from the first sensing entity with a first semantic; a second semantic inference rule associating data from the second sensing entity with a second semantic; a third semantic inference rule for a composite semantic indicating that the composite semantic is a combination of the first and the second semantic; a plurality of access control rules, each of the plurality of access control rules associating at least one time interval and at least one semantic from among the plurality of semantics stored in the memory with an access control action; the semantic engine being configured to interpret the plurality of rules; the semantic engine further being configured to perform the access control action by: inferring the first semantic based on an input from the first sensing entity at a first time and the first semantic inference rule; inferring the second semantic based on an input from the second sensing entity at a second time and the second semantic inference rule, wherein the second semantic is further inferred based on an external input; inferring the composite semantic based on the first and the second semantics and the third semantic inference rule; identifying a first access control rule from among the plurality of access control rules applicable to the composite semantic and performing the access control action associated with the first access control rule. 30. The system of claim 7 , wherein the system defines a semantic group comprising at least one of the first sensing entity and the second sensing entity based on the composite semantic. | 0.523736 |
1. A clustering apparatus comprising: an input unit configured to input at least one phonemic model attached with determination information indicating a small amount of speech data for training, and at least one phonemic model not attached with the determination information; a node initializing unit configured to generate a node including the inputted phonemic models as a root node of a tree structure; a candidate generating unit configured to generate candidates of a pair of child sets for a node having no child node among nodes in the tree structure, by partitioning a set of phonemic models included in the node into two; a candidate deleting unit configured to delete a candidate including the two child sets at least one of which includes only phonemic models attached with the determination information, from the generated candidates; a similarity calculating unit configured to calculate a similarity among the phonemic models included in each of the two child sets included in each of the candidates other than the deleted candidates, and calculates a sum of the similarities calculated for the child sets; a candidate selecting unit configured to select one of the candidates having a largest calculated sum; a node generating unit configured to generate two nodes including two child sets included in the selected candidate, respectively, as child nodes of the node that is a generation source of the selected candidate; and a clustering unit configured to cluster the phonemic models in units of phonemic model sets included in nodes of the tree structure. | 1. A clustering apparatus comprising: an input unit configured to input at least one phonemic model attached with determination information indicating a small amount of speech data for training, and at least one phonemic model not attached with the determination information; a node initializing unit configured to generate a node including the inputted phonemic models as a root node of a tree structure; a candidate generating unit configured to generate candidates of a pair of child sets for a node having no child node among nodes in the tree structure, by partitioning a set of phonemic models included in the node into two; a candidate deleting unit configured to delete a candidate including the two child sets at least one of which includes only phonemic models attached with the determination information, from the generated candidates; a similarity calculating unit configured to calculate a similarity among the phonemic models included in each of the two child sets included in each of the candidates other than the deleted candidates, and calculates a sum of the similarities calculated for the child sets; a candidate selecting unit configured to select one of the candidates having a largest calculated sum; a node generating unit configured to generate two nodes including two child sets included in the selected candidate, respectively, as child nodes of the node that is a generation source of the selected candidate; and a clustering unit configured to cluster the phonemic models in units of phonemic model sets included in nodes of the tree structure. 2. The apparatus according to claim 1 , wherein the input unit inputs at least one phonemic model attached with language determination information indicating a language having a small amount of the speech data as the determination information, and at least one phonemic model not attached with the language determination information, and the candidate deleting unit deletes a candidate including the two child sets at least one of which includes only phonemic models attached with the language determination information, from the generated candidates. | 0.5 |
1. A method for transcribing a spoken communication, comprising: receiving a spoken first communication from a first sender to a first recipient; obtaining information relating to a second communication from a second sender to a second recipient, wherein the second communication was made before the spoken first communication and is different from the spoken first communication; using the obtained information to create a final language model by: obtaining a general language model; using the obtained information to create a specific language model; and creating the final language model using the general language model and the specific language model; and using the language model to transcribe the spoken first communication. | 1. A method for transcribing a spoken communication, comprising: receiving a spoken first communication from a first sender to a first recipient; obtaining information relating to a second communication from a second sender to a second recipient, wherein the second communication was made before the spoken first communication and is different from the spoken first communication; using the obtained information to create a final language model by: obtaining a general language model; using the obtained information to create a specific language model; and creating the final language model using the general language model and the specific language model; and using the language model to transcribe the spoken first communication. 2. The method of claim 1 , wherein the first communication is a voicemail message left by the first sender for the first recipient. | 0.62779 |
7. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at the local computing system that comprises an enterprise computing system from a remote computing system that executes a hosted application, one or more configuration tables defining a predefined query scenario for querying and retrieving data from the hosted application for data stored on a database table; replicating a database table from a main database to a secondary database, the main database comprising updated data relative to data contained in the database table of the secondary database, the secondary database comprising an in-memory and the main database comprising a magnetic memory; receiving, at the local computing system, a query from the enterprise application for data stored on the database table, the query comprising a query return time and a context; comparing the context of the query to a context of the predefined query scenario, the context of the query comprising at least one of a database table name, a scenario application name or a scenario job name; based on the context of the query matching the context of the predefined query scenario, retrieving data stored on the secondary database replicated from data stored on the main database; and passing the retrieved data from the secondary database to the enterprise application. | 7. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at the local computing system that comprises an enterprise computing system from a remote computing system that executes a hosted application, one or more configuration tables defining a predefined query scenario for querying and retrieving data from the hosted application for data stored on a database table; replicating a database table from a main database to a secondary database, the main database comprising updated data relative to data contained in the database table of the secondary database, the secondary database comprising an in-memory and the main database comprising a magnetic memory; receiving, at the local computing system, a query from the enterprise application for data stored on the database table, the query comprising a query return time and a context; comparing the context of the query to a context of the predefined query scenario, the context of the query comprising at least one of a database table name, a scenario application name or a scenario job name; based on the context of the query matching the context of the predefined query scenario, retrieving data stored on the secondary database replicated from data stored on the main database; and passing the retrieved data from the secondary database to the enterprise application. 12. The computer storage medium of any claim 7 , wherein the secondary database comprises an in-memory database that comprises volatile RAM memory, and the main database comprises magnetic memory. | 0.62327 |
1. A broadcast system for broadcasting to a plurality of client receivers, comprising: a carousel configured to make iTV pages available; and an apparatus configured to provide data to the carousel, the apparatus including a content provider apparatus having a user interface configured to define a plurality of information templates, the information templates including a content for iTV pages, a composition provider apparatus having a user interface configured to define a plurality of presentation templates, the presentation templates specifying a presentational appearance for iTV pages, an editor having a user interface configured to receive a direct user association of a presentation template with an information template, and processor configured to modify said information template by modifying the content of the information template in accordance with at least one requirement of the associated presentation template, the processor being configured to output, to the carousel, both the presentation template and the modified information template, wherein both the presentation template and the modified information template are provided to the plurality of client receivers by the carousel, an iTV page being obtained from the carousel by displaying the content specified by the modified information template with the presentation appearance specified by the presentation template. | 1. A broadcast system for broadcasting to a plurality of client receivers, comprising: a carousel configured to make iTV pages available; and an apparatus configured to provide data to the carousel, the apparatus including a content provider apparatus having a user interface configured to define a plurality of information templates, the information templates including a content for iTV pages, a composition provider apparatus having a user interface configured to define a plurality of presentation templates, the presentation templates specifying a presentational appearance for iTV pages, an editor having a user interface configured to receive a direct user association of a presentation template with an information template, and processor configured to modify said information template by modifying the content of the information template in accordance with at least one requirement of the associated presentation template, the processor being configured to output, to the carousel, both the presentation template and the modified information template, wherein both the presentation template and the modified information template are provided to the plurality of client receivers by the carousel, an iTV page being obtained from the carousel by displaying the content specified by the modified information template with the presentation appearance specified by the presentation template. 4. The broadcast system according to claim 1 wherein: the editor is configured to define a plurality of links for information templates to identify other information templates; the processor is configured to provide, in the corresponding modified information templates, the links and a plurality of tags identifying respective links; and the composition provider apparatus is configured to define presentation templates having corresponding tags associated with a plurality of representations of operating keys such that, for a resulting iTV page, an operation of an operating key of a client receiver is configured to cause movement to another information template according to the link identified by the tag associated with the operating key. | 0.5 |
34. A method comprising: specifying a class network having a class, wherein a membership function defines whether an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; receiving pixel values obtained from a digital image; receiving metadata relating to the digital image; and executing the class network and the process hierarchy on a computer that implements the data network by selectively linking a plurality of objects to the pixel values and to the metadata according to the class network and the process hierarchy, wherein the process step is linked to the metadata. | 34. A method comprising: specifying a class network having a class, wherein a membership function defines whether an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; receiving pixel values obtained from a digital image; receiving metadata relating to the digital image; and executing the class network and the process hierarchy on a computer that implements the data network by selectively linking a plurality of objects to the pixel values and to the metadata according to the class network and the process hierarchy, wherein the process step is linked to the metadata. 42. The method of claim 34 , wherein the executing that implements the data network comprises performing the algorithm on each object of the plurality of objects that belongs to the class, and wherein the performing the algorithm yields a result, further comprising: determining based on the result whether the objects that belong to the class depict a target region on the digital image; and repeatedly respecifying the class network and performing the algorithm until the objects that belong to the class depict the target region. | 0.573551 |
1. A method of generating a representation of a plurality of learned rules from a learning engine of an application firewall based on a history of uniform resource locator (URL) communications with a web server, the method comprising: a) determining, by a learning engine of an application firewall, a plurality of learned rules based on a history of URL communications with a web server, each of the plurality of learned rules assigned a URL string; b) categorizing, by a visualizer, a subset of the plurality of learned rules under a first check type of a plurality of check types; c) generating, by the visualizer, a first tree representation of URL strings of the subset of learned rules, each node of the first tree corresponding to a segment of the URL strings identified based on application of a first selected delimiter to the URL strings to segment the URL strings into a first plurality of segments, each URL string comprising a path to a resource and comprising multiple segments identified based on application of the first selected delimiter; d) changing, via the visualizer responsive to a user operating the visualizer, the first delimiter to a second selected delimiter for the same URL strings of the subset of learned rules; and e) generating, by the visualizer, a second tree representation of the same URL strings responsive to the change to the second selected delimiter, each node of the second tree corresponding to a segment of the URL strings identified based on application of the second selected delimiter to the URL strings to segment the URL strings into a second plurality of segments, the change allowing a visual comparison of hierarchical distributions of the first plurality of segments and the second plurality of segments between the first tree and the second tree, and distributions of the subset of learned rules corresponding to the first plurality of segments and the second plurality of segments. | 1. A method of generating a representation of a plurality of learned rules from a learning engine of an application firewall based on a history of uniform resource locator (URL) communications with a web server, the method comprising: a) determining, by a learning engine of an application firewall, a plurality of learned rules based on a history of URL communications with a web server, each of the plurality of learned rules assigned a URL string; b) categorizing, by a visualizer, a subset of the plurality of learned rules under a first check type of a plurality of check types; c) generating, by the visualizer, a first tree representation of URL strings of the subset of learned rules, each node of the first tree corresponding to a segment of the URL strings identified based on application of a first selected delimiter to the URL strings to segment the URL strings into a first plurality of segments, each URL string comprising a path to a resource and comprising multiple segments identified based on application of the first selected delimiter; d) changing, via the visualizer responsive to a user operating the visualizer, the first delimiter to a second selected delimiter for the same URL strings of the subset of learned rules; and e) generating, by the visualizer, a second tree representation of the same URL strings responsive to the change to the second selected delimiter, each node of the second tree corresponding to a segment of the URL strings identified based on application of the second selected delimiter to the URL strings to segment the URL strings into a second plurality of segments, the change allowing a visual comparison of hierarchical distributions of the first plurality of segments and the second plurality of segments between the first tree and the second tree, and distributions of the subset of learned rules corresponding to the first plurality of segments and the second plurality of segments. 9. The method of claim 1 , wherein step (c) further comprises determining, by the visualizer for the first tree representation, a regular expression representative of URL strings of learned rules associated with a node. | 0.624638 |
14. The system of claim 10 , further comprising: a user device and a computer storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving from the data processing apparatus the command models for the action; receiving an input sentence of n-grams; applying the command models to the input sentence of n-grams to generate respective action scores; determining, from the command models, an action invoked by the input sentence based on the action scores, the action being one of the actions in the set of actions; and performing the action. | 14. The system of claim 10 , further comprising: a user device and a computer storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving from the data processing apparatus the command models for the action; receiving an input sentence of n-grams; applying the command models to the input sentence of n-grams to generate respective action scores; determining, from the command models, an action invoked by the input sentence based on the action scores, the action being one of the actions in the set of actions; and performing the action. 15. The system of claim 14 , wherein: each command model is a grammar rule model; and applying the command models to the input sentence of n-grams comprises, for each grammar rule model, parsing the input sentence of n-grams. | 0.923597 |
1. An electronic medical record management system for generating an electronic medical document based on a specific context from among a plurality of contexts within which an event may be documented, the system comprising: means for providing one or more headings and a selection of available subheadings corresponding to each of the one or more headings; means for receiving requests from one or more users to enter content under one or more of the selection of available subheadings corresponding to at least one of the one or more headings; means for converting each of the one or more available subheadings for which a request to enter content has been received into a corresponding one of one or more selected subheadings; means for receiving requests from the one or more users to associate at least one of a plurality of contexts with the one or more selected subheadings and headings; and means for generating an electronic medical document including the entered content and the corresponding selected subheadings and headings that are associated with a specific context from among the plurality of contexts. | 1. An electronic medical record management system for generating an electronic medical document based on a specific context from among a plurality of contexts within which an event may be documented, the system comprising: means for providing one or more headings and a selection of available subheadings corresponding to each of the one or more headings; means for receiving requests from one or more users to enter content under one or more of the selection of available subheadings corresponding to at least one of the one or more headings; means for converting each of the one or more available subheadings for which a request to enter content has been received into a corresponding one of one or more selected subheadings; means for receiving requests from the one or more users to associate at least one of a plurality of contexts with the one or more selected subheadings and headings; and means for generating an electronic medical document including the entered content and the corresponding selected subheadings and headings that are associated with a specific context from among the plurality of contexts. 2. The record management system of claim 1 further comprising means for directly entering quantitative information into said electronic document. | 0.68232 |
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. 2. The computer implemented method as claimed in claim 1 , wherein the providing further comprises ordering the plurality of keyword results based on relevance with the one or more textual characters. | 0.571616 |
10. A computer-readable storage medium for storing computer-readable instructions to instruct a processor of a processing system to execute a computer implemented method of providing a user interface for a search method, the search method aided by a set of topics, the topics not necessarily having a hierarchy, each topic having at least one attachment to at least one information item of a plurality of information items, the method comprising: causing a first user interface to be displayed to a first searcher, the user interface providing for the searcher to input search request information including at least one of the group consisting of a search phrase and a subset of one or more search topics of the set of topics; carrying out the search method, the search method including: accepting the search request information input by the first searcher; identifying one or more information items of the plurality of information items according to the accepted search request information; and determining one or more suggested topics from the set of topics, the suggested topics being determined according to the attachments of the suggested topics to the one or more identified information items; and as a result of carrying out the search method, causing a second user interface to be displayed to the first searcher, the second user interface including at least some of the identified information items and at least one of the suggested topics, the second user interface providing for the first searcher the ability to select one of the suggested topics, wherein the suggested topics include one or more refinement topics determined from the set of topics according to a refinement topic criterion using a refinement selection method, such that the first searcher selecting one of the suggested topics using the displayed second user interface generates additional results. | 10. A computer-readable storage medium for storing computer-readable instructions to instruct a processor of a processing system to execute a computer implemented method of providing a user interface for a search method, the search method aided by a set of topics, the topics not necessarily having a hierarchy, each topic having at least one attachment to at least one information item of a plurality of information items, the method comprising: causing a first user interface to be displayed to a first searcher, the user interface providing for the searcher to input search request information including at least one of the group consisting of a search phrase and a subset of one or more search topics of the set of topics; carrying out the search method, the search method including: accepting the search request information input by the first searcher; identifying one or more information items of the plurality of information items according to the accepted search request information; and determining one or more suggested topics from the set of topics, the suggested topics being determined according to the attachments of the suggested topics to the one or more identified information items; and as a result of carrying out the search method, causing a second user interface to be displayed to the first searcher, the second user interface including at least some of the identified information items and at least one of the suggested topics, the second user interface providing for the first searcher the ability to select one of the suggested topics, wherein the suggested topics include one or more refinement topics determined from the set of topics according to a refinement topic criterion using a refinement selection method, such that the first searcher selecting one of the suggested topics using the displayed second user interface generates additional results. 12. A storage medium as recited in claim 10 wherein the first user interface and the second user interface are a first webpage and a second webpage, respectively. | 0.539548 |
25. The medium of claim 24 , further comprising: converting each of the plurality of speech signals to the plurality of words using a specific secondary vocabulary application. | 25. The medium of claim 24 , further comprising: converting each of the plurality of speech signals to the plurality of words using a specific secondary vocabulary application. 26. The medium of claim 25 , further comprising: using a natural language understanding process for recognizing the converted words. | 0.954693 |
12. The information processing system of claim 11 further comprising: providing tooling on the user interface to enable user manipulation of the search-based content. | 12. The information processing system of claim 11 further comprising: providing tooling on the user interface to enable user manipulation of the search-based content. 16. The information processing system of claim 12 further comprising providing a digital image associated with the ranked object, wherein the search-based content is displayed upon selection of said digital image. | 0.888889 |
23. An information retrieval system comprising: a processor coupled to a computer readable medium having instructions stored thereon, wherein the processor executing the instructions implements modules comprising: an interface module that receives at least one search term and searches a plurality of text documents, wherein each text document is associated with one or more salient terms extracted from the document and each text document is associated with one or more properties that represent the one or more extracted salient terms; a database access module that retrieve a first set of retrieved documents from a query of the plurality of text documents, wherein each of the retrieved documents comprises the search term; a matching module that retrieves the associated salient terms for each of the retrieved documents and the associated properties; a clustering module that groups based on a distance metric the retrieved salient terms into one or more clusters of salient terms and provides the clusters of salient terms to the user, wherein each of the cluster of salient terms corresponds to one of the properties associated with the retrieved documents and each cluster displays the associated salient terms; the interface module that receives a selection of a first cluster of the clusters of salient terms from the user, wherein the first cluster comprises first salient terms; the matching module selecting a second set of retrieved documents from the first set of retrieved documents, wherein each second set document of the second set includes at least one of the first salient terms of the first cluster of salient terms; further comprising retrieving associated second salient terms for each of the second set documents; and grouping the second salient terms into one or more second clusters of salient terms and providing the second clusters of salient terms to the user. | 23. An information retrieval system comprising: a processor coupled to a computer readable medium having instructions stored thereon, wherein the processor executing the instructions implements modules comprising: an interface module that receives at least one search term and searches a plurality of text documents, wherein each text document is associated with one or more salient terms extracted from the document and each text document is associated with one or more properties that represent the one or more extracted salient terms; a database access module that retrieve a first set of retrieved documents from a query of the plurality of text documents, wherein each of the retrieved documents comprises the search term; a matching module that retrieves the associated salient terms for each of the retrieved documents and the associated properties; a clustering module that groups based on a distance metric the retrieved salient terms into one or more clusters of salient terms and provides the clusters of salient terms to the user, wherein each of the cluster of salient terms corresponds to one of the properties associated with the retrieved documents and each cluster displays the associated salient terms; the interface module that receives a selection of a first cluster of the clusters of salient terms from the user, wherein the first cluster comprises first salient terms; the matching module selecting a second set of retrieved documents from the first set of retrieved documents, wherein each second set document of the second set includes at least one of the first salient terms of the first cluster of salient terms; further comprising retrieving associated second salient terms for each of the second set documents; and grouping the second salient terms into one or more second clusters of salient terms and providing the second clusters of salient terms to the user. 27. The system of claim 23 , further comprising, after selecting the second set of retrieved documents, iteratively repeating the retrieving the associated salient terms, grouping the retrieved salient terms into one or more clusters of salient terms, receiving the selection of a first cluster, and selecting a second set of retrieved documents in response to additional selections of a cluster by the user. | 0.5 |
8. The system as recited in claim 1 further comprising a dialer to thereby allow said system to place outbound calls to a third party. | 8. The system as recited in claim 1 further comprising a dialer to thereby allow said system to place outbound calls to a third party. 9. The system as recited in claim 8 wherein said dialer is a predictive dialer. | 0.977434 |
10. A method for prepending nonce labels to DNS queries, the method comprising: evaluating whether a log contains at least one nonce label prepended domain name resolution query for a full domain name that resulted in a non-referral response, upon determination that a predetermined time duration has expired; determining, with a processor, whether the log contains a nonce-less domain name resolution query for the full domain name; and the processor flagging the full domain name as being exempt from nonce label prepending, upon determination that the log contains the nonce-less domain name resolution query. | 10. A method for prepending nonce labels to DNS queries, the method comprising: evaluating whether a log contains at least one nonce label prepended domain name resolution query for a full domain name that resulted in a non-referral response, upon determination that a predetermined time duration has expired; determining, with a processor, whether the log contains a nonce-less domain name resolution query for the full domain name; and the processor flagging the full domain name as being exempt from nonce label prepending, upon determination that the log contains the nonce-less domain name resolution query. 11. The method of claim 10 , wherein the log is a DNS resolver log. | 0.757899 |
1. A control device that can be connected to and controls a recording device that records on a recording medium and stores a plurality of font groups each storing font data for a plurality of characters used to record text on the recording medium, the control device comprising a processor and a non-transitory computer readable medium having code executable by the processor, the control device comprising: a table processing unit that creates or updates a character code conversion table that correlates each of a plurality of universal character codes that are rendered in a single font group and are specified from the control device side to information identifying a font group on the recording device side containing font data corresponding to the universal character code and information denoting the storage address of the font data in the font group; and a conversion processing unit that, when a recording job instructing the recording device to record a character is asserted, converts a universal character code contained in the recording job to a font data address based on the character code conversion table created or updated by the table processing unit. | 1. A control device that can be connected to and controls a recording device that records on a recording medium and stores a plurality of font groups each storing font data for a plurality of characters used to record text on the recording medium, the control device comprising a processor and a non-transitory computer readable medium having code executable by the processor, the control device comprising: a table processing unit that creates or updates a character code conversion table that correlates each of a plurality of universal character codes that are rendered in a single font group and are specified from the control device side to information identifying a font group on the recording device side containing font data corresponding to the universal character code and information denoting the storage address of the font data in the font group; and a conversion processing unit that, when a recording job instructing the recording device to record a character is asserted, converts a universal character code contained in the recording job to a font data address based on the character code conversion table created or updated by the table processing unit. 6. The control device described in claim 1 , further comprising: a font group information update processing unit that gets information identifying a plurality of font groups stored in the recording device from the recording device, and updates the font group information according to the plural font groups. | 0.786373 |
5. The apparatus of claim 1 , wherein the instructions are executable by the processor to: deliver a request for clarification of the spoken command. | 5. The apparatus of claim 1 , wherein the instructions are executable by the processor to: deliver a request for clarification of the spoken command. 6. The apparatus of claim 5 , wherein the request for clarification includes an audible message. | 0.966389 |
1. A method of performing speech recognition that is performed by one or more computers of an automated speech recognizer, the method comprising: receiving, by the one or more computers, data that indicates multiple candidate transcriptions for an utterance, wherein the one or more computers are in communication with (i) a first search system that provides a search service of a first domain, and (ii) a second search system that provides a search service for a second domain, the second domain being different from the first domain; for each particular candidate transcription of the candidate transcriptions: receiving, by the one or more computers, data from the first search system that provides the search service for the first domain, the data from the first search system indicating first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a first score based on the first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; receiving, by the one or more computers, data from the second search system that provides the search service for the second domain, the data from the second search system indicating second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a second score based on the second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; providing, by the one or more computers, (i) the first score that is determined based on the first search results and (ii) the second score that is determined based on the second search results as input to a classifier, wherein the classifier has been trained, using scores that represent characteristics of different search results from different domains, to indicate a likelihood that a transcription is correct based on scores for multiple different domains; and receiving, by the one or more computers and from the trained classifier, a classifier output in response to at least the first score and the second score, the classifier output indicating a likelihood that the particular candidate transcription is correct; selecting, by the one or more computers, a transcription for the utterance, from among the multiple candidate transcriptions, based on the classifier outputs; and providing, by the one or more computers, the transcription as output of the automated speech recognizer. | 1. A method of performing speech recognition that is performed by one or more computers of an automated speech recognizer, the method comprising: receiving, by the one or more computers, data that indicates multiple candidate transcriptions for an utterance, wherein the one or more computers are in communication with (i) a first search system that provides a search service of a first domain, and (ii) a second search system that provides a search service for a second domain, the second domain being different from the first domain; for each particular candidate transcription of the candidate transcriptions: receiving, by the one or more computers, data from the first search system that provides the search service for the first domain, the data from the first search system indicating first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a first score based on the first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; receiving, by the one or more computers, data from the second search system that provides the search service for the second domain, the data from the second search system indicating second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a second score based on the second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; providing, by the one or more computers, (i) the first score that is determined based on the first search results and (ii) the second score that is determined based on the second search results as input to a classifier, wherein the classifier has been trained, using scores that represent characteristics of different search results from different domains, to indicate a likelihood that a transcription is correct based on scores for multiple different domains; and receiving, by the one or more computers and from the trained classifier, a classifier output in response to at least the first score and the second score, the classifier output indicating a likelihood that the particular candidate transcription is correct; selecting, by the one or more computers, a transcription for the utterance, from among the multiple candidate transcriptions, based on the classifier outputs; and providing, by the one or more computers, the transcription as output of the automated speech recognizer. 10. The method of claim 1 , wherein the trained classifier has been trained using (i) a first set of scores corresponding to first features relevant to the first domain and (ii) a second set of feature scores for second features relevant to the second domain, wherein at least some of the second features are different from the first features. | 0.684272 |
11. Apparatus for distributing secure digital content that can be indexed by third party search engines, the apparatus comprising: a stripper that generates a text stream from the digital content by stripping all graphic information and punctuation from the digital content; means for fragmenting the text stream into multi-word phrases that are each contained in the digital content; a stream assembler that randomly assembles the phrases into a scrambled document such that the scrambled document contains at least nearly all of the words and at least most of the phrases as are contained in the digital content; and means for making the scrambled document available to third party search engines to permit indexing of the scrambled document that will result in an index that is comparable to an index that would result if the third party search engine indexed the digital content. | 11. Apparatus for distributing secure digital content that can be indexed by third party search engines, the apparatus comprising: a stripper that generates a text stream from the digital content by stripping all graphic information and punctuation from the digital content; means for fragmenting the text stream into multi-word phrases that are each contained in the digital content; a stream assembler that randomly assembles the phrases into a scrambled document such that the scrambled document contains at least nearly all of the words and at least most of the phrases as are contained in the digital content; and means for making the scrambled document available to third party search engines to permit indexing of the scrambled document that will result in an index that is comparable to an index that would result if the third party search engine indexed the digital content. 16. The apparatus of claim 11 further comprising means for returning the scrambled document content when the scrambled document is indexed by the third party search engines. | 0.554338 |
2. The electronic device of claim 1 , wherein the first section that includes a section from a time of detecting the voice signal to a predetermined time required for a formation the beamforming direction corresponding to the direction of the speaker, and wherein the second section that includes a section from after the first section to the end of the voice recognition operation. | 2. The electronic device of claim 1 , wherein the first section that includes a section from a time of detecting the voice signal to a predetermined time required for a formation the beamforming direction corresponding to the direction of the speaker, and wherein the second section that includes a section from after the first section to the end of the voice recognition operation. 3. The electronic device of claim 2 , wherein the processor is configured to: determine of the direction of the speaker and the beamforming direction when initiating the voice recognition, and control to change the beamforming direction based on a result of the determining. | 0.85881 |
3. The method of claim 1 , wherein said first SQL statements, when executed, cause one or more database object tables to be created. | 3. The method of claim 1 , wherein said first SQL statements, when executed, cause one or more database object tables to be created. 18. A volatile or non-volatile computer-readable storage medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 3 . | 0.816597 |
1. A computer-readable storage medium containing a program which, when executed by a processor, performs operations for managing execution of an analysis routine on input data, the operations comprising: receiving input; receiving user-selection of an analysis routine for processing the received input; wherein the analysis routine is defined by at least one abstract rule set having one or more abstract rules each having a conditional statement and a consequential statement; wherein the consequential statement defines a particular recommendation that is returned when the conditional statement is satisfied; wherein the conditional statement and the consequential statement are defined using logical field definitions defined in an abstraction model that models underlying physical data, wherein the logical field definitions each specify at least a logical field name and an access method mapping the logical field name to corresponding underlying physical data; and executing the analysis routine on the received input, comprising: identifying all required inputs for each abstract rule of the analysis routine; determining whether the received input includes data for all required inputs; and if the received input does not include data for one or more of the required inputs, retrieving suitable data for the one or more of the required inputs from a database. | 1. A computer-readable storage medium containing a program which, when executed by a processor, performs operations for managing execution of an analysis routine on input data, the operations comprising: receiving input; receiving user-selection of an analysis routine for processing the received input; wherein the analysis routine is defined by at least one abstract rule set having one or more abstract rules each having a conditional statement and a consequential statement; wherein the consequential statement defines a particular recommendation that is returned when the conditional statement is satisfied; wherein the conditional statement and the consequential statement are defined using logical field definitions defined in an abstraction model that models underlying physical data, wherein the logical field definitions each specify at least a logical field name and an access method mapping the logical field name to corresponding underlying physical data; and executing the analysis routine on the received input, comprising: identifying all required inputs for each abstract rule of the analysis routine; determining whether the received input includes data for all required inputs; and if the received input does not include data for one or more of the required inputs, retrieving suitable data for the one or more of the required inputs from a database. 7. The computer-readable storage medium of claim 1 , wherein executing the analysis routine on the received input further comprises: if the received input includes data for all required inputs, returning the particular recommendation as an analysis result for the analysis routine only if the conditional statement is resolved to true for all required inputs. | 0.5 |
25. An interactive coordinated book assembly, comprising: a plurality of left and right main pages, said pages containing textual material and a key word on each page; a plurality of left and right activity pages, each of said activity pages containing an activity area, said main pages and said activity pages being alternately interleaved and bound along one edge to form a book; a stiff support backing comprising a left portion and a right portion, said portions being attached to each other at a seam to form a book cover; a left direction booklet comprising a set of bound pages, said left direction booklet being attached to said left support portion and containing activity direction text to be read by a parent to a child, said direction area text being coordinated with said key word appearing on said left main page; a right direction booklet comprising a set of bound pages, said right direction booklet being attached to said right support portion and containing activity direction text to be read by a parent to a child, said direction area text being coordinated with said key word appearing on said right main page; and said left activity page containing a repetition of said key word present in said adjacent right main page and said right activity page containing a repetition said key word present in said adjacent left main page. | 25. An interactive coordinated book assembly, comprising: a plurality of left and right main pages, said pages containing textual material and a key word on each page; a plurality of left and right activity pages, each of said activity pages containing an activity area, said main pages and said activity pages being alternately interleaved and bound along one edge to form a book; a stiff support backing comprising a left portion and a right portion, said portions being attached to each other at a seam to form a book cover; a left direction booklet comprising a set of bound pages, said left direction booklet being attached to said left support portion and containing activity direction text to be read by a parent to a child, said direction area text being coordinated with said key word appearing on said left main page; a right direction booklet comprising a set of bound pages, said right direction booklet being attached to said right support portion and containing activity direction text to be read by a parent to a child, said direction area text being coordinated with said key word appearing on said right main page; and said left activity page containing a repetition of said key word present in said adjacent right main page and said right activity page containing a repetition said key word present in said adjacent left main page. 37. The assembly of claim 25, wherein said activity direction text contains matter selected from the group consisting of statements, questions, and instructions. | 0.592466 |
1. A machine-readable storage device encoding a computer program that causes data processing apparatus to perform operations comprising: receiving, from a reviewer, multiple comments about a word processing document; presenting the multiple comments to an editor; for each comment of the multiple comments presented to the editor, receiving, from the editor, an instruction to access the comment, accessing the comment in response to the instruction, receiving, from the editor, one or more changes to the word processing document that address the accessed comment, and storing the one or more received changes to the word processing document in a document difference record associated with the accessed comment; receiving, from the reviewer, a request selecting a first comment from among the multiple accessed comments; and presenting, to the reviewer in response to the request, the word processing document and a first document difference record associated with the selected first comment, while hiding document difference records that correspond to unselected comments from among the multiple comments. | 1. A machine-readable storage device encoding a computer program that causes data processing apparatus to perform operations comprising: receiving, from a reviewer, multiple comments about a word processing document; presenting the multiple comments to an editor; for each comment of the multiple comments presented to the editor, receiving, from the editor, an instruction to access the comment, accessing the comment in response to the instruction, receiving, from the editor, one or more changes to the word processing document that address the accessed comment, and storing the one or more received changes to the word processing document in a document difference record associated with the accessed comment; receiving, from the reviewer, a request selecting a first comment from among the multiple accessed comments; and presenting, to the reviewer in response to the request, the word processing document and a first document difference record associated with the selected first comment, while hiding document difference records that correspond to unselected comments from among the multiple comments. 2. The machine-readable storage device of claim 1 , wherein the operations comprise: receiving, from the reviewer, another request selecting a second comment from among the multiple accessed comments and unselecting the first comment; and presenting, to the reviewer in response to the other request, the word processing document and a second document difference record associated with the selected second comment, while hiding the first document difference record associated with the unselected first comment and any document difference records that correspond to any unselected comments different from the first comment from among the multiple comments. | 0.551552 |
1. A method comprising: receiving a search request from a first user; performing a search based on the search request; providing a set of search results; providing a set of categories for organizing the set of search results, wherein each category is identified based, at least in part, on one or more search results; organizing the set of search results into a hierarchy of categories, the hierarchy including at least one category from the set of categories; displaying at least a portion of the hierarchy of categories to the first user; receiving a request from the first user to modify the hierarchy of categories; modifying the hierarchy of categories in accordance with the request from the first user; associating the modified hierarchy of categories with a user profile for the first user; storing the modified hierarchy of categories associated with the first user to provide a customized hierarchy of categories to the first user for use in response to subsequent search requests from the first user; and providing a customized category hierarchy for the first user based on the user profile for the first user in response to a subsequent search request from the first user. | 1. A method comprising: receiving a search request from a first user; performing a search based on the search request; providing a set of search results; providing a set of categories for organizing the set of search results, wherein each category is identified based, at least in part, on one or more search results; organizing the set of search results into a hierarchy of categories, the hierarchy including at least one category from the set of categories; displaying at least a portion of the hierarchy of categories to the first user; receiving a request from the first user to modify the hierarchy of categories; modifying the hierarchy of categories in accordance with the request from the first user; associating the modified hierarchy of categories with a user profile for the first user; storing the modified hierarchy of categories associated with the first user to provide a customized hierarchy of categories to the first user for use in response to subsequent search requests from the first user; and providing a customized category hierarchy for the first user based on the user profile for the first user in response to a subsequent search request from the first user. 2. The method of claim 1 , wherein modifying the hierarchy of categories comprises adding a new category to generate a modified hierarchy of categories, the new category capable of being associated with one or more search results. | 0.610678 |
1. A method for creating a custom narration for a book, the book comprising text, the method comprising: making an audio recording of a narrator, wherein the audio recording comprises a first portion and a second portion that immediately follows the first portion; determining, using one or more processors, that the first portion is a reading of a first segment of the text; generating, using one or more processors, a first correlation between the first portion of the recording and the first segment of the text; determining, using one or more processors, that the second portion does not correspond to a second segment of the text, the second segment being a subset of the text that immediately follows the first segment; applying, using one or more processors and responsive to determining that the second portion does not correspond to the second segment of the text, a correlation algorithm to identify a component of the book to which the second portion is likely to correspond, applying the correlation algorithm comprising: responsive to determining the second portion is a repeat of the first portion, identifying the first segment of the text as the component of the book; responsive to determining the second segment of text is spatially proximate to an illustration, identifying the illustration as the component of the book; responsive to determining the first segment of the text is immediately followed by a chapter break, identifying the chapter break as the component of the book; and responsive to determining the second portion corresponds to a third segment of the text that follows the second segment of the text, identifying the third segment of the text as the component of the book; generating, using one or more processors, a second correlation between the second portion and the component of the book; and storing, using one or more processors, the first and second correlations such that upon playback, the first portion is presented as corresponding to the first segment and the second portion is presented as corresponding to the component. | 1. A method for creating a custom narration for a book, the book comprising text, the method comprising: making an audio recording of a narrator, wherein the audio recording comprises a first portion and a second portion that immediately follows the first portion; determining, using one or more processors, that the first portion is a reading of a first segment of the text; generating, using one or more processors, a first correlation between the first portion of the recording and the first segment of the text; determining, using one or more processors, that the second portion does not correspond to a second segment of the text, the second segment being a subset of the text that immediately follows the first segment; applying, using one or more processors and responsive to determining that the second portion does not correspond to the second segment of the text, a correlation algorithm to identify a component of the book to which the second portion is likely to correspond, applying the correlation algorithm comprising: responsive to determining the second portion is a repeat of the first portion, identifying the first segment of the text as the component of the book; responsive to determining the second segment of text is spatially proximate to an illustration, identifying the illustration as the component of the book; responsive to determining the first segment of the text is immediately followed by a chapter break, identifying the chapter break as the component of the book; and responsive to determining the second portion corresponds to a third segment of the text that follows the second segment of the text, identifying the third segment of the text as the component of the book; generating, using one or more processors, a second correlation between the second portion and the component of the book; and storing, using one or more processors, the first and second correlations such that upon playback, the first portion is presented as corresponding to the first segment and the second portion is presented as corresponding to the component. 7. The method of claim 1 , wherein storing the first correlation comprises writing correlation data to a correlation file stored in a computer readable medium. | 0.551293 |
9. A method for arranging on a plurality of word game dice a plurality of letters of an alphabet appearing in a corpus of words, said dice having a total number of faces thereon, comprising the method of a) determining a relative frequency of appearance of each of said letters in said corpus of words; b) multiplying said relative frequency of appearance of each said letters by said total number of faces to receive a product for each of said letters; c) dividing said product for each of said letters by one hundred to receive an initial number for each of said letters; d) rounding said initial number for each of said letters to the nearest whole number to receive a final number for each of said letters, said final number for each of said letters representing the number of faces of said dice on which each of said letters will be displayed; and e) displaying said final number of each of said letters on said dice such that none of said letters am displayed more than once on any one of said dice and such that placement of common bigrams on any one die is minimized, said method of arranging resulting in an arrangement of letters on the dice that maximize the numbers of words that can be formed using said letters displayed on said dice. | 9. A method for arranging on a plurality of word game dice a plurality of letters of an alphabet appearing in a corpus of words, said dice having a total number of faces thereon, comprising the method of a) determining a relative frequency of appearance of each of said letters in said corpus of words; b) multiplying said relative frequency of appearance of each said letters by said total number of faces to receive a product for each of said letters; c) dividing said product for each of said letters by one hundred to receive an initial number for each of said letters; d) rounding said initial number for each of said letters to the nearest whole number to receive a final number for each of said letters, said final number for each of said letters representing the number of faces of said dice on which each of said letters will be displayed; and e) displaying said final number of each of said letters on said dice such that none of said letters am displayed more than once on any one of said dice and such that placement of common bigrams on any one die is minimized, said method of arranging resulting in an arrangement of letters on the dice that maximize the numbers of words that can be formed using said letters displayed on said dice. 13. The method of claim 9 wherein step e) further includes displaying together two of said letters on one face of one die of said dice. | 0.66164 |
1. In a transaction processing system, a method for prioritizing and presenting incoming calls routed from callers through a communication network to an agent station having an associated agent, the incoming calls including voice-dialog communication and text-dialog communication, the method comprising the steps of: receiving both voice-dialog and text dialog calls from the communication network; determining at least one contact evaluation parameter associated with each call based on external real-world events, the contact evaluation parameter indicating a criteria governing identification of selected business rules, separate and distinct from the contact evaluation parameter, for evaluating priority of the call, said real-world events including a geographic location associated with an origin of the call, and a time period measured from receipt of the call to a time of close of business of the caller; applying one or more of the selected business rules to the contact evaluation parameter to generate a priority value corresponding to each call; assigning the corresponding priority value to each respective call; displaying to the agent an indication of each of the calls based on the assigned priority value; and modifying the assigned priority value of the calls dynamically in real-time in response to the real-world events. | 1. In a transaction processing system, a method for prioritizing and presenting incoming calls routed from callers through a communication network to an agent station having an associated agent, the incoming calls including voice-dialog communication and text-dialog communication, the method comprising the steps of: receiving both voice-dialog and text dialog calls from the communication network; determining at least one contact evaluation parameter associated with each call based on external real-world events, the contact evaluation parameter indicating a criteria governing identification of selected business rules, separate and distinct from the contact evaluation parameter, for evaluating priority of the call, said real-world events including a geographic location associated with an origin of the call, and a time period measured from receipt of the call to a time of close of business of the caller; applying one or more of the selected business rules to the contact evaluation parameter to generate a priority value corresponding to each call; assigning the corresponding priority value to each respective call; displaying to the agent an indication of each of the calls based on the assigned priority value; and modifying the assigned priority value of the calls dynamically in real-time in response to the real-world events. 4. The method according to claim 1 wherein the contact evaluation parameter is derived from information obtained from a database, the database being accessed based upon an identification of the call. | 0.538411 |
1. A computer system, comprising: at least one adaptive self-trained computer engine; at least one multi-core processor comprising a plurality of cores, wherein the at least one multi-core processor is associated with the at least one adaptive self-trained computer engine so that the at least one multi-core processor is configured to receive executing instructions from the at least one adaptive self-trained computer engine; wherein the computer system is configured to perform at least the following operations: during a training stage: electronically receiving, by the adaptive self-trained computer engine, an initial speech audio data generated by a microphone of a computing device, wherein the initial speech audio data corresponds to at least one initial utterance received by the microphone from a particular user wherein the at least one initial utterance corresponds to an initial text being read by the particular user; dynamically segmenting, by the adaptive self-trained computer engine, the initial speech audio data and the corresponding initial text into a plurality of user phonemes; dynamically querying, by the adaptive self-trained computer engine, at least one database object containing at least one computer dictionary of stored subject-specific phonetic pronunciations of subject-specific words, which are related to a particular activity, to match the plurality of user phonemes to a plurality of subject-specific phonetic pronunciations to form a plurality of user-specific subject-specific phonemes; dynamically associating, by the adaptive self-trained computer engine, a plurality of first timestamps with the plurality of user-specific subject-specific phonemes, wherein each first timestamp corresponds to a time segment location of a respective matched user phoneme in the initial speech audio data so as to form at least one user-specific subject-specific data dictionary of timestamped user-specific subject-specific phonemes; dynamically generating, by the adaptive self-trained computer engine, a plurality of user-specific subject-specific training instructions by utilizing the at least one user-specific subject-specific data dictionary of timestamped user-specific subject-specific phonemes as a user-specific subject-specific speech training model, wherein each user-specific subject-specific training instruction comprises a training text and a synthesized user-specific speech audio of the training text; dynamically outputting, by the adaptive self-trained computer engine, the training text of each user-specific subject-specific training instruction to the computing device; electronically receiving, by the adaptive self-trained computer engine, a training speech audio data generated by the microphone of the computing device, wherein the training speech audio data corresponds to a training utterance received by the microphone from the particular user wherein the training utterance corresponds to the training text of each user-specific subject-specific training instruction being read by the particular user; dynamically comparing, by the adaptive self-trained computer engine, the training speech audio data to the synthesized user-specific speech audio of the training text to train the user-specific subject-specific speech training model; during a transcription stage: electronically receiving, by the adaptive self-trained computer engine, to-be-transcribed speech audio data of at least one user, wherein the to-be-transcribed speech audio data corresponds to at least one to-be-transcribed utterance received from the at least one user; dynamically splitting, by the adaptive self-trained computer engine, the to-be transcribed speech audio data into a plurality of to-be-transcribed speech audio segments, wherein the splitting is at points of silence to form, after each split, two to-be-transcribed speech audio segments with an identical non-silent audio portion; dynamically associating, by the adaptive self-trained computer engine, a plurality of second timestamps with the plurality of to-be-transcribed speech audio segments, wherein each second timestamp corresponds to a particular time segment location of a respective to-be-transcribed speech audio segment in the to-be-transcribed speech audio data so as to form a plurality or timestamped to-be-transcribed speech audio segments; dynamically assigning, by the adaptive self-trained computer engine, at least one respective timestamped to-be-transcribed speech audio segment of the plurality of timestamped to-be-transcribed speech audio segments to a particular core of the plurality of cores of the at least one multi-core processor; dynamically streaming, by the adaptive self-trained computer engine, the at least one respective timestamped to-be-transcribed speech audio segment of the plurality of timestamped to-be-transcribed speech audio segments to the particular core of the plurality of cores of the at least one multi-core processor at a particular sampling rate for a duration that is n times less than a duration of the at least one to-be-transcribed utterance; dynamically transcribing, in parallel, by the at least one multi-core processor, the plurality of timestamped to-be-transcribed speech audio segments based, at least in part, on the user-specific subject-specific speech training model of the at least one user to generate a plurality of text transcript segments corresponding to the plurality of timestamped to-be-transcribed speech audio segments; wherein the at least one multi-core processor is configured to dynamically transcribe the plurality of timestamped to-be-transcribed speech audio segments such that each timestamped to-be-transcribed speech audio segment is transcribed by at least one core of the plurality of cores of the at least one multi-core processor; dynamically assembling, by the adaptive self-trained computer engine, the plurality of text transcript segments into a user-specific subject-specific output transcript of the to-be-transcribed speech audio data, based, at least in part, on the plurality or second timestamps; dynamically verifying, by the adaptive self-trained computer engine, an accuracy of the user-specific subject-specific output transcript of the to-be-transcribed speech audio data to form a verified user-specific subject-specific output transcript of the to-be-transcribed speech audio data; and dynamically and simultaneously applying, by the adaptive self-trained computer engine, a plurality of filters to the verified user-specific subject-specific output transcript to determine at least one subject-specific message of the at least one user in the to-be-transcribed speech audio data, wherein each filter is a data structure characterizing at least one subject-specific property of at least one particular subject-specific term and at least one context parameter identifying at least one context related to the particular activity, wherein the at least one particular subject-specific term is associated with the at least one context. | 1. A computer system, comprising: at least one adaptive self-trained computer engine; at least one multi-core processor comprising a plurality of cores, wherein the at least one multi-core processor is associated with the at least one adaptive self-trained computer engine so that the at least one multi-core processor is configured to receive executing instructions from the at least one adaptive self-trained computer engine; wherein the computer system is configured to perform at least the following operations: during a training stage: electronically receiving, by the adaptive self-trained computer engine, an initial speech audio data generated by a microphone of a computing device, wherein the initial speech audio data corresponds to at least one initial utterance received by the microphone from a particular user wherein the at least one initial utterance corresponds to an initial text being read by the particular user; dynamically segmenting, by the adaptive self-trained computer engine, the initial speech audio data and the corresponding initial text into a plurality of user phonemes; dynamically querying, by the adaptive self-trained computer engine, at least one database object containing at least one computer dictionary of stored subject-specific phonetic pronunciations of subject-specific words, which are related to a particular activity, to match the plurality of user phonemes to a plurality of subject-specific phonetic pronunciations to form a plurality of user-specific subject-specific phonemes; dynamically associating, by the adaptive self-trained computer engine, a plurality of first timestamps with the plurality of user-specific subject-specific phonemes, wherein each first timestamp corresponds to a time segment location of a respective matched user phoneme in the initial speech audio data so as to form at least one user-specific subject-specific data dictionary of timestamped user-specific subject-specific phonemes; dynamically generating, by the adaptive self-trained computer engine, a plurality of user-specific subject-specific training instructions by utilizing the at least one user-specific subject-specific data dictionary of timestamped user-specific subject-specific phonemes as a user-specific subject-specific speech training model, wherein each user-specific subject-specific training instruction comprises a training text and a synthesized user-specific speech audio of the training text; dynamically outputting, by the adaptive self-trained computer engine, the training text of each user-specific subject-specific training instruction to the computing device; electronically receiving, by the adaptive self-trained computer engine, a training speech audio data generated by the microphone of the computing device, wherein the training speech audio data corresponds to a training utterance received by the microphone from the particular user wherein the training utterance corresponds to the training text of each user-specific subject-specific training instruction being read by the particular user; dynamically comparing, by the adaptive self-trained computer engine, the training speech audio data to the synthesized user-specific speech audio of the training text to train the user-specific subject-specific speech training model; during a transcription stage: electronically receiving, by the adaptive self-trained computer engine, to-be-transcribed speech audio data of at least one user, wherein the to-be-transcribed speech audio data corresponds to at least one to-be-transcribed utterance received from the at least one user; dynamically splitting, by the adaptive self-trained computer engine, the to-be transcribed speech audio data into a plurality of to-be-transcribed speech audio segments, wherein the splitting is at points of silence to form, after each split, two to-be-transcribed speech audio segments with an identical non-silent audio portion; dynamically associating, by the adaptive self-trained computer engine, a plurality of second timestamps with the plurality of to-be-transcribed speech audio segments, wherein each second timestamp corresponds to a particular time segment location of a respective to-be-transcribed speech audio segment in the to-be-transcribed speech audio data so as to form a plurality or timestamped to-be-transcribed speech audio segments; dynamically assigning, by the adaptive self-trained computer engine, at least one respective timestamped to-be-transcribed speech audio segment of the plurality of timestamped to-be-transcribed speech audio segments to a particular core of the plurality of cores of the at least one multi-core processor; dynamically streaming, by the adaptive self-trained computer engine, the at least one respective timestamped to-be-transcribed speech audio segment of the plurality of timestamped to-be-transcribed speech audio segments to the particular core of the plurality of cores of the at least one multi-core processor at a particular sampling rate for a duration that is n times less than a duration of the at least one to-be-transcribed utterance; dynamically transcribing, in parallel, by the at least one multi-core processor, the plurality of timestamped to-be-transcribed speech audio segments based, at least in part, on the user-specific subject-specific speech training model of the at least one user to generate a plurality of text transcript segments corresponding to the plurality of timestamped to-be-transcribed speech audio segments; wherein the at least one multi-core processor is configured to dynamically transcribe the plurality of timestamped to-be-transcribed speech audio segments such that each timestamped to-be-transcribed speech audio segment is transcribed by at least one core of the plurality of cores of the at least one multi-core processor; dynamically assembling, by the adaptive self-trained computer engine, the plurality of text transcript segments into a user-specific subject-specific output transcript of the to-be-transcribed speech audio data, based, at least in part, on the plurality or second timestamps; dynamically verifying, by the adaptive self-trained computer engine, an accuracy of the user-specific subject-specific output transcript of the to-be-transcribed speech audio data to form a verified user-specific subject-specific output transcript of the to-be-transcribed speech audio data; and dynamically and simultaneously applying, by the adaptive self-trained computer engine, a plurality of filters to the verified user-specific subject-specific output transcript to determine at least one subject-specific message of the at least one user in the to-be-transcribed speech audio data, wherein each filter is a data structure characterizing at least one subject-specific property of at least one particular subject-specific term and at least one context parameter identifying at least one context related to the particular activity, wherein the at least one particular subject-specific term is associated with the at least one context. 2. The computer system of claim 1 , wherein the computer system is further configured to perform at least the following operations: dynamically analyzing, by the adaptive self-trained computer engine, a frequency spectrum of the initial speech audio data, the training speech audio data, or both, to generate a speaker profile of the particular user. | 0.506575 |
13. A system for analyzing executable content within at least one network of an enterprise, comprising: a plurality of collection agents disposed within one or more networks of an enterprise and executable by one or more hardware processors of one or more devices within the one or more networks, wherein each collection agent is configured to detect a presence of multiple instances of executable content within the enterprise; and a central analysis server remotely disposed from and in operative communication with the plurality of collection agents via the one or more networks, the central analysis server comprising: a collection engine, executable by a hardware processor of the central analysis server, that is configured to capture and store the multiple instances of executable content received from the plurality of collection agents; an extraction engine, executable by the hardware processor of the central analysis server, that is configured to extract one or more characteristics from each instance of the executable content; an analysis engine, executable by the hardware processor of the central analysis server, that is configured to: identify associations among the extracted characteristics; determine, based on the associations among the extracted characteristics, that a first portion of executable content is associated with a non-trusted entity; obtain a hash value for the first portion of executable content; and store the hash value and the associated extracted characteristics to create a non-trusted entity profile; and a first database that is configured to store the extracted characteristics, identified associations, and hash value, the first database being accessible by the hardware processor of the central analysis server and the plurality of collection agents such that each of the plurality of collection agents is operable to identify at least another portion of executable content associated with the non-trusted entity based on the hash value that has been recognized and presented in the database, wherein each of the plurality of collection agents is operable to transmit to the central analysis server an indication of notice indicative of a detection of the non-trusted entity at the corresponding collection agent, the indication comprising the hash value, location information but not a copy of the at least another portion of executable content to limit use of enterprise infrastructure resources and so as to update the non-trusted entity profile. | 13. A system for analyzing executable content within at least one network of an enterprise, comprising: a plurality of collection agents disposed within one or more networks of an enterprise and executable by one or more hardware processors of one or more devices within the one or more networks, wherein each collection agent is configured to detect a presence of multiple instances of executable content within the enterprise; and a central analysis server remotely disposed from and in operative communication with the plurality of collection agents via the one or more networks, the central analysis server comprising: a collection engine, executable by a hardware processor of the central analysis server, that is configured to capture and store the multiple instances of executable content received from the plurality of collection agents; an extraction engine, executable by the hardware processor of the central analysis server, that is configured to extract one or more characteristics from each instance of the executable content; an analysis engine, executable by the hardware processor of the central analysis server, that is configured to: identify associations among the extracted characteristics; determine, based on the associations among the extracted characteristics, that a first portion of executable content is associated with a non-trusted entity; obtain a hash value for the first portion of executable content; and store the hash value and the associated extracted characteristics to create a non-trusted entity profile; and a first database that is configured to store the extracted characteristics, identified associations, and hash value, the first database being accessible by the hardware processor of the central analysis server and the plurality of collection agents such that each of the plurality of collection agents is operable to identify at least another portion of executable content associated with the non-trusted entity based on the hash value that has been recognized and presented in the database, wherein each of the plurality of collection agents is operable to transmit to the central analysis server an indication of notice indicative of a detection of the non-trusted entity at the corresponding collection agent, the indication comprising the hash value, location information but not a copy of the at least another portion of executable content to limit use of enterprise infrastructure resources and so as to update the non-trusted entity profile. 16. The system of claim 13 further comprising: a second database, accessible by the hardware processor of the central analysis server, that is configured to store the non-trusted entity profile. | 0.654305 |
15. A tangible, non-transient computer-readable medium comprising instructions stored thereon for causing a computer to perform operations comprising: receiving, for a name of a person and from a plurality of third parties, information indicating a name characteristic that people with the name of the person typically have, each of the names is common to many people, the name characteristics for a particular name are characteristics that are expected to be found in people sharing the particular name; calculating a confidence value associated with the name characteristic as the percentage of the third parties that associated the name characteristic with the name; store the received names and associated name characteristics with the associated confidence values; receive a name of an individual person; determine whether the received name matches any of the stored names; if the received name matches a first of the stored names, identify one or more name characteristics associated with the received name; infer one or more user characteristics associated with the individual person using at least one of the identified name characteristics; and return at least one of the inferred user characteristics. | 15. A tangible, non-transient computer-readable medium comprising instructions stored thereon for causing a computer to perform operations comprising: receiving, for a name of a person and from a plurality of third parties, information indicating a name characteristic that people with the name of the person typically have, each of the names is common to many people, the name characteristics for a particular name are characteristics that are expected to be found in people sharing the particular name; calculating a confidence value associated with the name characteristic as the percentage of the third parties that associated the name characteristic with the name; store the received names and associated name characteristics with the associated confidence values; receive a name of an individual person; determine whether the received name matches any of the stored names; if the received name matches a first of the stored names, identify one or more name characteristics associated with the received name; infer one or more user characteristics associated with the individual person using at least one of the identified name characteristics; and return at least one of the inferred user characteristics. 17. The computer-readable medium of claim 15 , wherein the instructions are operable to cause the computer to perform further operations comprising: receive additional user information; and increase or decrease a confidence value for the identified name characteristics based on the received additional user information. | 0.512585 |
19. The method of claim 14 , wherein the sending of the scripted questions further comprises: sending a first question to the candidate; and sending at least one subsequent question to the candidate. | 19. The method of claim 14 , wherein the sending of the scripted questions further comprises: sending a first question to the candidate; and sending at least one subsequent question to the candidate. 21. The method of claim 19 , wherein the first question requests a job title for the candidate, and wherein each said at least one subsequent question is chosen based on a response by the candidate to the first question. | 0.920066 |
1. A method, comprising: detecting, at a discovery module of a service processor, a profile request from a console application; requesting class information for one or more classes corresponding to the detected profile request from a provider register; generating a profile-based web services description language (WSDL) file including the requested class information and usable by the console application to generate a management instruction; communicating the profile-based WSDL file to the console application; and receiving and implementing the management instruction generated by the console application using the profile-based WSDL file. | 1. A method, comprising: detecting, at a discovery module of a service processor, a profile request from a console application; requesting class information for one or more classes corresponding to the detected profile request from a provider register; generating a profile-based web services description language (WSDL) file including the requested class information and usable by the console application to generate a management instruction; communicating the profile-based WSDL file to the console application; and receiving and implementing the management instruction generated by the console application using the profile-based WSDL file. 2. The method of claim 1 , wherein requesting class information comprises querying a common information model (CIM)-Schema. | 0.545205 |
7. A non-transitory computer-readable medium containing software that, when executed, causes the computer to perform the acts of: executing software configured to teach a subject to a student using spatial-temporal concepts, wherein the software includes motion of spatial objects that are to be interactively controlled by the student in a chosen temporal order of plural actions that satisfies an objective corresponding to at least one concept of the subject, such that certain ones of the plural actions are available to the student only after certain other actions have been made by the student; and associating language-based concepts tested by a language-based test to corresponding spatial-temporal concepts in the software; determining a language-based proficiency level in the subject by administering the language-based test to the student; obtaining a spatial-temporal score that assesses the student's proficiency in the spatial-temporal concepts; and comparing the spatial-temporal score to the language-based proficiency level. | 7. A non-transitory computer-readable medium containing software that, when executed, causes the computer to perform the acts of: executing software configured to teach a subject to a student using spatial-temporal concepts, wherein the software includes motion of spatial objects that are to be interactively controlled by the student in a chosen temporal order of plural actions that satisfies an objective corresponding to at least one concept of the subject, such that certain ones of the plural actions are available to the student only after certain other actions have been made by the student; and associating language-based concepts tested by a language-based test to corresponding spatial-temporal concepts in the software; determining a language-based proficiency level in the subject by administering the language-based test to the student; obtaining a spatial-temporal score that assesses the student's proficiency in the spatial-temporal concepts; and comparing the spatial-temporal score to the language-based proficiency level. 21. The computer-readable medium of claim 7 , wherein the chosen temporal order of plural actions is chosen by the student from a plurality of possible temporal orders of plural actions that satisfy the objective. | 0.711529 |
11. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said memory unit containing instructions that when executed by the processor implement a method for searching and retrieving at least one reusable asset, a first asset of said at least one reusable asset being stored in an index file in a database, a search request comprising at least one search term, the method comprising: receiving a new request comprising a first search term of said at least one search term; searching the index file for the first search term in the new request, said searching comprising selecting, from the index file, all reusable assets having the first search term; building a new search result with all reusable assets having been selected from the index file during said searching; retrieving a past request from a search history stored in the database, the past request comprising a second search term of said at least one search term, the past request being coupled to a past search result comprising a second asset of said at least one reusable asset; correlating the new request with the past request, said correlating comprising: calculating a correlation coefficient R between the new request and the past request; determining the correlation coefficient R being greater than or equal to a first predefined threshold value R t for request correlation in a range of 0.2 to 0.99; adding the past search result to the new search result, wherein the past search result is not present within the new search result; and calculating a position value P of the past search result within the new search result as P=Round(wRS), wherein Round(x) is a mathematical function returning a closest integer to x, w is a predefined weight value chosen from a range of 0.1 to 1, and S is a number of reusable assets in the new search result; adjusting a relevance of each reusable asset within the new search result, the relevance indicating how the past search result for said each reusable asset is correlated with the new search result pursuant to a number of occurrences of said at least one search term in said each reusable asset; and storing the new request and the new search result into the search request history in the database upon determining that the relevance of said each reusable asset in the new search result is greater than a second predefined threshold value for the relevance, wherein said receiving, said searching, said building, said retrieving, said correlating, said adjusting, and said storing are performed by a search server, and wherein the search server is configured to store into and retrieve from the database. | 11. A computer system comprising a processor and a computer readable memory unit coupled to the processor, said memory unit containing instructions that when executed by the processor implement a method for searching and retrieving at least one reusable asset, a first asset of said at least one reusable asset being stored in an index file in a database, a search request comprising at least one search term, the method comprising: receiving a new request comprising a first search term of said at least one search term; searching the index file for the first search term in the new request, said searching comprising selecting, from the index file, all reusable assets having the first search term; building a new search result with all reusable assets having been selected from the index file during said searching; retrieving a past request from a search history stored in the database, the past request comprising a second search term of said at least one search term, the past request being coupled to a past search result comprising a second asset of said at least one reusable asset; correlating the new request with the past request, said correlating comprising: calculating a correlation coefficient R between the new request and the past request; determining the correlation coefficient R being greater than or equal to a first predefined threshold value R t for request correlation in a range of 0.2 to 0.99; adding the past search result to the new search result, wherein the past search result is not present within the new search result; and calculating a position value P of the past search result within the new search result as P=Round(wRS), wherein Round(x) is a mathematical function returning a closest integer to x, w is a predefined weight value chosen from a range of 0.1 to 1, and S is a number of reusable assets in the new search result; adjusting a relevance of each reusable asset within the new search result, the relevance indicating how the past search result for said each reusable asset is correlated with the new search result pursuant to a number of occurrences of said at least one search term in said each reusable asset; and storing the new request and the new search result into the search request history in the database upon determining that the relevance of said each reusable asset in the new search result is greater than a second predefined threshold value for the relevance, wherein said receiving, said searching, said building, said retrieving, said correlating, said adjusting, and said storing are performed by a search server, and wherein the search server is configured to store into and retrieve from the database. 12. The computer system of claim 11 , said calculating the correlation coefficient R comprising: calculating the correlation coefficient R, wherein R = 2 n c n n + n p , wherein n c is a number of search terms common to both the new request and the past request, n n is a number of search terms in the new request, and n p is a number of search terms in the past request. | 0.824363 |
20. The machine-readable storage medium of claim 19 , wherein when executed the instructions cause the processing system to: retrieve the first template data, wherein the first template data correspond to the first language; populate the first template with the first template data to define a first response in the first language; and communicate the first response to a recipient. | 20. The machine-readable storage medium of claim 19 , wherein when executed the instructions cause the processing system to: retrieve the first template data, wherein the first template data correspond to the first language; populate the first template with the first template data to define a first response in the first language; and communicate the first response to a recipient. 23. The machine-readable storage medium of claim 20 , wherein a plurality of different template types are provided for different types of queries, a template type from the plurality of template types is identified, and the first template is retrieved in the first language. | 0.848541 |
1. A hearing aid, comprising: a memory for storing first and second data characteristics of a first and respectively a second language; a processing unit for processing an input signal, the processing unit configured to selectively process the input signal based either on the first or on the second data, wherein the first and second characteristic data each comprise a language-specific amplification pattern having a plurality of amplification factors corresponding to a plurality of frequency bands; and a language recognition unit for automatically identifying a language associated with the input signal, wherein the processing unit is configured to amplify the input signal relative to the plurality of frequency bands based on the identified language. | 1. A hearing aid, comprising: a memory for storing first and second data characteristics of a first and respectively a second language; a processing unit for processing an input signal, the processing unit configured to selectively process the input signal based either on the first or on the second data, wherein the first and second characteristic data each comprise a language-specific amplification pattern having a plurality of amplification factors corresponding to a plurality of frequency bands; and a language recognition unit for automatically identifying a language associated with the input signal, wherein the processing unit is configured to amplify the input signal relative to the plurality of frequency bands based on the identified language. 4. The hearing aid according to claim 1 , wherein the processing unit comprises a plurality of selectable hearing programs, each hearing programs related to a specific language. | 0.720544 |
1. A method of computer implemented sorting of a plurality of documents relevant to one or more of a plurality of specialties, said method being employed to construct or maintain a computer accessible database to be accessed by a plurality of readers or groups of readers, said method comprising the steps of developing a list of said plurality of specialties in a field of interest to said plurality of readers or groups of readers, identifying documents relevant to respective ones of said one or more specialties, wherein said step of identifying is carried out by at least one expert in said one or more specialties, said expert being a person, selecting a limited number of documents for inclusion in said plurality of documents, wherein said step of selecting is carried out by at least one expert in said one or more specialties, said expert being a person, developing a hierarchical master index of subject matter referred to in said plurality of documents, each entry in said hierarchical master index having at least one of an index term and an associated code, wherein said step of developing a hierarchical master index is carried out by at least one expert in said one or more specialties, said expert being a person, assigning a limited number of index terms and associated codes of said hierarchical master index to each document of said plurality of documents, wherein said step of assigning a limited number of index terms and associated codes is carried out by at least one expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of index terms or codes is based on primary relevance of material described as determined by said expert, assigning at least one of said one or more specialties of said list of specialties developed in said developing step to each document of said plurality of documents, wherein said step of assigning at least one of said one or more specialties is carried out separately from said step of assigning a limited number of index terms by at least one expert in said one or more specialties, said expert being a person, assembling, using a computer, a plurality of hierarchical specialty indices of subject matter for respective ones of said plurality of specialties from index terms and associated codes assigned to respective documents in each of said ones of said plurality of specialties, wherein results of said step of assigning a limited number of index terms and results of said step of assigning at least one of said plurality of specialties as applied to respective ones of said documents identified in said step of identifying documents relevant to respective ones of said one or more specialities are merged by said computer, and sorting, using said computer, respective documents of said plurality of documents in accordance with a respective one of said plurality of hierarchical speciality indices for a respective one or more specialties, wherein said method results in construction or maintenance of a database from which documents, limited in number in accordance with said selecting step and relevant to each respective speciality, are retrieved with improved accuracy and reduction of false positives, and wherein the creation of empty folders in said hierarchical speciality indices is prevented. | 1. A method of computer implemented sorting of a plurality of documents relevant to one or more of a plurality of specialties, said method being employed to construct or maintain a computer accessible database to be accessed by a plurality of readers or groups of readers, said method comprising the steps of developing a list of said plurality of specialties in a field of interest to said plurality of readers or groups of readers, identifying documents relevant to respective ones of said one or more specialties, wherein said step of identifying is carried out by at least one expert in said one or more specialties, said expert being a person, selecting a limited number of documents for inclusion in said plurality of documents, wherein said step of selecting is carried out by at least one expert in said one or more specialties, said expert being a person, developing a hierarchical master index of subject matter referred to in said plurality of documents, each entry in said hierarchical master index having at least one of an index term and an associated code, wherein said step of developing a hierarchical master index is carried out by at least one expert in said one or more specialties, said expert being a person, assigning a limited number of index terms and associated codes of said hierarchical master index to each document of said plurality of documents, wherein said step of assigning a limited number of index terms and associated codes is carried out by at least one expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of index terms or codes is based on primary relevance of material described as determined by said expert, assigning at least one of said one or more specialties of said list of specialties developed in said developing step to each document of said plurality of documents, wherein said step of assigning at least one of said one or more specialties is carried out separately from said step of assigning a limited number of index terms by at least one expert in said one or more specialties, said expert being a person, assembling, using a computer, a plurality of hierarchical specialty indices of subject matter for respective ones of said plurality of specialties from index terms and associated codes assigned to respective documents in each of said ones of said plurality of specialties, wherein results of said step of assigning a limited number of index terms and results of said step of assigning at least one of said plurality of specialties as applied to respective ones of said documents identified in said step of identifying documents relevant to respective ones of said one or more specialities are merged by said computer, and sorting, using said computer, respective documents of said plurality of documents in accordance with a respective one of said plurality of hierarchical speciality indices for a respective one or more specialties, wherein said method results in construction or maintenance of a database from which documents, limited in number in accordance with said selecting step and relevant to each respective speciality, are retrieved with improved accuracy and reduction of false positives, and wherein the creation of empty folders in said hierarchical speciality indices is prevented. 13. The method of claim 1 , further comprising the step of placing sorted documents into one or more assigned speciality collections corresponding to said hierarchical indices. | 0.509776 |
1. A method comprising: presenting an electronic document data file including dynamic content and organized according to a page descriptive format, the dynamic content comprising a media content that changes state over time, wherein the media content comprises scripted content, the page descriptive format being a device-independent and display resolution-independent fixed-layout document format; adding a comment to the media content, the comment being directed to a state of the media content selected from a plurality of states of the media content, wherein the selected state comprises user-customized content elements; adding opaque state information to the electronic document data file such that the comment and the selected state of the media content to which the comment is directed can be rendered from the electronic document data file using the opaque state information, the opaque state information referencing the selected state of the media content associated with the comment and including frame information associated with the media content; subsequent to adding the opaque state information to the electronic document data file, receiving an indication to access the comment; in response to receiving the indication to access the comment, rendering the comment and the selected state of the media content to which the comment is directed based on the opaque state information. | 1. A method comprising: presenting an electronic document data file including dynamic content and organized according to a page descriptive format, the dynamic content comprising a media content that changes state over time, wherein the media content comprises scripted content, the page descriptive format being a device-independent and display resolution-independent fixed-layout document format; adding a comment to the media content, the comment being directed to a state of the media content selected from a plurality of states of the media content, wherein the selected state comprises user-customized content elements; adding opaque state information to the electronic document data file such that the comment and the selected state of the media content to which the comment is directed can be rendered from the electronic document data file using the opaque state information, the opaque state information referencing the selected state of the media content associated with the comment and including frame information associated with the media content; subsequent to adding the opaque state information to the electronic document data file, receiving an indication to access the comment; in response to receiving the indication to access the comment, rendering the comment and the selected state of the media content to which the comment is directed based on the opaque state information. 4. The method of claim 1 , further comprising: adding the dynamic content to the electronic document data file responsive to an indication provided by a graphical user interface. | 0.577656 |
1. An editable information management method comprising: storing editable information as a master file and a plurality of segment files, each segment file being editable independently of other segment files; combining said master file and said segment files in a manner specified by said master file to create said editable information; displaying said editable information for editing using an application program, said application program comprising an add in configured to combine said segment objects; receiving edit instructions to edit part of the displayed editable information corresponding to a predetermined segment file; and updating said predetermined segment file in response to said editing. | 1. An editable information management method comprising: storing editable information as a master file and a plurality of segment files, each segment file being editable independently of other segment files; combining said master file and said segment files in a manner specified by said master file to create said editable information; displaying said editable information for editing using an application program, said application program comprising an add in configured to combine said segment objects; receiving edit instructions to edit part of the displayed editable information corresponding to a predetermined segment file; and updating said predetermined segment file in response to said editing. 12. A method according to claim 1 , comprising storing a plurality of different versions of the master file. | 0.654261 |
1. A method, with an information processing system, for generating a plurality of candidate database schemas including relational and mark-up language elements, the method comprising: receiving an information model comprising a plurality of entities and at least one relationship defined there between, wherein the information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic; analyzing the information model that has been annotated; associating a score, in response to the analyzing, with each entity based at least in part on attributes associated with each entity; classifying, in response to associating a score, each entity as one of a relational element and a mark-up language element; partitioning, in response to the classifying, the information model that has been annotated into a plurality of relational element mappings and a plurality of mark-up language element mappings; and generating, in response to the partitioning, a plurality of database schemas associated with the information model that has been annotated. | 1. A method, with an information processing system, for generating a plurality of candidate database schemas including relational and mark-up language elements, the method comprising: receiving an information model comprising a plurality of entities and at least one relationship defined there between, wherein the information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic; analyzing the information model that has been annotated; associating a score, in response to the analyzing, with each entity based at least in part on attributes associated with each entity; classifying, in response to associating a score, each entity as one of a relational element and a mark-up language element; partitioning, in response to the classifying, the information model that has been annotated into a plurality of relational element mappings and a plurality of mark-up language element mappings; and generating, in response to the partitioning, a plurality of database schemas associated with the information model that has been annotated. 5. The method of claim 1 , wherein the partitioning further comprises: generating for each entity classified as a relational element a table comprising a relational column; and defining a relational schema for the column. | 0.855469 |
2. The method of claim 1 wherein: the group definition syntax provides for assignment of a group ID to each defined group; the group IDs can be used in SQL functions as an argument in SQL functions in place of a column name; the defining of the first group of columns includes assignment of a first group ID to the first group of columns; and the performance of the first group function includes placing the first group ID into an argument portion of an SQL function. | 2. The method of claim 1 wherein: the group definition syntax provides for assignment of a group ID to each defined group; the group IDs can be used in SQL functions as an argument in SQL functions in place of a column name; the defining of the first group of columns includes assignment of a first group ID to the first group of columns; and the performance of the first group function includes placing the first group ID into an argument portion of an SQL function. 4. The method of claim 2 further comprising: outputting a result of the first group function in human understandable form and format. | 0.919879 |
12. A system for inputting a place, comprising: a terminal device including: a first communicator configured to receive a text; and a first processor configured to receive the text from the first communicator, to identify a sender who transmits the text, to determine whether to extract place-associated information from the text according to the sender who transmits the text, and to search for the place-associated information from the text; and a navigation device including: a second communicator configured to communicate with the terminal device; and a second processor configured to receive the place-associated information or a text including the place-associated information from the terminal device if the place-associated information is searched for from the text, and configured to establish a destination on the basis of the place-associated information, wherein the place-associated information includes a sender intention text including an expression associated with intention of the sender, wherein the sender intention text comprises at least one word or phrase that is related to a request to move to a specific place, wherein the terminal device or the navigation device searches for the sender intention text from the text using a sender intention text database. | 12. A system for inputting a place, comprising: a terminal device including: a first communicator configured to receive a text; and a first processor configured to receive the text from the first communicator, to identify a sender who transmits the text, to determine whether to extract place-associated information from the text according to the sender who transmits the text, and to search for the place-associated information from the text; and a navigation device including: a second communicator configured to communicate with the terminal device; and a second processor configured to receive the place-associated information or a text including the place-associated information from the terminal device if the place-associated information is searched for from the text, and configured to establish a destination on the basis of the place-associated information, wherein the place-associated information includes a sender intention text including an expression associated with intention of the sender, wherein the sender intention text comprises at least one word or phrase that is related to a request to move to a specific place, wherein the terminal device or the navigation device searches for the sender intention text from the text using a sender intention text database. 13. The system according to claim 12 , wherein the place-associated information further includes at least one of an address, a region name, or a place type. | 0.632789 |
20. The non-transitory computer readable storage medium of claim 19 , wherein the one or more potential ambiguities comprises a plurality of matching attributes for the value. | 20. The non-transitory computer readable storage medium of claim 19 , wherein the one or more potential ambiguities comprises a plurality of matching attributes for the value. 22. The non-transitory computer readable storage medium of claim 20 , wherein the value comprises at least one of a set of alphanumeric characters and a set of special characters, wherein the special characters comprise at least one of a punctuation marks, a symbol, a picture, and a character selected from a language that uses non-alphabetic characters. | 0.908612 |
39. A multiplayer game for teaching learners a multiplicity of target education skills from a server communicated through a learner connection to a learner's control module comprising: a. means for engaging each learner in target education skill practice; b. means for each learner to receive one or more game possessions for demonstrating the target education skills; c. means for measuring game performance; d. means for game activities without target education skills; and e. means for a learner to receive feedback on errors in demonstration of target education skills by reduced game performance of possessions in game activities without target education skills. | 39. A multiplayer game for teaching learners a multiplicity of target education skills from a server communicated through a learner connection to a learner's control module comprising: a. means for engaging each learner in target education skill practice; b. means for each learner to receive one or more game possessions for demonstrating the target education skills; c. means for measuring game performance; d. means for game activities without target education skills; and e. means for a learner to receive feedback on errors in demonstration of target education skills by reduced game performance of possessions in game activities without target education skills. 40. The multiplayer game of claim 39 further comprising means for a learner to improve possession performance in game activities. | 0.84417 |
8. A computer readable medium comprising machine readable instructions that, when executed by a computer, perform a method comprising: receiving a demand for a display of a document; and in a real time response to the demand, and without further input from a user: accessing a database to identify one or more auxiliary files and a location for each said auxiliary file; attempting to validate the one or more auxiliary files using a predetermined schema and the one or more auxiliary files: in an event that validating the one or more auxiliary files is successful: if at least one of the one or more auxiliary files are valid: facilitating a merging of information from a main file with information from the at least one of the said auxiliary files, wherein the facilitating comprises: determining from the predetermined schema which information in the main file is to be replaced by information in the at least one auxiliary files; determining from the predetermined schema which information in the main file is to be replaced by information in the at least one auxiliary files; determining from the predetermined schema which information in the at least one auxiliary files is to be appended to the main file; determining from the predetermined schema which information in the main file is to be removed; and displaying the document using information merged from the main document and the at least one auxiliary file; and in an event that no said auxiliary file is validated, generating the document using only the information from the main file; and displaying the document. | 8. A computer readable medium comprising machine readable instructions that, when executed by a computer, perform a method comprising: receiving a demand for a display of a document; and in a real time response to the demand, and without further input from a user: accessing a database to identify one or more auxiliary files and a location for each said auxiliary file; attempting to validate the one or more auxiliary files using a predetermined schema and the one or more auxiliary files: in an event that validating the one or more auxiliary files is successful: if at least one of the one or more auxiliary files are valid: facilitating a merging of information from a main file with information from the at least one of the said auxiliary files, wherein the facilitating comprises: determining from the predetermined schema which information in the main file is to be replaced by information in the at least one auxiliary files; determining from the predetermined schema which information in the main file is to be replaced by information in the at least one auxiliary files; determining from the predetermined schema which information in the at least one auxiliary files is to be appended to the main file; determining from the predetermined schema which information in the main file is to be removed; and displaying the document using information merged from the main document and the at least one auxiliary file; and in an event that no said auxiliary file is validated, generating the document using only the information from the main file; and displaying the document. 9. A computer readable medium as recited in claim 8 , wherein the specification of a predetermined schema comprises a plurality of attributes comprising: a placement attribute, a target attribute, a component attribute. | 0.522852 |
15. The method of claim 11 , wherein, after said anchor is built, said chat data is categorized into said team/department names using said filters. | 15. The method of claim 11 , wherein, after said anchor is built, said chat data is categorized into said team/department names using said filters. 16. The method of claim 15 , wherein specific filters are applied for voice categorization. | 0.92801 |
11. The method of claim 7 , wherein an appropriate set of criteria is determined to find similarity in the received contextual information. | 11. The method of claim 7 , wherein an appropriate set of criteria is determined to find similarity in the received contextual information. 12. The method of claim 11 , wherein the received contextual information with the similarity is aggregated and, if the aggregation meets a corresponding threshold, an event is generated. | 0.947462 |
1. A system comprising: a processor; an objective occurrence data acquisition module configured to acquire objective occurrence data, the objective occurrence data to be acquired including data indicating occurrence of at least one objective occurrence; a subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data; a subjective user state data acquisition module configured to acquire the subjective user state data; and a correlation module configured to correlate the objective occurrence data with the subjective user state data, wherein said correlation module configured to correlate the objective occurrence data with the subjective user state data comprises: a sequential pattern determination module configured to determine at least one sequential pattern associated with occurrence of the at least one subjective user state and occurrence of the at least one objective occurrence. | 1. A system comprising: a processor; an objective occurrence data acquisition module configured to acquire objective occurrence data, the objective occurrence data to be acquired including data indicating occurrence of at least one objective occurrence; a subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data; a subjective user state data acquisition module configured to acquire the subjective user state data; and a correlation module configured to correlate the objective occurrence data with the subjective user state data, wherein said correlation module configured to correlate the objective occurrence data with the subjective user state data comprises: a sequential pattern determination module configured to determine at least one sequential pattern associated with occurrence of the at least one subjective user state and occurrence of the at least one objective occurrence. 31. The system of claim 1 , wherein said subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data comprises: a subjective user state data solicitation module configured to solicit data that indicates one or more attributes associated with the at least one subjective state. | 0.606324 |
1. A computer-implemented method for mapping at run time a value to a text in a system, the system comprising a first computer including a user interface and a second computer including a service adapter, the method comprising: receiving at run time a request, by a service manager and from the user interface at the first computer, the request being associated with an object node, the request made in response to the request from the user interface to obtain configuration information for a page to be presented at the user interface, the service manager including an application programming interface to receive the request, the service manager configured to analyze the request to determine whether to instantiate the service adapter to map the value to the text; instantiating, by a service manager at the second computer, the service adapter for mapping at run time the value included in the object node to the text included in a text node based on a text association selected at runtime from a plurality of text associations, the text associations determined before run time, each of the text associations linking the object node to a different text node including a corresponding text to be mapped at run time to the object node, the object node including a text enabled field to indicate that the object node includes the text association and text node to be mapped; and providing to the user interface at run time, the text determined based on the text association, such that the text is responsive to the request from the user interface. | 1. A computer-implemented method for mapping at run time a value to a text in a system, the system comprising a first computer including a user interface and a second computer including a service adapter, the method comprising: receiving at run time a request, by a service manager and from the user interface at the first computer, the request being associated with an object node, the request made in response to the request from the user interface to obtain configuration information for a page to be presented at the user interface, the service manager including an application programming interface to receive the request, the service manager configured to analyze the request to determine whether to instantiate the service adapter to map the value to the text; instantiating, by a service manager at the second computer, the service adapter for mapping at run time the value included in the object node to the text included in a text node based on a text association selected at runtime from a plurality of text associations, the text associations determined before run time, each of the text associations linking the object node to a different text node including a corresponding text to be mapped at run time to the object node, the object node including a text enabled field to indicate that the object node includes the text association and text node to be mapped; and providing to the user interface at run time, the text determined based on the text association, such that the text is responsive to the request from the user interface. 4. The method of claim 1 , wherein instantiating further comprises: determining the text association by modeling object nodes in a repository. | 0.5 |
9. A computer system comprising: a central processing unit (CPU); a memory coupled to said CPU; a computer-readable, tangible storage device coupled to said CPU, said storage device containing instructions that are carried out by said CPU via said memory to implement a method of querying multifaceted information, said method comprising: constructing an inverted index having a plurality of unique indexed tokens associated with a plurality of posting lists in a one-to-one correspondence, each posting list including one or more documents of a plurality of documents, wherein an indexed token of said plurality of unique indexed tokens is one of a facet token included as an annotation in a document of said plurality of documents and a path prefix of said facet token, wherein said annotation indicates a path within a tree structure representing a facet that includes said document, said tree structure including a plurality of nodes representing a category and one or more sub-categories that categorize said document; receiving a query that includes a plurality of constraints on said plurality of documents, said plurality of constraints being associated with multiple indexed tokens of said plurality of unique indexed tokens and multiple posting lists corresponding to said multiple indexed tokens; and executing said query by identifying said multiple posting lists via a utilization of said plurality of constraints and said inverted index, and intersecting said multiple posting lists to obtain a result of said query. | 9. A computer system comprising: a central processing unit (CPU); a memory coupled to said CPU; a computer-readable, tangible storage device coupled to said CPU, said storage device containing instructions that are carried out by said CPU via said memory to implement a method of querying multifaceted information, said method comprising: constructing an inverted index having a plurality of unique indexed tokens associated with a plurality of posting lists in a one-to-one correspondence, each posting list including one or more documents of a plurality of documents, wherein an indexed token of said plurality of unique indexed tokens is one of a facet token included as an annotation in a document of said plurality of documents and a path prefix of said facet token, wherein said annotation indicates a path within a tree structure representing a facet that includes said document, said tree structure including a plurality of nodes representing a category and one or more sub-categories that categorize said document; receiving a query that includes a plurality of constraints on said plurality of documents, said plurality of constraints being associated with multiple indexed tokens of said plurality of unique indexed tokens and multiple posting lists corresponding to said multiple indexed tokens; and executing said query by identifying said multiple posting lists via a utilization of said plurality of constraints and said inverted index, and intersecting said multiple posting lists to obtain a result of said query. 11. The system of claim 9 , wherein said constructing said inverted index comprises: generating a full path token and a full path token posting list associated therewith by said inverted index, said full path token posting list including a plurality of identifiers representing said plurality of documents, wherein an identifier of said plurality of identifiers represents said document and includes a payload value, said payload value identifying a full path of said document in said tree structure, and said payload value including a set of full path indicators provided by a scheme that uniquely labels each sibling node of said tree structure. | 0.619651 |
10. A device for generating and retrieving opinion pairs having sentiment orientation based impact relations, comprising: a central processing unit (CPU) receiving a plurality of object-oriented opinions, said CPU extracting impact-related object-oriented opinions from said plurality of object-oriented opinions, said impact-related object-oriented opinions comprising any object-oriented opinions in said plurality of object-oriented opinions and having impact relations with any other object-oriented opinions in said plurality of object-oriented opinions, said CPU analyzing said impact-related object-oriented opinions to determine sentiment orientations between pairs of said impact-related object-oriented opinions, each sentiment orientation indicating whether a first object-oriented opinion has one of a positive impact and a negative impact on a second object-oriented opinion, said CPU calculating confidence scores for said impact relations between said impact-related object-oriented opinions, said CPU establishing an impact relation database and storing, in said database in a memory unit, each pair of said impact-related object-oriented opinions with an associated sentiment orientation and an associated confidence score, said CPU retrieving, from said impact relations database in response to a query, any of said pairs of said impact-related object-oriented opinions associated with an object of said query, said CPU calculating said associated confidence score for a specific pair of said impact-related object-oriented opinions, said specific pair comprising a specific first object-oriented opinion that impacts a specific second object-oriented opinion, by determining a number of other pairs of said impact-related object-oriented opinions that comprise other first object-oriented opinions that impact said specific second object-oriented opinion and dividing 1 by said number. | 10. A device for generating and retrieving opinion pairs having sentiment orientation based impact relations, comprising: a central processing unit (CPU) receiving a plurality of object-oriented opinions, said CPU extracting impact-related object-oriented opinions from said plurality of object-oriented opinions, said impact-related object-oriented opinions comprising any object-oriented opinions in said plurality of object-oriented opinions and having impact relations with any other object-oriented opinions in said plurality of object-oriented opinions, said CPU analyzing said impact-related object-oriented opinions to determine sentiment orientations between pairs of said impact-related object-oriented opinions, each sentiment orientation indicating whether a first object-oriented opinion has one of a positive impact and a negative impact on a second object-oriented opinion, said CPU calculating confidence scores for said impact relations between said impact-related object-oriented opinions, said CPU establishing an impact relation database and storing, in said database in a memory unit, each pair of said impact-related object-oriented opinions with an associated sentiment orientation and an associated confidence score, said CPU retrieving, from said impact relations database in response to a query, any of said pairs of said impact-related object-oriented opinions associated with an object of said query, said CPU calculating said associated confidence score for a specific pair of said impact-related object-oriented opinions, said specific pair comprising a specific first object-oriented opinion that impacts a specific second object-oriented opinion, by determining a number of other pairs of said impact-related object-oriented opinions that comprise other first object-oriented opinions that impact said specific second object-oriented opinion and dividing 1 by said number. 13. The device according to claim 10 , for each of said pairs of said impact-related object-oriented, said associated confidence score indicates a degree of influence said first object-oriented opinion has on said second object-oriented opinion. | 0.5 |
10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. | 10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. 14. The computer program product of claim 10 , wherein: identifying an aspect of the XML electronic document structure that fails to conform to rules associated with the XML electronic document includes identifying one or more aspects of the XML electronic document structure that fail to conform to rules associated with the document; and applying the correction selected by the input includes applying the correction selected by the input to the XML electronic document, thereby bringing the entire XML electronic document structure into conformance with the rules. | 0.517333 |
20. A computer-readable medium having thereon computer-executable instructions for performing a method comprising: providing language constructs comprising program state reversion constructs; receiving a representation of a program having one or more program state reversion constructs comprising a reversion indication construct indicating a series of instructions to revert; inserting code into the program comprising: code for recording program state before modifications are made by the series of instructions indicated by the reversion indication construct, and code for reverting program state to recorded values when an exception arises from the series of instructions indicated by the reversion indication construct; and executing the program and inserted code comprising: recording program state prior to executing the series of instructions indicated by the reversion indication construct in a data structure indicated for stack modifications, the data structure comprising a first linked list saving program state for value types that are changed in heap memory, a second linked list saving program state for value types that are changed in non-heap memory, a third linked list saving program state for object references that are changed in heap memory and a fourth linked list for saving program state for object references that are changed in non-heap memory, and upon generating an exception while executing the series of instructions indicated by the reversion indication construct, reverting program state according to the recorded program state. | 20. A computer-readable medium having thereon computer-executable instructions for performing a method comprising: providing language constructs comprising program state reversion constructs; receiving a representation of a program having one or more program state reversion constructs comprising a reversion indication construct indicating a series of instructions to revert; inserting code into the program comprising: code for recording program state before modifications are made by the series of instructions indicated by the reversion indication construct, and code for reverting program state to recorded values when an exception arises from the series of instructions indicated by the reversion indication construct; and executing the program and inserted code comprising: recording program state prior to executing the series of instructions indicated by the reversion indication construct in a data structure indicated for stack modifications, the data structure comprising a first linked list saving program state for value types that are changed in heap memory, a second linked list saving program state for value types that are changed in non-heap memory, a third linked list saving program state for object references that are changed in heap memory and a fourth linked list for saving program state for object references that are changed in non-heap memory, and upon generating an exception while executing the series of instructions indicated by the reversion indication construct, reverting program state according to the recorded program state. 22. The computer-readable medium of claim 20 , wherein the recording program state only records only a first state change. | 0.578316 |
1. A method comprising the steps of: analyzing an audio communication between a first party and a second party to develop a transcript of the audio communication; analyzing words spoken during the audio communication by at least one computer processor to develop a set of keywords, in which the set of keywords comprises a subset of the words spoken during the audio communication; providing a graphical user interface (“GUI”) to display on a computer monitor, the GUI comprising a timeline representing the audio communication; displaying a plurality of sets of icons on the GUI in conjunction with the timeline, wherein each set of icons comprises a text-based icon and an audio-based icon representing an occurrence of a keyword in the audio communication, the keyword being from the set of keywords and the text-based icon and the audio-based icon being displayed on the GUI at one or more locations with respect to the timeline proximate to a time of the occurrence of the keyword in the audio communication; receiving an input from a user as a result of the user selecting a particular text-based icon or a particular audio-based icon representing a particular occurrence of a particular keyword in the audio communication; and after receiving the input: displaying a portion of the transcript containing the particular occurrence of the particular keyword if the user selected the particular text-based icon representing the particular occurrence of the particular keyword; and playing a portion of the audio communication containing the particular occurrence of the particular keyword if the user selected the particular audio-based icon representing the particular occurrence of the particular keyword. | 1. A method comprising the steps of: analyzing an audio communication between a first party and a second party to develop a transcript of the audio communication; analyzing words spoken during the audio communication by at least one computer processor to develop a set of keywords, in which the set of keywords comprises a subset of the words spoken during the audio communication; providing a graphical user interface (“GUI”) to display on a computer monitor, the GUI comprising a timeline representing the audio communication; displaying a plurality of sets of icons on the GUI in conjunction with the timeline, wherein each set of icons comprises a text-based icon and an audio-based icon representing an occurrence of a keyword in the audio communication, the keyword being from the set of keywords and the text-based icon and the audio-based icon being displayed on the GUI at one or more locations with respect to the timeline proximate to a time of the occurrence of the keyword in the audio communication; receiving an input from a user as a result of the user selecting a particular text-based icon or a particular audio-based icon representing a particular occurrence of a particular keyword in the audio communication; and after receiving the input: displaying a portion of the transcript containing the particular occurrence of the particular keyword if the user selected the particular text-based icon representing the particular occurrence of the particular keyword; and playing a portion of the audio communication containing the particular occurrence of the particular keyword if the user selected the particular audio-based icon representing the particular occurrence of the particular keyword. 6. The method of claim 1 , wherein the GUI identifies at least one of the first party and the second party as being associated with each occurrence of the keywords in the audio communication. | 0.818966 |
10. The processing device of claim 8 , wherein the detecting an existence of a tabular structure within handwritten input including a plurality of atoms, further comprises: detecting a left grouping structure based on the plurality of atoms, removing from consideration atoms forming the left grouping structure and leaving a remaining group of atoms for consideration, projecting the remaining group of atoms onto an x-axis and a y-axis to determine a number of rows and a number of columns, assigning ones of the remaining group of atoms to respective cells of the rows and the columns based on a position of each of the respective ones of the remaining group of atoms, merging a pair of the rows of cells or a pair of the columns of cells when at least one empty cell exists to eliminate the at least one empty cell, and validating a final number of rows and a final number of columns. | 10. The processing device of claim 8 , wherein the detecting an existence of a tabular structure within handwritten input including a plurality of atoms, further comprises: detecting a left grouping structure based on the plurality of atoms, removing from consideration atoms forming the left grouping structure and leaving a remaining group of atoms for consideration, projecting the remaining group of atoms onto an x-axis and a y-axis to determine a number of rows and a number of columns, assigning ones of the remaining group of atoms to respective cells of the rows and the columns based on a position of each of the respective ones of the remaining group of atoms, merging a pair of the rows of cells or a pair of the columns of cells when at least one empty cell exists to eliminate the at least one empty cell, and validating a final number of rows and a final number of columns. 11. The processing device of claim 10 , wherein the merging a pair of the rows of cells or a pair of the columns of cells when at least one empty cell exists to eliminate the at least one empty cell, further comprises: determining whether more empty cells exist in a row of one of the at least one empty cell or in a column of the at least one empty cell, merging a pair of rows of cells when more empty cells are determined to exist in a row of one of the at least one empty cell, merging a pair of columns of cells when more empty cells are determined to exist in a column of one of the at least one empty cell, and choosing a merging direction such that a number of remaining empty cells will be a minimum number after merging. | 0.75682 |
21. An automated method for providing awareness of speech habits of a speaker comprising: providing a speech processing system wearable or hand-held by the speaker; processing by the speech processing system speech input from the speaker during a speaking session; processing by the speech processing system speech input from a different speaker during the speaking session; segmenting in real time by the speech processing system the speech input from the speaker from the speech input from the different speaker; analyzing by the speech processing system speech processing results of the speaker using pre-specified criteria to identify a speech habit of the speaker; and alerting the speaker in real time while the speaker is speaking during the speaking session from which the speech input of the speaker and the speech input of the different speaker is segmented, wherein the speech input of the speaker is analyzed to detect one or more words or expressions or sounds, if any, which are specified in a vocabulary list, in the speech input of the user, wherein an identified speech habit comprises exceeding a range of volume of speaking a word or expression specified in the vocabulary list, and wherein a counter is incremented corresponding to a number of instances of exceeding a range of volume in the speech input from the speaker and the counter is compared to a repetition threshold for determining a speech habit in the speech input from the speaker based upon a predetermined value of the counter within a predetermined time period. | 21. An automated method for providing awareness of speech habits of a speaker comprising: providing a speech processing system wearable or hand-held by the speaker; processing by the speech processing system speech input from the speaker during a speaking session; processing by the speech processing system speech input from a different speaker during the speaking session; segmenting in real time by the speech processing system the speech input from the speaker from the speech input from the different speaker; analyzing by the speech processing system speech processing results of the speaker using pre-specified criteria to identify a speech habit of the speaker; and alerting the speaker in real time while the speaker is speaking during the speaking session from which the speech input of the speaker and the speech input of the different speaker is segmented, wherein the speech input of the speaker is analyzed to detect one or more words or expressions or sounds, if any, which are specified in a vocabulary list, in the speech input of the user, wherein an identified speech habit comprises exceeding a range of volume of speaking a word or expression specified in the vocabulary list, and wherein a counter is incremented corresponding to a number of instances of exceeding a range of volume in the speech input from the speaker and the counter is compared to a repetition threshold for determining a speech habit in the speech input from the speaker based upon a predetermined value of the counter within a predetermined time period. 30. The method of claim 21 , wherein alerting the speaker comprises providing an audio alert signal. | 0.641575 |
4. In a speech recognition system in which labels, from an alphabet of labels, are generated by an acoustic processor at successive label times in response to a speech input and in which words or portions thereof are represented probabilistically by Markov models, wherein each Markov model is characterized by (i) states, (ii) transitions between states, and (iii) probabiltity items wherein some probability items have previously defined probability values .theta.' which correspond to the likelihood of a transition in a given model being taken and wherein other probability items have previously defined probability values .theta.' which correspond to the likelihood of a specific label being produced at a transition of one or more predefined transitions in a given model, a method of evaluating counts from which enhanced probability values are derived comprising the steps of: (a) storing for each probability item a preliminary value .theta.'; (b) defining and storing a set of counts wherein each probability item is determined from the value of at least one count associated therewith in storage, each count in the set having a value corresponding to the probability of a specific transition .tau.i being taken from a specific state Sj given (i) a specific label interval time t, (ii) a specific string of generated labels, and (iii) the stored .theta.' values; (c) uttering a known subject word and generating outputs in response thereto; (d) selecting an incorrect word other than the known word and, for each count used in deriving the value of a probability item in said incorrect word model, determining a minus count value from the generated outputs of the uttered known word; and (e) defining an adjusted count value wherein the stored value of each count serves as an addend and the minus value of each count serves as a subtrahend thereof. | 4. In a speech recognition system in which labels, from an alphabet of labels, are generated by an acoustic processor at successive label times in response to a speech input and in which words or portions thereof are represented probabilistically by Markov models, wherein each Markov model is characterized by (i) states, (ii) transitions between states, and (iii) probabiltity items wherein some probability items have previously defined probability values .theta.' which correspond to the likelihood of a transition in a given model being taken and wherein other probability items have previously defined probability values .theta.' which correspond to the likelihood of a specific label being produced at a transition of one or more predefined transitions in a given model, a method of evaluating counts from which enhanced probability values are derived comprising the steps of: (a) storing for each probability item a preliminary value .theta.'; (b) defining and storing a set of counts wherein each probability item is determined from the value of at least one count associated therewith in storage, each count in the set having a value corresponding to the probability of a specific transition .tau.i being taken from a specific state Sj given (i) a specific label interval time t, (ii) a specific string of generated labels, and (iii) the stored .theta.' values; (c) uttering a known subject word and generating outputs in response thereto; (d) selecting an incorrect word other than the known word and, for each count used in deriving the value of a probability item in said incorrect word model, determining a minus count value from the generated outputs of the uttered known word; and (e) defining an adjusted count value wherein the stored value of each count serves as an addend and the minus value of each count serves as a subtrahend thereof. 5. The method of claim 4 comprising the further steps of: (f) for each count used in deriving a probability item in the known word model, determining a plus count value from the generated outputs of the uttered known word; (g) the plus count value of a subject count serving as an addend in defining the adjusted count value for the subject count; the adjusted value of a subject count being determined by adding the stored value and plus count value and subtracting the minus count value. | 0.591478 |
7. A method for receiving an encoded audio/video data stream to be processed by a receiver decoder comprising a decoding unit and a processing unit, said data having been encrypted by control words, a cryptogram relative to said control words being received in a security message included within a control message stream, said security message also containing at least one instruction, including the following steps: a. downloading at least two micro programs contained in the security messages, these micro programs being executable by the processing unit; b. storing said micro programs in a micro program memory of said processing unit; c. receiving a security message containing a cryptogram relative to a control word and at least one instruction relative to the control word and extracting the cryptogram and the instruction; d. selecting one micro program among the micro programs according to the value of the instruction; e. executing said selected micro program with at least the extracted cryptogram as an entry variable of the selected micro program; f. in response to executing the selected micro program, calculate the control word; and g. transmit the calculated control word to an audio/video decoding unit to decrypt the encrypted audio/video digital data. | 7. A method for receiving an encoded audio/video data stream to be processed by a receiver decoder comprising a decoding unit and a processing unit, said data having been encrypted by control words, a cryptogram relative to said control words being received in a security message included within a control message stream, said security message also containing at least one instruction, including the following steps: a. downloading at least two micro programs contained in the security messages, these micro programs being executable by the processing unit; b. storing said micro programs in a micro program memory of said processing unit; c. receiving a security message containing a cryptogram relative to a control word and at least one instruction relative to the control word and extracting the cryptogram and the instruction; d. selecting one micro program among the micro programs according to the value of the instruction; e. executing said selected micro program with at least the extracted cryptogram as an entry variable of the selected micro program; f. in response to executing the selected micro program, calculate the control word; and g. transmit the calculated control word to an audio/video decoding unit to decrypt the encrypted audio/video digital data. 8. The method according to claim 7 , wherein the micro program is in an encrypted and/or authenticated form in the security message, and that it includes a decryption step and/or authentication of the micro program before its execution. | 0.5 |
13. The method of claim 8 further comprising indexing fragments of the first text and indexing fragments of the second text in accordance with determined correspondence of the fragments of the first and the second texts. | 13. The method of claim 8 further comprising indexing fragments of the first text and indexing fragments of the second text in accordance with determined correspondence of the fragments of the first and the second texts. 15. The method of claim 13 wherein indexing further comprises indexing semantic structures and their parameters of the first text and the second text. | 0.953822 |
1. A method for automatic ranking of target files according to a predefined scheme, comprising the steps of: building a database of reference files already ranked according to the predefined scheme; for each target file: i) determining a neighborhood of the target file among the reference files in the database of reference files, and forming a training set comprising reference files of this neighborhood, versus which neighborhood as a whole the target file is to be assessed, wherein said step of forming a training set comprises extracting a feature vector of the target file and finding n closest neighbors of the feature vector of the target file among features vectors in the database of reference files, and wherein said finding n closest neighbors comprises using one of: i) Euclidean distance, ii) cosine distance and iii) Jensen-Shannon distribution similarity; ii) building a test set from features of the target file; iii) dynamically generating a learning model from the training set, the learning model defining a correlation between the reference files in the training set and a rank thereof according to the predefined scheme; and iv) applying the learning model to the test set; whereby a rank corresponding to the target file is predicted according to the predefined scheme. | 1. A method for automatic ranking of target files according to a predefined scheme, comprising the steps of: building a database of reference files already ranked according to the predefined scheme; for each target file: i) determining a neighborhood of the target file among the reference files in the database of reference files, and forming a training set comprising reference files of this neighborhood, versus which neighborhood as a whole the target file is to be assessed, wherein said step of forming a training set comprises extracting a feature vector of the target file and finding n closest neighbors of the feature vector of the target file among features vectors in the database of reference files, and wherein said finding n closest neighbors comprises using one of: i) Euclidean distance, ii) cosine distance and iii) Jensen-Shannon distribution similarity; ii) building a test set from features of the target file; iii) dynamically generating a learning model from the training set, the learning model defining a correlation between the reference files in the training set and a rank thereof according to the predefined scheme; and iv) applying the learning model to the test set; whereby a rank corresponding to the target file is predicted according to the predefined scheme. 16. The method of claim 1 , wherein said step of dynamically generating a learning model comprises applying a Support Vector Model to the n closest neighbors of the target file's feature vector in the database of reference files. | 0.532725 |
15. A non-transitory computer-readable storage medium storing computer program instructions executed by a computer processor for formatting a user-generated comment for display on a page of a website, the computer program instructions comprising instructions for: retrieving the comment from a repository; determining whether the comment includes a programmatically identifiable watermark; responsive to the comment including a programmatically identifiable watermark, adjusting a spam score associated with the comment, the adjusted spam score indicating high likelihood that the comment is a form of spam; and responsive to comment not including a programmatically identifiable watermark: determining whether the comment is a form of spam; responsive to the comment being spam, adding a programmatically identifiable watermark to the comment; and formatting the comment with the programmatically identifiable watermark for display on the page. | 15. A non-transitory computer-readable storage medium storing computer program instructions executed by a computer processor for formatting a user-generated comment for display on a page of a website, the computer program instructions comprising instructions for: retrieving the comment from a repository; determining whether the comment includes a programmatically identifiable watermark; responsive to the comment including a programmatically identifiable watermark, adjusting a spam score associated with the comment, the adjusted spam score indicating high likelihood that the comment is a form of spam; and responsive to comment not including a programmatically identifiable watermark: determining whether the comment is a form of spam; responsive to the comment being spam, adding a programmatically identifiable watermark to the comment; and formatting the comment with the programmatically identifiable watermark for display on the page. 19. The non-transitory computer-readable storage medium of claim 15 , wherein the computer program instructions for determining whether the comment includes a programmatically identifiable watermark further comprise instructions for: identifying the programmatically identifiable watermark based on whether the comment is displayed in a particular font. | 0.708101 |
19. A computer program product comprising machine-readable program code stored on a non-transitory computer-readable medium to be executed by one or more processors, the program code including instructions to: enable access to the data of the organization for a support representative associated with a management organization that maintains the data for the organization stored in an on-demand database system by the one or more processors generating a Security Assertion Markup Language (SAML) assertion upon a data access request by the support representative, the-SAML assertion establishing an identity of the support representative as a member of a support user class that is granted defined administrative privileges with respect to the data; initiate a network session to the organization upon the data access request of the support representative, wherein the network session associates the administrative privileges to the support user representative to enable access to the data to the extent of the administrative privileges; and grant access to the on-demand database application associated with the data to the support representative as an organization user for a limited term, the support representative being different from the organization user, wherein the support representative is granted use privileges of the on-demand database application for a limited term. | 19. A computer program product comprising machine-readable program code stored on a non-transitory computer-readable medium to be executed by one or more processors, the program code including instructions to: enable access to the data of the organization for a support representative associated with a management organization that maintains the data for the organization stored in an on-demand database system by the one or more processors generating a Security Assertion Markup Language (SAML) assertion upon a data access request by the support representative, the-SAML assertion establishing an identity of the support representative as a member of a support user class that is granted defined administrative privileges with respect to the data; initiate a network session to the organization upon the data access request of the support representative, wherein the network session associates the administrative privileges to the support user representative to enable access to the data to the extent of the administrative privileges; and grant access to the on-demand database application associated with the data to the support representative as an organization user for a limited term, the support representative being different from the organization user, wherein the support representative is granted use privileges of the on-demand database application for a limited term. 20. The computer program product of claim 19 wherein the data comprises at least one of: metadata related to usage parameters of the organization to resources of the system, and metadata of an application installed for use by the organization. | 0.511565 |
17. A non-transitory computer readable storage medium having computer readable program codes embodied in the computer readable storage medium for automated auditing of an insurance agreement, the computer readable program codes, when executed, cause a computer to perform: providing the insurance agreement for determining whether the insurance agreement is in compliance with a standard; prompting an input of a first selection criteria including at least one attribute describing the insurance agreement, the first selection criteria identifying a type of insurance agreement to be audited including at least one of life insurance, health insurance, personal property insurance, business casualty insurance, key-man insurance, and board of director's liability insurance; receiving the first selection criteria; automatically retrieving a second selection criteria including other attributes describing the insurance agreement, the second selection criteria based on the first selection criteria, the second selection criteria including at least a face value of the insurance agreement; automatically selecting a subset of questions from a plurality of questions in accordance with the first and second selection criteria, the subset of questions associated with at least one of the attributes describing the insurance agreement, at least one question of the subset of questions is assigned a question weight; organizing the subset of questions into a plurality of pre-assigned categories, wherein each question included within the plurality of questions is pre-assigned to a category based on subject matter of the associated question, the plurality of pre-assigned categories including at least one of coverage, compliance, pricing, risk selection, underwriting, and line of business, and at least one of the plurality of pre-assigned categories is assigned a category weight; presenting the subset to a user; receiving answers to the subset from said user; scoring the answers to generate an answer score for each of the answers received from the user and modifying the answer score in accordance with the category weight; generating a categorical score for each category associated with the subset of questions, wherein the categorical score is a function of one or more answer scores; generating an overall score associated with the subset of questions, the overall score being a function of one or more answer scores; comparing the generated categorical scores to corresponding categorical threshold scores to determine whether the insurance agreement is in compliance with the standard; and comparing the overall score to a corresponding threshold score to determine whether the insurance agreement is in compliance with the standard, wherein at least one question of the subset of questions is assigned a zero-weight value such that the answer to a zero-weight value question is not scored, wherein each question is associated with at least two answer options, and wherein an answer weight for each question varies between the at least two answer options. | 17. A non-transitory computer readable storage medium having computer readable program codes embodied in the computer readable storage medium for automated auditing of an insurance agreement, the computer readable program codes, when executed, cause a computer to perform: providing the insurance agreement for determining whether the insurance agreement is in compliance with a standard; prompting an input of a first selection criteria including at least one attribute describing the insurance agreement, the first selection criteria identifying a type of insurance agreement to be audited including at least one of life insurance, health insurance, personal property insurance, business casualty insurance, key-man insurance, and board of director's liability insurance; receiving the first selection criteria; automatically retrieving a second selection criteria including other attributes describing the insurance agreement, the second selection criteria based on the first selection criteria, the second selection criteria including at least a face value of the insurance agreement; automatically selecting a subset of questions from a plurality of questions in accordance with the first and second selection criteria, the subset of questions associated with at least one of the attributes describing the insurance agreement, at least one question of the subset of questions is assigned a question weight; organizing the subset of questions into a plurality of pre-assigned categories, wherein each question included within the plurality of questions is pre-assigned to a category based on subject matter of the associated question, the plurality of pre-assigned categories including at least one of coverage, compliance, pricing, risk selection, underwriting, and line of business, and at least one of the plurality of pre-assigned categories is assigned a category weight; presenting the subset to a user; receiving answers to the subset from said user; scoring the answers to generate an answer score for each of the answers received from the user and modifying the answer score in accordance with the category weight; generating a categorical score for each category associated with the subset of questions, wherein the categorical score is a function of one or more answer scores; generating an overall score associated with the subset of questions, the overall score being a function of one or more answer scores; comparing the generated categorical scores to corresponding categorical threshold scores to determine whether the insurance agreement is in compliance with the standard; and comparing the overall score to a corresponding threshold score to determine whether the insurance agreement is in compliance with the standard, wherein at least one question of the subset of questions is assigned a zero-weight value such that the answer to a zero-weight value question is not scored, wherein each question is associated with at least two answer options, and wherein an answer weight for each question varies between the at least two answer options. 23. The non-transitory computer readable storage medium of claim 17 , wherein the method further comprises: comparing the answer score of at least one question of the subset of questions to an associated threshold value; indicating the result of the comparison; and providing the user a score improvement recommendation including identifying at least one question based on the comparison of the answer score to the associated threshold value and providing a guideline to improve at least one of the categorical score and the overall score. | 0.5 |
1. A method comprising: receiving a set of queries at a computing device, wherein each query is associated with a user who provided the query and each query has an associated time; dividing the received set of queries into a set of queries that are commercial queries and a set of queries that are non-commercial queries, by the computing device; generating a first set of query communities from the set of queries that are non-commercial queries and a second set of query communities from the set of queries that are commercial queries by the computing device, wherein each query community comprises a plurality of queries of the set of queries and each query in a query community is related to each other query in the query community, wherein a first query is related to a second query if the first query and the second query were provided by the same user with associated times that are within a time window more than a threshold number of times; determining a set of mappings of query communities from the first set of query communities to query communities from the second set of query communities by the computing device according to the users and times associated with the queries in the query communities; receiving a query from the first set of query communities at the computing device; and recommending one or more queries from the second set of query communities using the received query and the set of mappings. | 1. A method comprising: receiving a set of queries at a computing device, wherein each query is associated with a user who provided the query and each query has an associated time; dividing the received set of queries into a set of queries that are commercial queries and a set of queries that are non-commercial queries, by the computing device; generating a first set of query communities from the set of queries that are non-commercial queries and a second set of query communities from the set of queries that are commercial queries by the computing device, wherein each query community comprises a plurality of queries of the set of queries and each query in a query community is related to each other query in the query community, wherein a first query is related to a second query if the first query and the second query were provided by the same user with associated times that are within a time window more than a threshold number of times; determining a set of mappings of query communities from the first set of query communities to query communities from the second set of query communities by the computing device according to the users and times associated with the queries in the query communities; receiving a query from the first set of query communities at the computing device; and recommending one or more queries from the second set of query communities using the received query and the set of mappings. 6. The method of claim 1 , wherein determining the set of mappings of query communities from the first set of query communities to query communities from the second set of query communities comprises, for each unique pair of query communities comprising a query community from the first set of query communities and a query community from the second set of query communities: determining, from the set of queries, a first amount of users who provided a query from the query community from the first set of query communities followed by a query from the query community from the second set of query communities; determining, from the set of queries, a second amount of users who provided a query from the query community from the second set of query communities followed by a query from the query community from the first set of query communities; and if the first amount is greater than a threshold amount, and the first amount is greater than the second amount, adding a mapping from the query community from the first set of query communities to the query community from the second set of query communities to the set of mappings. | 0.529092 |
1. In a computing system, a method comprising: analyzing an electronic document to generate document identifying data; classifying the electronic document in one of one or more display categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document; displaying the classified electronic document in the one of the one or more display categories; receiving a user feedback regarding prioritization of the one of the electronic document; and updating the classification rule based on the feedback from the user, wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising: associating one or more concepts with the one of the one or more display categories, extracting the one or more concepts from the electronic document, and pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories. | 1. In a computing system, a method comprising: analyzing an electronic document to generate document identifying data; classifying the electronic document in one of one or more display categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document; displaying the classified electronic document in the one of the one or more display categories; receiving a user feedback regarding prioritization of the one of the electronic document; and updating the classification rule based on the feedback from the user, wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising: associating one or more concepts with the one of the one or more display categories, extracting the one or more concepts from the electronic document, and pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories. 19. The method of claim 1 , further comprising assigning workspace quota to each of the one or more categories. | 0.666887 |
1. A method, implemented at a computer system that includes one or more processors, of organizing data wherein the data has spatial significance, the method comprising: at a user interface, displaying to a user a representation of spatially structured data which includes one or more displayed objects; at the user interface, indicating that a particular object included in the spatially structured data has been selected, including displaying a plurality of directional user interface controls, including (i) a first user interface control above the particular object indicating that an up directional user input associated with the particular object can be received, (ii) a second user interface control below the particular object indicating that a down directional user input associated with the particular object can be received, (iii) a third user interface control to the left of the particular object indicating that a left directional user input associated with the particular object can be received, and (iv) a fourth user interface control to the right of the particular object indicating that a right directional user input associated with the particular object can be received; receiving a directional user input through one or more hardware input devices that is associated with the particular object, the directional user input being selected from among an up direction, a down direction, a left direction, and a right direction; based on receiving the directional user input, determining a domain type of the particular object; and based on the determined domain type of the particular object, interpreting the directional user input to add a new object to the spatially structured data in association with the particular object, wherein: if the domain type is a first domain type, the type of the new object is selected from within a first plurality of object types that are associated with the first domain type, and the type of the new object is further selected from among the first plurality of object types based on the particular direction of the directional user input, at least two different directions being associated with different object types in the first plurality of object types; and if the domain type is a second domain type, the type of the new object is selected from within a second plurality of object types that are different from the first plurality of object types that are associated with the second domain type, and the type of the new object is further selected from among the second plurality of object types based on the particular direction of the directional user input, at least two different directions being associated with different object types in the second plurality of object types. | 1. A method, implemented at a computer system that includes one or more processors, of organizing data wherein the data has spatial significance, the method comprising: at a user interface, displaying to a user a representation of spatially structured data which includes one or more displayed objects; at the user interface, indicating that a particular object included in the spatially structured data has been selected, including displaying a plurality of directional user interface controls, including (i) a first user interface control above the particular object indicating that an up directional user input associated with the particular object can be received, (ii) a second user interface control below the particular object indicating that a down directional user input associated with the particular object can be received, (iii) a third user interface control to the left of the particular object indicating that a left directional user input associated with the particular object can be received, and (iv) a fourth user interface control to the right of the particular object indicating that a right directional user input associated with the particular object can be received; receiving a directional user input through one or more hardware input devices that is associated with the particular object, the directional user input being selected from among an up direction, a down direction, a left direction, and a right direction; based on receiving the directional user input, determining a domain type of the particular object; and based on the determined domain type of the particular object, interpreting the directional user input to add a new object to the spatially structured data in association with the particular object, wherein: if the domain type is a first domain type, the type of the new object is selected from within a first plurality of object types that are associated with the first domain type, and the type of the new object is further selected from among the first plurality of object types based on the particular direction of the directional user input, at least two different directions being associated with different object types in the first plurality of object types; and if the domain type is a second domain type, the type of the new object is selected from within a second plurality of object types that are different from the first plurality of object types that are associated with the second domain type, and the type of the new object is further selected from among the second plurality of object types based on the particular direction of the directional user input, at least two different directions being associated with different object types in the second plurality of object types. 8. The method of claim 1 , further comprising changing a default type of data within the new object to a new type using user input generated with the assistance of a hinting module that causes a filtered list of types to be displayed in response to detecting a typed character and receiving a user selection of the new type from the filtered list of types. | 0.551258 |
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