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15. A voice guidance method comprising steps of: obtaining a plurality of voice data items for each of a plurality of voice guidance phrases, wherein each of the plurality of voice data items for a specific voice guidance phrase includes the specific voice guidance phrase at a different frequency and at least one of the plurality of voice data items is read from a memory and others of the plurality of voice data items are synthesized from the voice data item read from the memory; producing a first mixed voice data item by mixing at least two voice data items from a first voice guidance phrase selected from the plurality of voice guidance phrases; outputting and sounding the first guidance phrase using a first mixed voice for the first voice guidance phrase based on the first mixed voice data item; detecting a response voice uttered by a user responding to the outputted first guidance phrase using the first mixed voice; measuring a frequency with respect to the detected response voice; producing a second voice data item by mixing at least two voice data items for a second voice guidance phrase of the plurality of guidance phrases, different than the first voice guidance phrase and different from the detected response, the second mixed voice data item having the characteristic of the frequency that is measured with response to the response voice detected after the first mixed voice was sounded; and outputting and sounding only the second voice guidance phrase using a second mixed voice based on the second mixed voice data item in response to the response voice, the second voice guidance phrase approximating the frequency that is measured with respect to the response voice in order to assist the user to hear and understand the second voice guidance phrase.
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15. A voice guidance method comprising steps of: obtaining a plurality of voice data items for each of a plurality of voice guidance phrases, wherein each of the plurality of voice data items for a specific voice guidance phrase includes the specific voice guidance phrase at a different frequency and at least one of the plurality of voice data items is read from a memory and others of the plurality of voice data items are synthesized from the voice data item read from the memory; producing a first mixed voice data item by mixing at least two voice data items from a first voice guidance phrase selected from the plurality of voice guidance phrases; outputting and sounding the first guidance phrase using a first mixed voice for the first voice guidance phrase based on the first mixed voice data item; detecting a response voice uttered by a user responding to the outputted first guidance phrase using the first mixed voice; measuring a frequency with respect to the detected response voice; producing a second voice data item by mixing at least two voice data items for a second voice guidance phrase of the plurality of guidance phrases, different than the first voice guidance phrase and different from the detected response, the second mixed voice data item having the characteristic of the frequency that is measured with response to the response voice detected after the first mixed voice was sounded; and outputting and sounding only the second voice guidance phrase using a second mixed voice based on the second mixed voice data item in response to the response voice, the second voice guidance phrase approximating the frequency that is measured with respect to the response voice in order to assist the user to hear and understand the second voice guidance phrase. 16. The voice guidance method of claim 15 , further comprising: producing a second voice data item for the second voice guidance phrase, wherein the second voice data item has the frequency that is measured with respect to the response voice.
| 0.85 |
1. A method comprising: receiving a query that is configured by an issuer of the query to perform a local search, wherein the local search is performed over a first dataset and a second data set, wherein the first dataset comprises a first entity and the second dataset comprises a second entity, and wherein the query comprises a first token and a second token; parsing the query such that the first token of the query is mapped to the first entity in the first dataset and the second token of the query is mapped to the second entity in the second dataset; and returning search results based at least in part upon the parsing of the query, wherein the method is executed by a processor of a computing device.
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1. A method comprising: receiving a query that is configured by an issuer of the query to perform a local search, wherein the local search is performed over a first dataset and a second data set, wherein the first dataset comprises a first entity and the second dataset comprises a second entity, and wherein the query comprises a first token and a second token; parsing the query such that the first token of the query is mapped to the first entity in the first dataset and the second token of the query is mapped to the second entity in the second dataset; and returning search results based at least in part upon the parsing of the query, wherein the method is executed by a processor of a computing device. 2. The method of claim 1 , wherein the first dataset is a custom dataset, wherein the custom dataset comprises a plurality of entities generated by an end user, and wherein the plurality of entities comprise attributes that describe the plurality of entities and shapes pertaining to the plurality of entities.
| 0.617719 |
13. The information handling system of claim 12 , comprising determining whether the user has permission to access the retrieved data.
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13. The information handling system of claim 12 , comprising determining whether the user has permission to access the retrieved data. 14. The information handling system of claim 13 , wherein the receiving comprises receiving from the user at least one of: a set of one or more search parameters; and a text-based query.
| 0.950935 |
3. The system of claim 1 , wherein a location of at least one of the source portion within the source document and the target portion within the target document is determined by the computer system executing the metric module.
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3. The system of claim 1 , wherein a location of at least one of the source portion within the source document and the target portion within the target document is determined by the computer system executing the metric module. 6. The system of claim 3 , wherein: the memory further stores a plurality of dictionary entries matching words in the first language to words in the second language; and the computer system executes the metric module to select the location according to changes in a concentration of words contained within the plurality of dictionary entries and within one of the source document and target document.
| 0.866031 |
13. A non-transitory computer readable storage medium storing one or more programs configured for execution by a server system, the one or more programs comprising instructions for: receiving a search hints request, the search hints request including at least a character string including at least one character; determining a set of search hints based on the character string, each search hint in the set of search hints being associated with one or more digital media assets available from the online media store and each digital media asset having an associated media type; for each respective search hint in the determined set of search hints: determining whether the client device supports the media type of at least one of the one or more digital media assets associated with the respective search hint in the determined set of search hints; in accordance with a determination that the client device does not support the media type associated with any of the one or more digital media assets associated with the respective search hint, removing the respective search hint from the determined set of search hints; obtaining a media popularity indication for each of a plurality of the search hints in the set of search hints; prioritizing each of the plurality of the search hints in the set of search hints based on the media popularity indication, the media popularity indication based on purchase data for the digital media assets; and selecting a subset of the search hints having the highest media popularity indications; and sending the subset of the search hints.
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13. A non-transitory computer readable storage medium storing one or more programs configured for execution by a server system, the one or more programs comprising instructions for: receiving a search hints request, the search hints request including at least a character string including at least one character; determining a set of search hints based on the character string, each search hint in the set of search hints being associated with one or more digital media assets available from the online media store and each digital media asset having an associated media type; for each respective search hint in the determined set of search hints: determining whether the client device supports the media type of at least one of the one or more digital media assets associated with the respective search hint in the determined set of search hints; in accordance with a determination that the client device does not support the media type associated with any of the one or more digital media assets associated with the respective search hint, removing the respective search hint from the determined set of search hints; obtaining a media popularity indication for each of a plurality of the search hints in the set of search hints; prioritizing each of the plurality of the search hints in the set of search hints based on the media popularity indication, the media popularity indication based on purchase data for the digital media assets; and selecting a subset of the search hints having the highest media popularity indications; and sending the subset of the search hints. 14. The non-transitory computer readable storage medium of claim 13 , wherein the digital media information pertains to digital media assets available in an online media store, and wherein the media popularity indication for a particular one of the search hints pertains to popularity of the corresponding digital media asset with respect to the online media store.
| 0.547423 |
1. A method comprising: receiving a first software release comprising a set of software packages; parsing the first software release to identify first modeling information comprising package information, package dependency information, and function dependency information associated with each software package in the set of software packages, wherein the function dependency information identifies a relationship between a plurality of functions performed by the set of software packages in the first software release; generating, by a processing device, a first graph model representing the first modeling information, wherein the first graph model comprises a package node for each software package in the set of software packages and a function node for each function in the set of software packages of the first software release; generating, by the processing device, a second graph model representing second modeling information associated with a second software release comprising a second set of software packages, wherein the second graph model comprises a package node for each software package in the second set of software packages and a function node for each function in the second set of software packages; storing the first graph model associated with the first software release and the second graph model associated with the second software release; and comparing the first graph model and the second graph model to identify a change producing an incompatibility in an integration of the second software release in view of a policy.
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1. A method comprising: receiving a first software release comprising a set of software packages; parsing the first software release to identify first modeling information comprising package information, package dependency information, and function dependency information associated with each software package in the set of software packages, wherein the function dependency information identifies a relationship between a plurality of functions performed by the set of software packages in the first software release; generating, by a processing device, a first graph model representing the first modeling information, wherein the first graph model comprises a package node for each software package in the set of software packages and a function node for each function in the set of software packages of the first software release; generating, by the processing device, a second graph model representing second modeling information associated with a second software release comprising a second set of software packages, wherein the second graph model comprises a package node for each software package in the second set of software packages and a function node for each function in the second set of software packages; storing the first graph model associated with the first software release and the second graph model associated with the second software release; and comparing the first graph model and the second graph model to identify a change producing an incompatibility in an integration of the second software release in view of a policy. 5. The method of claim 1 , further comprising searching at least one of the first graph model or the second graph model using a depth-first search.
| 0.616833 |
25. A system comprising: a processing device comprising computer memory storing a script containing simple object access protocol (SOAP) commands; and a device associated with an apparatus, the device for executing instructions stored in computer memory to perform operations comprising: receiving the script from the processing device, the script defining one or more variables that are used in execution of the script, at least some of the SOAP commands in the script including corresponding arguments; interpreting the script to execute functions contained in the script; parsing the SOAP commands from the script during execution of the functions; executing the SOAP commands; wherein the apparatus is configured by execution of the SOAP commands and the functions; and wherein the execution of the SOAP commands and the functions comprises passing a variable in the script as an argument to a first SOAP command, returning an output of the first SOAP command to the script, and executing a second SOAP command based on the output.
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25. A system comprising: a processing device comprising computer memory storing a script containing simple object access protocol (SOAP) commands; and a device associated with an apparatus, the device for executing instructions stored in computer memory to perform operations comprising: receiving the script from the processing device, the script defining one or more variables that are used in execution of the script, at least some of the SOAP commands in the script including corresponding arguments; interpreting the script to execute functions contained in the script; parsing the SOAP commands from the script during execution of the functions; executing the SOAP commands; wherein the apparatus is configured by execution of the SOAP commands and the functions; and wherein the execution of the SOAP commands and the functions comprises passing a variable in the script as an argument to a first SOAP command, returning an output of the first SOAP command to the script, and executing a second SOAP command based on the output. 30. The system of claim 25 , wherein the functions comprise a conditional statement.
| 0.587768 |
11. A computer program product for generating a summary of an online communication session, the computer program product comprising: one or more computer readable storage medium(s) and program instructions stored on the one or more computer readable storage medium(s), the program instructions comprising: program instructions to receive a particular topic and summary information for each of one or more episodes of a current online communication session, and information regarding topics of interests for each member of a group of users, wherein content of the current online communication session is generated by members of the group of users; program instructions to receive a pictorial representation of the particular topic for the one or more episodes of the current online communication session, wherein determining the pictorial representation of each episode of the one or more episodes of the current online communication session is based on the particular topic of each episode; and program instructions to generate a summary of the current online communication session that is personalized for members of the group of users, wherein the program instructions to generate the summary that is personalized includes: program instructions to determine a level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session, for a member of the group of users, based on one or a combination of: an amount of participation and contribution by the member of the group of users during the current online communication session, an amount of participation and contribution by the member of the group of users during previous online communication sessions that include the first topic, and interest preferences input by the member of the group of users; program instructions to list the summary and pictorial representation of the one or more episodes of the current online communication session in an order that corresponds to the level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session held by the member of the group of users; and responsive to determining the level of interest held by the member of the group of users, for the first topic of the first episode of the one or more episodes, to be greater than the level of interest held by the member of the group of users for the second topic of the second episode of the one or more episodes, program instructions to provide a complete summary of the first topic of the first episode positioned before a condensed summary of the second topic of the second episode.
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11. A computer program product for generating a summary of an online communication session, the computer program product comprising: one or more computer readable storage medium(s) and program instructions stored on the one or more computer readable storage medium(s), the program instructions comprising: program instructions to receive a particular topic and summary information for each of one or more episodes of a current online communication session, and information regarding topics of interests for each member of a group of users, wherein content of the current online communication session is generated by members of the group of users; program instructions to receive a pictorial representation of the particular topic for the one or more episodes of the current online communication session, wherein determining the pictorial representation of each episode of the one or more episodes of the current online communication session is based on the particular topic of each episode; and program instructions to generate a summary of the current online communication session that is personalized for members of the group of users, wherein the program instructions to generate the summary that is personalized includes: program instructions to determine a level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session, for a member of the group of users, based on one or a combination of: an amount of participation and contribution by the member of the group of users during the current online communication session, an amount of participation and contribution by the member of the group of users during previous online communication sessions that include the first topic, and interest preferences input by the member of the group of users; program instructions to list the summary and pictorial representation of the one or more episodes of the current online communication session in an order that corresponds to the level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session held by the member of the group of users; and responsive to determining the level of interest held by the member of the group of users, for the first topic of the first episode of the one or more episodes, to be greater than the level of interest held by the member of the group of users for the second topic of the second episode of the one or more episodes, program instructions to provide a complete summary of the first topic of the first episode positioned before a condensed summary of the second topic of the second episode. 15. The computer program product of claim 11 , wherein a pictorial representation of the particular topic and the summary information of an episode of the one or more episodes of the online communication session is obtained by a graphical engine, based on the graphical engine receiving a topic and summary information from a cognitive engine that analyzes the content of the current online communication session.
| 0.66343 |
15. An image forming apparatus configured to function as a groupware terminal and connectable to a groupware server of a groupware, said groupware server comprising plural document databases configured to store document data, and an attribute database configured to store multiple lists of different plural kinds of attribute information, each kind of the attribute information being setting items unique to each document database, the setting items being required to be set when storing the document data in the document database, said image forming apparatus comprising: a scan part configured to scan a paper document and to obtain document data; a first display screen that displays a selection screen enabling selection of one of the plural document databases; an acquiring part configured to acquire one of the lists of attribute information from the attribute database corresponding to the selected document database; a second display screen that displays an input screen to set the unique predetermined setting items included in the acquired attribute information; a setting part configured to add the attribute information including the set setting items to the document data obtained by the scan part; and a sending part configured to send to the groupware server the document data having the set attribute information, so that said groupware server stores the document data having the added attribute information including the set setting items, in the document database, wherein: the document data having the added attribute information including the set setting item sent from the image forming apparatus is stored in the document database of the groupware server.
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15. An image forming apparatus configured to function as a groupware terminal and connectable to a groupware server of a groupware, said groupware server comprising plural document databases configured to store document data, and an attribute database configured to store multiple lists of different plural kinds of attribute information, each kind of the attribute information being setting items unique to each document database, the setting items being required to be set when storing the document data in the document database, said image forming apparatus comprising: a scan part configured to scan a paper document and to obtain document data; a first display screen that displays a selection screen enabling selection of one of the plural document databases; an acquiring part configured to acquire one of the lists of attribute information from the attribute database corresponding to the selected document database; a second display screen that displays an input screen to set the unique predetermined setting items included in the acquired attribute information; a setting part configured to add the attribute information including the set setting items to the document data obtained by the scan part; and a sending part configured to send to the groupware server the document data having the set attribute information, so that said groupware server stores the document data having the added attribute information including the set setting items, in the document database, wherein: the document data having the added attribute information including the set setting item sent from the image forming apparatus is stored in the document database of the groupware server. 22. The image forming apparatus as claimed in claim 15 , wherein: said groupware server comprises a user information database configured to store user information that is used to log-in to the groupware, said image forming apparatus further comprises a storage medium read part configured to read information from a storage medium recorded with the user information, and said groupware server authenticates the user information when user information matching the user information read by the storage medium read part exists in the user information database.
| 0.526264 |
10. The method of claim 1 , further comprising presenting one or more media objects in a collection.
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10. The method of claim 1 , further comprising presenting one or more media objects in a collection. 11. The method of claim 10 , wherein the presenting of the one or more media objects comprises presenting a hierarchical tree representing an ordering of the media objects in the collection.
| 0.941483 |
13. A non-transitory computer readable medium having computer executable program code embodied thereon, the computer executable program code configured to cause a computing device to perform the operations of: partitioning a digital real estate document into a set of token patterns; normalizing the set of token patterns to obtain a normalized set of token patterns; applying a first filter to the normalized set of token patterns to obtain a first indicator of whether the digital real estate document is a member of a first document classification and a first confidence score for the first indicator; applying a second filter to the normalized set of token patterns to obtain a second indicator of whether the digital real estate document is a member of a second document classification and a second confidence score for the second indicator; and determining a document classification of the digital real estate document from a set of indicators associated with the digital real estate document and set of confidence scores associated with the set of indicators, wherein the set of indicators includes the first and second indicators and the set of confidence scores includes the first and second confidence scores; wherein the first filter comprises a set of indicative token patterns and a set of non-indicative token patterns, wherein the indicative token patterns are those associated with the first document classification, wherein the non-indicative token patterns are those not associated with the first document classification; and wherein applying the first filter to the normalized set of token patterns to obtain the first indicator and the first confidence score comprises: performing a determination of whether the digital real estate document is a member of the first document classification based on the set of indicative token patterns, the set of non-indicative token patterns, and the normalized set of token patterns; setting the first indicator according to the determination; and calculating the first confidence score based on a level of confidence in the determination.
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13. A non-transitory computer readable medium having computer executable program code embodied thereon, the computer executable program code configured to cause a computing device to perform the operations of: partitioning a digital real estate document into a set of token patterns; normalizing the set of token patterns to obtain a normalized set of token patterns; applying a first filter to the normalized set of token patterns to obtain a first indicator of whether the digital real estate document is a member of a first document classification and a first confidence score for the first indicator; applying a second filter to the normalized set of token patterns to obtain a second indicator of whether the digital real estate document is a member of a second document classification and a second confidence score for the second indicator; and determining a document classification of the digital real estate document from a set of indicators associated with the digital real estate document and set of confidence scores associated with the set of indicators, wherein the set of indicators includes the first and second indicators and the set of confidence scores includes the first and second confidence scores; wherein the first filter comprises a set of indicative token patterns and a set of non-indicative token patterns, wherein the indicative token patterns are those associated with the first document classification, wherein the non-indicative token patterns are those not associated with the first document classification; and wherein applying the first filter to the normalized set of token patterns to obtain the first indicator and the first confidence score comprises: performing a determination of whether the digital real estate document is a member of the first document classification based on the set of indicative token patterns, the set of non-indicative token patterns, and the normalized set of token patterns; setting the first indicator according to the determination; and calculating the first confidence score based on a level of confidence in the determination. 21. The computer readable medium of claim 13 , the program instructions further configured to cause a computer system to perform the operations of training a filter from a plurality of document classification filters.
| 0.578514 |
7. A computer-implemented method, comprising: under control of one or more computer systems configured with executable instructions, analyzing keywords of previous searches to detect fixed phrases suitable for inclusion in a search index, each fixed phrase including a first keyword and a second keyword; determining a first count of the first keyword, a second count of the second keyword, and a mutual count of the first keyword and the second keyword appearing simultaneously in the previous searches; weighting each individual count of the first count, the second count, and the mutual count based at least in part on age of a respective individual count with respect to the previous searches; determining a pointwise mutual information score using the weighted first count of the first keyword, the weighted second count of the second keyword, and the weighted mutual count of the first keyword and the second keyword; associating a respective suitable fixed phrase with the search index based at least in part on the determined pointwise mutual score being greater than a threshold score; in response to receiving a search request, determine a relevance score for each of at least a portion of the keywords, including the respective suitable fixed phrase, with respect to a collection of content; provide at least one search result for presentation, the at least one search result at least referencing content selected from the collection of content based at least in part on the at least one relevance score; detect interaction with a search result of the provided at least one result from a user; and update the keywords associated with the search result.
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7. A computer-implemented method, comprising: under control of one or more computer systems configured with executable instructions, analyzing keywords of previous searches to detect fixed phrases suitable for inclusion in a search index, each fixed phrase including a first keyword and a second keyword; determining a first count of the first keyword, a second count of the second keyword, and a mutual count of the first keyword and the second keyword appearing simultaneously in the previous searches; weighting each individual count of the first count, the second count, and the mutual count based at least in part on age of a respective individual count with respect to the previous searches; determining a pointwise mutual information score using the weighted first count of the first keyword, the weighted second count of the second keyword, and the weighted mutual count of the first keyword and the second keyword; associating a respective suitable fixed phrase with the search index based at least in part on the determined pointwise mutual score being greater than a threshold score; in response to receiving a search request, determine a relevance score for each of at least a portion of the keywords, including the respective suitable fixed phrase, with respect to a collection of content; provide at least one search result for presentation, the at least one search result at least referencing content selected from the collection of content based at least in part on the at least one relevance score; detect interaction with a search result of the provided at least one result from a user; and update the keywords associated with the search result. 8. A computer-implemented method according to claim 7 , further comprising: associating the keywords of the previous searches in accordance with a latent Dirichlet allocation.
| 0.606003 |
3. An active learning system as set forth in claim 2 , further comprising: a fixed-basis function decomposition module using Haar wavelets to extract a relevant feature set from the potential object candidate; a static classifier for initial or temporary classification of the potential object candidate, thereby generating a classification category selected from a group consisting of a positive identification, a negative identification, a false positive identification, and a false negative identification, and where upon classification, the static classifier communicates the classification to the incremental learning module.
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3. An active learning system as set forth in claim 2 , further comprising: a fixed-basis function decomposition module using Haar wavelets to extract a relevant feature set from the potential object candidate; a static classifier for initial or temporary classification of the potential object candidate, thereby generating a classification category selected from a group consisting of a positive identification, a negative identification, a false positive identification, and a false negative identification, and where upon classification, the static classifier communicates the classification to the incremental learning module. 4. An active learning system as set forth in claim 3 , wherein the feature vector is based on local intensity variations present in an image region around the point as seen from a given view, such that a number of points that form the object model is selected based on local photometric energy at each point, with the point being retained as an actual object point if its photometric energy is greater than a threshold where the threshold is computed based on the photometric energy associated with points within the image region.
| 0.78579 |
8. A non-transitory, computer-readable medium encoded with instructions that, when executed by at least one processor, cause the at least one processor to perform a method for providing a graphical user interface that enables the creation of a new electronic medical document using at least a portion of one or more existing electronic documents, the new electronic medical document including material describing an encounter between a patient and a medical service provider, the method comprising: adding to the new electronic medical document text resulting from performing speech-to-text processing on input speech of the medical service provider describing the encounter between the patient and the medical service provider; receiving a query identifying one or more search parameters via the graphical user interface; and retrieving the one or more existing electronic medical documents in response to determining that the one or more existing electronic medical documents satisfy the one or more search parameters identified in the query; display, on a computer display, a list of medical document sections and, associated with each one section of the medical document sections of the list, a title of the one section and one or mor excerpts comprising text that was included in the one section in at least one of the one or more existing electronic medical documents, wherein the medical document sections included in the list include a first section, wherein the one or more excerpt included in the first section include a first excerpt and a second excerpt that were included in the first section in a first existing electronic medical document of the one or more existing electronic medical documents, and wherein the text of each of the first and second excerpts is less than all text included in the first section in the first existing electronic medical document; for each of the displayed excerpts, displaying at least one corresponding indicator on the computer display, each displayed indicator including information indicating whether the indicator is in a selected state or an unselected state; enabling a user to operate the graphical user interface so as to selectively alter the states of the displayed indicators; and for each one section of the list of medical document sections and for each one of at least one displayed excerpt, of the one section, for which the user has put a corresponding indicator in the selected state, copying text of the one displayed excerpt into a medical document section of the new electronic medical document corresponding to the one section.
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8. A non-transitory, computer-readable medium encoded with instructions that, when executed by at least one processor, cause the at least one processor to perform a method for providing a graphical user interface that enables the creation of a new electronic medical document using at least a portion of one or more existing electronic documents, the new electronic medical document including material describing an encounter between a patient and a medical service provider, the method comprising: adding to the new electronic medical document text resulting from performing speech-to-text processing on input speech of the medical service provider describing the encounter between the patient and the medical service provider; receiving a query identifying one or more search parameters via the graphical user interface; and retrieving the one or more existing electronic medical documents in response to determining that the one or more existing electronic medical documents satisfy the one or more search parameters identified in the query; display, on a computer display, a list of medical document sections and, associated with each one section of the medical document sections of the list, a title of the one section and one or mor excerpts comprising text that was included in the one section in at least one of the one or more existing electronic medical documents, wherein the medical document sections included in the list include a first section, wherein the one or more excerpt included in the first section include a first excerpt and a second excerpt that were included in the first section in a first existing electronic medical document of the one or more existing electronic medical documents, and wherein the text of each of the first and second excerpts is less than all text included in the first section in the first existing electronic medical document; for each of the displayed excerpts, displaying at least one corresponding indicator on the computer display, each displayed indicator including information indicating whether the indicator is in a selected state or an unselected state; enabling a user to operate the graphical user interface so as to selectively alter the states of the displayed indicators; and for each one section of the list of medical document sections and for each one of at least one displayed excerpt, of the one section, for which the user has put a corresponding indicator in the selected state, copying text of the one displayed excerpt into a medical document section of the new electronic medical document corresponding to the one section. 9. The computer-readable medium of claim 8 , wherein the method further comprises: in response to receiving the input from the user indicating that the user has finished altering the states of the displayed indicators, for each displayed excerpt for which a corresponding indicator is in the unselected state, refraining from copying into the new electronic medical document a portion of one or more of the existing electronic medical document corresponding to that displayed excerpt.
| 0.50596 |
1. A method of generating procedural language code for extracting data from an operational system, the method comprising: accepting a declarative specification; and generating procedural language code from the declarative specification to execute a data extraction, transformation and loading process defined by the declarative specification.
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1. A method of generating procedural language code for extracting data from an operational system, the method comprising: accepting a declarative specification; and generating procedural language code from the declarative specification to execute a data extraction, transformation and loading process defined by the declarative specification. 8. The method of claim 1 , wherein the generating procedural language code forms part of generating ABAP code with parameter expressions to be evaluated at run time.
| 0.707265 |
1. A search system, including: query means in a search computer for processing a query to assign respective weights to terms of said query based on the grammatical structure of the query and the meaning of the terms of the query and to generate a query vector including said weights; index means in the search computer responsive to said query vector to output indices to data in response to said query, said index means being a self generating neural network having nodes of weight vectors representing categories and terms of said data, said nodes further including pointers to other nodes, and leaf nodes of said network each including an index to said data; feature extraction means in the search computer for extracting said indices and respective terms of said data as term weight pairs, the weights of the pairs being based on the importance and uniqueness of component ngrams of the terms of an indexed document and the terms being extracted on the basis of the distribution of ngrams in a document space of indexed documents of said data; and wherein said neural network is generated on the basis of training examples including said term weight pairs, and the format of said query vectors and said weight vectors of said network is generated on the basis of said training examples.
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1. A search system, including: query means in a search computer for processing a query to assign respective weights to terms of said query based on the grammatical structure of the query and the meaning of the terms of the query and to generate a query vector including said weights; index means in the search computer responsive to said query vector to output indices to data in response to said query, said index means being a self generating neural network having nodes of weight vectors representing categories and terms of said data, said nodes further including pointers to other nodes, and leaf nodes of said network each including an index to said data; feature extraction means in the search computer for extracting said indices and respective terms of said data as term weight pairs, the weights of the pairs being based on the importance and uniqueness of component ngrams of the terms of an indexed document and the terms being extracted on the basis of the distribution of ngrams in a document space of indexed documents of said data; and wherein said neural network is generated on the basis of training examples including said term weight pairs, and the format of said query vectors and said weight vectors of said network is generated on the basis of said training examples. 3. A search system as claimed in claim 1 , wherein said query means analyses said terms using a dictionary and thesaurus of terms of said data.
| 0.591456 |
1. A method for web documents clustering, comprising: inputting a plurality of web documents; collecting link information and directory structure information of the inputted web documents; extracting, by a processor, according to the collected link information and directory structure information, a hierarchical structure for the plurality of web documents; after extracting the hierarchical structure, revising the extracted hierarchical structure by analyzing the link information in the inputted web documents; and generating and outputting, based on the extracted hierarchical structure, plurality of clusters of the plurality of web documents, wherein the directory structure information is extracted by comparing directory paths of the web documents, wherein the directory paths include information about a location in a web server where each of the plurality of web documents are stored, and the extracted hierarchical structure corresponds to ancestor-descendent relationship structure of the plurality of web documents, wherein the plurality of web documents are grouped into the plurality of clusters according to the extracted hierarchical structure such that a first web document of the plurality of web documents and descendent web documents of the first web documents are grouped as a first cluster of the plurality of clusters, and a second web document of the plurality of web documents and descendent web documents of the second web documents are grouped as a second cluster of the plurality of clusters, and wherein the first and the second clusters have an ancestor-descendent relationship between each other corresponding to the extracted hierarchal structure.
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1. A method for web documents clustering, comprising: inputting a plurality of web documents; collecting link information and directory structure information of the inputted web documents; extracting, by a processor, according to the collected link information and directory structure information, a hierarchical structure for the plurality of web documents; after extracting the hierarchical structure, revising the extracted hierarchical structure by analyzing the link information in the inputted web documents; and generating and outputting, based on the extracted hierarchical structure, plurality of clusters of the plurality of web documents, wherein the directory structure information is extracted by comparing directory paths of the web documents, wherein the directory paths include information about a location in a web server where each of the plurality of web documents are stored, and the extracted hierarchical structure corresponds to ancestor-descendent relationship structure of the plurality of web documents, wherein the plurality of web documents are grouped into the plurality of clusters according to the extracted hierarchical structure such that a first web document of the plurality of web documents and descendent web documents of the first web documents are grouped as a first cluster of the plurality of clusters, and a second web document of the plurality of web documents and descendent web documents of the second web documents are grouped as a second cluster of the plurality of clusters, and wherein the first and the second clusters have an ancestor-descendent relationship between each other corresponding to the extracted hierarchal structure. 9. The method according to claim 1 , wherein the directory structure information is obtained from an Uniform Resource Locator (URL) of each of the plurality of web documents.
| 0.624607 |
1. A method for dynamically accessing secure content, comprising: crawling a group of documents in a secure data source; indexing, using a processor, each crawled document and storing document metadata for said each crawled document including a generic link for said each crawled document; receiving a query from an authenticated user of an enterprise, wherein an indexed document satisfies the query relating to the previously indexed document, and the authenticated user has user security attribute values stored in a computer system; sending a callback to the secure data source from which the indexed document was crawled, the callback including the metadata for the previously indexed document and the user security attribute values; building, in response to the callback, an updated document metadata for the indexed document, wherein the updated document metadata for the indexed document is different from the stored document metadata for the indexed document, modifying the metadata for the indexed document based on the updated document metadata, and building an updated link that is updated based on the existing generic link and the user security attribute values, the updated link pointing to results that are appropriate for the user at substantially the time of the query, wherein building the updated link includes receiving an updated link from a secure application, wherein the updated link includes encoded information for the secure data source; and stamping each of the results in an index with the user security attribute values such that the stamped results are only available for search in the index by the user associated with the user security attribute values.
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1. A method for dynamically accessing secure content, comprising: crawling a group of documents in a secure data source; indexing, using a processor, each crawled document and storing document metadata for said each crawled document including a generic link for said each crawled document; receiving a query from an authenticated user of an enterprise, wherein an indexed document satisfies the query relating to the previously indexed document, and the authenticated user has user security attribute values stored in a computer system; sending a callback to the secure data source from which the indexed document was crawled, the callback including the metadata for the previously indexed document and the user security attribute values; building, in response to the callback, an updated document metadata for the indexed document, wherein the updated document metadata for the indexed document is different from the stored document metadata for the indexed document, modifying the metadata for the indexed document based on the updated document metadata, and building an updated link that is updated based on the existing generic link and the user security attribute values, the updated link pointing to results that are appropriate for the user at substantially the time of the query, wherein building the updated link includes receiving an updated link from a secure application, wherein the updated link includes encoded information for the secure data source; and stamping each of the results in an index with the user security attribute values such that the stamped results are only available for search in the index by the user associated with the user security attribute values. 3. The method according to claim 1 , wherein: the updated link is an active and valid link for only the current user.
| 0.898276 |
8. A method in a computing system for generating an extensible stylesheet, the method comprising: receiving a target file in a first markup language, the target file including a plurality of dynamic objects, at least two of the dynamic objects related to at least one element in a source file in a second markup language; providing a structure tree corresponding to one or more source files including the source file, each node of the structure tree corresponding to one of the dynamic objects in the target file; creating a data structure by associating respectively the dynamic objects with the source file by a plurality of meta-tags via the structure tree; identifying corresponding ones of the meta-tags for the at least two of the dynamic objects related to the same element in the source file, wherein the corresponding ones of the meta-tags is labeled by a different identifier; and generating the extensible stylesheet in reference to the target file and the data structure, wherein the stylesheet, when applied to the target file, controls visual aspects of how the target file is displayed, wherein said associating respectively the dynamic objects with the source file by a plurality of meta-tags via the structure tree comprises: copying each of the dynamic objects into one of the nodes in the structure tree or creating or updating an identifier to link each of the dynamic objects with one of the nodes in the structure tree; and traversing the structure tree to obtain related information for one or more of the meta-tags, wherein the related information includes associations between the one or more of the dynamic objects and at least one element in the at least one source file.
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8. A method in a computing system for generating an extensible stylesheet, the method comprising: receiving a target file in a first markup language, the target file including a plurality of dynamic objects, at least two of the dynamic objects related to at least one element in a source file in a second markup language; providing a structure tree corresponding to one or more source files including the source file, each node of the structure tree corresponding to one of the dynamic objects in the target file; creating a data structure by associating respectively the dynamic objects with the source file by a plurality of meta-tags via the structure tree; identifying corresponding ones of the meta-tags for the at least two of the dynamic objects related to the same element in the source file, wherein the corresponding ones of the meta-tags is labeled by a different identifier; and generating the extensible stylesheet in reference to the target file and the data structure, wherein the stylesheet, when applied to the target file, controls visual aspects of how the target file is displayed, wherein said associating respectively the dynamic objects with the source file by a plurality of meta-tags via the structure tree comprises: copying each of the dynamic objects into one of the nodes in the structure tree or creating or updating an identifier to link each of the dynamic objects with one of the nodes in the structure tree; and traversing the structure tree to obtain related information for one or more of the meta-tags, wherein the related information includes associations between the one or more of the dynamic objects and at least one element in the at least one source file. 13. The method of claim 8 , wherein the different identifier is selected from a group consisting of a numeral, a character, a text and an alphanumeric symbol.
| 0.722114 |
1. A method of automating the application of constraints to one or more design objects in a circuit design created using an electronic design automation tool, wherein the one or more design objects represent physical circuit objects in a circuit being designed using the electronic design automation tool, comprising: providing a template type in a computer system; wherein the template type includes a selectable template type identifier in produced in a computer user interface display of the computer system to identify the template type, wherein template type includes template instance generation code stored in a computer readable storage device of the computer system to run a template instance generation process, wherein template type further includes template instance validation code stored in the computer readable storage to run a template instance validation process; receiving by the computer system, a user selection of the template type identifier; in response to the received user selection of the template type identifier, invoking the template instance generation code to run the template instance generation process on the computer system, to produce a template instance, wherein the produced template instance identifies a constraint set that includes multiple constraints and that identifies associations between the multiple constraints in the constraint set and the one or more design objects to store the produced template instance in the memory device, and to create an association in the memory device between the produced template instance and the template type.
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1. A method of automating the application of constraints to one or more design objects in a circuit design created using an electronic design automation tool, wherein the one or more design objects represent physical circuit objects in a circuit being designed using the electronic design automation tool, comprising: providing a template type in a computer system; wherein the template type includes a selectable template type identifier in produced in a computer user interface display of the computer system to identify the template type, wherein template type includes template instance generation code stored in a computer readable storage device of the computer system to run a template instance generation process, wherein template type further includes template instance validation code stored in the computer readable storage to run a template instance validation process; receiving by the computer system, a user selection of the template type identifier; in response to the received user selection of the template type identifier, invoking the template instance generation code to run the template instance generation process on the computer system, to produce a template instance, wherein the produced template instance identifies a constraint set that includes multiple constraints and that identifies associations between the multiple constraints in the constraint set and the one or more design objects to store the produced template instance in the memory device, and to create an association in the memory device between the produced template instance and the template type. 15. The method of claim 1 further including: in response to a change in a constraint in the constraint set identified by the template instance or to a change in an object associated by the template instance with a constraint of the identified constraint set, using the created association to invoke the template instance validation code to run the template instance validation process to determine whether one or more are constraints invalid.
| 0.5 |
4. The method of claim 1 , further comprising: setting a restriction flag in said revised document to activate edit restriction.
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4. The method of claim 1 , further comprising: setting a restriction flag in said revised document to activate edit restriction. 5. The method of claim 4 wherein said restricting step is activated in response to reading said set restriction flag.
| 0.944497 |
30. A method for signifying a large number of information objects comprising the steps: obtaining a first plurality of information objects; developing a set of deliberately ambiguated signifier prompts, wherein the set of deliberately ambiguated signifier prompts comprise at least one of one-dimensional figures and multi-dimensional figures, each of the figures having a plurality of labeled points specifying attributes; providing the set of deliberately ambiguated signifier prompts to at least one indexer, wherein the at least one indexer signifies the first plurality of information objects by indicating a position on each of the set of deliberately ambiguated signifier prompts to represent the information object; storing on a computer system the responses of the indexer with the first plurality of information objects; training an automated classifier using the stored responses of the indexer; obtaining a second plurality of information objects; and using the trained automated classifier to signify the second plurality of information objects.
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30. A method for signifying a large number of information objects comprising the steps: obtaining a first plurality of information objects; developing a set of deliberately ambiguated signifier prompts, wherein the set of deliberately ambiguated signifier prompts comprise at least one of one-dimensional figures and multi-dimensional figures, each of the figures having a plurality of labeled points specifying attributes; providing the set of deliberately ambiguated signifier prompts to at least one indexer, wherein the at least one indexer signifies the first plurality of information objects by indicating a position on each of the set of deliberately ambiguated signifier prompts to represent the information object; storing on a computer system the responses of the indexer with the first plurality of information objects; training an automated classifier using the stored responses of the indexer; obtaining a second plurality of information objects; and using the trained automated classifier to signify the second plurality of information objects. 32. The method for signifying a large number of information objects of claim 30 , wherein the second plurality of information objects comprises information objects obtained from a search using a commercial internet search engine.
| 0.589087 |
8. The method of claim 1 wherein associating the one or more matching tags with the respective source file further comprises associating a respective hierarchical level of each tag of the one or more matching tags, wherein the respective hierarchical level relates to a hierarchical level within the dictionary.
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8. The method of claim 1 wherein associating the one or more matching tags with the respective source file further comprises associating a respective hierarchical level of each tag of the one or more matching tags, wherein the respective hierarchical level relates to a hierarchical level within the dictionary. 9. The method of claim 8 wherein generating the first virtual relational network comprises generating a hierarchical network corresponding to a hierarchy of matching dictionary tags.
| 0.948535 |
8. The computer-readable hardware medium of claim 4 , wherein the instructions to estimate acoustic model parameters with confidence-based discriminative training include instructions that when executed cause the computing system to: estimate model parameters by separating statistics for a numerator lattice corresponding to the original transcription from the statistics of a decoding lattice generated by decoding the audio data with an existing acoustic model to generate the decoding lattice.
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8. The computer-readable hardware medium of claim 4 , wherein the instructions to estimate acoustic model parameters with confidence-based discriminative training include instructions that when executed cause the computing system to: estimate model parameters by separating statistics for a numerator lattice corresponding to the original transcription from the statistics of a decoding lattice generated by decoding the audio data with an existing acoustic model to generate the decoding lattice. 9. The computer-readable hardware medium of claim 8 , wherein the instructions to estimate model parameters include instructions that when executed cause the computing system to: calculate the update formulas for mean (μ jk ) and variance (σ jk 2 ) for a jth state and a kth mixture model as: μ jk = θ jk num ( O ) - θ jk den ( O ) + D jk μ jk ′ γ jk num - γ jk den + D jk σ jk 2 = θ jk num ( O 2 ) - θ jk den ( O 2 ) + D jk ( σ jk ′2 + μ jk ′2 ) γ jk num - γ jk den + D jk - μ jk 2 where γ jk den = ∑ q = 1 Q ∑ t = e q e q γ qjk den ( t ) γ q den θ jk den ( O ) = ∑ q = 1 Q ∑ t = e q e q γ qjk deb ( t ) γ q den O ( t ) θ jk den ( O 2 ) = ∑ q = 1 Q ∑ t = e q e q γ qjk den ( t ) γ q den O ( t ) 2 where γ q den is the qth word/phone arc posterior in the decoding lattice, and γ qjk den (t) is the posterior on the qth word/phone arc.
| 0.697135 |
8. The method of claim 7 , wherein: the modifying the displaying of the three-dimensional model in the display window results in the second spatial location of the annotation indicator being outside the second set of view area limitations; and the annotation indicator is displayed on a periphery of the display window.
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8. The method of claim 7 , wherein: the modifying the displaying of the three-dimensional model in the display window results in the second spatial location of the annotation indicator being outside the second set of view area limitations; and the annotation indicator is displayed on a periphery of the display window. 10. The method of claim 8 , wherein the annotation indicator includes a direction pointer corresponding to a bearing to the second spatial location on the second display view.
| 0.911527 |
12. A machine-readable storage medium, with instruction which when processed, result in a machine: defining a document model for generation of documents, wherein the document model includes: a header model including a set of header methods to provide interaction capabilities to other portions of a system, one or more item models, including a set of item methods to provide interaction capabilities to other portions of the system, wherein the header model and the one or more item models each include an association with one or more component models, and wherein each component model includes: a set of component methods to provide interaction capabilities to other portions of the system, and component specific logic accessible through the component methods, providing a first map within the header model between the set of header methods and the set of item methods, providing a second map within the item model between the set of item methods and the set of component methods, and providing a link between the set of component methods and the component specific logic.
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12. A machine-readable storage medium, with instruction which when processed, result in a machine: defining a document model for generation of documents, wherein the document model includes: a header model including a set of header methods to provide interaction capabilities to other portions of a system, one or more item models, including a set of item methods to provide interaction capabilities to other portions of the system, wherein the header model and the one or more item models each include an association with one or more component models, and wherein each component model includes: a set of component methods to provide interaction capabilities to other portions of the system, and component specific logic accessible through the component methods, providing a first map within the header model between the set of header methods and the set of item methods, providing a second map within the item model between the set of item methods and the set of component methods, and providing a link between the set of component methods and the component specific logic. 13. The machine-readable medium of claim 12 , wherein the instructions when processed, further result in the machine: storing the document model.
| 0.741404 |
1. A method, comprising: identifying a plurality of refinements R(q) of a first search query q, each refinement rεR(q) being a search query that follows the first query q in a session of queries submitted to a search system; identifying a document set D(r) of each of the refinements r, the document set of a refinement being the documents d that have been presented as search results in response to the refinement by the search system and that have received user selections while being presented as the search results; building a representation of a graph G for the first search query q, wherein the graph G has a node for the first search query q, a node for each of the refinements r, a node for each document d in the document sets of the refinements, and an off-topic node for an off-topic state f and wherein the graph G has edges from the first search query node q to each of the refinement nodes r, edges from the first search query node q to each document node of the respective document set D(q) of the first search query q, edges from each refinement node to each document node in the respective document set D(r) of the refinement, and edges from each refinement node to each node for a co-occurring query Q(r) of the refinement and to the off-topic node; building a transition probability matrix P for the graph G that includes first probabilities for each edge (r i , d), second probabilities for each edge (r i , f) and third probabilities for each edge (r i , r j ); calculating a visit probability vector for each refinement in the plurality of refinements R(q) from the transition probability matrix P, where each vector has elements representing a probability for each document in the document set D(q) and the document sets of the refinements R(q); clustering the refinements into refinement clusters by partitioning the visit probability vectors into proper subsets; and deriving search suggestion for the first search query based on the refinement clusters and providing, to a user device, data that causes the user device to display the search suggestions as search suggestions for the first query.
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1. A method, comprising: identifying a plurality of refinements R(q) of a first search query q, each refinement rεR(q) being a search query that follows the first query q in a session of queries submitted to a search system; identifying a document set D(r) of each of the refinements r, the document set of a refinement being the documents d that have been presented as search results in response to the refinement by the search system and that have received user selections while being presented as the search results; building a representation of a graph G for the first search query q, wherein the graph G has a node for the first search query q, a node for each of the refinements r, a node for each document d in the document sets of the refinements, and an off-topic node for an off-topic state f and wherein the graph G has edges from the first search query node q to each of the refinement nodes r, edges from the first search query node q to each document node of the respective document set D(q) of the first search query q, edges from each refinement node to each document node in the respective document set D(r) of the refinement, and edges from each refinement node to each node for a co-occurring query Q(r) of the refinement and to the off-topic node; building a transition probability matrix P for the graph G that includes first probabilities for each edge (r i , d), second probabilities for each edge (r i , f) and third probabilities for each edge (r i , r j ); calculating a visit probability vector for each refinement in the plurality of refinements R(q) from the transition probability matrix P, where each vector has elements representing a probability for each document in the document set D(q) and the document sets of the refinements R(q); clustering the refinements into refinement clusters by partitioning the visit probability vectors into proper subsets; and deriving search suggestion for the first search query based on the refinement clusters and providing, to a user device, data that causes the user device to display the search suggestions as search suggestions for the first query. 5. The method of claim 1 , wherein for each document d (all of which are terminal in G), then self-transitions:
P[d,d]= 1
| 0.878193 |
4. The system of claim 3 , further comprising an engine which enables production of a graph of the plurality of rules.
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4. The system of claim 3 , further comprising an engine which enables production of a graph of the plurality of rules. 5. The system of claim 4 , wherein the graph comprises the documentation of each rule and a graphical display of a rules hierarchy.
| 0.966822 |
1. A computer-implemented method comprising: receiving a spoken query from a user; processing the spoken query using an adapted language model, wherein the adapted language model is created using data associated with the spoken query, previous queries of the user and previous queries of a plurality of other users that share at least one common characteristic with the previous queries of the user, wherein the common characteristic is data for a selected uniform resource locator that is included in the previous queries of the user and included in the previous queries of the plurality of other users; and generating, using the adapted language model, a recognition result for the spoken query.
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1. A computer-implemented method comprising: receiving a spoken query from a user; processing the spoken query using an adapted language model, wherein the adapted language model is created using data associated with the spoken query, previous queries of the user and previous queries of a plurality of other users that share at least one common characteristic with the previous queries of the user, wherein the common characteristic is data for a selected uniform resource locator that is included in the previous queries of the user and included in the previous queries of the plurality of other users; and generating, using the adapted language model, a recognition result for the spoken query. 2. The computer-implemented method of claim 1 , further comprising converting the spoken query to text, and wherein the converted text for the spoken query is processed by the adapted language model to generate the recognition result.
| 0.798032 |
1. An apparatus, comprising: a processor circuit; and an application program operative on the processor circuit to manage a collaborative document having a presentation surface with multiple constructs, the application program comprising: a document render component operative to render a first document instance of the collaborative document; a document share component operative to receive a document update list comprising a set of change records for a second document instance of the collaborative document, each change record comprising information for a modification made to a construct of the second document instance, determine whether a time stamp of a change record for the first document instance of the collaborative document and a time stamp of a change record for the second document instance of the collaborative document are both within a synchronization interval when the change records have matching constructs, annotate the change records as conflict records, and modify properties of one or more constructs for the first document instance based on the change records to form a merged document instance of the collaborative document; and an undo manager component operative to manage a local undo stack for the first document instance, the local undo stack comprising a set of undo records each storing information to undo a modification made to a construct of the first document instance, compare the set of undo records and the set of change records, and determine whether to preserve one or more of the undo records of the local undo stack after formation of the merged document instance based on one or more of the change records.
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1. An apparatus, comprising: a processor circuit; and an application program operative on the processor circuit to manage a collaborative document having a presentation surface with multiple constructs, the application program comprising: a document render component operative to render a first document instance of the collaborative document; a document share component operative to receive a document update list comprising a set of change records for a second document instance of the collaborative document, each change record comprising information for a modification made to a construct of the second document instance, determine whether a time stamp of a change record for the first document instance of the collaborative document and a time stamp of a change record for the second document instance of the collaborative document are both within a synchronization interval when the change records have matching constructs, annotate the change records as conflict records, and modify properties of one or more constructs for the first document instance based on the change records to form a merged document instance of the collaborative document; and an undo manager component operative to manage a local undo stack for the first document instance, the local undo stack comprising a set of undo records each storing information to undo a modification made to a construct of the first document instance, compare the set of undo records and the set of change records, and determine whether to preserve one or more of the undo records of the local undo stack after formation of the merged document instance based on one or more of the change records. 5. The apparatus of claim 1 , the undo manager component operative to determine whether a time stamp of an undo record and a time stamp of a change record are both within a synchronization interval when the undo record and the change record have matching constructs, and annotate the undo record as a conflict record.
| 0.5 |
9. A computing device, comprising: means for receiving from a server computing device a full classifier model and sigmoid parameters; means for determining a normalized confidence value based on the received sigmoid parameters; and means for classifying a device behavior of the computing device based on a combination of: an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters.
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9. A computing device, comprising: means for receiving from a server computing device a full classifier model and sigmoid parameters; means for determining a normalized confidence value based on the received sigmoid parameters; and means for classifying a device behavior of the computing device based on a combination of: an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters. 13. The computing device of claim 9 , wherein means for classifying the device behavior of the computing device comprises: means for applying collected behavior information included in the behavior vector information structure to each of a plurality of boosted decision stumps included in the lean classifier model; means for computing a weighted average of a result of applying the collected behavior information to each of the plurality of boosted decision stumps included in the lean classifier model; and means for classifying the device behavior of the computing device based on a result of comparing the weighted average to a threshold value.
| 0.655861 |
13. A system, comprising: one or more processors; and memory storing instructions that when executed by at least some of the one or more processors effectuates operations comprising: receiving, over the Internet, from a user terminal, a query spoken by a user, wherein the query spoken by the user includes a speech utterance representing a category of businesses and a speech utterance representing a geographic location; recognizing the geographic location with a speech recognition engine based on the speech utterance representing the geographic location; recognizing the category of businesses with the speech recognition engine based on the speech utterance representing the category of businesses; searching a business listing for businesses within both the recognized category of businesses and the recognized geographic location to select businesses responsive to the query spoken by the user; and sending to the user terminal information related to at least some of the responsive businesses.
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13. A system, comprising: one or more processors; and memory storing instructions that when executed by at least some of the one or more processors effectuates operations comprising: receiving, over the Internet, from a user terminal, a query spoken by a user, wherein the query spoken by the user includes a speech utterance representing a category of businesses and a speech utterance representing a geographic location; recognizing the geographic location with a speech recognition engine based on the speech utterance representing the geographic location; recognizing the category of businesses with the speech recognition engine based on the speech utterance representing the category of businesses; searching a business listing for businesses within both the recognized category of businesses and the recognized geographic location to select businesses responsive to the query spoken by the user; and sending to the user terminal information related to at least some of the responsive businesses. 19. The system of claim 13 , wherein the operations comprise: selecting an adjacent location that is adjacent to the recognized location; searching the business listing for businesses within both the recognized category of businesses and the adjacent location to select additional businesses responsive to the query spoken by the user; and sending to the user terminal information related to at least some of the additional businesses.
| 0.559275 |
36. The system of claim 35 : wherein a communication session is established between the sandboxed application and the sandbox reachable service by appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, the header being either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the sandbox reachable service optionally verifies that the sandboxed application is in the common private network, wherein the sandbox reachable service communicates a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, wherein the sandboxed application communicates the MAC address and the unique identifier to a pairing server of the system, and wherein the script embedded in the at least one of the client device, the supply-side platform, and the data provider integrated with the supply side platform is automatically regenerated when the common private network is shared by the sandboxed application and sandboxed reachable service based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server.
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36. The system of claim 35 : wherein a communication session is established between the sandboxed application and the sandbox reachable service by appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, the header being either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the sandbox reachable service optionally verifies that the sandboxed application is in the common private network, wherein the sandbox reachable service communicates a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, wherein the sandboxed application communicates the MAC address and the unique identifier to a pairing server of the system, and wherein the script embedded in the at least one of the client device, the supply-side platform, and the data provider integrated with the supply side platform is automatically regenerated when the common private network is shared by the sandboxed application and sandboxed reachable service based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. 37. The system of claim 36 , wherein the client device is configured to: extend the security sandbox with a discovery algorithm and a relay algorithm through a discovery module and a relay module added to the security sandbox, and bypass the pairing server having the discovery algorithm and the relay algorithm when establishing the communication session between the sandboxed application and the sandbox reachable service when the security sandbox is extended with the discovery algorithm and the relay algorithm through the discovery module and the relay module added to the security sandbox.
| 0.863988 |
1. A method of processing Extensible Markup Language (XML) documents, said method comprising: parsing an XML document comprising content in an XML format; converting said content into pcodes according to a conversion key, wherein said conversion key comprises a lookup table (LUT) comprising a plurality of XML tags, said XML tags each having a corresponding pcode, wherein an XML tag is converted into a pcode according to said conversion key and wherein said content converted into pcodes is convertible back to XML using said conversion key; representing a recurring sequence of different XML source code segments comprising multiple XML tags as a single same pcode, wherein said LUT further comprises an entry comprising said recurring sequence and said single pcode; generating a pcode file comprising said XML document parsed and converted into pcode, wherein said pcode file comprises said single pcode in lieu of each occurrence of said recurring sequence of XML tags; and forwarding said conversion key with said pcode file from one computer system to another computer system.
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1. A method of processing Extensible Markup Language (XML) documents, said method comprising: parsing an XML document comprising content in an XML format; converting said content into pcodes according to a conversion key, wherein said conversion key comprises a lookup table (LUT) comprising a plurality of XML tags, said XML tags each having a corresponding pcode, wherein an XML tag is converted into a pcode according to said conversion key and wherein said content converted into pcodes is convertible back to XML using said conversion key; representing a recurring sequence of different XML source code segments comprising multiple XML tags as a single same pcode, wherein said LUT further comprises an entry comprising said recurring sequence and said single pcode; generating a pcode file comprising said XML document parsed and converted into pcode, wherein said pcode file comprises said single pcode in lieu of each occurrence of said recurring sequence of XML tags; and forwarding said conversion key with said pcode file from one computer system to another computer system. 2. The method of claim 1 , further comprising: reading an unrecognized XML tag, wherein an unrecognized XML tag is an XML tag not in said LUT; generating a new pcode for said unrecognized XML tag; and adding said new pcode and said unrecognized XML tag to said LUT.
| 0.566053 |
1. A method in a computer system for generating information retrieval tokens from an input string, the method comprising the steps of: creating from the input string a primary logical form characterizing a semantic relationship between selected words in the input string; identifying hypernyms of the selected words in the input string, at least one hypernym being identified from a group of hypernyms associated with a selected word wherein at least one other hypernym in the group is not identified; constructing from the primary logical form one or more alternative logical forms, each alternative logical form being constructed by, for each of one or more of the selected words in the input string, replacing the selected word in the primary logical form with an identified hypernym of the selected word; and generating tokens representing both the primary logical form and the alternative logical forms, the generated tokens being distinguishable by an information retrieval engine.
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1. A method in a computer system for generating information retrieval tokens from an input string, the method comprising the steps of: creating from the input string a primary logical form characterizing a semantic relationship between selected words in the input string; identifying hypernyms of the selected words in the input string, at least one hypernym being identified from a group of hypernyms associated with a selected word wherein at least one other hypernym in the group is not identified; constructing from the primary logical form one or more alternative logical forms, each alternative logical form being constructed by, for each of one or more of the selected words in the input string, replacing the selected word in the primary logical form with an identified hypernym of the selected word; and generating tokens representing both the primary logical form and the alternative logical forms, the generated tokens being distinguishable by an information retrieval engine. 8. The method of claim 1 wherein the identifying step identifies hypernyms of the selected words that have coherent hyponym sets with respect to the selected words.
| 0.612142 |
1. A computer-implemented method for scoring documents comprising: obtaining a set of attributes derived from an element of a web page, wherein the element is identified from eye-tracking data of a user viewing the web page, wherein the element of the web page comprises a text portion or an image portion of the web page, and wherein an attribute comprises a meaning of the text portion or an identity of the image portion of the web page; weighting each attribute of the set of attributes based on the eye-tracking data with respect to each attribute; receiving a search query of a database, wherein the search query comprises at least one query term, wherein the database comprises an index of web pages; identifying a set of web page documents in the database according to the search query; determining an attribute score for each document based on a relevancy of each web page document to the set of weighted attributes; and sorting the search query results according to the attribute score of each web page document.
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1. A computer-implemented method for scoring documents comprising: obtaining a set of attributes derived from an element of a web page, wherein the element is identified from eye-tracking data of a user viewing the web page, wherein the element of the web page comprises a text portion or an image portion of the web page, and wherein an attribute comprises a meaning of the text portion or an identity of the image portion of the web page; weighting each attribute of the set of attributes based on the eye-tracking data with respect to each attribute; receiving a search query of a database, wherein the search query comprises at least one query term, wherein the database comprises an index of web pages; identifying a set of web page documents in the database according to the search query; determining an attribute score for each document based on a relevancy of each web page document to the set of weighted attributes; and sorting the search query results according to the attribute score of each web page document. 2. The computer-implemented method of claim 1 , further comprising: determining a commonality between the query term and at least one member of the set of attributes.
| 0.594048 |
1. A method of using a computer to modify a list of terms assigned to a semantic category, the method comprising: receiving an indication of a seed term; using a computer to identify from a log of queries, a query having a set of query terms that includes at least one instance of the seed term in combination with a context word; utilizing the computer to automatically identify, from the log of queries, a second query having a set of query terms that does not include the seed termbut does include the context word in combination with a different term, the different term being different than the seed term and the context term; and utilizing the computer to remove the different term from the list of terms assigned to the semantic category, the different term being removed based on a determination that a significant enough context does not exist between the different term and the seed term, the significance of the context being determined utilizing the formula,
Score(c) =F_type{c}* log(g(c)/C), where g(c) =F_type{c}/F_inst{c}, where C =F_type{ctopx}/F_inst{ctopx}, where F_type is a frequency of context c in the semantic category, where F_inst is a frequency of context in an entire data, and where ctopx is x number of the most frequent contexts.
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1. A method of using a computer to modify a list of terms assigned to a semantic category, the method comprising: receiving an indication of a seed term; using a computer to identify from a log of queries, a query having a set of query terms that includes at least one instance of the seed term in combination with a context word; utilizing the computer to automatically identify, from the log of queries, a second query having a set of query terms that does not include the seed termbut does include the context word in combination with a different term, the different term being different than the seed term and the context term; and utilizing the computer to remove the different term from the list of terms assigned to the semantic category, the different term being removed based on a determination that a significant enough context does not exist between the different term and the seed term, the significance of the context being determined utilizing the formula,
Score(c) =F_type{c}* log(g(c)/C), where g(c) =F_type{c}/F_inst{c}, where C =F_type{ctopx}/F_inst{ctopx}, where F_type is a frequency of context c in the semantic category, where F_inst is a frequency of context in an entire data, and where ctopx is x number of the most frequent contexts. 4. The method of claim 1 , wherein identifying a query comprises identifying a plurality of queries in the log of queries.
| 0.5 |
13. An embedded user interface system for use in a gaming machine, the gaming machine including a gaming presentation and gaming processor, the embedded user interface system comprising: a web content capable display screen, wherein the display screen presents information to a user via the display screen; a dictionary extension, wherein the dictionary extension receives an incoming text data message directed to be displayed to a player upon a display screen, and translates the message into an XML, HTML, or DHTML enhanced player message directed to be displayed to the player upon the display screen; and an embedded processor that employs an internal operating system and communicates with the gaming processor, wherein the embedded processor reads an incoming text data message sent from a game monitoring unit to the player, calls the dictionary component, returns a set of actions upon which a display manager performs, and displays the enhanced player message to the player on the display screen.
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13. An embedded user interface system for use in a gaming machine, the gaming machine including a gaming presentation and gaming processor, the embedded user interface system comprising: a web content capable display screen, wherein the display screen presents information to a user via the display screen; a dictionary extension, wherein the dictionary extension receives an incoming text data message directed to be displayed to a player upon a display screen, and translates the message into an XML, HTML, or DHTML enhanced player message directed to be displayed to the player upon the display screen; and an embedded processor that employs an internal operating system and communicates with the gaming processor, wherein the embedded processor reads an incoming text data message sent from a game monitoring unit to the player, calls the dictionary component, returns a set of actions upon which a display manager performs, and displays the enhanced player message to the player on the display screen. 23. The embedded user interface of claim 13 , wherein the embedded enhanced user interface connects to an Ethernet-networked backbone.
| 0.771552 |
15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system.
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15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. 93. The computer program product of claim 15 , wherein the computer program product is further operable such that a first document associated with the first application which includes a word processor with tagging capabilities is capable of being subject of a publishing function of the second application, the tagging capabilities including: receiving a request; code for, in response to the request, displaying an interface for receiving an indication of one or more tags, the interface including a list of suggested previously-existing tags from which a selection is capable of being made; code for, utilizing the interface, receiving the indication of one or more tags utilizing the list; and code for utilizing the one or more tags for correlation purposes.
| 0.5 |
17. One or more non-transitory machine-readable media that store instructions for use in transferring data via a communication session between a client application on a first network and a server application on a second network, the instructions for causing one or more processing devices to perform operations comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application is on the second network behind a second firewall that is different from the first firewall.
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17. One or more non-transitory machine-readable media that store instructions for use in transferring data via a communication session between a client application on a first network and a server application on a second network, the instructions for causing one or more processing devices to perform operations comprising: outputting, to a device that includes the client application, a Web page comprising a proxy, the proxy for converting between a non-local protocol and a local protocol associated with the client application to thereby provide data to the client application in the local protocol; assigning an identifier to the communication session; creating at least one queue associated with the communication session; storing data received from the server application in the at least one queue, the received data being stored using the identifier; receiving polling data from the proxy to obtain the received data that is destined for the client application from the at least one queue associated with the communication session; outputting the received data to the proxy in response to the polling data; wherein the client application and the server application run local protocols, and the received data is passed from the server application to the client application via an intermediary protocol that corresponds to the non-local protocol; and wherein the client application is on the first network behind a first firewall, and the server application is on the second network behind a second firewall that is different from the first firewall. 21. The one or more non-transitory machine-readable media of claim 17 , wherein the identifier is associated with the at least one queue.
| 0.63073 |
35. A method of estimating a country where a device is configured to operate, said method comprising: at a server, receiving a plurality of configuration settings defined for said device, wherein said configuration settings comprise a first configuration setting that is based on time and a second configuration setting that is not based on time; and at the server, using a recursive rule program to estimate the country where the device is configured to operate based on said received plurality of configuration settings.
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35. A method of estimating a country where a device is configured to operate, said method comprising: at a server, receiving a plurality of configuration settings defined for said device, wherein said configuration settings comprise a first configuration setting that is based on time and a second configuration setting that is not based on time; and at the server, using a recursive rule program to estimate the country where the device is configured to operate based on said received plurality of configuration settings. 37. The method of claim 35 , wherein the second configuration setting comprises a language setting.
| 0.826479 |
1. A system for creating, distributing, and managing of shared compression dictionaries, comprising: a compressor configured to generate at least one shared compression dictionary based on a context of data streams flow between a client web browser and an origin server, wherein the context being derived from data streams is of at least one request and a corresponding response between the client web browser and the origin server; an origin accelerator communicatively connected to the origin server and configured to encode an encountered data stream to a compressed form based on the at least one shared compression dictionary; an edge accelerator communicatively connected to the client web browser and configured to decode the compressed form of the data stream to an uncompressed form using the at least one shared compression dictionary; and a dictionary database accessible to each of the edge accelerator, the origin accelerator and the compressor, wherein the compressor is configured to generate and save the at least one shared compression dictionary in the dictionary database developed as part of an offline process.
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1. A system for creating, distributing, and managing of shared compression dictionaries, comprising: a compressor configured to generate at least one shared compression dictionary based on a context of data streams flow between a client web browser and an origin server, wherein the context being derived from data streams is of at least one request and a corresponding response between the client web browser and the origin server; an origin accelerator communicatively connected to the origin server and configured to encode an encountered data stream to a compressed form based on the at least one shared compression dictionary; an edge accelerator communicatively connected to the client web browser and configured to decode the compressed form of the data stream to an uncompressed form using the at least one shared compression dictionary; and a dictionary database accessible to each of the edge accelerator, the origin accelerator and the compressor, wherein the compressor is configured to generate and save the at least one shared compression dictionary in the dictionary database developed as part of an offline process. 3. The system of claim 1 , wherein each of the origin accelerator and the edge accelerator is configured to select the at least one shared compression dictionary based on a context of the encountered data stream.
| 0.736396 |
6. The user electronic device of claim 5 , wherein the additional information is related to one or more products or services.
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6. The user electronic device of claim 5 , wherein the additional information is related to one or more products or services. 8. The user electronic device of claim 6 , wherein the additional information is related to a product category associated with the one or more products or services.
| 0.936538 |
1. A computer-implemented system that facilitates content presentation, comprising: a profile component that facilitates user creation of user preferences data in a user profile of a user; a control component that facilitates the user's control to incrementally expose portions of the user preferences data from the user profile of the user to a vendor and to independently expose different amounts of the user preference data to each of a plurality of different vendors; and a content component that presents content of the vendor to the user based on the exposed portions of the user preferences data.
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1. A computer-implemented system that facilitates content presentation, comprising: a profile component that facilitates user creation of user preferences data in a user profile of a user; a control component that facilitates the user's control to incrementally expose portions of the user preferences data from the user profile of the user to a vendor and to independently expose different amounts of the user preference data to each of a plurality of different vendors; and a content component that presents content of the vendor to the user based on the exposed portions of the user preferences data. 5. The system of claim 1 , wherein the content component further presents the content of the vendor based on a preferred content format expressed in the user preferences.
| 0.630747 |
1. A method for online task advising that assists a user to complete a task, the method comprising: receiving, from a user by a system comprising a hardware processor, a request to customize a task definition of a customizable script in a memory; updating, by the system, the task definition based on the request; receiving, from a user by the system, a selection of a task definition to be completed, the task definition to be completed being the updated task definition; creating, by the system, a task instance based, at least in part, on the selected task definition, the task instance comprising a step associated with completing the task, the step comprising a status indicator; receiving, by the system, a selection of the step from a user; determining, by the system, whether the selected step is associated with an action; responsive to the selected step being associated with the action, by the system: executing the action, and updating the status indicator of the selected step based on the executed action; responsive to the selected step not being associated with the action, by the system: presenting the user with the selected step for election whether to complete the selected step, receiving, from the user, an indication that the selected step is complete, and updating the status indicator of the selected step based on the indication from the user; and providing, by the system, the task instance for presentation on a display.
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1. A method for online task advising that assists a user to complete a task, the method comprising: receiving, from a user by a system comprising a hardware processor, a request to customize a task definition of a customizable script in a memory; updating, by the system, the task definition based on the request; receiving, from a user by the system, a selection of a task definition to be completed, the task definition to be completed being the updated task definition; creating, by the system, a task instance based, at least in part, on the selected task definition, the task instance comprising a step associated with completing the task, the step comprising a status indicator; receiving, by the system, a selection of the step from a user; determining, by the system, whether the selected step is associated with an action; responsive to the selected step being associated with the action, by the system: executing the action, and updating the status indicator of the selected step based on the executed action; responsive to the selected step not being associated with the action, by the system: presenting the user with the selected step for election whether to complete the selected step, receiving, from the user, an indication that the selected step is complete, and updating the status indicator of the selected step based on the indication from the user; and providing, by the system, the task instance for presentation on a display. 6. The method of claim 1 , wherein the action is associated with an interactive wizard, and the method further comprises: receiving a notification that the interactive wizard was successfully completed, wherein the updating the status indicator of the selected step comprises automatically updating the status indicator to indicate the selected step is complete based on the notification.
| 0.511918 |
2. The method of claim 1 , wherein the information comprises a script.
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2. The method of claim 1 , wherein the information comprises a script. 3. The method of claim 2 , wherein the script comprises a markup language document.
| 0.959459 |
1. A method of providing semantic information related to the meaning of input text, the method comprising with a processor: receiving input text; processing at least portions of the input text to identify self-describing fragments of the input text based on a hierarchical schema, the hierarchical schema defining a domain with at least one top-level node and child nodes, wherein each identified self-describing fragment includes hierarchical context with respect to the hierarchical schema of each corresponding portion of the input text and positional information of words forming the corresponding portion in the input text; and providing semantic information related to the meaning of at least some portion of the input text based on the identified self-describing fragments.
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1. A method of providing semantic information related to the meaning of input text, the method comprising with a processor: receiving input text; processing at least portions of the input text to identify self-describing fragments of the input text based on a hierarchical schema, the hierarchical schema defining a domain with at least one top-level node and child nodes, wherein each identified self-describing fragment includes hierarchical context with respect to the hierarchical schema of each corresponding portion of the input text and positional information of words forming the corresponding portion in the input text; and providing semantic information related to the meaning of at least some portion of the input text based on the identified self-describing fragments. 6. The method of claim 1 wherein providing semantic information related to the meaning of at least some portion of the input text based on the identified self-describing fragments comprises providing a set of semantic solutions, each solution being a potential meaning of at least a portion of the input text.
| 0.674101 |
5. An optical system as in claim 1 , further comprising a plurality of lasers and detectors.
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5. An optical system as in claim 1 , further comprising a plurality of lasers and detectors. 10. An optical system as in claim 5 , further comprising one or more circuits selected from the group consisting of: a burst-mode circuit and a forward-error correction circuit.
| 0.940942 |
4. The network of claim 3 , wherein the service bureau includes a mixed media reality content delivery module for receiving the request from the customer and generating a query on the database, and for delivering results of the query to the user.
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4. The network of claim 3 , wherein the service bureau includes a mixed media reality content delivery module for receiving the request from the customer and generating a query on the database, and for delivering results of the query to the user. 5. The network of claim 4 , wherein the service bureau includes a revenue allocation module for receiving information about which original content was accessed and which customer content was presented to the user, for collect fees from the user and allocating the collected fees, the revenue allocation module adapted for communication with the clearinghouse and the content delivery module.
| 0.710358 |
1. A transverse coupler for a spinal correction system, the transverse coupler comprising: an adjustment assembly configured to be secured to a first rod extending longitudinally along a first side of a spine, the adjustment assembly including a rider, a retainer, and a first rod coupler, the first rod coupler configured to receive the first rod such that the first rod is free to translate axially through the first rod coupler, pivot in pitch and yaw at the first rod coupler, and roll within the first rod coupler; an adjustment arm configured to be secured to a second rod extending longitudinally along a second side of a spine and to be extended from a second side of a spine toward a first side of a spine, the adjustment arm defining a first end, a second end, a first surface, a second surface, and a longitudinal axis extending from the first end to the second end; a force directing member with an elongate body configured to couple with the rider and the first end of the adjustment arm, the rider and the elongate body being configured to form a complementary fit, wherein the rider can move along the elongate body and couple with the adjustment arm at a plurality of angles; a first intermediate anchor adapted to be positioned along the second rod between the adjustment arm and a first stabilizing anchor; and a second intermediate anchor adapted to be positioned along the second rod between the adjustment arm and a second stabilizing anchor, wherein each of the first and second intermediate anchors is adapted to substantially constrain the second rod against substantial lateral translation.
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1. A transverse coupler for a spinal correction system, the transverse coupler comprising: an adjustment assembly configured to be secured to a first rod extending longitudinally along a first side of a spine, the adjustment assembly including a rider, a retainer, and a first rod coupler, the first rod coupler configured to receive the first rod such that the first rod is free to translate axially through the first rod coupler, pivot in pitch and yaw at the first rod coupler, and roll within the first rod coupler; an adjustment arm configured to be secured to a second rod extending longitudinally along a second side of a spine and to be extended from a second side of a spine toward a first side of a spine, the adjustment arm defining a first end, a second end, a first surface, a second surface, and a longitudinal axis extending from the first end to the second end; a force directing member with an elongate body configured to couple with the rider and the first end of the adjustment arm, the rider and the elongate body being configured to form a complementary fit, wherein the rider can move along the elongate body and couple with the adjustment arm at a plurality of angles; a first intermediate anchor adapted to be positioned along the second rod between the adjustment arm and a first stabilizing anchor; and a second intermediate anchor adapted to be positioned along the second rod between the adjustment arm and a second stabilizing anchor, wherein each of the first and second intermediate anchors is adapted to substantially constrain the second rod against substantial lateral translation. 7. The transverse coupler of claim 1 , wherein the force directing member is rigidly secured to the first end of the adjustment arm and extends from the first surface of the adjustment arm at a substantially fixed angle relative to the longitudinal axis.
| 0.566441 |
22. The non-transitory computer readable data storage medium article of manufacture of claim 21 , wherein the method further comprises: weighing the user-rated value of content in the interaction record based upon the rating of the user within the community of users.
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22. The non-transitory computer readable data storage medium article of manufacture of claim 21 , wherein the method further comprises: weighing the user-rated value of content in the interaction record based upon the rating of the user within the community of users. 23. The non-transitory computer readable data storage medium article of manufacture of claim 22 , wherein the method further comprises: performing a direct community rating, wherein an individual user rates the community of users in which the individual user participates; determining a collective member score of the community of users, wherein the collective member score includes a sum of the ratings of the individual users in the community of users; determining an average resource rating, wherein the average resource rating includes an average rating of interaction records within the community of users; and rating the community of users based upon the direct community rating, the collective member score, and the average resource rating.
| 0.753064 |
14. The non-transitory computer storage medium of claim 13 , wherein the operations further comprise identifying, based on the user search activity, a set of follow-up queries for the query pair, each follow-up query in the set being a query that was received following receipt of the first query and the second query in at least one previous user search session, the set of follow-up queries including the third query.
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14. The non-transitory computer storage medium of claim 13 , wherein the operations further comprise identifying, based on the user search activity, a set of follow-up queries for the query pair, each follow-up query in the set being a query that was received following receipt of the first query and the second query in at least one previous user search session, the set of follow-up queries including the third query. 17. The non-transitory computer storage medium of claim 14 , wherein the operations further comprise selecting, for providing to the user device, the third query from the set of follow-up queries based on a number of occurrences of the third query in the stored search log data.
| 0.907016 |
1. A computer system for generating a representation of time-based media, the system comprising: a feature extraction module for: extracting, using a feature extraction technique, features from the time-based media, the feature extraction technique specified by a document format specification file; and generating a media representation of the time-based media that represents the extracted features, the media representation including a waveform representing the time based media including the extracted features, a corresponding timeline and a plurality of user-selectable identifiers indicating locations on the timeline corresponding to the extracted features; a formatting module communicatively coupled to the feature extraction module, the formatting module for: formatting the media representation according to layout parameters specified by the document format specification file; and a printer communicatively coupled to the formatting module, the printer for: printing the formatted media representation, wherein each of the plurality of user-selectable identifiers in the printed, formatted media representation can be selected to access a corresponding part of the time-based media.
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1. A computer system for generating a representation of time-based media, the system comprising: a feature extraction module for: extracting, using a feature extraction technique, features from the time-based media, the feature extraction technique specified by a document format specification file; and generating a media representation of the time-based media that represents the extracted features, the media representation including a waveform representing the time based media including the extracted features, a corresponding timeline and a plurality of user-selectable identifiers indicating locations on the timeline corresponding to the extracted features; a formatting module communicatively coupled to the feature extraction module, the formatting module for: formatting the media representation according to layout parameters specified by the document format specification file; and a printer communicatively coupled to the formatting module, the printer for: printing the formatted media representation, wherein each of the plurality of user-selectable identifiers in the printed, formatted media representation can be selected to access a corresponding part of the time-based media. 19. The system of claim 1 , wherein the document format specification comprises a number of user-definable fields specifying feature extraction techniques to apply to the time-based media.
| 0.527994 |
1. A method comprising: updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure for the content; and classifying, by the predictive coding system, a second training document containing the content based on the probability measure.
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1. A method comprising: updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure for the content; and classifying, by the predictive coding system, a second training document containing the content based on the probability measure. 6. The method of claim 1 , further comprising: identifying one or more exemplar documents used by the predictive coding system to classify a prediction document in the updated set of updated training documents; and identifying a region of the prediction document used by the predictive coding system to determine the classification for the prediction document in the updated set of training documents.
| 0.560224 |
1. A method performed by one or more processing devices, comprising: obtaining search results responsive to a search query submitted by a user; determining, based on usage of a social network by the user, a maturity score for the user, where the maturity score represents a measure of user development of the user within the social network; for a particular type of content associated with a search result, retrieving, from a set of utility score instructions, a utility score instruction for the particular type of content; wherein the utility score instruction defines, for the particular type of content in the social network, a relationship between a utility score and the maturity score; wherein the utility score represents a measure of utility of the particular type of content to the user as defined by the measure of user development in the social network; and wherein the utility score is determined independent of user input; wherein defined relationships across the set of utility score instructions promote a first pre-defined type of content among less mature users of the social network relative to other maturities of other users of the social network and promote a second pre-defined type of content among more mature users of the social network relative to the other maturities of the other users of the social network; determining, based on the set of utility score instructions and the maturity score, utility scores for the search results; and adjusting rankings of the search results based on the utility scores.
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1. A method performed by one or more processing devices, comprising: obtaining search results responsive to a search query submitted by a user; determining, based on usage of a social network by the user, a maturity score for the user, where the maturity score represents a measure of user development of the user within the social network; for a particular type of content associated with a search result, retrieving, from a set of utility score instructions, a utility score instruction for the particular type of content; wherein the utility score instruction defines, for the particular type of content in the social network, a relationship between a utility score and the maturity score; wherein the utility score represents a measure of utility of the particular type of content to the user as defined by the measure of user development in the social network; and wherein the utility score is determined independent of user input; wherein defined relationships across the set of utility score instructions promote a first pre-defined type of content among less mature users of the social network relative to other maturities of other users of the social network and promote a second pre-defined type of content among more mature users of the social network relative to the other maturities of the other users of the social network; determining, based on the set of utility score instructions and the maturity score, utility scores for the search results; and adjusting rankings of the search results based on the utility scores. 4. The method of claim 1 , wherein the utility score instructions comprise instructions for calculating, based on the maturity score, the utility scores; and wherein determining the utility scores comprises: determining, based on executing the utility score instructions, the utility scores.
| 0.82619 |
13. A system comprising: a memory that stores instructions; and one or more processors configured by the instructions to perform operations comprising: accessing a first schema comprising a first plurality of business entities including a first business entity, the first business entity having a first name in the first schema; accessing a second schema comprising a second plurality of business entities including the first business entity, the first business entity having a second name in the second schema; generating from the first schema and the second schema, a merged schema comprising a third plurality of business entities, including a single instance of the first business entity; storing the merged schema in a database; extracting a first sequence of words from the first name of the first business entity; generating candidate phrases for the business entity from the first and second sequences of words; and ranking the candidate phrases for the first business entity; analyzing candidate sets of labels for the third plurality of business entities, each candidate set of labels including a label for each business entity of the third plurality of business entities, no two business entities having the same label in the candidate set of labels, the label for the first business entity being selected from the candidate phrases for the first business entity; and assigning labels to each business entity of the third plurality of business entities based on the analysis of the candidate sets of labels; and receiving data stored using the first schema; converting the received data to the merged schema; and causing a presentation of the converted data using the assigned labels.
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13. A system comprising: a memory that stores instructions; and one or more processors configured by the instructions to perform operations comprising: accessing a first schema comprising a first plurality of business entities including a first business entity, the first business entity having a first name in the first schema; accessing a second schema comprising a second plurality of business entities including the first business entity, the first business entity having a second name in the second schema; generating from the first schema and the second schema, a merged schema comprising a third plurality of business entities, including a single instance of the first business entity; storing the merged schema in a database; extracting a first sequence of words from the first name of the first business entity; generating candidate phrases for the business entity from the first and second sequences of words; and ranking the candidate phrases for the first business entity; analyzing candidate sets of labels for the third plurality of business entities, each candidate set of labels including a label for each business entity of the third plurality of business entities, no two business entities having the same label in the candidate set of labels, the label for the first business entity being selected from the candidate phrases for the first business entity; and assigning labels to each business entity of the third plurality of business entities based on the analysis of the candidate sets of labels; and receiving data stored using the first schema; converting the received data to the merged schema; and causing a presentation of the converted data using the assigned labels. 17. The system of claim 13 , wherein the ranking of the candidate phrases for the first business entity includes ranking the candidate phrases for the first business entity based on an inverse of a frequency of words in each candidate phrase in names of all business entities in the third plurality of business entities.
| 0.763623 |
3. An electronic language translator according to claim 2, wherein the first and second discrimination codes are stored in the respective first and second language memory means in association with both the respective ones of the plurality of sentences and the replacement words.
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3. An electronic language translator according to claim 2, wherein the first and second discrimination codes are stored in the respective first and second language memory means in association with both the respective ones of the plurality of sentences and the replacement words. 4. An electronic language translator according to claim 3, wherein the first and second discrimination codes distinguish between the selected word stored in a respective one of the plurality of sentences and the replacement words capable of replacing the selected word stored in the respective sentence.
| 0.941985 |
20. A computerized method for determining whether an insurance claim merits recovery comprising: receiving an electronic claim file via a communications network; compiling said electronic claim file in a processor to develop a dictionary of term data having synonyms relating to said electronic claim file via a search and indexing engine; storing said term data in a database, wherein the database stores the synonyms in association with one or more concepts, each of said concepts forming into an element in a vector, said search and indexing engine comparing said synonyms against elements of said vector to determine whether said electronic claim file contains a stored concept element; generating a score in said processor based on said determination of whether said electronic claim file contains said stored concept element; and routing the score to one or more recipients via said communications network.
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20. A computerized method for determining whether an insurance claim merits recovery comprising: receiving an electronic claim file via a communications network; compiling said electronic claim file in a processor to develop a dictionary of term data having synonyms relating to said electronic claim file via a search and indexing engine; storing said term data in a database, wherein the database stores the synonyms in association with one or more concepts, each of said concepts forming into an element in a vector, said search and indexing engine comparing said synonyms against elements of said vector to determine whether said electronic claim file contains a stored concept element; generating a score in said processor based on said determination of whether said electronic claim file contains said stored concept element; and routing the score to one or more recipients via said communications network. 22. The computerized method of claim 20 wherein said score is derived from an N-Gram analysis to form an element for deciding if a claim merits claim recovery efforts.
| 0.50744 |
15. An apparatus for enabling interoperability between virtual world and real world, the apparatus comprising: a processor comprising: an adaptation unit configured to acquire sensed information of a predefined representation syntax from a sensor, wherein the predefined representation syntax defines elements, mnemonics of the elements, flags corresponding to the elements, and mnemonics of the flags, wherein the elements comprise an ID element, a sensor ID reference element, a linked list element, a group ID element, a priority element, and an activation element, and wherein the sensed information includes the flags corresponding to the elements, and at least one element corresponding to at least one flag having a predefined logic value.
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15. An apparatus for enabling interoperability between virtual world and real world, the apparatus comprising: a processor comprising: an adaptation unit configured to acquire sensed information of a predefined representation syntax from a sensor, wherein the predefined representation syntax defines elements, mnemonics of the elements, flags corresponding to the elements, and mnemonics of the flags, wherein the elements comprise an ID element, a sensor ID reference element, a linked list element, a group ID element, a priority element, and an activation element, and wherein the sensed information includes the flags corresponding to the elements, and at least one element corresponding to at least one flag having a predefined logic value. 17. The apparatus of claim 15 , wherein the elements comprise a position element, an orientation element, a velocity element, an angular velocity element, an acceleration element.
| 0.684564 |
1. A method of learning-free detection and localization of actions, comprising: a. providing a query video action of interest and providing a target video by using an appropriately programmed computer; b. obtaining at least one query space-time localized steering kernel (3-D LSK) from said query video action of interest and obtaining at least one target 3-D LSK from said target video by using said appropriately programmed computer, wherein said kernel 3-D LSK and said target 3-D LSK implicitly contain information about local motion of voxels across time, wherein no explicit motion estimation is required; c. determining at least one query feature from said query 3-D LSK and determining at least one target patch feature from said target 3-D LSK by using said appropriately programmed computer; and d. outputting a resemblance map, wherein said resemblance map provides a likelihood of a similarity between each said query feature and each said target patch feature by using said appropriately programmed computer to output learning-free detection and localization of actions.
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1. A method of learning-free detection and localization of actions, comprising: a. providing a query video action of interest and providing a target video by using an appropriately programmed computer; b. obtaining at least one query space-time localized steering kernel (3-D LSK) from said query video action of interest and obtaining at least one target 3-D LSK from said target video by using said appropriately programmed computer, wherein said kernel 3-D LSK and said target 3-D LSK implicitly contain information about local motion of voxels across time, wherein no explicit motion estimation is required; c. determining at least one query feature from said query 3-D LSK and determining at least one target patch feature from said target 3-D LSK by using said appropriately programmed computer; and d. outputting a resemblance map, wherein said resemblance map provides a likelihood of a similarity between each said query feature and each said target patch feature by using said appropriately programmed computer to output learning-free detection and localization of actions. 8. The method of detection and localization of actions in claim 1 , wherein each said 3-D LSK is densely computed and normalized.
| 0.614235 |
15. The method of claim 13, wherein the step of selecting, for each quadrant of each ideogrammatic character to be typed in which a characteristic stroke configuration appears, the single keyboard indicium which most closely identifies that stroke configuration, whereby between one and four indicia are combined to provide the identifier for each character.
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15. The method of claim 13, wherein the step of selecting, for each quadrant of each ideogrammatic character to be typed in which a characteristic stroke configuration appears, the single keyboard indicium which most closely identifies that stroke configuration, whereby between one and four indicia are combined to provide the identifier for each character. 16. The method of claim 15, wherein the symbolic language is Chinese.
| 0.929774 |
1. A computer-implemented method for searching for program code libraries in multiple programming languages in a networked computing environment, comprising: receiving, in a computer memory medium, a request, from a user, to search at least one program code library repository associated with an integrated development environment (IDE) for a program code library, the request comprising a set of annotations corresponding to a primary program code language of the program code library and an alternate program code language of the program code library; searching, based on the set of annotations, the at least one program code library repository for the program code library in the primary program code language; if no matches are found, expanding the search to include the alternate program code language; if a match is found, building a wrapper method in the primary program code language on top of the alternate program code language; and executing the wrapper method.
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1. A computer-implemented method for searching for program code libraries in multiple programming languages in a networked computing environment, comprising: receiving, in a computer memory medium, a request, from a user, to search at least one program code library repository associated with an integrated development environment (IDE) for a program code library, the request comprising a set of annotations corresponding to a primary program code language of the program code library and an alternate program code language of the program code library; searching, based on the set of annotations, the at least one program code library repository for the program code library in the primary program code language; if no matches are found, expanding the search to include the alternate program code language; if a match is found, building a wrapper method in the primary program code language on top of the alternate program code language; and executing the wrapper method. 8. The computer-implemented method of claim 1 , the networked computing environment comprising a cloud computing environment.
| 0.632694 |
1. A mobile device for processing multi-modal natural language inputs, comprising: a conversational voice user interface that receives a multi-modal natural language input from a user, the multi-modal natural language input including a natural language utterance and a non-speech input, the conversational voice user interface coupled to a transcription module that transcribes the non-speech input to create a non-speech-based transcription; a conversational speech analysis engine that identifies the user that provided the multi-modal natural language input, the conversational speech analysis engine using a speech recognition engine and a semantic knowledge-based model to create a speech-based transcription of the natural language utterance, wherein the semantic knowledge-based model includes a personalized cognitive model derived from one or more prior interactions between the identified user and the mobile device, a general cognitive model derived from one or more prior interactions between a plurality of users and the mobile device, and an environmental model derived from an environment of the identified user and the mobile device; a merging module that merges the speech-based transcription and the non-speech-based transcription to create a merged transcription; a knowledge-enhanced speech recognition engine that identifies one or more entries in a context stack matching information contained in the merged transcription and determines a most likely context for the multi-modal natural language input based on the identified entries; and a response generating module that identifies a domain agent associated with the most likely context for the multi-modal input, communicates a request to the identified domain agent, and generates a response to the user from content provided by the identified domain agent as a result of processing the request.
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1. A mobile device for processing multi-modal natural language inputs, comprising: a conversational voice user interface that receives a multi-modal natural language input from a user, the multi-modal natural language input including a natural language utterance and a non-speech input, the conversational voice user interface coupled to a transcription module that transcribes the non-speech input to create a non-speech-based transcription; a conversational speech analysis engine that identifies the user that provided the multi-modal natural language input, the conversational speech analysis engine using a speech recognition engine and a semantic knowledge-based model to create a speech-based transcription of the natural language utterance, wherein the semantic knowledge-based model includes a personalized cognitive model derived from one or more prior interactions between the identified user and the mobile device, a general cognitive model derived from one or more prior interactions between a plurality of users and the mobile device, and an environmental model derived from an environment of the identified user and the mobile device; a merging module that merges the speech-based transcription and the non-speech-based transcription to create a merged transcription; a knowledge-enhanced speech recognition engine that identifies one or more entries in a context stack matching information contained in the merged transcription and determines a most likely context for the multi-modal natural language input based on the identified entries; and a response generating module that identifies a domain agent associated with the most likely context for the multi-modal input, communicates a request to the identified domain agent, and generates a response to the user from content provided by the identified domain agent as a result of processing the request. 7. The mobile device of claim 1 , wherein the conversational speech analysis engine identifies the user based on at least one of voiceprint matching, password matching, or pass-phrase matching.
| 0.520393 |
1. A system for detecting a global harmful video, the system comprising: at least one processor configured to: determine harmfulness of learning video segments from video learning information to analyze occurrence information of harmful learning video segments among the learning video segments, and generate a global harmfulness determination policy based on the analyzed occurrence information; and determine harmfulness of input video segments from information of an input video to analyze occurrence information of harmful input video segments among the input video segments, and determine whether the input video is harmful or not based on the analyzed occurrence information of the harmful input video segments and the generated global harmfulness determination policy, wherein the at least one processor is further configured to determine harmfulness of the learning video segments; analyze the occurrence information of the harmful learning video segments based on the harmfulness determination results of the learning video segments to thereby derive occurrence frequencies, occurrence continuities and occurrence probability values of the harmful learning video segment; and generate the global harmfulness determination policy by determining weights for each of the occurrence frequencies, the occurrence continuities and the occurrence probability values of the harmful learning video segments.
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1. A system for detecting a global harmful video, the system comprising: at least one processor configured to: determine harmfulness of learning video segments from video learning information to analyze occurrence information of harmful learning video segments among the learning video segments, and generate a global harmfulness determination policy based on the analyzed occurrence information; and determine harmfulness of input video segments from information of an input video to analyze occurrence information of harmful input video segments among the input video segments, and determine whether the input video is harmful or not based on the analyzed occurrence information of the harmful input video segments and the generated global harmfulness determination policy, wherein the at least one processor is further configured to determine harmfulness of the learning video segments; analyze the occurrence information of the harmful learning video segments based on the harmfulness determination results of the learning video segments to thereby derive occurrence frequencies, occurrence continuities and occurrence probability values of the harmful learning video segment; and generate the global harmfulness determination policy by determining weights for each of the occurrence frequencies, the occurrence continuities and the occurrence probability values of the harmful learning video segments. 5. The system of claim 1 , wherein the at least one processor is further configured to: calculate the occurrence frequencies of the harmful learning video segments and locations of the occurrences; assign the occurrence continuities to the harmful learning video segments which successively appear; and calculate the occurrence probability values of the harmful learning video segments by combining harmfulness probability values of the harmful learning video segments with the occurrence continuities.
| 0.648629 |
20. The computational device according to claim 15 , wherein said determinator is configured to determine connective matching measures.
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20. The computational device according to claim 15 , wherein said determinator is configured to determine connective matching measures. 21. The computational device according to claim 20 , further comprising a compensator configured to compensate for translation, angle or length differences between the segments such that the connective features are relative between the adjacent segments.
| 0.88975 |
4. The computer system of claim 1 wherein the entity models are interrelated by relationships having a plurality of relationship types.
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4. The computer system of claim 1 wherein the entity models are interrelated by relationships having a plurality of relationship types. 5. The computer system of claim 4 wherein each relationship between two entity models is navigable in at least one direction.
| 0.974646 |
1. In a medical implant assembly having at least two bone anchors cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) first and second segments, the first segment having a first bore formed in a first end surface thereof, the second segment having a second bore formed in a second end surface thereof, the first segment attached to the first bone anchor and the second segment attached to the second bone anchor; b) an inner elongate core partially disposed and slidingly received within each of the bores of the first and second segments; c) at least one spacer member disposed about the core and located between the first and second segments; and d) an elastic structure surrounding the at least one spacer member, the elastic structure gripping at least the first segment, the spacer member being slidable along the inner core with the elastic structure being in a stretched orientation when one of the first and second segments moves away from the other of the first and second segments.
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1. In a medical implant assembly having at least two bone anchors cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) first and second segments, the first segment having a first bore formed in a first end surface thereof, the second segment having a second bore formed in a second end surface thereof, the first segment attached to the first bone anchor and the second segment attached to the second bone anchor; b) an inner elongate core partially disposed and slidingly received within each of the bores of the first and second segments; c) at least one spacer member disposed about the core and located between the first and second segments; and d) an elastic structure surrounding the at least one spacer member, the elastic structure gripping at least the first segment, the spacer member being slidable along the inner core with the elastic structure being in a stretched orientation when one of the first and second segments moves away from the other of the first and second segments. 3. The improvement of claim 1 wherein the first segment has a first end plate and the elastic structure is molded about the first end plate.
| 0.614888 |
4. A method comprising: generating summary records that summarize full item records, the generating of the summary records being performed by a machine; receiving a request from a user and indicative of a geographic region; and presenting at least part of a full item record among the full item records based on the generated summary records that summarize the full item records and based on the geographic region in response to the received request.
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4. A method comprising: generating summary records that summarize full item records, the generating of the summary records being performed by a machine; receiving a request from a user and indicative of a geographic region; and presenting at least part of a full item record among the full item records based on the generated summary records that summarize the full item records and based on the geographic region in response to the received request. 12. The method of claim 4 further comprising: accessing a category list that corresponds to the geographic region indicated by the request and identifies a category to which the full item record belongs; and wherein the presenting of at least the part of the full item. record is based on the category list that corresponds to the geographic region,
| 0.6415 |
14. A system for controlling an event structure, the system comprising: a multiple-person interaction primitives recognizing unit to recognize multiple-person interaction primitives from an image, which is displayed on a display screen; and a multi-thread parser to compose an event by inference based on temporal relations using the multiple-person interaction primitives, and to determine a final event by eliminating an unnecessary event from the composed event and adding a new event in the composed event after the unnecessary event is eliminated.
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14. A system for controlling an event structure, the system comprising: a multiple-person interaction primitives recognizing unit to recognize multiple-person interaction primitives from an image, which is displayed on a display screen; and a multi-thread parser to compose an event by inference based on temporal relations using the multiple-person interaction primitives, and to determine a final event by eliminating an unnecessary event from the composed event and adding a new event in the composed event after the unnecessary event is eliminated. 15. The system of claim 14 , further comprising at least one of: a trajectory extracting unit to extract a trajectory of multiple persons; and an optical flow extracting unit to extract features related with behaviors of multiple persons based on a speed in which a pixel on the display screen displaying the person is moved to the next position within a predetermined period.
| 0.714451 |
5. The method of claim 1 wherein processing the feedback data to identify modifications to the converted clinician note data in the electronic medical record comprises: analyzing linguistics of the electronic medical record as modified to determine discrete contexts of portions of the electronic medical record; analyzing statistics associated with the medical record interpretation rules; and modifying the medical record interpretation rules in accordance with the linguistics and statistics analysis.
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5. The method of claim 1 wherein processing the feedback data to identify modifications to the converted clinician note data in the electronic medical record comprises: analyzing linguistics of the electronic medical record as modified to determine discrete contexts of portions of the electronic medical record; analyzing statistics associated with the medical record interpretation rules; and modifying the medical record interpretation rules in accordance with the linguistics and statistics analysis. 6. The method of claim 5 wherein analyzing statistics associated with the medical record interpretation rules comprises: identifying variables that affect one or more of the medical record interpretation rules; and modifying the medical record interpretation rules so that processing of subsequent clinician note data has a higher probability of accuracy and completeness relative to a probability of accuracy and completeness in processing of previous clinician note data.
| 0.870492 |
3. An interactive control apparatus that can interact with a plurality of interactive agents, comprising: a computer; an input portion that interprets input information input by a user, based on a recognition lexicon that has been generated in advance; a recognition lexicon generation portion that obtains terms accepted by interactive agents from a group of interactive agents performing a response to a result of said interpretation, regenerates the recognition lexicon by consolidating the accepted terms of each of the interactive agents by excluding duplicate terms from the accepted terms of the interactive agents, generates consolidated and reorganized information associating identifiers of two or more conflicting interactive agents, which accept duplicate terms among the accepted terms of the interactive agents, with those terms, and performs, for each interaction, the obtaining of the accepted terms of the interactive agents, performs as well as the generation of the recognized lexicon and the consolidated and reorganized information; an input interpretation portion for selecting one of the interactive agents and assigning the input information to the selected interactive agent, when the input portion interprets a word which exists only in the recognition lexicon and assigning the interpreted result of the input information to an interactive agent corresponding to any of the identifiers of the conflicting interactive agents associated with the input information based upon an importance given to each interactive agent, an importance given to the duplicate term, usage frequency of each interactive agent based upon historical data, and the most recent interactive agent associated with the duplicate term, when the interpreted information input is included in the consolidated and reorganized information; and a response output generation portion that obtains from the selected interactive agent or the interactive agent corresponding to any of the identifiers of the conflicting interactive agents associated with the input information a response corresponding to the interpretation result of the input information, and generates response output data, wherein the recognition lexicon generation portion generates the recognition lexicon by selecting the accepted terms within a range that does not exceed a predetermined upper limit for the number of terms constituting the recognition lexicon.
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3. An interactive control apparatus that can interact with a plurality of interactive agents, comprising: a computer; an input portion that interprets input information input by a user, based on a recognition lexicon that has been generated in advance; a recognition lexicon generation portion that obtains terms accepted by interactive agents from a group of interactive agents performing a response to a result of said interpretation, regenerates the recognition lexicon by consolidating the accepted terms of each of the interactive agents by excluding duplicate terms from the accepted terms of the interactive agents, generates consolidated and reorganized information associating identifiers of two or more conflicting interactive agents, which accept duplicate terms among the accepted terms of the interactive agents, with those terms, and performs, for each interaction, the obtaining of the accepted terms of the interactive agents, performs as well as the generation of the recognized lexicon and the consolidated and reorganized information; an input interpretation portion for selecting one of the interactive agents and assigning the input information to the selected interactive agent, when the input portion interprets a word which exists only in the recognition lexicon and assigning the interpreted result of the input information to an interactive agent corresponding to any of the identifiers of the conflicting interactive agents associated with the input information based upon an importance given to each interactive agent, an importance given to the duplicate term, usage frequency of each interactive agent based upon historical data, and the most recent interactive agent associated with the duplicate term, when the interpreted information input is included in the consolidated and reorganized information; and a response output generation portion that obtains from the selected interactive agent or the interactive agent corresponding to any of the identifiers of the conflicting interactive agents associated with the input information a response corresponding to the interpretation result of the input information, and generates response output data, wherein the recognition lexicon generation portion generates the recognition lexicon by selecting the accepted terms within a range that does not exceed a predetermined upper limit for the number of terms constituting the recognition lexicon. 4. The interactive control apparatus according to claim 3 , wherein the recognition lexicon generation portion further obtains importances of the accepted terms from the interactive agents, and generates the recognition lexicon by selecting the accepted terms based on these importances.
| 0.509002 |
1. A computer-implemented method for analyzing a collection of documents, comprising: (a) tokenizing one or more queries to generate an ordered sequence of query tokens for each query; (b) tokenizing one or more documents to generate an ordered sequence of document tokens for each document; (c) selecting an ordered sequence of document tokens from the tokenized one or more documents; (d) selecting an ordered sequence of query tokens from the tokenized one or more queries; (e) configuring a buffer to hold a subsequence of the selected ordered sequence of document tokens; (f) comparing the selected ordered sequence of query tokens to successive subsequences of the selected ordered sequence of document tokens in the configured buffer, wherein each of the successive subsequences and the selected ordered sequence of query tokens have the same length in tokens; (g) determining a match result based upon the comparison; and (h) updating one or more statistics based upon the determined match result, wherein the one or more statistics are stored in global memory, wherein the one or more statistics are updated asynchronously by two or more processes executing steps (a)-(g), and wherein each of the two or more processes steps (a)-(g) for at least one document and at least one query, including generating a first match result by the first process and a second match result by the second process, wherein the first match result and the second match result are combined as the determined match result.
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1. A computer-implemented method for analyzing a collection of documents, comprising: (a) tokenizing one or more queries to generate an ordered sequence of query tokens for each query; (b) tokenizing one or more documents to generate an ordered sequence of document tokens for each document; (c) selecting an ordered sequence of document tokens from the tokenized one or more documents; (d) selecting an ordered sequence of query tokens from the tokenized one or more queries; (e) configuring a buffer to hold a subsequence of the selected ordered sequence of document tokens; (f) comparing the selected ordered sequence of query tokens to successive subsequences of the selected ordered sequence of document tokens in the configured buffer, wherein each of the successive subsequences and the selected ordered sequence of query tokens have the same length in tokens; (g) determining a match result based upon the comparison; and (h) updating one or more statistics based upon the determined match result, wherein the one or more statistics are stored in global memory, wherein the one or more statistics are updated asynchronously by two or more processes executing steps (a)-(g), and wherein each of the two or more processes steps (a)-(g) for at least one document and at least one query, including generating a first match result by the first process and a second match result by the second process, wherein the first match result and the second match result are combined as the determined match result. 8. The computer-implemented method of claim 1 , wherein the first query and the second query are parts of a complex query, and wherein the combination of the first match result and the second match result represent a match result for the complex query.
| 0.663428 |
15. A computer-program product for composing a web page, comprising: a non-transitory computer readable storage medium storing one or more programs for execution by one or more processors on a server, the one or more programs comprising: instructions, which, when executed, transmit an authoring web page including an embedded authoring tool to a client computer of a publisher of the web page using a network, the authoring tool for composing the web page; and instructions, which, when executed, receive from the client computer web-page content corresponding to the composed web page, wherein the composed web page includes one or more advertisement regions that are placeholders designated for displaying one or more advertisements having one or more links to one or more content locations; wherein the composed web page is configured for display at run-time at respective clients of visitors who download the composed web page from a web page server; and wherein the one or more advertisement regions do not contain any of the web-page content.
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15. A computer-program product for composing a web page, comprising: a non-transitory computer readable storage medium storing one or more programs for execution by one or more processors on a server, the one or more programs comprising: instructions, which, when executed, transmit an authoring web page including an embedded authoring tool to a client computer of a publisher of the web page using a network, the authoring tool for composing the web page; and instructions, which, when executed, receive from the client computer web-page content corresponding to the composed web page, wherein the composed web page includes one or more advertisement regions that are placeholders designated for displaying one or more advertisements having one or more links to one or more content locations; wherein the composed web page is configured for display at run-time at respective clients of visitors who download the composed web page from a web page server; and wherein the one or more advertisement regions do not contain any of the web-page content. 19. The computer program product of claim 15 , wherein the authoring tool includes instructions, which, when executed, place one or more instances of predefined structured fields in the composed web page, and place field content within the one or more instances of the predefined structured fields.
| 0.5 |
15. A system to locate and deny theft of personal information in a computer network, the system comprising: a. a search engine bot arranged to scan and write to memory existing or newly uncovered locations where personal data are being traded in the computer network; b. a conversation bot interactive with the search engine bot and arranged to solicit a transaction of stolen personal information through a natural language human conversation enticement; c. a notification bot interactive with the search engine bot to provide notification of the existence of a stolen personal information provider discovered through the conversation bot; and d. a computer, wherein one or more of the search engine bot, the conversation bot and the notification bot are embodied in one or more computer programs stored in a computer readable medium and are executed by the computer, wherein the notification bot further includes means for informing or requesting electronically the assistance of one or more law enforcement agencies using networks, whether through a private notification system or a common public notification system.
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15. A system to locate and deny theft of personal information in a computer network, the system comprising: a. a search engine bot arranged to scan and write to memory existing or newly uncovered locations where personal data are being traded in the computer network; b. a conversation bot interactive with the search engine bot and arranged to solicit a transaction of stolen personal information through a natural language human conversation enticement; c. a notification bot interactive with the search engine bot to provide notification of the existence of a stolen personal information provider discovered through the conversation bot; and d. a computer, wherein one or more of the search engine bot, the conversation bot and the notification bot are embodied in one or more computer programs stored in a computer readable medium and are executed by the computer, wherein the notification bot further includes means for informing or requesting electronically the assistance of one or more law enforcement agencies using networks, whether through a private notification system or a common public notification system. 16. The system as claimed in claim 15 wherein the means for informing or requesting further includes one or more filters applied to generate, using preexisting forms of the one or more law enforcement agencies, automated notifications as though the user were typing data directly into such forms by screen scraping and automated keystrokes.
| 0.504779 |
1. A computer program product, comprising: a computer readable storage medium to store a computer readable program, wherein the computer readable program, when executed by a processor within a computer, causes the computer to perform operations for linguistical analytic consolidation, the operations comprising: displaying a user interface on a mobile device; receiving source text content to display in the user interface; scanning the source text content for a specific element; generating a mobility score for the source text content, wherein the mobility score describes a compatibility of the source text content for display on a device; and flagging the specific element of the source text content to be modified according to a set of linguistic rules, wherein modifying the specific element according to the set of linguistic rules results in a consolidated form of the source text content.
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1. A computer program product, comprising: a computer readable storage medium to store a computer readable program, wherein the computer readable program, when executed by a processor within a computer, causes the computer to perform operations for linguistical analytic consolidation, the operations comprising: displaying a user interface on a mobile device; receiving source text content to display in the user interface; scanning the source text content for a specific element; generating a mobility score for the source text content, wherein the mobility score describes a compatibility of the source text content for display on a device; and flagging the specific element of the source text content to be modified according to a set of linguistic rules, wherein modifying the specific element according to the set of linguistic rules results in a consolidated form of the source text content. 6. The computer program product of claim 1 , wherein the consolidated form of the source text content comprises fewer characters than the source text content.
| 0.715925 |
1. A computer system comprising: a repository having stored therein predefined data elements configured for use by a sender system in identifying information portions in electronic communications such that the information portions are automatically displayed and used by a receiver system to interpret contents of the electronic communications, each of the predefined data elements being associated with semantic information indicating its definition and intended use, the receiver system using the semantic information to display and interpret the electronic communications, wherein the data elements identify corresponding ones of the information portions according to the semantic information; and a modeling tool that, upon selection by a user, displays any of the predefined data elements for editing of the predefined data element and not of the information portions, the modeling tool presenting the semantic information for the selected data element, wherein an edited predefined data element is stored in the repository and accessed there by the receiver system.
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1. A computer system comprising: a repository having stored therein predefined data elements configured for use by a sender system in identifying information portions in electronic communications such that the information portions are automatically displayed and used by a receiver system to interpret contents of the electronic communications, each of the predefined data elements being associated with semantic information indicating its definition and intended use, the receiver system using the semantic information to display and interpret the electronic communications, wherein the data elements identify corresponding ones of the information portions according to the semantic information; and a modeling tool that, upon selection by a user, displays any of the predefined data elements for editing of the predefined data element and not of the information portions, the modeling tool presenting the semantic information for the selected data element, wherein an edited predefined data element is stored in the repository and accessed there by the receiver system. 8. The computer system of claim 1 , wherein the modeling tool is configured to present more than one physical representation of the selected data element.
| 0.615522 |
3. The method of claim 1 wherein extracting terms and establishing term correlations includes forming tuples of correlated terms.
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3. The method of claim 1 wherein extracting terms and establishing term correlations includes forming tuples of correlated terms. 4. The method of claim 3 wherein validating the term correlations includes calculating a frequency of occurrence of each of the tuples of correlated terms, and comparing the frequency of occurrence to a minimum frequency threshold.
| 0.952711 |
14. A computer program product for providing affinity data in a virtual universe (VU), comprising: a non-transitory computer readable medium storing signals for causing a digital data processor to perform the steps of: creating a first description of a VU objective entity, said first description comprising a plurality of descriptive elements, wherein said VU objective entity is a first inanimate object that is not an avatar; generating, from said first description, an affinity measure of the objective entity to a second inanimate object that is not an avatar, said second inanimate object having a second description comprising a further plurality of descriptive elements, said generating step including a comparison of said first description of said VU objective entity with said second description of said second inanimate object to find matches between said plurality of descriptive elements of said first description and said further plurality of descriptive elements of said second description; displaying the affinity measure to an owner of the second inanimate object, giving the owner an opportunity to determine a response as desired; and controlling operation of the second inanimate object based on the response by the owner of the second inanimate object VU subject to the displayed affinity measure in regard to the VU objective entity, wherein the affinity measure is a measure of similarity of descriptive elements and/or number of similar descriptive elements that are held in common by both the first description of the VU objective entity and the second description of the second inanimate object according to said matches found from said comparison, and wherein said displaying step displays said affinity measure as a compiled list of description elements which match for both the VU objective entity and the second inanimate object or as a metric describing an overall match between said plurality of descriptive elements of said first description and said further plurality of descriptive elements of said second description.
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14. A computer program product for providing affinity data in a virtual universe (VU), comprising: a non-transitory computer readable medium storing signals for causing a digital data processor to perform the steps of: creating a first description of a VU objective entity, said first description comprising a plurality of descriptive elements, wherein said VU objective entity is a first inanimate object that is not an avatar; generating, from said first description, an affinity measure of the objective entity to a second inanimate object that is not an avatar, said second inanimate object having a second description comprising a further plurality of descriptive elements, said generating step including a comparison of said first description of said VU objective entity with said second description of said second inanimate object to find matches between said plurality of descriptive elements of said first description and said further plurality of descriptive elements of said second description; displaying the affinity measure to an owner of the second inanimate object, giving the owner an opportunity to determine a response as desired; and controlling operation of the second inanimate object based on the response by the owner of the second inanimate object VU subject to the displayed affinity measure in regard to the VU objective entity, wherein the affinity measure is a measure of similarity of descriptive elements and/or number of similar descriptive elements that are held in common by both the first description of the VU objective entity and the second description of the second inanimate object according to said matches found from said comparison, and wherein said displaying step displays said affinity measure as a compiled list of description elements which match for both the VU objective entity and the second inanimate object or as a metric describing an overall match between said plurality of descriptive elements of said first description and said further plurality of descriptive elements of said second description. 15. The computer program product as recited in claim 14 , wherein the description creation step further comprises a combination of the steps of: gathering information about the VU objective entity from records maintained at a VU database; and accessing description information made available by the VU objective entity.
| 0.543611 |
27. A computer-implemented method of managing documents and records in a document repository of an institution having a defined organization, the method comprising: maintaining, using a computer, an electronically readable organization chart and organizational chart information including information identifying individuals on said organization chart; maintaining, using said computer, an electronic document repository containing accessible documents; controlling, using said computer, requested access to each document of said accessible documents in said electronic document repository; and mapping, using said computer, to said organization chart and said organizational chart information, each said requested access to said each document of said accessible documents; and displaying a document usage summary chart history, using said computer, based on historical tracking of actual usage and treatment of each document by individuals and groups within said organization chart.
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27. A computer-implemented method of managing documents and records in a document repository of an institution having a defined organization, the method comprising: maintaining, using a computer, an electronically readable organization chart and organizational chart information including information identifying individuals on said organization chart; maintaining, using said computer, an electronic document repository containing accessible documents; controlling, using said computer, requested access to each document of said accessible documents in said electronic document repository; and mapping, using said computer, to said organization chart and said organizational chart information, each said requested access to said each document of said accessible documents; and displaying a document usage summary chart history, using said computer, based on historical tracking of actual usage and treatment of each document by individuals and groups within said organization chart. 29. The method of claim 27 , wherein maintaining said electronic document repository includes adding and subtracting documents and editing documents and document metadata, using said computer.
| 0.561708 |
13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies a respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents.
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13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies a respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents. 17. The system claim 13 , wherein each training instance includes data representing a previously computed score for the selected first document.
| 0.690244 |
7. The system as in claim 6 wherein said query engine means includes means for testing the set of joins for multiple paths.
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7. The system as in claim 6 wherein said query engine means includes means for testing the set of joins for multiple paths. 8. The system as in claim 7 wherein said query engine means includes means for selecting between multiple paths.
| 0.980699 |
1. One or more computer-readable storage memories that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective or socially-derived information; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples in which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples in which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data.
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1. One or more computer-readable storage memories that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective or socially-derived information; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples in which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples in which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data. 6. The one or more computer-readable storage memories of claim 1 , said aspect of relevance being based on a determination that words in said query and an annotation of a person in said social graph are both associated with a concept in a concept graph.
| 0.73055 |
1. A system for predicting a lexical answer types (LAT) in a question comprising: a memory storage device including a plurality of syntactic frames; a processor device operatively connected to said memory storage device and configured to: receive a question text string; extract at least one syntactic frame from said question string, designate, in said syntactic frame, a placeholder for an entity corresponding to a potential lexical answer type; and query a lexical knowledge database to automatically obtain at least one replacement term for said placeholder of said at least one syntactic frame, wherein said entity placeholder is a part of a question focus indicating a LAT of the question.
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1. A system for predicting a lexical answer types (LAT) in a question comprising: a memory storage device including a plurality of syntactic frames; a processor device operatively connected to said memory storage device and configured to: receive a question text string; extract at least one syntactic frame from said question string, designate, in said syntactic frame, a placeholder for an entity corresponding to a potential lexical answer type; and query a lexical knowledge database to automatically obtain at least one replacement term for said placeholder of said at least one syntactic frame, wherein said entity placeholder is a part of a question focus indicating a LAT of the question. 3. The system as claimed in claim 1 , wherein said processor device is further configured to: substitute at least one of said replacement terms with a generalized type information term using a database of entity type knowledge.
| 0.63886 |
1. A method for displaying search results comprising: performing a search to identify results related to a seed term; displaying the results in a graphical representation, the graphical representation having a set of branches, each of the set of branches corresponding to a particular information source from which the results were obtained; and arranging the results along the set of branches in an order of relevance to the seed term.
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1. A method for displaying search results comprising: performing a search to identify results related to a seed term; displaying the results in a graphical representation, the graphical representation having a set of branches, each of the set of branches corresponding to a particular information source from which the results were obtained; and arranging the results along the set of branches in an order of relevance to the seed term. 7. The method of claim 1 , further comprising: receiving a selection of one of the results arranged along one of the set of branches; and displaying a new graphical representation based on the selection, the new graphical representation having results related to a search performed based on the selection, the results being arranged along a new set of branches of the new graphical representation.
| 0.633576 |
18. The method of claim 1 , further comprising: allowing the user to incorporate a photo in the selected stationery/card design.
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18. The method of claim 1 , further comprising: allowing the user to incorporate a photo in the selected stationery/card design. 19. The method of claim 18 , further comprising: allowing the user to select a photo stored on the wireless device, from a cloud image storage, from a web-based image storage, or from a social network.
| 0.946476 |
6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining a plurality of sequences of item identifiers indicating a history of items accessed; randomizing an order of item identifiers included in at least a portion of the plurality of sequences of item identifiers to generate a randomized plurality of sequences of item identifiers; generating a language model using the randomized plurality of sequences of item identifiers as the words of the language modeled by the language model, the language model configured to provide one or more candidate predictions for items of a processing target; receiving a request from an access device of a processing target, the request including information indicative of items for the processing target; generating a candidate prediction for the processing target using the language model and the items for the processing target; and providing a prediction for the processing target using the candidate prediction.
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6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining a plurality of sequences of item identifiers indicating a history of items accessed; randomizing an order of item identifiers included in at least a portion of the plurality of sequences of item identifiers to generate a randomized plurality of sequences of item identifiers; generating a language model using the randomized plurality of sequences of item identifiers as the words of the language modeled by the language model, the language model configured to provide one or more candidate predictions for items of a processing target; receiving a request from an access device of a processing target, the request including information indicative of items for the processing target; generating a candidate prediction for the processing target using the language model and the items for the processing target; and providing a prediction for the processing target using the candidate prediction. 7. The computer-implemented method of claim 6 , wherein the language model comprises a recurrent neural network language model.
| 0.780913 |
1. An image processing apparatus comprising: an image data input portion that inputs image data; a text data input portion that inputs text data; a voice data converter that converts into voice data, the text data inputted by the text data input portion; a connector that connects to each other, the voice data obtained by the voice data converter and the image data inputted by the image data input portion; a file creator that creates a file including the image data and the voice data connected to each other by the connector; the image data input portion and the text data input portion correspond to a reader that reads out image data by scanning a document; the voice data converter converts into voice data, text data extracted from the image data read out from the document by the reader; the connector connects to each other, the obtained voice data and the image data appropriate for the voice data; the text data converted into voice data is extracted from the image data read out from one side of the document; and the voice data into which the text data is converted is connected to the image data read out from the other side of the document.
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1. An image processing apparatus comprising: an image data input portion that inputs image data; a text data input portion that inputs text data; a voice data converter that converts into voice data, the text data inputted by the text data input portion; a connector that connects to each other, the voice data obtained by the voice data converter and the image data inputted by the image data input portion; a file creator that creates a file including the image data and the voice data connected to each other by the connector; the image data input portion and the text data input portion correspond to a reader that reads out image data by scanning a document; the voice data converter converts into voice data, text data extracted from the image data read out from the document by the reader; the connector connects to each other, the obtained voice data and the image data appropriate for the voice data; the text data converted into voice data is extracted from the image data read out from one side of the document; and the voice data into which the text data is converted is connected to the image data read out from the other side of the document. 3. The image data processing apparatus recited in claim 1 , wherein: the image data is comprised of image data pieces read out from a plurality of pages, and voice data pieces about the respective pages are connected to the image data pieces, and further comprising: an output portion that outputs the image data pieces to a display apparatus and outputs the voice data pieces to a speech output apparatus, and wherein: the output portion starts outputting to the speech output apparatus a voice data piece connected to an image data piece read out from one page, based on the output of the image data piece to the display apparatus, and the output portion starts outputting to the display apparatus an image data piece read out from a following page, based on the detection of a predetermined partition of the voice data piece.
| 0.5 |
1. A computer-implemented data delivery system, comprising: a tagging component for adding a user to a social graph for a recipient and tagging the added user with a social relationship tag according to a type of social relationship as defined by a category in the social graph, the social graph comprising an entry for each added user, each entry comprising a link to the added user and at least one social relationship tag; an import component for importing information related to the tagged user from external sources to augment the social graph, the import component comprising a contact aggregation provider to access the external sources using delegated authentication codes or password authorization; a data component for handling data, received from the tagged user, based on the social graph, the data including messages; a perimeter component for accessing the social graph from a perimeter and controlling delivery of the messages at the perimeter of an email deployment, the perimeter component to block, at the perimeter, messages from users tagged as blocked in the social graph from passing to internal message servers; and a processor implementing one or more of the tagging component, the data component, or the perimeter component.
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1. A computer-implemented data delivery system, comprising: a tagging component for adding a user to a social graph for a recipient and tagging the added user with a social relationship tag according to a type of social relationship as defined by a category in the social graph, the social graph comprising an entry for each added user, each entry comprising a link to the added user and at least one social relationship tag; an import component for importing information related to the tagged user from external sources to augment the social graph, the import component comprising a contact aggregation provider to access the external sources using delegated authentication codes or password authorization; a data component for handling data, received from the tagged user, based on the social graph, the data including messages; a perimeter component for accessing the social graph from a perimeter and controlling delivery of the messages at the perimeter of an email deployment, the perimeter component to block, at the perimeter, messages from users tagged as blocked in the social graph from passing to internal message servers; and a processor implementing one or more of the tagging component, the data component, or the perimeter component. 6. The system of claim 1 , further comprising a policy component for applying a generic action to multiple tagged users based on the social graph.
| 0.601652 |
6. The method of claim 1 , further comprising storing in a first portion of the memory at least a portion of the recipients of the number of recipients of the second message.
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6. The method of claim 1 , further comprising storing in a first portion of the memory at least a portion of the recipients of the number of recipients of the second message. 7. The method of claim 6 , further comprising seeking in the first portion of the memory said recipient that corresponds with the ambiguous input.
| 0.962798 |
1. A method, in a data processing system comprising a processor and a memory configured to implement a question and answer (QA) system, for effectively ingesting data for answering questions in the QA system, the method comprising: parsing, by a processor in the QA system, a received input question having a set of question characteristics; comparing, by the processor, the set of question characteristics found in the received input question to question characteristics associated with a set of previous questions; responsive to the set of question characteristics found in the received input question matching the question characteristics associated with one or more previous questions in the set of previous questions above a related-question predetermined threshold, identifying, by the processor, whether answers to the one or more previous questions were obtained from static information sources or real-time information sources; and responsive to the answers to the one or more previous questions being obtained from the real-time information sources above the predetermined real-time threshold, initially utilizing, by the processor, real-time information sources related to the characteristics of the input question to answer the input question.
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1. A method, in a data processing system comprising a processor and a memory configured to implement a question and answer (QA) system, for effectively ingesting data for answering questions in the QA system, the method comprising: parsing, by a processor in the QA system, a received input question having a set of question characteristics; comparing, by the processor, the set of question characteristics found in the received input question to question characteristics associated with a set of previous questions; responsive to the set of question characteristics found in the received input question matching the question characteristics associated with one or more previous questions in the set of previous questions above a related-question predetermined threshold, identifying, by the processor, whether answers to the one or more previous questions were obtained from static information sources or real-time information sources; and responsive to the answers to the one or more previous questions being obtained from the real-time information sources above the predetermined real-time threshold, initially utilizing, by the processor, real-time information sources related to the characteristics of the input question to answer the input question. 2. The method of claim 1 , further comprising: responsive to the answers to the one or more previous questions failing to be obtained from the real-time information sources above the predetermined real-time threshold and responsive to the answers to the one or more previous questions being obtained from the static information sources above a predetermined static threshold, initially utilizing, by the processor, static information sources related to the characteristics of the input question to answer the input question.
| 0.53543 |
1. A method of generating testcases, comprising: receiving, at a data processing system, a new product specification for an application; performing, by the data processing system, a new noun-verb pairing on the new product specification; attempting to locate, by the data processing system, a similar noun-verb pairing, corresponding to the new noun-verb pairing, in a previous product specification for the application; in response to locating the similar noun-verb pairing in the previous product specification, generating, by the data processing system, a new testcase by modifying a previous testcase that is associated with the similar noun-verb pairing in the previous product specification; in response to not locating the similar noun-verb pairing in the previous product specification, indicating, by the data processing system, that the new testcase was not generated; loading, by the data processing system, the previous product specification and the previous testcase; performing, by the data processing system, natural language processing on the previous product specification to identify the similar noun-verb pairing in the previous product specification; matching, by the data processing system, the similar noun-verb pairing with the previous testcase; and training, by the data processing system, a classifier using the similar noun-verb pairing and the previous testcase.
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1. A method of generating testcases, comprising: receiving, at a data processing system, a new product specification for an application; performing, by the data processing system, a new noun-verb pairing on the new product specification; attempting to locate, by the data processing system, a similar noun-verb pairing, corresponding to the new noun-verb pairing, in a previous product specification for the application; in response to locating the similar noun-verb pairing in the previous product specification, generating, by the data processing system, a new testcase by modifying a previous testcase that is associated with the similar noun-verb pairing in the previous product specification; in response to not locating the similar noun-verb pairing in the previous product specification, indicating, by the data processing system, that the new testcase was not generated; loading, by the data processing system, the previous product specification and the previous testcase; performing, by the data processing system, natural language processing on the previous product specification to identify the similar noun-verb pairing in the previous product specification; matching, by the data processing system, the similar noun-verb pairing with the previous testcase; and training, by the data processing system, a classifier using the similar noun-verb pairing and the previous testcase. 4. The method of claim 1 , wherein the new testcase corresponds to automated test code for a graphical user interface (GUI) element of the application.
| 0.54494 |
1. A non-transitory computer readable medium storing computer-executable instructions for performing a method of processing an electronic document, the method comprising: providing a first post-design editing session of a first instance of a document, wherein the document is complete; during the post-design editing session, iteratively triggering transformation of the document, to produce a second instance of the document, via user interaction within a displayable interview pane that is superimposed over or juxtaposed with the document, the interview pane including multiple, separate user-interaction components arranged to provide variability in the strict content of the document, the user-interaction components including: a guided-fill component configured to guide users to enter text into data fields, with the entered text becoming part of the second instance of the document or triggering inclusion of additional content in the second instance of the document; a free-form text component configured to permit users to enter text in free-form in portions of the document, including permission to add free-form text as new portions of the document; and an interview component configured to prompt queries to the user, wherein answers to the queries determine at least one format parameter and at least one content parameter, and wherein the user is permitted to vary the strict content of the document via directly adding or removing text in free-form in the document while the interview pane is an active state and simultaneously displayed with the document; and controlling, as a function of user characteristics including at least one of an identity, a title, or a role, user access to predetermined content of the interactive document and user access regarding which, if any, of the respective displayable user-interaction components within the interview pane associated with the first instance of the document are accessible by a user.
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1. A non-transitory computer readable medium storing computer-executable instructions for performing a method of processing an electronic document, the method comprising: providing a first post-design editing session of a first instance of a document, wherein the document is complete; during the post-design editing session, iteratively triggering transformation of the document, to produce a second instance of the document, via user interaction within a displayable interview pane that is superimposed over or juxtaposed with the document, the interview pane including multiple, separate user-interaction components arranged to provide variability in the strict content of the document, the user-interaction components including: a guided-fill component configured to guide users to enter text into data fields, with the entered text becoming part of the second instance of the document or triggering inclusion of additional content in the second instance of the document; a free-form text component configured to permit users to enter text in free-form in portions of the document, including permission to add free-form text as new portions of the document; and an interview component configured to prompt queries to the user, wherein answers to the queries determine at least one format parameter and at least one content parameter, and wherein the user is permitted to vary the strict content of the document via directly adding or removing text in free-form in the document while the interview pane is an active state and simultaneously displayed with the document; and controlling, as a function of user characteristics including at least one of an identity, a title, or a role, user access to predetermined content of the interactive document and user access regarding which, if any, of the respective displayable user-interaction components within the interview pane associated with the first instance of the document are accessible by a user. 4. The computer readable medium of claim 1 , wherein providing the first post-design editing session of the first instance of an electronic document comprises providing the first instance of the electronic document via: encapsulating operative components in a predetermined electronic file format, the format including a compressed (zip) portion for storing predetermined portions of selected operative components, the operative components supporting at least: the iterative transformation of the document via user interaction within the displayable interview pane superimposed over or juxtaposed with the first instance of the document; and the controlling of user access to predetermined content of the document and user access regarding the respective displayable user-interaction components within the interview pane.
| 0.5 |
54. The server of claim 48 , wherein said server applies a function g to {Q, A, I(Q), C, A(C), S} to assign said score, wherein Q is an initial set of questions, A comprises corresponding answers to said initial set of questions, I(Q) is the encoded information, C is a set of challenge questions, A(C) comprises corresponding answers to C, and S comprises additional state information.
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54. The server of claim 48 , wherein said server applies a function g to {Q, A, I(Q), C, A(C), S} to assign said score, wherein Q is an initial set of questions, A comprises corresponding answers to said initial set of questions, I(Q) is the encoded information, C is a set of challenge questions, A(C) comprises corresponding answers to C, and S comprises additional state information. 55. The server of claim 54 , wherein said function g is a probabilistic function.
| 0.864951 |
9. The method of claim 6 further comprising access means to said first and second tables.
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9. The method of claim 6 further comprising access means to said first and second tables. 11. The method of claim 9 wherein said access means providing an insert operation.
| 0.967879 |
9. The system of claim 8 wherein the at least one of the first aerial drone device and the second aerial drone device is configured to locate a person based on where the breach occurred and by detecting the person, using a camera of the at least one of the first aerial drone device and the second aerial drone device and object recognition.
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9. The system of claim 8 wherein the at least one of the first aerial drone device and the second aerial drone device is configured to locate a person based on where the breach occurred and by detecting the person, using a camera of the at least one of the first aerial drone device and the second aerial drone device and object recognition. 11. The system of claim 9 wherein the at least one of the first aerial drone device and the second aerial drone device is configured to track the person and transmit tracking location information to the security system or another device, wherein the at least one of the first aerial drone device and the second aerial drone device is configured to track the person by acquiring image data of the person and maintaining the image data of the person within a view of the camera of the at least one of the first aerial drone device and the second aerial drone device, and the at least one of the first aerial drone device and the second aerial drone device is configured to locate evidence or vehicle information using the database of template targets.
| 0.671524 |
1. A computer-implemented method of collecting first and second DNA profile data using first and second different DNA typing technologies about an unidentified remain and first and second DNA profile data of the same first and second DNA typing technologies of each of a selected first and a selected second family member genetically related to a hypothesized identity of the unidentified remain and the first and the second family members being selected via application of a family member selection rule base considering available members of the family for DNA typing, the family member data including first and second DNA profile data obtained from a specimen associated with a selected typed family member and a genetic relationship existing among each of the first and the second selected family member and the hypothesized identity of the unidentified remain, the method for determining one of a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the selected first and second typed family member and that the unidentified remain can be excluded as not consistent with the first and the second selected typed family member, the method for implementation on telecommunications computer apparatus comprising a processor, an input device coupled to the processor comprising one of a touch screen of a display, a camera, a keyboard and a bar code reader for reading one and two dimension bar codes, an output device coupled to the processor comprising a display, a telecommunications interface coupled to the processor, and a memory for storing the first and the second DNA profile data obtained from said unidentified remain and said first and said second DNA profile data obtained from each specimen of said first selected and said second selected typed family member, the memory coupled to the processor, the computer-implemented method comprising: (a) storing the first and the second DNA profile data obtained from typing said unidentified remain using the first and the second DNA typing technologies in said memory via said bar code reader input device for reading a one dimension bar code uniquely identifying the unidentified remain and two different associated two dimension bar codes for transformation to the first and the second DNA profile data of the two different typing technologies for the unidentified remain; (b) storing a genetic relationship in said memory among said hypothesized identity of said unidentified remain of said missing person and each of said first and said second selected family member and family member and hypothesized identity identification data input via said input device; (c) storing said first and said second DNA profile data of each of the first and the second selected family member in said memory, each of the first and the second selected family members uniquely identified by a one dimension bar code and their associated first and second DNA profile data represented by two different two dimension bar codes being uniquely transformable into first and second DNA profile data of the first and the second DNA typing technologies, said first and said second DNA profile data obtained from the specimen associated with each of the first and the second selected typed family member and storing said first and said second DNA profile data from the unidentified remain, said first and said second family member DNA profile data for each of said first and said second selected typed family member being identified with a different two-dimensional bar code representing the same first and second typing technologies used for typing the unidentified remain; (d) displaying a family pedigree representing genetic relationships among the first and the second family members and the hypothesized identity of the unidentified remain, the family pedigree displayed on said display, said family pedigree being responsive to input received by said input device, said input causing information about a selected family member to be displayed including the stored DNA profile data associated with the selected family member, an identity being input by the input device and at least one of a first and a second type of collected DNA profile data each indicated by a predetermined color, each type comprising one of STR, Y-STR and mitochondrial DNA, at least one DNA typing technology comprising STR; (e) evaluating the genetic consistency of said stored genetic relationship by computing a pedigree likelihood ratio for each of said stored first and said second DNA typing technologies using said DNA profile data of each of said selected typed family member with said first and said second DNA profile data of said unidentified remain and a joint likelihood ratio computed as the product of the pedigree likelihood ratios; and (f) using the computed joint likelihood ratio to output a decision whether said stored genetic relationship and said stored first and said second DNA profile data obtained from the specimen associated with the first and second selected typed family member and said unidentified remain are consistent and outputting a decision of whether there exists one of said genetic relationship among the first and second family members and the hypothesized identity of the unidentified remain and exclusion of said genetic relationship among the first and second family members and the unidentified remain, including computing of the pedigree likelihood ratio according to evaluating the genetic consistency using a modified Elston Stewart algorithm for determining a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the typed first and second second family member or can be excluded as not consistent with the typed first and second selected available family member, the modification expressing a probability of mutation.
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1. A computer-implemented method of collecting first and second DNA profile data using first and second different DNA typing technologies about an unidentified remain and first and second DNA profile data of the same first and second DNA typing technologies of each of a selected first and a selected second family member genetically related to a hypothesized identity of the unidentified remain and the first and the second family members being selected via application of a family member selection rule base considering available members of the family for DNA typing, the family member data including first and second DNA profile data obtained from a specimen associated with a selected typed family member and a genetic relationship existing among each of the first and the second selected family member and the hypothesized identity of the unidentified remain, the method for determining one of a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the selected first and second typed family member and that the unidentified remain can be excluded as not consistent with the first and the second selected typed family member, the method for implementation on telecommunications computer apparatus comprising a processor, an input device coupled to the processor comprising one of a touch screen of a display, a camera, a keyboard and a bar code reader for reading one and two dimension bar codes, an output device coupled to the processor comprising a display, a telecommunications interface coupled to the processor, and a memory for storing the first and the second DNA profile data obtained from said unidentified remain and said first and said second DNA profile data obtained from each specimen of said first selected and said second selected typed family member, the memory coupled to the processor, the computer-implemented method comprising: (a) storing the first and the second DNA profile data obtained from typing said unidentified remain using the first and the second DNA typing technologies in said memory via said bar code reader input device for reading a one dimension bar code uniquely identifying the unidentified remain and two different associated two dimension bar codes for transformation to the first and the second DNA profile data of the two different typing technologies for the unidentified remain; (b) storing a genetic relationship in said memory among said hypothesized identity of said unidentified remain of said missing person and each of said first and said second selected family member and family member and hypothesized identity identification data input via said input device; (c) storing said first and said second DNA profile data of each of the first and the second selected family member in said memory, each of the first and the second selected family members uniquely identified by a one dimension bar code and their associated first and second DNA profile data represented by two different two dimension bar codes being uniquely transformable into first and second DNA profile data of the first and the second DNA typing technologies, said first and said second DNA profile data obtained from the specimen associated with each of the first and the second selected typed family member and storing said first and said second DNA profile data from the unidentified remain, said first and said second family member DNA profile data for each of said first and said second selected typed family member being identified with a different two-dimensional bar code representing the same first and second typing technologies used for typing the unidentified remain; (d) displaying a family pedigree representing genetic relationships among the first and the second family members and the hypothesized identity of the unidentified remain, the family pedigree displayed on said display, said family pedigree being responsive to input received by said input device, said input causing information about a selected family member to be displayed including the stored DNA profile data associated with the selected family member, an identity being input by the input device and at least one of a first and a second type of collected DNA profile data each indicated by a predetermined color, each type comprising one of STR, Y-STR and mitochondrial DNA, at least one DNA typing technology comprising STR; (e) evaluating the genetic consistency of said stored genetic relationship by computing a pedigree likelihood ratio for each of said stored first and said second DNA typing technologies using said DNA profile data of each of said selected typed family member with said first and said second DNA profile data of said unidentified remain and a joint likelihood ratio computed as the product of the pedigree likelihood ratios; and (f) using the computed joint likelihood ratio to output a decision whether said stored genetic relationship and said stored first and said second DNA profile data obtained from the specimen associated with the first and second selected typed family member and said unidentified remain are consistent and outputting a decision of whether there exists one of said genetic relationship among the first and second family members and the hypothesized identity of the unidentified remain and exclusion of said genetic relationship among the first and second family members and the unidentified remain, including computing of the pedigree likelihood ratio according to evaluating the genetic consistency using a modified Elston Stewart algorithm for determining a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the typed first and second second family member or can be excluded as not consistent with the typed first and second selected available family member, the modification expressing a probability of mutation. 10. The method of claim 1 further comprising outputting a decision whether it is possible that said typed unknown biological specimen originated from or can be excluded as originating from said missing person of the pedigree.
| 0.533448 |
13. A computer-readable storage device having instructions stored which, when executed on a computing device, cause the computing device to perform operations comprising: identifying, via a processor, a first segment of a dialog turn associated with soliciting a first probable user response as part of a dialog with a dialog system; identifying, via the processor, a second segment of the dialog turn associated with soliciting a second probable user response, wherein the first segment and the second segment are further identified based on a first timing of the first probable user response and a second timing of the second probable user response; activating a first weighted grammar for the first segment of the dialog for processing speech received during the first segment, to yield a first activated weighted grammar, wherein the first weighted grammar is weighted based on a user profile which consists of information about a number called from, demographic information, account information, a time of day, and a date; activating a second weighted grammar for the second segment of the dialog for processing speech received during the second segment, to yield a second activated weighted grammar; recognizing user speech received during the first segment of the dialog using the first activated weighted grammar; and recognizing user speech received during the second segment of the dialog using the second activated weighted grammar.
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13. A computer-readable storage device having instructions stored which, when executed on a computing device, cause the computing device to perform operations comprising: identifying, via a processor, a first segment of a dialog turn associated with soliciting a first probable user response as part of a dialog with a dialog system; identifying, via the processor, a second segment of the dialog turn associated with soliciting a second probable user response, wherein the first segment and the second segment are further identified based on a first timing of the first probable user response and a second timing of the second probable user response; activating a first weighted grammar for the first segment of the dialog for processing speech received during the first segment, to yield a first activated weighted grammar, wherein the first weighted grammar is weighted based on a user profile which consists of information about a number called from, demographic information, account information, a time of day, and a date; activating a second weighted grammar for the second segment of the dialog for processing speech received during the second segment, to yield a second activated weighted grammar; recognizing user speech received during the first segment of the dialog using the first activated weighted grammar; and recognizing user speech received during the second segment of the dialog using the second activated weighted grammar. 14. The computer-readable storage device of claim 13 , having additional instructions stored which, when executed by the computing device, result in operations comprising assigning a first probability to the first weighted grammar and a second probability to the second weighted grammar based on historical user responses and activating the first weighted grammar based on the first probability and activating the second weighted grammar based on the second probability.
| 0.534226 |
2. The method of claim 1 , wherein the first nonextensible schema and first extensible schema are referenced in a commerce XML (cXML) document.
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2. The method of claim 1 , wherein the first nonextensible schema and first extensible schema are referenced in a commerce XML (cXML) document. 3. The method of claim 2 , wherein the first nonextensible schema comprises a document type definition (DTD).
| 0.959368 |
26. The system of claim 25 , wherein the text string is generated based on metadata associated with or identifying a media asset.
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26. The system of claim 25 , wherein the text string is generated based on metadata associated with or identifying a media asset. 29. The system of claim 26 , wherein the text string includes one or more fields of information extracted the metadata and omits at least one field of information available in the metadata.
| 0.895425 |
1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain a sequence of feature vectors, wherein the sequence of feature vectors represents at least a portion of a stream of audio data; generate a keyword score based at least partly on a likelihood that a particular feature vector of the sequence of feature vectors represents audio data corresponding to a keyword; generate a background score based at least partly on a likelihood that the particular feature vector represents audio data corresponding to background audio; determine that a difference between the keyword score and the background score is greater than differences associated with feature vectors preceding the particular feature vector in a subset of the sequence of feature vectors, wherein the particular feature vector is in a center of the subset; determine that the difference is greater than differences associated with feature vectors subsequent to the particular feature vector in the subset; and generate data indicating the particular feature vector corresponds to an end of the keyword.
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1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain a sequence of feature vectors, wherein the sequence of feature vectors represents at least a portion of a stream of audio data; generate a keyword score based at least partly on a likelihood that a particular feature vector of the sequence of feature vectors represents audio data corresponding to a keyword; generate a background score based at least partly on a likelihood that the particular feature vector represents audio data corresponding to background audio; determine that a difference between the keyword score and the background score is greater than differences associated with feature vectors preceding the particular feature vector in a subset of the sequence of feature vectors, wherein the particular feature vector is in a center of the subset; determine that the difference is greater than differences associated with feature vectors subsequent to the particular feature vector in the subset; and generate data indicating the particular feature vector corresponds to an end of the keyword. 3. The system of claim 1 , wherein the one or more processors are further programmed by the executable instructions to at least determine a size of the subset based at least partly on an expected length of time for the keyword to be uttered.
| 0.561047 |
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