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8,559,695 | 3 | 4 |
3. The method of claim 1 , wherein the detecting includes detecting a plurality of find bills.
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3. The method of claim 1 , wherein the detecting includes detecting a plurality of find bills. 4. The method of claim 3 , further comprising automatically stopping the transporting of the U.S. currency bills such that a first one of the plurality of detected find bills is the last U.S. currency bill transported to the one or more output receptacles.
| 0.661376 |
9,760,260 | 6 | 8 |
6. A computer program product for modifying a set of annotations that include metadata describing properties of associated text fragments within an annotated text corpus, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer processing circuit to cause the circuit to perform the method comprising: receiving a query specifying parameters for annotations from the set of the annotations; extracting, from the set of annotations and by the query, a first entity subset of annotations, a second entity subset of annotations, and a relations subset of annotations between the first entity subset of annotations and the second entity subset of annotations, wherein each annotation in the first and second entity subset of annotations serves as an anchor for each respective relations subset annotation and each piece of contextual information; extracting, from the annotated text corpus, contextual information relative to the extracted annotations; generating a user interface having display frames populated by frame elements that include the entity subsets of annotations, the relations subset of annotations, and the contextual information; receiving, responsive to selections of the frame elements, input specifying modifications to the annotations; modifying, based on the input specifying modifications to the annotations, the set of annotations in the annotated text corpus; receiving additional input specifying a change to the particular annotation label; receiving additional input specifying a subset of the plurality of annotations; and modifying, based on the additional input, the particular annotation label for each of the annotations in the subset of the plurality of annotations having the shared particular annotation label.
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6. A computer program product for modifying a set of annotations that include metadata describing properties of associated text fragments within an annotated text corpus, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer processing circuit to cause the circuit to perform the method comprising: receiving a query specifying parameters for annotations from the set of the annotations; extracting, from the set of annotations and by the query, a first entity subset of annotations, a second entity subset of annotations, and a relations subset of annotations between the first entity subset of annotations and the second entity subset of annotations, wherein each annotation in the first and second entity subset of annotations serves as an anchor for each respective relations subset annotation and each piece of contextual information; extracting, from the annotated text corpus, contextual information relative to the extracted annotations; generating a user interface having display frames populated by frame elements that include the entity subsets of annotations, the relations subset of annotations, and the contextual information; receiving, responsive to selections of the frame elements, input specifying modifications to the annotations; modifying, based on the input specifying modifications to the annotations, the set of annotations in the annotated text corpus; receiving additional input specifying a change to the particular annotation label; receiving additional input specifying a subset of the plurality of annotations; and modifying, based on the additional input, the particular annotation label for each of the annotations in the subset of the plurality of annotations having the shared particular annotation label. 8. The computer program product of claim 6 , wherein the extracting, from the set of annotations and by the query, further comprises: filtering, responsive to first entity parameters specified in the query, the set of annotations for the first entity subset of annotations; filtering, responsive to second entity parameters specified in the query, the set of annotations for the second entity subset of annotations; and filtering, responsive to parameters specified in the query, the set of annotations for the relations subset of annotations.
| 0.5 |
7,551,779 | 1 | 11 |
1. A computer-implemented method for intuitively applying scratch-out gestures in a computing device that comprises a handwriting surface component that receives electronic ink from a digitizer, as well as a component that provides boundary information corresponding to boundaries of words or characters and a scratch-out gesture detector coupled to the handwriting surface component and the component that provides the boundary information, wherein the scratch-out gesture detector also evaluates electronic ink received at the handwriting surface against criteria based on the boundary information to determine whether the electronic ink corresponds to any of a plurality of different acceptable scratch-out gesture types, the method comprising: the scratch-out gesture detector associating a plurality of different acceptable types of scratch-out gestures with a scratch-out gesture process that erases previously-entered ink; the computing device receiving user input corresponding to inking data entered via a digitizer at a handwriting surface component of the computing device; the scratch-out gesture detector evaluating the inking data based on boundary threshold data of at least one corresponding word or character displayed by the computing device to determine whether the user input is a scratch-out gesture corresponding to at least one of the plurality of different acceptable types of scratch-out gesture types and that would cause the scratch-out process to erase previously-entered ink; and wherein a) if the inking data is a scratch-out gesture, erasing previously-entered ink corresponding to the scratch-out gesture, as well as the inking data corresponding to the scratch-out gesture; and b) if the inking data is not a scratch-out gesture, processing the inking data as ink stroke data of at least part of a word or character.
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1. A computer-implemented method for intuitively applying scratch-out gestures in a computing device that comprises a handwriting surface component that receives electronic ink from a digitizer, as well as a component that provides boundary information corresponding to boundaries of words or characters and a scratch-out gesture detector coupled to the handwriting surface component and the component that provides the boundary information, wherein the scratch-out gesture detector also evaluates electronic ink received at the handwriting surface against criteria based on the boundary information to determine whether the electronic ink corresponds to any of a plurality of different acceptable scratch-out gesture types, the method comprising: the scratch-out gesture detector associating a plurality of different acceptable types of scratch-out gestures with a scratch-out gesture process that erases previously-entered ink; the computing device receiving user input corresponding to inking data entered via a digitizer at a handwriting surface component of the computing device; the scratch-out gesture detector evaluating the inking data based on boundary threshold data of at least one corresponding word or character displayed by the computing device to determine whether the user input is a scratch-out gesture corresponding to at least one of the plurality of different acceptable types of scratch-out gesture types and that would cause the scratch-out process to erase previously-entered ink; and wherein a) if the inking data is a scratch-out gesture, erasing previously-entered ink corresponding to the scratch-out gesture, as well as the inking data corresponding to the scratch-out gesture; and b) if the inking data is not a scratch-out gesture, processing the inking data as ink stroke data of at least part of a word or character. 11. The method of claim 1 wherein evaluating the inking data based on boundary threshold data comprises determining whether the gesture extends a threshold distance into the box.
| 0.85622 |
7,844,563 | 13 | 15 |
13. A system for screening incoming data of a network, comprising: means for determining a relationship between a plurality of existing rules in a rule set of a rule based system used to screen the incoming data of the network, wherein the relationship includes a cause interaction and an effect interaction among the existing rules; means for creating a representation of the relationship including the cause interaction and the effect interaction; means for receiving a new rule to be inserted into the rule set; means for inserting a further relationship between the new rule and the existing rules into the representation to create a modified representation; and means for determining, based on the modified representation, if a conflict is created by insertion of the new rule in the rule set.
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13. A system for screening incoming data of a network, comprising: means for determining a relationship between a plurality of existing rules in a rule set of a rule based system used to screen the incoming data of the network, wherein the relationship includes a cause interaction and an effect interaction among the existing rules; means for creating a representation of the relationship including the cause interaction and the effect interaction; means for receiving a new rule to be inserted into the rule set; means for inserting a further relationship between the new rule and the existing rules into the representation to create a modified representation; and means for determining, based on the modified representation, if a conflict is created by insertion of the new rule in the rule set. 15. The system of claim 13 , further comprising: means for adding the new rule to the rule set when the new rule can be added without conflict.
| 0.625654 |
8,332,391 | 10 | 11 |
10. A system comprising: one or more computers and one or more non-transitory computer-readable storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value.
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10. A system comprising: one or more computers and one or more non-transitory computer-readable storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value. 11. The system of claim 10 , wherein determining a second quantity of search results comprises determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more terms, and in which two or more of the terms appear non-consecutively.
| 0.5 |
8,392,187 | 8 | 14 |
8. A speech recognition system comprising: a microphone configured to receive a speech signal; a frame constructor configured to create a plurality of frames from the speech signal; a feature extractor configured to produced feature vectors from the frames; and a decoder configured to: expand a search network based on a frame; determine a best hypothesis in the search network; modify a default beam threshold to produce a modified beam threshold, wherein modifying a default beam threshold further comprises modifying the default beam threshold based on at least one selected from a group consisting of: a time the frame is received, a speed with which the search network is increasing in size, and a number of active phones, wherein the default beam threshold is increased by an empirically determined amount if an acceleration of the speed with which the search network is increasing in size for the frame exceeds an empirically determined amount; and prune the search network using the modified beam threshold and the best hypothesis.
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8. A speech recognition system comprising: a microphone configured to receive a speech signal; a frame constructor configured to create a plurality of frames from the speech signal; a feature extractor configured to produced feature vectors from the frames; and a decoder configured to: expand a search network based on a frame; determine a best hypothesis in the search network; modify a default beam threshold to produce a modified beam threshold, wherein modifying a default beam threshold further comprises modifying the default beam threshold based on at least one selected from a group consisting of: a time the frame is received, a speed with which the search network is increasing in size, and a number of active phones, wherein the default beam threshold is increased by an empirically determined amount if an acceleration of the speed with which the search network is increasing in size for the frame exceeds an empirically determined amount; and prune the search network using the modified beam threshold and the best hypothesis. 14. The speech recognition system of claim 8 , wherein the executable instructions further recognize speech by pruning the search network based on an empirically determined average number of frames per state for a search path.
| 0.5 |
9,256,587 | 22 | 23 |
22. The website editor of claim 20 , wherein the gallery webpage comprises a page for displaying media content.
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22. The website editor of claim 20 , wherein the gallery webpage comprises a page for displaying media content. 23. The website editor of claim 22 , wherein the gallery webpage comprises an option for one or more alternate views of the media content comprising one or more of a thumbnail view and a page view.
| 0.5 |
8,949,377 | 1 | 24 |
1. A computer-implemented method for managing a conversational system on a server, the method comprising: presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; and reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party.
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1. A computer-implemented method for managing a conversational system on a server, the method comprising: presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; and reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party. 24. The method of claim 1 , wherein the event to launch the chatbot includes minimizing a web page.
| 0.916102 |
9,524,650 | 14 | 15 |
14. The automated training system according to claim 13 , further comprising a text-to-speech system that converts the stored text files to respective audio files to be part of the execution of the training script.
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14. The automated training system according to claim 13 , further comprising a text-to-speech system that converts the stored text files to respective audio files to be part of the execution of the training script. 15. The automated training system according to claim 14 , wherein the generation of the scoring report is based on a scoring matrix including fields related to the determined number of words in the voice responses that were not understood, the comparison of the voice responses, the tone, and the comparison of the external system responses.
| 0.5 |
10,127,305 | 1 | 4 |
1. A method comprising: accessing, by one or more processors, a first profile of a first member of a social network, the first profile being accessed in response to an action that references at least part of the first profile; determining, by one or more of the processors, a similarity score that quantifies similarity between the first profile and a second profile of a second member of the social network; ranking, by one or more of the processors, the second profile of the second member based on the determined similarity score and based on an elapsed time since the action that references at least the part of the first profile; and presenting, by one or more of the processors, the second profile based on the ranking of the second profile.
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1. A method comprising: accessing, by one or more processors, a first profile of a first member of a social network, the first profile being accessed in response to an action that references at least part of the first profile; determining, by one or more of the processors, a similarity score that quantifies similarity between the first profile and a second profile of a second member of the social network; ranking, by one or more of the processors, the second profile of the second member based on the determined similarity score and based on an elapsed time since the action that references at least the part of the first profile; and presenting, by one or more of the processors, the second profile based on the ranking of the second profile. 4. The method of claim 1 , wherein: the action in response to which the first profile of the first number is accessed includes submission of an annotation that corresponds to the first profile; and the ranking of the second profile of the second member is based on the elapsed time since the submission of the annotation that corresponds to the first profile.
| 0.579625 |
8,321,199 | 61 | 78 |
61. A non-transitory computer readable medium comprising computer program instructions tangibly stored on the computer readable medium, wherein the computer program instructions are executable by at least one computer processor to perform a method, the method comprising: (A) identifying a document including a first coding having a first feature, the first coding being associated with a first code, the first code having first data; (B) rendering the first data on an output device based on the first feature; (C) receiving, via an input device, a first indication from a user of a verification status of the rendering; and (D) identifying, based on the verification status of the rendering, a verification status of the first feature, comprising: (D)(1) if the verification status of the rendering indicates that the rendering is accurate, then identifying a verification status of the first feature indicating that the first feature is accurate; and (D)(2) otherwise, identifying a verification status of the first feature indicating that the first feature is inaccurate; (E) identifying, based on the verification status of the first feature, a verification status of the first coding; and (F) storing, in a non-transitory computer-readable medium, a record of the verification status of the first coding.
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61. A non-transitory computer readable medium comprising computer program instructions tangibly stored on the computer readable medium, wherein the computer program instructions are executable by at least one computer processor to perform a method, the method comprising: (A) identifying a document including a first coding having a first feature, the first coding being associated with a first code, the first code having first data; (B) rendering the first data on an output device based on the first feature; (C) receiving, via an input device, a first indication from a user of a verification status of the rendering; and (D) identifying, based on the verification status of the rendering, a verification status of the first feature, comprising: (D)(1) if the verification status of the rendering indicates that the rendering is accurate, then identifying a verification status of the first feature indicating that the first feature is accurate; and (D)(2) otherwise, identifying a verification status of the first feature indicating that the first feature is inaccurate; (E) identifying, based on the verification status of the first feature, a verification status of the first coding; and (F) storing, in a non-transitory computer-readable medium, a record of the verification status of the first coding. 78. The computer readable medium of claim 61 , wherein a second coding includes the first coding and a third coding, the third coding being associated with a third code, the third code having third data, and wherein (B) does not include rendering the third code or the third data.
| 0.534884 |
10,083,492 | 1 | 2 |
1. A method for educating a patient through a collaborative network, the method comprising: authenticating the patient with a username and a password, wherein the username and password are registered by way of an authentication number provided through a hospital entry process such that the authentication number ensures the authenticity of the patient and ensures that patient information is gapped to ensure privacy; receiving a request by a server from a client computer for entry to a repository for a plurality of educational design activities, wherein each of the plurality of educational design activities includes exemplar design configurations and material lists, and wherein each of the plurality of educational design activities is configured to include photographs and written texts for other patients who have completed the associated educational design activity; transmitting a hypertext document to the client computer that includes the plurality of educational design activities, wherein the hypertext document is configured to be displayed through a browsing application on the client computer; receiving a request by the server from the client computer for access to a selected education design activity; providing access to a design engine for the selected educational design activity; storing a design file created by the patient using the design engine; transmitting the design file to a shared workstation, wherein the shared workstation includes a vinyl cutting machine; and generating vinyl shapes based at least in part on the design file.
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1. A method for educating a patient through a collaborative network, the method comprising: authenticating the patient with a username and a password, wherein the username and password are registered by way of an authentication number provided through a hospital entry process such that the authentication number ensures the authenticity of the patient and ensures that patient information is gapped to ensure privacy; receiving a request by a server from a client computer for entry to a repository for a plurality of educational design activities, wherein each of the plurality of educational design activities includes exemplar design configurations and material lists, and wherein each of the plurality of educational design activities is configured to include photographs and written texts for other patients who have completed the associated educational design activity; transmitting a hypertext document to the client computer that includes the plurality of educational design activities, wherein the hypertext document is configured to be displayed through a browsing application on the client computer; receiving a request by the server from the client computer for access to a selected education design activity; providing access to a design engine for the selected educational design activity; storing a design file created by the patient using the design engine; transmitting the design file to a shared workstation, wherein the shared workstation includes a vinyl cutting machine; and generating vinyl shapes based at least in part on the design file. 2. The method of claim 1 , wherein the step of authenticating further comprises creating a secure socket layer (SSL) session.
| 0.696602 |
8,364,694 | 13 | 14 |
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.
| 0.667577 |
7,877,343 | 11 | 19 |
11. A method for automatically extracting relational information from a corpus of text with a computing device without specifying criteria or patterns for controlling extraction of the relational information by the computing device, comprising the steps of: (a) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (b) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree.
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11. A method for automatically extracting relational information from a corpus of text with a computing device without specifying criteria or patterns for controlling extraction of the relational information by the computing device, comprising the steps of: (a) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (b) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree. 19. The method of claim 11 , further comprising the step of mapping each tuple extracted from the corpus of text to a feature vector representation, wherein all features are domain independent.
| 0.662587 |
7,873,516 | 1 | 7 |
1. A computer implemented method for providing context in an electronic text communication, the method comprising: identifying, by a processing unit in a computer, a first set of metrics based on a sender interacting with a biometric gathering input device, wherein the biometric gathering input device is associated with a sending data processing system; calibrating, by the processing unit, a sending communications process on the sending data processing system based on the first set of metrics; identifying, by the processing unit, a portion of the first set of metrics based on the sender interacting with the biometric gathering input device during generation of the electronic text communication to form a second set of metrics; and sending the second set of metrics and the electronic text communication from the sending communications process on the sending data processing system to a recipient data processing system, wherein the second set of metrics is represented at the recipient data processing system using criteria selected by a recipient of the electronic text communication.
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1. A computer implemented method for providing context in an electronic text communication, the method comprising: identifying, by a processing unit in a computer, a first set of metrics based on a sender interacting with a biometric gathering input device, wherein the biometric gathering input device is associated with a sending data processing system; calibrating, by the processing unit, a sending communications process on the sending data processing system based on the first set of metrics; identifying, by the processing unit, a portion of the first set of metrics based on the sender interacting with the biometric gathering input device during generation of the electronic text communication to form a second set of metrics; and sending the second set of metrics and the electronic text communication from the sending communications process on the sending data processing system to a recipient data processing system, wherein the second set of metrics is represented at the recipient data processing system using criteria selected by a recipient of the electronic text communication. 7. The computer implemented method of claim 1 , wherein the biometric input gathering device is a pressure sensitive keyboard.
| 0.898714 |
7,860,877 | 14 | 15 |
14. The method of claim 13 , wherein the rendering engine receives query results and transforms the query results using a transformation language.
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14. The method of claim 13 , wherein the rendering engine receives query results and transforms the query results using a transformation language. 15. The method of claim 14 , wherein the rendering engine uses XSL to transform the query results.
| 0.5 |
9,355,385 | 1 | 2 |
1. A method comprising: receiving, at an application programming interface (API) server associated with an email and calendaring service, a request message comprising content from a location field within a meeting item from a client of the email and calendaring service, wherein the meeting item includes: a meeting request form, appointment, email, calendar entry, or a contact entry, the request message being a request to invoke a find place method defined in an API provided by the API server; and sending a response message to the client in reply to the request message, the response message comprising results of the find place method, the results comprising location information associated with a place name or source-related identifier indicated by the request message, wherein the find place method comprises: parsing the request message for the place name, street address, or the source-related identifier; querying a web service, mailbox, and/or managed database using the place name, the street address, or the source-related identifier; receiving results of the query; and filtering and formatting the results to generate the response message.
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1. A method comprising: receiving, at an application programming interface (API) server associated with an email and calendaring service, a request message comprising content from a location field within a meeting item from a client of the email and calendaring service, wherein the meeting item includes: a meeting request form, appointment, email, calendar entry, or a contact entry, the request message being a request to invoke a find place method defined in an API provided by the API server; and sending a response message to the client in reply to the request message, the response message comprising results of the find place method, the results comprising location information associated with a place name or source-related identifier indicated by the request message, wherein the find place method comprises: parsing the request message for the place name, street address, or the source-related identifier; querying a web service, mailbox, and/or managed database using the place name, the street address, or the source-related identifier; receiving results of the query; and filtering and formatting the results to generate the response message. 2. The method of claim 1 , wherein the request message specifies a location string corresponding to the place name or street address of a place; wherein the find place method performs a look-up of information related to the place using the location string.
| 0.649315 |
9,386,037 | 8 | 12 |
8. The method of claim 1 , wherein comparing the hash signature of the DOM object to the known hash signature of the DOM object associated with the known website further comprises: determining a classification for comparing a similarity of the website to known websites; identifying a plurality of known hash signatures, each of the plurality of known hash signatures corresponding to a different one of DOM objects, wherein each of the DOM objects corresponds to a different one of the known websites associated with the classification, and wherein the plurality of known hash signatures is identified by searching a database of hash signatures for each of the plurality of known hash signatures classified as being associated with the classification; calculating a similarity measurement of the hash signature of the DOM object for the classification; comparing the similarity measurement of the hash signature of the DOM object to a similarity threshold associated with the classification; and reporting the website as being associated with the classification based on the determining that the similarity measurement is over the similarity threshold associated with the classification.
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8. The method of claim 1 , wherein comparing the hash signature of the DOM object to the known hash signature of the DOM object associated with the known website further comprises: determining a classification for comparing a similarity of the website to known websites; identifying a plurality of known hash signatures, each of the plurality of known hash signatures corresponding to a different one of DOM objects, wherein each of the DOM objects corresponds to a different one of the known websites associated with the classification, and wherein the plurality of known hash signatures is identified by searching a database of hash signatures for each of the plurality of known hash signatures classified as being associated with the classification; calculating a similarity measurement of the hash signature of the DOM object for the classification; comparing the similarity measurement of the hash signature of the DOM object to a similarity threshold associated with the classification; and reporting the website as being associated with the classification based on the determining that the similarity measurement is over the similarity threshold associated with the classification. 12. The method of claim 8 , wherein the classification determined for comparing the similarity of the website to the known websites includes being associated with copyrighted content.
| 0.913516 |
7,996,214 | 9 | 13 |
9. A system for exploiting information in an utterance for dialog act tagging, the system comprising: a first module configured to control a processor to receive a user utterance; a second module configured to control the processor to compute at periodic intervals at least one parameter in the user utterance; a third module configured to control the processor to quantize the at least one parameter at each periodic interval; a fourth module configured to control the processor to approximate conditional probabilities using an n-gram over a sliding window over the periodic intervals; and a fifth module configured to control the processor to tag the utterance as a dialog act based on the approximated conditional probabilities.
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9. A system for exploiting information in an utterance for dialog act tagging, the system comprising: a first module configured to control a processor to receive a user utterance; a second module configured to control the processor to compute at periodic intervals at least one parameter in the user utterance; a third module configured to control the processor to quantize the at least one parameter at each periodic interval; a fourth module configured to control the processor to approximate conditional probabilities using an n-gram over a sliding window over the periodic intervals; and a fifth module configured to control the processor to tag the utterance as a dialog act based on the approximated conditional probabilities. 13. The system of claim 9 , wherein the quantized at least one parameter at the periodic intervals over at least a portion of the utterance are used as a feature vector for a user with the n-gram model.
| 0.5 |
8,468,122 | 38 | 44 |
38. A system for responding to a query initiated at a user device, comprising: one or more data stores having a knowledge base stored therein that includes data representing first knowledge about a plurality of objects using a plurality of relationships among the objects, the knowledge base further having natural language translation objects associated therewith operable to translate between natural language and syntax associated with the knowledge base; and one or more computing devices configured to generate a response to the query using at least one of the natural language translation objects and second knowledge not statically stored or represented in the at least one knowledge base prior to receipt of the query, the second knowledge being generated by inference from the first knowledge in response to the query, the inference including retrieving one or more first facts included in the first knowledge, the first facts corresponding to first ones of the objects and first ones of the relationships, and generating one or more second facts from the first facts that express at least one new relationship for at least one of the one or more first objects.
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38. A system for responding to a query initiated at a user device, comprising: one or more data stores having a knowledge base stored therein that includes data representing first knowledge about a plurality of objects using a plurality of relationships among the objects, the knowledge base further having natural language translation objects associated therewith operable to translate between natural language and syntax associated with the knowledge base; and one or more computing devices configured to generate a response to the query using at least one of the natural language translation objects and second knowledge not statically stored or represented in the at least one knowledge base prior to receipt of the query, the second knowledge being generated by inference from the first knowledge in response to the query, the inference including retrieving one or more first facts included in the first knowledge, the first facts corresponding to first ones of the objects and first ones of the relationships, and generating one or more second facts from the first facts that express at least one new relationship for at least one of the one or more first objects. 44. The system of claim 38 wherein the one or more computing devices are further configured to generate a natural language response with reference to selected ones of the plurality of objects and using the at least one natural language translation object.
| 0.814949 |
9,213,684 | 1 | 2 |
1. A method for rendering a document, the method comprising: converting a plurality of resources in a document file into a plurality of files that are native to a browser; creating a style sheet based on the document file, wherein an aggregate of the plurality of files together with the style sheet are configured to cause the browser to render an appearance of the document file; and generating, based on the document file, an invisible layer to be laid on the appearance, wherein the invisible layer enables actions to be performed on the document file.
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1. A method for rendering a document, the method comprising: converting a plurality of resources in a document file into a plurality of files that are native to a browser; creating a style sheet based on the document file, wherein an aggregate of the plurality of files together with the style sheet are configured to cause the browser to render an appearance of the document file; and generating, based on the document file, an invisible layer to be laid on the appearance, wherein the invisible layer enables actions to be performed on the document file. 2. The method of claim 1 , further comprising: streaming pages of the document file to the browser individually as each page is processed.
| 0.795252 |
8,949,878 | 38 | 42 |
38. A device for filtering material from a multimedia program, comprising: a learning module to generate filter criteria learned based on user instructions by examples of objectionable content; at least two of a visual analysis module to extract image features; an audio analysis module to extract second verbal audible features; a transcript analysis module to extract text features based on a transcript; and a filter to process the multimedia program, according to the extracted features and the titter criteria generated by the learning module, and generate a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to a portion of the multimedia program, and eliminate, in accordance with the numeric ranking, objectionable material from the multimedia program.
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38. A device for filtering material from a multimedia program, comprising: a learning module to generate filter criteria learned based on user instructions by examples of objectionable content; at least two of a visual analysis module to extract image features; an audio analysis module to extract second verbal audible features; a transcript analysis module to extract text features based on a transcript; and a filter to process the multimedia program, according to the extracted features and the titter criteria generated by the learning module, and generate a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to a portion of the multimedia program, and eliminate, in accordance with the numeric ranking, objectionable material from the multimedia program. 42. The device of claim 38 , embodied in a television set.
| 0.933638 |
7,516,145 | 38 | 41 |
38. A method comprising: applying a transformation file on a hierarchical data file containing a node to produce a first result; applying a transformation file subtree of the transformation file on a data file subtree containing the node of the hierarchical data file for a range of possible changes to the node to produce a second result; applying the transformation file on the hierarchical data file with the node having the range of possible changes to produce a third result; determining if the first result in conjunction with the second result is equal to the third result; and recording the data file subtree of the hierarchical data file to be isolatable if the determining is true.
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38. A method comprising: applying a transformation file on a hierarchical data file containing a node to produce a first result; applying a transformation file subtree of the transformation file on a data file subtree containing the node of the hierarchical data file for a range of possible changes to the node to produce a second result; applying the transformation file on the hierarchical data file with the node having the range of possible changes to produce a third result; determining if the first result in conjunction with the second result is equal to the third result; and recording the data file subtree of the hierarchical data file to be isolatable if the determining is true. 41. A computer-readable medium comprising computer-executable instructions that perform the method of claim 38 when executed by a computer.
| 0.5 |
8,731,916 | 8 | 12 |
8. A computer system for estimating noise and channel distortions and updating distorted speech parameters for an utterance, within an unscented transformation framework, during automatic speech recognition, comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative to: receive the utterance, wherein the utterance comprises speech generated from a transmission source for delivery to a receiver; apply the unscented transformation framework to speech feature vectors representative of the speech, to determine static distorted speech parameters and dynamic distorted speech parameters with initial noise and channel distortions, the initial noise distortions comprising speech parameters which are initialized by averaging a predetermined number of frames at the beginning and ending of the utterance, wherein the unscented transformation framework utilizes non-linear mapping; and estimate noise and channel distortions in the utterance from the static distorted speech parameters and the dynamic distorted speech parameters.
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8. A computer system for estimating noise and channel distortions and updating distorted speech parameters for an utterance, within an unscented transformation framework, during automatic speech recognition, comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative to: receive the utterance, wherein the utterance comprises speech generated from a transmission source for delivery to a receiver; apply the unscented transformation framework to speech feature vectors representative of the speech, to determine static distorted speech parameters and dynamic distorted speech parameters with initial noise and channel distortions, the initial noise distortions comprising speech parameters which are initialized by averaging a predetermined number of frames at the beginning and ending of the utterance, wherein the unscented transformation framework utilizes non-linear mapping; and estimate noise and channel distortions in the utterance from the static distorted speech parameters and the dynamic distorted speech parameters. 12. The system of claim 8 , wherein the processor, in the unscented transformation framework to the speech feature vectors to determine static distorted speech parameters and dynamic distorted speech parameters, is operative to: determine a static transformed mean utilizing a non-linear function corresponding to the speech in the utterance, the static transformed mean comprising a static transformed speech feature mean vector; and determine a static transformed variance utilizing the non-linear function corresponding to the speech in the utterance, the static transformed speech feature variance comprising elements of a diagonal covariance matrix, utilizing the non-linear function corresponding to the speech in the utterance.
| 0.5 |
9,980,753 | 8 | 9 |
8. The bone anchor assembly of claim 1 , wherein the closure structure has a corresponding continuous helically wound structure engageable with the discontinuous helically wound guide and advancement structure.
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8. The bone anchor assembly of claim 1 , wherein the closure structure has a corresponding continuous helically wound structure engageable with the discontinuous helically wound guide and advancement structure. 9. The bone anchor assembly of claim 8 , wherein the closure structure is configured to abut the longitudinal connecting member positioned in the receiver first channel.
| 0.761972 |
9,519,686 | 4 | 5 |
4. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: responsive to receiving an input question, identify a set of candidate answers from a knowledge domain based on a correlation between an identified one or more predicates and an identified one or more arguments associated with the one or more predicates from the input question; associate an initial confidence score with each candidate answer of the set of candidate answers; refine each initial confidence score associated with each candidate answer based on a set of temporal characteristics identified in the input question, wherein each confidence score associated with each candidate answer is refined based on the set of temporal characteristics using a reference time of the input question and a respective reference time associated with the candidate answer thereby forming a temporally refined confidence score associated with the candidate answer, wherein the temporally refined confidence score associated with the candidate answer is identified by: generating a distance value in terms of years for the respective reference time associated with the candidate answer and the reference time of the input question; using the distance value, determining a multiplier value with which to weight the confidence score associated with the candidate answer using multiplier function: multiplier value=1/(2*distance value+0.5); identifying a sentiment value of the candidate answer to weight the determined multiplier value either positively or negatively; and providing a final weight for the temporally refined confidence score associated with the candidate answer using distance function: final weight=initial confidence score*multiplier value*sentiment value; and provide a set of candidate answers with the temporally refined confidence scores to the user.
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4. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: responsive to receiving an input question, identify a set of candidate answers from a knowledge domain based on a correlation between an identified one or more predicates and an identified one or more arguments associated with the one or more predicates from the input question; associate an initial confidence score with each candidate answer of the set of candidate answers; refine each initial confidence score associated with each candidate answer based on a set of temporal characteristics identified in the input question, wherein each confidence score associated with each candidate answer is refined based on the set of temporal characteristics using a reference time of the input question and a respective reference time associated with the candidate answer thereby forming a temporally refined confidence score associated with the candidate answer, wherein the temporally refined confidence score associated with the candidate answer is identified by: generating a distance value in terms of years for the respective reference time associated with the candidate answer and the reference time of the input question; using the distance value, determining a multiplier value with which to weight the confidence score associated with the candidate answer using multiplier function: multiplier value=1/(2*distance value+0.5); identifying a sentiment value of the candidate answer to weight the determined multiplier value either positively or negatively; and providing a final weight for the temporally refined confidence score associated with the candidate answer using distance function: final weight=initial confidence score*multiplier value*sentiment value; and provide a set of candidate answers with the temporally refined confidence scores to the user. 5. The apparatus of claim 4 , wherein the reference time of the input question is identified from the set of temporal characteristics.
| 0.605882 |
9,032,366 | 9 | 10 |
9. The apparatus of claim 6 , wherein the source code file is generated in a form corresponding to a preset source code template.
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9. The apparatus of claim 6 , wherein the source code file is generated in a form corresponding to a preset source code template. 10. The apparatus of claim 9 , wherein the source code file is generated in a form corresponding to the preset source code template based on preset source code conversion rules.
| 0.5 |
9,798,801 | 9 | 13 |
9. The method in accordance with claim 8 , at least one of the first set of query results comprising a table, and the second set of query results comprising a modified table.
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9. The method in accordance with claim 8 , at least one of the first set of query results comprising a table, and the second set of query results comprising a modified table. 13. The method in accordance with claim 9 , a modification causing the table to be modified to the modified table comprising: applying one or more constraints to the table to form the modified table.
| 0.5 |
8,375,116 | 2 | 4 |
2. The method of claim 1 , wherein said operation interface specifications further include data identifying respective descriptions of sets of storage units and logical structures for the sets of storage units.
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2. The method of claim 1 , wherein said operation interface specifications further include data identifying respective descriptions of sets of storage units and logical structures for the sets of storage units. 4. The method of claim 2 , wherein the storage units comprise unparsed data.
| 0.815534 |
8,887,062 | 1 | 4 |
1. A method of streamlined web site navigation, including: providing a command line interface to a particular web site supplemental to a GUI interface, wherein the command line interface accepts entry of verbs and parameters from a web site-specific vocabulary, wherein the verbs and parameters have meaning local to a web server hosting the particular web site, wherein the web site-specific vocabulary allows a user to access functions of a GUI interface page of the web site by entering at least one verb and without navigating page links to reach the GUI interface page; receiving data entered at the command line interface, including the at least one verb; identifying a particular web page responsive to the verb; and sending the particular web page towards a client system.
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1. A method of streamlined web site navigation, including: providing a command line interface to a particular web site supplemental to a GUI interface, wherein the command line interface accepts entry of verbs and parameters from a web site-specific vocabulary, wherein the verbs and parameters have meaning local to a web server hosting the particular web site, wherein the web site-specific vocabulary allows a user to access functions of a GUI interface page of the web site by entering at least one verb and without navigating page links to reach the GUI interface page; receiving data entered at the command line interface, including the at least one verb; identifying a particular web page responsive to the verb; and sending the particular web page towards a client system. 4. The method of claim 1 , wherein the verb is a custom verb, further including: receiving with the data entered at the command line interface at least one parameter that modifies the custom verb; and responsive to the custom verb and the parameter, performing one or more operations supported by the web site without transmitting corresponding operations pages, before sending the particular web page.
| 0.5 |
8,506,304 | 11 | 12 |
11. The method of claim 10 wherein the student profile comprises community data, school data, class data, teacher data, and student background.
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11. The method of claim 10 wherein the student profile comprises community data, school data, class data, teacher data, and student background. 12. The method of claim 11 wherein the learning patterns are identified using a pattern recognition algorithm.
| 0.5 |
8,359,570 | 9 | 10 |
9. The method according to claim 8 , further comprising: adding a user-defined scripting command as one of the scripting commands associated with one of said scripting languages, said user-defined command cooperating with said interface of said framework; constructing a binary executable form of said user-defined command; providing a detailed description of said user-defined command, associating said detailed description with said user-defined command; and, constructing said common interface in a programming neutral language format.
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9. The method according to claim 8 , further comprising: adding a user-defined scripting command as one of the scripting commands associated with one of said scripting languages, said user-defined command cooperating with said interface of said framework; constructing a binary executable form of said user-defined command; providing a detailed description of said user-defined command, associating said detailed description with said user-defined command; and, constructing said common interface in a programming neutral language format. 10. The method according to claim 9 , wherein: said user-defined command is in XML format; said detailed description of said user-defined command is meta-data in XML format and contains National Language Support; and, said programming neutral language format is in XML format.
| 0.5 |
4,450,520 | 9 | 11 |
9. A method, for detecting matches between strings of input characters and one or more patterns, each pattern comprising elements consisting of tokens, employing a finite state automaton, responsive to said strings of input characters, comprising a plurality of character matchers acting in concert; each character matcher being characterized as capable of existing in one of a plurality of states, each such state having (a) one token from a pattern, to be compared against a current input character, (b) first instructions, which govern transitions to the next state of said character matcher, (c) second instructions, which force other character matchers into specified states, and (d) a start-up table, responsive to said input character, which causes said character matcher to transition to a specified state upon recognition of a portion of one or more elements of said pattern; each character matcher being further characterized as having at least an initial state, to be occupied by said character matcher at the start of the matching procedure, and an idle state, to be occupied by said character matcher after an unsuccessful comparison between the token specified in the current state of said character matcher and the current input character; the respective states being partitioned among said character matchers to avoid any sequence of input characters requiring any character matcher to be simultaneously in more than one state; said method, for each string of input characters to be matched and a corresponding character matcher, comprising: (a) comparing, with the character matcher in its initial state, a first input character against the token specified in the initial state of the character matcher, whereby said comparison is either successful or unsuccessful; (b) transitioning, in consequence of an unsuccessful comparison, to the idle state of the character matcher; (c) transitioning, in consequence of a successful comparison, to a succeeding state, in accordance with instructions contained in the current state of the character matcher; (d) transitioning to the specified state in response to instructions from the start-up table of said character matcher whenever such a transition is so indicated; (e) forcing other character matchers into new states specified in the instructions of the current state of the character matcher of step (c); (f) comparing a succeeding input character against the token specified in the succeeding state and transitioning to a further succeeding state in accordance with steps (b), (c), (d), and (e); and (g) repeating step (e) until all input characters have been compared.
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9. A method, for detecting matches between strings of input characters and one or more patterns, each pattern comprising elements consisting of tokens, employing a finite state automaton, responsive to said strings of input characters, comprising a plurality of character matchers acting in concert; each character matcher being characterized as capable of existing in one of a plurality of states, each such state having (a) one token from a pattern, to be compared against a current input character, (b) first instructions, which govern transitions to the next state of said character matcher, (c) second instructions, which force other character matchers into specified states, and (d) a start-up table, responsive to said input character, which causes said character matcher to transition to a specified state upon recognition of a portion of one or more elements of said pattern; each character matcher being further characterized as having at least an initial state, to be occupied by said character matcher at the start of the matching procedure, and an idle state, to be occupied by said character matcher after an unsuccessful comparison between the token specified in the current state of said character matcher and the current input character; the respective states being partitioned among said character matchers to avoid any sequence of input characters requiring any character matcher to be simultaneously in more than one state; said method, for each string of input characters to be matched and a corresponding character matcher, comprising: (a) comparing, with the character matcher in its initial state, a first input character against the token specified in the initial state of the character matcher, whereby said comparison is either successful or unsuccessful; (b) transitioning, in consequence of an unsuccessful comparison, to the idle state of the character matcher; (c) transitioning, in consequence of a successful comparison, to a succeeding state, in accordance with instructions contained in the current state of the character matcher; (d) transitioning to the specified state in response to instructions from the start-up table of said character matcher whenever such a transition is so indicated; (e) forcing other character matchers into new states specified in the instructions of the current state of the character matcher of step (c); (f) comparing a succeeding input character against the token specified in the succeeding state and transitioning to a further succeeding state in accordance with steps (b), (c), (d), and (e); and (g) repeating step (e) until all input characters have been compared. 11. The method of claim 9 wherein the plurality of character matchers are disposed in a ring configuration wherein each character matcher is capable of forcing only the two neighboring character matchers into a specified state.
| 0.5 |
8,174,559 | 10 | 13 |
10. An apparatus as in claim 9 , wherein the time alignment information comprises a first time stamp indicative of a time associated with the compressed video data and a second time stamp indicative of a time associated with the compressed audio data.
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10. An apparatus as in claim 9 , wherein the time alignment information comprises a first time stamp indicative of a time associated with the compressed video data and a second time stamp indicative of a time associated with the compressed audio data. 13. An apparatus as in claim 10 wherein the time stamps are representative specified intervals of time.
| 0.669872 |
8,959,166 | 21 | 22 |
21. A computing system, comprising: one or more processors configured to identify a first set of visits to one or more webpages by a first participant of a social network, the one or more processors further configured to determine for each of the first set of visits to the one or more webpages, whether the first participant received a social annotation during said each of the first set of the visits to the one or more webpages, the one or more processors further configured to identify a second set of visits to at least one of the one or more webpages by a second participant of the social network, the one or more processors further configured to determine whether the second participant received a social annotation during at least one of the second set of visits to the one or more webpages, the one or more processors further configured to calculate a first total number of missed social annotations for said each of the one or more webpages for the first participant of the social network based at least in part on the first set of visits to the one or more webpages and the determined social annotations received during said each of the first set of the visits to the one or more webpages, the one or more processors further configured to calculate a second total number of missed social annotations for said each of the one or more webpages for the second participant of the social network, the one or more processors further configured to determine a combined calculation of missed social annotations for said each of the one or more webpages based at least in part on the first total number of missed social annotations for said each of the one or more webpages for the first participant and the second total number of missed social annotations for said each of the one or more webpages for the second participant, the one or more processors further configured to generate an indication for a third participant of one or more websites for which to provide a social annotation based at least in part on the combined calculation of missed social annotations for said each of the one or more webpages, the one or more processors further configured to provide for display to the third participant the indication of one or more websites for which to provide the social annotation.
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21. A computing system, comprising: one or more processors configured to identify a first set of visits to one or more webpages by a first participant of a social network, the one or more processors further configured to determine for each of the first set of visits to the one or more webpages, whether the first participant received a social annotation during said each of the first set of the visits to the one or more webpages, the one or more processors further configured to identify a second set of visits to at least one of the one or more webpages by a second participant of the social network, the one or more processors further configured to determine whether the second participant received a social annotation during at least one of the second set of visits to the one or more webpages, the one or more processors further configured to calculate a first total number of missed social annotations for said each of the one or more webpages for the first participant of the social network based at least in part on the first set of visits to the one or more webpages and the determined social annotations received during said each of the first set of the visits to the one or more webpages, the one or more processors further configured to calculate a second total number of missed social annotations for said each of the one or more webpages for the second participant of the social network, the one or more processors further configured to determine a combined calculation of missed social annotations for said each of the one or more webpages based at least in part on the first total number of missed social annotations for said each of the one or more webpages for the first participant and the second total number of missed social annotations for said each of the one or more webpages for the second participant, the one or more processors further configured to generate an indication for a third participant of one or more websites for which to provide a social annotation based at least in part on the combined calculation of missed social annotations for said each of the one or more webpages, the one or more processors further configured to provide for display to the third participant the indication of one or more websites for which to provide the social annotation. 22. The computing system of claim 21 , wherein the one or more processors are further configured to determine a value coefficient for at least one of the one or more webpages.
| 0.639918 |
8,578,265 | 1 | 39 |
1. A method of generating a dynamic document, the method comprising: providing a web-based visual editor structured to facilitate generation of a markup language version of the dynamic document, the markup language version of the dynamic document including first data indicative of a dynamic field; converting the markup language version of the dynamic document to a stylesheet version of the dynamic document, the stylesheet version of the dynamic document including second data indicative of the dynamic field; deploying the stylesheet version of the dynamic document via a network at an application server, wherein when the stylesheet version of the dynamic document is executed by a first user, a first instance of the dynamic document is generated using data associated with the first user as a first output document, and when the stylesheet version of the dynamic document is executed by a second different user, a second different instance of the dynamic document is generated using data associated with the second user as a second output document; transmitting the first output document to a first client device of the first user from the application server; and transmitting the second output document to a second client device of the second user from the application server, wherein the markup language version of the dynamic document is displayed as an XHTML page within a web browser at a designer terminal that provides the web-based visual editor, the stylesheet version of the dynamic document is an XSL:FO file stored at the application server, and the first and second output documents are at least one of PDF and RTF files stored locally at the first and second client devices, the client devices being located remotely from the application server.
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1. A method of generating a dynamic document, the method comprising: providing a web-based visual editor structured to facilitate generation of a markup language version of the dynamic document, the markup language version of the dynamic document including first data indicative of a dynamic field; converting the markup language version of the dynamic document to a stylesheet version of the dynamic document, the stylesheet version of the dynamic document including second data indicative of the dynamic field; deploying the stylesheet version of the dynamic document via a network at an application server, wherein when the stylesheet version of the dynamic document is executed by a first user, a first instance of the dynamic document is generated using data associated with the first user as a first output document, and when the stylesheet version of the dynamic document is executed by a second different user, a second different instance of the dynamic document is generated using data associated with the second user as a second output document; transmitting the first output document to a first client device of the first user from the application server; and transmitting the second output document to a second client device of the second user from the application server, wherein the markup language version of the dynamic document is displayed as an XHTML page within a web browser at a designer terminal that provides the web-based visual editor, the stylesheet version of the dynamic document is an XSL:FO file stored at the application server, and the first and second output documents are at least one of PDF and RTF files stored locally at the first and second client devices, the client devices being located remotely from the application server. 39. The method of claim 1 , wherein the markup language version of the dynamic document is an XHTML file stored at a designer terminal that provides the web-based visual editor, the stylesheet version of the dynamic document is an XSL:FO file stored at an application server, and the first output document is a PDF file stored at the client devices.
| 0.582536 |
7,823,058 | 1 | 11 |
1. An interactive, electronic method of authoring annotated traversals through visual data, the method comprising: displaying the visual data, wherein the visual data comprises motion video; interactively defining a traversal of the displayed visual data by positioning a resizable overlay window relative to the displayed visual data, wherein said resizable overlay window is resizable while the visual data is being displayed, said traversal comprising a subset of motion video that specifies a time-based sequence of frames of said motion video, each of said frames comprising the visual data delineated by the overlay window, wherein the displaying said visual data comprises displaying the visual data in a cylindrical layout, and wherein said positioning of the overlay window is defined by a field of view of a virtual camera located centrally to said cylindrical layout; annotating the traversal; storing a persistent record of the annotated traversal; and using an integrated graphical user interface to perform said method, and wherein said graphical user interface comprises a plurality of computer display regions including: an overview region displaying the visual data; a detail region displaying current data within the overlay window; and a worksheet region displaying a list of a plurality of stored annotated traversal records.
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1. An interactive, electronic method of authoring annotated traversals through visual data, the method comprising: displaying the visual data, wherein the visual data comprises motion video; interactively defining a traversal of the displayed visual data by positioning a resizable overlay window relative to the displayed visual data, wherein said resizable overlay window is resizable while the visual data is being displayed, said traversal comprising a subset of motion video that specifies a time-based sequence of frames of said motion video, each of said frames comprising the visual data delineated by the overlay window, wherein the displaying said visual data comprises displaying the visual data in a cylindrical layout, and wherein said positioning of the overlay window is defined by a field of view of a virtual camera located centrally to said cylindrical layout; annotating the traversal; storing a persistent record of the annotated traversal; and using an integrated graphical user interface to perform said method, and wherein said graphical user interface comprises a plurality of computer display regions including: an overview region displaying the visual data; a detail region displaying current data within the overlay window; and a worksheet region displaying a list of a plurality of stored annotated traversal records. 11. The method of claim 1 , wherein the annotating includes, at least in part, data selected from one or more of the following categories: {textual comments; graphical symbols; classification codes; meta-data; audio transcription}.
| 0.621311 |
9,940,394 | 13 | 15 |
13. The apparatus of claim 1 , further, comprising: a machine learning structure generating component in the component collection, and the processor issues instructions from the machine learning structure generating component, stored in the memory, to: determine, via at least one processor, a ranking application for which to generate a machine learning structure; determine, via at least one processor, a set of inputs for the machine learning structure based on the ranking application, wherein at least some of the inputs in the set of inputs correspond to work graph data stored in the work graph data structure; train, via at least one processor, the machine learning structure using at least some of the work graph data stored in the work graph data structure; and store, via at least one processor, machine learning structure parameters of the trained machine learning structure, wherein the trained machine learning structure is associated with group level access control data.
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13. The apparatus of claim 1 , further, comprising: a machine learning structure generating component in the component collection, and the processor issues instructions from the machine learning structure generating component, stored in the memory, to: determine, via at least one processor, a ranking application for which to generate a machine learning structure; determine, via at least one processor, a set of inputs for the machine learning structure based on the ranking application, wherein at least some of the inputs in the set of inputs correspond to work graph data stored in the work graph data structure; train, via at least one processor, the machine learning structure using at least some of the work graph data stored in the work graph data structure; and store, via at least one processor, machine learning structure parameters of the trained machine learning structure, wherein the trained machine learning structure is associated with group level access control data. 15. The apparatus of claim 13 , wherein the ranking application is any of: ranking metadata access control carrying messages, ranking people, ranking channels.
| 0.5 |
7,739,115 | 44 | 55 |
44. A method of improving agent performance, the method comprising at least the following: identifying at least one interaction handled by at least one agent, which interaction is deficient in at least one aspect, the at least one interaction being recorded as a video recording; obtaining a voice record of at least a portion of the at least one interaction; obtaining a further voice record of at least a portion of at least a further pre-recorded interaction or a plurality of pre-recorded interactions, wherein the plurality of pre-recorded interactions are stored in a library or data store containing exemplary interactions by the at least one agent made available for future reference, in which the at least one aspect is determined by generating a score using confidence level thresholds of an at least one automatic speech recognition component such that the confidence level thresholds are assigned to each of the plurality of panels and evaluating the score against a static or a varying standard of the least one automatic speech recognition component; and transmitting data representing at least the portions of the voice record and the further pre-recorded voice record or plurality of pre-recorded interactions to the at least one agent.
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44. A method of improving agent performance, the method comprising at least the following: identifying at least one interaction handled by at least one agent, which interaction is deficient in at least one aspect, the at least one interaction being recorded as a video recording; obtaining a voice record of at least a portion of the at least one interaction; obtaining a further voice record of at least a portion of at least a further pre-recorded interaction or a plurality of pre-recorded interactions, wherein the plurality of pre-recorded interactions are stored in a library or data store containing exemplary interactions by the at least one agent made available for future reference, in which the at least one aspect is determined by generating a score using confidence level thresholds of an at least one automatic speech recognition component such that the confidence level thresholds are assigned to each of the plurality of panels and evaluating the score against a static or a varying standard of the least one automatic speech recognition component; and transmitting data representing at least the portions of the voice record and the further pre-recorded voice record or plurality of pre-recorded interactions to the at least one agent. 55. The method of claim 44 , wherein transmitting the voice record and the further voice record includes emailing the data representing the voice record and the further voice record to the at least one agent.
| 0.691395 |
9,311,505 | 1 | 3 |
1. A method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on the following: an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models; a generation, by at least one processor implemented in hardware, of one or more user models for the items data corresponding to each abstraction level of the ontology; a processing of at least one request for one or more recommendations (a) to determine a requested abstraction level, and (b) to determine a privacy level, a security level, or a combination thereof associated with the at least one request; a processing of the privacy level, the security level, or the combination thereof against one or more privacy policies, one or more security policies, or a combination thereof to determine permission to access the requested abstraction level; a generation, a retrieval, or a combination thereof of the at least one of the one or more user models based, at least in part, on whether the at least one of the one or more user models exists at the requested abstraction level, a selection of at least one of the one or more user models for generating the one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on the one or more privacy policies, the one or more security policies, or the combination thereof; and wherein the one or more abstraction levels correspond to different levels of the privacy policies and the security policies of the one or more user models.
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1. A method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on the following: an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models; a generation, by at least one processor implemented in hardware, of one or more user models for the items data corresponding to each abstraction level of the ontology; a processing of at least one request for one or more recommendations (a) to determine a requested abstraction level, and (b) to determine a privacy level, a security level, or a combination thereof associated with the at least one request; a processing of the privacy level, the security level, or the combination thereof against one or more privacy policies, one or more security policies, or a combination thereof to determine permission to access the requested abstraction level; a generation, a retrieval, or a combination thereof of the at least one of the one or more user models based, at least in part, on whether the at least one of the one or more user models exists at the requested abstraction level, a selection of at least one of the one or more user models for generating the one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on the one or more privacy policies, the one or more security policies, or the combination thereof; and wherein the one or more abstraction levels correspond to different levels of the privacy policies and the security policies of the one or more user models. 3. A method of claim 1 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following: a processing of the at least one request to determine a requested segment of the selected at least one user model; and a generation, a retrieval, or a combination thereof of the requested segment based, at least in part, on whether the requested segment exists.
| 0.660131 |
7,774,290 | 9 | 10 |
9. A system for generating an abstract representation for source code of an application, the system comprising: a processor; a non-transitory computer readable medium; a contextual pattern decoder engine configured for receiving the source code in a programming language; a pattern classification engine configured for identifying a plurality of blocks in the source code using first patterns, and classifying two or more of the plurality of blocks into a logic block that corresponds to a business rule; a pattern conversion engine configured for extracting a plurality of knowledge elements from the logic block using second patterns, wherein the pattern classification engine is further configured for classifying the plurality of knowledge elements using third patterns, and the contextual pattern decoder engine is further configured for determining context for the plurality of knowledge elements using user defined rules; a pattern abstraction engine configured for generating the abstract representation of the source code in a standard format independent of the programming language of the source code using a dynamic rule and a fourth pattern, wherein the abstract representation includes the plurality of knowledge elements, wherein each of the first, second, third, and fourth patterns matches at least a part of the source code, and wherein each of the first, second, third, and fourth patterns comprises a predefined pattern or a dynamic pattern; and a pattern hatcher engine configured for hatching a dynamic pattern when no predefined pattern matches a part of the source code, wherein the dynamic pattern is created using fuzzy-neural rules and dynamic rules and is determined to be stored in a contextual taxonomy store segment, wherein the pattern conversion engine is further configured for identifying the context of the plurality of knowledge elements in the abstract representation.
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9. A system for generating an abstract representation for source code of an application, the system comprising: a processor; a non-transitory computer readable medium; a contextual pattern decoder engine configured for receiving the source code in a programming language; a pattern classification engine configured for identifying a plurality of blocks in the source code using first patterns, and classifying two or more of the plurality of blocks into a logic block that corresponds to a business rule; a pattern conversion engine configured for extracting a plurality of knowledge elements from the logic block using second patterns, wherein the pattern classification engine is further configured for classifying the plurality of knowledge elements using third patterns, and the contextual pattern decoder engine is further configured for determining context for the plurality of knowledge elements using user defined rules; a pattern abstraction engine configured for generating the abstract representation of the source code in a standard format independent of the programming language of the source code using a dynamic rule and a fourth pattern, wherein the abstract representation includes the plurality of knowledge elements, wherein each of the first, second, third, and fourth patterns matches at least a part of the source code, and wherein each of the first, second, third, and fourth patterns comprises a predefined pattern or a dynamic pattern; and a pattern hatcher engine configured for hatching a dynamic pattern when no predefined pattern matches a part of the source code, wherein the dynamic pattern is created using fuzzy-neural rules and dynamic rules and is determined to be stored in a contextual taxonomy store segment, wherein the pattern conversion engine is further configured for identifying the context of the plurality of knowledge elements in the abstract representation. 10. The system of claim 9 , wherein the pattern abstraction engine is further configured for formatting the source code by removing unreadable characters.
| 0.579235 |
4,739,398 | 34 | 36 |
34. The system of claim 33 further comprising: a plurality of local sites, each of said sites located in a different geographic region for monitoring broadcast signals in said region; a central site; and a communications network linking said central site and said plurality of local sites; wherein: each of said local sites maintains a local library of segment signatures applicable to broadcast signals in its geographic region, each of said local sites having at least said storing means, said monitoring means, said searching means, said comparing means, and said detecting means; said central site has said constructing means and maintains a global library containing all of the information in all of said local libraries; and said classifying and identifying means comprises: means at each of said local sites for generating compressed audio and video information, a temporary digital signature, and parametized monitored signal information for a potential unknown segment not found in the respective local library and for transmitting at least said parametized monitored signal information and said temporary digital signature for a potential unknown segment via said communications network to said central site; means at said central site for searching and comparing signatures stored in said global library with said transmitted parametized montiored signal information; means at said central site for grouping together like potential unknown segments received by said central site from said local sites and not found in said global library; means at said central site for requesting at least one of said compressed audio and video information for at least one of said grouped potential unknown segments and for allowing an operator to play back said at least one of said audio and video information to classify said segment and to instruct said constructing means to automatically construct a signature for said segment; and means for adding said signature constructed by said constructing means at said central site to said global library and for transmitting it via said communciations network to said local libraries.
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34. The system of claim 33 further comprising: a plurality of local sites, each of said sites located in a different geographic region for monitoring broadcast signals in said region; a central site; and a communications network linking said central site and said plurality of local sites; wherein: each of said local sites maintains a local library of segment signatures applicable to broadcast signals in its geographic region, each of said local sites having at least said storing means, said monitoring means, said searching means, said comparing means, and said detecting means; said central site has said constructing means and maintains a global library containing all of the information in all of said local libraries; and said classifying and identifying means comprises: means at each of said local sites for generating compressed audio and video information, a temporary digital signature, and parametized monitored signal information for a potential unknown segment not found in the respective local library and for transmitting at least said parametized monitored signal information and said temporary digital signature for a potential unknown segment via said communications network to said central site; means at said central site for searching and comparing signatures stored in said global library with said transmitted parametized montiored signal information; means at said central site for grouping together like potential unknown segments received by said central site from said local sites and not found in said global library; means at said central site for requesting at least one of said compressed audio and video information for at least one of said grouped potential unknown segments and for allowing an operator to play back said at least one of said audio and video information to classify said segment and to instruct said constructing means to automatically construct a signature for said segment; and means for adding said signature constructed by said constructing means at said central site to said global library and for transmitting it via said communciations network to said local libraries. 36. The system of claim 34 further comprising means for transmitting from each of said local sites to said central site information concerning the occurrence of broadcast segments and means at said central site for logging said information.
| 0.74359 |
8,478,780 | 1 | 5 |
1. A computer-readable memory having instructions stored thereon that, when executed by a computing device, cause the computer device to perform operations comprising: providing an ontology that defines a hierarchy of a plurality of concepts at different concept domain layers and that links natural language words to the plurality of concepts at different concept domain layers; classifying each of a plurality of received queries with a particular intent category based on the ontology, wherein the intent category is pre-defined by a single natural language word or phrase that summarizes in a same natural language word formation a generalized information requested by the queries and wherein the queries use different natural language formations to request different types of information summarized by the single natural language word or phrase of the particular intent category; associating an intent response formulated of natural language words or phrases with the particular intent category, wherein the intent response provides a single common applicable response for the queries; providing an intent hierarchy of a plurality of intent categories including the particular intent category, wherein natural language phrases representing the hierarchy of intent categories at different domain layers of the intent hierarchy have different generalities of terms than natural language phrases representing the intent categories in other domain layers of the intent hierarchy, and wherein the intent hierarchy is independent and different from a hierarchy of the ontology; determining if the particular intent category has a parent hierarchical intent category located in a higher domain layer of the intent hierarchy; and if the parent hierarchical intent category is present in the particular intent hierarchy, then displaying an intent response of the parent hierarchical intent category.
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1. A computer-readable memory having instructions stored thereon that, when executed by a computing device, cause the computer device to perform operations comprising: providing an ontology that defines a hierarchy of a plurality of concepts at different concept domain layers and that links natural language words to the plurality of concepts at different concept domain layers; classifying each of a plurality of received queries with a particular intent category based on the ontology, wherein the intent category is pre-defined by a single natural language word or phrase that summarizes in a same natural language word formation a generalized information requested by the queries and wherein the queries use different natural language formations to request different types of information summarized by the single natural language word or phrase of the particular intent category; associating an intent response formulated of natural language words or phrases with the particular intent category, wherein the intent response provides a single common applicable response for the queries; providing an intent hierarchy of a plurality of intent categories including the particular intent category, wherein natural language phrases representing the hierarchy of intent categories at different domain layers of the intent hierarchy have different generalities of terms than natural language phrases representing the intent categories in other domain layers of the intent hierarchy, and wherein the intent hierarchy is independent and different from a hierarchy of the ontology; determining if the particular intent category has a parent hierarchical intent category located in a higher domain layer of the intent hierarchy; and if the parent hierarchical intent category is present in the particular intent hierarchy, then displaying an intent response of the parent hierarchical intent category. 5. The computer-readable memory of claim 1 , wherein the operations further comprise: identifying at least some most frequently queried intent categories for the queries; and providing pre-query intent responses or links for at least a portion of the identified most frequently queried intent categories.
| 0.877122 |
9,292,522 | 9 | 15 |
9. A system for performing operations on structured computer text, the system comprising: a processor; a storage device; a user input device; a user display; and computer executable instructions operative on the processor for: converting structured text in a computing system into strings of tokens representing text formats; identifying repeating patterns of said text formats within said structured computer text; determining pattern transformation procedures for transforming text strings within said structured computer text; building transformation algorithms for performing said pattern transformation procedures on said text strings; applying said algorithms to said text strings within said structured computer text that match a pattern; whereby said structured computer text is transformed from a first pattern to a second pattern; accepting a first input array of strings containing actual lexeme types; determining all possible text patterns within said first input array; building a third output array of strings representing text patterns in said structured computer text; accepting said third output array of strings representing text patterns in said structured computer text; removing all text patterns within said third output array containing text patterns of smaller size; removing all patterns within said third output array containing text patterns that can be generated by shifting elements in other text patterns.
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9. A system for performing operations on structured computer text, the system comprising: a processor; a storage device; a user input device; a user display; and computer executable instructions operative on the processor for: converting structured text in a computing system into strings of tokens representing text formats; identifying repeating patterns of said text formats within said structured computer text; determining pattern transformation procedures for transforming text strings within said structured computer text; building transformation algorithms for performing said pattern transformation procedures on said text strings; applying said algorithms to said text strings within said structured computer text that match a pattern; whereby said structured computer text is transformed from a first pattern to a second pattern; accepting a first input array of strings containing actual lexeme types; determining all possible text patterns within said first input array; building a third output array of strings representing text patterns in said structured computer text; accepting said third output array of strings representing text patterns in said structured computer text; removing all text patterns within said third output array containing text patterns of smaller size; removing all patterns within said third output array containing text patterns that can be generated by shifting elements in other text patterns. 15. The system according to claim 9 , further including: accepting a fourth input array of strings and a fifth input array of strings; identifying the source of text patterns within said fourth input array of strings and said fifth input array of strings.
| 0.721616 |
9,817,917 | 23 | 24 |
23. The non-transitory, computer readable medium of claim 19 wherein the computer readable program when executed on the computer further causes the computer to perform: identifying a controlling numeric value for a dynamic COBOL construct clause; identifying an instance of the dynamic COBOL construct clause affecting a dynamic COBOL construct subset; recursively rereading the dynamic COBOL construct subset based at least in part on a new definition specified by the customized object model; and automatically forming each reread portion of the dynamic COBOL construct subset as the object instance.
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23. The non-transitory, computer readable medium of claim 19 wherein the computer readable program when executed on the computer further causes the computer to perform: identifying a controlling numeric value for a dynamic COBOL construct clause; identifying an instance of the dynamic COBOL construct clause affecting a dynamic COBOL construct subset; recursively rereading the dynamic COBOL construct subset based at least in part on a new definition specified by the customized object model; and automatically forming each reread portion of the dynamic COBOL construct subset as the object instance. 24. The non-transitory, computer readable medium of claim 23 wherein the dynamic COBOL construct clause is a member of a group consisting of an OCCURS DEPENDING ON clause and a REDEFINE clause.
| 0.5 |
9,400,956 | 9 | 12 |
9. A system for generating a first answer relationship in a first answer sequence of a plurality of answer sequences, the system comprising: a memory; and at least one processor in communication with the memory, wherein the at least one processor is configured to perform a method comprising: receiving, from a user, a question; identifying, in response to the received question, a plurality of answer sequences, wherein each answer sequence of the plurality of answer sequences is a procedure that includes as parts of that procedure a plurality of answers to be used together by the user to complete a task associated with the question; identifying, in response to the received question, the first answer sequence of the plurality of answer sequences, the first answer sequence including a first answer and a second answer; analyzing, using the first answer and the second answer, a corpus to identify a set of influence factors corresponding to both the first answer and the second answer, wherein each influence factor of the set of influence factors is an interaction that is likely to occur if the first answer and the second answer are used together as provided for in the first answer sequence to complete the task; and generating, based on the set of influence factors, the first answer relationship between the first answer and the second answer.
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9. A system for generating a first answer relationship in a first answer sequence of a plurality of answer sequences, the system comprising: a memory; and at least one processor in communication with the memory, wherein the at least one processor is configured to perform a method comprising: receiving, from a user, a question; identifying, in response to the received question, a plurality of answer sequences, wherein each answer sequence of the plurality of answer sequences is a procedure that includes as parts of that procedure a plurality of answers to be used together by the user to complete a task associated with the question; identifying, in response to the received question, the first answer sequence of the plurality of answer sequences, the first answer sequence including a first answer and a second answer; analyzing, using the first answer and the second answer, a corpus to identify a set of influence factors corresponding to both the first answer and the second answer, wherein each influence factor of the set of influence factors is an interaction that is likely to occur if the first answer and the second answer are used together as provided for in the first answer sequence to complete the task; and generating, based on the set of influence factors, the first answer relationship between the first answer and the second answer. 12. The system of claim 9 , wherein the method further comprises: assigning a relationship score to the first answer relationship, the relationship score calculated based on the set of influence factors; and evaluating, based on the relationship score, the first answer relationship.
| 0.87717 |
9,852,219 | 10 | 11 |
10. The method of claim 1 , wherein a group includes samples from two or more tracks.
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10. The method of claim 1 , wherein a group includes samples from two or more tracks. 11. The method of claim 10 , further comprising: identifying the group including samples from two or more tracks with metadata associated with all related tracks.
| 0.5 |
7,958,138 | 1 | 11 |
1. A method for using a computer system, in response to a reader's request for display of electronic text, to automatically identify and provide additional reading material related to concepts referred to within said electronic text comprising, in sequence, the steps of: a) on a server system, via a network, accepting a request for electronic text from a client system; b) formulating a search request for additional reading material related to at least one concept in a text section of said electronic text, wherein said search request includes at least one term that was not provided to said server system by said client system; and c) via a network, along with said electronic text, providing instructions to said client system that when executed: i) cause said search request to be transmitted via a computer network, resulting in the search of an index, said search resulting in identification of related material; and ii) provide to said client system an indicator of said related material to be presented in the same presentation as the requested electronic text; wherein: said index contains a plurality of terms by which it may be searched; substantially all terms in said index are associated with at least one pointer to a text section; and at least one term in said index is associated with a plurality of pointers, at least two of said plurality of pointers pointing to different text sections.
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1. A method for using a computer system, in response to a reader's request for display of electronic text, to automatically identify and provide additional reading material related to concepts referred to within said electronic text comprising, in sequence, the steps of: a) on a server system, via a network, accepting a request for electronic text from a client system; b) formulating a search request for additional reading material related to at least one concept in a text section of said electronic text, wherein said search request includes at least one term that was not provided to said server system by said client system; and c) via a network, along with said electronic text, providing instructions to said client system that when executed: i) cause said search request to be transmitted via a computer network, resulting in the search of an index, said search resulting in identification of related material; and ii) provide to said client system an indicator of said related material to be presented in the same presentation as the requested electronic text; wherein: said index contains a plurality of terms by which it may be searched; substantially all terms in said index are associated with at least one pointer to a text section; and at least one term in said index is associated with a plurality of pointers, at least two of said plurality of pointers pointing to different text sections. 11. The method of claim 1 , wherein said search request of step (b) is formulated by a method that comprises analyzing said text section for embedded commands.
| 0.762687 |
7,484,960 | 10 | 11 |
10. A print medium having a plurality of characters affixed thereto, comprising one or more conventional textual characters suitable for reading by a sighted person printed on a medium, and one or more Braille characters presented on said medium on selected locations thereof so as to provide a one-to-one correspondence between each of said textual characters and its corresponding Braille character and such that each Braille character is presented substantially directly below a corresponding textual character, the corresponding conventional textual and Braille character pairs being presented in a first portion of the print medium, and another copy of said textual characters presented in a second portion of the print medium, said second portion being sufficiently removed from said first portion such that a sighted person can read the textual characters in said second portion while a visually impaired person is reading the corresponding Braille characters in said first portion.
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10. A print medium having a plurality of characters affixed thereto, comprising one or more conventional textual characters suitable for reading by a sighted person printed on a medium, and one or more Braille characters presented on said medium on selected locations thereof so as to provide a one-to-one correspondence between each of said textual characters and its corresponding Braille character and such that each Braille character is presented substantially directly below a corresponding textual character, the corresponding conventional textual and Braille character pairs being presented in a first portion of the print medium, and another copy of said textual characters presented in a second portion of the print medium, said second portion being sufficiently removed from said first portion such that a sighted person can read the textual characters in said second portion while a visually impaired person is reading the corresponding Braille characters in said first portion. 11. The print medium of claim 10 , wherein said second portion is positioned above said first portion.
| 0.633094 |
9,396,332 | 8 | 9 |
8. The method of claim 1 , comprising: receiving user feedback to the moderation of the current user account event; and based on the user feedback, modifying one or more confidence weights associated with one or more decision structures to update one or more of the plurality of risk assessment models.
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8. The method of claim 1 , comprising: receiving user feedback to the moderation of the current user account event; and based on the user feedback, modifying one or more confidence weights associated with one or more decision structures to update one or more of the plurality of risk assessment models. 9. The method of claim 8 , the user feedback indicating that the current user passed a user authentication challenge.
| 0.5 |
9,805,027 | 1 | 2 |
1. A method performed by a computing device having at least one processor and a memory, the method comprising: receiving, from an application being executed by the at least one processor, a request to provide a first word for use by the application; determining a default language of the computing device; accessing, in the memory of the computing device, one or more resources; determining if the one or more resources include the first word in the default language by iteratively eliminating, based on identified qualifiers, resource directories for the one or more resources until only one resource directory remains, the one resource directory excluding resource files that contradict a configuration of the computing device; if the one or more resources include the first word in the default language, then providing, from the one resource directory, the first word to the application; and if the one or more resources do not include the first word in the default language, then: transmitting the first word and an indication of the default language to a translation server; receiving from the translation server a second word obtained by translating the first word into the default language; and providing the second word to the application.
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1. A method performed by a computing device having at least one processor and a memory, the method comprising: receiving, from an application being executed by the at least one processor, a request to provide a first word for use by the application; determining a default language of the computing device; accessing, in the memory of the computing device, one or more resources; determining if the one or more resources include the first word in the default language by iteratively eliminating, based on identified qualifiers, resource directories for the one or more resources until only one resource directory remains, the one resource directory excluding resource files that contradict a configuration of the computing device; if the one or more resources include the first word in the default language, then providing, from the one resource directory, the first word to the application; and if the one or more resources do not include the first word in the default language, then: transmitting the first word and an indication of the default language to a translation server; receiving from the translation server a second word obtained by translating the first word into the default language; and providing the second word to the application. 2. The method of claim 1 , wherein the one or more resources include resources stored as text files.
| 0.778761 |
8,683,318 | 8 | 13 |
8. A hardware computer-readable storage medium having stored therein computer-readable instructions that, when executed by a computer-based system for processing a document written in a markup language, implements operations comprising: creating, by the computer-based system, a template document using the markup language, wherein the template document includes a set of tags associated with the markup language; parsing, by the computer based system, the template document to retrieve the set of tags; creating, by the computer-based system, a linkage data structure corresponding to a second programming language different from the markup language, wherein the linkage data structure includes a field for each tag in the set of tags retrieved by the parsing; generating, by the computer based system, program code in the second programming language based on the set of tags retrieved by the parsing, wherein the generating comprises: creating a procedure division statement in the second programming language, wherein the procedure division statement is capable of accepting a document written in the markup language wherein the document is variable length, and wherein the procedure division statement is capable of returning a fixed format data structure corresponding to the linkage data structure, creating a second programming language section to contain the program code in the second programming language; producing by the procedure division statement and the second programming language section, the program code in the second programming language, wherein the program code is configured to extract, from the document written in the markup language, a plurality of tags associated with the markup language and at least one attribute associated with each tag; forming, by the computer-based system, an application programming interface (API) that includes the linkage data structure and the program code; and using, by the computer-based system, the application programming interface (API) to pass content from one or more documents written in the markup language to a program element of a program written in the second programming language.
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8. A hardware computer-readable storage medium having stored therein computer-readable instructions that, when executed by a computer-based system for processing a document written in a markup language, implements operations comprising: creating, by the computer-based system, a template document using the markup language, wherein the template document includes a set of tags associated with the markup language; parsing, by the computer based system, the template document to retrieve the set of tags; creating, by the computer-based system, a linkage data structure corresponding to a second programming language different from the markup language, wherein the linkage data structure includes a field for each tag in the set of tags retrieved by the parsing; generating, by the computer based system, program code in the second programming language based on the set of tags retrieved by the parsing, wherein the generating comprises: creating a procedure division statement in the second programming language, wherein the procedure division statement is capable of accepting a document written in the markup language wherein the document is variable length, and wherein the procedure division statement is capable of returning a fixed format data structure corresponding to the linkage data structure, creating a second programming language section to contain the program code in the second programming language; producing by the procedure division statement and the second programming language section, the program code in the second programming language, wherein the program code is configured to extract, from the document written in the markup language, a plurality of tags associated with the markup language and at least one attribute associated with each tag; forming, by the computer-based system, an application programming interface (API) that includes the linkage data structure and the program code; and using, by the computer-based system, the application programming interface (API) to pass content from one or more documents written in the markup language to a program element of a program written in the second programming language. 13. The computer-readable storage medium of claim 8 , wherein the length of the array is provided at run time based on at least one attribute associated with at least one tag parsed from the template document.
| 0.815697 |
6,115,709 | 42 | 48 |
42. The system of claim 33 wherein the confidence logic identifies a term within the content.
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42. The system of claim 33 wherein the confidence logic identifies a term within the content. 48. The system of claim 42 wherein the confidence logic determines a frequency with which the term occurs within a plurality of electronic documents associated with the first user.
| 0.5 |
8,126,713 | 1 | 5 |
1. A conversation control computer comprising a general-purpose computer for implementing a conversation controller and conversation control method according to a program therefor stored on a nontransitory physical storage medium operable with the general-purpose computer, the conversation control computer being configured to retrieve, based on input information received from a user, a reply sentence to the input information and comprising: a morpheme extracting unit configured to extract, based on a character string corresponding to the input information, at least one morpheme constituting a minimum unit of the character string, as first morpheme information; a conversation database configured to store pieces of second morpheme information each including a morpheme including a character, a string of characters or a combination thereof, and a plurality of reply sentences, which are associated with the pieces of second morpheme information; a topic search unit configured to compare, based on the first morpheme information extracted at the morpheme extracting unit, the first morpheme information with the pieces of second morpheme information, and to search a piece of second morpheme information including a portion of the first morpheme information from among the pieces of second morpheme information; a reply retrieval unit configured to retrieve, based on the piece of second morpheme information searched at the topic search unit, a reply sentence associated with the searched piece of second morpheme information; a topic identification information search unit configured to compare, based on the first morpheme information extracted at the morpheme extracting unit, the first morpheme information with pieces of topic identification information for identifying a topic, and to search a piece of topic identification information corresponding to the at least one morpheme constituting the first morpheme information from among the pieces of topic identification information, wherein the pieces of topic identification information are each associated with pieces of second morpheme information; the topic search unit is configured to compare, based on the searched piece of topic identification information, pieces of second morpheme information associated with the searched piece of topic identification information with the first morpheme information extracted at the morpheme extracting unit, and to search a piece of second morpheme information corresponding to the first morpheme information from among the pieces of second morpheme information associated with the searched piece of topic identification information; and an elliptical sentence supplementation unit configured to add the searched piece of topic identification information to the first morpheme information extracted at the morpheme extracting unit to provide a supplemented first morpheme information when no piece of second morpheme information including a portion of the extracted first morpheme information can be located by the search performed at the topic search unit, wherein, the topic search unit is configured to search, based on the supplemented first morpheme information, a piece of second morpheme information including a portion of the supplemented first morpheme information from among the pieces of second morpheme information.
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1. A conversation control computer comprising a general-purpose computer for implementing a conversation controller and conversation control method according to a program therefor stored on a nontransitory physical storage medium operable with the general-purpose computer, the conversation control computer being configured to retrieve, based on input information received from a user, a reply sentence to the input information and comprising: a morpheme extracting unit configured to extract, based on a character string corresponding to the input information, at least one morpheme constituting a minimum unit of the character string, as first morpheme information; a conversation database configured to store pieces of second morpheme information each including a morpheme including a character, a string of characters or a combination thereof, and a plurality of reply sentences, which are associated with the pieces of second morpheme information; a topic search unit configured to compare, based on the first morpheme information extracted at the morpheme extracting unit, the first morpheme information with the pieces of second morpheme information, and to search a piece of second morpheme information including a portion of the first morpheme information from among the pieces of second morpheme information; a reply retrieval unit configured to retrieve, based on the piece of second morpheme information searched at the topic search unit, a reply sentence associated with the searched piece of second morpheme information; a topic identification information search unit configured to compare, based on the first morpheme information extracted at the morpheme extracting unit, the first morpheme information with pieces of topic identification information for identifying a topic, and to search a piece of topic identification information corresponding to the at least one morpheme constituting the first morpheme information from among the pieces of topic identification information, wherein the pieces of topic identification information are each associated with pieces of second morpheme information; the topic search unit is configured to compare, based on the searched piece of topic identification information, pieces of second morpheme information associated with the searched piece of topic identification information with the first morpheme information extracted at the morpheme extracting unit, and to search a piece of second morpheme information corresponding to the first morpheme information from among the pieces of second morpheme information associated with the searched piece of topic identification information; and an elliptical sentence supplementation unit configured to add the searched piece of topic identification information to the first morpheme information extracted at the morpheme extracting unit to provide a supplemented first morpheme information when no piece of second morpheme information including a portion of the extracted first morpheme information can be located by the search performed at the topic search unit, wherein, the topic search unit is configured to search, based on the supplemented first morpheme information, a piece of second morpheme information including a portion of the supplemented first morpheme information from among the pieces of second morpheme information. 5. The conversation control computer as set forth in claim 1 , further comprising: a ranking unit configured to perform a ranking according to a frequency of search of a piece of second morpheme information at the topic search unit, wherein: the reply sentences are each associated with priority levels; and the reply retrieval unit is configured to compare the priority levels associated with the reply sentences with the rank determined at the ranking unit, to identify a priority level corresponding to the determined rank from among the priority levels, and to retrieve a reply sentence associated with the identified priority level; and the reply retrieval unit is configured to not retrieve the reply sentence when the rank determined at the ranking unit is the lowest.
| 0.567522 |
8,140,549 | 6 | 8 |
6. A computer program product for performing operations via a spreadsheet, the computer program product comprising: program instructions, stored on at least one of the one or more storage devices, to provide by a spreadsheet a dimension type, a dimension object comprising one or more elements and having a name; program instructions, stored on at least one of the one or more storage devices, to create by the spreadsheet a dimension object, the dimension object comprising one or more elements, the creating comprising: evaluating an expression entered into a text-based interface of the spreadsheet, wherein the expression includes a function and the dimension object is an output value of the function; and assigning to each element of the dimension object a name unique in the dimension object; and program instructions, stored on at least one of the one or more storage devices, to specify a sequence of the one or more elements.
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6. A computer program product for performing operations via a spreadsheet, the computer program product comprising: program instructions, stored on at least one of the one or more storage devices, to provide by a spreadsheet a dimension type, a dimension object comprising one or more elements and having a name; program instructions, stored on at least one of the one or more storage devices, to create by the spreadsheet a dimension object, the dimension object comprising one or more elements, the creating comprising: evaluating an expression entered into a text-based interface of the spreadsheet, wherein the expression includes a function and the dimension object is an output value of the function; and assigning to each element of the dimension object a name unique in the dimension object; and program instructions, stored on at least one of the one or more storage devices, to specify a sequence of the one or more elements. 8. The computer program product of claim 6 , wherein the program instructions to create by the spreadsheet a dimension object comprises: program instructions to create in the spreadsheet a filter object, wherein the filter object is a dimension object and each element of the filter object refers to an element of some other dimension object; and program instructions for a user to access the filter object by a name of the filter object.
| 0.594444 |
7,693,823 | 6 | 7 |
6. The method of claim 1 wherein the value of the frequency spectral for an angular frequency is represented by the following: S N ( λ ) = ∑ t = 1 N q t ⅇ - ⅈ λ t λ ∈ [ - π , π ] .
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6. The method of claim 1 wherein the value of the frequency spectral for an angular frequency is represented by the following: S N ( λ ) = ∑ t = 1 N q t ⅇ - ⅈ λ t λ ∈ [ - π , π ] . 7. The method of claim 6 wherein a peak is a locally maximum value of the frequency spectral within a range as represented by the following: S N ( λ j ) ≥ S N ( λ ) , where λ ∈ [ λ j - 1 / 2 N , λ j + 1 / 2 N ] .
| 0.5 |
10,013,977 | 6 | 7 |
6. A smart home control method comprising: acquiring a voice information from a user; performing a first emotion recognition for a speech tone of the voice information and generating a first emotion recognition result; converting the voice information into a text information; performing a second emotion recognition for a semantics of the text information and generating a second motion recognition result, comprising: selecting a plurality of commendatory words as commendatory-seed-words and a plurality of derogatory words as derogatory-seed-words and generating an emotion dictionary; respectively calculating a similarity between a plurality of words in the text information, the commendatory-seed-words and the derogatory-seed-words in the emotion dictionary; and generating the second emotion recognition result through a preset emotion recognition method for semantics, according to a word similarity; based on the first emotion recognition result and the second emotion recognition result, generating a user's emotion recognition result according to a preset determination method for emotion recognition result; based on the user's emotion recognition result, controlling a smart home device to perform a corresponding operation; wherein the first emotion recognition result is a commendatory emotion, while the second emotion recognition result is a derogatory emotion or the first emotion recognition result is a derogatory emotion, while the second emotion recognition result is a commendatory emotion, recollecting the voice information of the user; and redoing the first emotion recognition and the second emotion recognition for the voice information and generating a new first emotion recognition result and a new second emotion recognition result.
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6. A smart home control method comprising: acquiring a voice information from a user; performing a first emotion recognition for a speech tone of the voice information and generating a first emotion recognition result; converting the voice information into a text information; performing a second emotion recognition for a semantics of the text information and generating a second motion recognition result, comprising: selecting a plurality of commendatory words as commendatory-seed-words and a plurality of derogatory words as derogatory-seed-words and generating an emotion dictionary; respectively calculating a similarity between a plurality of words in the text information, the commendatory-seed-words and the derogatory-seed-words in the emotion dictionary; and generating the second emotion recognition result through a preset emotion recognition method for semantics, according to a word similarity; based on the first emotion recognition result and the second emotion recognition result, generating a user's emotion recognition result according to a preset determination method for emotion recognition result; based on the user's emotion recognition result, controlling a smart home device to perform a corresponding operation; wherein the first emotion recognition result is a commendatory emotion, while the second emotion recognition result is a derogatory emotion or the first emotion recognition result is a derogatory emotion, while the second emotion recognition result is a commendatory emotion, recollecting the voice information of the user; and redoing the first emotion recognition and the second emotion recognition for the voice information and generating a new first emotion recognition result and a new second emotion recognition result. 7. The smart home control method according to claim 6 , wherein, the step of respectively calculating a similarity between the plurality of words in the text information, the commendatory-seed-words and the derogatory-seed-words in the emotion dictionary, comprises: based on a calculation method for semantic similarity, calculating respectively the word similarity between the plurality of words in the text information and the commendatory-seed-words, and the word similarity between the plurality of words in the text information and the derogatory-seed-words.
| 0.512111 |
8,341,167 | 9 | 14 |
9. A computer system for generating a related search phrase to search a data repository, comprising: a processor; a keyword repository configured to relate each of a plurality of user-submitted keywords to at least one of a plurality of derivative keywords; a facet repository configured to store a contextual relationship between a keyword of the plurality of user-submitted keywords and a facet, wherein the facet is a term that is contextually related to the plurality of user-submitted keywords based on historical usage by multiple users of the user-submitted keywords when searching in a domain of a product; and a management engine executing on the processor and operatively connected to the facet repository, the management engine configured to: receive a first search phrase for a search within the domain of the product; evaluate the first search phrase based on the domain of the product, wherein evaluating the first search phrase comprises: obtaining the plurality of user-submitted keywords from the first search phrase, querying the keyword repository with at least two user-submitted keywords of the plurality of user-submitted keywords to obtain a derivative keyword of the plurality of derivative keywords, and identifying the facet from the facet repository using the plurality of user-submitted keywords based on the contextual relationship between the facet and the user-submitted keywords, wherein the facet, the derivative keyword, and the plurality of user-submitted keywords are used to obtain a plurality of search terms, apply a backward filter to revise the plurality of search terms into a second search phrase, and identifying a previously submitted question based on the facet, the derivative keyword, and the plurality of user-submitted keywords, wherein the second search phrase and the previously submitted question are displayed in a user interface.
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9. A computer system for generating a related search phrase to search a data repository, comprising: a processor; a keyword repository configured to relate each of a plurality of user-submitted keywords to at least one of a plurality of derivative keywords; a facet repository configured to store a contextual relationship between a keyword of the plurality of user-submitted keywords and a facet, wherein the facet is a term that is contextually related to the plurality of user-submitted keywords based on historical usage by multiple users of the user-submitted keywords when searching in a domain of a product; and a management engine executing on the processor and operatively connected to the facet repository, the management engine configured to: receive a first search phrase for a search within the domain of the product; evaluate the first search phrase based on the domain of the product, wherein evaluating the first search phrase comprises: obtaining the plurality of user-submitted keywords from the first search phrase, querying the keyword repository with at least two user-submitted keywords of the plurality of user-submitted keywords to obtain a derivative keyword of the plurality of derivative keywords, and identifying the facet from the facet repository using the plurality of user-submitted keywords based on the contextual relationship between the facet and the user-submitted keywords, wherein the facet, the derivative keyword, and the plurality of user-submitted keywords are used to obtain a plurality of search terms, apply a backward filter to revise the plurality of search terms into a second search phrase, and identifying a previously submitted question based on the facet, the derivative keyword, and the plurality of user-submitted keywords, wherein the second search phrase and the previously submitted question are displayed in a user interface. 14. The computer system of claim 9 , wherein a search term of the plurality of search terms is the derivative keyword, and wherein applying the backward filter comprises: correcting a spelling of the search term.
| 0.660256 |
8,793,199 | 9 | 10 |
9. The system of claim 8 , wherein generating the negative indicators further comprises: searching for the negative indicators in the training corpus using an N-gram parameter, wherein the N-gram parameter determines a maximum number of consecutive words for each phrase in which the negative indicators are found.
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9. The system of claim 8 , wherein generating the negative indicators further comprises: searching for the negative indicators in the training corpus using an N-gram parameter, wherein the N-gram parameter determines a maximum number of consecutive words for each phrase in which the negative indicators are found. 10. The system of claim 9 , wherein performing the positive terms test further comprises: searching for term modifiers within the maximum number of words according to the N-gram parameter, wherein the term modifiers modify the terms and the term variants.
| 0.5 |
8,589,383 | 19 | 20 |
19. The non-transitory computer storage medium of claim 18 , wherein providing one or more of the suggested answers includes providing one or more ranked suggested answers and wherein providing one or more ranked suggested answers includes: grouping similar suggested answers based on a semantic similarity measure; and ranking the suggested answers where each group of similar suggested answers is given a combined ranking.
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19. The non-transitory computer storage medium of claim 18 , wherein providing one or more of the suggested answers includes providing one or more ranked suggested answers and wherein providing one or more ranked suggested answers includes: grouping similar suggested answers based on a semantic similarity measure; and ranking the suggested answers where each group of similar suggested answers is given a combined ranking. 20. The non-transitory computer storage medium of claim 19 , wherein ranking the suggested answers further comprises: for each group of similar suggested answers, determining a rank score for the group by counting the instances that a suggested answer in the group was submitted or selected by a second user; for each distinct suggested answer, determining a rank score for the distinct suggested answer by counting the instances that the distinct suggested answer was submitted or selected by a second user; and ranking the distinct suggested answers and groups of similar suggested answers based on the determined rank scores.
| 0.5 |
8,274,520 | 31 | 32 |
31. The computer-readable storage medium of claim 28 , wherein returning the subcache in response to the filtering query involves indicating a maximum size allowed for the subcache and indicting a maximum age and a purgeable age for identifiers for images in the subcache.
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31. The computer-readable storage medium of claim 28 , wherein returning the subcache in response to the filtering query involves indicating a maximum size allowed for the subcache and indicting a maximum age and a purgeable age for identifiers for images in the subcache. 32. The computer-readable storage medium of claim 31 , wherein each subcache includes a maximum age and purgeable age limit, wherein the method further comprises: removing an identifier for an image from the cache if the identifier for the image is older than the maximum age limit, wherein removing the identifier for the image involves removing the underlying image from the location in memory or on disk; marking the identifier for the image as purgeable if the identifier for the image is older than the purgeable age; and wherein when an identifier for an image is marked as purgeable, the method further comprises removing the associated image from the location in memory if the location in memory is required for another purpose.
| 0.5 |
8,850,332 | 7 | 11 |
7. A computer hardware system, comprising: a web page authoring system having a user input system and an editing screen display for displaying a representation of a tag associated with a display artifact represented on the editing screen display, wherein, the web page authoring system is configured to perform: receiving a user action input selecting a reference point on the editing screen display for a web page being authored; setting a reference area on the editing screen display enclosing the selected reference point; selecting the display object closest to the reference point as a reference display artifact from among display artifacts in the reference area; selecting a tag associated with the reference display artifact from among tags associated with the display artifacts in the reference area; and drawing a first rectangle on the editing screen display artifact and a second, larger rectangle enclosing said first rectangle, a space between said first and second rectangles representing the selected tag, wherein the selected tag, associated with the first rectangle and the selected display object, includes an open tag and a corresponding close tag.
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7. A computer hardware system, comprising: a web page authoring system having a user input system and an editing screen display for displaying a representation of a tag associated with a display artifact represented on the editing screen display, wherein, the web page authoring system is configured to perform: receiving a user action input selecting a reference point on the editing screen display for a web page being authored; setting a reference area on the editing screen display enclosing the selected reference point; selecting the display object closest to the reference point as a reference display artifact from among display artifacts in the reference area; selecting a tag associated with the reference display artifact from among tags associated with the display artifacts in the reference area; and drawing a first rectangle on the editing screen display artifact and a second, larger rectangle enclosing said first rectangle, a space between said first and second rectangles representing the selected tag, wherein the selected tag, associated with the first rectangle and the selected display object, includes an open tag and a corresponding close tag. 11. The system of claim 7 , wherein storing web page data in a tree.
| 0.773333 |
6,054,990 | 1 | 6 |
1. A computer system for sketching an illustration and for writing annotations by a user, said computer system comprising: a processor; a memory device coupled to said processor; a display device coupled to said processor; an input device adapted to receive a user annotation or a sketch; a keypad coupled to said processor; a lens coupled to said processor, said lens adapted to capture an image; a shutter coupled to said processor; an image sensor coupled to said processor for detecting photographic conditions; a photographic media adapted to receive said image and said user annotation; a non-cursive handwriting recognizer adapted to receive a predetermined set of non-cursive characters from the input device; and an encoder adapted to be coupled to said processor and to said photographic media, said encoder adapted to archive said annotation and sketch and said image onto the photographic media.
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1. A computer system for sketching an illustration and for writing annotations by a user, said computer system comprising: a processor; a memory device coupled to said processor; a display device coupled to said processor; an input device adapted to receive a user annotation or a sketch; a keypad coupled to said processor; a lens coupled to said processor, said lens adapted to capture an image; a shutter coupled to said processor; an image sensor coupled to said processor for detecting photographic conditions; a photographic media adapted to receive said image and said user annotation; a non-cursive handwriting recognizer adapted to receive a predetermined set of non-cursive characters from the input device; and an encoder adapted to be coupled to said processor and to said photographic media, said encoder adapted to archive said annotation and sketch and said image onto the photographic media. 6. The computer system of claim 1, wherein said photographic media is a magnetic disk, further comprising a light receptor device coupled to said processor for capturing and digitizing said image.
| 0.858177 |
9,584,662 | 18 | 19 |
18. The computer-readable storage device of claim 17 , wherein the dialog call detail record comprises a prompt issued to a user and a response from the user.
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18. The computer-readable storage device of claim 17 , wherein the dialog call detail record comprises a prompt issued to a user and a response from the user. 19. The computer-readable storage device of claim 18 , wherein the dialog call detail record further comprises an interpretation of the response.
| 0.5 |
7,912,291 | 1 | 9 |
1. A method comprising: accessing header information from a multi-resolution codestream of compressed data of a first image; deriving one or more retrieval attributes solely from a bit distribution extracted from the header information; and performing image analysis based on the one or more retrieval attributes from the bit distribution extracted from header information, wherein the one or more retrieval attributes are non-image data that describe visual attributes of the first image, wherein the image analysis comprises similarity matching or clustering between the first image and a second image.
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1. A method comprising: accessing header information from a multi-resolution codestream of compressed data of a first image; deriving one or more retrieval attributes solely from a bit distribution extracted from the header information; and performing image analysis based on the one or more retrieval attributes from the bit distribution extracted from header information, wherein the one or more retrieval attributes are non-image data that describe visual attributes of the first image, wherein the image analysis comprises similarity matching or clustering between the first image and a second image. 9. The method defined in claim 1 wherein the first image comprises a scanned compound document.
| 0.939949 |
9,098,635 | 29 | 33 |
29. A computer program product that includes a non-transitory computer readable storage medium, the computer readable medium comprising a plurality of computer instructions which, when executed by a processor, cause the processor to execute performing a process for testing a user interface to a software application, the process comprising: extending a hardware verification language by defining one or more custom libraries such that the extended hardware verification language can be used to interface with the user interface to the software application in addition to hardware designs, wherein the hardware verification language is different from a programming language used to create the user interface to the software application, and is a programming language specifically designed for verification of hardware designs, and wherein the extended hardware verification language is extended by providing an API (applications programming interface) corresponding to the e language; generating a test for the user interface to the software application written in the extended hardware verification language; using the test written in the extended hardware verification language to drive one or more elements of the user interface to the software application; collecting data resulting from driving the user interface to the software application using the test; analyzing the data from driving the user interface to the software application; and displaying analysis results or storing the analysis results in a computer readable medium.
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29. A computer program product that includes a non-transitory computer readable storage medium, the computer readable medium comprising a plurality of computer instructions which, when executed by a processor, cause the processor to execute performing a process for testing a user interface to a software application, the process comprising: extending a hardware verification language by defining one or more custom libraries such that the extended hardware verification language can be used to interface with the user interface to the software application in addition to hardware designs, wherein the hardware verification language is different from a programming language used to create the user interface to the software application, and is a programming language specifically designed for verification of hardware designs, and wherein the extended hardware verification language is extended by providing an API (applications programming interface) corresponding to the e language; generating a test for the user interface to the software application written in the extended hardware verification language; using the test written in the extended hardware verification language to drive one or more elements of the user interface to the software application; collecting data resulting from driving the user interface to the software application using the test; analyzing the data from driving the user interface to the software application; and displaying analysis results or storing the analysis results in a computer readable medium. 33. The computer program product of claim 29 further comprising coverage analysis.
| 0.719178 |
7,818,340 | 12 | 13 |
12. A server comprising: a data processor; a memory, coupled to the data processor, for storing instructions and data; a sponsored concept receiver to receive a sponsored concept from a sponsoring company via a data network; an interface component to interface with a search engine, the search engine to produce search results from the one or more content datastores by matching a search query with content items stored in the one or more content datastores, the interface component to receive a first search query corresponding to a search by a first user, the first search query being used by the search engine to match with content items stored in the one or more content datastores, the first search query also being used to determine if the sponsored concept and the first search query fit within match criteria; a related query processor to determine if the sponsored concept and the first search query fit within match criteria, the related query processor to generate for the first user, if the sponsored concept and the first search query fit within match criteria, a first link enabling the first user to initiate a conversation between the first user and an agent of the sponsoring company, the first link being a user interface element that can be activated by the first user; a communication component to initiate a conversation between the first user and the agent of the sponsoring company upon activation of the first link; the interface component to receive a second search query corresponding to a search by a second user, the second search query being used by the search engine to match with content items stored in the one or more content datastores; the related query processor to determine if the first search query and the second search query fit within match criteria, the related query processor to generate for the first user, if the first search query and the second search query fit within match criteria, a second link enabling the first user to initiate a conversation between the first user and the second user, the second link being a user interface element that can be activated by the first user, the second link including at least a portion of the second search query from the second user; and the communication component to initiate a conversation between the first user and the second user upon activation of the second link.
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12. A server comprising: a data processor; a memory, coupled to the data processor, for storing instructions and data; a sponsored concept receiver to receive a sponsored concept from a sponsoring company via a data network; an interface component to interface with a search engine, the search engine to produce search results from the one or more content datastores by matching a search query with content items stored in the one or more content datastores, the interface component to receive a first search query corresponding to a search by a first user, the first search query being used by the search engine to match with content items stored in the one or more content datastores, the first search query also being used to determine if the sponsored concept and the first search query fit within match criteria; a related query processor to determine if the sponsored concept and the first search query fit within match criteria, the related query processor to generate for the first user, if the sponsored concept and the first search query fit within match criteria, a first link enabling the first user to initiate a conversation between the first user and an agent of the sponsoring company, the first link being a user interface element that can be activated by the first user; a communication component to initiate a conversation between the first user and the agent of the sponsoring company upon activation of the first link; the interface component to receive a second search query corresponding to a search by a second user, the second search query being used by the search engine to match with content items stored in the one or more content datastores; the related query processor to determine if the first search query and the second search query fit within match criteria, the related query processor to generate for the first user, if the first search query and the second search query fit within match criteria, a second link enabling the first user to initiate a conversation between the first user and the second user, the second link being a user interface element that can be activated by the first user, the second link including at least a portion of the second search query from the second user; and the communication component to initiate a conversation between the first user and the second user upon activation of the second link. 13. The server as claimed in claim 12 wherein the conversation initiated upon activation of the first link is initiated without installing application-specific software on the first user's system.
| 0.667797 |
9,280,766 | 4 | 6 |
4. A computer program product for determining EDI rules to enforce, comprising: a non-transitory computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to determine entity-specific rules from corresponding companion guides for each of a plurality of entities; computer usable program code configured to express each entity-specific rule in a neutral and machine readable format; computer usable program code configured to classify each of the entity-specific rules by determining for each entity-specific rule: whether the entity-specific rule is common with at least one other entity-specific rule, or whether the entity-specific rule is similar to at least one other entity-specific rule, Or whether the entity-specific rule is unique; computer usable program code configured to convey results of classifying the entity-specific rules by: creating an inventory of rules, the inventory including a common set of rules for the plurality of entities; dynamically adjusting said inventory of the rules based upon the entity-specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; storing the inventory of rules in a storage according to the classification of each rule as common, similar, or unique; creating a respective, corresponding pointer to the entity-specific rules in the inventory of rules associated with at least one of the plurality of entities; and storing the corresponding pointer in a storage for use in retrieving an appropriate current rule set when validating an EDI document for the at least one of the plurality of entities.
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4. A computer program product for determining EDI rules to enforce, comprising: a non-transitory computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to determine entity-specific rules from corresponding companion guides for each of a plurality of entities; computer usable program code configured to express each entity-specific rule in a neutral and machine readable format; computer usable program code configured to classify each of the entity-specific rules by determining for each entity-specific rule: whether the entity-specific rule is common with at least one other entity-specific rule, or whether the entity-specific rule is similar to at least one other entity-specific rule, Or whether the entity-specific rule is unique; computer usable program code configured to convey results of classifying the entity-specific rules by: creating an inventory of rules, the inventory including a common set of rules for the plurality of entities; dynamically adjusting said inventory of the rules based upon the entity-specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; storing the inventory of rules in a storage according to the classification of each rule as common, similar, or unique; creating a respective, corresponding pointer to the entity-specific rules in the inventory of rules associated with at least one of the plurality of entities; and storing the corresponding pointer in a storage for use in retrieving an appropriate current rule set when validating an EDI document for the at least one of the plurality of entities. 6. The computer program product of claim 4 , further comprising: computer usable program code configured to update the inventory of rules and the pointers in response to a change in the entity-specific rules.
| 0.867516 |
8,175,876 | 14 | 24 |
14. A system for end-point decision for a speech signal, the system comprising: a processor configured to: receive a plurality of frames of the speech signal; extract an energy parameter and a cepstral vector parameter for at least one frame of the plurality of frames; calculate a cepstral distance between the cepstral vector parameter and a silence mean cepstral vector; use a first condition to make a first end-point decision for the at least one frame of the plurality of frames by comparing the energy parameter to a first energy threshold; and use a second condition to make a second end-point decision for the at least one frame of the plurality of frames by comparing the energy parameter to a second energy threshold and by comparing the cepstral distance to a first cepstral distance threshold, wherein the second energy threshold is lower than the first energy threshold.
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14. A system for end-point decision for a speech signal, the system comprising: a processor configured to: receive a plurality of frames of the speech signal; extract an energy parameter and a cepstral vector parameter for at least one frame of the plurality of frames; calculate a cepstral distance between the cepstral vector parameter and a silence mean cepstral vector; use a first condition to make a first end-point decision for the at least one frame of the plurality of frames by comparing the energy parameter to a first energy threshold; and use a second condition to make a second end-point decision for the at least one frame of the plurality of frames by comparing the energy parameter to a second energy threshold and by comparing the cepstral distance to a first cepstral distance threshold, wherein the second energy threshold is lower than the first energy threshold. 24. The system of claim 14 , wherein the processor is further configured to: receive an initial plurality of frames of the speech signal; calculate the silence mean cepstral vector using the initial plurality of frames; calculate a silence cepstral distance of the initial plurality of frames using the silence mean cepstral vector; obtain the first cepstral distance threshold using the silence cepstral distance.
| 0.674528 |
8,983,955 | 7 | 8 |
7. The computer readable medium according to claim 1 , wherein said plurality of links comprises any data in addition to the text-based data.
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7. The computer readable medium according to claim 1 , wherein said plurality of links comprises any data in addition to the text-based data. 8. The computer readable medium according to claim 7 , wherein at least one of said plurality of links comprises code or markup that allows departure and destination points to be created between said plurality of predefined portions of text-based data.
| 0.5 |
9,466,073 | 10 | 12 |
10. The method of claim 1 , wherein the first content overlay information further enables the first user device to present a graphical visualization of: a second control that allows the user to indicate a favorable opinion of the relevant advertisement; a third control that, responsive to user selection, causes the first user device to present information relating to the use of the re-publishing control; and a fourth control that, responsive to user selection, causes the first user device to present information relating to the content of the relevant advertisement.
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10. The method of claim 1 , wherein the first content overlay information further enables the first user device to present a graphical visualization of: a second control that allows the user to indicate a favorable opinion of the relevant advertisement; a third control that, responsive to user selection, causes the first user device to present information relating to the use of the re-publishing control; and a fourth control that, responsive to user selection, causes the first user device to present information relating to the content of the relevant advertisement. 12. The method of claim 10 , wherein the first content overlay information further enables the first user device to present a graphical visualization of a fifth control that allows the user to specify users of the third-party content site that are permitted to view information on the user's interactions with the relevant advertisement or the re-publishing control.
| 0.5 |
10,143,913 | 1 | 10 |
1. A system for operating an interactive electronic multimedia puzzle, comprising: a puzzle generation engine comprising at least a plurality of programming instructions stored in a memory and operating on a processor of a computing device and configured to: load a plurality of multimedia content from a plurality of content sources, the multimedia content comprising at least visual content, the visual content being drawn from one or more of the set of video, image, and text; divide at least a portion of the multimedia content into a plurality of segments; associate at least a portion of the plurality of content segments with at least a portion of a plurality of puzzle tiles; present at least a portion of the plurality of puzzle tiles for interaction by a human user; receive a plurality of user interaction; and direct a rearrangement of puzzle tiles for presentation to a user, the rearrangement being based at least in part on at least a portion of the user interaction; wherein, for each tile of at least a subset of the tiles, a visual portion of the multimedia content of the respective tile is obfuscated using a plurality of transformations that effectively reduce utility of each affected tile's obfuscated media for solving the puzzle.
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1. A system for operating an interactive electronic multimedia puzzle, comprising: a puzzle generation engine comprising at least a plurality of programming instructions stored in a memory and operating on a processor of a computing device and configured to: load a plurality of multimedia content from a plurality of content sources, the multimedia content comprising at least visual content, the visual content being drawn from one or more of the set of video, image, and text; divide at least a portion of the multimedia content into a plurality of segments; associate at least a portion of the plurality of content segments with at least a portion of a plurality of puzzle tiles; present at least a portion of the plurality of puzzle tiles for interaction by a human user; receive a plurality of user interaction; and direct a rearrangement of puzzle tiles for presentation to a user, the rearrangement being based at least in part on at least a portion of the user interaction; wherein, for each tile of at least a subset of the tiles, a visual portion of the multimedia content of the respective tile is obfuscated using a plurality of transformations that effectively reduce utility of each affected tile's obfuscated media for solving the puzzle. 10. The system of claim 1 , wherein at least a portion of the content segments are obfuscated using electronic processing.
| 0.771536 |
9,331,965 | 1 | 10 |
1. A system for automatic generation of subject lines for electronic mail (email), comprising: a memory, and at least one processor operatively coupled to the memory; an extraction module executed via the at least one processor and capable of extracting topics from an email message; a prioritization module executed via the at least one processor and capable of computing a sender relevance score for each topic, and ranking the topics based on the sender relevance scores; a sorting module executed via the at least one processor and capable of ranking a plurality of syntactic units from the email message based on the topic ranking; and an assignment module executed via the at least one processor and capable of assigning one or more subject lines to the email message based on the ranking of the syntactic units; wherein the assignment module is further capable of: assigning different subject lines to the email message for each respective intended recipient of a plurality of intended recipients of the email message so that each respective intended recipient is sent the same email message with a different subject line from that of other intended recipients, wherein the different subject line corresponding to an intended recipient is determined based on one or more characteristics of the intended recipient; and assigning an identifying subject line different from the one or more of the subject lines assigned to the email message, the identifying subject line indicating one or more preferences of a sender of the email message and being visible to the sender and not visible to a recipient of the email message; wherein, when the sender receives a reply to the email message from the recipient, the reply email message includes the identifying subject line instead of the one or more of the subject lines assigned to the email message, or a combination of the identifying subject line and the one or more of the subject lines assigned to the email message.
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1. A system for automatic generation of subject lines for electronic mail (email), comprising: a memory, and at least one processor operatively coupled to the memory; an extraction module executed via the at least one processor and capable of extracting topics from an email message; a prioritization module executed via the at least one processor and capable of computing a sender relevance score for each topic, and ranking the topics based on the sender relevance scores; a sorting module executed via the at least one processor and capable of ranking a plurality of syntactic units from the email message based on the topic ranking; and an assignment module executed via the at least one processor and capable of assigning one or more subject lines to the email message based on the ranking of the syntactic units; wherein the assignment module is further capable of: assigning different subject lines to the email message for each respective intended recipient of a plurality of intended recipients of the email message so that each respective intended recipient is sent the same email message with a different subject line from that of other intended recipients, wherein the different subject line corresponding to an intended recipient is determined based on one or more characteristics of the intended recipient; and assigning an identifying subject line different from the one or more of the subject lines assigned to the email message, the identifying subject line indicating one or more preferences of a sender of the email message and being visible to the sender and not visible to a recipient of the email message; wherein, when the sender receives a reply to the email message from the recipient, the reply email message includes the identifying subject line instead of the one or more of the subject lines assigned to the email message, or a combination of the identifying subject line and the one or more of the subject lines assigned to the email message. 10. The system according to claim 1 , wherein the assignment module is further capable of assigning a plurality of the subject lines to the email message to be visible to an intended recipient in a configuration for displaying the plurality of the subject lines.
| 0.658854 |
10,133,477 | 9 | 27 |
9. A method, comprising: determining a user command based on user input, associated with displayed representation of at least one portion of one or more documents on a display medium of a computing device, wherein one or more portions of said one or more documents comprise a plurality of document locations, each accessible by one or more operations; automatically identifying one or more variables, associated with at least one operation, representing a plurality of at least one user chosen location based on at least one portion of said user command, and automatically determining one of said plurality of at least one user chosen location at which to apply said user command, wherein: said at least one operation is configured to automatically determine said one of said plurality of at least one user chosen location within said plurality of document locations based on said one or more variables, and said user command is associable with one or more: text characters or graphic elements, at said one of said plurality of at least one user chosen location.
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9. A method, comprising: determining a user command based on user input, associated with displayed representation of at least one portion of one or more documents on a display medium of a computing device, wherein one or more portions of said one or more documents comprise a plurality of document locations, each accessible by one or more operations; automatically identifying one or more variables, associated with at least one operation, representing a plurality of at least one user chosen location based on at least one portion of said user command, and automatically determining one of said plurality of at least one user chosen location at which to apply said user command, wherein: said at least one operation is configured to automatically determine said one of said plurality of at least one user chosen location within said plurality of document locations based on said one or more variables, and said user command is associable with one or more: text characters or graphic elements, at said one of said plurality of at least one user chosen location. 27. The method of claim 9 wherein said determining said user command comprises recognizing at least one portion of said user input.
| 0.82987 |
9,418,221 | 1 | 9 |
1. A method comprising: determining whether a user, who utilizes a computing device to interact with a computerized service, is either an authorized user or an attacker; wherein the determining comprises: generating a temporary input/output interference that causes an anomaly between (A) input gestures that the user performs via an input unit of said computing device, and (B) output that is displayed on a display unit of said computing device as a result of the input gestures; wherein the temporary input/output interference is a binary-type interference defined to trigger one of two possible manual user responses, wherein the two possible manual user responses comprise: a first possible manual user response that is performed by a majority of a general population of users; and a second possible manual user response that is performed by a minority of the general population of users; based on a level of uniqueness in the general population of users, of a particular response-to-interference that is identified in input-unit interactions of said user, determining whether or not to re-use said temporary input/output interference in subsequent usage sessions of said user; wherein the method further comprises: presenting to a user of an electronic device a screen comprising content and an advertisement; injecting a temporary input/output aberration that causes an on-screen pointer, that is on route to click within said advertisement, to deviate from its regular route; tracking user interactions with an input unit of said electronic device in response to said temporary input/output aberration; determining whether said user performed manual correction operations that fix said temporary input/output aberration; in response to determining that said user performed manual correction operations that fixed said temporary input/output aberration, determining that a click of said user within said advertisement was performed by a genuine user and not by a click-fraud mechanism; in response to determining that said user performed manual correction operations that did not fix said temporary input/output aberration, determining that a click of said user within said advertisement was performed by a click-fraud mechanism.
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1. A method comprising: determining whether a user, who utilizes a computing device to interact with a computerized service, is either an authorized user or an attacker; wherein the determining comprises: generating a temporary input/output interference that causes an anomaly between (A) input gestures that the user performs via an input unit of said computing device, and (B) output that is displayed on a display unit of said computing device as a result of the input gestures; wherein the temporary input/output interference is a binary-type interference defined to trigger one of two possible manual user responses, wherein the two possible manual user responses comprise: a first possible manual user response that is performed by a majority of a general population of users; and a second possible manual user response that is performed by a minority of the general population of users; based on a level of uniqueness in the general population of users, of a particular response-to-interference that is identified in input-unit interactions of said user, determining whether or not to re-use said temporary input/output interference in subsequent usage sessions of said user; wherein the method further comprises: presenting to a user of an electronic device a screen comprising content and an advertisement; injecting a temporary input/output aberration that causes an on-screen pointer, that is on route to click within said advertisement, to deviate from its regular route; tracking user interactions with an input unit of said electronic device in response to said temporary input/output aberration; determining whether said user performed manual correction operations that fix said temporary input/output aberration; in response to determining that said user performed manual correction operations that fixed said temporary input/output aberration, determining that a click of said user within said advertisement was performed by a genuine user and not by a click-fraud mechanism; in response to determining that said user performed manual correction operations that did not fix said temporary input/output aberration, determining that a click of said user within said advertisement was performed by a click-fraud mechanism. 9. The method of claim 1 , wherein generating the temporary input/output interference comprises: temporarily hiding an on-screen pointer at the output unit of said computing device; defining the first possible manual response as movement of the input unit by the user; defining the second possible manual response as clicking a button of the input unit by the user; wherein detecting the manual correction operation of said user comprises: determining whether said user performed a manual correction operation having either movement of the input unit or clicking the button of the input unit.
| 0.850051 |
9,361,883 | 11 | 13 |
11. The method of claim 10 , wherein said providing the at least one option to modify the selected part of the rendered text comprises: receiving a selection of a part of the rendered text, to provide the selected part; and providing a menu that includes a plurality of options regarding different respective ways in which the selected part is modifiable.
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11. The method of claim 10 , wherein said providing the at least one option to modify the selected part of the rendered text comprises: receiving a selection of a part of the rendered text, to provide the selected part; and providing a menu that includes a plurality of options regarding different respective ways in which the selected part is modifiable. 13. The method of claim 11 , wherein the plurality of options include at least one of: an option to choose an alternative word or phrase to replace the selected part; an option to add a punctuation mark to the selected part; an option to add formatting to the selected part; an option to delete the selected part; an option to spell out the selected part by voice; an option to invoke a soft keyboard; and an option to re-speak the selected part.
| 0.5 |
8,244,804 | 5 | 6 |
5. The method of claim 1 , the executing of the script at the server device comprising: in the server-side application executing on the server device, creating a second object associated with a second method, the second method to receive the text file and at least one second input parameter, and the second method to invoke a second script evaluation engine to execute the script on the server device using the at least one second input parameter to produce the second result; and in the server-side application executing on the server device, initiating execution of the script using the second method by passing a reference to the script and the input data to the second method, the input data being used in the second method for the at least one second input parameter.
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5. The method of claim 1 , the executing of the script at the server device comprising: in the server-side application executing on the server device, creating a second object associated with a second method, the second method to receive the text file and at least one second input parameter, and the second method to invoke a second script evaluation engine to execute the script on the server device using the at least one second input parameter to produce the second result; and in the server-side application executing on the server device, initiating execution of the script using the second method by passing a reference to the script and the input data to the second method, the input data being used in the second method for the at least one second input parameter. 6. The method of claim 5 , further comprising: retrieving a value associated with the user of the client device from a database in response to receiving the input data, the value representing a status of the user in the online game; passing the value to the second method to initiate the execution of the script, the value being used in the second method for the at least one second input parameter.
| 0.5 |
9,940,581 | 13 | 14 |
13. A computer system for distinguishing a business rule from a non-business rule in a computer program, the computer system comprising: one or more processors; one or more computer-readable memories; one or more computer-readable storage devices; and program instructions stored on the one or more storage devices for execution by the one or more processors via the one or more memories, the program instructions comprising: first program instructions to identify a first rule in the computer program based on a conditional statement within the first rule; second program instructions to determine whether the first rule performs an underlying operation of the program, the underlying operation being independent of a business function of the program, by determining whether the first rule includes a first key word which indicates the underlying operation, which is a housekeeping process, exception handling, error checking, data validation, parameter cleanup, a reservation of computer memory, or a buffer setup; third program instructions to determine whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program; fourth program instructions to, if the first rule includes the first key word or the sequence of program steps in the first rule matches the predetermined sequence of steps indicative of the underlying operation of the program independent of the business function of the program, determine the first rule is a non-business rule, or if the first rule does not include the first key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program: search the first rule and metadata of the first rule for a second key word which indicates part of a business transaction with a customer of a business using the computer program; determine whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of a business rule; and if the first rule includes the second key word, the metadata of the first rule includes the second key word, or the sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determine the first rule is the business rule, or if the first rule and the metadata of the first rule do not include the second key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determine the first rule is not classifiable as the business rule or the non-business rule; sixth program instructions to receive a first set of one or more semantic tags specifying a first candidate business rule in the computer program, the first candidate business rule being initially not classifiable as a first actual business rule or a first actual non-business rule; seventh program instructions to, based on the first set of one or more semantic tags, determine the first candidate business rule is specified by a pattern expressed in a context-free grammar for a programming language of the computer program, the pattern specifying a code structure included in the first candidate business rule, the pattern being included in a class of an ontology, and the class identifying a concept of the programming language; eighth program instructions to determine that a confidence level of the pattern is less than a first threshold, the confidence level indicating how likely the first candidate business rule is the first actual business rule, and the ontology associating the pattern with the confidence level; ninth program instructions to, based on the confidence level being less than the first threshold, determine a lack of confidence in the first candidate business rule being the first actual business rule; tenth program instructions to receive other sets of one or more semantic tags specifying other candidate business rules, each of the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, and each of the other candidate business rules being not classifiable as an actual business rule or an actual non-business rule; eleventh program instructions to, based on the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, determine the other candidate business rules are specified by the pattern that also specifies the first candidate business rule; twelfth program instructions to, based on the other candidate business rules being specified by the pattern that also specifies the first candidate business rule, determine that the other candidate business rules include the code structure specified by the pattern; thirteenth program instructions to determine a count of candidate business rules among the first candidate business rule and the other candidate business rules that include the code structure specified by the pattern; fourteenth program instructions to determine that the count of the candidate business rules exceeds a second threshold; fifteenth program instructions to, based on the count of the candidate business rules exceeding the second threshold, increase the confidence level of the pattern which indicates an increase in a likelihood that the candidate business rules are actual business rules; sixteenth program instructions to update the ontology to associate the pattern with the increased confidence level; seventeenth program instructions to determine the increased confidence level of the pattern is greater than the first threshold; eighteenth program instructions to, subsequent to the step of determining the increased confidence level is greater than the first threshold, receive a second set of one or more semantic tags specifying a second candidate business rule in the computer program or in another computer program; nineteenth program instructions to determine that the second candidate business rule includes the code structure specified by the pattern and determine that the second set of one or more semantic tags matches the first set of one or more semantic tags; and twentieth program instructions to, based on the second candidate business rule including the code structure specified by the pattern, the second set of one or more semantic tags matching the first set of one or more semantic tags, and the updated ontology associating the pattern with the increased confidence level, automatically determine that the second candidate business rule is a second actual business rule and display the second candidate business rule as the second actual business rule, without a manual classification of the second candidate business rule as the second actual business rule by a human expert.
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13. A computer system for distinguishing a business rule from a non-business rule in a computer program, the computer system comprising: one or more processors; one or more computer-readable memories; one or more computer-readable storage devices; and program instructions stored on the one or more storage devices for execution by the one or more processors via the one or more memories, the program instructions comprising: first program instructions to identify a first rule in the computer program based on a conditional statement within the first rule; second program instructions to determine whether the first rule performs an underlying operation of the program, the underlying operation being independent of a business function of the program, by determining whether the first rule includes a first key word which indicates the underlying operation, which is a housekeeping process, exception handling, error checking, data validation, parameter cleanup, a reservation of computer memory, or a buffer setup; third program instructions to determine whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program; fourth program instructions to, if the first rule includes the first key word or the sequence of program steps in the first rule matches the predetermined sequence of steps indicative of the underlying operation of the program independent of the business function of the program, determine the first rule is a non-business rule, or if the first rule does not include the first key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program: search the first rule and metadata of the first rule for a second key word which indicates part of a business transaction with a customer of a business using the computer program; determine whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of a business rule; and if the first rule includes the second key word, the metadata of the first rule includes the second key word, or the sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determine the first rule is the business rule, or if the first rule and the metadata of the first rule do not include the second key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determine the first rule is not classifiable as the business rule or the non-business rule; sixth program instructions to receive a first set of one or more semantic tags specifying a first candidate business rule in the computer program, the first candidate business rule being initially not classifiable as a first actual business rule or a first actual non-business rule; seventh program instructions to, based on the first set of one or more semantic tags, determine the first candidate business rule is specified by a pattern expressed in a context-free grammar for a programming language of the computer program, the pattern specifying a code structure included in the first candidate business rule, the pattern being included in a class of an ontology, and the class identifying a concept of the programming language; eighth program instructions to determine that a confidence level of the pattern is less than a first threshold, the confidence level indicating how likely the first candidate business rule is the first actual business rule, and the ontology associating the pattern with the confidence level; ninth program instructions to, based on the confidence level being less than the first threshold, determine a lack of confidence in the first candidate business rule being the first actual business rule; tenth program instructions to receive other sets of one or more semantic tags specifying other candidate business rules, each of the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, and each of the other candidate business rules being not classifiable as an actual business rule or an actual non-business rule; eleventh program instructions to, based on the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, determine the other candidate business rules are specified by the pattern that also specifies the first candidate business rule; twelfth program instructions to, based on the other candidate business rules being specified by the pattern that also specifies the first candidate business rule, determine that the other candidate business rules include the code structure specified by the pattern; thirteenth program instructions to determine a count of candidate business rules among the first candidate business rule and the other candidate business rules that include the code structure specified by the pattern; fourteenth program instructions to determine that the count of the candidate business rules exceeds a second threshold; fifteenth program instructions to, based on the count of the candidate business rules exceeding the second threshold, increase the confidence level of the pattern which indicates an increase in a likelihood that the candidate business rules are actual business rules; sixteenth program instructions to update the ontology to associate the pattern with the increased confidence level; seventeenth program instructions to determine the increased confidence level of the pattern is greater than the first threshold; eighteenth program instructions to, subsequent to the step of determining the increased confidence level is greater than the first threshold, receive a second set of one or more semantic tags specifying a second candidate business rule in the computer program or in another computer program; nineteenth program instructions to determine that the second candidate business rule includes the code structure specified by the pattern and determine that the second set of one or more semantic tags matches the first set of one or more semantic tags; and twentieth program instructions to, based on the second candidate business rule including the code structure specified by the pattern, the second set of one or more semantic tags matching the first set of one or more semantic tags, and the updated ontology associating the pattern with the increased confidence level, automatically determine that the second candidate business rule is a second actual business rule and display the second candidate business rule as the second actual business rule, without a manual classification of the second candidate business rule as the second actual business rule by a human expert. 14. The computer system of claim 13 , further comprising: twenty-first program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to receive, subsequent to an execution of the fourth program instructions to determine the first rule is not classifiable as the business rule or the non-business rule, manual classifications of the first rule and one or more other rules in the computer program or in other computer program(s) as the business rule; twenty-second program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to receive a pattern of semantic tags specifying the first rule and each of the one or more other rules; twenty-third program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to determine a count of the received manual classifications exceeds a predetermined threshold; twenty-fourth program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to update, based on the count exceeding the threshold and the pattern of semantic tags specifying the first rule and each of the one or more other rules, an ontology to include an association between the pattern of semantic tags and the business rule; twenty-fifth program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to identify, subsequent to an update of the ontology by an execution of the twenty-fourth program instructions to update, a second rule in the computer program or in another computer program based on a conditional statement within the second rule; twenty-sixth program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to determine the pattern of semantic tags included in the ontology specifies the second rule; and twenty-seventh program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to automatically determine, based on (1) the ontology including the association between the pattern of semantic tags and the business rule and (2) the pattern of semantic tags specifying the second rule, the second rule is the business rule.
| 0.518341 |
7,528,990 | 1 | 11 |
1. An image-forming system configured to perform at least a first operation to input image data, a second operation to process said image data and form a print finish, and a third operation to display an expected image finish as a result of said first and said second operations, comprising: a finish information generation unit configured to generate expected image finish information on completion of said first and said second operations; an input setting screen information generation unit configured to generate input setting screen information for receiving a setting input by an operator based on said expected image finish information generated by said finish information generation unit; a display unit configured to display on a display unit an expected image finish resulting from said expected image finish information and an input setting screen resulting from said input setting screen information generated by said input setting screen information generation unit; and a setting unit configured to receive a variety of setting inputs including said setting input by the operator by way of said input setting screen displayed on said display unit, wherein, on receiving said variety of setting inputs by said setting unit: said finish information generation unit generates said expected image finish information based on said variety of setting inputs currently received, said input setting screen information generation unit generates said input setting screen information based on said expected image finish information generated by said finish information generation unit, said display unit displays said expected image finish resulting from said expected image finish information and said input setting screen resulting from said input setting screen information generated by said input setting screen information generation unit, and said setting unit receives said variety of setting inputs including said setting input by the operator by way of said input setting screen displayed on said display unit.
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1. An image-forming system configured to perform at least a first operation to input image data, a second operation to process said image data and form a print finish, and a third operation to display an expected image finish as a result of said first and said second operations, comprising: a finish information generation unit configured to generate expected image finish information on completion of said first and said second operations; an input setting screen information generation unit configured to generate input setting screen information for receiving a setting input by an operator based on said expected image finish information generated by said finish information generation unit; a display unit configured to display on a display unit an expected image finish resulting from said expected image finish information and an input setting screen resulting from said input setting screen information generated by said input setting screen information generation unit; and a setting unit configured to receive a variety of setting inputs including said setting input by the operator by way of said input setting screen displayed on said display unit, wherein, on receiving said variety of setting inputs by said setting unit: said finish information generation unit generates said expected image finish information based on said variety of setting inputs currently received, said input setting screen information generation unit generates said input setting screen information based on said expected image finish information generated by said finish information generation unit, said display unit displays said expected image finish resulting from said expected image finish information and said input setting screen resulting from said input setting screen information generated by said input setting screen information generation unit, and said setting unit receives said variety of setting inputs including said setting input by the operator by way of said input setting screen displayed on said display unit. 11. The image-forming system according to claim 1 , wherein: said finish information generation unit generates expected image finish information containing text information, said input setting screen information generation unit generates an input setting screen information containing said text information based on said expected image finish information containing said text information, said display unit displays said expected image finish containing said text information and said input setting screen containing said text information, and said setting unit receives a variety of setting inputs containing said text information.
| 0.5 |
8,813,027 | 10 | 14 |
10. A computer-readable storage memory comprising computer-executable instructions which when executed cause at least one processor to: provide static type checking against an external data source in an interactive editing environment by: providing an extension point for the external data source, the extension point accessed by a public application programming interface, the public application programming interface providing an interface to an extension customized for the external data source, the extension comprising logic specific to the external data source and specific to how information from the external data source is to appear within a programming language type system within the interactive editing environment, wherein data of the external data source is dynamically accessible by calling a method on the external data source to receive the data; implementing the interface by creating a class that inherits from a system synthetic type so that a synthetic class is created for the external data source, the synthetic class representing a hosted model; importing types marked with an attribute denoting the extension and transforming the imported types into internal representations based on methods inherited from the system synthetic type; generating code when a call is made on the system synthetic type or when a method is invoked on the system synthetic type that calls a method invocation on the synthetic class for the hosted model; and replacing the synthetic types with dynamic calls to the external data source during compilation, wherein the external data source comprises at least one of an instance of a database, an Extensible Markup Language (XML) file containing data specific to a domain, a spreadsheet containing data pertaining to a specific domain or a web.
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10. A computer-readable storage memory comprising computer-executable instructions which when executed cause at least one processor to: provide static type checking against an external data source in an interactive editing environment by: providing an extension point for the external data source, the extension point accessed by a public application programming interface, the public application programming interface providing an interface to an extension customized for the external data source, the extension comprising logic specific to the external data source and specific to how information from the external data source is to appear within a programming language type system within the interactive editing environment, wherein data of the external data source is dynamically accessible by calling a method on the external data source to receive the data; implementing the interface by creating a class that inherits from a system synthetic type so that a synthetic class is created for the external data source, the synthetic class representing a hosted model; importing types marked with an attribute denoting the extension and transforming the imported types into internal representations based on methods inherited from the system synthetic type; generating code when a call is made on the system synthetic type or when a method is invoked on the system synthetic type that calls a method invocation on the synthetic class for the hosted model; and replacing the synthetic types with dynamic calls to the external data source during compilation, wherein the external data source comprises at least one of an instance of a database, an Extensible Markup Language (XML) file containing data specific to a domain, a spreadsheet containing data pertaining to a specific domain or a web. 14. The computer-readable storage memory of claim 10 , comprising further computer-executable instructions, which when executed cause the at least one processor to: provide an interface to an extension for an external data source comprising an database, a spread sheet or a domain specific model.
| 0.503356 |
8,880,438 | 1 | 7 |
1. A computer-implemented method for ranking relevance of parameters of a content item, the method comprising: receiving, using at least one processing circuit, a plurality of parameters of a content item and a plurality of corresponding initial relevance scores of the parameters indicating relevance of the parameters to the content item; estimating, using a statistical model, a plurality of revised relevance scores from the initial relevance scores, wherein each of the revised relevance scores is a function of at least two of the plurality of initial relevance scores; and ranking the plurality of parameters based on the revised relevance scores.
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1. A computer-implemented method for ranking relevance of parameters of a content item, the method comprising: receiving, using at least one processing circuit, a plurality of parameters of a content item and a plurality of corresponding initial relevance scores of the parameters indicating relevance of the parameters to the content item; estimating, using a statistical model, a plurality of revised relevance scores from the initial relevance scores, wherein each of the revised relevance scores is a function of at least two of the plurality of initial relevance scores; and ranking the plurality of parameters based on the revised relevance scores. 7. The method of claim 1 , further comprising receiving a bid for an online slot for the content item based on the ranking.
| 0.74898 |
9,690,526 | 1 | 3 |
1. A printer processing method comprising: providing a printer with a mark-up language parsing unit interpreting mark-up language data written in a mark-up language; wherein: the printer receives first mark-up language data from (POS) application; the mark-up language parsing unit executes a first binary data conversion step for converting the first mark-up language data received from the POS application to first binary data executable by the printer based on model-dependent information that is specific to the printer and that defines conversion rules for character attributes and printer control commands, and executes a second binary data conversion step for converting second binary data generated by the printer to second mark-up language data based on the model-dependent information that is specific to the printer, and that further defines a rule for converting the second binary data to the second mark-up language data; the second mark-up language data is sent to the POS application; the second binary data generated by the printer is printer status information; the POS application runs on a host device remote from the printer; the first mark-up language data is part of a first mark-up language document output from the POS application, the POS application executing a transaction process and generating transaction data; the mark-up language parsing unit further executes a status information conversion step for converting the printer status information to the second mark-up language data based on the model-dependent information that is specific to the printer and that defines the rule for converting the second binary data to the second mark-UP language data; and when the second mark-up language data is sent to the POS application, the second mark-up language data is sent as a second mark-up language document to the POS application.
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1. A printer processing method comprising: providing a printer with a mark-up language parsing unit interpreting mark-up language data written in a mark-up language; wherein: the printer receives first mark-up language data from (POS) application; the mark-up language parsing unit executes a first binary data conversion step for converting the first mark-up language data received from the POS application to first binary data executable by the printer based on model-dependent information that is specific to the printer and that defines conversion rules for character attributes and printer control commands, and executes a second binary data conversion step for converting second binary data generated by the printer to second mark-up language data based on the model-dependent information that is specific to the printer, and that further defines a rule for converting the second binary data to the second mark-up language data; the second mark-up language data is sent to the POS application; the second binary data generated by the printer is printer status information; the POS application runs on a host device remote from the printer; the first mark-up language data is part of a first mark-up language document output from the POS application, the POS application executing a transaction process and generating transaction data; the mark-up language parsing unit further executes a status information conversion step for converting the printer status information to the second mark-up language data based on the model-dependent information that is specific to the printer and that defines the rule for converting the second binary data to the second mark-UP language data; and when the second mark-up language data is sent to the POS application, the second mark-up language data is sent as a second mark-up language document to the POS application. 3. The printer processing method of claim 1 , wherein the first and second mark-up language documents are XML documents.
| 0.907264 |
9,971,834 | 4 | 5 |
4. The system according to claim 3 , wherein the system also comprises: a polyphonic word database and a phoneticizing unit; and wherein the memory further storing instructions that upon execution by the processor cause the system to: store Chinese character(s) and a marked Pinyin corresponding to the Chinese character(s); query the polyphonic word database to acquire the marked Pinyin corresponding to the input Chinese character when the number of the primary recommended word(s) is less than a preset threshold value; query again the recommended word database according to the Pinyin mark to acquire extended Chinese character(s) corresponding to the Pinyin mark; query the search tree storage unit according to the extended Chinese character(s) to acquire address information of extended recommended word(s) with the extended Chinese character(s) as a prefix; and query the recommended word database according to the address information of the mentioned extended recommended word(s) to acquire the extended recommended word(s) and then suggest the extended recommended word(s) to a user.
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4. The system according to claim 3 , wherein the system also comprises: a polyphonic word database and a phoneticizing unit; and wherein the memory further storing instructions that upon execution by the processor cause the system to: store Chinese character(s) and a marked Pinyin corresponding to the Chinese character(s); query the polyphonic word database to acquire the marked Pinyin corresponding to the input Chinese character when the number of the primary recommended word(s) is less than a preset threshold value; query again the recommended word database according to the Pinyin mark to acquire extended Chinese character(s) corresponding to the Pinyin mark; query the search tree storage unit according to the extended Chinese character(s) to acquire address information of extended recommended word(s) with the extended Chinese character(s) as a prefix; and query the recommended word database according to the address information of the mentioned extended recommended word(s) to acquire the extended recommended word(s) and then suggest the extended recommended word(s) to a user. 5. The system according to claim 4 , wherein a combination of Pinyin is used to correspond to Chinese phrases containing polyphone in the polyphonic word database.
| 0.5 |
7,870,085 | 2 | 3 |
2. The method of claim 1 , further comprising: receiving, by said inference engine, second sensor cohort data associated with a second cohort, said second cohort located within said first aircraft; receiving, by said inference engine, second group technology inferences associated with said second cohort; generating, by said inference engine, second risk cohort inferences, said generating said second risk cohort inferences based on said second group technology inferences and said second sensor cohort data; receiving, by said inference engine, seventh inference data generated by said inference engine, said seventh inference data comprising a seventh plurality of inferences associated with said second cohort and said security perimeter area surrounding said airport; receiving, by said inference engine, eighth inference data generated by said inference engine, said eighth inference data comprising an eighth plurality of inferences associated with said second cohort and said pre/post security area within said airport; receiving, by said inference engine, ninth inference data generated by said inference engine, said ninth inference data comprising a ninth plurality of inferences associated with said second cohort and said gate area within said airport; receiving, by said inference engine, tenth inference data generated by said inference engine, said tenth inference data comprising a tenth of plurality of inferences associated with said second cohort and said second aircraft; generating, by said inference engine, eleventh inference data, said eleventh inference data comprising an eleventh plurality of inferences associated with said second cohort, wherein said generating said eleventh inference data is based on second risk cohort inferences, said seventh inference data, said eighth inference data, said ninth inference data, and said tenth inference data; generating, by said inference engine based on said eleventh inference data, a second associated risk level score for said second cohort; and storing, by said computing system, said eleventh inference data and said second associated risk level score.
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2. The method of claim 1 , further comprising: receiving, by said inference engine, second sensor cohort data associated with a second cohort, said second cohort located within said first aircraft; receiving, by said inference engine, second group technology inferences associated with said second cohort; generating, by said inference engine, second risk cohort inferences, said generating said second risk cohort inferences based on said second group technology inferences and said second sensor cohort data; receiving, by said inference engine, seventh inference data generated by said inference engine, said seventh inference data comprising a seventh plurality of inferences associated with said second cohort and said security perimeter area surrounding said airport; receiving, by said inference engine, eighth inference data generated by said inference engine, said eighth inference data comprising an eighth plurality of inferences associated with said second cohort and said pre/post security area within said airport; receiving, by said inference engine, ninth inference data generated by said inference engine, said ninth inference data comprising a ninth plurality of inferences associated with said second cohort and said gate area within said airport; receiving, by said inference engine, tenth inference data generated by said inference engine, said tenth inference data comprising a tenth of plurality of inferences associated with said second cohort and said second aircraft; generating, by said inference engine, eleventh inference data, said eleventh inference data comprising an eleventh plurality of inferences associated with said second cohort, wherein said generating said eleventh inference data is based on second risk cohort inferences, said seventh inference data, said eighth inference data, said ninth inference data, and said tenth inference data; generating, by said inference engine based on said eleventh inference data, a second associated risk level score for said second cohort; and storing, by said computing system, said eleventh inference data and said second associated risk level score. 3. The method of claim 2 , further comprising: receiving, by said inference engine, twelfth inference data generated by said inference engine, said twelfth inference data comprising a twelfth plurality of inferences associated with said second cohort and said aircraft, wherein said generating said eleventh inference data is further based on said twelfth inference data.
| 0.5 |
9,240,178 | 3 | 6 |
3. A non-transitory computer-readable storage medium storing processor-executable instructions for controlling a computing device, comprising program code to: receive a first text-to-speech (TTS) request including a representation of first text; process the representation of first text using a first voice corpus to produce a first TTS output; send the first TTS output to a first device; store the representation of the first text; process the representation of first text using a second voice corpus to produce a second TTS output, the second voice corpus being different from the first voice corpus; store the second TTS output; receive a second TTS request including a representation of second text; compare the representation of second text to the representation of first text; and determine a third TTS output using at least a portion of the second TTS output, the third TTS output corresponding to the representation of second text.
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3. A non-transitory computer-readable storage medium storing processor-executable instructions for controlling a computing device, comprising program code to: receive a first text-to-speech (TTS) request including a representation of first text; process the representation of first text using a first voice corpus to produce a first TTS output; send the first TTS output to a first device; store the representation of the first text; process the representation of first text using a second voice corpus to produce a second TTS output, the second voice corpus being different from the first voice corpus; store the second TTS output; receive a second TTS request including a representation of second text; compare the representation of second text to the representation of first text; and determine a third TTS output using at least a portion of the second TTS output, the third TTS output corresponding to the representation of second text. 6. The non-transitory computer-readable storage medium of claim 3 , further comprising program code to send the third TTS output to a second device, the second device being different from the first device.
| 0.691265 |
8,484,083 | 16 | 28 |
16. A non-transitory computer readable storage medium storing an executable program for sending a message in a social network, where the program performs steps of: receiving from a source of the message or from a user a keyword relating to a subject of the message; retrieving from an ontology source a normalized set of concepts associated with the keyword, wherein the ontology source comprises at least one community-generated ontology source; collecting information from the social network, the information comprising one or more interactions between users of the social network and profile information for the users; identifying a subset of the information that corresponds to the normalized set of concepts, wherein the subset of the information is used to form a global topic model comprising at least one topic; sending the message to at least one of the users of the social network who is associated with the at least one topic; and dynamically updating the global topic model as new information is collected from the social network.
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16. A non-transitory computer readable storage medium storing an executable program for sending a message in a social network, where the program performs steps of: receiving from a source of the message or from a user a keyword relating to a subject of the message; retrieving from an ontology source a normalized set of concepts associated with the keyword, wherein the ontology source comprises at least one community-generated ontology source; collecting information from the social network, the information comprising one or more interactions between users of the social network and profile information for the users; identifying a subset of the information that corresponds to the normalized set of concepts, wherein the subset of the information is used to form a global topic model comprising at least one topic; sending the message to at least one of the users of the social network who is associated with the at least one topic; and dynamically updating the global topic model as new information is collected from the social network. 28. The non-transitory computer readable storage medium of claim 16 , wherein the ontology source comprises mapped words extracted from at least one of the one or more interactions and the profile information.
| 0.714481 |
8,705,706 | 23 | 24 |
23. A method comprising: recording to a first file, by a data-processing system, a first utterance in response to a first event in a voice-response system; recording to a second file, by the data-processing system, a second utterance in response to a second event in a voice-response system; storing in a database: (i) the first file, (ii) an association between the first file and the first event, (iii) the second file, and (iv) an association between the second file and the second event; receiving at the database a first signal that indicates selection of a link and a telephone number of the caller; in response to the receipt of the first signal, retrieving from the database those files that are associated with the link and with the telephone number, wherein the first utterance is associated with selected elements of a call that are of interest; and playing the first utterance to a user.
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23. A method comprising: recording to a first file, by a data-processing system, a first utterance in response to a first event in a voice-response system; recording to a second file, by the data-processing system, a second utterance in response to a second event in a voice-response system; storing in a database: (i) the first file, (ii) an association between the first file and the first event, (iii) the second file, and (iv) an association between the second file and the second event; receiving at the database a first signal that indicates selection of a link and a telephone number of the caller; in response to the receipt of the first signal, retrieving from the database those files that are associated with the link and with the telephone number, wherein the first utterance is associated with selected elements of a call that are of interest; and playing the first utterance to a user. 24. The method of claim 23 further comprising: in response to a signal that indicates the first event, retrieving from the database those files associated with the first event without retrieving a file that comprises an utterance and that is not associated with the first event.
| 0.669048 |
9,313,232 | 1 | 2 |
1. One or more non-transitory machine-readable storage media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving a plurality of parameters based, at least in part, on metadata information obtained from data mining one or more databases, at least one database containing tags associated with objects, wherein the data mining is to apply one or more filters to the tags of the at least one database to obtain at least a portion of the metadata information; creating a rule associated with at least some of the parameters; and incorporating the rule into a security policy to be used by a capture system, wherein the security policy is to control network communications captured by the capture system.
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1. One or more non-transitory machine-readable storage media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving a plurality of parameters based, at least in part, on metadata information obtained from data mining one or more databases, at least one database containing tags associated with objects, wherein the data mining is to apply one or more filters to the tags of the at least one database to obtain at least a portion of the metadata information; creating a rule associated with at least some of the parameters; and incorporating the rule into a security policy to be used by a capture system, wherein the security policy is to control network communications captured by the capture system. 2. The one or more non-transitory machine-readable storage media of claim 1 , the operations further comprising: generating a capture rule for capturing items intended to be propagated as part of the network communications; and generating a discovery rule for objects to be registered for future rule creations.
| 0.5 |
9,148,499 | 14 | 15 |
14. An electronic device, comprising: a processor configured to execute at least a voice interface program and a non-voice interface application program; memory including a buffer and operably coupled to the processor; an input interface including an audio input interface; and an output interface; the processor further configured to: receive, through the voice interface program, a voice input command that includes a command element and a content element, identify from the voice input command the command element, store the command element in the buffer, end the voice interface program without performing the voice input command, receive, through the application program, a user input which identifies input command data for executing an application program command, and upon successful execution of the application program command: determine that the non-voice interface application program is associated with the command element which was buffered in the buffer, and identify audio of at least the content element or the entire voice input command as a voice tag associated with the input command data identified by the user input.
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14. An electronic device, comprising: a processor configured to execute at least a voice interface program and a non-voice interface application program; memory including a buffer and operably coupled to the processor; an input interface including an audio input interface; and an output interface; the processor further configured to: receive, through the voice interface program, a voice input command that includes a command element and a content element, identify from the voice input command the command element, store the command element in the buffer, end the voice interface program without performing the voice input command, receive, through the application program, a user input which identifies input command data for executing an application program command, and upon successful execution of the application program command: determine that the non-voice interface application program is associated with the command element which was buffered in the buffer, and identify audio of at least the content element or the entire voice input command as a voice tag associated with the input command data identified by the user input. 15. The electronic device as claimed in claim 14 , wherein the content element comprises at least part of a contact name.
| 0.786972 |
8,447,608 | 3 | 4 |
3. The method of claim 2 , where the one or more source texts are structured documents and the processing includes removing tags indicating document structure.
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3. The method of claim 2 , where the one or more source texts are structured documents and the processing includes removing tags indicating document structure. 4. The method of claim 3 , where the one or more source texts are in XML format.
| 0.5 |
9,367,807 | 4 | 5 |
4. The logic-programming-based computer system of claim 3 wherein the body of the gateway rule further comprises: a first predicate, having a first-predicate name, different from the name of the gateway rule head predicate name, that uniquely identifies a set of rules implemented by the gateway rule and the set of fact-rule pairs; and a second predicate that represents a built-in evaluation operation.
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4. The logic-programming-based computer system of claim 3 wherein the body of the gateway rule further comprises: a first predicate, having a first-predicate name, different from the name of the gateway rule head predicate name, that uniquely identifies a set of rules implemented by the gateway rule and the set of fact-rule pairs; and a second predicate that represents a built-in evaluation operation. 5. The logic-programming-based computer system of claim 4 wherein the first predicate of the body includes n+1 variable arguments, the first 77 variable arguments corresponding to n arguments of the head predicate of the gateway rule and the final variable having a final-variable name.
| 0.5 |
7,797,316 | 13 | 18 |
13. A method, performed by one or more server devices, of determining the freshness of a first document, comprising: determining, by a processor of the one or more server devices, whether a freshness attribute is associated with the first document; identifying, by a processor of the one or more server devices and based on the determination, a set of second documents that each contains, or previously contained, a link to the first document; assigning, by a processor of the one or more server devices, a freshness score to the first document based on a freshness attribute associated with each document of the set of second documents or the freshness attribute associated with the first document, where the freshness attribute indicates when each document was last modified; and using, by a processor of the one or more server devices, the assigned freshness score as a basis for ranking the first document among a plurality of documents returned as results of an executed search.
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13. A method, performed by one or more server devices, of determining the freshness of a first document, comprising: determining, by a processor of the one or more server devices, whether a freshness attribute is associated with the first document; identifying, by a processor of the one or more server devices and based on the determination, a set of second documents that each contains, or previously contained, a link to the first document; assigning, by a processor of the one or more server devices, a freshness score to the first document based on a freshness attribute associated with each document of the set of second documents or the freshness attribute associated with the first document, where the freshness attribute indicates when each document was last modified; and using, by a processor of the one or more server devices, the assigned freshness score as a basis for ranking the first document among a plurality of documents returned as results of an executed search. 18. The method of claim 13 , further comprising: executing a search of a corpus of documents to return results comprising the plurality of documents, where the plurality of documents include the first document.
| 0.665605 |
4,128,737 | 16 | 19 |
16. The speech synthesizer of claim 12 wherein said vocal source is adapted to produce a voiced excitation signal having a waveform comprised of a first segment that increases in magnitude, a second segment that decreases in magnitude, and a third segment that remains at a constant magnitude.
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16. The speech synthesizer of claim 12 wherein said vocal source is adapted to produce a voiced excitation signal having a waveform comprised of a first segment that increases in magnitude, a second segment that decreases in magnitude, and a third segment that remains at a constant magnitude. 19. The speech synthesizer of claim 16 wherein said suppression means increases said predetermined bandwidths of said resonant filters during said first segment of said voiced excitation signal, decreases said bandwidths of said resonant filters from said increased levels during said second segment of said voiced excitation signal, and has no effect on said predetermined bandwidths of said resonant filters during said third segment of said voiced excitation signal.
| 0.5 |
7,949,539 | 1 | 6 |
1. A document audit system comprising: a digital controller; a document data entry device in communication with said digital controller; and a document report generator in communication with said digital controller; wherein said digital controller is programmed to: cause characteristic document data indicative of the characteristics of each of a plurality of documents to be received, compare said characteristic document data for each of said plurality of documents to migration data metrics which specify the characteristic document data of documents that can appropriately be assigned to one of a plurality of migration categories, save the identities of those documents of said plurality of documents that have characteristic document data that meet document data specified by said migration data metrics for said one of said plurality of migration categories, and enable said document report generator to generate a migration report, listing the identities of those documents of said plurality of documents that have characteristic document data that meet document data specified by said migration data metrics for said one of said plurality of migration categories.
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1. A document audit system comprising: a digital controller; a document data entry device in communication with said digital controller; and a document report generator in communication with said digital controller; wherein said digital controller is programmed to: cause characteristic document data indicative of the characteristics of each of a plurality of documents to be received, compare said characteristic document data for each of said plurality of documents to migration data metrics which specify the characteristic document data of documents that can appropriately be assigned to one of a plurality of migration categories, save the identities of those documents of said plurality of documents that have characteristic document data that meet document data specified by said migration data metrics for said one of said plurality of migration categories, and enable said document report generator to generate a migration report, listing the identities of those documents of said plurality of documents that have characteristic document data that meet document data specified by said migration data metrics for said one of said plurality of migration categories. 6. A system as claimed in claim 1 , wherein said report generator comprises a data output port coupled to a document management system.
| 0.765625 |
10,037,374 | 13 | 14 |
13. An apparatus for measuring similarity between clustered data grammars, comprising: means for receiving at least a first data stream from a first device and a second data stream from a second device, wherein the first data stream and the second data stream each include one or more sequenced data items; means for constructing at least a first grammar associated with the first device and a second grammar associated with the second device, wherein the first grammar and the second grammar each comprise a symbol sequence that re-expresses the one or more sequenced data items in the respective data streams received from the first device and the second device; means for comparing one or more rules that represent a repeated pattern in the symbol sequence associated with the first grammar and one or more rules that represent a repeated pattern in the symbol sequence associated with the second grammar to calculate one or more distance metrics that quantify a similarity between the first grammar and the second grammar; and means for determining a relationship between the first device and the second device according to the one or more distance metrics.
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13. An apparatus for measuring similarity between clustered data grammars, comprising: means for receiving at least a first data stream from a first device and a second data stream from a second device, wherein the first data stream and the second data stream each include one or more sequenced data items; means for constructing at least a first grammar associated with the first device and a second grammar associated with the second device, wherein the first grammar and the second grammar each comprise a symbol sequence that re-expresses the one or more sequenced data items in the respective data streams received from the first device and the second device; means for comparing one or more rules that represent a repeated pattern in the symbol sequence associated with the first grammar and one or more rules that represent a repeated pattern in the symbol sequence associated with the second grammar to calculate one or more distance metrics that quantify a similarity between the first grammar and the second grammar; and means for determining a relationship between the first device and the second device according to the one or more distance metrics. 14. The apparatus recited in claim 13 , wherein the one or more distance metrics include at least one distance metric that quantifies a syntactic similarity between the first grammar and the second grammar.
| 0.755924 |
8,401,837 | 7 | 9 |
7. The method of claim 6 further comprising: determining whether l>R; and responsive to l>R, rejecting the input data as containing at least some non-linguistic text.
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7. The method of claim 6 further comprising: determining whether l>R; and responsive to l>R, rejecting the input data as containing at least some non-linguistic text. 9. The method of claim 7 further comprising: responsive to l<R, accepting the input data as linguistic text.
| 0.5 |
8,301,450 | 9 | 10 |
9. The method of claim 8 , wherein the calculating the distance involves using the history information relative to the previous dialogue for the output text obtained as the result of the backward decoding of the previous dialogue and information obtained from a probability factor database having probability factors used for calculating the distance for each of the one or more candidate topic domains.
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9. The method of claim 8 , wherein the calculating the distance involves using the history information relative to the previous dialogue for the output text obtained as the result of the backward decoding of the previous dialogue and information obtained from a probability factor database having probability factors used for calculating the distance for each of the one or more candidate topic domains. 10. The method of claim 9 , wherein contents of the probability factor database are created using a training corpus including text information to be spoken, which has been previously established according to topic domains.
| 0.851206 |
8,447,720 | 1 | 6 |
1. A computer-implemented method comprising the steps of: receiving a user-specified context comprising one or more natural language contextual antecedents; for each contextual antecedent, creating a modified contextual antecedent by performing a bisection search of a word base and converting each contextual antecedent to a sequence of integers using the word base; comparing each modified contextual antecedent to each of a plurality of cases stored in a case base, each case comprising one or more case antecedents and one or more case consequents, wherein the case antecedents and case consequents are stored in the case base as sequences of integers representing the respective case antecedents and case consequents; selecting the case having the case antecedents that best match the contextual antecedents; displaying the case consequents of the selected case to a user; and receiving feedback from the user regarding the displayed case consequents.
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1. A computer-implemented method comprising the steps of: receiving a user-specified context comprising one or more natural language contextual antecedents; for each contextual antecedent, creating a modified contextual antecedent by performing a bisection search of a word base and converting each contextual antecedent to a sequence of integers using the word base; comparing each modified contextual antecedent to each of a plurality of cases stored in a case base, each case comprising one or more case antecedents and one or more case consequents, wherein the case antecedents and case consequents are stored in the case base as sequences of integers representing the respective case antecedents and case consequents; selecting the case having the case antecedents that best match the contextual antecedents; displaying the case consequents of the selected case to a user; and receiving feedback from the user regarding the displayed case consequents. 6. The computer-implemented method of claim 1 , wherein the step of receiving feedback from the user regarding the displayed case consequent comprises receiving confirmation that the displayed case consequent is correct.
| 0.866667 |
9,563,665 | 1 | 2 |
1. A search method, comprising: receiving a query word string; retrieving a plurality of product information entries related to the query word string; extracting, from a memory, a first core product word from the query word string to obtain a first key product word, the first core product word being a smallest semantic unit; extracting, from the memory, a plurality of second core product words from the product information entries, the plurality of second core product words being smallest semantic units, wherein the extracting of the plurality of second core product words comprises: extracting last product words from the plurality of product information entries, the plurality of second core product words including the last product words, the plurality of product information entries corresponding to titles of products, descriptions of products, or a combination thereof; for a first second core product word, checking a list of candidate product words relating to the first key product word for a presence of the first second core product word; in the event that the first second core product word is present in the list of candidate product words, reducing a weighting of the product information entry corresponding to the first second core product word, wherein the list of candidate product words contains a first candidate product word, the first candidate product word relating to the first second core product word, wherein the first candidate product word is combined with the first key product word to obtain a synthesized product word, and wherein the first key product word and the synthesized product word do not belong to the same category; and sorting and outputting the product information entries according to the reduced weightings of the product information entries.
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1. A search method, comprising: receiving a query word string; retrieving a plurality of product information entries related to the query word string; extracting, from a memory, a first core product word from the query word string to obtain a first key product word, the first core product word being a smallest semantic unit; extracting, from the memory, a plurality of second core product words from the product information entries, the plurality of second core product words being smallest semantic units, wherein the extracting of the plurality of second core product words comprises: extracting last product words from the plurality of product information entries, the plurality of second core product words including the last product words, the plurality of product information entries corresponding to titles of products, descriptions of products, or a combination thereof; for a first second core product word, checking a list of candidate product words relating to the first key product word for a presence of the first second core product word; in the event that the first second core product word is present in the list of candidate product words, reducing a weighting of the product information entry corresponding to the first second core product word, wherein the list of candidate product words contains a first candidate product word, the first candidate product word relating to the first second core product word, wherein the first candidate product word is combined with the first key product word to obtain a synthesized product word, and wherein the first key product word and the synthesized product word do not belong to the same category; and sorting and outputting the product information entries according to the reduced weightings of the product information entries. 2. The method as described in claim 1 , further comprising: establishing the list of candidate product words comprises: for at least one product information entry contained in a database: performing a coarse granularity segmentation by the largest semantic units; and extracting a third core product word contained in segmented results; determining whether the third core product word has been extracted from the segmented results; in the event that the third core product word has been extracted from the segmented results, performing a fine granularity segmentation by the smallest semantic units: determining whether at least two of the words obtained are product words; in the event that at least two of the words obtained are product words; using the first product word as a key product word; and using the last product word as a candidate product word of the key product word; computing correlations of at least one key product word and at least one candidate product word; determining whether the correlation of the at least one key product word and the at least one candidate product word meets a threshold value; selecting a candidate product word having a correlation that meets the threshold value; and for the same key product word, generating the list of candidate product words based on the selected candidate product word.
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9,418,094 | 16 | 18 |
16. An apparatus configured for performing multi-stage table updates, comprising: a processor; a receiving mechanism configured to receive a query at the processor for updating a table in a database; a sub-query-generating mechanism configured to generate a set of sub-queries responsive to a storage space needed for storing a transaction log associated with the received query the pre-determined threshold, wherein while generating the sub-queries, the sub-query-generating mechanism is configured to: identify partitions in the table; and for each partition: determine if a storage space needed for storing a transaction log associated with a sub-query corresponding to the partition exceeds the pre-determined threshold; if not, process the sub-query corresponding to the partition; and if so, divide the partition into multiple subsets such that a storage space needed for storing a transaction log associated with each sub-query corresponding to a subset is less than the pre-determined threshold.
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16. An apparatus configured for performing multi-stage table updates, comprising: a processor; a receiving mechanism configured to receive a query at the processor for updating a table in a database; a sub-query-generating mechanism configured to generate a set of sub-queries responsive to a storage space needed for storing a transaction log associated with the received query the pre-determined threshold, wherein while generating the sub-queries, the sub-query-generating mechanism is configured to: identify partitions in the table; and for each partition: determine if a storage space needed for storing a transaction log associated with a sub-query corresponding to the partition exceeds the pre-determined threshold; if not, process the sub-query corresponding to the partition; and if so, divide the partition into multiple subsets such that a storage space needed for storing a transaction log associated with each sub-query corresponding to a subset is less than the pre-determined threshold. 18. The apparatus of claim 16 , further comprising: a mini-commit mechanism configured to perform a mini-commit operation for each sub-query; and a commit mechanism configured to perform a commit operation for the received query in response to mini-commit operations for all sub-queries being performed successfully, and to roll back the mini-commit operations for all sub-queries in response to a mini-commit operation for any sub-query being performed unsuccessfully.
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