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1. A computer-implemented method, the method comprising the following operations performed by at least one processor: forming a first feature vector for-a search query received from a user having a plurality of search terms and being associated with a particular date, the first feature vector comprising a first set of numerical values corresponding to the search terms and including user interest data; obtaining a set of second feature vectors for a plurality of documents having publication dates that are temporally proximate to the particular date, the set of second feature vectors comprising second sets of numerical values associated with terms in corresponding ones of the documents; computing, based on the second sets of numerical values, a centroid feature vector representative of at least a portion of the second feature vectors; generating an augmented feature vector based on a comparison of the first feature vector and the centroid feature vector; and identifying at least one target document that corresponds to the search query based on the augmented feature vector. | 1. A computer-implemented method, the method comprising the following operations performed by at least one processor: forming a first feature vector for-a search query received from a user having a plurality of search terms and being associated with a particular date, the first feature vector comprising a first set of numerical values corresponding to the search terms and including user interest data; obtaining a set of second feature vectors for a plurality of documents having publication dates that are temporally proximate to the particular date, the set of second feature vectors comprising second sets of numerical values associated with terms in corresponding ones of the documents; computing, based on the second sets of numerical values, a centroid feature vector representative of at least a portion of the second feature vectors; generating an augmented feature vector based on a comparison of the first feature vector and the centroid feature vector; and identifying at least one target document that corresponds to the search query based on the augmented feature vector. 3. The method of claim 1 , wherein the plurality of documents comprise at least one document associated with a current event, the at least one current event document having a publication date that falls within a threshold time period of a date associated with the search query. | 0.678422 |
2. A system, including: a receiving component configured to receive a post-processed definition of declarative source code, the post-processed definition including a compiled transformation of an order-independent execution model included in the declarative source code, wherein an order of entering values into a data abstraction of the order-independent execution model is unobservable to a target repository, and wherein a declarative format of the order-independent execution model is preserved in the post-processed definition; and a packaging component configured to package the post-processed definition of the declarative source code as an image file, wherein the image file preserves the declarative format of the order-independent execution model in an extensible storage abstraction, and wherein the image file includes at least one artifact of the compiled transformation stored in the extensible storage abstraction and metadata describing attributes of contents stored in the extensible storage abstraction, the extensible storage abstraction including a plurality of tables having a plurality of entries representing the post-processed definition. | 2. A system, including: a receiving component configured to receive a post-processed definition of declarative source code, the post-processed definition including a compiled transformation of an order-independent execution model included in the declarative source code, wherein an order of entering values into a data abstraction of the order-independent execution model is unobservable to a target repository, and wherein a declarative format of the order-independent execution model is preserved in the post-processed definition; and a packaging component configured to package the post-processed definition of the declarative source code as an image file, wherein the image file preserves the declarative format of the order-independent execution model in an extensible storage abstraction, and wherein the image file includes at least one artifact of the compiled transformation stored in the extensible storage abstraction and metadata describing attributes of contents stored in the extensible storage abstraction, the extensible storage abstraction including a plurality of tables having a plurality of entries representing the post-processed definition. 14. The system of claim 2 , the declarative source code including an M language source code. | 0.582493 |
1. A method for electronically processing at least one document stored as an electronic document image containing undecoded text to identify a selected portion thereof, said method comprising the steps or: segmenting said at least one document image into words, each word having an undecoded textual content; classifying the textual content of at least some of said words relative to other said words, without decoding the words, based on an evaluation of predetermined morphological characteristics of said words; and selecting words for further processing according to the classification of said words obtained in said classifying step. | 1. A method for electronically processing at least one document stored as an electronic document image containing undecoded text to identify a selected portion thereof, said method comprising the steps or: segmenting said at least one document image into words, each word having an undecoded textual content; classifying the textual content of at least some of said words relative to other said words, without decoding the words, based on an evaluation of predetermined morphological characteristics of said words; and selecting words for further processing according to the classification of said words obtained in said classifying step. 6. The method of claim 1 wherein a document corpus containing a plurality of documents is processed, and said segmenting, classifying and selecting steps are performed with respect to the document image for each document in the document corpus. | 0.674644 |
5. The method of claim 4 , further comprising the step of: determining whether the count for the counter of the target document equals zero. | 5. The method of claim 4 , further comprising the step of: determining whether the count for the counter of the target document equals zero. 6. The method of claim 5 , wherein if the counter equals zero, further comprising the step of: sending a message to an author of the target document asking whether the author wants to delete the target document from the storage. | 0.848344 |
4. A method comprising: receiving, by one or more computer processors, a scanned image of a source text, the scanned image comprising a first glyph and a second glyph, wherein the first glyph and the second glyph correspond to a first instance and a second instance of a character in the source text, respectively, and wherein the first instance of the character appears in a first word of the source text and the second instance of the character appears in a second word of the source text; generating, by the one or more computer processors, an image representative of each of the first glyph and the second glyph; determining, by the one or more computer processors, a first positional reference line indicative of a default position of a first character along a horizontal or vertical baseline, wherein the default position indicates an origin of the first character; determining, by the one or more computer processors, a second positional reference line indicative of an alignment of characters forming the first word and a third positional reference line indicative of an alignment of characters forming the second word; determining, by the one or more computer processors, a first distance value between the first positional reference line and the second positional reference line; assigning, by the one or more computer processors, a first numerical identifier to the first glyph; generating, by the one or more computer processors, first glyph data associated with the first glyph, the first glyph data comprising the first numerical identifier and the first distance value; generating, by the one or more computer processors, a font file configured to be executed by a renderer to render the source text, the font file comprising the image and the first glyph data; and generating, by the one or more computer processors, a digitally renderable format for the source text based at least in part on the font file and the scanned image. | 4. A method comprising: receiving, by one or more computer processors, a scanned image of a source text, the scanned image comprising a first glyph and a second glyph, wherein the first glyph and the second glyph correspond to a first instance and a second instance of a character in the source text, respectively, and wherein the first instance of the character appears in a first word of the source text and the second instance of the character appears in a second word of the source text; generating, by the one or more computer processors, an image representative of each of the first glyph and the second glyph; determining, by the one or more computer processors, a first positional reference line indicative of a default position of a first character along a horizontal or vertical baseline, wherein the default position indicates an origin of the first character; determining, by the one or more computer processors, a second positional reference line indicative of an alignment of characters forming the first word and a third positional reference line indicative of an alignment of characters forming the second word; determining, by the one or more computer processors, a first distance value between the first positional reference line and the second positional reference line; assigning, by the one or more computer processors, a first numerical identifier to the first glyph; generating, by the one or more computer processors, first glyph data associated with the first glyph, the first glyph data comprising the first numerical identifier and the first distance value; generating, by the one or more computer processors, a font file configured to be executed by a renderer to render the source text, the font file comprising the image and the first glyph data; and generating, by the one or more computer processors, a digitally renderable format for the source text based at least in part on the font file and the scanned image. 14. The method of claim 4 , further comprising rendering the source text on a display based at least in part on the scanned image and the font file. | 0.850401 |
14. A string signature scanning system, the system comprising: a machine-readable storage device including a computer program; and one or more processors or one or more special purpose logic circuits operable to execute the computer program, and perform operations including providing one or more modules including: a signature pre-processing module operable to process one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; a fingerprint scan engine operable to identify one or more fingerprints associated with one or more signatures on an input string field, the identifying including scanning the input string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size; a signature search engine operable to identify signatures for the identified fingerprints. | 14. A string signature scanning system, the system comprising: a machine-readable storage device including a computer program; and one or more processors or one or more special purpose logic circuits operable to execute the computer program, and perform operations including providing one or more modules including: a signature pre-processing module operable to process one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; a fingerprint scan engine operable to identify one or more fingerprints associated with one or more signatures on an input string field, the identifying including scanning the input string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size; a signature search engine operable to identify signatures for the identified fingerprints. 15. The system of claim 14 , each of one or more fingerprints of one or more lengths being decomposed into one or more fingerprint segments and the plurality of fingerprint segments for the one or more fingerprints being scanned by one or more fingerprint scan engines, each of the one or more fingerprint scan engines including a fingerprint synthesis engine that is operable to synthesize a plurality of fingerprint segments into any fingerprint matches either in parallel or sequentially using one or more of a fingerprint segment bitmap, fingerprint length information, and one or more content addressable memories (CAM). | 0.5 |
18. The computer readable storage medium of claim 11 , wherein the step (f) further comprises the step of: prompting the second user to make a suggestion if the second user thinks that the chosen listed knowledge object is irrelevant to the first user's request. | 18. The computer readable storage medium of claim 11 , wherein the step (f) further comprises the step of: prompting the second user to make a suggestion if the second user thinks that the chosen listed knowledge object is irrelevant to the first user's request. 19. The computer readable storage medium of claim 18 , further comprising any step of: returning to the first user an unlisted knowledge object from the second user's private domain if the second user so decides; and prompting the second user to make the unlisted knowledge object as listed or published. | 0.859736 |
2. The apparatus of claim 1 wherein (A) comprises: (A1) program code for providing a document summarization function for creating a summary of the document, the summary comprising selected content of the document processed by the document summarization function. | 2. The apparatus of claim 1 wherein (A) comprises: (A1) program code for providing a document summarization function for creating a summary of the document, the summary comprising selected content of the document processed by the document summarization function. 3. The apparatus of claim 2 further comprising: (G) program code for presenting the summary document in association with the document processed by the document summarization function. | 0.921902 |
1. A method for recommending mobile device activities, the method comprising: receiving an indication of a content item contained on a Web page that is currently presented by a mobile device; determining semantic information about the indicated content item, including accessing a semantic network that is a graph data structure that includes multiple entities that each have is-a and/or member-of relations to other entities or categories of the semantic network, wherein the is-a and/or member-of relations are represented as links between the entities or categories of the semantic network, to: identify one or more entities in the semantic network that are referenced by the indicated content item and relationships relating to the identified entities; identify one or more entities in the semantic network that are related to the identified one or more entities; and identify one or more categories in the semantic network that are associated with the identified one or more entities and/or the related one or more entities, wherein the identified one or more categories are part of a taxonomic hierarchy in which each of the identified one or more categories is part of a corresponding taxonomic path that includes multiple categories related to one another via is-a relations, wherein the one or more categories are identified by traversing the links representing relations within the semantic network by traversing at most N taxonomic paths within the semantic network, where N is determined by user setting or data mining; determining a plurality of mobile device activities, wherein each activity has one or more associated entities and/or categories in common with the determined semantic information; and transmitting information about the determined plurality of activities. | 1. A method for recommending mobile device activities, the method comprising: receiving an indication of a content item contained on a Web page that is currently presented by a mobile device; determining semantic information about the indicated content item, including accessing a semantic network that is a graph data structure that includes multiple entities that each have is-a and/or member-of relations to other entities or categories of the semantic network, wherein the is-a and/or member-of relations are represented as links between the entities or categories of the semantic network, to: identify one or more entities in the semantic network that are referenced by the indicated content item and relationships relating to the identified entities; identify one or more entities in the semantic network that are related to the identified one or more entities; and identify one or more categories in the semantic network that are associated with the identified one or more entities and/or the related one or more entities, wherein the identified one or more categories are part of a taxonomic hierarchy in which each of the identified one or more categories is part of a corresponding taxonomic path that includes multiple categories related to one another via is-a relations, wherein the one or more categories are identified by traversing the links representing relations within the semantic network by traversing at most N taxonomic paths within the semantic network, where N is determined by user setting or data mining; determining a plurality of mobile device activities, wherein each activity has one or more associated entities and/or categories in common with the determined semantic information; and transmitting information about the determined plurality of activities. 11. The method of claim 1 wherein transmitting the information about the determined plurality of activities includes presenting an indication of one or more of the plurality of activities on a display of the mobile device. | 0.60755 |
10. A method for online character recognition of East Asian characters, implemented at least in part by a computing device, the method comprising: acquiring time sequential, online ink data for a handwritten East Asian character; conditioning the ink data to produce conditioned ink data where the conditioned ink data comprises ink data frames and information as to writing sequence of the handwritten East Asian character; determining neighborhoods of ink data frames wherein the determining neighborhoods comprises: determining a turning angle between two adjacent ink data frames; determining at least one other turning angle between the two adjacent ink data frames; determining a cumulative angle based on the turning angle and the at least one other turning angle; and comparing the cumulative angle to a predetermined threshold to decide if the two adjacent ink data frames belong to the same neighborhood; and applying a Hidden Markov Model based character recognition system to recognize the handwritten East Asian character. | 10. A method for online character recognition of East Asian characters, implemented at least in part by a computing device, the method comprising: acquiring time sequential, online ink data for a handwritten East Asian character; conditioning the ink data to produce conditioned ink data where the conditioned ink data comprises ink data frames and information as to writing sequence of the handwritten East Asian character; determining neighborhoods of ink data frames wherein the determining neighborhoods comprises: determining a turning angle between two adjacent ink data frames; determining at least one other turning angle between the two adjacent ink data frames; determining a cumulative angle based on the turning angle and the at least one other turning angle; and comparing the cumulative angle to a predetermined threshold to decide if the two adjacent ink data frames belong to the same neighborhood; and applying a Hidden Markov Model based character recognition system to recognize the handwritten East Asian character. 13. The method of claim 10 wherein the conditioned ink data comprises ink data frames for real strokes and ink data frames for imaginary strokes. | 0.560394 |
13. The method of claim 1 , wherein said providing a stimulus set comprises providing a stimulus word set comprising a plurality of stimulus words, each comprising a word element; the method further comprising: displaying a plurality of bins via a computing device, wherein each of the plurality of bins represents a respective word element from a plurality of word elements; wherein said graphically presenting a stimulus from the stimulus set to the student via the computing device comprises: presenting a stimulus word from the stimulus word set to the student, wherein the stimulus word contains one of the plurality of word elements represented by the plurality of bins; wherein said requiring the student to respond to the stimulus comprises: requiring the student to select a bin from the plurality of bins representing a word element contained in the presented stimulus word; wherein said determining if the response is correct comprises: determining if the student selected the bin correctly; wherein said performing said graphically presenting, said requiring, and said determining for each of a plurality of stimuli comprises: repeating said displaying, said presenting, said requiring, and said determining for each stimulus word in the stimulus word set; and wherein said repeating builds accuracy and fluency in phonemic analysis, decoding, and spelling skills in the student. | 13. The method of claim 1 , wherein said providing a stimulus set comprises providing a stimulus word set comprising a plurality of stimulus words, each comprising a word element; the method further comprising: displaying a plurality of bins via a computing device, wherein each of the plurality of bins represents a respective word element from a plurality of word elements; wherein said graphically presenting a stimulus from the stimulus set to the student via the computing device comprises: presenting a stimulus word from the stimulus word set to the student, wherein the stimulus word contains one of the plurality of word elements represented by the plurality of bins; wherein said requiring the student to respond to the stimulus comprises: requiring the student to select a bin from the plurality of bins representing a word element contained in the presented stimulus word; wherein said determining if the response is correct comprises: determining if the student selected the bin correctly; wherein said performing said graphically presenting, said requiring, and said determining for each of a plurality of stimuli comprises: repeating said displaying, said presenting, said requiring, and said determining for each stimulus word in the stimulus word set; and wherein said repeating builds accuracy and fluency in phonemic analysis, decoding, and spelling skills in the student. 16. The method of claim 13 , wherein the word element is a spelling pattern; wherein said presenting the stimulus word comprises audibly presenting the stimulus word from the stimulus word set to the student. | 0.723943 |
1. A method, in a data processing system comprising a processor and a memory, for answering an input question, the method comprising: receiving, in the data processing system, an input question to be answered from a source; processing, by the data processing system, the input question to extract one or more features of the input question; comparing, by the data processing system, the extracted one or more features to cached features stored in one or more entries of a question and answer (QA) cache of the data processing system; determining, by the data processing system, whether there is a matching entry in the one or more entries of the QA cache based on results of the comparing, wherein determining whether there is a matching entry in the one or more entries of the QA cache comprises: generating, for each entry in the QA cache, a match value indicative of a degree of matching between the one or more extracted features of the input question to cached features of the entry in the QA cache; and comparing the match value to one or more threshold values indicating one or more requisite degrees of similarity between the input question and an entry in the QA cache, wherein: in response to the match value equaling or exceeding a first threshold value, a corresponding entry is determined to match the input question, and in response to the match value being less than the first threshold value but the match value being equal to or greater than a second threshold value, determining that the corresponding entry is sufficiently similar for updating the corresponding entry with the one or more extracted features of the input question; retrieving, by the data processing system, in response to a matching entry being present in the one or more entries of the QA cache, candidate answer information from the matching entry; and returning, by the data processing system, the retrieved candidate answer information to the source of the input question as candidate answer information for answering the input question. | 1. A method, in a data processing system comprising a processor and a memory, for answering an input question, the method comprising: receiving, in the data processing system, an input question to be answered from a source; processing, by the data processing system, the input question to extract one or more features of the input question; comparing, by the data processing system, the extracted one or more features to cached features stored in one or more entries of a question and answer (QA) cache of the data processing system; determining, by the data processing system, whether there is a matching entry in the one or more entries of the QA cache based on results of the comparing, wherein determining whether there is a matching entry in the one or more entries of the QA cache comprises: generating, for each entry in the QA cache, a match value indicative of a degree of matching between the one or more extracted features of the input question to cached features of the entry in the QA cache; and comparing the match value to one or more threshold values indicating one or more requisite degrees of similarity between the input question and an entry in the QA cache, wherein: in response to the match value equaling or exceeding a first threshold value, a corresponding entry is determined to match the input question, and in response to the match value being less than the first threshold value but the match value being equal to or greater than a second threshold value, determining that the corresponding entry is sufficiently similar for updating the corresponding entry with the one or more extracted features of the input question; retrieving, by the data processing system, in response to a matching entry being present in the one or more entries of the QA cache, candidate answer information from the matching entry; and returning, by the data processing system, the retrieved candidate answer information to the source of the input question as candidate answer information for answering the input question. 3. The method of claim 1 , further comprising: in response to determining that there is not a matching entry in the one or more entries of the QA cache, processing the input question through a QA system pipeline to generate one or more generated candidate answers for answering the input question. | 0.533229 |
1. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, receiving, at a server, a request from a first user to store a media item for later access by an electronic book reader device associated with a second user, wherein the request from the first user does not include information identifying the second user or the electronic book reader device associated with the second user as an intended recipient of the media item; in response to receiving the request at the server, associating a pass phrase with the request to store the media item; sending the pass phrase from the server to a device of the first user or to another device associated with the first user; after sending the pass phrase, receiving, at the server, the media item from the device of the first user; after receiving the media item at the server, storing the media item in association with the pass phrase, the pass phrase being usable for the later access of the media item by the electronic book reader device associated with the second user; receiving, at the server, the pass phrase from the electronic book reader device associated with the second user; and sending the media item from the server to the electronic book reader device associated with the second user at least partly in response to the receiving of the pass phrase at the server. | 1. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, receiving, at a server, a request from a first user to store a media item for later access by an electronic book reader device associated with a second user, wherein the request from the first user does not include information identifying the second user or the electronic book reader device associated with the second user as an intended recipient of the media item; in response to receiving the request at the server, associating a pass phrase with the request to store the media item; sending the pass phrase from the server to a device of the first user or to another device associated with the first user; after sending the pass phrase, receiving, at the server, the media item from the device of the first user; after receiving the media item at the server, storing the media item in association with the pass phrase, the pass phrase being usable for the later access of the media item by the electronic book reader device associated with the second user; receiving, at the server, the pass phrase from the electronic book reader device associated with the second user; and sending the media item from the server to the electronic book reader device associated with the second user at least partly in response to the receiving of the pass phrase at the server. 19. The computer-implemented method of claim 1 , further comprising: sending a piece of information in addition to the pass phrase from the server to the device of the first user or to the other device associated with the first user, the piece of information also for accessing the media item by the electronic reader device associated with the second user; in response to receiving the media item at the server, storing the media item in association with the piece of information; receiving, at the server, in addition to the pass phrase, the piece of information from the electronic book reader device of the second user; and wherein the sending of the media item to the electronic book reader device associated with the second user is also at least partly in response to the receiving of the piece of information at the server. | 0.5 |
1. A process implemented across a network having a search engine, the search engine having access to a content source, the process comprising the steps of: receiving at an application module a search query from a user at a user terminal, the search query comprising at least one search parameter specified by the user; receiving at the application module an identification of at least one ratings service specified by the user, wherein the at least one ratings service is external to the application module, to the search engine, and to the content source, and wherein the ratings service is accessible to the application module across the network; responsive to the receipt of the user-specified ratings services, sending a data query from the application module to at least one of the user-specified ratings services; receiving rating information at the application module across the network from at least one of the user-specified ratings services in response to the sent data query, wherein the rating information is independently maintained by the at least one ratings service; providing a refined search through the application module, wherein the refinement comprises any of at the application module, using the received rating information from at least one of the user-specified ratings services in conjunction with the search parameters received from the user to perform the search at the search engine through retrieval of content from the content source, wherein search results received from the search engine at the application module comply with both the search parameters received from the user and the received rating information from at least one of the user-specified ratings services, performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently filtering search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services, and performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently providing any of organizing and sorting of the search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services; and returning the results of the refined search from the application module to any of the user at the user terminal and a recipient at a recipient terminal, the recipient other than the user. | 1. A process implemented across a network having a search engine, the search engine having access to a content source, the process comprising the steps of: receiving at an application module a search query from a user at a user terminal, the search query comprising at least one search parameter specified by the user; receiving at the application module an identification of at least one ratings service specified by the user, wherein the at least one ratings service is external to the application module, to the search engine, and to the content source, and wherein the ratings service is accessible to the application module across the network; responsive to the receipt of the user-specified ratings services, sending a data query from the application module to at least one of the user-specified ratings services; receiving rating information at the application module across the network from at least one of the user-specified ratings services in response to the sent data query, wherein the rating information is independently maintained by the at least one ratings service; providing a refined search through the application module, wherein the refinement comprises any of at the application module, using the received rating information from at least one of the user-specified ratings services in conjunction with the search parameters received from the user to perform the search at the search engine through retrieval of content from the content source, wherein search results received from the search engine at the application module comply with both the search parameters received from the user and the received rating information from at least one of the user-specified ratings services, performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently filtering search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services, and performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently providing any of organizing and sorting of the search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services; and returning the results of the refined search from the application module to any of the user at the user terminal and a recipient at a recipient terminal, the recipient other than the user. 13. The process of claim 1 , wherein the received search parameters have an applicability to one or more subjects, the process further comprising the steps of: determining a subject matter of the received search query; and integrating any of the received search parameters with the search query, wherein the integrated received search parameters are applicable to the determined subject matter. | 0.526073 |
4. The document conversion apparatus of claim 2 , wherein the at least one computer program further comprises program code that, when executed by the computer processor, implements an acquiring unit that acquires a first data type corresponding to the first document element and a second data type corresponding to the second document element, the first data type different from the second data type. | 4. The document conversion apparatus of claim 2 , wherein the at least one computer program further comprises program code that, when executed by the computer processor, implements an acquiring unit that acquires a first data type corresponding to the first document element and a second data type corresponding to the second document element, the first data type different from the second data type. 11. The document conversion apparatus of claim 4 , wherein the acquiring unit is configured to determine the first binary conversion algorithm to be performed on the first document element based on the first data type. | 0.898675 |
33. A system for generating a rule for automated credit request decisioning, comprising: a processor for executing stored instructions to receive information associated with an applicant through a user interface; receive data associated with the applicant from at least one data source; configure the user interface to allow the user to define a plurality of decision rules in a near-natural language; determine information associated with the plurality of decision rules based on the plurality of decisions rules in the near-natural language; generate a decision flow in response to receiving an identification from the user through the user interface of a flow element, of a decision block, and of a flow path for connecting to at least one of the decision block or the flow element, the decision flow comprises the flow element, the decision block, and the flow path; determine a decision for the applicant based on the information associated with the applicant, the data associated with the applicant from at least one data source, the information associated with the plurality of decision rules determined based on the plurality of decision rules in the near-natural language, and the decision flow by applying in accordance with the decision flow an executable version of the information associate with the plurality of decision rules in the near-natural language to the data associated with the applicant from at least one data source; and provide the decision to the user interface. | 33. A system for generating a rule for automated credit request decisioning, comprising: a processor for executing stored instructions to receive information associated with an applicant through a user interface; receive data associated with the applicant from at least one data source; configure the user interface to allow the user to define a plurality of decision rules in a near-natural language; determine information associated with the plurality of decision rules based on the plurality of decisions rules in the near-natural language; generate a decision flow in response to receiving an identification from the user through the user interface of a flow element, of a decision block, and of a flow path for connecting to at least one of the decision block or the flow element, the decision flow comprises the flow element, the decision block, and the flow path; determine a decision for the applicant based on the information associated with the applicant, the data associated with the applicant from at least one data source, the information associated with the plurality of decision rules determined based on the plurality of decision rules in the near-natural language, and the decision flow by applying in accordance with the decision flow an executable version of the information associate with the plurality of decision rules in the near-natural language to the data associated with the applicant from at least one data source; and provide the decision to the user interface. 34. The system of claim 33 , wherein the processor is configured to execute stored instructions to apply in accordance with the plurality of decision rules in the near-natural language to the data associated with the applicant from at least one data source to generate a decision for the applicant by: determining a series of execution steps from the decision rule associated with the plurality of decision rules; in accordance with the series of execution steps, generating at least one attribute representing a statistical aggregation of at least one of (i) the data associated with the applicant from at least one data source; or (ii) the information associated with the applicant; and applying the information associated with the plurality of decision rules on the at least one attribute to generate the decision, the decision comprising one of: denial of a credit line; granting an approval of a credit line; denial of a loan; granting approval of a loan; or approval for receiving an offer of credit. | 0.507816 |
1. A method of identifying symbols including traffic pictograms for use with a Global Positioning Satellite (GPS) device, comprising: receiving image information from an imaging device, the image information including an image and a GPS location at which the image was captured; and processing the received image information in a database server located geographically remotely from the GPS location at which the image was captured to determine a meaning of the image at the location at which the image was captured, the processing comprising comparing the image with stored images or symbols in a database in the database server to determine whether the image matches a stored image or symbol in the database, the stored images or symbols including traffic pictograms and being associated with the GPS location at which the image was captured, and when a match is not determined based on the comparing, storing the image in the database. | 1. A method of identifying symbols including traffic pictograms for use with a Global Positioning Satellite (GPS) device, comprising: receiving image information from an imaging device, the image information including an image and a GPS location at which the image was captured; and processing the received image information in a database server located geographically remotely from the GPS location at which the image was captured to determine a meaning of the image at the location at which the image was captured, the processing comprising comparing the image with stored images or symbols in a database in the database server to determine whether the image matches a stored image or symbol in the database, the stored images or symbols including traffic pictograms and being associated with the GPS location at which the image was captured, and when a match is not determined based on the comparing, storing the image in the database. 3. The method of claim 1 , further comprising: when a match is determined based on the comparing, transmitting from the database server to a user device the determined meaning of the image at the GPS, location at which the image was captured, the meaning being associated with the stored image or symbol determined to match the image. | 0.623466 |
22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device. | 22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device. 43. The system of claim 22 , wherein the object evaluation component calculates the matching metric for each candidate object by summing the number of contact locations in the input sequence exceeding a threshold distance to the location assigned to the character in the corresponding position of the candidate object. | 0.589536 |
1. A machine interpreter comprising: a parallel translation data base for storing an example sentence of a first language and a corresponding translation of the example sentence of a second language; a variable semantic feature dictionary for designating a variable word group of at least one word corresponding to a particular word group, of at least one word, of the example sentence, and for storing word groups of the first and second languages in pairs; input means for inputting a request for retrieval from the parallel translation data base; retrieving means for retrieving an example sentence and a translated sentence from the parallel translation data base based upon an input retrieval request; display for displaying the example sentence and translated sentence retrieved from the parallel translation data base; control means for arranging words of a variable word group in the variable semantic feature dictionary corresponding to the particular word group of the example sentence, and for causing the display to display the arranged words and a word group corresponding to the arranged words; and substituting means for substituting a translated word of the arranged words, equivalent to a word requested by the input means, for the particular word of the example sentence. | 1. A machine interpreter comprising: a parallel translation data base for storing an example sentence of a first language and a corresponding translation of the example sentence of a second language; a variable semantic feature dictionary for designating a variable word group of at least one word corresponding to a particular word group, of at least one word, of the example sentence, and for storing word groups of the first and second languages in pairs; input means for inputting a request for retrieval from the parallel translation data base; retrieving means for retrieving an example sentence and a translated sentence from the parallel translation data base based upon an input retrieval request; display for displaying the example sentence and translated sentence retrieved from the parallel translation data base; control means for arranging words of a variable word group in the variable semantic feature dictionary corresponding to the particular word group of the example sentence, and for causing the display to display the arranged words and a word group corresponding to the arranged words; and substituting means for substituting a translated word of the arranged words, equivalent to a word requested by the input means, for the particular word of the example sentence. 2. The machine interpreter as defined in claim 1, wherein the control means arranges the words of the variable word group in the variable semantic feature dictionary corresponding to the particular word of the example sentence, and causes the display to display the words of the variable word group in a particular order. | 0.552394 |
1. A computer readable storage medium having stored therein a keyword output program causing a computer to execute a keyword output method comprising: receiving a target keyword from a predetermined input unit; extracting, from a keyword storage unit that stores a plurality of keywords in association with each other according to degrees of relation among each other, a plurality of related keywords that have degrees of relation equal to or greater than a predetermined degree of relation with respect to the target keyword received, the stored plurality of keywords having been used for a search at a search site for searching contents; reading evaluation expressions corresponding to the target keyword and the plurality of related keywords from an evaluation expression storage unit that stores evaluation expressions correspondingly with each of the plurality of keywords stored in the keyword storage unit, each evaluation expression having been extracted from a content containing the corresponding keyword, and calculating for each of the plurality of related keywords a commonness degree between the evaluation expressions corresponding to the related keyword and the evaluation expressions corresponding to the target keyword; calculating for each of the plurality of related keywords a degree of association between the related keyword and the target keyword by using a distance derived from the keyword storage unit for each of the plurality of related keywords with respect to the target keyword and the commonness degree of the evaluation expressions calculated for each of the plurality of related keywords; determining whether the degree of association calculated is greater than a predetermined degree of association and extracting a first related keyword having a degree of association greater than the predetermined degree of association from among the plurality of related keywords; and outputting a keyword layout drawing including the target keyword and the plurality of related keywords arranged according to the degrees of association between each other through a predetermined output unit such that the the first related keyword is displayed distinguishably from other related keyword. | 1. A computer readable storage medium having stored therein a keyword output program causing a computer to execute a keyword output method comprising: receiving a target keyword from a predetermined input unit; extracting, from a keyword storage unit that stores a plurality of keywords in association with each other according to degrees of relation among each other, a plurality of related keywords that have degrees of relation equal to or greater than a predetermined degree of relation with respect to the target keyword received, the stored plurality of keywords having been used for a search at a search site for searching contents; reading evaluation expressions corresponding to the target keyword and the plurality of related keywords from an evaluation expression storage unit that stores evaluation expressions correspondingly with each of the plurality of keywords stored in the keyword storage unit, each evaluation expression having been extracted from a content containing the corresponding keyword, and calculating for each of the plurality of related keywords a commonness degree between the evaluation expressions corresponding to the related keyword and the evaluation expressions corresponding to the target keyword; calculating for each of the plurality of related keywords a degree of association between the related keyword and the target keyword by using a distance derived from the keyword storage unit for each of the plurality of related keywords with respect to the target keyword and the commonness degree of the evaluation expressions calculated for each of the plurality of related keywords; determining whether the degree of association calculated is greater than a predetermined degree of association and extracting a first related keyword having a degree of association greater than the predetermined degree of association from among the plurality of related keywords; and outputting a keyword layout drawing including the target keyword and the plurality of related keywords arranged according to the degrees of association between each other through a predetermined output unit such that the the first related keyword is displayed distinguishably from other related keyword. 3. The computer readable storage medium according to claim 1 , wherein a plurality of target keywords are received, the plurality of related keywords are extracted for each of the plurality of target keywords, the commonness degree for each of the plurality of related keywords for each of the target keywords is calculated, the degree of association for each of the plurality of related keywords for each of the plurality of target keywords is calculated, the first related keyword for each of the plurality of target keywords is extracted, and the output keyword layout drawing includes the plurality of target keywords and the plurality of related keywords arranged according to the degrees of association between each other such that the first related keyword for each of the plurality of target keywords is displayed distinguishably from the other related keyword. | 0.53125 |
1. A method for a computer system to interpret an input from a user and generate a response, comprising: receiving a user input; converting the user input into an input array comprising rows and columns having a plurality of concepts; determining if any of the plurality of concepts in the input array is derived from a root concept; if any of the plurality of concepts is derived from a root concept, replacing each such derived concept with the corresponding root concept, identifying one or more related concepts that relate to the root concept, and generating a multi-dimensional array based on the input array that includes the one or more related concepts; generating one or more additional multi-dimensional arrays, based on the input, containing any composite concepts, each derived from two or more concepts contained in the original array; marking one or more concepts in the multi-dimensional arrays as essential based on application-specific criteria; correlating a plurality of concepts in the multi-dimensional array to a plurality of first elements in a database by comparing a plurality of linear arrays derived from the multidimensional array to the plurality of elements in the database, wherein the first elements in the database includes a link to a second element in the database do not comprise possible responses; determining a plurality of possible responses to the user input based on the correlation of the multi-dimensional array and the plurality of elements in the database; and generating a response to the user input. | 1. A method for a computer system to interpret an input from a user and generate a response, comprising: receiving a user input; converting the user input into an input array comprising rows and columns having a plurality of concepts; determining if any of the plurality of concepts in the input array is derived from a root concept; if any of the plurality of concepts is derived from a root concept, replacing each such derived concept with the corresponding root concept, identifying one or more related concepts that relate to the root concept, and generating a multi-dimensional array based on the input array that includes the one or more related concepts; generating one or more additional multi-dimensional arrays, based on the input, containing any composite concepts, each derived from two or more concepts contained in the original array; marking one or more concepts in the multi-dimensional arrays as essential based on application-specific criteria; correlating a plurality of concepts in the multi-dimensional array to a plurality of first elements in a database by comparing a plurality of linear arrays derived from the multidimensional array to the plurality of elements in the database, wherein the first elements in the database includes a link to a second element in the database do not comprise possible responses; determining a plurality of possible responses to the user input based on the correlation of the multi-dimensional array and the plurality of elements in the database; and generating a response to the user input. 12. The method of claim 1 wherein the user is a human. | 0.575449 |
1. A computer-implemented method, comprising: generating, by at least one specialized computer system, a plurality of position specific surveys; wherein each position specific survey comprises a plurality of survey questions specific to competency skills related to performance of at least one position; wherein each survey question of the plurality of survey questions seeks a response in a form of a number on a numerical extent scale; wherein each position specific survey is configured for calculating an average score in each competency skills group of the competency skills by averaging numbers of the numerical extent scale across responses received from reference providers to the plurality of survey questions so that the responses from each of reference providers are confidential from employers and job candidates; wherein the at least one specialized computer system comprises at least one specialized computer machine comprising a non-transient memory having at least one region for storing specific computer executable program code and wherein the at least one specialized computer machine is specifically programmed to perform at least one step of the computer-implemented method; receiving, by the at least one specialized computer system, through at least one first computer programmed interface, from at least one first employer, at least the following information: i) job information, wherein the job information is related to at least one first position, ii) an identity of each job candidate applying to be interviewed, and iii) a selection identifying, from the plurality of position specific surveys, at least one first position specific survey related to at least one first position; wherein the at least one first employer requires references from a plurality of reference providers to be received for each job candidate before the at least one first employer decides whether or not to conduct a job interview; wherein the at least one computer system is independent from each job candidate and the at least one first employer; wherein the job information at least identifies whether the at least one first position involves managing others; receiving, by the at least one specialized computer system, through at least one second computer programmed interface, from a first job candidate from a plurality of job candidates applying to be interviewed, first contact information identifying the plurality of reference providers, automatically assigning, by the at least one specialized computer system, a first unique identifier to a first reference provider of the plurality of reference providers; automatically assigning, by the at least one specialized computer system, a second unique identifier to a second reference provider of the plurality of reference providers; automatically assigning, by the at least one specialized computer system, a third unique identifier to a third reference provider of the plurality of reference providers; automatically transmitting, by the at least one specialized computer system, at least one first personalized request to complete the at least one first position specific survey to the first reference provider, wherein the at least one first personalized request comprises: i) a first URL link to access the at least one first position specific survey, and ii) the first unique identifier, and iii) information informing that responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting, by the at least one specialized computer system, at least one second personalized request to complete the at least one first position specific survey to the second reference provider, wherein the at least one second personalized request comprises: i) a second URL link to access the at least one first position specific survey, and ii) the second unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting, by the at least one specialized computer system, at least one third personalized request to complete the at least one first position specific survey to the third reference provider, wherein the at least one third personalized request comprises: i) a third URL link to access the at least one first position specific survey, and ii) the third unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; causing to display, by the at least one specialized computer system, through at least one second computer interface, the at least one first position specific survey to the first, the second and the third reference providers in response to: i) the first, the second and the third URL links being activated respectively and ii) the first, the second and the third unique identifiers being supplied respectively; receiving, by the at least one specialized computer system, from the first, the second and the third reference providers, the responses to the at least one first position specific survey; calculating, by the at least one specialized computer system, each average score of the first job candidate in each competency skills group of the competency skills based on the responses in each competency skills group of the first, the second and the third reference providers; generating, by the at least one specialized computer system, for the at least one first employer, at least one reference report related to the first job candidate, wherein the at least one reference report comprises average scores of the first job candidate in the competency skills groups of the at least one first position specific survey, calculated based on the responses of the first, the second and the third reference providers so as to maintain the confidentiality of the responses of the plurality of reference providers from the at least one first employer and the first job candidate; wherein the average scores of the first job candidate are benchmarked against average scores of other job candidates who applied to a specific position that is at least similar to the at least one first position; and wherein the at least one reference report is configured to allow the at least one first employer to decide whether or not to conduct the job interview with the first job candidate who has applied to be interviewed. | 1. A computer-implemented method, comprising: generating, by at least one specialized computer system, a plurality of position specific surveys; wherein each position specific survey comprises a plurality of survey questions specific to competency skills related to performance of at least one position; wherein each survey question of the plurality of survey questions seeks a response in a form of a number on a numerical extent scale; wherein each position specific survey is configured for calculating an average score in each competency skills group of the competency skills by averaging numbers of the numerical extent scale across responses received from reference providers to the plurality of survey questions so that the responses from each of reference providers are confidential from employers and job candidates; wherein the at least one specialized computer system comprises at least one specialized computer machine comprising a non-transient memory having at least one region for storing specific computer executable program code and wherein the at least one specialized computer machine is specifically programmed to perform at least one step of the computer-implemented method; receiving, by the at least one specialized computer system, through at least one first computer programmed interface, from at least one first employer, at least the following information: i) job information, wherein the job information is related to at least one first position, ii) an identity of each job candidate applying to be interviewed, and iii) a selection identifying, from the plurality of position specific surveys, at least one first position specific survey related to at least one first position; wherein the at least one first employer requires references from a plurality of reference providers to be received for each job candidate before the at least one first employer decides whether or not to conduct a job interview; wherein the at least one computer system is independent from each job candidate and the at least one first employer; wherein the job information at least identifies whether the at least one first position involves managing others; receiving, by the at least one specialized computer system, through at least one second computer programmed interface, from a first job candidate from a plurality of job candidates applying to be interviewed, first contact information identifying the plurality of reference providers, automatically assigning, by the at least one specialized computer system, a first unique identifier to a first reference provider of the plurality of reference providers; automatically assigning, by the at least one specialized computer system, a second unique identifier to a second reference provider of the plurality of reference providers; automatically assigning, by the at least one specialized computer system, a third unique identifier to a third reference provider of the plurality of reference providers; automatically transmitting, by the at least one specialized computer system, at least one first personalized request to complete the at least one first position specific survey to the first reference provider, wherein the at least one first personalized request comprises: i) a first URL link to access the at least one first position specific survey, and ii) the first unique identifier, and iii) information informing that responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting, by the at least one specialized computer system, at least one second personalized request to complete the at least one first position specific survey to the second reference provider, wherein the at least one second personalized request comprises: i) a second URL link to access the at least one first position specific survey, and ii) the second unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting, by the at least one specialized computer system, at least one third personalized request to complete the at least one first position specific survey to the third reference provider, wherein the at least one third personalized request comprises: i) a third URL link to access the at least one first position specific survey, and ii) the third unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; causing to display, by the at least one specialized computer system, through at least one second computer interface, the at least one first position specific survey to the first, the second and the third reference providers in response to: i) the first, the second and the third URL links being activated respectively and ii) the first, the second and the third unique identifiers being supplied respectively; receiving, by the at least one specialized computer system, from the first, the second and the third reference providers, the responses to the at least one first position specific survey; calculating, by the at least one specialized computer system, each average score of the first job candidate in each competency skills group of the competency skills based on the responses in each competency skills group of the first, the second and the third reference providers; generating, by the at least one specialized computer system, for the at least one first employer, at least one reference report related to the first job candidate, wherein the at least one reference report comprises average scores of the first job candidate in the competency skills groups of the at least one first position specific survey, calculated based on the responses of the first, the second and the third reference providers so as to maintain the confidentiality of the responses of the plurality of reference providers from the at least one first employer and the first job candidate; wherein the average scores of the first job candidate are benchmarked against average scores of other job candidates who applied to a specific position that is at least similar to the at least one first position; and wherein the at least one reference report is configured to allow the at least one first employer to decide whether or not to conduct the job interview with the first job candidate who has applied to be interviewed. 2. The computer method of claim 1 , wherein the average scores of the first job candidate are benchmarked on a company-wide basis. | 0.80522 |
1. A non-transitory computer-readable medium comprising a plurality of computer instructions executable by a computing device, wherein, when executed, the plurality of computer instructions cause the computing device to at least: obtain a text block; identify a series of characters within the text block according to at least one rule, the series of characters being a subset of the text block; bind the series of characters to generate a text unit; assign a label to the text unit based at least upon content in the text unit, wherein the label specifies that the text unit is a particular class of text unit; encode the text block to generate an encoded text block, wherein the encoded text block specifies the label for the text unit and comprises a first signal that instructs an application to: cause an entirety of the series of characters in the text unit to be selected in response to a first selection of a subset of the series of characters; and cause a text format of the text unit to be visually contrasted from a remainder of the text in the text block; decode the encoded text block to generate a decoded text block, the decoded text block comprising the series of characters bound as the text unit; and encode, in response to a second selection of the subset of the series of characters in the decoded text block, the decoded text block to generate an additional encoded text block, wherein the additional encoded text block comprises metadata indicating an unbinding of the series of characters, and wherein the additional encoded text block comprises a second signal that instructs the application to: cause the label to be removed; and cause the entirety of the series of characters to be treated as being unbound. | 1. A non-transitory computer-readable medium comprising a plurality of computer instructions executable by a computing device, wherein, when executed, the plurality of computer instructions cause the computing device to at least: obtain a text block; identify a series of characters within the text block according to at least one rule, the series of characters being a subset of the text block; bind the series of characters to generate a text unit; assign a label to the text unit based at least upon content in the text unit, wherein the label specifies that the text unit is a particular class of text unit; encode the text block to generate an encoded text block, wherein the encoded text block specifies the label for the text unit and comprises a first signal that instructs an application to: cause an entirety of the series of characters in the text unit to be selected in response to a first selection of a subset of the series of characters; and cause a text format of the text unit to be visually contrasted from a remainder of the text in the text block; decode the encoded text block to generate a decoded text block, the decoded text block comprising the series of characters bound as the text unit; and encode, in response to a second selection of the subset of the series of characters in the decoded text block, the decoded text block to generate an additional encoded text block, wherein the additional encoded text block comprises metadata indicating an unbinding of the series of characters, and wherein the additional encoded text block comprises a second signal that instructs the application to: cause the label to be removed; and cause the entirety of the series of characters to be treated as being unbound. 5. The non-transitory computer-readable medium of claim 1 , wherein the label specifies that the series of characters in the text unit indicates a tracking number. | 0.555695 |
1. A method comprising: receiving data, wherein the data is organized as a plurality of named fields, wherein each named field includes a set of values associated with the named field, wherein each named field is assigned to a category from a plurality of categories and wherein each set of values includes two or more entries; determining, for at least one category, whether there is at least one identifier field for that category, wherein each identifier field is a named field that acts as an identifier for that category; and selecting a concept, wherein selecting the concept includes: determining whether one of the categories includes an identifier field that has a unique value for each entry in the identifier field set of values and, if so, selecting the identifier field as the concept; if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values, determining whether one of the categories includes two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values and, if so, selecting the combined identifier fields as the concept; and if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values and if none of the categories include two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values, adding a new identifier field, wherein adding the new identifier field includes providing a unique value for each entry in set of values included in the new identifier field, associating the new identifier field with one of the categories, and selecting the new identifier field as the concept. | 1. A method comprising: receiving data, wherein the data is organized as a plurality of named fields, wherein each named field includes a set of values associated with the named field, wherein each named field is assigned to a category from a plurality of categories and wherein each set of values includes two or more entries; determining, for at least one category, whether there is at least one identifier field for that category, wherein each identifier field is a named field that acts as an identifier for that category; and selecting a concept, wherein selecting the concept includes: determining whether one of the categories includes an identifier field that has a unique value for each entry in the identifier field set of values and, if so, selecting the identifier field as the concept; if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values, determining whether one of the categories includes two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values and, if so, selecting the combined identifier fields as the concept; and if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values and if none of the categories include two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values, adding a new identifier field, wherein adding the new identifier field includes providing a unique value for each entry in set of values included in the new identifier field, associating the new identifier field with one of the categories, and selecting the new identifier field as the concept. 10. The method of claim 1 , wherein adding the new identifier field includes inserting a unique value in that field for each entry of the set of values. | 0.558824 |
25. A system for managing a pre-defined patient intake form completion process prior to a scheduled appointment, the system comprising: at least one interface configured to: provide a pre-defined patient intake form comprising a plurality of questions in a selected language, wherein at least a portion of the plurality of questions request free form answers, receive a completed patient intake form corresponding with the pre-defined patient intake form prior to the scheduled appointment, the completed patient intake form comprising the free form answers for translation by a translation specialist if the selected language does not match a service provider language, provide the completed patient intake form to the translation specialist, and receive a translation of the completed patient intake form; and a processing engine configured to: process the completed patient intake form to determine whether the selected language matches the service provider language, determine a priority of a work item associated with the completed patient intake form based on at least one of an appointment date and an appointment time of the scheduled appointment, queue the work item if the selected language does not match the service provider language, wherein the work item is queued based on the priority associated with the work item, dequeue the work item when the completed patient intake form is provided to the translation specialist based on the determined priority, and generate a provider form based on at least one of the completed patient intake form and the translation of the completed patient intake form provided by the translation specialist. | 25. A system for managing a pre-defined patient intake form completion process prior to a scheduled appointment, the system comprising: at least one interface configured to: provide a pre-defined patient intake form comprising a plurality of questions in a selected language, wherein at least a portion of the plurality of questions request free form answers, receive a completed patient intake form corresponding with the pre-defined patient intake form prior to the scheduled appointment, the completed patient intake form comprising the free form answers for translation by a translation specialist if the selected language does not match a service provider language, provide the completed patient intake form to the translation specialist, and receive a translation of the completed patient intake form; and a processing engine configured to: process the completed patient intake form to determine whether the selected language matches the service provider language, determine a priority of a work item associated with the completed patient intake form based on at least one of an appointment date and an appointment time of the scheduled appointment, queue the work item if the selected language does not match the service provider language, wherein the work item is queued based on the priority associated with the work item, dequeue the work item when the completed patient intake form is provided to the translation specialist based on the determined priority, and generate a provider form based on at least one of the completed patient intake form and the translation of the completed patient intake form provided by the translation specialist. 37. The system of claim 25 , wherein processing engine is configured to queue the work item based on at least one of: the selected language associated with the work item, an identity of the service provider, and an availability of translation specialists. | 0.599907 |
21. The one or more non-transitory computer readable media of claim 16 , wherein the question is obtained from a user. | 21. The one or more non-transitory computer readable media of claim 16 , wherein the question is obtained from a user. 22. The one or more non-transitory computer readable media of claim 21 , wherein the process further comprises providing the new answer to a user. | 0.950271 |
23. The apparatus of claim 22 , wherein the execution mechanism is configured to perform a garbage-collection operation to remove excess or unused resources from the cache or set resources as purgeable if those resources are over the purgeable age. | 23. The apparatus of claim 22 , wherein the execution mechanism is configured to perform a garbage-collection operation to remove excess or unused resources from the cache or set resources as purgeable if those resources are over the purgeable age. 24. The apparatus of claim 23 , wherein upon receiving a resource query for resources in a given subcache after the resource has been added to the cache or removed from the cache, the execution mechanism is configured to perform a corresponding filtering query on the cache and a corresponding filtering query on any intervening subcaches to update the given subcache to account for the added or removed resource. | 0.807663 |
19. A non-transitory computer readable storage medium storing one or more programs for execution by the one or more processors of a computer system, the one or more programs comprising instructions for: receiving message information from a server system, the message information representing a set of messages, and an importance score associated with each respective message in the set of messages, wherein the importance score is generated based at least in part on a global importance prediction model, and a user importance prediction model; in accordance with a determination that the set of messages include one or more unread priority messages, wherein priority messages comprise messages with which the associated importance score satisfy one or more predefined message importance criteria: presenting a new mail notification, wherein the global importance prediction model includes a social graph-related weight, the user importance prediction model is based on information associated with a single user, and the global importance prediction model is based on information associated with a plurality of users. | 19. A non-transitory computer readable storage medium storing one or more programs for execution by the one or more processors of a computer system, the one or more programs comprising instructions for: receiving message information from a server system, the message information representing a set of messages, and an importance score associated with each respective message in the set of messages, wherein the importance score is generated based at least in part on a global importance prediction model, and a user importance prediction model; in accordance with a determination that the set of messages include one or more unread priority messages, wherein priority messages comprise messages with which the associated importance score satisfy one or more predefined message importance criteria: presenting a new mail notification, wherein the global importance prediction model includes a social graph-related weight, the user importance prediction model is based on information associated with a single user, and the global importance prediction model is based on information associated with a plurality of users. 22. The non-transitory computer readable storage medium of claim 19 , wherein the importance score associated with a respective message is generated by: determining a first weight for the respective message using the global importance prediction model; determining a second weight for the respective message using the user importance prediction model; and combining the first weight and the second weight. | 0.5 |
8. A method of delivering search results comprising: using a computing device, receiving, by a search engine, a search string comprising search terms; using the computing device, identifying pages relevant to the search string; using the computing device, for each of the identified pages relevant to the search string: obtaining a snippet for the corresponding identified page, the snippet is an excerpt from the corresponding identified page, the snippet, generated by searching a database, illustrates relevance of the corresponding identified page to the search string; determining that the snippet does not contain search terms of the search string, obtaining reference information comprising first anchor text of a link to the corresponding identified page from a web page other than the corresponding identified page, the first anchor text is used by the web page other than the corresponding identified page to reference the corresponding identified page; and displaying links to each identified page with the snippet and the obtained reference information for the identified page, wherein the reference information further comprises a second anchor text used by another page to link to the at least one of the identified pages, wherein the second anchor text is different from the first anchor text, and wherein the second anchor text is relevant to the search string. | 8. A method of delivering search results comprising: using a computing device, receiving, by a search engine, a search string comprising search terms; using the computing device, identifying pages relevant to the search string; using the computing device, for each of the identified pages relevant to the search string: obtaining a snippet for the corresponding identified page, the snippet is an excerpt from the corresponding identified page, the snippet, generated by searching a database, illustrates relevance of the corresponding identified page to the search string; determining that the snippet does not contain search terms of the search string, obtaining reference information comprising first anchor text of a link to the corresponding identified page from a web page other than the corresponding identified page, the first anchor text is used by the web page other than the corresponding identified page to reference the corresponding identified page; and displaying links to each identified page with the snippet and the obtained reference information for the identified page, wherein the reference information further comprises a second anchor text used by another page to link to the at least one of the identified pages, wherein the second anchor text is different from the first anchor text, and wherein the second anchor text is relevant to the search string. 9. The method of claim 8 , wherein the referencing information further comprises a link to at least one referencing page using the first anchor text to link to the at least one of the identified pages. | 0.606511 |
1. An electronic device comprising: a memory configured to store a user pronunciation lexicon; a voice inputter; and a processor configured to: control the voice inputter to receive a user voice, obtain a word corresponding to the user voice using the user pronunciation lexicon, obtain a first pronunciation for a phoneme included in the user voice, compare the first pronunciation and a second pronunciation pre stored for the word, identify a pronunciation pattern by using a result of the comparing, and update the user pronunciation lexicon according to a pronunciation pattern rule obtained based on the pronunciation pattern, wherein the pronunciation pattern rule is a rule that a user repeats according to at least one of a pronunciation habit of the user and a pronunciation characteristic of the user. | 1. An electronic device comprising: a memory configured to store a user pronunciation lexicon; a voice inputter; and a processor configured to: control the voice inputter to receive a user voice, obtain a word corresponding to the user voice using the user pronunciation lexicon, obtain a first pronunciation for a phoneme included in the user voice, compare the first pronunciation and a second pronunciation pre stored for the word, identify a pronunciation pattern by using a result of the comparing, and update the user pronunciation lexicon according to a pronunciation pattern rule obtained based on the pronunciation pattern, wherein the pronunciation pattern rule is a rule that a user repeats according to at least one of a pronunciation habit of the user and a pronunciation characteristic of the user. 7. The electronic device as claimed in claim 1 , wherein the processor is further configured to delete a pronunciation string that the user does not use for more than a predetermined number of times among pronunciation strings stored in the user pronunciation lexicon and add the pronunciation string that is not stored in the user pronunciation lexicon among pronunciation strings generated based on the pronunciation pattern rule to the user pronunciation lexicon. | 0.5 |
1. A method for identifying a most likely source language of a snippet, comprising: receiving an indication of the snippet, wherein the snippet is a digital representation of words or character groups; determining two or more possible source languages for the snippet; generating, by one or more machine translation engines, two or more translations of the snippet each having a specified translation source language, wherein at least one of the two or more translations of the snippet is generated having a first of the two or more possible source languages for the snippet set as the specified translation source language, and wherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first of the two or more possible source languages for the snippet set as the specified translation source language; computing, by one or more translation score models trained using or more neural networks, accuracy scores for at least two of the generated two or more translations of the snippet; producing a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language; and selecting, as the most likely source language, the possible source language for the snippet that is associated with a highest confidence factor. | 1. A method for identifying a most likely source language of a snippet, comprising: receiving an indication of the snippet, wherein the snippet is a digital representation of words or character groups; determining two or more possible source languages for the snippet; generating, by one or more machine translation engines, two or more translations of the snippet each having a specified translation source language, wherein at least one of the two or more translations of the snippet is generated having a first of the two or more possible source languages for the snippet set as the specified translation source language, and wherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first of the two or more possible source languages for the snippet set as the specified translation source language; computing, by one or more translation score models trained using or more neural networks, accuracy scores for at least two of the generated two or more translations of the snippet; producing a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language; and selecting, as the most likely source language, the possible source language for the snippet that is associated with a highest confidence factor. 5. The method of claim 1 further comprising: performing an initial source language identification for the snippet; wherein the initial source language identification for the snippet identifies one or more of the possible source languages each with a corresponding initial confidence value; and wherein each initial confidence value indicates, for a corresponding possible source language, a confidence that the corresponding possible source language is a language of the snippet. | 0.626617 |
14. An information processing method comprising: retrieving first experience information of a person, the first experience information indicating a future experience of the person and including information related to non-geographical experience scene; retrieving second experience information of other people, the second experience information indicating future experiences of other people and including information related to non-geographical experience scene; and extracting, from among the other people, those people who have a commonality with the person based on the information including the non-geographical experience scene of the first experience information and the information including the non-geographical experience scene of the second experience information. | 14. An information processing method comprising: retrieving first experience information of a person, the first experience information indicating a future experience of the person and including information related to non-geographical experience scene; retrieving second experience information of other people, the second experience information indicating future experiences of other people and including information related to non-geographical experience scene; and extracting, from among the other people, those people who have a commonality with the person based on the information including the non-geographical experience scene of the first experience information and the information including the non-geographical experience scene of the second experience information. 21. The information processing method according to claim 14 , further comprising: recommending a time or a place for avoiding experience sharing with another person to at least a part of the other people included in the extracted people. | 0.684444 |
7. An information handling system comprising: one or more processors; one or more data stores accessible by at least one of the processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: performing a biological meaningfulness analysis on a biological relationship graph that has a plurality of paths through the graph, wherein each of the plurality of paths includes a plurality of connected nodes, and wherein the biological meaningfulness analysis is based on a process similarity calculation of gene ontologies of the nodes in the paths and a contextual similarity calculation of word occurrences from a plurality of documents in a corpus where a reference to the respective nodes are found; performing a biological interestingness analysis on the biological relationship graph that is based on a path diversity value calculated for each of the paths and a path rarity value calculated for each of the paths, wherein the path diversity value is based on a number of distinct documents in each of the paths and the number of connections in the respective paths, and wherein the path rarity value is based a total degrees of nodes that form each of the paths; and screening the plurality of paths in the biological relationship graph based on the biological meaningfulness analysis and the biological interestingness analysis, wherein the screened plurality of paths are displayed to a user, and wherein the screening further comprises actions of: identifying one or more meaningful paths through the biological relationship graph based on comparing a path meaningfulness value (PMV) with a threshold; and ranking the meaningful paths by a path interestingness value (PIV) corresponding to each of the meaningful paths. | 7. An information handling system comprising: one or more processors; one or more data stores accessible by at least one of the processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: performing a biological meaningfulness analysis on a biological relationship graph that has a plurality of paths through the graph, wherein each of the plurality of paths includes a plurality of connected nodes, and wherein the biological meaningfulness analysis is based on a process similarity calculation of gene ontologies of the nodes in the paths and a contextual similarity calculation of word occurrences from a plurality of documents in a corpus where a reference to the respective nodes are found; performing a biological interestingness analysis on the biological relationship graph that is based on a path diversity value calculated for each of the paths and a path rarity value calculated for each of the paths, wherein the path diversity value is based on a number of distinct documents in each of the paths and the number of connections in the respective paths, and wherein the path rarity value is based a total degrees of nodes that form each of the paths; and screening the plurality of paths in the biological relationship graph based on the biological meaningfulness analysis and the biological interestingness analysis, wherein the screened plurality of paths are displayed to a user, and wherein the screening further comprises actions of: identifying one or more meaningful paths through the biological relationship graph based on comparing a path meaningfulness value (PMV) with a threshold; and ranking the meaningful paths by a path interestingness value (PIV) corresponding to each of the meaningful paths. 11. The information handling system of claim 7 wherein performing the biological interestingness analysis further comprises actions of: selecting each of the plurality of paths through the graph; for each of the selected paths: selecting each of the connections between the nodes that form the selected path; setting a degree of each of the selected nodes included in the selected path to a number of connections between the selected node an other nodes in the graph; and calculating the path rarity value as a total number of degrees included in all of the nodes that form the selected path. | 0.589953 |
4. A peripheral device control method for an information processing apparatus capable of managing a peripheral device, the method comprising: managing a peripheral device application via a peripheral device management screen to be displayed in a viewing area using peripheral device management function control information that defines information required to control each function; storing storage destination information relating to the peripheral device application in a storage unit; externally designating the storage destination information; and comparing first language information included in first storage destination information externally designated with second language information included in second storage destination information stored in the storage unit, wherein the display of the peripheral device management screen is switched using language information included in the peripheral device management function control information and the second language information, and the peripheral device application switches a view content of the viewing area using the first storage destination information when the first language information matches the second language information, and using third storage destination information, which can be generated by replacing the first language information included in the first storage destination information by the second language information, when the first language information does not match the second language information. | 4. A peripheral device control method for an information processing apparatus capable of managing a peripheral device, the method comprising: managing a peripheral device application via a peripheral device management screen to be displayed in a viewing area using peripheral device management function control information that defines information required to control each function; storing storage destination information relating to the peripheral device application in a storage unit; externally designating the storage destination information; and comparing first language information included in first storage destination information externally designated with second language information included in second storage destination information stored in the storage unit, wherein the display of the peripheral device management screen is switched using language information included in the peripheral device management function control information and the second language information, and the peripheral device application switches a view content of the viewing area using the first storage destination information when the first language information matches the second language information, and using third storage destination information, which can be generated by replacing the first language information included in the first storage destination information by the second language information, when the first language information does not match the second language information. 5. A non-transitory computer-readable storage medium storing a program that causes a computer to execute the peripheral device control method defined in claim 4 . | 0.825107 |
29. A system for graphically characterizing statements about an object, comprising: a sub system configured, as a result of the computing hardware and programmable memory, to apply frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; a sub system configured, as a result of the computing hardware and programmable memory, to identify a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a sentiment of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a polarity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize an intensity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to determine a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; a sub system configured, as a result of the computing hardware and programmable memory, to produce a first graphical representation, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and a sub-system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a second axis, in accordance with the net intensity measure. | 29. A system for graphically characterizing statements about an object, comprising: a sub system configured, as a result of the computing hardware and programmable memory, to apply frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; a sub system configured, as a result of the computing hardware and programmable memory, to identify a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a sentiment of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize a polarity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to categorize an intensity of each statement, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to determine a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; a sub system configured, as a result of the computing hardware and programmable memory, to produce a first graphical representation, of the first object-specific corpus; a sub system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and a sub-system configured, as a result of the computing hardware and programmable memory, to place the first graphical representation, relative to a second axis, in accordance with the net intensity measure. 31. The system of claim 29 , further comprising: a sub-system configured to produce of a first and a second dividing line, each dividing line parallel to, respectively, the first axis and the second axis; a sub-system configured to apply frame extraction, to a second corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; a sub-system configured to identify a first plurality of object-specific corpuses, each of which is a subset of the second corpus, where all the statements, of an object-specific corpus, are about a same object; a sub-system configured to categorize a polarity and intensity of each statement of each object-specific corpus, wherein each object-specific corpus is a member of the first plurality of object-specific corpuses; a sub-system configured to determine a second net polarity measure and a second net intensity measure, for each object-specific corpus, as a function of the categorization, wherein each object-specific corpus is a member of the first plurality of object-specific corpuses; a sub-system configured to determine a median net polarity measure, from the second net polarity measures; a sub-system configured to determine a median net intensity measure, from the second net intensity measures; and a sub-system configured to place each of the first and second dividing lines, respectively, at a location that approximately intersects the median net intensity and median net polarity measures. | 0.5 |
9. The computationally-implemented method of claim 1 , wherein said soliciting, based at least in part on a hypothesis that links one or more objective occurrences with one or more subjective user states and in response at least in part to an incidence of at least one subjective user state associated with a user, at least a portion of objective occurrence data including data indicating incidence of at least one objective occurrence comprises: requesting for the data indicating incidence of at least one objective occurrence from one or more remote devices. | 9. The computationally-implemented method of claim 1 , wherein said soliciting, based at least in part on a hypothesis that links one or more objective occurrences with one or more subjective user states and in response at least in part to an incidence of at least one subjective user state associated with a user, at least a portion of objective occurrence data including data indicating incidence of at least one objective occurrence comprises: requesting for the data indicating incidence of at least one objective occurrence from one or more remote devices. 14. The computationally-implemented method of claim 9 , wherein said requesting for the data indicating incidence of at least one objective occurrence from one or more remote devices comprises: requesting for the data indicating incidence of at least one objective occurrence from one or more sensors. | 0.789799 |
1. A computer-implemented method comprising: decomposing, by at least one processor of a computer system, a search query that includes three or more words into a plurality of candidate phrasifications, including different groupings of words of the search query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the search query; scoring, by at least one of the processors of the computer system, at least two of the candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, and wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases, and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; selecting, by at least one of the processors of the computer system and based on scores of the candidate phrasifications, a subset of the candidate phrasification; and executing a query of a document indexing, by at least one of the processors of the computer system, using the selected subset of candidate phrasifications, wherein the query comprises the component phrases of each selected phrasification. | 1. A computer-implemented method comprising: decomposing, by at least one processor of a computer system, a search query that includes three or more words into a plurality of candidate phrasifications, including different groupings of words of the search query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the search query; scoring, by at least one of the processors of the computer system, at least two of the candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, and wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases, and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; selecting, by at least one of the processors of the computer system and based on scores of the candidate phrasifications, a subset of the candidate phrasification; and executing a query of a document indexing, by at least one of the processors of the computer system, using the selected subset of candidate phrasifications, wherein the query comprises the component phrases of each selected phrasification. 18. The method of claim 1 , wherein the selected subset of candidate phrasifications is organized as a Boolean phrase tree. | 0.650225 |
1. A depth detection apparatus comprising: a memory storing raw time-of-flight sensor data received from a time-of-flight sensor; and a processor comprising a trained machine learning component having been trained using training data pairs, a training data pair comprising at least one simulated raw time-of-flight sensor frame and a corresponding simulated ground truth depth map; the trained machine learning component configured to compute in a single stage, for an item of the stored raw time-of-flight sensor data, a depth map of a surface depicted by the item, by pushing the item through the trained machine learning component. | 1. A depth detection apparatus comprising: a memory storing raw time-of-flight sensor data received from a time-of-flight sensor; and a processor comprising a trained machine learning component having been trained using training data pairs, a training data pair comprising at least one simulated raw time-of-flight sensor frame and a corresponding simulated ground truth depth map; the trained machine learning component configured to compute in a single stage, for an item of the stored raw time-of-flight sensor data, a depth map of a surface depicted by the item, by pushing the item through the trained machine learning component. 14. The apparatus of claim 1 where the trained machine learning component is a convolutional neural network and where each training data pair comprises a frame of simulated raw time-of-flight sensor data and a ground truth depth map. | 0.633903 |
10. In a computing environment, a system comprising: a computer; a topic identification mechanism implemented at least in part by the computer and configured for extracting topics from a set of web pages that correspond to a query, wherein the topics are noun phrases that represent subjects of the web pages; a topic match mechanism implemented at least in part by the computer and coupled to the topic identification mechanism and configured for computing a relevance score for each extracted topic, wherein each relevance score is based on a predicted match level from a group of match levels comprising a first match level that indicates an exact match between the each extracted topic and the query, a second match level that indicates a same meaning between the each extracted topic and the query, a third match level that indicates that the each extracted topic is relevant to the query, a fourth match level that indicates that the each extracted topic is irrelevant to the query, and a fifth match level that indicates that the each extracted topic does not match the query, and wherein the predicted match level is based on a conditional probability model P(L|Q→T) where L denotes a level, and where Q→T denotes an event that comprises generating topic T from query Q; and a page ordering mechanism implemented at least in part by the computer and coupled to the topic match mechanism and configured for ranking the web pages relative to one another based on the relevance score computed for each web page. | 10. In a computing environment, a system comprising: a computer; a topic identification mechanism implemented at least in part by the computer and configured for extracting topics from a set of web pages that correspond to a query, wherein the topics are noun phrases that represent subjects of the web pages; a topic match mechanism implemented at least in part by the computer and coupled to the topic identification mechanism and configured for computing a relevance score for each extracted topic, wherein each relevance score is based on a predicted match level from a group of match levels comprising a first match level that indicates an exact match between the each extracted topic and the query, a second match level that indicates a same meaning between the each extracted topic and the query, a third match level that indicates that the each extracted topic is relevant to the query, a fourth match level that indicates that the each extracted topic is irrelevant to the query, and a fifth match level that indicates that the each extracted topic does not match the query, and wherein the predicted match level is based on a conditional probability model P(L|Q→T) where L denotes a level, and where Q→T denotes an event that comprises generating topic T from query Q; and a page ordering mechanism implemented at least in part by the computer and coupled to the topic match mechanism and configured for ranking the web pages relative to one another based on the relevance score computed for each web page. 11. The system of claim 10 wherein the topic identification mechanism is further configured for extracting topics from at least one of a group comprising a title of the web page, anchor text of the web page, a uniform resource locator (“URL”) referencing the web page, tags assigned to the web page, a query associated with the web page, and a body of the web page. | 0.5 |
10. The computer-implemented method of claim 6 , further comprising displaying content associated with the matched item on the source web page document. | 10. The computer-implemented method of claim 6 , further comprising displaying content associated with the matched item on the source web page document. 11. The computer-implemented method of claim 10 , wherein: the matched item comprises a keyword; and the associated content comprises an advertisement. | 0.967312 |
1. A method comprising: determining a set of item-item affinities between a first item and a first plurality of items from a set of user-item data; determining a first set of nearest neighbor items from the first plurality of items based in part on the set of item-item affinities; determining a set of user feature-item affinities between a second plurality of items and a set of user features; determining a second set of nearest neighbor items based at least in part on the set of user feature-item affinities; determining affinity weights for a set of candidate items, the set of candidate items to be determined at least in part on the first set of nearest neighbor items and the second set of nearest neighbor items; and presenting to a user as a recommendation a candidate item from the set of candidate items, the candidate item to be determined at least in part based on an affinity weight of the candidate item; wherein determining the set of item-item affinities between the first item and the first plurality of items comprises for each particular column of a user-item matrix, setting an item-item affinity between the first item and another item represented by the particular column equal to a cosine similarity between the particular column and a first column of the user-item matrix representing the first item; wherein said each particular column of the user-item matrix indicates multiple ratings that multiple users have given to an item represented by said each particular column; wherein determining the set of user feature-item affinities between the second plurality of items and the set of user features comprises performing least square regression relative to an equation involving both said user-item matrix and a user profile matrix that is separate from said user-item matrix; wherein each particular column of the user profile matrix corresponds to a different user feature of a plurality of user features; wherein all user features in said plurality of user features differ from all items represented by columns of said user-item matrix; wherein each particular row of said user profile matrix corresponds to a different user of a plurality of users; and wherein the method is performed by one or more computing devices programmed to be special purpose machines pursuant to program instructions. | 1. A method comprising: determining a set of item-item affinities between a first item and a first plurality of items from a set of user-item data; determining a first set of nearest neighbor items from the first plurality of items based in part on the set of item-item affinities; determining a set of user feature-item affinities between a second plurality of items and a set of user features; determining a second set of nearest neighbor items based at least in part on the set of user feature-item affinities; determining affinity weights for a set of candidate items, the set of candidate items to be determined at least in part on the first set of nearest neighbor items and the second set of nearest neighbor items; and presenting to a user as a recommendation a candidate item from the set of candidate items, the candidate item to be determined at least in part based on an affinity weight of the candidate item; wherein determining the set of item-item affinities between the first item and the first plurality of items comprises for each particular column of a user-item matrix, setting an item-item affinity between the first item and another item represented by the particular column equal to a cosine similarity between the particular column and a first column of the user-item matrix representing the first item; wherein said each particular column of the user-item matrix indicates multiple ratings that multiple users have given to an item represented by said each particular column; wherein determining the set of user feature-item affinities between the second plurality of items and the set of user features comprises performing least square regression relative to an equation involving both said user-item matrix and a user profile matrix that is separate from said user-item matrix; wherein each particular column of the user profile matrix corresponds to a different user feature of a plurality of user features; wherein all user features in said plurality of user features differ from all items represented by columns of said user-item matrix; wherein each particular row of said user profile matrix corresponds to a different user of a plurality of users; and wherein the method is performed by one or more computing devices programmed to be special purpose machines pursuant to program instructions. 6. The method of claim 1 , further comprising: recalculating a weighting of the first set of nearest neighbors items or the second set of nearest neighbor items. | 0.572814 |
1. A program product for automating a filing to an electronic submission portal, the program product including one or more non-transitory storage media on which executable program code is recorded, the executable program code comprising: a data acquisition component that, when executed by one or more processors in the computing platform, is configured to acquire data from one or more source systems and extract data components utilized in the filing; a filing creation component that, when executed by one or more processors disposed in the computing platform, is configured to merge one or more of the extracted data components into the filing; a filing completion component that is configured to create automated workflow routines for the filing that are compatible with the electronic submission portal, monitoring errors at the electronic submission portal, adapting one or more of the automated workflow routines in response to a first of one or more errors, discontinuing one or more of the automated workflow routines in response to a second of one or more errors, and aborting the filing in response to a third of one or more errors so that incorrect filings do not occur, and a polling component that is configured to poll a docket and execute decision-making to identify associated filings with prior docketed events or other registered events or data from the polled docket for inclusion in the filing, the polling component being further configured for mining docket data to locate CM/ECF (Case Management/Electronic Case Filing) events that satisfy applicable requirements for cross-references for the identified associated filings, the cross-references including one of either a prior docket entry for the filing or an adversary case filing. | 1. A program product for automating a filing to an electronic submission portal, the program product including one or more non-transitory storage media on which executable program code is recorded, the executable program code comprising: a data acquisition component that, when executed by one or more processors in the computing platform, is configured to acquire data from one or more source systems and extract data components utilized in the filing; a filing creation component that, when executed by one or more processors disposed in the computing platform, is configured to merge one or more of the extracted data components into the filing; a filing completion component that is configured to create automated workflow routines for the filing that are compatible with the electronic submission portal, monitoring errors at the electronic submission portal, adapting one or more of the automated workflow routines in response to a first of one or more errors, discontinuing one or more of the automated workflow routines in response to a second of one or more errors, and aborting the filing in response to a third of one or more errors so that incorrect filings do not occur, and a polling component that is configured to poll a docket and execute decision-making to identify associated filings with prior docketed events or other registered events or data from the polled docket for inclusion in the filing, the polling component being further configured for mining docket data to locate CM/ECF (Case Management/Electronic Case Filing) events that satisfy applicable requirements for cross-references for the identified associated filings, the cross-references including one of either a prior docket entry for the filing or an adversary case filing. 15. The program product of claim 1 in which the executable program code further comprises an electronic submission portal interface component that is configured to implement automated interaction with the electronic submission portal that substantially mimics human interaction. | 0.552644 |
14. A computer-implemented method of characterizing an audience of subscribers to a digital content feed service to support selection or editing of preflight articles, the method comprising: selecting a plurality of articles to publish to the audience of subscribers based on one or more subscriber profiles; publishing the plurality of articles to the subscriber audience via the feed service; analyzing each of the published articles to generate article information; storing the generated article information for each published article in a data store in association with an identifier of a corresponding author; tracking individual subscriber actions associated with each of the published articles to acquire attention data, wherein tracking includes identifying if an individual subscriber leaves one or more of the published articles “unread”; analyzing the acquired attention data to form an indication of each subscriber's response to each of the published articles; storing the indicia of each subscriber's response to support correlation of subscriber attention to the stored article information; and building profiles based on the stored article information and the attention analyzer. | 14. A computer-implemented method of characterizing an audience of subscribers to a digital content feed service to support selection or editing of preflight articles, the method comprising: selecting a plurality of articles to publish to the audience of subscribers based on one or more subscriber profiles; publishing the plurality of articles to the subscriber audience via the feed service; analyzing each of the published articles to generate article information; storing the generated article information for each published article in a data store in association with an identifier of a corresponding author; tracking individual subscriber actions associated with each of the published articles to acquire attention data, wherein tracking includes identifying if an individual subscriber leaves one or more of the published articles “unread”; analyzing the acquired attention data to form an indication of each subscriber's response to each of the published articles; storing the indicia of each subscriber's response to support correlation of subscriber attention to the stored article information; and building profiles based on the stored article information and the attention analyzer. 17. The method of claim 14 wherein the digital content feed service is an internal enterprise content feed service. | 0.650348 |
22. The medium of claim 19 , wherein the search result conditioning component is configured to, for each respective search result of the search result group, determine a quantity of other search results of the search result group that are similar to the respective search result as being equivalent to the quantity of edges between the node representing the respective search result and one or more other nodes that represent search results in the connected graph. | 22. The medium of claim 19 , wherein the search result conditioning component is configured to, for each respective search result of the search result group, determine a quantity of other search results of the search result group that are similar to the respective search result as being equivalent to the quantity of edges between the node representing the respective search result and one or more other nodes that represent search results in the connected graph. 23. The medium of claim 22 , wherein to label the given search result, the search result conditioning component is configured to: determine a set of similar search results that includes the given search result and one or more particular search results based on the connectivity of the connected graph; determine a first search result of said set of similar search results, the first search result having a determined quantity that is higher than a determined quantity for each of the other search results; and assign a common label to each search result in the set of similar search results, wherein said particular label is the same as an identifier of said first search result. | 0.845004 |
6. The method of claim 4 , wherein the at least one phoneme-independent spectral feature vector is further decomposed into at least one content input sequence and authenticating the speech signal further comprises: authenticating the input speech signal if the at least one content input sequence is similar to the at least one content reference sequence. | 6. The method of claim 4 , wherein the at least one phoneme-independent spectral feature vector is further decomposed into at least one content input sequence and authenticating the speech signal further comprises: authenticating the input speech signal if the at least one content input sequence is similar to the at least one content reference sequence. 7. The method of claim 6 further comprising: determining similarity based on a distance calculated between the at least one content input sequence and the at least one content reference sequence. | 0.872995 |
6. An apparatus for inputting an alphabet character in a terminal with a numeric keypad comprising a plurality of keys with ambiguous character entry, the apparatus comprising: a memory for storing various alphabet characters input through the keypad and respective priority tables that correspond to the various alphabet characters, and storing in each of the priority tables, an occurrence frequency of at least two alphabet characters mapped, in the priority table, to a second key input immediately succeeding a corresponding first input character; and a controller for searching for a priority table whenever the key is stroked for a first input character, receiving a second input character by sequentially traversing a plurality of alphabet characters mapped to the second key, retrieved from the priority table in a prioritized order from higher associated frequency to lower associated frequency, and determining, as the second input character, a character from among the retrieved characters mapped to the second key, wherein the priority table has at least one association of a succeeding alphabet character with a position of the succeeding alphabet character in a word based on the succeeding alphabet character's frequency of occurrence succeeding the first input character. | 6. An apparatus for inputting an alphabet character in a terminal with a numeric keypad comprising a plurality of keys with ambiguous character entry, the apparatus comprising: a memory for storing various alphabet characters input through the keypad and respective priority tables that correspond to the various alphabet characters, and storing in each of the priority tables, an occurrence frequency of at least two alphabet characters mapped, in the priority table, to a second key input immediately succeeding a corresponding first input character; and a controller for searching for a priority table whenever the key is stroked for a first input character, receiving a second input character by sequentially traversing a plurality of alphabet characters mapped to the second key, retrieved from the priority table in a prioritized order from higher associated frequency to lower associated frequency, and determining, as the second input character, a character from among the retrieved characters mapped to the second key, wherein the priority table has at least one association of a succeeding alphabet character with a position of the succeeding alphabet character in a word based on the succeeding alphabet character's frequency of occurrence succeeding the first input character. 9. The apparatus of claim 6 , wherein the controller determines whether there is any key input corresponding to an end of inputting a sentence, and stores the sentence as a message, if the key input corresponds to the end of inputting the sentence. | 0.6785 |
16. The system of claim 15 , wherein the at least one processor is configured to execute the computer-executable instructions to compute the similarity measure based at least in part on accessing fingerprint information of the one or more other queries stored in the query classification database and comparing the fingerprint information of the one or more other queries to the fingerprint information of the identified query. | 16. The system of claim 15 , wherein the at least one processor is configured to execute the computer-executable instructions to compute the similarity measure based at least in part on accessing fingerprint information of the one or more other queries stored in the query classification database and comparing the fingerprint information of the one or more other queries to the fingerprint information of the identified query. 17. The system of claim 16 , wherein the at least one processor is configured to execute the computer-executable instructions to compute the similarity measure based on comparing one or more actions in the fingerprint information of the one or more other queries with one or more actions in the fingerprint information of the identified query. | 0.784384 |
1. A computer system for returning a list of playable media objects to a user, comprising: a server configured to receive a search query object from the user; a first module configured to: identify additional terms related to the search query object by providing the search query object to at least one internet search engine and processing results returned by the internet search engine, wherein processing includes: receiving a page identified in the result returned by the internet search engine, parsing the received page to extract terms from the page and identify sections in the page, generating relationship vectors based on the extracted terms, scoring sections of the received page based on the generated relationship vectors, and selecting additional terms based at least in part on the scores; and a second module configured to query one or more video storage web sites based on the identified additional terms to obtain a list of playable media objects stored on the one or more video storage web sites, the playable media objects comprising the identified additional terms. | 1. A computer system for returning a list of playable media objects to a user, comprising: a server configured to receive a search query object from the user; a first module configured to: identify additional terms related to the search query object by providing the search query object to at least one internet search engine and processing results returned by the internet search engine, wherein processing includes: receiving a page identified in the result returned by the internet search engine, parsing the received page to extract terms from the page and identify sections in the page, generating relationship vectors based on the extracted terms, scoring sections of the received page based on the generated relationship vectors, and selecting additional terms based at least in part on the scores; and a second module configured to query one or more video storage web sites based on the identified additional terms to obtain a list of playable media objects stored on the one or more video storage web sites, the playable media objects comprising the identified additional terms. 10. The computer system of claim 1 , wherein the second module is further configured to query a plurality of the video storage web sites in order to generate the list of playable media objects, and wherein the second module is configured to aggregate the query results and rank the query results in the list of playable media objects. | 0.5 |
5. The method of claim 1 further including the step of generating the flowchart, wherein this step includes the substeps of: defining the start unit, the start unit being graphically represented by a box; defining the one or more logic units, wherein each such definition includes the logic statement represented by the logic unit, and each logic unit is graphically represented by a box having an appearance different from the start unit box; defining the one or more value units, wherein each value unit is graphically represented by a box having an appearance different from the boxes of the start unit and the one or more logic units. | 5. The method of claim 1 further including the step of generating the flowchart, wherein this step includes the substeps of: defining the start unit, the start unit being graphically represented by a box; defining the one or more logic units, wherein each such definition includes the logic statement represented by the logic unit, and each logic unit is graphically represented by a box having an appearance different from the start unit box; defining the one or more value units, wherein each value unit is graphically represented by a box having an appearance different from the boxes of the start unit and the one or more logic units. 6. The method of claim 5 further including the substep of defining the paths, the paths being graphically represented by lines, wherein each line extends between two of the units. | 0.881654 |
8. An article of manufacture comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer to: receive one or more speech recognition parameters prior to issuing a verbal prompt to a user; issue the verbal prompt to the user; receive an acoustic input from the user in response to the verbal prompt; process one or more sequences of phonemes to obtain one or more acoustic representations, wherein the one or more sequences of phonemes are generated from a list of expected responses to the issued verbal prompt; compare the acoustic input from the user to the one or more acoustic representations to determine an acoustic channel characterization and/or speaker class; and adjust one or more speech recognition parameters based on the comparison, wherein the adjustment comprises an application of feature space mapping to the acoustic input, and further wherein the one or more adjusted speech recognition parameters are used to adapt a speech recognition module of a speech recognition system to use an acoustic model that is consistent with the acoustic channel characterization and/or speaker class so that the selected acoustic model is used for decoding subsequent acoustic input provided by the user as the conversation progresses. | 8. An article of manufacture comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer to: receive one or more speech recognition parameters prior to issuing a verbal prompt to a user; issue the verbal prompt to the user; receive an acoustic input from the user in response to the verbal prompt; process one or more sequences of phonemes to obtain one or more acoustic representations, wherein the one or more sequences of phonemes are generated from a list of expected responses to the issued verbal prompt; compare the acoustic input from the user to the one or more acoustic representations to determine an acoustic channel characterization and/or speaker class; and adjust one or more speech recognition parameters based on the comparison, wherein the adjustment comprises an application of feature space mapping to the acoustic input, and further wherein the one or more adjusted speech recognition parameters are used to adapt a speech recognition module of a speech recognition system to use an acoustic model that is consistent with the acoustic channel characterization and/or speaker class so that the selected acoustic model is used for decoding subsequent acoustic input provided by the user as the conversation progresses. 11. The article of claim 8 , wherein the comparison comprises a performance of a voice print analysis on the acoustic input. | 0.523409 |
7. The method of claim 6 wherein the text is stretched or shrunk to change the size of the text. | 7. The method of claim 6 wherein the text is stretched or shrunk to change the size of the text. 8. The method of claim 7 wherein the text is stretched or shrunk using standard multi-finger gestures. | 0.967712 |
1. A method for employing a printer to print a document, comprising: providing a print request and the document to the printer in a native, non-page-description-language, file format that is editable by a document-processing application; employing the print request to determine one or more pages of the document to be printed, wherein the print request includes information identifying the one or more pages; determining a page representation for each of the identified one or more pages of the document from the native file format independent of a page description language, wherein each page representation includes a plurality of graphics primitives that are directly supported by the printer; determining an image representation for each page representation based on the plurality of graphics primitives included with each corresponding page representation; determining separate subsets of the plurality of graphics primitives that correspond to separate bands of the one or more pages; rendering at least a portion of the one or more pages based on the separate subsets of graphics primitives; decompressing, at the printer, at least a portion of the document that corresponds to the one or more pages prior to determining each page representation; and printing the one or more pages of the document based on the determined image representations. | 1. A method for employing a printer to print a document, comprising: providing a print request and the document to the printer in a native, non-page-description-language, file format that is editable by a document-processing application; employing the print request to determine one or more pages of the document to be printed, wherein the print request includes information identifying the one or more pages; determining a page representation for each of the identified one or more pages of the document from the native file format independent of a page description language, wherein each page representation includes a plurality of graphics primitives that are directly supported by the printer; determining an image representation for each page representation based on the plurality of graphics primitives included with each corresponding page representation; determining separate subsets of the plurality of graphics primitives that correspond to separate bands of the one or more pages; rendering at least a portion of the one or more pages based on the separate subsets of graphics primitives; decompressing, at the printer, at least a portion of the document that corresponds to the one or more pages prior to determining each page representation; and printing the one or more pages of the document based on the determined image representations. 4. The method of claim 1 , further comprising: obtaining the one or more pages of the document at the printer straight from a portable storage medium connected to an input interface of the printer. | 0.843354 |
21. A non-transitory machine-readable storage device having instructions stored thereon which, when executed by at least one data processing apparatus, cause the at least one data processing apparatus to perform operations comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; obtaining search results responsive to the query during a second time period that chronologically follows the plurality of time periods; adjusting a ranking of the first search result in the obtained search results during the second time period. | 21. A non-transitory machine-readable storage device having instructions stored thereon which, when executed by at least one data processing apparatus, cause the at least one data processing apparatus to perform operations comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; obtaining search results responsive to the query during a second time period that chronologically follows the plurality of time periods; adjusting a ranking of the first search result in the obtained search results during the second time period. 28. The storage device of claim 21 wherein the first time period and the second time period are each a same day of a week, same days of a week, same annual holidays, same weeks of a month, same weeks of a year, same biweekly periods of a year, same months of a year, or same seasons of a year. | 0.511556 |
15. A system comprising: one or more processors; storage media storing executable instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: obtaining a plurality of search results for a query based on first relevance scores; classifying the plurality of search results into a plurality of classifications; generating second relevance scores for the plurality of search results based on respective rankings of the plurality of search results in corresponding classifications of the plurality of classifications; and ranking the plurality of search results based on the first relevance scores and the second relevance scores. | 15. A system comprising: one or more processors; storage media storing executable instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: obtaining a plurality of search results for a query based on first relevance scores; classifying the plurality of search results into a plurality of classifications; generating second relevance scores for the plurality of search results based on respective rankings of the plurality of search results in corresponding classifications of the plurality of classifications; and ranking the plurality of search results based on the first relevance scores and the second relevance scores. 16. The system of claim 15 , the acts further comprising extracting a preset number of search results from the plurality of search results. | 0.511822 |
16. An article of manufacture comprising: a computer-readable storage medium having executable instructions thereon which when executed cause a processor to perform operations comprising: (a) calculating estimated weights for identified errors in recognition of utterances based on a reference string; (b) marking sections of the utterances as being misrecognized and associating the estimated weights with the sections of the utterances; and (c) using the weighted sections of the utterances to convert a speaker independent model to a speaker dependent model; wherein the estimated weights are computed through computing an average likelihood difference per frame and then computing a weight value by averaging the average likelihood difference over error words. | 16. An article of manufacture comprising: a computer-readable storage medium having executable instructions thereon which when executed cause a processor to perform operations comprising: (a) calculating estimated weights for identified errors in recognition of utterances based on a reference string; (b) marking sections of the utterances as being misrecognized and associating the estimated weights with the sections of the utterances; and (c) using the weighted sections of the utterances to convert a speaker independent model to a speaker dependent model; wherein the estimated weights are computed through computing an average likelihood difference per frame and then computing a weight value by averaging the average likelihood difference over error words. 20. The article of manufacture of claim 16 wherein the executable instructions causing the processor to perform calculating estimated weights comprises executable instructions thereon which when executed cause the processor to perform operations comprising: running a force alignment program on the reference string to obtain statistics of references; decoding the utterances to obtain statistics of 1-best hypothesis; and aligning the 1-best hypothesis with the reference string to obtain the error words. | 0.736697 |
2. The method of claim 1 wherein the at least one emotive feature comprises one or more facial features. | 2. The method of claim 1 wherein the at least one emotive feature comprises one or more facial features. 11. The method of claim 2 wherein the one or more facial features include at least one of an ear, a dimple, an eyebrow, a brow, a chin, and a nose. | 0.972316 |
6. The method as recited in claim 1 wherein said indication comprises a graphical representation of each said relevance score. | 6. The method as recited in claim 1 wherein said indication comprises a graphical representation of each said relevance score. 21. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of the method recited in claim 6 . | 0.974108 |
15. The method of claim 10 , further comprising: receiving, from the user via a voice input, a second word or phrase corresponding to a second control action associated with the first application; and associating the second word or phrase with the second control action. | 15. The method of claim 10 , further comprising: receiving, from the user via a voice input, a second word or phrase corresponding to a second control action associated with the first application; and associating the second word or phrase with the second control action. 16. The method of claim 15 , further comprising: performing speech recognition to identify the second word or phrase; verifying with the user whether the identified second word or phrase is correct; and associating the second word or phrase with the second control action in response to verifying that the identified second word or phrase is correct. | 0.849695 |
1. A method comprising: (a) receiving a search query; (b) determining whether the search query has been previously received; (c) responsive to a determination that the search query has not been previously received, (i) receiving a new result set associated with the search query, (ii) storing the new result set associated with the search query in an offline-accessible data store, and (iii) outputting the new result set as a search result of the search query; (d) responsive to a determination that the search query has been previously received, (i) retrieving a previously stored result set associated with the search query from the offline-accessible data store, the previously stored result set comprising a plurality of categories each of which comprises one or more articles, (ii) determining whether at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, and (iii) responsive to a determination that the at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, outputting the at least one of the plurality of categories of the previously stored result set associated with the search query as a search result of the search query. | 1. A method comprising: (a) receiving a search query; (b) determining whether the search query has been previously received; (c) responsive to a determination that the search query has not been previously received, (i) receiving a new result set associated with the search query, (ii) storing the new result set associated with the search query in an offline-accessible data store, and (iii) outputting the new result set as a search result of the search query; (d) responsive to a determination that the search query has been previously received, (i) retrieving a previously stored result set associated with the search query from the offline-accessible data store, the previously stored result set comprising a plurality of categories each of which comprises one or more articles, (ii) determining whether at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, and (iii) responsive to a determination that the at least one of the plurality of categories of the previously stored result set associated with the search query is a valid search result set for the search query, outputting the at least one of the plurality of categories of the previously stored result set associated with the search query as a search result of the search query. 7. The method of claim 1 , wherein receiving a search query comprises at least one of the following: receiving the search query from a user operating an offline client-side device, receiving the search query from a user operating an online client-side device. | 0.729099 |
22. A method of invoking a feature in a switching system having an internal numbering plan in a telecommunications network having a network numbering plan, comprising the steps of: receiving at the switching system, from a user directly served by the switching system, a first symbol sequence included in the internal numbering plan; in response to the receipt of the first symbol sequence, parsing the received first symbol sequence by using stored first information defining a syntax and a grammar of the internal numbering plan and defining the first symbol sequence as a feature access code for a corresponding feature, to determine a meaning of the first symbol sequence within the internal numbering plan; receiving at the switching system a second symbol sequence included in the network numbering plan; in response to the receipt of the second symbol sequence, parsing the received second symbol sequence by using stored second information defining a syntax and a grammar of the network numbering plan and defining the second symbol sequence as an equivalent of the first symbol sequence, to determine a meaning of the second symbol sequence within the network numbering plan; and in response to the determined meaning of either one of the received first symbol sequence and the received second symbol sequence, invoking the feature that corresponds to the first symbol sequence. | 22. A method of invoking a feature in a switching system having an internal numbering plan in a telecommunications network having a network numbering plan, comprising the steps of: receiving at the switching system, from a user directly served by the switching system, a first symbol sequence included in the internal numbering plan; in response to the receipt of the first symbol sequence, parsing the received first symbol sequence by using stored first information defining a syntax and a grammar of the internal numbering plan and defining the first symbol sequence as a feature access code for a corresponding feature, to determine a meaning of the first symbol sequence within the internal numbering plan; receiving at the switching system a second symbol sequence included in the network numbering plan; in response to the receipt of the second symbol sequence, parsing the received second symbol sequence by using stored second information defining a syntax and a grammar of the network numbering plan and defining the second symbol sequence as an equivalent of the first symbol sequence, to determine a meaning of the second symbol sequence within the network numbering plan; and in response to the determined meaning of either one of the received first symbol sequence and the received second symbol sequence, invoking the feature that corresponds to the first symbol sequence. 24. The method of claim 22 wherein: the stored second information defines the second symbol sequence as translating into the first symbol sequence; the step of parsing the second symbol sequence comprises the steps of in response to the determined meaning of the second symbol sequence, translating the second symbol sequence into the first symbol sequence, and in response to the translation, parsing the first symbol sequence resulting from the translation by using the stored first information to determine the meaning of the first symbol sequence within the internal numbering plan; and the step of invoking comprises the step of in response to the determined meaning of either one of the received first symbol sequence and the first symbol sequence resulting from the translation, invoking the feature that corresponds to the first symbol sequence by using the determined meaning and the stored first information. | 0.508764 |
1. A method comprising: receiving, by a processor, a domain description from an audio monitoring device, the domain description identifying a domain associated with a sensor input of the audio monitoring device, wherein the domain description is formatted according to a hierarchical naming structure; receiving the sensor input from the audio monitoring device, the sensor input including at least one audio sample monitored by the audio monitoring device in the domain; selecting a training data set from a plurality of training data sets based upon the received domain description and sensor input; determining a combination of a subset of classifiers for classifying the sensor input from a set of classifiers based upon the selected training data set, wherein the determining further includes determining a combination of a subset of audio feature extractors from a set of audio feature extractors and a subset of audio classifiers from a set of audio classifiers based upon the selected training data set; and sending an indication of the determined combination to the audio monitoring device, wherein the audio monitoring device is configured to monitor for audio signals within the domain using the determined combination of the subset of audio feature extractors and the subset of audio classifiers. | 1. A method comprising: receiving, by a processor, a domain description from an audio monitoring device, the domain description identifying a domain associated with a sensor input of the audio monitoring device, wherein the domain description is formatted according to a hierarchical naming structure; receiving the sensor input from the audio monitoring device, the sensor input including at least one audio sample monitored by the audio monitoring device in the domain; selecting a training data set from a plurality of training data sets based upon the received domain description and sensor input; determining a combination of a subset of classifiers for classifying the sensor input from a set of classifiers based upon the selected training data set, wherein the determining further includes determining a combination of a subset of audio feature extractors from a set of audio feature extractors and a subset of audio classifiers from a set of audio classifiers based upon the selected training data set; and sending an indication of the determined combination to the audio monitoring device, wherein the audio monitoring device is configured to monitor for audio signals within the domain using the determined combination of the subset of audio feature extractors and the subset of audio classifiers. 2. The method of claim 1 , wherein the subset of audio classifiers is selected based upon an accuracy measure of each of audio classifiers. | 0.90085 |
7. The method of claim 1 , wherein the step of assigning each word image to a word cluster based on its feature vector, comprises: calculating a distance between each one of the multiple word images and every other one of the multiple word images, based on feature vectors associated with those word images; selecting, from among the multiple word images, two of the word images that are closest in distance to each other; and assigning the two of the word images to the word cluster. | 7. The method of claim 1 , wherein the step of assigning each word image to a word cluster based on its feature vector, comprises: calculating a distance between each one of the multiple word images and every other one of the multiple word images, based on feature vectors associated with those word images; selecting, from among the multiple word images, two of the word images that are closest in distance to each other; and assigning the two of the word images to the word cluster. 8. The method of claim 7 , further comprising: selecting, from among the multiple word images other than the assigned word images, an additional one of the multiple word images that is closest to the representative word image; assigning the additional one of the word images to the word cluster; and repeating the foregoing steps until a predetermined number of the multiple word images have been assigned to the word cluster. | 0.774209 |
3. The method of claim 1 , wherein the applying the discriminative adaptation method comprises receiving environment adaptive speech data corresponding to speech collected in a predetermined environment. | 3. The method of claim 1 , wherein the applying the discriminative adaptation method comprises receiving environment adaptive speech data corresponding to speech collected in a predetermined environment. 4. The method of claim 3 , wherein a quantity of the environment adaptive speech data is less than that of the speech training data. | 0.928341 |
1. A method in a Multitenant Database System, the method comprising: generating tenant-level statistics for each of a plurality of tenants having data stored within a database system of the Multitenant Database System, wherein the database system includes one or more data tables to store the data, each data table having one or more columns defining data categories and one or more rows associated with one or more tenants among the plurality of tenants having data stored within the data tables; receiving communications from user systems over a network to request tenant-level data from the Multitenant Database System, the communications received at an interface of the Multitenant Database System; generating one or more queries designed to access the information requested; and optimizing the one or more queries based on the tenant-level statistics to increase system performance for an individual tenant among the plurality of tenants whose data is being searched. | 1. A method in a Multitenant Database System, the method comprising: generating tenant-level statistics for each of a plurality of tenants having data stored within a database system of the Multitenant Database System, wherein the database system includes one or more data tables to store the data, each data table having one or more columns defining data categories and one or more rows associated with one or more tenants among the plurality of tenants having data stored within the data tables; receiving communications from user systems over a network to request tenant-level data from the Multitenant Database System, the communications received at an interface of the Multitenant Database System; generating one or more queries designed to access the information requested; and optimizing the one or more queries based on the tenant-level statistics to increase system performance for an individual tenant among the plurality of tenants whose data is being searched. 16. The method of claim 1 , wherein optimizing the one or more queries based on the tenant-level statistics comprises: evaluating a each of a plurality of filters for expected selectiveness; and choosing a most selective filter. | 0.549687 |
14. A system for locating structured data, comprising: a communication interface configured to receive a query; a processor configured to: determine a first plurality of subunits in first structured data; for a first subunit included in the first structured data, determine a first mapping between the first subunit and a first dictionary entry; for a second subunit included in the first structured data, determine a second mapping between the second subunit and a second dictionary entry; aggregate at least the first and second dictionary entries into an aggregation, wherein the aggregation maintains a structure of the first plurality of subunits in the first structured data; search an index for at least the aggregation using a search query aggregation determined from the query, wherein the search query aggregation maintains a structure of a second plurality of subunits of second structured data included in the query; and return one or more search results based on the search, wherein the one or more search results represent structured data that is determined to satisfy the query of second structured data; and a memory configured to provide the processor with instructions. | 14. A system for locating structured data, comprising: a communication interface configured to receive a query; a processor configured to: determine a first plurality of subunits in first structured data; for a first subunit included in the first structured data, determine a first mapping between the first subunit and a first dictionary entry; for a second subunit included in the first structured data, determine a second mapping between the second subunit and a second dictionary entry; aggregate at least the first and second dictionary entries into an aggregation, wherein the aggregation maintains a structure of the first plurality of subunits in the first structured data; search an index for at least the aggregation using a search query aggregation determined from the query, wherein the search query aggregation maintains a structure of a second plurality of subunits of second structured data included in the query; and return one or more search results based on the search, wherein the one or more search results represent structured data that is determined to satisfy the query of second structured data; and a memory configured to provide the processor with instructions. 20. The system of claim 14 wherein return one or more search results includes provide as output one or more lines of source code. | 0.595395 |
1. A method for training acoustic models for automatic speech recognition comprising: building a dialect recognition system configured to identify at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the building the dialect recognition system further comprising generating a phone decoder for building an acoustic training data set; applying the dialect recognition system with at least one processor to identify portions of the acoustic training data set that conform to the at least one dialect based on distinguished phones of the at least one dialect in the training data set; and performing automatic speech recognition using at least one dialect language model trained based on the portions of the acoustic training data set that are identified as conforming to the at least one dialect. | 1. A method for training acoustic models for automatic speech recognition comprising: building a dialect recognition system configured to identify at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the building the dialect recognition system further comprising generating a phone decoder for building an acoustic training data set; applying the dialect recognition system with at least one processor to identify portions of the acoustic training data set that conform to the at least one dialect based on distinguished phones of the at least one dialect in the training data set; and performing automatic speech recognition using at least one dialect language model trained based on the portions of the acoustic training data set that are identified as conforming to the at least one dialect. 2. The method of claim 1 , wherein the applying further comprises applying the dialect recognition system to identify portions of the acoustic training data set that conform to the standard form language. | 0.552941 |
1. A computer-implemented method for identifying plausible sources of error in a risk assessment system, comprising: identifying, by a computer, a first variable and a second variable of the risk assessment system, wherein an initial distribution of the first variable is a first hypothesis and an initial distribution of the second variable is a second hypothesis; implementing, by the computer, a Bayesian network to represent implications between the first and second variables; determining, by the computer, an initial probability of the first hypothesis that the first variable has not changed given the second hypothesis that the second variable has not changed, wherein the initial probability is based on a state of knowledge at the time of determining the initial probability; receiving, by the computer, data regarding the first and second variables after determining the initial probability of the first hypothesis; identifying, by the computer, a change of value in the first or second variable; determining, by the computer, by probabilistic induction at least one cause of the change of value in the first or second variable, wherein the at least one cause is a plausible source of error; and determining, by the computer, the plausibility that the change is an error in the data by evaluating the initial probability of the first hypothesis based on the at least one cause. | 1. A computer-implemented method for identifying plausible sources of error in a risk assessment system, comprising: identifying, by a computer, a first variable and a second variable of the risk assessment system, wherein an initial distribution of the first variable is a first hypothesis and an initial distribution of the second variable is a second hypothesis; implementing, by the computer, a Bayesian network to represent implications between the first and second variables; determining, by the computer, an initial probability of the first hypothesis that the first variable has not changed given the second hypothesis that the second variable has not changed, wherein the initial probability is based on a state of knowledge at the time of determining the initial probability; receiving, by the computer, data regarding the first and second variables after determining the initial probability of the first hypothesis; identifying, by the computer, a change of value in the first or second variable; determining, by the computer, by probabilistic induction at least one cause of the change of value in the first or second variable, wherein the at least one cause is a plausible source of error; and determining, by the computer, the plausibility that the change is an error in the data by evaluating the initial probability of the first hypothesis based on the at least one cause. 5. The method of claim 1 , wherein the at least one variable of the risk assessment system comprises input data of the risk assessment system. | 0.705761 |
15. A computer-readable storage device storing computer instructions, which when executed by a processor of a computer, causes the computer to: execute a Turing test to test the one or more avatars, wherein the Turing test evaluates positional movement of each of the one or more avatars; determine the behavior characteristics of the one of the one or more avatars, wherein the behavior characteristics comprise whether each of the one or more avatars is able to demonstrate human intelligence; retrieve from an avatar its multimedia characteristics, the VU system comprising one or more avatars that each have behavior characteristics, wherein at least one of the avatars is an automated, non-human operated spam avatar created by an advertiser operating within the VU, the VU system having memory that stores behavior characteristics of known spam avatars; compare the retrieved behavior characteristics with behavior characteristics of known spam avatars; identify similarities between the retrieved behavior characteristics with behavior characteristics of known spam avatars; and identify the avatar as an automated, non-human operated spam avatar based upon the similarities between the behavior characteristics of the avatar with the behavior characteristics of the known spam avatars. | 15. A computer-readable storage device storing computer instructions, which when executed by a processor of a computer, causes the computer to: execute a Turing test to test the one or more avatars, wherein the Turing test evaluates positional movement of each of the one or more avatars; determine the behavior characteristics of the one of the one or more avatars, wherein the behavior characteristics comprise whether each of the one or more avatars is able to demonstrate human intelligence; retrieve from an avatar its multimedia characteristics, the VU system comprising one or more avatars that each have behavior characteristics, wherein at least one of the avatars is an automated, non-human operated spam avatar created by an advertiser operating within the VU, the VU system having memory that stores behavior characteristics of known spam avatars; compare the retrieved behavior characteristics with behavior characteristics of known spam avatars; identify similarities between the retrieved behavior characteristics with behavior characteristics of known spam avatars; and identify the avatar as an automated, non-human operated spam avatar based upon the similarities between the behavior characteristics of the avatar with the behavior characteristics of the known spam avatars. 18. The computer-readable storage device as defined in claim 15 wherein the Turing test further evaluates an ability of the one or more avatars to recall and demonstrate a series of commands. | 0.639529 |
10. An avatar portal service providing an online editor to one or more IP clients wherein each of said IP clients create and customize digital avatars based on detected key facial features detected from at least one uploaded photograph of one or more subscribers associated with said IP clients, said portal service comprising: an avatar web server storing data corresponding to digital avatars associated with said IP clients and preferences associated with subscribers associated with each of said IP clients and rendering an avatar portal interface to subscribers; a photofit server creating the 3D model of uploaded photographs of said subscribers; an avatar editor server rendering said user's avatars according to a plurality of customization operations; a video renderer creating pre-encoded stock footages of said avatars; an avatar repository receiving said pre-encoded stock footages and storing said uploaded photographs, avatars and pre-encoded stock footages of said subscribers; and said pre-encoded stock footages created by said video renderer being used in said avatar-calling service for lip, face and body movement synchronization operations. | 10. An avatar portal service providing an online editor to one or more IP clients wherein each of said IP clients create and customize digital avatars based on detected key facial features detected from at least one uploaded photograph of one or more subscribers associated with said IP clients, said portal service comprising: an avatar web server storing data corresponding to digital avatars associated with said IP clients and preferences associated with subscribers associated with each of said IP clients and rendering an avatar portal interface to subscribers; a photofit server creating the 3D model of uploaded photographs of said subscribers; an avatar editor server rendering said user's avatars according to a plurality of customization operations; a video renderer creating pre-encoded stock footages of said avatars; an avatar repository receiving said pre-encoded stock footages and storing said uploaded photographs, avatars and pre-encoded stock footages of said subscribers; and said pre-encoded stock footages created by said video renderer being used in said avatar-calling service for lip, face and body movement synchronization operations. 15. The portal service of claim 10 , wherein said portal service is used to create clothes and accessories for avatars via his/her IP client. | 0.667481 |
7. The method of claim 1 , wherein the derivable number of virtual concept definitions is based upon a qualitative aspect. | 7. The method of claim 1 , wherein the derivable number of virtual concept definitions is based upon a qualitative aspect. 8. The method of claim 7 , wherein the qualitative aspect is determined by the confidence gradient. | 0.942385 |
1. A method comprising: under control of one or more processors executing computer-executable instructions: receiving an indication of at least one command relating to text that contains at least one first glyph; determining that the at least one first glyph maps to multiple corresponding Unicode representations, the multiple corresponding Unicode representations defining a collision; resolving the collision such that the at least one first glyph maps to only a single Unicode representation of the multiple corresponding Unicode representations; converting the at least one first glyph to the single corresponding Unicode representation in response to the command; performing the command on the single Unicode representation of the at least one first glyph; creating at least one further glyph for the single Unicode representation of the at least one first glyph; and mapping the at least one further glyph element to the at least one first glyph via a glyph substitution table. | 1. A method comprising: under control of one or more processors executing computer-executable instructions: receiving an indication of at least one command relating to text that contains at least one first glyph; determining that the at least one first glyph maps to multiple corresponding Unicode representations, the multiple corresponding Unicode representations defining a collision; resolving the collision such that the at least one first glyph maps to only a single Unicode representation of the multiple corresponding Unicode representations; converting the at least one first glyph to the single corresponding Unicode representation in response to the command; performing the command on the single Unicode representation of the at least one first glyph; creating at least one further glyph for the single Unicode representation of the at least one first glyph; and mapping the at least one further glyph element to the at least one first glyph via a glyph substitution table. 9. The method of claim 1 , wherein receiving an indication of at least one command includes receiving an indication of at least one command related to editing text displayed to a user. | 0.719697 |
3. The system of claim 1 , wherein at least some of the scene traits are representative of a controlled environmental setting as the scene. | 3. The system of claim 1 , wherein at least some of the scene traits are representative of a controlled environmental setting as the scene. 4. The system of claim 3 , wherein the at least some of the scene traits comprise adjustable parameters within the controlled environment setting. | 0.947337 |
6. The method according to claim 1 , wherein before receiving the first context request, the method further comprising: receiving by the context aware service platform, a request for releasing a context source, wherein the request for releasing the context source carries identity information, access type information, and access control policy information of the context source; and storing by the context aware service platform, the identity information, access type information, and access control policy information of the context source. | 6. The method according to claim 1 , wherein before receiving the first context request, the method further comprising: receiving by the context aware service platform, a request for releasing a context source, wherein the request for releasing the context source carries identity information, access type information, and access control policy information of the context source; and storing by the context aware service platform, the identity information, access type information, and access control policy information of the context source. 8. The method according to claim 6 , when the context source updates its context information, comprising: the context aware service platform creates a monitor event and sends a notice to the context source; after updating the context information of the context source, the context source sends the updated context information, through a monitor port, to the context aware service platform initiatively. | 0.872549 |
44. The system of claim 19 , further including profiling the datasets in the group of related datasets to determine statistics associated with multiple fields, including at least one field of the first dataset and at least one field of the second dataset that is indicated by the constraint specification as being equivalent to the field of the first dataset. | 44. The system of claim 19 , further including profiling the datasets in the group of related datasets to determine statistics associated with multiple fields, including at least one field of the first dataset and at least one field of the second dataset that is indicated by the constraint specification as being equivalent to the field of the first dataset. 45. The system of claim 44 , wherein the one or more transformations applied to the records from the second dataset are applied based at least in part on preserving a statistical consistency between a distribution of values in the field of the first dataset and a distribution of values in the field of the second dataset according to the determined statistics and the results of applying the transformations to the records from the first dataset. | 0.872932 |
8. A apparatus comprising: a processor; and a memory to store computer program instructions, the computer program instructions when executed on the processor cause the processor to perform operations comprising: identifying, based on keywords identified by an intercept module monitoring user input and user communications, items of interest to present to a user via a webpage, each of the keywords having a date and time stamp and ranked according to occurrence in the user input and the user communications; reducing a ranking of one of the keywords identified by the intercept module based on expiration of a user defined period of time that begins on a date and a time identified by a time stamp of the one of the keywords; and generating the webpage including information related to at least one of the items of interest. | 8. A apparatus comprising: a processor; and a memory to store computer program instructions, the computer program instructions when executed on the processor cause the processor to perform operations comprising: identifying, based on keywords identified by an intercept module monitoring user input and user communications, items of interest to present to a user via a webpage, each of the keywords having a date and time stamp and ranked according to occurrence in the user input and the user communications; reducing a ranking of one of the keywords identified by the intercept module based on expiration of a user defined period of time that begins on a date and a time identified by a time stamp of the one of the keywords; and generating the webpage including information related to at least one of the items of interest. 11. The apparatus of claim 8 , wherein the keywords are generated based on the user input to a user device associated with the user. | 0.553254 |
1. A method for searching Web pages comprising: identifying query criteria entered into a search provider; determining a plurality of Web pages that satisfy the query criteria; ascertaining a page ranking for each of the plurality of Web pages, wherein each page ranking is based upon at least one relevancy factor; and presenting ordered results for the query criteria, which are ordered by the ascertained page rankings, wherein the at least one relevancy factor includes a browsing-time factor, wherein the browsing-time factor is determined based upon a behavioral event of a user at the plurality of Web pages gathered by a behavioral capture engine, an elapsed time taken by the user before the user returns to the search provider gathered by a return-to-engine timer, and a cumulative score calculated from a first set of scores and a second set of scores, wherein the first set of scores correspond to types of behavioral actions performed by the user on a browsed Web page gathered by the behavioral capture engine, and wherein the second set of scores correspond to time spent by the user at the browsed Web page and the elapsed time taken by the user to return to the search provider from the browsed Web page gathered by the return-to-engine timer, wherein the browsing-time factor disregards input from a computing device in response to a fixed number of accesses which have occurred from the computing device per a predetermined time period, wherein the browsing-time factor is adjusted responsive to an adjustment event, wherein the browsing-time factor is adjusted by detecting a negative adjustment event relating to the browsed Web page, and unfavorably adjusting the browsing-time factor responsive to the negative adjustment event, and wherein the negative adjustment event indicates the user adding the browsed Web page to a list of Web pages blocked by a firewall. | 1. A method for searching Web pages comprising: identifying query criteria entered into a search provider; determining a plurality of Web pages that satisfy the query criteria; ascertaining a page ranking for each of the plurality of Web pages, wherein each page ranking is based upon at least one relevancy factor; and presenting ordered results for the query criteria, which are ordered by the ascertained page rankings, wherein the at least one relevancy factor includes a browsing-time factor, wherein the browsing-time factor is determined based upon a behavioral event of a user at the plurality of Web pages gathered by a behavioral capture engine, an elapsed time taken by the user before the user returns to the search provider gathered by a return-to-engine timer, and a cumulative score calculated from a first set of scores and a second set of scores, wherein the first set of scores correspond to types of behavioral actions performed by the user on a browsed Web page gathered by the behavioral capture engine, and wherein the second set of scores correspond to time spent by the user at the browsed Web page and the elapsed time taken by the user to return to the search provider from the browsed Web page gathered by the return-to-engine timer, wherein the browsing-time factor disregards input from a computing device in response to a fixed number of accesses which have occurred from the computing device per a predetermined time period, wherein the browsing-time factor is adjusted responsive to an adjustment event, wherein the browsing-time factor is adjusted by detecting a negative adjustment event relating to the browsed Web page, and unfavorably adjusting the browsing-time factor responsive to the negative adjustment event, and wherein the negative adjustment event indicates the user adding the browsed Web page to a list of Web pages blocked by a firewall. 4. The method of claim 1 , wherein the time spent at the browsed Web page is determined based on previous browsing of the web page and scrolling the Web page to see a complete Web page, and wherein the time spent by the user corresponds to an average time spent by a plurality of different users at the browsed Web page responsive to a search based upon criteria similar to the query criteria. | 0.504984 |
7. A method for managing and executing interpreted language code comprising: parsing controlled language code against a language grammar to build an execution model comprising known concepts; parsing a statement to determine that the statement includes a term; determining that the term is not part of the language grammar; execute pattern matching to determine that a first pattern associated with the term in the statement matches a second pattern associated with one or more of the parsed known concepts; determining, based at least in part on the first pattern matching the second pattern, that the term represents a new concept; creating the new concept; and saving the new concept into an object model and into the language grammar so that current and future parsing errors will not occur when recognizing the new concept. | 7. A method for managing and executing interpreted language code comprising: parsing controlled language code against a language grammar to build an execution model comprising known concepts; parsing a statement to determine that the statement includes a term; determining that the term is not part of the language grammar; execute pattern matching to determine that a first pattern associated with the term in the statement matches a second pattern associated with one or more of the parsed known concepts; determining, based at least in part on the first pattern matching the second pattern, that the term represents a new concept; creating the new concept; and saving the new concept into an object model and into the language grammar so that current and future parsing errors will not occur when recognizing the new concept. 8. The method of claim 7 , wherein an error during parsing of the statement triggers execution of the pattern matching. | 0.738651 |
7. One or more computer readable media storing information to enable a computing device to process a search request specifying a search of a representation of a social network, the representation of the social network comprising nodes representing persons in the social network and comprising connections between the nodes that represent social connections between the persons, the process comprising: receiving the search request, the search request comprising a string in a query language other than a query language implemented by a database that stores the representation of the social network, the query language having structure that corresponds to a schema, the schema including a person schema modeling person nodes and properties thereof and including a connector schema modeling connector nodes and properties thereof including one or more properties that comprise instances of the person nodes modeled by the schema, the person and the connector schema defining one or more fields as computed fields that do not have a corresponding field stored in the database, the search request comprising: person information indicating properties of persons to be searched for; and connection information indicating properties of persons who directly or indirectly connect, within the social network, a person making the search request to the persons specified by the properties of the persons to be searched for, the search request thereby specifying that the search only be satisfied by nodes that both (1) satisfy the person information and (2) are connected to the person making the request by nodes that satisfy the connection information, where specified connecting nodes do not themselves satisfy the search request; and searching the representation of a social network which is stored in a database, where the searching is performed by a search engine in communication with the database, the searching comprising: receiving the query request, validating the query request against the schema, and using the schema to translate the query request into a query request in a query language implemented by the database, wherein both the indicated properties of the persons to be searched for and the specified properties of the persons who directly or indirectly or connect are mapped using the person schema defined in the schema; and receiving results satisfying the translated query from the database, and using the schema to translate the results of the searching the database to results structured to conform to the schema. | 7. One or more computer readable media storing information to enable a computing device to process a search request specifying a search of a representation of a social network, the representation of the social network comprising nodes representing persons in the social network and comprising connections between the nodes that represent social connections between the persons, the process comprising: receiving the search request, the search request comprising a string in a query language other than a query language implemented by a database that stores the representation of the social network, the query language having structure that corresponds to a schema, the schema including a person schema modeling person nodes and properties thereof and including a connector schema modeling connector nodes and properties thereof including one or more properties that comprise instances of the person nodes modeled by the schema, the person and the connector schema defining one or more fields as computed fields that do not have a corresponding field stored in the database, the search request comprising: person information indicating properties of persons to be searched for; and connection information indicating properties of persons who directly or indirectly connect, within the social network, a person making the search request to the persons specified by the properties of the persons to be searched for, the search request thereby specifying that the search only be satisfied by nodes that both (1) satisfy the person information and (2) are connected to the person making the request by nodes that satisfy the connection information, where specified connecting nodes do not themselves satisfy the search request; and searching the representation of a social network which is stored in a database, where the searching is performed by a search engine in communication with the database, the searching comprising: receiving the query request, validating the query request against the schema, and using the schema to translate the query request into a query request in a query language implemented by the database, wherein both the indicated properties of the persons to be searched for and the specified properties of the persons who directly or indirectly or connect are mapped using the person schema defined in the schema; and receiving results satisfying the translated query from the database, and using the schema to translate the results of the searching the database to results structured to conform to the schema. 10. One or more computer readable media storing a search request according to claim 7 , where the connection information specifies a strength of a relationship in the social network between a person connecting the searcher to a person matching the person information. | 0.512131 |
18. A method for telephone-based electronic communication, said method comprising: receiving an incoming telephone call from a user; allowing said user to enter login and password information using predetermined codes; verifying login and password information for said user to provide access to a menu of communication options; presenting a menu of communication options to said user including: interacting with newsgroups; interacting with an e-mail account; and browsing the internet; and allowing said user to select one of said communication options using a predetermined code, wherein said communication option of browsing the internet includes: accepting a document location from said user specified by at least one of a favorites menu and a user input; retrieving a text document including HTML tags specified by the document location; building a new text body based on the text document, wherein the new text body includes HTML document table text in accordance with a subscript tag and a superscript tag; and further comprising adding comma length pauses in accordance with at least one of: a list item tag, a hyperlink tag, a paragraph tag, a horizontal line tag, and a table element end tag in the HTML document; converting the new text body to speech; listing at least one link in the text document; accepting input from said user to designate one of said links as a selected link; and retrieving a second document specified by the selected link, wherein said communication option of interacting with an e-mail account includes: retrieving an e-mail from a mail account; listing the subject line and send name of said e-mail for said user; presenting the user with the option of sending one of several preselected replies by entering a code; and sending an e-mail reply selected by said user, wherein said communication option of interacting with newsgroups includes: retrieving a list of available newsgroups; listing the list of available newsgroups to said user; accepting a newsgroup selection from said user specified by at least one of a favorites menu and a user input; listing the articles present; accepting a user selection of an article from said user; and audibly transmitting the article to said user. | 18. A method for telephone-based electronic communication, said method comprising: receiving an incoming telephone call from a user; allowing said user to enter login and password information using predetermined codes; verifying login and password information for said user to provide access to a menu of communication options; presenting a menu of communication options to said user including: interacting with newsgroups; interacting with an e-mail account; and browsing the internet; and allowing said user to select one of said communication options using a predetermined code, wherein said communication option of browsing the internet includes: accepting a document location from said user specified by at least one of a favorites menu and a user input; retrieving a text document including HTML tags specified by the document location; building a new text body based on the text document, wherein the new text body includes HTML document table text in accordance with a subscript tag and a superscript tag; and further comprising adding comma length pauses in accordance with at least one of: a list item tag, a hyperlink tag, a paragraph tag, a horizontal line tag, and a table element end tag in the HTML document; converting the new text body to speech; listing at least one link in the text document; accepting input from said user to designate one of said links as a selected link; and retrieving a second document specified by the selected link, wherein said communication option of interacting with an e-mail account includes: retrieving an e-mail from a mail account; listing the subject line and send name of said e-mail for said user; presenting the user with the option of sending one of several preselected replies by entering a code; and sending an e-mail reply selected by said user, wherein said communication option of interacting with newsgroups includes: retrieving a list of available newsgroups; listing the list of available newsgroups to said user; accepting a newsgroup selection from said user specified by at least one of a favorites menu and a user input; listing the articles present; accepting a user selection of an article from said user; and audibly transmitting the article to said user. 22. The method of claim 18 wherein said accepting an instruction for said user to retrieve said additional document includes accepting a voice instruction. | 0.504791 |
29. A system for managing a collaborative deal closing process that provides a means for tracking and managing signature pages of a closing deal using a taxonomy displayable by a computing device, the system comprising: means for receiving a list of users that are authorized to access the closing deal, the list including an identifier associated with each of the users; means for storing the list of authorized users; means for parsing the identifier associated with each user, wherein the identifier includes one from the group consisting of an email address, a domain name, a name of a company or group, and any combination thereof of the authorized users; means for grouping the users according to parties based on the identifier; means for creating a taxonomy including a listing of documents relevant to the deal and a listing of the parties of the deal; means for receiving at least one document at the server; and means for storing relevant pages of the at least one document, wherein each page is associated with a relevant party in the taxonomy. | 29. A system for managing a collaborative deal closing process that provides a means for tracking and managing signature pages of a closing deal using a taxonomy displayable by a computing device, the system comprising: means for receiving a list of users that are authorized to access the closing deal, the list including an identifier associated with each of the users; means for storing the list of authorized users; means for parsing the identifier associated with each user, wherein the identifier includes one from the group consisting of an email address, a domain name, a name of a company or group, and any combination thereof of the authorized users; means for grouping the users according to parties based on the identifier; means for creating a taxonomy including a listing of documents relevant to the deal and a listing of the parties of the deal; means for receiving at least one document at the server; and means for storing relevant pages of the at least one document, wherein each page is associated with a relevant party in the taxonomy. 33. A system according to claim 29 , wherein the means for storing further comprises: means for parsing content of the relevant pages; means for suggesting individual files for each of the relevant pages to be stored; and means for storing the relevant pages in individual files, wherein an individual file is associated with an individual cell of the taxonomy. | 0.5 |
1. A computer program product embodied in a computer readable storage device for improving information exchange in a social network environment, the computer program product comprising the programming instructions for: receiving, by a concept service server, a copy of an e-mail, a status update or a comment from a client; detecting, by said concept service server, copying, pasting or highlighting performed on said e-mail, said status update or said comment by a user of said client; detecting, by said concept service server, entry of said e-mail, said status update or said comment in a social networking website; identifying, by said concept service server, an association between said social networking website and said e-mail, said status update or said comment; identifying, by said concept service server, one or more rule patterns based on said detected copying, pasting or highlighting, said detected entry of said e-mail, said status update or said comment in said social networking website and said identified association between said networking website and said e-mail, said status update or said comment; storing, by said concept service server, an indication of said association between said social networking website and said e-mail, said status update or said comment in terms of concept nodes in a hierarchical tree using said identified one or more rule patterns; searching, by said concept service server, for any social networking feeds of interest using said hierarchical tree as well as a current e-mail, status update or comment of said user; identifying a social networking feed of interest that matches node selection criteria for said concept nodes; and providing said user an opportunity to respond to said identified social networking feed of interest. | 1. A computer program product embodied in a computer readable storage device for improving information exchange in a social network environment, the computer program product comprising the programming instructions for: receiving, by a concept service server, a copy of an e-mail, a status update or a comment from a client; detecting, by said concept service server, copying, pasting or highlighting performed on said e-mail, said status update or said comment by a user of said client; detecting, by said concept service server, entry of said e-mail, said status update or said comment in a social networking website; identifying, by said concept service server, an association between said social networking website and said e-mail, said status update or said comment; identifying, by said concept service server, one or more rule patterns based on said detected copying, pasting or highlighting, said detected entry of said e-mail, said status update or said comment in said social networking website and said identified association between said networking website and said e-mail, said status update or said comment; storing, by said concept service server, an indication of said association between said social networking website and said e-mail, said status update or said comment in terms of concept nodes in a hierarchical tree using said identified one or more rule patterns; searching, by said concept service server, for any social networking feeds of interest using said hierarchical tree as well as a current e-mail, status update or comment of said user; identifying a social networking feed of interest that matches node selection criteria for said concept nodes; and providing said user an opportunity to respond to said identified social networking feed of interest. 3. The computer program product as recited in claim 1 further comprising the programming instructions for: providing said user a link to said identified social networking feed of interest that also matches one or more keywords in said current e-mail, status update or comment of said user. | 0.5 |
7. A synthetic speech system comprising: means for storing speech to be synthesized in a computer memory; means for a processor to read said speech from said computer memory and for said processor to detect natural timing boundaries in words to be spoken by said synthetic speech system, to produce natural timing intervals; means for identifying phonemes in said natural timing intervals; means for assigning first time durations for each of said phonemes; means for changing a selected first time duration of a selected phoneme to achieve a desired time duration for a selected natural timing interval containing said selected phoneme; means for setting a plurality of said natural timing intervals to substantially the same second time duration, a particular phoneme having a computed time duration in response to number of phonemes within said selected natural timing interval and said second time duration; and means for applying said synthesized speech to an electromechanical acoustic coupler to make audible speech; wherein respective time durations of at least certain respective phonemes are based upon respective selectable parameters indicative of respective degrees to which said respective time durations may be adjusted without undesirably degrading speech produced by said system. | 7. A synthetic speech system comprising: means for storing speech to be synthesized in a computer memory; means for a processor to read said speech from said computer memory and for said processor to detect natural timing boundaries in words to be spoken by said synthetic speech system, to produce natural timing intervals; means for identifying phonemes in said natural timing intervals; means for assigning first time durations for each of said phonemes; means for changing a selected first time duration of a selected phoneme to achieve a desired time duration for a selected natural timing interval containing said selected phoneme; means for setting a plurality of said natural timing intervals to substantially the same second time duration, a particular phoneme having a computed time duration in response to number of phonemes within said selected natural timing interval and said second time duration; and means for applying said synthesized speech to an electromechanical acoustic coupler to make audible speech; wherein respective time durations of at least certain respective phonemes are based upon respective selectable parameters indicative of respective degrees to which said respective time durations may be adjusted without undesirably degrading speech produced by said system. 9. The system as in claim 7 wherein each said natural timing interval is a respective interval between two respective stressed phonemes. | 0.541257 |
20. The computing device of claim 14 , wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: receiving additional verbal input; filtering one or more non-responsive portions of the additional verbal input; and determining that no part of the filtered additional verbal input includes the missing information. | 20. The computing device of claim 14 , wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: receiving additional verbal input; filtering one or more non-responsive portions of the additional verbal input; and determining that no part of the filtered additional verbal input includes the missing information. 21. The computing device of claim 20 , wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: determining a second clarification question, wherein the second clarification question is different from the clarification question for the one or more words; and outputting the second clarification question. | 0.877527 |
14. A system for ranking auctions, comprising: at least one processor; memory storing instructions that, when executed cause the processor to: store relevance information for each of a plurality of auctions with respect to a plurality of search terms: receive selection information for a selected auction of the plurality of auctions when a first user performs a selection action with respect to the selected auction and at least one first search term; update the relevance information for the selected auction based at least in part upon the received selection information; receive a query from a second user; identifies auctions that satisfy the received query using a mapping of auctions to query terms, the mapping including the relevance information for each of the identified auctions with respect to the at least one search term; generate a ranking for at least some of the identified auctions using the relevance information for each second term in the query mapped to at least one of the identified actions; and provide ordered search results corresponding to the ranked auctions for display to the user. | 14. A system for ranking auctions, comprising: at least one processor; memory storing instructions that, when executed cause the processor to: store relevance information for each of a plurality of auctions with respect to a plurality of search terms: receive selection information for a selected auction of the plurality of auctions when a first user performs a selection action with respect to the selected auction and at least one first search term; update the relevance information for the selected auction based at least in part upon the received selection information; receive a query from a second user; identifies auctions that satisfy the received query using a mapping of auctions to query terms, the mapping including the relevance information for each of the identified auctions with respect to the at least one search term; generate a ranking for at least some of the identified auctions using the relevance information for each second term in the query mapped to at least one of the identified actions; and provide ordered search results corresponding to the ranked auctions for display to the user. 16. The system of claim 14 , wherein the selection action corresponds to a bid placed by another user at an auction that was identified as satisfying a query including at least one common search term. | 0.782468 |
1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. | 1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. 25. The computer-implemented method of claim 1 , wherein the inferred attribute is an age of the selected user and the set of users is determined by performing cluster analysis of users connected to the selected user based on their age values. | 0.56822 |
1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receiving from the first user a text query comprising one or more character strings; identifying one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identifying one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generating one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges. | 1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receiving from the first user a text query comprising one or more character strings; identifying one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identifying one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generating one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges. 4. The method of claim 1 , wherein identifying one or more of the second-user nodes comprises, for each character string: determining for each of the second-user nodes whether the second-user node matches the character string; and identifying each second-user node that matches the character string. | 0.544825 |
15. The method of claim 7 , wherein the lexicon is a phonetic lexicon. | 15. The method of claim 7 , wherein the lexicon is a phonetic lexicon. 16. The method of claim 15 , further comprising: using the phonetic lexicon to perform recognition on the spoken utterance to generate a recognized transcript of the spoken utterance, said recognized transcript being characterized by a corresponding pronunciation; and generating an N-best list of alternatives to the recognized transcript, each alternative of that N-best list of alternatives having a corresponding pronunciation, wherein the initial pronunciation is selected from the N-best list of alternatives. | 0.779487 |
6. A non-transitory computer readable storage medium comprising a program product which, when executed, is configured to perform an operation for retrieving query results, comprising: receiving a first abstract query comprising at least two logical fields defined by a first data abstraction model comprising a plurality of first logical field definitions mapped to physical fields of a first database in a first device, wherein one or more of the first logical fields definitions associate respective first logical fields to respective concepts of a predefined set of concepts, the concepts being standardized metadata; for each of the at least two logical fields of the first abstract query, determining whether a second data abstraction model comprises a logical field associated with a concept associated with the respective logical field of the abstract query, wherein the second data abstraction model comprises a plurality of second logical field definitions mapping the second logical fields to physical fields of a second database in a second device, wherein one or more of the second logical fields definitions associate respective second logical fields to respective concepts of the predefined set of concepts; and upon determining that the second data abstraction model does not comprise the logical field associated with the concept associated with the respective logical field of the abstract query, modifying the first abstract query to remove the respective logical field from the first abstract query such that the modified first abstract query includes only the at least two logical fields less the removed logical field. | 6. A non-transitory computer readable storage medium comprising a program product which, when executed, is configured to perform an operation for retrieving query results, comprising: receiving a first abstract query comprising at least two logical fields defined by a first data abstraction model comprising a plurality of first logical field definitions mapped to physical fields of a first database in a first device, wherein one or more of the first logical fields definitions associate respective first logical fields to respective concepts of a predefined set of concepts, the concepts being standardized metadata; for each of the at least two logical fields of the first abstract query, determining whether a second data abstraction model comprises a logical field associated with a concept associated with the respective logical field of the abstract query, wherein the second data abstraction model comprises a plurality of second logical field definitions mapping the second logical fields to physical fields of a second database in a second device, wherein one or more of the second logical fields definitions associate respective second logical fields to respective concepts of the predefined set of concepts; and upon determining that the second data abstraction model does not comprise the logical field associated with the concept associated with the respective logical field of the abstract query, modifying the first abstract query to remove the respective logical field from the first abstract query such that the modified first abstract query includes only the at least two logical fields less the removed logical field. 7. The non-transitory computer readable storage medium of claim 6 , wherein the operation further comprises generating a second abstract query based on the first abstract query, wherein the second abstract query comprises one or more of the second logical field definitions of the second data abstraction model. | 0.5 |
1. A digital image search and retrieval system, comprising: a query parser for parsing a query submitted by a user through a client computer, said query including at least one metadata criterion relating to a first type of recorded metadata and said query is void of any reference to a second type of recorded metadata different than the first type of recorded metadata; said query parser having access to a metadata database for searching the metadata database for one or more digital images satisfying said metadata criterion; and a response composer communicatively coupled to the query parser for receiving from the parser a notification of metadata results responsive to the query; said response composer having access to the metadata database and a digital image database storing images identified by metadata stored in the metadata database wherein the response composer composes a response including one or more digital images from said digital image database corresponding to the metadata results from the query, the metadata for these images which corresponds to the first type of recorded metadata, and other metadata for these images which corresponds to the second type of recorded metadata, from said metadata database; and said response composer being communicatively coupled to said client computer for sending the response to the client computer for display to said user. | 1. A digital image search and retrieval system, comprising: a query parser for parsing a query submitted by a user through a client computer, said query including at least one metadata criterion relating to a first type of recorded metadata and said query is void of any reference to a second type of recorded metadata different than the first type of recorded metadata; said query parser having access to a metadata database for searching the metadata database for one or more digital images satisfying said metadata criterion; and a response composer communicatively coupled to the query parser for receiving from the parser a notification of metadata results responsive to the query; said response composer having access to the metadata database and a digital image database storing images identified by metadata stored in the metadata database wherein the response composer composes a response including one or more digital images from said digital image database corresponding to the metadata results from the query, the metadata for these images which corresponds to the first type of recorded metadata, and other metadata for these images which corresponds to the second type of recorded metadata, from said metadata database; and said response composer being communicatively coupled to said client computer for sending the response to the client computer for display to said user. 15. The system of claim 1 , wherein the other metadata for these images comprises at least one user-specified metadata. | 0.533875 |
1. A process for generating a taxonomy for a plurality of information resources in a communications network, including: (i) collecting said plurality of information resources from said communications network; (ii) generating clusters of said plurality of collected information resources on the basis of a similarity threshold value for clustering and similarity values for said plurality of collected information resources; (iii) iteratively generating sub-clusters of said generated clusters based on the similarity threshold value for clustering and similarity values for information resources within each of said generated clusters and within each of said generated sub-clusters, wherein the generated clusters and sub-clusters provide a hierarchy of resource clusters, wherein the number of resource clusters at each level of said hierarchy is determined by content of said plurality of collected information resources; (iv) collecting further information resources from said communications network; (v) assigning the further collected information resources to a plurality of the resource clusters; (vi) maintaining the coherence of the plurality of resource clusters as further collected information resources are assigned by at least one of: (a) reducing the similarity threshold value for clustering with an increasing number of the further collected information resources; and (b) selecting a random subset of resources from the collected information resources; generating a new similarity threshold value for clustering based on the selected random subset of resources; and re-clustering the collected information resources using the generated new similarity threshold value for clustering; and (vii) repeating the steps of collecting further information resources, reducing similarity and maintaining the coherence. | 1. A process for generating a taxonomy for a plurality of information resources in a communications network, including: (i) collecting said plurality of information resources from said communications network; (ii) generating clusters of said plurality of collected information resources on the basis of a similarity threshold value for clustering and similarity values for said plurality of collected information resources; (iii) iteratively generating sub-clusters of said generated clusters based on the similarity threshold value for clustering and similarity values for information resources within each of said generated clusters and within each of said generated sub-clusters, wherein the generated clusters and sub-clusters provide a hierarchy of resource clusters, wherein the number of resource clusters at each level of said hierarchy is determined by content of said plurality of collected information resources; (iv) collecting further information resources from said communications network; (v) assigning the further collected information resources to a plurality of the resource clusters; (vi) maintaining the coherence of the plurality of resource clusters as further collected information resources are assigned by at least one of: (a) reducing the similarity threshold value for clustering with an increasing number of the further collected information resources; and (b) selecting a random subset of resources from the collected information resources; generating a new similarity threshold value for clustering based on the selected random subset of resources; and re-clustering the collected information resources using the generated new similarity threshold value for clustering; and (vii) repeating the steps of collecting further information resources, reducing similarity and maintaining the coherence. 16. The process as claimed in claim 1 , wherein the plurality of information resources collected at step (i) are a selected subset of a larger set of resources including the further information resources collected at step (iv). | 0.541089 |
11. A system for providing an Internet fax service, comprising: a fax sever to receive messages through fax transmissions on a plurality of direct inward dialing (DID) lines assigned to a plurality of users of the service, respectively, and store raw fax documents derived from the received fax transmissions, respectively, wherein the fax server is to retrieve the users' account information to determine each of the users' subscriber status or subscriber classification including whether or not the user is subscribed to the Internet service; a web server to make the received messages available to the users, respectively, over an Internet and in accordance with the users' account information; and a fax content processing unit to, on a per user basis according to the user's subscriber status or classification, (i) process the raw fax documents using digital character recognition to extract text therefrom, (ii) scan the extracted text to find one or more specified keywords therein, wherein the found keywords arc a subset of the extracted text, (iii) store the found keywords in association with their raw fax documents in a database, wherein the fax content processing unit is to further receive a plurality of requests for message searches, from two or more of said plurality of users, respectively, in accordance with each user's account information, and process each one of the plurality of requests by searching amongst the found keywords that are stored in the database to find ones that satisfy search criteria designated by each one of the plurality of requests, wherein the web server is to further make results of the searching available over the Internet to said two or more of the plurality of users, respectively, in accordance with each user's account information. | 11. A system for providing an Internet fax service, comprising: a fax sever to receive messages through fax transmissions on a plurality of direct inward dialing (DID) lines assigned to a plurality of users of the service, respectively, and store raw fax documents derived from the received fax transmissions, respectively, wherein the fax server is to retrieve the users' account information to determine each of the users' subscriber status or subscriber classification including whether or not the user is subscribed to the Internet service; a web server to make the received messages available to the users, respectively, over an Internet and in accordance with the users' account information; and a fax content processing unit to, on a per user basis according to the user's subscriber status or classification, (i) process the raw fax documents using digital character recognition to extract text therefrom, (ii) scan the extracted text to find one or more specified keywords therein, wherein the found keywords arc a subset of the extracted text, (iii) store the found keywords in association with their raw fax documents in a database, wherein the fax content processing unit is to further receive a plurality of requests for message searches, from two or more of said plurality of users, respectively, in accordance with each user's account information, and process each one of the plurality of requests by searching amongst the found keywords that are stored in the database to find ones that satisfy search criteria designated by each one of the plurality of requests, wherein the web server is to further make results of the searching available over the Internet to said two or more of the plurality of users, respectively, in accordance with each user's account information. 17. The system of claim 11 , wherein the fax content processing unit is to further: look up a keyword that is either designated by an owner of one of the received messages or is a found keyword, to find a related keyword, and tag said one of the received messages with both the keyword and the related keyword. | 0.603143 |
14. The data storage and query method, as recited in claim 8 , wherein the Key server has three kernel data structures of: (1) a B+ tree, for storing corresponding relations between the Keys and address codes; (2) an address translating table, for storing corresponding relations between the address codes and IP addresses, and between the address codes and the port numbers; and (3) a MiniTable server monitoring table, for storing for storing loading conditions of the MiniTable servers corresponding to each address code; wherein when the Key server receives a primitive request, the Key server checks whether the primitive request is a valid Query primitive; if yes, the Key server queries an address code corresponding to a Key in the B+ tree; if no existing Key, the Key server returns information of no existing Key; if the Key exists, the Key server queries an IP address and a port number corresponding to the address code in the address translating table; if no existing IP address and no existing port number, the Key server returns to error; if the IP address and the port number exist, the Key server transfers the request to the MiniTable server corresponding to the IP address and the port number; if the request is not a valid Query primitive, the Key server checks whether the request is a valid Create primitive; if yes, the Key server queries whether a designated Key exists in the B+ tree; if the designated Key exists, the Key server returns information that the designated Key has existed; if no existing designated Key, the Key server allocates an address code according to a dispatch algorithm and the MiniTable server monitoring table, updates the MiniTable server monitoring table, queries an IP address and a port number corresponding to the address code and transfers the request to the corresponding MiniTable server; if the request is not a valid Create primitive, the Key server checks whether the request is a valid Delete primitive; if yes, the Key server queries whether a designated Key exists in the B+ tree; If no existing designated Key, the Key server returns information of no existing designated Key; if the designated Key exists, the Key server queries an IP address and a port number corresponding to an address code in the address translating table, deletes the corresponding Key in the B+ tree, updates the MiniTable server monitoring table, queries the IP address and the port number and transfers the request to the corresponding MiniTable server. | 14. The data storage and query method, as recited in claim 8 , wherein the Key server has three kernel data structures of: (1) a B+ tree, for storing corresponding relations between the Keys and address codes; (2) an address translating table, for storing corresponding relations between the address codes and IP addresses, and between the address codes and the port numbers; and (3) a MiniTable server monitoring table, for storing for storing loading conditions of the MiniTable servers corresponding to each address code; wherein when the Key server receives a primitive request, the Key server checks whether the primitive request is a valid Query primitive; if yes, the Key server queries an address code corresponding to a Key in the B+ tree; if no existing Key, the Key server returns information of no existing Key; if the Key exists, the Key server queries an IP address and a port number corresponding to the address code in the address translating table; if no existing IP address and no existing port number, the Key server returns to error; if the IP address and the port number exist, the Key server transfers the request to the MiniTable server corresponding to the IP address and the port number; if the request is not a valid Query primitive, the Key server checks whether the request is a valid Create primitive; if yes, the Key server queries whether a designated Key exists in the B+ tree; if the designated Key exists, the Key server returns information that the designated Key has existed; if no existing designated Key, the Key server allocates an address code according to a dispatch algorithm and the MiniTable server monitoring table, updates the MiniTable server monitoring table, queries an IP address and a port number corresponding to the address code and transfers the request to the corresponding MiniTable server; if the request is not a valid Create primitive, the Key server checks whether the request is a valid Delete primitive; if yes, the Key server queries whether a designated Key exists in the B+ tree; If no existing designated Key, the Key server returns information of no existing designated Key; if the designated Key exists, the Key server queries an IP address and a port number corresponding to an address code in the address translating table, deletes the corresponding Key in the B+ tree, updates the MiniTable server monitoring table, queries the IP address and the port number and transfers the request to the corresponding MiniTable server. 20. The data storage and query method, as recited in claim 14 , wherein each MiniTable server has two kernel data structures of: (1) a memory table, for storing a partial MiniTable in memory according to a cache policy; and (2) a MiniTable lock, for recording locked MiniTable; wherein when the MiniTable server receives the request transferred by the Key server, the MiniTable server semantically parses the request and judges whether the MiniTable which requests an operation is locked or not; if yes, the MiniTable server adds the request into a waiting queue; if no, the MiniTable server locks up the MiniTable and generates an executive plan; thereafter, the MiniTable server judges whether the MiniTable is located in the memory table; if yes, the MiniTable server directly executes the request; if no, the MiniTable server further judges whether there is enough memory space or not; if no, the MiniTable server writes a partial MiniTable into a distributed file system according to the dispatch policy, comprising comparing a memory version of the MiniTable with a file version of the MiniTable and then only writing updated parts in in a log compressed format; after obtaining enough memory space, the MiniTable server reads the MiniTable file from the distributed file system and decompresses; the MiniTable server transforms the log files of the MiniTable into a format of data and stores the log files in the format of data into the memory table; then the MiniTable server executes the request, unlocks the MiniTable and returns a result. | 0.5 |
47. A method as claimed in claim 46 , wherein the content document comprises content code defining information to be displayed and predefined tags for controlling the presentation of the information to be displayed; wherein the interpreting means interprets each tag with reference to the selected device dependent information. | 47. A method as claimed in claim 46 , wherein the content document comprises content code defining information to be displayed and predefined tags for controlling the presentation of the information to be displayed; wherein the interpreting means interprets each tag with reference to the selected device dependent information. 48. A method as claimed in claim 47 , wherein the device dependent information is stored as a set of tables and wherein the device dependent information is assimilated in a set of objects accessible to the tags in a run time environment of the code generating engine. | 0.927313 |
1. A method of representing commands of a user interface of an application comprising: receiving one or more command descriptions for one or more commands, each of said one or more command descriptions having one or more properties and representing an instance of one of the commands; receiving one or more command group descriptions for one or more command groups, each of said one or more command group descriptions having one or more properties, representing an instance of one of said command groups at a level in a group hierarchy, and specifying one or more group members, each of said one or more group members representing a derived instance of one of said commands or a derived instance of one of said command groups, properties of each derived instance of a command and each derived instance of a command group inheriting properties from one or more ancestor instances; storing a first derived instance of a first command of the one or more commands or of a first command group of the one or more command groups in metadata attributes in a command registry; deriving a second derived instance of a second command of the one or more commands or of a second command group of the one or more command groups using one or more processing units; not storing the second derived instance in the metadata attributes in the command registry; and maintaining the second derived instance in a component that requests creation of the second derived instance. | 1. A method of representing commands of a user interface of an application comprising: receiving one or more command descriptions for one or more commands, each of said one or more command descriptions having one or more properties and representing an instance of one of the commands; receiving one or more command group descriptions for one or more command groups, each of said one or more command group descriptions having one or more properties, representing an instance of one of said command groups at a level in a group hierarchy, and specifying one or more group members, each of said one or more group members representing a derived instance of one of said commands or a derived instance of one of said command groups, properties of each derived instance of a command and each derived instance of a command group inheriting properties from one or more ancestor instances; storing a first derived instance of a first command of the one or more commands or of a first command group of the one or more command groups in metadata attributes in a command registry; deriving a second derived instance of a second command of the one or more commands or of a second command group of the one or more command groups using one or more processing units; not storing the second derived instance in the metadata attributes in the command registry; and maintaining the second derived instance in a component that requests creation of the second derived instance. 3. The method of claim 1 , wherein a command group instance includes a third derived instance of a command having a first property with a first value and an ancestor of said third instance is a fourth instance of said command having a second property with a second value, said third instance inheriting said second property with said second value from said fourth instance. | 0.5 |
17. A computer readable storage medium storing one or more programs configured to be executed by a computer system, the one or more programs having instructions to: execute a widget application in response to one or more commands from a user; under control of the widget application, receive from a server a content feed of logged search engine queries, wherein the logged search engine queries are historical queries submitted by the user to a search engine associated with the server; and display, using the widget application, at least a portion of the received content feed. | 17. A computer readable storage medium storing one or more programs configured to be executed by a computer system, the one or more programs having instructions to: execute a widget application in response to one or more commands from a user; under control of the widget application, receive from a server a content feed of logged search engine queries, wherein the logged search engine queries are historical queries submitted by the user to a search engine associated with the server; and display, using the widget application, at least a portion of the received content feed. 18. The computer readable storage medium of claim 17 , wherein the received content feed includes information representing links, included in responses to the search engine queries, that were selected by the user. | 0.615994 |
12. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising: receiving a single database query language statement, the single database query language statement comprising both a lexical portion having one or more lexical terms and a sentiment clause portion, the sentiment clause portion comprising: a sentiment-aware operator corresponding to a particular sentiment sought after, wherein the sentiment-aware operator comprises a first parameter and a second parameter that are both contained within the sentiment-aware operator, the first parameter corresponding to one or more sentiment terms such that a sentiment analysis is performed for the one or more sentiment terms and the second parameter corresponding to a sentiment assessment indication term corresponding to the particular sentiment to be searched for relative to the one or more sentiment terms, wherein at least one of the one or more sentiment terms in the sentiment clause portion differs from the one or more lexical terms in the lexical portion; parsing, by a computer processor, the single database query language statement to identify the one or more lexical terms to be used in a retrieval of documents containing the one or more of the lexical terms; parsing the single database query language statement based at least on the sentiment-aware operator to identify the one or more sentiment terms for performing sentiment analysis and to identify the sentiment assessment indication term that pertains to the particular sentiment relative to the one or more sentiment terms; retrieving the documents that contain at least one of the one or more lexical terms; and after retrieving the documents that contain at least one of the one or more lexical terms, performing the sentiment analysis on the one or more sentiment terms found within the documents to identify the documents that pertain to the particular sentiment based at least in part on the sentiment assessment indication term. | 12. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising: receiving a single database query language statement, the single database query language statement comprising both a lexical portion having one or more lexical terms and a sentiment clause portion, the sentiment clause portion comprising: a sentiment-aware operator corresponding to a particular sentiment sought after, wherein the sentiment-aware operator comprises a first parameter and a second parameter that are both contained within the sentiment-aware operator, the first parameter corresponding to one or more sentiment terms such that a sentiment analysis is performed for the one or more sentiment terms and the second parameter corresponding to a sentiment assessment indication term corresponding to the particular sentiment to be searched for relative to the one or more sentiment terms, wherein at least one of the one or more sentiment terms in the sentiment clause portion differs from the one or more lexical terms in the lexical portion; parsing, by a computer processor, the single database query language statement to identify the one or more lexical terms to be used in a retrieval of documents containing the one or more of the lexical terms; parsing the single database query language statement based at least on the sentiment-aware operator to identify the one or more sentiment terms for performing sentiment analysis and to identify the sentiment assessment indication term that pertains to the particular sentiment relative to the one or more sentiment terms; retrieving the documents that contain at least one of the one or more lexical terms; and after retrieving the documents that contain at least one of the one or more lexical terms, performing the sentiment analysis on the one or more sentiment terms found within the documents to identify the documents that pertain to the particular sentiment based at least in part on the sentiment assessment indication term. 19. The computer program product of claim 12 , wherein parsing the query comprises parsing group operator. | 0.544339 |
18. In a computing environment, a method for generating a declarative model editor configured to provide model creation and editing functionality for a user, the method comprising: an act of receiving a first user input indicating a selection of a native underlying schema, selected from a plurality of native underlying schemas, that is to be used in the generation of a declarative model editor corresponding to the selected native schema, the native schema comprising one or more constraints that are to be followed by models based on the native schema; an act of receiving a second user input indicating a declarative entry that includes one or more user-configurable model editor characteristics configurable by a user for application to one or more of the models based on the selected native schema, the models being instances of the native schema, the model editor characteristics including one or more characteristics that are not specified by the native underlying schema and that customize the model editor for editing a selected model; an act of automatically generating a declarative model editor based on the selected native schema and one or more user-configurable model editor characteristics. | 18. In a computing environment, a method for generating a declarative model editor configured to provide model creation and editing functionality for a user, the method comprising: an act of receiving a first user input indicating a selection of a native underlying schema, selected from a plurality of native underlying schemas, that is to be used in the generation of a declarative model editor corresponding to the selected native schema, the native schema comprising one or more constraints that are to be followed by models based on the native schema; an act of receiving a second user input indicating a declarative entry that includes one or more user-configurable model editor characteristics configurable by a user for application to one or more of the models based on the selected native schema, the models being instances of the native schema, the model editor characteristics including one or more characteristics that are not specified by the native underlying schema and that customize the model editor for editing a selected model; an act of automatically generating a declarative model editor based on the selected native schema and one or more user-configurable model editor characteristics. 19. The method of claim 18 , further comprising an act of accessing the selected native schema based on the received first user input. | 0.595977 |
1. A computer implemented process for customizing a display of a tag cloud, the computer implemented process comprising: displaying an interactive legend in conjunction with the display of the tag cloud, the interactive legend comprising a plurality of tag attributes, each tag attribute associated with a drop down menu comprising a plurality of display characteristics; responsive to a selection of a display characteristic from the drop down menu, mapping the display characteristic to a tag in the tag cloud, each display characteristic representing one of the plurality of tag attributes; modifying the tag cloud, wherein each tag is displayed in accordance with a display characteristic mapped to the tag by the interactive legend; and wherein the tag attributes are rearranged, added, or removed from the interactive legend. | 1. A computer implemented process for customizing a display of a tag cloud, the computer implemented process comprising: displaying an interactive legend in conjunction with the display of the tag cloud, the interactive legend comprising a plurality of tag attributes, each tag attribute associated with a drop down menu comprising a plurality of display characteristics; responsive to a selection of a display characteristic from the drop down menu, mapping the display characteristic to a tag in the tag cloud, each display characteristic representing one of the plurality of tag attributes; modifying the tag cloud, wherein each tag is displayed in accordance with a display characteristic mapped to the tag by the interactive legend; and wherein the tag attributes are rearranged, added, or removed from the interactive legend. 3. The computer implemented process of claim 1 wherein the plurality of tag attributes comprise: popularity of an item, last update of an item, frequency of updates to an item, age of an item, size of an item, most recently accessed, and whether there have been comments or replies related to an item. | 0.621778 |
11. A system for enforcing application-layer policies to documents, each policy defining a rule and an action, comprising: a XML parser for parsing a XML document received as streaming XML data in a hierarchical structure to enable evaluation of an object in the XML document; a simple policies data structure for storing XPath queries that do not use wildcard “*” and descendent “//” expressions; a complex policies data structure for storing XPath queries that use wildcard “*” and descendent “//” expressions; means for simultaneously querying the simple and complex policies data structures to identify all policies corresponding to the object; and means for executing the actions defined by the policies corresponding to the object identified in the data structures. | 11. A system for enforcing application-layer policies to documents, each policy defining a rule and an action, comprising: a XML parser for parsing a XML document received as streaming XML data in a hierarchical structure to enable evaluation of an object in the XML document; a simple policies data structure for storing XPath queries that do not use wildcard “*” and descendent “//” expressions; a complex policies data structure for storing XPath queries that use wildcard “*” and descendent “//” expressions; means for simultaneously querying the simple and complex policies data structures to identify all policies corresponding to the object; and means for executing the actions defined by the policies corresponding to the object identified in the data structures. 16. The system of claim 11 , wherein the simple policies data structure is a simple policies database. | 0.815975 |
1. A method of developing multiple natural language versions of software, the method comprising: providing a first iteration of a computer program, wherein the computer program comprises natural language portions of source text in a first natural language; providing an interface for a translator to provide a translation of at least some of the natural language portions of the source text into a second natural language, wherein the providing of the interface for the translator is configured to allow the translator to translate the natural language portions of the source text in parallel with the development of the source text of the computer program; displaying, for the translator, within a first graphical display window of the interface, a first version of the natural language potions of the source text of the computer program in the first natural language, the first graphical display window displaying the source text in the first natural language as it will appear in the first version of the computer program; displaying, for the translator, within a second graphical display window of the interface, a second version of the natural language portions of the computer program in the second natural language, the second graphical display window comprising the translation of the source text in the second natural language as it will appear in the second version of the computer program; receiving modifications to the natural language portions of the source text; based on the received modifications to the natural language portions of the source text, updating an update status table, wherein the update status table includes a record of the modifications made to the natural language portions of the source text; displaying, for the translator, within a third graphical display window of the interface the updated status table to indicate the modifications made to the natural language portions of the source text, wherein the first, second, and third graphical display windows are simultaneously displayed in the interface; and receiving translation of the modified portions of the natural language portions of the source text from the first natural language to the second natural language. | 1. A method of developing multiple natural language versions of software, the method comprising: providing a first iteration of a computer program, wherein the computer program comprises natural language portions of source text in a first natural language; providing an interface for a translator to provide a translation of at least some of the natural language portions of the source text into a second natural language, wherein the providing of the interface for the translator is configured to allow the translator to translate the natural language portions of the source text in parallel with the development of the source text of the computer program; displaying, for the translator, within a first graphical display window of the interface, a first version of the natural language potions of the source text of the computer program in the first natural language, the first graphical display window displaying the source text in the first natural language as it will appear in the first version of the computer program; displaying, for the translator, within a second graphical display window of the interface, a second version of the natural language portions of the computer program in the second natural language, the second graphical display window comprising the translation of the source text in the second natural language as it will appear in the second version of the computer program; receiving modifications to the natural language portions of the source text; based on the received modifications to the natural language portions of the source text, updating an update status table, wherein the update status table includes a record of the modifications made to the natural language portions of the source text; displaying, for the translator, within a third graphical display window of the interface the updated status table to indicate the modifications made to the natural language portions of the source text, wherein the first, second, and third graphical display windows are simultaneously displayed in the interface; and receiving translation of the modified portions of the natural language portions of the source text from the first natural language to the second natural language. 5. The method of claim 1 , further comprising: monitoring development of the computer program, wherein the interface is provided for the translator in response to detection of a revision of the computer program. | 0.588542 |
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