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5. The method of claim 1 , where determining the plurality of word hypotheses for the voice query further includes: identifying a language associated with the voice query; and determining the plurality of word hypotheses based on the identified language.
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5. The method of claim 1 , where determining the plurality of word hypotheses for the voice query further includes: identifying a language associated with the voice query; and determining the plurality of word hypotheses based on the identified language. 6. The method of claim 5 , where determining the respective weights includes: determining the respective weights based on a language model associated with the language.
| 0.904727 |
1. A system for automatically extracting contract data from electronic contracts, comprising: an administrator module configured to provide templates for inputting document patterns and a list of contract data tags for each of a plurality of contract document types, said document patterns being based on at least one predetermined region of a document, one of said regions including the first line of the document; a processor having a parser configured to convert an electronic contract document into a contract text document and reformat the contract text document to provide a pattern for the contract text document; a pattern recognition engine configured to determine a list of contract document types in the electronic contract by comparing and matching patterns of all known contract document types with the pattern of the contract text document; and a contract data extraction engine configured to extract contract data for each contract document type on the list.
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1. A system for automatically extracting contract data from electronic contracts, comprising: an administrator module configured to provide templates for inputting document patterns and a list of contract data tags for each of a plurality of contract document types, said document patterns being based on at least one predetermined region of a document, one of said regions including the first line of the document; a processor having a parser configured to convert an electronic contract document into a contract text document and reformat the contract text document to provide a pattern for the contract text document; a pattern recognition engine configured to determine a list of contract document types in the electronic contract by comparing and matching patterns of all known contract document types with the pattern of the contract text document; and a contract data extraction engine configured to extract contract data for each contract document type on the list. 2. The system as recited in claim 1 , wherein the administrator module is configured to construct pattern matrices to provide the templates for inputting document patterns.
| 0.526718 |
1. A method for performing natural language processing, comprising: receiving a primary text file; scanning the received primary text file to determine a set of statistics related to a frequency at which various words of the primary text file follow other words of the primary text file; creating a probabilistic word generator, based on the determined set of statistics, that generates synthetic text exhibiting the determined set of statistics; generating synthetic text directly into a main memory of a computer system, the generated synthetic text including a plurality of sentences, each of which including a predetermined number of probabilistically selected words exhibiting the determined set of statistics, related to a frequency at which various words of the primary text file follow other words of the primary text file, using the created probabilistic word generator; performing word vectorization on the synthetic text, within the main memory of the computer system; using results of the performed vectorization to perform machine learning tasks; and using the machine learning tasks to perform natural language processing to interpret a subsequent text, wherein, in generating the synthetic text that is used to perform machine learning directly into the main memory, no text data is loaded into the main memory from a memory storage device.
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1. A method for performing natural language processing, comprising: receiving a primary text file; scanning the received primary text file to determine a set of statistics related to a frequency at which various words of the primary text file follow other words of the primary text file; creating a probabilistic word generator, based on the determined set of statistics, that generates synthetic text exhibiting the determined set of statistics; generating synthetic text directly into a main memory of a computer system, the generated synthetic text including a plurality of sentences, each of which including a predetermined number of probabilistically selected words exhibiting the determined set of statistics, related to a frequency at which various words of the primary text file follow other words of the primary text file, using the created probabilistic word generator; performing word vectorization on the synthetic text, within the main memory of the computer system; using results of the performed vectorization to perform machine learning tasks; and using the machine learning tasks to perform natural language processing to interpret a subsequent text, wherein, in generating the synthetic text that is used to perform machine learning directly into the main memory, no text data is loaded into the main memory from a memory storage device. 12. The method of claim 1 , wherein vectorization is additionally performed in parallel on the primary text file and on generated text.
| 0.616299 |
14. The computer-readable storage medium of claim 8 , wherein the dynamic influence is provided by a user.
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14. The computer-readable storage medium of claim 8 , wherein the dynamic influence is provided by a user. 15. The computer-readable storage medium of claim 14 , further comprising computer-readable instructions for causing the at least one processor to temporarily stop performing the at least one test function while the dynamic influence is provided by the user.
| 0.885601 |
1. A method for generating test data, the method comprising: a computer receiving a corpus of sample documents associated with a knowledge domain, wherein each sample document of the corpus includes unstructured information; the computer identifying a sample document of the corpus of sample documents; the computer identifying that the knowledge domain of the sample document is associated with a database, wherein the database contains resources relevant to the knowledge domain including, at least, a plurality of annotators associated with the knowledge domain and a knowledge domain specific dictionary; the computer annotating the sample document using the plurality of annotators associated with the knowledge domain to produce annotations associated with the sample document; the computer determining a plurality of patterns in the sample document based on the annotations, wherein each pattern comprises a combination of annotations in a sequence; the computer populating a template using the at least one of the plurality of patterns; and the computer varying parts of the at least one of the plurality of patterns in the template to generate test data, wherein varying the at least one of the plurality of patterns comprises identifying portions of data from the knowledge domain specific dictionary corresponding to an annotation of the at least one of the plurality of patterns and inserting a portion of data from the knowledge domain specific dictionary corresponding to the annotation into the at least one of the plurality of patterns based on the sequence of the combination of annotations.
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1. A method for generating test data, the method comprising: a computer receiving a corpus of sample documents associated with a knowledge domain, wherein each sample document of the corpus includes unstructured information; the computer identifying a sample document of the corpus of sample documents; the computer identifying that the knowledge domain of the sample document is associated with a database, wherein the database contains resources relevant to the knowledge domain including, at least, a plurality of annotators associated with the knowledge domain and a knowledge domain specific dictionary; the computer annotating the sample document using the plurality of annotators associated with the knowledge domain to produce annotations associated with the sample document; the computer determining a plurality of patterns in the sample document based on the annotations, wherein each pattern comprises a combination of annotations in a sequence; the computer populating a template using the at least one of the plurality of patterns; and the computer varying parts of the at least one of the plurality of patterns in the template to generate test data, wherein varying the at least one of the plurality of patterns comprises identifying portions of data from the knowledge domain specific dictionary corresponding to an annotation of the at least one of the plurality of patterns and inserting a portion of data from the knowledge domain specific dictionary corresponding to the annotation into the at least one of the plurality of patterns based on the sequence of the combination of annotations. 6. The method of claim 1 , wherein the knowledge domain is selected from the group consisting of: insurance, engineering, medicine, computer programming, and finance.
| 0.532193 |
8. A method being performed by one or more computing devices including at least one processor, the method for reconciling query results associated with multiple indices, the method comprising: at a computing device, receiving a search query comprising a word having a first spelling; comparing the first spelling to a first index that is specific to the computing device and, based on the comparison, generating a first alternate spelling suggestion; determining a first query result based on the first alternate spelling suggestion and on the first index; receiving a second query result from a comparison of the received search query with a second index, the second index being specific to web-based content; assigning confidence values to each of the first query result and the second query result, the confidence values indicating a likelihood that an associated query result is reflective of an intent of the search query, wherein the confidence values are assigned based on a search pattern associated with a user of the computing device; selecting one of the first query result or the second query result as most responsive to the received search query; and providing for display a descriptor for the selected query result that is most responsive to the received search query and an indication of which index was utilized in determining the selected query result.
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8. A method being performed by one or more computing devices including at least one processor, the method for reconciling query results associated with multiple indices, the method comprising: at a computing device, receiving a search query comprising a word having a first spelling; comparing the first spelling to a first index that is specific to the computing device and, based on the comparison, generating a first alternate spelling suggestion; determining a first query result based on the first alternate spelling suggestion and on the first index; receiving a second query result from a comparison of the received search query with a second index, the second index being specific to web-based content; assigning confidence values to each of the first query result and the second query result, the confidence values indicating a likelihood that an associated query result is reflective of an intent of the search query, wherein the confidence values are assigned based on a search pattern associated with a user of the computing device; selecting one of the first query result or the second query result as most responsive to the received search query; and providing for display a descriptor for the selected query result that is most responsive to the received search query and an indication of which index was utilized in determining the selected query result. 12. The method of claim 8 , wherein the first alternate spelling suggestion comprises a personal contact name that is stored locally on the computing device.
| 0.625272 |
1. A method in a computing system for debugging interpreted code in a visual debugger using breakpoints to facilitate step-based evaluation of expressions, comprising: presenting a visual user interface for receiving debugging commands; in response to a received debug command to set or change an indicated breakpoint in a segment of code that is expressed in an interpreted programming language and that defines one or more expressions, determining the nearest enclosing expression to the indicated breakpoint, including when the nearest enclosing expression begins on a line of source code associated with the code segment that is different from a line of the associated source code that contains the indicated breakpoint; and generating a breakpoint address that indicates a location in the segment of code that corresponds to the beginning of the determined enclosing expression when the code segment is evaluated; causing the code segment to be evaluated using an interpreter for the interpreted programming language, such that evaluation automatically stops when the location in the code segment that corresponds to the breakpoint address is encountered; causing one or more source code statements that correspond to and indicate the location in the code segment where the evaluation stopped to be displayed in the visual interface; and receiving one or more additional debug commands to further control the evaluation of the code segment or to examine aspects of the code segment under evaluation.
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1. A method in a computing system for debugging interpreted code in a visual debugger using breakpoints to facilitate step-based evaluation of expressions, comprising: presenting a visual user interface for receiving debugging commands; in response to a received debug command to set or change an indicated breakpoint in a segment of code that is expressed in an interpreted programming language and that defines one or more expressions, determining the nearest enclosing expression to the indicated breakpoint, including when the nearest enclosing expression begins on a line of source code associated with the code segment that is different from a line of the associated source code that contains the indicated breakpoint; and generating a breakpoint address that indicates a location in the segment of code that corresponds to the beginning of the determined enclosing expression when the code segment is evaluated; causing the code segment to be evaluated using an interpreter for the interpreted programming language, such that evaluation automatically stops when the location in the code segment that corresponds to the breakpoint address is encountered; causing one or more source code statements that correspond to and indicate the location in the code segment where the evaluation stopped to be displayed in the visual interface; and receiving one or more additional debug commands to further control the evaluation of the code segment or to examine aspects of the code segment under evaluation. 5. The method of claim 1 wherein the visual user interface is an Interactive Development Environment (“IDE”) having a predefined set of interfaces for developing and testing program code.
| 0.614893 |
1. A method for generating speech from text, comprising the steps of: storing a set of decision tree context-dependent phoneme-based units of a target speaker, wherein a central phoneme-based unit is selected from a group consisting of a phoneme and a diphone, wherein each context-dependent phoneme-based unit is arranged based on context of at least one immediately preceding and succeeding phoneme-based unit, and wherein one context-dependent phoneme-based unit is chosen to represent each leaf node in the decision trees; obtaining a string of phonetic symbols representative of a text to be converted to speech; selecting stored decision-tree based context-dependent phoneme-based units from the set of decision tree based context-dependent phoneme-based units based on the contexts of the phonetic symbols; and synthesizing the selected context-based phoneme-based units to generate speech corresponding to the text.
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1. A method for generating speech from text, comprising the steps of: storing a set of decision tree context-dependent phoneme-based units of a target speaker, wherein a central phoneme-based unit is selected from a group consisting of a phoneme and a diphone, wherein each context-dependent phoneme-based unit is arranged based on context of at least one immediately preceding and succeeding phoneme-based unit, and wherein one context-dependent phoneme-based unit is chosen to represent each leaf node in the decision trees; obtaining a string of phonetic symbols representative of a text to be converted to speech; selecting stored decision-tree based context-dependent phoneme-based units from the set of decision tree based context-dependent phoneme-based units based on the contexts of the phonetic symbols; and synthesizing the selected context-based phoneme-based units to generate speech corresponding to the text. 3. The method of claim 1 wherein the phoneme-based unit comprises a phoneme and wherein the context-dependent phoneme-based unit comprises a quinphone, a phoneme in the context of the two immediately preceding and succeeding phonemes.
| 0.617143 |
9. The computer-readable medium of instructions with computer-readable instructions stored thereon for secure document transmission of claim 8 , wherein the instructions for communicating the hybrid electronic document to a selected destination further comprises: instructions for rendering the hybrid electronic document so as to output the hybrid electronic document as a hardcopy document; instructions for scanning the hardcopy document to generate facsimile data representative of the hybrid electronic document; and instructions for transmitting the facsimile data to the selected destination.
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9. The computer-readable medium of instructions with computer-readable instructions stored thereon for secure document transmission of claim 8 , wherein the instructions for communicating the hybrid electronic document to a selected destination further comprises: instructions for rendering the hybrid electronic document so as to output the hybrid electronic document as a hardcopy document; instructions for scanning the hardcopy document to generate facsimile data representative of the hybrid electronic document; and instructions for transmitting the facsimile data to the selected destination. 10. The computer-readable medium of instructions with computer-readable instructions stored thereon for secure document transmission of claim 9 , further comprising: instructions for receiving the facsimile data; and instructions for rendering a rendered hardcopy document of the facsimile data.
| 0.758501 |
12. A non-transitory computer readable medium storing instructions for interviewing a candidate, the instructions when executed by a processor comprising functionality to: provide a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtain a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjust the interview plan to generate an adjusted interview plan based on the mock interview score qualified candidate profile and the pre-determined qualification score; collect a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyze the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively present the candidate profile to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information.
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12. A non-transitory computer readable medium storing instructions for interviewing a candidate, the instructions when executed by a processor comprising functionality to: provide a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtain a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjust the interview plan to generate an adjusted interview plan based on the mock interview score qualified candidate profile and the pre-determined qualification score; collect a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyze the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively present the candidate profile to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information. 20. The computer readable medium of claim 12 , the instructions further comprising functionality to: store the candidate profile information for at least one selected from a group consisting of a different position, a future position, a different recruiter, and a different employer, wherein the candidate is interviewed by the virtual interview assistant for the recruiter based on a current position of an employer.
| 0.583224 |
1. A circuit pattern comparison apparatus for extracting portions matched to a designated predetermined search pattern from an object of comparison represented by a circuit network having a set of nodes and node-to-node arcs or links, comprising: search pattern editing means for schematically describing said designated predetermined search pattern having a plurality of nodes; comparison order designating means for designating a comparison order of the nodes contained in the designated predetermined search pattern; search code synthesizing means for synthesizing at least one search code by subjecting, to code conversion, said designated predetermined search pattern schematically described by said search pattern editing means; comparing means for comparing the designated predetermined search pattern to the object of comparison utilizing the at least one search code; and extracting means for extracting at least one portion of the object of comparison matched to said designated predetermined search pattern.
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1. A circuit pattern comparison apparatus for extracting portions matched to a designated predetermined search pattern from an object of comparison represented by a circuit network having a set of nodes and node-to-node arcs or links, comprising: search pattern editing means for schematically describing said designated predetermined search pattern having a plurality of nodes; comparison order designating means for designating a comparison order of the nodes contained in the designated predetermined search pattern; search code synthesizing means for synthesizing at least one search code by subjecting, to code conversion, said designated predetermined search pattern schematically described by said search pattern editing means; comparing means for comparing the designated predetermined search pattern to the object of comparison utilizing the at least one search code; and extracting means for extracting at least one portion of the object of comparison matched to said designated predetermined search pattern. 21. A circuit pattern comparison apparatus according to claim 1, further comprising: normal comparison order knowledge input means for inputting normal comparison order knowledge independent of an individual pattern for the comparison order; and comparison order synthesizing means for combining the normal comparison order knowledge input from the normal comparison order knowledge input means and the comparison order designated by said comparison order designating means and for synthesizing a new comparison order, wherein said comparing means includes means for comparing said designated predetermined comparison pattern from the object of comparison in accordance with the new comparison order synthesized by said comparison order synthesizing means.
| 0.5 |
10. The system of claim 9 , wherein the operations further comprise: receiving information associated with a user performing the image capture process on the rendered document; identifying the user, based on the received information; identifying the rendered document, based on the output of performing the image capture process; identifying, from a corpus of electronic documents, an electronic document that corresponds to the rendered document; and storing, in a repository, a record of the instruction to perform the particular action, the record comprising an identifier of the user, an identifier of the electronic document, an identifier of the particular action, and a timestamp associated with performing the particular action.
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10. The system of claim 9 , wherein the operations further comprise: receiving information associated with a user performing the image capture process on the rendered document; identifying the user, based on the received information; identifying the rendered document, based on the output of performing the image capture process; identifying, from a corpus of electronic documents, an electronic document that corresponds to the rendered document; and storing, in a repository, a record of the instruction to perform the particular action, the record comprising an identifier of the user, an identifier of the electronic document, an identifier of the particular action, and a timestamp associated with performing the particular action. 11. The system of claim 10 , wherein the operations further comprise: determining formatting information of the rendered document, based on the output of performing the image capture process, wherein the record of the instruction to perform the particular action further comprises the formatting information of the rendered document and an identifier of the rendered document.
| 0.607218 |
47. The article of manufacture according to claim 43, further comprising: computer-readable program code means for recording the student's response to the interactive process; said computer-readable program code means for calculating student performance based on an average percent correct of all past student responses recorded by said computer-readable program code means for recording, the difficulty level of the interactive process presented by said computer-readable program code means for presenting, and the response time measured by said computer-readable program code means for measuring the response time; and said computer-readable program code means for adjusting the difficulty level of the test presented by said computer-readable program code means for presenting based on the student performance calculated in said computer-readable program code means for calculating.
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47. The article of manufacture according to claim 43, further comprising: computer-readable program code means for recording the student's response to the interactive process; said computer-readable program code means for calculating student performance based on an average percent correct of all past student responses recorded by said computer-readable program code means for recording, the difficulty level of the interactive process presented by said computer-readable program code means for presenting, and the response time measured by said computer-readable program code means for measuring the response time; and said computer-readable program code means for adjusting the difficulty level of the test presented by said computer-readable program code means for presenting based on the student performance calculated in said computer-readable program code means for calculating. 48. The article of manufacture according to claim 47, further comprising: computer-readable program code means for inputting the student's age wherein the student's age may be a chronological age or a reading level, said computer-readable program code means for calculating student performance based on an average percent correct of all past student responses recorded by said computer-readable program code means for recording, the difficulty level of the interactive process presented by said computer-readable program code means for presenting, and the response time measured by said computer-readable program code means for measuring the response time; and said computer-readable program code means for adjusting the difficulty level of the test presented by said computer-readable program code means for presenting based on the student performance calculated by said computer-readable program code means for calculating and the student's age inputted in said computer-readable program code means for inputting.
| 0.651376 |
1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document.
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1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. 23. The method of claim 1 , wherein at least one writing profile representation comprises at least one global characteristic of the writing.
| 0.73694 |
15. A system for creating a language model, the system comprising: a processor; a data remembrance component; an input device; a display device; a web crawler that collects a set of documents, that evaluates said documents and that counts occurrence of N-grams in said documents, that creates data indicating counts of N-grams in said documents,that is configured to indicate counts of N-grams in a first set of documents, wherein said web crawler is configured to create a quantity indicating how well a first statistical language model predicts counts of N-grams in said first set of documents, and is configured to create a second statistical language model based on a first probability distribution in said first statistical language model, a second probability distribution based on N-gram counts of said first set of documents, and said quantity, M being a number of N-grams in said first set of documents, said web crawler being configured to create said quantity by calculating a divergence between said first probability distribution and said second probability distribution, and by raising a number to a power that is based on said divergence; and a text receipt component that is stored in said data remembrance component, that executes on said processor, that is configured to receive text entered by a user, and that is configured to use said second statistical language model to present, on said display, suggested phrases that begin with said text entered by said user.
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15. A system for creating a language model, the system comprising: a processor; a data remembrance component; an input device; a display device; a web crawler that collects a set of documents, that evaluates said documents and that counts occurrence of N-grams in said documents, that creates data indicating counts of N-grams in said documents,that is configured to indicate counts of N-grams in a first set of documents, wherein said web crawler is configured to create a quantity indicating how well a first statistical language model predicts counts of N-grams in said first set of documents, and is configured to create a second statistical language model based on a first probability distribution in said first statistical language model, a second probability distribution based on N-gram counts of said first set of documents, and said quantity, M being a number of N-grams in said first set of documents, said web crawler being configured to create said quantity by calculating a divergence between said first probability distribution and said second probability distribution, and by raising a number to a power that is based on said divergence; and a text receipt component that is stored in said data remembrance component, that executes on said processor, that is configured to receive text entered by a user, and that is configured to use said second statistical language model to present, on said display, suggested phrases that begin with said text entered by said user. 20. The system of claim 15 , said documents comprising web documents.
| 0.867661 |
9. The system of claim 1 wherein computing the set of coordinate vectors from each media object comprising the subset of media objects comprises initially embedding each media object in the subset into a multidimensional space.
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9. The system of claim 1 wherein computing the set of coordinate vectors from each media object comprising the subset of media objects comprises initially embedding each media object in the subset into a multidimensional space. 14. The system of claim 9 wherein initially embedding each media object into a multidimensional space comprises performing a multidimensional scaling-based processing of the sparse graph of media object similarities.
| 0.883596 |
11. A method comprising: processing, by at least one server computer, electronic page requests and determining whether to implement normal page navigation operations or minimal download operations, wherein in response to implementing the minimal download operations creating difference packages associated with previously-rendered electronic pages and target electronic pages including script differences, style differences, and other differences, wherein, each difference package to include information associated with differences between a previously-rendered electronic page and a target electronic page as part of a navigation operation, the information associated with differences to include a page script set, a page style sheet set, and markup differences associated with the previously-rendered electronic page and the target electronic page; using a client computer to request electronic pages, browse electronic pages, and use difference packages as part of processing page navigation operations, wherein each electronic page is configured to be rendered according to a number of page portions that include one or more script portions, style portions, and markup portions, further using the client computer to use a difference package provided by the at least one server computer to perform a difference application at the client computer to update one or multiple areas of the target electronic page using differences included with the difference package as part of simulating a page navigation mechanism that includes an unload operation associated with the previously-rendered electronic page and a render operation for the target electronic page followed by running target global script and firing target load events; using an electronic page request operation to determine whether to use normal page navigation operations or minimal download operations, wherein the minimal download operations operate to determine page differences between the target page and the previously-rendered page, the page differences including script differences, style differences, and other differences; and using the difference package to update an interactive interface at the client computer to navigate between electronic pages as part of providing simulated page transition operations including performing a difference application of the page differences at the client computer to render the target electronic page, wherein using the difference package further includes displaying the target electronic page including using new script, styles, and encoded markup included with the difference package and adding an inline style to a global style array for each inline style of the target electronic page.
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11. A method comprising: processing, by at least one server computer, electronic page requests and determining whether to implement normal page navigation operations or minimal download operations, wherein in response to implementing the minimal download operations creating difference packages associated with previously-rendered electronic pages and target electronic pages including script differences, style differences, and other differences, wherein, each difference package to include information associated with differences between a previously-rendered electronic page and a target electronic page as part of a navigation operation, the information associated with differences to include a page script set, a page style sheet set, and markup differences associated with the previously-rendered electronic page and the target electronic page; using a client computer to request electronic pages, browse electronic pages, and use difference packages as part of processing page navigation operations, wherein each electronic page is configured to be rendered according to a number of page portions that include one or more script portions, style portions, and markup portions, further using the client computer to use a difference package provided by the at least one server computer to perform a difference application at the client computer to update one or multiple areas of the target electronic page using differences included with the difference package as part of simulating a page navigation mechanism that includes an unload operation associated with the previously-rendered electronic page and a render operation for the target electronic page followed by running target global script and firing target load events; using an electronic page request operation to determine whether to use normal page navigation operations or minimal download operations, wherein the minimal download operations operate to determine page differences between the target page and the previously-rendered page, the page differences including script differences, style differences, and other differences; and using the difference package to update an interactive interface at the client computer to navigate between electronic pages as part of providing simulated page transition operations including performing a difference application of the page differences at the client computer to render the target electronic page, wherein using the difference package further includes displaying the target electronic page including using new script, styles, and encoded markup included with the difference package and adding an inline style to a global style array for each inline style of the target electronic page. 12. The method of claim 11 , further comprising using the minimal download operations as part of displaying the interactive interface, including running the new script and using the new styles of the difference package to provide a simulated page navigation transition.
| 0.5 |
2. The method according to claim 1 , wherein utilizing a processing device to evaluate the realization pattern against the target computing environment model further comprises: performing at least one reconfiguration action that modifies the target computing environment model; modifying the model graph corresponding to the modified target computing environment model; and re-executing at least one pattern matching algorithm that attempts to match the pattern graph to the modified model graph to identify whether the realization pattern matches to the modified target computing environment model.
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2. The method according to claim 1 , wherein utilizing a processing device to evaluate the realization pattern against the target computing environment model further comprises: performing at least one reconfiguration action that modifies the target computing environment model; modifying the model graph corresponding to the modified target computing environment model; and re-executing at least one pattern matching algorithm that attempts to match the pattern graph to the modified model graph to identify whether the realization pattern matches to the modified target computing environment model. 4. The method according to claim 2 , wherein: utilizing at least one pattern matching algorithm comprises implementing a pattern matching algorithm wherein: the implemented algorithm handles allowable reconfiguration actions that are viewed as graph edit operations performed on the model graph; and the implemented pattern matching algorithm is used to find an isomorphic match of the pattern graph in the model graph corresponding to a match of the realization pattern in the target computing environment model; and performing at least one reconfiguration action comprises utilizing at least one allowable reconfiguration action in a set of allowable graph edit operations to the model graph to transform the model graph in search of a sub-graph that is isomorphic to the pattern graph.
| 0.78419 |
11. A computer-implemented method for facilitating creation of an ad hoc social networking forum for a cohort of users, the method being implemented in a computer system comprising one or more physical processors programmed with computer readable instructions to, the method comprising: obtaining, by the one or more physical processors, from one or more publicly available sources, information related to a first cohort prior to receiving a user request to join a first social networking forum that is related to the first cohort, the first cohort comprising a plurality of users that have a pre-established association with a first experience scheduled to occur at a first time, first date, and a first location, the information related to the first cohort comprising information related to the first experience; and receiving, by the one or more physical processors, a request from a first user of the first cohort to join the first social networking forum associated with the first cohort; determining, by the one or more physical processors, whether the first social networking forum has been created; and responsive to a determination that the first social networking forum has not been created: creating, by the one or more physical processors, the first social networking forum; and adding, by the one or more physical processors, the first user as a member of the first social networking forum; and facilitating, by the one or more physical processors, sharing of one or more items of content via the first social networking forum.
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11. A computer-implemented method for facilitating creation of an ad hoc social networking forum for a cohort of users, the method being implemented in a computer system comprising one or more physical processors programmed with computer readable instructions to, the method comprising: obtaining, by the one or more physical processors, from one or more publicly available sources, information related to a first cohort prior to receiving a user request to join a first social networking forum that is related to the first cohort, the first cohort comprising a plurality of users that have a pre-established association with a first experience scheduled to occur at a first time, first date, and a first location, the information related to the first cohort comprising information related to the first experience; and receiving, by the one or more physical processors, a request from a first user of the first cohort to join the first social networking forum associated with the first cohort; determining, by the one or more physical processors, whether the first social networking forum has been created; and responsive to a determination that the first social networking forum has not been created: creating, by the one or more physical processors, the first social networking forum; and adding, by the one or more physical processors, the first user as a member of the first social networking forum; and facilitating, by the one or more physical processors, sharing of one or more items of content via the first social networking forum. 12. The method of claim 11 , further comprising: receiving, by the one or more physical processors, a request from a second user of the first cohort to join the first social networking forum associated with the first cohort; determining, by the one or more physical processors, whether the first social networking forum has been created; and responsive to a determination that the first social networking forum has been created: adding, by the one or more physical processors, the second user as a second member of the first social networking forum.
| 0.738272 |
18. The system of claim 17 wherein the second end of the another connector rod of the one or more additional implants includes a yoke that is receivable over the shank of the first implant associated with the first motion segment.
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18. The system of claim 17 wherein the second end of the another connector rod of the one or more additional implants includes a yoke that is receivable over the shank of the first implant associated with the first motion segment. 21. The system of claim 18 wherein: the shank includes an outer wall; the outer wall includes has a hexagonal shape; and the yoke has a shape of a box-end wrench.
| 0.935698 |
1. An apparatus comprising: an electronic data processing device configured to perform a multi-task machine learning method to generate a multi-task (MT) predictor for a set of N classification tasks where N is greater than or equal to two, the machine learning method including: learning a multi-task decision tree (MT-DT) including learning decision rules for nodes of the MT-DT that optimize an aggregate information gain (IG) that aggregates single-task IG values for tasks of the set of N classification tasks; and constructing the MT predictor based on one or more learned MT-DTs.
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1. An apparatus comprising: an electronic data processing device configured to perform a multi-task machine learning method to generate a multi-task (MT) predictor for a set of N classification tasks where N is greater than or equal to two, the machine learning method including: learning a multi-task decision tree (MT-DT) including learning decision rules for nodes of the MT-DT that optimize an aggregate information gain (IG) that aggregates single-task IG values for tasks of the set of N classification tasks; and constructing the MT predictor based on one or more learned MT-DTs. 6. The apparatus of claim 1 wherein the constructing includes: constructing the MT predictor based on a single learned MT-DT.
| 0.615816 |
19. A computer program stored in a non-transitory manner in one or more computer storage media, said computer program when loaded and run in a computer system causing the computer system to be configured as follows and to carry out the following steps though not necessarily in the sequence recited below: receiving in or generating by the computer system plural documents in respective formats according to respective different applications through which the documents are generated or modified, which formats differ from one of the documents to another for at least some of the documents; said computer system being configured to automatically generate and store in computer storage respective representations of said documents, thereby forming a main collection of document representations corresponding to a man collection of said documents; said computer system automatically generating and storing said main collection of document representations without requiring the user to designate a directory structure, a physical location for storage of document representations of corresponding documents, or another pre-imposed document categorization structure for each of said document representations or documents; selectively displaying on a computer screen graphical depictions of only a portion of the main collection of document representations, corresponding to only a portion of the main collection of documents, wherein the displayed graphical depictions of only a portion of said main collection of document representations comprise a display of partly overlapping, receding graphical depictions of document representations; said automatically generated and stored document representations being in an essentially consistent format despite differences in format from one to another of the documents corresponding thereto; said automatically generated and stored representations of said documents including respective automatically generated time indicators associated with the documents corresponding to said representations; said automatically generated and stored main collection of document representations being unbounded in time and size and being configured to include documents associated with time indicators related to future times as well as to past and present times; said automatically generated and stored main collection of document representations requiring no fixed beginning or end and being non-transitory and selectively searchable by the computer system; said computer system automatically maintaining the main collection of document representations live, dynamic and persistent by being responsive to subsequent events to expand said main collection of document representations by automatically generating and incorporating therein, in said computer storage, additional document representations of additional documents corresponding thereto that are subsequently received by or generated by the computer system; said additional document representations also including automatically generated respective time indicators associated with the subsequently received or generated documents; providing selected search criteria; causing said computer system to search at least one of said main collection of document representations and said main collection of documents according to said search criteria, to provide search results, and to utilize said search results to generate a sub-collection of document representations related to a respective sub-collection of documents that comprise a subset of the main collection of documents; said computer system automatically maintaining said sub-collection of document representations live, dynamic and persistent, and being responsive to subsequent events to expand said sub-collection of document representations by automatically incorporating therein document representations of documents that are subsequently received by or generated by the computer system and meet said search criteria; selectively displaying on a computer screen graphical depictions of only a portion of the sub-collection of document representations, corresponding to only a portion of said sub-collection of documents, wherein the displayed graphical depictions of said portion of said sub-collection of document representations comprise a display of partly overlapping, receding graphical depictions; automatically showing on the display screen a display of a glance view of a displayed graphical depiction while showing other displayed graphical depictions as a display of partly overlapping and receding graphical depictions; said glance view being an abbreviated version of the document representation or document corresponding to the graphical depiction and being indicative of content thereof; and said showing of the glance view occurring in response to a user designation, with an input device, of a screen area associated with the graphical depiction, without requiring dwelling of a cursor for at least about a second on a selected area of the screen associated with the currently displayed collection or sub-collection of graphical depictions in order to enable said showing of the glance view.
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19. A computer program stored in a non-transitory manner in one or more computer storage media, said computer program when loaded and run in a computer system causing the computer system to be configured as follows and to carry out the following steps though not necessarily in the sequence recited below: receiving in or generating by the computer system plural documents in respective formats according to respective different applications through which the documents are generated or modified, which formats differ from one of the documents to another for at least some of the documents; said computer system being configured to automatically generate and store in computer storage respective representations of said documents, thereby forming a main collection of document representations corresponding to a man collection of said documents; said computer system automatically generating and storing said main collection of document representations without requiring the user to designate a directory structure, a physical location for storage of document representations of corresponding documents, or another pre-imposed document categorization structure for each of said document representations or documents; selectively displaying on a computer screen graphical depictions of only a portion of the main collection of document representations, corresponding to only a portion of the main collection of documents, wherein the displayed graphical depictions of only a portion of said main collection of document representations comprise a display of partly overlapping, receding graphical depictions of document representations; said automatically generated and stored document representations being in an essentially consistent format despite differences in format from one to another of the documents corresponding thereto; said automatically generated and stored representations of said documents including respective automatically generated time indicators associated with the documents corresponding to said representations; said automatically generated and stored main collection of document representations being unbounded in time and size and being configured to include documents associated with time indicators related to future times as well as to past and present times; said automatically generated and stored main collection of document representations requiring no fixed beginning or end and being non-transitory and selectively searchable by the computer system; said computer system automatically maintaining the main collection of document representations live, dynamic and persistent by being responsive to subsequent events to expand said main collection of document representations by automatically generating and incorporating therein, in said computer storage, additional document representations of additional documents corresponding thereto that are subsequently received by or generated by the computer system; said additional document representations also including automatically generated respective time indicators associated with the subsequently received or generated documents; providing selected search criteria; causing said computer system to search at least one of said main collection of document representations and said main collection of documents according to said search criteria, to provide search results, and to utilize said search results to generate a sub-collection of document representations related to a respective sub-collection of documents that comprise a subset of the main collection of documents; said computer system automatically maintaining said sub-collection of document representations live, dynamic and persistent, and being responsive to subsequent events to expand said sub-collection of document representations by automatically incorporating therein document representations of documents that are subsequently received by or generated by the computer system and meet said search criteria; selectively displaying on a computer screen graphical depictions of only a portion of the sub-collection of document representations, corresponding to only a portion of said sub-collection of documents, wherein the displayed graphical depictions of said portion of said sub-collection of document representations comprise a display of partly overlapping, receding graphical depictions; automatically showing on the display screen a display of a glance view of a displayed graphical depiction while showing other displayed graphical depictions as a display of partly overlapping and receding graphical depictions; said glance view being an abbreviated version of the document representation or document corresponding to the graphical depiction and being indicative of content thereof; and said showing of the glance view occurring in response to a user designation, with an input device, of a screen area associated with the graphical depiction, without requiring dwelling of a cursor for at least about a second on a selected area of the screen associated with the currently displayed collection or sub-collection of graphical depictions in order to enable said showing of the glance view. 28. The computer program of claim 19 in which said computer system automatically orders said document representations according to the time indicators associated therewith, without requiring a user command requesting time-order, and said graphical depictions are displayed in time order.
| 0.522753 |
3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set.
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3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. 4. The method of claim 3 , wherein the audit information comprises application-identifying information.
| 0.708015 |
2. The method of claim 1 , further comprising: receiving the search query; and determining search results for the search query using the indices associated with the first set of medical documents and second set of medical documents, wherein the search results include a subset of medical documents from the first set of medical documents and second set of medical documents that are determined to match the search query.
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2. The method of claim 1 , further comprising: receiving the search query; and determining search results for the search query using the indices associated with the first set of medical documents and second set of medical documents, wherein the search results include a subset of medical documents from the first set of medical documents and second set of medical documents that are determined to match the search query. 3. The method of claim 2 , further comprising displaying the search results in an interface, wherein the subset of medical documents is displayed in the image-based format.
| 0.908874 |
1. A computer implemented method of conducting commerce, using one or more computers, the method comprising: receiving by one or more computer systems text inputs corresponding to transactions; analyzing by the one or more computer systems the text inputs by executing natural language processing programs; producing by the one or more computers, based on results of analyzing the transactions by the natural language processing programs, added information, searching a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response triggering a facility to present additional information about the key concept; building by a conversational engine running on the one or more computer systems, a conversation based on the transaction requests and key concept, statistically analyzing by the one or more computers the information stored in the database based on the added information; tracking by the one or more computers interactions with the user; storing information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generating in the one or more computers voice-synthesized responses based on the received transaction requests through an avatar; generating additional, voice-synthesized, follow-up responses through the avatar in response to the transactions based on information stored in the database, including the added information regarding the transactions; receiving by the one or more computer systems subsequent text inputs from the user; analyzing in the one or more computers the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take; and causing execution of the determined action.
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1. A computer implemented method of conducting commerce, using one or more computers, the method comprising: receiving by one or more computer systems text inputs corresponding to transactions; analyzing by the one or more computer systems the text inputs by executing natural language processing programs; producing by the one or more computers, based on results of analyzing the transactions by the natural language processing programs, added information, searching a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response triggering a facility to present additional information about the key concept; building by a conversational engine running on the one or more computer systems, a conversation based on the transaction requests and key concept, statistically analyzing by the one or more computers the information stored in the database based on the added information; tracking by the one or more computers interactions with the user; storing information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generating in the one or more computers voice-synthesized responses based on the received transaction requests through an avatar; generating additional, voice-synthesized, follow-up responses through the avatar in response to the transactions based on information stored in the database, including the added information regarding the transactions; receiving by the one or more computer systems subsequent text inputs from the user; analyzing in the one or more computers the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take; and causing execution of the determined action. 7. The method of claim 1 wherein receiving one of the text inputs is in response to a suggestion generated by the avatar.
| 0.522399 |
9. An article comprising: a tangible storage medium having a plurality of machine accessible instructions; wherein, when the instructions are executed by a processor, the instructions provide for: bundling two or more hardware-specific variants of a run-time function into a generic function that corresponds to a parallel programming keyword of a parallel programming language; generating one or more meta-wrappers for the generic function based on an annotation supplied for each of the two or more hardware-specific variants of the run-time function; compiling source code of a user program that comprises (i) statements from a high-level programming language and (ii) the parallel programming keyword of the parallel programming language to generate a compiled binary of the user program, the compiled binary comprises (i) compiled code that corresponds to the statements from the high-level programming language and (ii) a run-time function call to the generic function embedded in the compiled binary as a function of the one or more meta wrappers; during runtime execution of the compiled binary, (i) executing the run-time function call to the generic function and (ii) dynamically selecting a hardware-specific variant of the run-time function for a selected sub-task associated with the parallel programming keyword; and dispatching the selected hardware-specific variant for execution on a hardware processing element associated with the selected hardware-specific variant.
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9. An article comprising: a tangible storage medium having a plurality of machine accessible instructions; wherein, when the instructions are executed by a processor, the instructions provide for: bundling two or more hardware-specific variants of a run-time function into a generic function that corresponds to a parallel programming keyword of a parallel programming language; generating one or more meta-wrappers for the generic function based on an annotation supplied for each of the two or more hardware-specific variants of the run-time function; compiling source code of a user program that comprises (i) statements from a high-level programming language and (ii) the parallel programming keyword of the parallel programming language to generate a compiled binary of the user program, the compiled binary comprises (i) compiled code that corresponds to the statements from the high-level programming language and (ii) a run-time function call to the generic function embedded in the compiled binary as a function of the one or more meta wrappers; during runtime execution of the compiled binary, (i) executing the run-time function call to the generic function and (ii) dynamically selecting a hardware-specific variant of the run-time function for a selected sub-task associated with the parallel programming keyword; and dispatching the selected hardware-specific variant for execution on a hardware processing element associated with the selected hardware-specific variant. 13. The article of claim 9 , wherein said instructions that provide for dynamically selecting a hardware-specific variant further provide for: said dynamically selecting a hardware-specific variant is based, at least in part, on one or more annotations associated with the variant.
| 0.548787 |
16. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code portions stored therein, the computer-executable program code portions comprising program code instructions for: causing display of a) a content package comprising a first content segment from a first content source, and b) a plurality of other content packages each comprising respective displayed content segments from the first content source; receiving an indication of a first gesture input in a positional relationship to the first content segment; identifying a second content segment relating to the first content segment from a second content source; in response to the indication of the first gesture input, gradually adapting the content packaging, causing display of at least a portion of the second content segment; receiving a second indication, wherein the second indication is a gradual extension of the first input gesture; and in response to the second indication, causing the content package to be further gradually adapted to reveal at least an additional portion of the second content segment, wherein the gradual adaption of the content package is performed simultaneously and proportionately gradually to the gradual extension of the first input gesture such that the first content segment from the first content source is gradually hidden and the second content segment from the second content source is gradually further revealed from beneath the first content segment, and while the gradual adaptation of the content package is performed, the respective displayed content segments from the first content source remain displayed.
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16. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code portions stored therein, the computer-executable program code portions comprising program code instructions for: causing display of a) a content package comprising a first content segment from a first content source, and b) a plurality of other content packages each comprising respective displayed content segments from the first content source; receiving an indication of a first gesture input in a positional relationship to the first content segment; identifying a second content segment relating to the first content segment from a second content source; in response to the indication of the first gesture input, gradually adapting the content packaging, causing display of at least a portion of the second content segment; receiving a second indication, wherein the second indication is a gradual extension of the first input gesture; and in response to the second indication, causing the content package to be further gradually adapted to reveal at least an additional portion of the second content segment, wherein the gradual adaption of the content package is performed simultaneously and proportionately gradually to the gradual extension of the first input gesture such that the first content segment from the first content source is gradually hidden and the second content segment from the second content source is gradually further revealed from beneath the first content segment, and while the gradual adaptation of the content package is performed, the respective displayed content segments from the first content source remain displayed. 19. The computer program product of claim 16 , wherein the second content segment includes a media type different from a media type of the first content segment.
| 0.584178 |
1. A method of enhancing speech, comprising: receiving noisy speech comprising a clean speech component and a non-stationary noise component; providing a speech model; providing a noise model having at least one shape and a gain; dynamically modifying the at least one shape and the gain of the noise model based at least in part on the speech model and the received noisy speech using a processor; and enhancing the noisy speech at least based on the modified noise model.
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1. A method of enhancing speech, comprising: receiving noisy speech comprising a clean speech component and a non-stationary noise component; providing a speech model; providing a noise model having at least one shape and a gain; dynamically modifying the at least one shape and the gain of the noise model based at least in part on the speech model and the received noisy speech using a processor; and enhancing the noisy speech at least based on the modified noise model. 2. The method of claim 1 , wherein the at least one shape and gain of the noise model are respectively modified separately.
| 0.59891 |
12. The system of claim 11 , wherein determining that the at least one topic is associated with the user comprises: identifying a set of topics associated with the user based on the data associated with the user; and determining that the at least one topic is included in the set of topics associated with the user.
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12. The system of claim 11 , wherein determining that the at least one topic is associated with the user comprises: identifying a set of topics associated with the user based on the data associated with the user; and determining that the at least one topic is included in the set of topics associated with the user. 13. The system of claim 12 , wherein the data associated with the user comprises an identifier assigned to the user.
| 0.935508 |
17. The computer-executed method of claim 1 , comprising: filtering the first population based on a filtering criteria; and wherein the affinity score is determined based on an intersection of social media users in the filtered first population and the second population.
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17. The computer-executed method of claim 1 , comprising: filtering the first population based on a filtering criteria; and wherein the affinity score is determined based on an intersection of social media users in the filtered first population and the second population. 19. The computer-executed method of claim 17 , wherein the filtering criteria is a content criteria, and wherein filtering the first population based on demographic criteria comprises: for each social media user in the first population, extracting social media features from a plurality of social media content items authored by the social media user; comparing the extracted features to the content criteria; and removing the social media user from the first population responsive to determining that none of the extracted features match the content criteria.
| 0.63311 |
1. A method of editing a document, the method including: a) receiving data associated with the document, the data including mark-up language data; b) processing the received data to render at least part of the document for display in a first display area of a display, and displaying as rendered the at least part of the document in the first display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; c) processing the received data to render the at least part of the document for display in a second display area of the display, and displaying as rendered the at least part of the document in the second display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; d) receiving editing data; e) editing the at least part of the document displayed in the second display area using the editing data, and applying said editing to the at least part of the document displayed in the first display area; f) storing data associated with the at least part of the document edited in e) as a first edited version; g) receiving further editing data; h) further editing the at least part of the document displayed in the second display area using the further editing data and applying the further editing to the edited at least part of the document displayed in the first display area; and i) storing as a second edited version data associated with the further edited at least part of the document.
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1. A method of editing a document, the method including: a) receiving data associated with the document, the data including mark-up language data; b) processing the received data to render at least part of the document for display in a first display area of a display, and displaying as rendered the at least part of the document in the first display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; c) processing the received data to render the at least part of the document for display in a second display area of the display, and displaying as rendered the at least part of the document in the second display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; d) receiving editing data; e) editing the at least part of the document displayed in the second display area using the editing data, and applying said editing to the at least part of the document displayed in the first display area; f) storing data associated with the at least part of the document edited in e) as a first edited version; g) receiving further editing data; h) further editing the at least part of the document displayed in the second display area using the further editing data and applying the further editing to the edited at least part of the document displayed in the first display area; and i) storing as a second edited version data associated with the further edited at least part of the document. 4. A method according to claim 1 , including in e) displaying the editing in the first display area during said editing.
| 0.559026 |
6. The computer-implemented method of claim 5 , wherein determining the matching score includes: assigning costs to edits made to the character class string, wherein the costs are based on a similarity between characters.
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6. The computer-implemented method of claim 5 , wherein determining the matching score includes: assigning costs to edits made to the character class string, wherein the costs are based on a similarity between characters. 7. The computer-implemented method of claim 6 , wherein the costs assigned to the edits made to the character class string are represented in an N by M matrix where N represents a number possible ASCII characters and M represents a number of possible character classes.
| 0.854221 |
1. A method comprising: receiving, at a search engine provider and from a user device, an initial query submitted by a current user; identifying additional queries relating to the initial query; identifying one or more respective advertisements for each of the additional queries from an inventory of advertisements; determining a respective measure of commerciality for each additional query based at least in part on a graph having: nodes corresponding to queries users have previously entered in search sessions and edges connecting the nodes, and an edge connecting, from among the nodes, a first node and a second node representing that the users have previously entered a second query represented by the second node after entering the initial query represented by the first node, wherein a weight of the edge represents a likelihood that the second query will be entered by the current user following the user's entry of the initial query, and wherein the commerciality for each additional query represents an estimated amount of revenue the search engine provider will receive by providing one or more of the advertisements identified for the additional queries in response to entry of the additional query by the user; selecting the second query based on the second query having a highest measure of commerciality among the additional queries; and updating a user interface of the user device to incorporate a presentation of the second query with content blocks that include one or more of the advertisements identified for the second query and search results associated with the initial query.
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1. A method comprising: receiving, at a search engine provider and from a user device, an initial query submitted by a current user; identifying additional queries relating to the initial query; identifying one or more respective advertisements for each of the additional queries from an inventory of advertisements; determining a respective measure of commerciality for each additional query based at least in part on a graph having: nodes corresponding to queries users have previously entered in search sessions and edges connecting the nodes, and an edge connecting, from among the nodes, a first node and a second node representing that the users have previously entered a second query represented by the second node after entering the initial query represented by the first node, wherein a weight of the edge represents a likelihood that the second query will be entered by the current user following the user's entry of the initial query, and wherein the commerciality for each additional query represents an estimated amount of revenue the search engine provider will receive by providing one or more of the advertisements identified for the additional queries in response to entry of the additional query by the user; selecting the second query based on the second query having a highest measure of commerciality among the additional queries; and updating a user interface of the user device to incorporate a presentation of the second query with content blocks that include one or more of the advertisements identified for the second query and search results associated with the initial query. 3. The method of claim 1 , wherein a commerce keyword identifies a name of a commercial product.
| 0.872368 |
3. The media of claim 1 , further comprising computing a ranking for the first clinical document in relation to the at least the second clinical document.
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3. The media of claim 1 , further comprising computing a ranking for the first clinical document in relation to the at least the second clinical document. 4. The media of claim 3 , wherein the ranking indicates the relative risk of the first clinical document having inappropriate duplication from the at least the second clinical document.
| 0.965517 |
5. The method of claim 1 , further comprising storing at least one association between at least one of the issue object, the question object, the answer object, and the decision object, and another of the issue object, the question object, the answer object, and the decision object.
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5. The method of claim 1 , further comprising storing at least one association between at least one of the issue object, the question object, the answer object, and the decision object, and another of the issue object, the question object, the answer object, and the decision object. 10. The method of claim 5 , wherein there are a plurality of questions related to the issue and a plurality of answers related to the plurality of questions.
| 0.905459 |
15. A system comprising: a server; a plurality of provider computers operatively coupled with the server and offering products for sale via the server; a plurality of client devices operatively coupled with the server, wherein the server is configured to: send a reclusive rules engine to a client device from the plurality of client devices, wherein the rules engine comprises a set of discount rules configured for automatically determining a purchase order discount from a coupon code when a purchase order is made and when a purchase order is modified, and wherein execution of the rules engine comprises: recursively evaluate a first set of rules for determining an applicability of the purchase order discount; recursively evaluate second set of rules for determining a discount value relating to an applicable discount; recursively evaluate the first set of rules and the second set of rules by performing an automatic process that recursively calls itself; receive a purchase order placed by a user of the client device along with a coupon code; receive the purchase order discount from the client device for the purchase order as automatically determined by the rules engine upon placement of a purchase order; applying the discount for the purchase order without independently determining the discount; relying on the determination of the rules engine; apply the discount without independently determining the purchase order discount; and process the purchase order along with the purchase order discount.
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15. A system comprising: a server; a plurality of provider computers operatively coupled with the server and offering products for sale via the server; a plurality of client devices operatively coupled with the server, wherein the server is configured to: send a reclusive rules engine to a client device from the plurality of client devices, wherein the rules engine comprises a set of discount rules configured for automatically determining a purchase order discount from a coupon code when a purchase order is made and when a purchase order is modified, and wherein execution of the rules engine comprises: recursively evaluate a first set of rules for determining an applicability of the purchase order discount; recursively evaluate second set of rules for determining a discount value relating to an applicable discount; recursively evaluate the first set of rules and the second set of rules by performing an automatic process that recursively calls itself; receive a purchase order placed by a user of the client device along with a coupon code; receive the purchase order discount from the client device for the purchase order as automatically determined by the rules engine upon placement of a purchase order; applying the discount for the purchase order without independently determining the discount; relying on the determination of the rules engine; apply the discount without independently determining the purchase order discount; and process the purchase order along with the purchase order discount. 17. The system of claim 15 , wherein the discount rules are further configured for determining a total discount value for a plurality of applicable discount types, wherein the discount rules are configured for executing the discount rules to automatically determine the total discount value associated with the purchase order.
| 0.509336 |
25. A computer system for verification analysis comprising: a memory which stores instructions; one or more processors coupled to the memory wherein the one or more processors are configured to: obtain a word-level data flow graph and obtain a bit-level data flow graph; search the bit-level data flow graph to find partial-product encoding; remove redundancy from the bit-level data flow graph; check the word-level data flow graph and the bit-level data flow graph for input correspondence; and perform equivalence checking between the bit-level data flow graph and the word-level data flow graph.
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25. A computer system for verification analysis comprising: a memory which stores instructions; one or more processors coupled to the memory wherein the one or more processors are configured to: obtain a word-level data flow graph and obtain a bit-level data flow graph; search the bit-level data flow graph to find partial-product encoding; remove redundancy from the bit-level data flow graph; check the word-level data flow graph and the bit-level data flow graph for input correspondence; and perform equivalence checking between the bit-level data flow graph and the word-level data flow graph. 26. The system of claim 25 wherein the one or more processors are further configured to generate a reference model based on the word-level data flow graph.
| 0.5 |
19. The method of claim 1 , wherein the user has obtained the authorization credential in exchange for user-performance of a specified action.
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19. The method of claim 1 , wherein the user has obtained the authorization credential in exchange for user-performance of a specified action. 21. The method of claim 19 , wherein the specified action is contributing an annotation of a digital work.
| 0.928152 |
1. A computer-implemented method, comprising: receiving social media data that includes topic information included in the social media data, sentiment values for at least some of the topic information, and location information correlated with the topic information; receiving user selection of a search term, a search term density value, and a sentiment density value for a particular sentiment value; comparing, for locations identified in the location information, a number of occurrences of the search term to a total volume of social media data received to determine a density of the search term at each of the locations; filtering the social media data to identify a set of locations that meet the user selected search term density value; filtering the set of locations to identify a subset of locations that meet the user selected sentiment density value for the particular sentiment value; and populating a map interface with indicia of the search term such that the search term is visually associated with the subset of locations, the indicia of the search term indicating one or more particular locations where the determined density of the particular sentiment value for the search term meets the user selected density value for the particular sentiment value.
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1. A computer-implemented method, comprising: receiving social media data that includes topic information included in the social media data, sentiment values for at least some of the topic information, and location information correlated with the topic information; receiving user selection of a search term, a search term density value, and a sentiment density value for a particular sentiment value; comparing, for locations identified in the location information, a number of occurrences of the search term to a total volume of social media data received to determine a density of the search term at each of the locations; filtering the social media data to identify a set of locations that meet the user selected search term density value; filtering the set of locations to identify a subset of locations that meet the user selected sentiment density value for the particular sentiment value; and populating a map interface with indicia of the search term such that the search term is visually associated with the subset of locations, the indicia of the search term indicating one or more particular locations where the determined density of the particular sentiment value for the search term meets the user selected density value for the particular sentiment value. 4. A computer-implemented method as recited in claim 1 , wherein the indicia of the topic information are overlaid on geographic regions of the map interface that correspond to the locations identified by the location information.
| 0.564235 |
8. A non-transitory computer readable storage medium comprising executable instructions for causing a computing system to perform operations comprising: performing a first syntactic and semantic analysis of a training natural language text to produce a first plurality of language-independent semantic structures representing a plurality of sentences of the training natural language text; producing, based on the first plurality of language-independent semantic structures, a text classifier model; performing a second syntactic and semantic analysis of an input natural language text to produce a second plurality of language-independent semantic structures representing a plurality of sentences of the input natural language text; extracting, using the second plurality of language-independent semantic structures, a set of features, wherein at least one feature references a semantic class of a language-independent semantic hierarchy comprising a plurality of semantic classes, in which the semantic class exhibits one or more properties inherited from its parent semantic class; applying the text classifier model to the set of features to produce a classification spectrum comprising a plurality of weight values, wherein each weight value references a degree of association of the input natural language text with a particular category of natural language texts; and associating the input natural language text with one or more categories using the classification spectrum.
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8. A non-transitory computer readable storage medium comprising executable instructions for causing a computing system to perform operations comprising: performing a first syntactic and semantic analysis of a training natural language text to produce a first plurality of language-independent semantic structures representing a plurality of sentences of the training natural language text; producing, based on the first plurality of language-independent semantic structures, a text classifier model; performing a second syntactic and semantic analysis of an input natural language text to produce a second plurality of language-independent semantic structures representing a plurality of sentences of the input natural language text; extracting, using the second plurality of language-independent semantic structures, a set of features, wherein at least one feature references a semantic class of a language-independent semantic hierarchy comprising a plurality of semantic classes, in which the semantic class exhibits one or more properties inherited from its parent semantic class; applying the text classifier model to the set of features to produce a classification spectrum comprising a plurality of weight values, wherein each weight value references a degree of association of the input natural language text with a particular category of natural language texts; and associating the input natural language text with one or more categories using the classification spectrum. 11. The non-transitory computer readable medium of claim 8 , wherein the second syntactic and semantic analysis further includes determining a syntactic feature of the input natural language text.
| 0.675 |
9. An apparatus for searching address book information, the apparatus comprising: A database for storing a search preference corresponding to a requesting client; and A server configured to: receive a search request message for searching for address book information using preference information of a requesting client form the requesting client; in response to receiving the search request message, obtaining address information of a plurality of external directories and the preference information representing at least one external directory preferred by the requesting client from an external server; check address information of at least one external directory form among the address information of the plurality of external directories based on the preference information and the address information; forward an external search request message to the at least one external directory using the address information of the at least one external directory; receive an external search response message including an external search result searched by the at least one external directory from the at least one external directory; prioritize the external search result and arranging the prioritized external search result; and forward a final search result including at least part of the arranged external search result to the requesting client, wherein the preference information further comprises information regarding application or non-application of a search preference to the search request of the address book information, information regarding application or non-application of the search preference to at least one external search domain corresponding to the at least one external directory, and information regarding application or non-application of the search preference for a dynamic search according to a user's location, and wherein the information regarding application or non-application of the search preference to the at least one external search domain comprises the at least one external search domain and a preference weight value per domain.
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9. An apparatus for searching address book information, the apparatus comprising: A database for storing a search preference corresponding to a requesting client; and A server configured to: receive a search request message for searching for address book information using preference information of a requesting client form the requesting client; in response to receiving the search request message, obtaining address information of a plurality of external directories and the preference information representing at least one external directory preferred by the requesting client from an external server; check address information of at least one external directory form among the address information of the plurality of external directories based on the preference information and the address information; forward an external search request message to the at least one external directory using the address information of the at least one external directory; receive an external search response message including an external search result searched by the at least one external directory from the at least one external directory; prioritize the external search result and arranging the prioritized external search result; and forward a final search result including at least part of the arranged external search result to the requesting client, wherein the preference information further comprises information regarding application or non-application of a search preference to the search request of the address book information, information regarding application or non-application of the search preference to at least one external search domain corresponding to the at least one external directory, and information regarding application or non-application of the search preference for a dynamic search according to a user's location, and wherein the information regarding application or non-application of the search preference to the at least one external search domain comprises the at least one external search domain and a preference weight value per domain. 21. The apparatus of claim 9 , wherein the database is further configured to update the preference information based on the external search result if a dynamic search preference of the search preference is set.
| 0.534194 |
13. The system of claim 12 , wherein a representation of a first subset of characteristics extracted from the plurality of other negotiable documents is stored in a public document validation profile associated with the account, wherein the public document validation profile is shared by the financial institution holding the account and at least one other financial institution, and wherein the comparison module is configured to compare the characteristics extracted from the image with characteristics in the first subset of characteristics extracted from the plurality of other negotiable documents to produce a comparison result.
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13. The system of claim 12 , wherein a representation of a first subset of characteristics extracted from the plurality of other negotiable documents is stored in a public document validation profile associated with the account, wherein the public document validation profile is shared by the financial institution holding the account and at least one other financial institution, and wherein the comparison module is configured to compare the characteristics extracted from the image with characteristics in the first subset of characteristics extracted from the plurality of other negotiable documents to produce a comparison result. 14. The system of claim 13 , wherein a representation of a second subset of characteristics extracted from the plurality of other negotiable documents is stored in a private document validation profile associated with the account, wherein the private document validation profile is available only to the financial institution holding the account.
| 0.826609 |
12. The method of claim 1 , wherein said message is to be sent with a given messaging service.
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12. The method of claim 1 , wherein said message is to be sent with a given messaging service. 16. The method of claim 12 , wherein said messaging service is a multi-media messaging service.
| 0.972109 |
1. A method of indexing documents, the method comprising: extracting, by a computer processor, feature information from each of a plurality of documents to be indexed; defining a plurality of indexes based on statistical properties of the extracted feature information, wherein the defining includes establishing, for each of the indexes, an upper limit on each of one or more parameters measuring a size of the index; for each of at least some of the documents: selecting one of the indexes as a destination index for the document based on the feature information extracted from the document, wherein the selecting includes: identifying a current index from among the plurality of indexes; determining, for each of the one or more parameters, whether adding the document to the current index will result in the index exceeding the upper limit on the parameter; and selecting the current index as the destination index for the document in the event that adding the document to the current index will not result in the index exceeding the upper limit on any of the one or more parameters; and adding a searchable representation of the document to the destination index; and storing the plurality of indexes in a computer-readable storage medium.
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1. A method of indexing documents, the method comprising: extracting, by a computer processor, feature information from each of a plurality of documents to be indexed; defining a plurality of indexes based on statistical properties of the extracted feature information, wherein the defining includes establishing, for each of the indexes, an upper limit on each of one or more parameters measuring a size of the index; for each of at least some of the documents: selecting one of the indexes as a destination index for the document based on the feature information extracted from the document, wherein the selecting includes: identifying a current index from among the plurality of indexes; determining, for each of the one or more parameters, whether adding the document to the current index will result in the index exceeding the upper limit on the parameter; and selecting the current index as the destination index for the document in the event that adding the document to the current index will not result in the index exceeding the upper limit on any of the one or more parameters; and adding a searchable representation of the document to the destination index; and storing the plurality of indexes in a computer-readable storage medium. 6. The method of claim 1 wherein the document is associated with a metadata item, wherein defining the indexes includes associating different ones of the indexes with different values of the metadata item, and wherein selecting one of the indexes as a destination index for the document is performed based in part on the metadata item.
| 0.529412 |
1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer.
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1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer. 7. A method according to claim 1 wherein said processing determines the acceleration of at least one point.
| 0.614286 |
18. The system of claim 13 wherein the decoration comprises a color through which the phrase is readable.
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18. The system of claim 13 wherein the decoration comprises a color through which the phrase is readable. 19. The system of claim 18 wherein said format element includes a color merge element wherein an area on the display screen defined by two overlapping expandable container images displays a color different from the colors unique to the two overlapping expandable container images.
| 0.946265 |
1. A method of deriving a motion vector predictor (MVP) for a motion vector (MV) of a current block in Inter, Merge, or Skip mode, wherein the MVP is selected from MVP candidates comprising one or more spatial MVP candidates associated with one or more neighboring blocks and one or more temporal MVP candidates associated with one or more co-located blocks, the method comprising: determining whether said one or more temporal MVP candidates are disabled according to a flag in a video bitstream, wherein the flag is utilized for selectively disabling use of said one or more temporal MVP candidates for motion vector prediction; deriving the MVP based on said one or more spatial MVP candidates responsive to the flag indicating that said one or more temporal MVP candidates are not to be utilized for motion vector prediction; deriving the MVP based on said one or more spatial MVP candidates and said one or more temporal MVP candidates responsive to the flag indicating that said one or more temporal MVP candidates are to be utilized for motion vector prediction; and providing the MVP for the current block.
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1. A method of deriving a motion vector predictor (MVP) for a motion vector (MV) of a current block in Inter, Merge, or Skip mode, wherein the MVP is selected from MVP candidates comprising one or more spatial MVP candidates associated with one or more neighboring blocks and one or more temporal MVP candidates associated with one or more co-located blocks, the method comprising: determining whether said one or more temporal MVP candidates are disabled according to a flag in a video bitstream, wherein the flag is utilized for selectively disabling use of said one or more temporal MVP candidates for motion vector prediction; deriving the MVP based on said one or more spatial MVP candidates responsive to the flag indicating that said one or more temporal MVP candidates are not to be utilized for motion vector prediction; deriving the MVP based on said one or more spatial MVP candidates and said one or more temporal MVP candidates responsive to the flag indicating that said one or more temporal MVP candidates are to be utilized for motion vector prediction; and providing the MVP for the current block. 6. The method of claim 1 , the flag is in a sequence level, wherein the flag is used to indicate that the temporal MVP candidates are not to be utilized for motion vector prediction for all reference pictures in an entire sequence.
| 0.561602 |
19. A computer program product comprising a non-transitory computer-readable medium having computer-executable code recorded thereon for causing a processor to perform operations of: creating one or more concept line items (CLIs) from at least one mathematical representation, wherein a CLI is an expression of a mathematical concept that is searchable in the computer program product; mapping defined interrelationships between the CLIs wherein each defined interrelationship is a prerequisite, a dependency, or a lack of relationship; assigning at least one unique identification code (IC) to each CLI to create CLI/IC pairs including mapped interrelationships; storing the CLI/IC pairs and their mapped interrelationships in at least one database; creating an index relating each of a plurality of documents with the CLI/IC pairs; and receiving a search request to retrieve documents having an indexed relationship with one or more CLIs, ICs, or CLI/IC pairs through a search interface, wherein the one or more CLIs, ICs, or CLI/IC pairs are derived from the search request, whether the CLIs, ICs, or CLI/IC pairs are expressly or implicitly included in the search request.
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19. A computer program product comprising a non-transitory computer-readable medium having computer-executable code recorded thereon for causing a processor to perform operations of: creating one or more concept line items (CLIs) from at least one mathematical representation, wherein a CLI is an expression of a mathematical concept that is searchable in the computer program product; mapping defined interrelationships between the CLIs wherein each defined interrelationship is a prerequisite, a dependency, or a lack of relationship; assigning at least one unique identification code (IC) to each CLI to create CLI/IC pairs including mapped interrelationships; storing the CLI/IC pairs and their mapped interrelationships in at least one database; creating an index relating each of a plurality of documents with the CLI/IC pairs; and receiving a search request to retrieve documents having an indexed relationship with one or more CLIs, ICs, or CLI/IC pairs through a search interface, wherein the one or more CLIs, ICs, or CLI/IC pairs are derived from the search request, whether the CLIs, ICs, or CLI/IC pairs are expressly or implicitly included in the search request. 25. The computer program product of claim 19 wherein each CLI is assigned an importance score, wherein said importance score for a given CLI is derived from any one of or any combination of weight, distance, edge weight, proximity, inclusion in a spine of an ontology, being a predictor of concept consolidation, or being a developer of procedural flexibility.
| 0.5 |
5. The method according to claim 1 , wherein said identifying further comprises, in case said checking for said candidate vector yields a negative result, checking if said computed distance between said at least sorted representation of said input vector and said candidate vector is smaller than said distance between said reference vector and said at least sorted representation of said input vector, and defining said reference vector to be said candidate vector if said computed distance between said at least sorted representation of said input vector and said candidate vector is smaller than said distance between said reference vector and said at least sorted representation of said input vector.
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5. The method according to claim 1 , wherein said identifying further comprises, in case said checking for said candidate vector yields a negative result, checking if said computed distance between said at least sorted representation of said input vector and said candidate vector is smaller than said distance between said reference vector and said at least sorted representation of said input vector, and defining said reference vector to be said candidate vector if said computed distance between said at least sorted representation of said input vector and said candidate vector is smaller than said distance between said reference vector and said at least sorted representation of said input vector. 7. The method according to claim 5 , wherein said distance between said reference vector and said at least sorted representation of said input vector corresponds to a distance between a previously checked candidate vector of said plurality of candidate vectors and said at least sorted representation of said input vector computed for said previously checked candidate vector, and is retrieved from a memory where it has been at least temporarily stored.
| 0.823266 |
1. A method comprising: obtaining, by a computer system including one or more computers, a first set of test values, a second set of test values, and a third set of test values; receiving, by the computer system, text comprising characters represented as code point values, the characters identified as being in a first encoding format, each code point value representing one character in the text; and making a determination by the computer system that the text likely includes characters incorrectly converted from a second encoding format to the first encoding format, wherein making the determination includes (i) determining for a sequence of code point values consisting of a first code point value followed by a second code point value that the first code point value is in the first set of test values and that the second code point value is in the second set of test values, or (ii) determining for a sequence of code point values consisting of a first code point value followed by a second code point value followed by a third code point value that the first code point value is in the third set of test values, that the second code point value is in the second set of test values, and that the third code point value is in the second set of test values.
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1. A method comprising: obtaining, by a computer system including one or more computers, a first set of test values, a second set of test values, and a third set of test values; receiving, by the computer system, text comprising characters represented as code point values, the characters identified as being in a first encoding format, each code point value representing one character in the text; and making a determination by the computer system that the text likely includes characters incorrectly converted from a second encoding format to the first encoding format, wherein making the determination includes (i) determining for a sequence of code point values consisting of a first code point value followed by a second code point value that the first code point value is in the first set of test values and that the second code point value is in the second set of test values, or (ii) determining for a sequence of code point values consisting of a first code point value followed by a second code point value followed by a third code point value that the first code point value is in the third set of test values, that the second code point value is in the second set of test values, and that the third code point value is in the second set of test values. 8. The method of claim 1 , wherein the third set of test values matches a bit mask having a format 1110 xxxx, and includes hexadecimal values in Win-1252 encoding format, wherein a first half-byte of the bit mask is always E and one of hexadecimal values 0-F matches a second half-byte of the bit mask.
| 0.543351 |
14. The computer readable medium of claim 13 , wherein the predetermined node template outputs node to the screen file when node is found by the parsing, calls a predetermined PointTexture template when PointTexture is found by the parsing, and calls a predetermined OctreeImage template when Octreeimage is found by the parsing.
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14. The computer readable medium of claim 13 , wherein the predetermined node template outputs node to the screen file when node is found by the parsing, calls a predetermined PointTexture template when PointTexture is found by the parsing, and calls a predetermined OctreeImage template when Octreeimage is found by the parsing. 20. The computer readable medium of claim 14 , wherein the predetermined OctreeImage template outputs ‘OctreeImage {’ to the scene file when OctreeImage is found by the parsing, outputs octreeResolution, octree[ ], and voxelImageIndex[ ], and values thereof to the scene file when octreeResolution, octree, and voxelImageIndex are found by the parsing, outputs images[ ]to the scene file when images are found by the parsing and calls a predetermined images template, and output } to the scene file.
| 0.798357 |
25. Apparatus comprising: a) at least one processor; b) an input for accepting ad scores wherein each of the ad scores indicates a value of a user selection of an ad; and c) at least one storage device storing a computer executable code which, when executed by the at least one processor, performs a method of 1)scoring a document using ad scores of the ads when the ads are served with the document and ad scores of the ads when the ads are served across a collection of documents to generate a document score, 2) accepting a cost for an action with respect to an ad when the ad is served with the document, and 3) adjusting the cost using the document score to generate a modified cost.
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25. Apparatus comprising: a) at least one processor; b) an input for accepting ad scores wherein each of the ad scores indicates a value of a user selection of an ad; and c) at least one storage device storing a computer executable code which, when executed by the at least one processor, performs a method of 1)scoring a document using ad scores of the ads when the ads are served with the document and ad scores of the ads when the ads are served across a collection of documents to generate a document score, 2) accepting a cost for an action with respect to an ad when the ad is served with the document, and 3) adjusting the cost using the document score to generate a modified cost. 26. The apparatus of claim 25 wherein each of the ad scores indicates a conversion rate of an ad.
| 0.804781 |
11. A training method comprising: receiving electrocardiogram (ECG) training data; augmenting the ECG data; and filtering the ECG signal using a band pass filter; training a neural network model for ECG authentication based on the augmented ECG training data; training candidate neural network models for the augmented ECG training data; selecting a candidate neural network model from the candidate neural network models by minimizing a cross-entropy based on an uppermost layer of the candidate neural network model, wherein the augmenting comprises detecting a fiducial point from the ECG data after filtering and acquiring a data segment from the filtered ECG signal based on the fiducial point.
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11. A training method comprising: receiving electrocardiogram (ECG) training data; augmenting the ECG data; and filtering the ECG signal using a band pass filter; training a neural network model for ECG authentication based on the augmented ECG training data; training candidate neural network models for the augmented ECG training data; selecting a candidate neural network model from the candidate neural network models by minimizing a cross-entropy based on an uppermost layer of the candidate neural network model, wherein the augmenting comprises detecting a fiducial point from the ECG data after filtering and acquiring a data segment from the filtered ECG signal based on the fiducial point. 16. The training method of claim 11 , wherein the training of the neural network model comprises: training candidate neural network models for each item of the augmented ECG training data; and selecting a candidate neural network model from the candidate neural network models based on an accuracy of a candidate semantic feature extracted using each of the candidate neural network models.
| 0.673507 |
17. A non-transitory computer readable storage medium storing an electronic document that is to be processed by a computing system, the electronic document comprising: textual content that is set to be displayed by the computing system according to a hierarchy that contains a plurality of nodes, each one of the plurality of nodes having at least one of a plurality of visualization forms, the plurality of visualization forms including at least an open form, a tokenized form, and an invisible form, the plurality of nodes including a first node associated with a first portion of the textual content and a second node that is associated with a second different portion of the textual content and is also a child of the first node, the second node being a leaf node of the hierarchy, each one of the plurality of nodes having a value that is set to indicate the at least one of the plurality of visualization forms, wherein the textual content of each one of the plurality of nodes is set to be displayed according to the value that indicates the visualization form, wherein the value of each one of the plurality of nodes is set to be modified by a user, wherein the textual content of the second node is not displayed by the computing system when the visualization form for the second node includes the invisible form, wherein less than a full amount of the textual content associated with the second node is displayed by the computing system when the visualization form for the second node includes the tokenized form, and wherein the textual content associated with the second node is displayed by the computing system when the visualization form for the second node includes the open form.
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17. A non-transitory computer readable storage medium storing an electronic document that is to be processed by a computing system, the electronic document comprising: textual content that is set to be displayed by the computing system according to a hierarchy that contains a plurality of nodes, each one of the plurality of nodes having at least one of a plurality of visualization forms, the plurality of visualization forms including at least an open form, a tokenized form, and an invisible form, the plurality of nodes including a first node associated with a first portion of the textual content and a second node that is associated with a second different portion of the textual content and is also a child of the first node, the second node being a leaf node of the hierarchy, each one of the plurality of nodes having a value that is set to indicate the at least one of the plurality of visualization forms, wherein the textual content of each one of the plurality of nodes is set to be displayed according to the value that indicates the visualization form, wherein the value of each one of the plurality of nodes is set to be modified by a user, wherein the textual content of the second node is not displayed by the computing system when the visualization form for the second node includes the invisible form, wherein less than a full amount of the textual content associated with the second node is displayed by the computing system when the visualization form for the second node includes the tokenized form, and wherein the textual content associated with the second node is displayed by the computing system when the visualization form for the second node includes the open form. 19. The medium of claim 17 , wherein the electronic document is set to be displayed on a standard computer interface.
| 0.512805 |
1. A system for providing reference documents as a suggestion for classifying electronically stored information using nearest neighbor, comprising: a clustering module to provide a set of uncoded electronically stored information items and a different set of reference electronically stored information items that are each classified with a code; a similarity module to compare at least one of the uncoded electronically stored information items from the set with the set of reference electronically stored information items and to identify one or more of the reference electronically stored information items that are similar to the at least one uncoded electronically stored information item; a processing module to process the classification codes associated with the similar reference electronically stored information items, comprising: a type module to determine a number of different types of the classification codes associated with the similar reference electronically stored information items; a presence module to determine one or more of a presence and absence of the similar reference electronically stored information items with each type of the different classification codes; and a quantity module to determine for each type of the classification codes a quantity of the similar reference electronically stored information items; a suggestion module to display a visual classification suggestion based on at least one of the presence and the absence and the quantity and the number of the types via a display of the at least one uncoded electronically stored information item and the similar reference electronically stored information items; a receipt module to receive a classification code of one of the types for the at least one uncoded electronically stored information item from a human reviewer based on the suggestion; and a processor to execute the modules.
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1. A system for providing reference documents as a suggestion for classifying electronically stored information using nearest neighbor, comprising: a clustering module to provide a set of uncoded electronically stored information items and a different set of reference electronically stored information items that are each classified with a code; a similarity module to compare at least one of the uncoded electronically stored information items from the set with the set of reference electronically stored information items and to identify one or more of the reference electronically stored information items that are similar to the at least one uncoded electronically stored information item; a processing module to process the classification codes associated with the similar reference electronically stored information items, comprising: a type module to determine a number of different types of the classification codes associated with the similar reference electronically stored information items; a presence module to determine one or more of a presence and absence of the similar reference electronically stored information items with each type of the different classification codes; and a quantity module to determine for each type of the classification codes a quantity of the similar reference electronically stored information items; a suggestion module to display a visual classification suggestion based on at least one of the presence and the absence and the quantity and the number of the types via a display of the at least one uncoded electronically stored information item and the similar reference electronically stored information items; a receipt module to receive a classification code of one of the types for the at least one uncoded electronically stored information item from a human reviewer based on the suggestion; and a processor to execute the modules. 2. A system according to claim 1 , further comprising: a reference set module to generate the set of reference electronically stored information items, comprising at least one of: a comparison module to obtain a set of electronically stored information items, to identify one or more electronically stored information items that are dissimilar from each other electronically stored information item, and to assign a classification code to each of the dissimilar electronically stored information items, as the reference electronically stored information items; and a reference clustering module to group electronically stored information items for a document review project into one or more clusters, to select one or more of the electronically stored information items in at least one cluster, and to assign a classification code to each of the selected electronically stored information items, as the reference electronically stored information items.
| 0.5 |
4. The computer method of claim 3 , further comprising: searching a repository for the at least one image; fetching the at least one image from the repository; and presenting the at least one image to the author user.
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4. The computer method of claim 3 , further comprising: searching a repository for the at least one image; fetching the at least one image from the repository; and presenting the at least one image to the author user. 6. The computer method of claim 4 , wherein the images are fetched only from a trusted source.
| 0.963027 |
39. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving information characterizing explicit relationships between a first member, a second member, and a third member in a member network; receiving a first search query submitted by the first member; responding to the first search query with a) first links to a collection of articles in a result set responsive to the first search query, and b) one or more second links for receiving input characterizing the first member's ratings of local product or service providers identified in the result set responsive to the first search query; receiving the first member's selection of one of the second links; storing the information characterizing the first member's rating of a first local product or service provider that corresponds with the selected one of the second links; receiving a third search query submitted by the third member; responding to the third search query with a) third links to a collection of articles in a result set responsive to the third search query, and b) one or more fourth links for receiving input characterizing the third member's ratings of local product or service providers identified in the result set responsive to the third search query; receiving the third member's selection of one of the fourth links; storing the information characterizing the third member's rating of a second local product or service provider that corresponds with the selected one of the fourth links; receiving a local search query submitted by the second member, wherein the local search query comprises information identifying one or more items to be found and a geographic locale to be searched; determining a result set responsive to the local search query; ranking items in the result set using a degree of the relationship between the first member and the second member and on a degree of the relationship between the third member and the second member; and based on the relationship between the first member and the second member and on the relationship between the third member and the second member, providing the second member with information describing the result set, the identity of the first member, the availability of the information characterizing the first member's rating, the identity of the third member, and the availability of the information characterizing the third member's rating.
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39. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving information characterizing explicit relationships between a first member, a second member, and a third member in a member network; receiving a first search query submitted by the first member; responding to the first search query with a) first links to a collection of articles in a result set responsive to the first search query, and b) one or more second links for receiving input characterizing the first member's ratings of local product or service providers identified in the result set responsive to the first search query; receiving the first member's selection of one of the second links; storing the information characterizing the first member's rating of a first local product or service provider that corresponds with the selected one of the second links; receiving a third search query submitted by the third member; responding to the third search query with a) third links to a collection of articles in a result set responsive to the third search query, and b) one or more fourth links for receiving input characterizing the third member's ratings of local product or service providers identified in the result set responsive to the third search query; receiving the third member's selection of one of the fourth links; storing the information characterizing the third member's rating of a second local product or service provider that corresponds with the selected one of the fourth links; receiving a local search query submitted by the second member, wherein the local search query comprises information identifying one or more items to be found and a geographic locale to be searched; determining a result set responsive to the local search query; ranking items in the result set using a degree of the relationship between the first member and the second member and on a degree of the relationship between the third member and the second member; and based on the relationship between the first member and the second member and on the relationship between the third member and the second member, providing the second member with information describing the result set, the identity of the first member, the availability of the information characterizing the first member's rating, the identity of the third member, and the availability of the information characterizing the third member's rating. 42. The computer storage medium of claim 39 , the operations comprising determining at least one of the degrees of the relationships using the information characterizing the explicit relationships.
| 0.629056 |
1. An apparatus for associating and aggregating attributes in a token-based environment, comprising: a memory operable to store a plurality of tokens indicating a device has been identified and is capable of consuming a resource; and a processor operable to: receive a subject token indicating an attempt to authenticate a user that is attempting to access a resource, the subject token representing at least one attribute associated with the user; determine at least one token-based rule based at least in part upon a token in the plurality of tokens and the subject token, the at least one token-based rule indicating a plurality of attributes required to access the resource; determine, from the at least one token-based rule, the plurality of attributes required to access the resource; determine a second plurality of attributes represented by the plurality of tokens and the subject token; determine at least one missing attribute, the at least one missing attribute in the plurality of attributes but not in the second plurality of attributes; request the at least one missing attribute; and receive, in response to the request for the at least one missing attribute, a first token representing the at least one missing attribute.
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1. An apparatus for associating and aggregating attributes in a token-based environment, comprising: a memory operable to store a plurality of tokens indicating a device has been identified and is capable of consuming a resource; and a processor operable to: receive a subject token indicating an attempt to authenticate a user that is attempting to access a resource, the subject token representing at least one attribute associated with the user; determine at least one token-based rule based at least in part upon a token in the plurality of tokens and the subject token, the at least one token-based rule indicating a plurality of attributes required to access the resource; determine, from the at least one token-based rule, the plurality of attributes required to access the resource; determine a second plurality of attributes represented by the plurality of tokens and the subject token; determine at least one missing attribute, the at least one missing attribute in the plurality of attributes but not in the second plurality of attributes; request the at least one missing attribute; and receive, in response to the request for the at least one missing attribute, a first token representing the at least one missing attribute. 6. The apparatus of claim 1 , the plurality of tokens indicating that a container to facilitate access to the resource has been provisioned to the device.
| 0.742547 |
1. A prosody generation apparatus that receives phonological information and linguistic information so as to generate prosody, the prosody generation apparatus being operable to refer to (a) a representative prosodic pattern storage unit for accumulating beforehand representative prosodic patterns of portions of speech data, the portions including prosody changing points; (b) a selection rule storage unit that stores a selection rule predetermined according to attributes concerning phonology or attributes concerning linguistic information of the portions of the speech data including the prosody changing points; and (c) a transformation rule storage unit that stores a transformation rule predetermined according to attributes concerning the phonology or the linguistic information of the portions of the speech data including the prosody changing points; the prosody generation apparatus comprising a computer processing unit and a memory storing a program that are configured to implement: a prosody changing point setting unit that sets a prosody changing point according to at least any one of the received phonological information and the linguistic information; a pattern selection unit that selects a representative prosodic pattern from the representative prosodic pattern storage unit according to the selection rule, based on the received phonological information and the linguistic information; and a prosody generation unit that transforms the representative prosodic pattern selected by the pattern selection unit according to the transformation rule and interpolates the transformed prosodic pattern for a portion between the prosodic patterns corresponding to the prosody changing points, wherein assuming that a difference in pitch between adjacent moras or adjacent syllables of the speech data is ΔP, the prosody changing point is a point where the ΔP and an immediately following ΔP are different in sign.
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1. A prosody generation apparatus that receives phonological information and linguistic information so as to generate prosody, the prosody generation apparatus being operable to refer to (a) a representative prosodic pattern storage unit for accumulating beforehand representative prosodic patterns of portions of speech data, the portions including prosody changing points; (b) a selection rule storage unit that stores a selection rule predetermined according to attributes concerning phonology or attributes concerning linguistic information of the portions of the speech data including the prosody changing points; and (c) a transformation rule storage unit that stores a transformation rule predetermined according to attributes concerning the phonology or the linguistic information of the portions of the speech data including the prosody changing points; the prosody generation apparatus comprising a computer processing unit and a memory storing a program that are configured to implement: a prosody changing point setting unit that sets a prosody changing point according to at least any one of the received phonological information and the linguistic information; a pattern selection unit that selects a representative prosodic pattern from the representative prosodic pattern storage unit according to the selection rule, based on the received phonological information and the linguistic information; and a prosody generation unit that transforms the representative prosodic pattern selected by the pattern selection unit according to the transformation rule and interpolates the transformed prosodic pattern for a portion between the prosodic patterns corresponding to the prosody changing points, wherein assuming that a difference in pitch between adjacent moras or adjacent syllables of the speech data is ΔP, the prosody changing point is a point where the ΔP and an immediately following ΔP are different in sign. 17. The prosody generation apparatus according to claim 1 , wherein the transformation is compression or extension in a dynamic range on an amplitude axis of a power pattern.
| 0.692498 |
7. A computer implemented method of forensic data analysis, the method comprising: extracting, with a data extraction module, unknown raw data from a plurality of raw data sources; providing the extracted unknown raw data to an interpreter module; receiving, at the interpreter module, the extracted unknown raw data from the data extraction module; storing a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms; accessing, at the interpreter module, one or more of the search packs each having associated suspect data features; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying, using the interpreter module, suspect data from among the extracted raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and generating, using the interpreter module, a report indicating any matches between the extracted data and any similar suspect data features.
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7. A computer implemented method of forensic data analysis, the method comprising: extracting, with a data extraction module, unknown raw data from a plurality of raw data sources; providing the extracted unknown raw data to an interpreter module; receiving, at the interpreter module, the extracted unknown raw data from the data extraction module; storing a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms; accessing, at the interpreter module, one or more of the search packs each having associated suspect data features; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying, using the interpreter module, suspect data from among the extracted raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and generating, using the interpreter module, a report indicating any matches between the extracted data and any similar suspect data features. 9. The method of claim 7 , wherein each search pack further includes a header, one or more SML scripts, and data features.
| 0.624471 |
41. A system for communicating visual images to a handicapped person, said system comprising: at least one device for physically transmitting information about said visual images to said handicapped person; and said at least one device including means for delivering a physical signal representative of a key word associated with said visual images to a first part of a body of said handicapped person, wherein said at least one device further comprises means for delivering at least one physical input describing a dynamic element associated with said key word to a palm of said handicapped person; and wherein Dividing the fingers of a hand of said handicapped person into a first group consisting of a pointer finger and a middle finger and into a second group consisting of a ring finger and a pinky and said transmitting step comprises transmitting information about a bad character to one of said fingers of said first group and transmitting information about a good character to one of said fingers of said second group.
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41. A system for communicating visual images to a handicapped person, said system comprising: at least one device for physically transmitting information about said visual images to said handicapped person; and said at least one device including means for delivering a physical signal representative of a key word associated with said visual images to a first part of a body of said handicapped person, wherein said at least one device further comprises means for delivering at least one physical input describing a dynamic element associated with said key word to a palm of said handicapped person; and wherein Dividing the fingers of a hand of said handicapped person into a first group consisting of a pointer finger and a middle finger and into a second group consisting of a ring finger and a pinky and said transmitting step comprises transmitting information about a bad character to one of said fingers of said first group and transmitting information about a good character to one of said fingers of said second group. 45. A system according to claim 41 , wherein said delivering means comprises means for delivering said key word to a body part in Morse code form.
| 0.666984 |
1. A method comprising: by one or more computer systems, accessing a social graph of a social-networking system, the social graph comprising: user nodes that are each associated with a respective user of the social-networking system; concept nodes that each correspond to a respective device; and a plurality of ownership edges connecting the user nodes and the concept nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular concept node; by the one or more computer systems, determining from the social graph a device of a user of the social-networking system; by the one or more computer systems, determining, from the social graph, media content that a friend or a connection of the user in the social graph is currently viewing; and by the one or more computer systems, providing the media content that the friend or the connection of the user is currently viewing for display on the device of the user.
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1. A method comprising: by one or more computer systems, accessing a social graph of a social-networking system, the social graph comprising: user nodes that are each associated with a respective user of the social-networking system; concept nodes that each correspond to a respective device; and a plurality of ownership edges connecting the user nodes and the concept nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular concept node; by the one or more computer systems, determining from the social graph a device of a user of the social-networking system; by the one or more computer systems, determining, from the social graph, media content that a friend or a connection of the user in the social graph is currently viewing; and by the one or more computer systems, providing the media content that the friend or the connection of the user is currently viewing for display on the device of the user. 3. The method of claim 1 , further comprising: by the one or more computer systems, determining a first and a second device used or owned by the user of the social-networking system; and by the one or more computer systems, updating the social graph to include a first node corresponding to the first device and a second node corresponding to the second device; wherein determining from the social graph the device of the user comprises selecting, from the first and second devices, an optimal device for displaying the media content.
| 0.5 |
6. A system for interactively viewing raster images using scalable vector graphics (SVG), comprising: a receiver for (i) receiving an SVG document from a server computer, the SVG document including a reference to a raster image within the SVG document, the reference indicating a rectangular portion, a display width and height, and an IP address for a server computer, (ii) receiving a modified SVG document from the server computer, modified according to a different portion, and (iii) receiving a portion of raster image data from the server computer; a transmitter for (i) requesting from the server computer a first portion of raster image data corresponding to the rectangular portion, display width and display height, the first portion of raster image data being derived from the raster image, and (ii) requesting a different portion of the raster image data; and an SVG renderer operatively coupled with said receiver and said transmitter for rendering an SVG document, comprising a raster image processor for displaying a portion of raster image data.
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6. A system for interactively viewing raster images using scalable vector graphics (SVG), comprising: a receiver for (i) receiving an SVG document from a server computer, the SVG document including a reference to a raster image within the SVG document, the reference indicating a rectangular portion, a display width and height, and an IP address for a server computer, (ii) receiving a modified SVG document from the server computer, modified according to a different portion, and (iii) receiving a portion of raster image data from the server computer; a transmitter for (i) requesting from the server computer a first portion of raster image data corresponding to the rectangular portion, display width and display height, the first portion of raster image data being derived from the raster image, and (ii) requesting a different portion of the raster image data; and an SVG renderer operatively coupled with said receiver and said transmitter for rendering an SVG document, comprising a raster image processor for displaying a portion of raster image data. 9. The system of claim 6 wherein the modified SVG document has a modified display width within the reference to the raster image.
| 0.516129 |
5. A camera system comprising: (a) a camera that is operable to take and store pictures, and that includes: (i) a lens, (ii) an image sensor, (iii) at least one microphone, (iv) a voice recognizer, (v) a camera controller, (vi) a wireless network interface, and (vii) a touch sensitive display; (b) the camera controller including a control program having instructions to control and respond to the voice recognizer; (c) the voice recognizer coupled to the microphone and the camera controller, and configured to receive and process sounds into recognized words; (d) the camera further configured to maintain and store a plurality of recognizable words having different plain meanings and commonly associated with taking a picture, the recognition of any of which will cause the camera to take a picture; (e) wherein the voice recognizer is operable to receive a first and a second human sound spoken by the same person, and to recognize: (i) the first human sound as a first human spoken word from among the plurality, the recognized first human spoken word being assigned by the control program to be a command for the camera to take a picture, and (ii) the second human sound as a second human spoken word from among the plurality, the recognized second human spoken word being different from the first human spoken word and also assigned by the control program to be the same camera command to take a picture; (f) the camera controller configured to: (i) cause the camera to take a picture in response to the voice recognizer recognizing either the first or second human spoken word and to store the picture in a local memory in the camera; and (ii) automatically upload the picture stored in the local memory of the camera via the wireless network interface and an internet connection to a location at an internet picture hosting website as instructed by a user of the camera, but only if predetermined conditions are met, the predetermined conditions including at least the camera controller receiving: (1) an indication from the wireless network interface that the system can make an internet connection via the wireless network interface; and (2) an indication from the local memory that a user has elected an option to designate at least one picture stored in local memory to be uploaded to the internet picture hosting website.
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5. A camera system comprising: (a) a camera that is operable to take and store pictures, and that includes: (i) a lens, (ii) an image sensor, (iii) at least one microphone, (iv) a voice recognizer, (v) a camera controller, (vi) a wireless network interface, and (vii) a touch sensitive display; (b) the camera controller including a control program having instructions to control and respond to the voice recognizer; (c) the voice recognizer coupled to the microphone and the camera controller, and configured to receive and process sounds into recognized words; (d) the camera further configured to maintain and store a plurality of recognizable words having different plain meanings and commonly associated with taking a picture, the recognition of any of which will cause the camera to take a picture; (e) wherein the voice recognizer is operable to receive a first and a second human sound spoken by the same person, and to recognize: (i) the first human sound as a first human spoken word from among the plurality, the recognized first human spoken word being assigned by the control program to be a command for the camera to take a picture, and (ii) the second human sound as a second human spoken word from among the plurality, the recognized second human spoken word being different from the first human spoken word and also assigned by the control program to be the same camera command to take a picture; (f) the camera controller configured to: (i) cause the camera to take a picture in response to the voice recognizer recognizing either the first or second human spoken word and to store the picture in a local memory in the camera; and (ii) automatically upload the picture stored in the local memory of the camera via the wireless network interface and an internet connection to a location at an internet picture hosting website as instructed by a user of the camera, but only if predetermined conditions are met, the predetermined conditions including at least the camera controller receiving: (1) an indication from the wireless network interface that the system can make an internet connection via the wireless network interface; and (2) an indication from the local memory that a user has elected an option to designate at least one picture stored in local memory to be uploaded to the internet picture hosting website. 14. The camera system of claim 5 wherein one of the words is “shoot.”
| 0.534751 |
16. The method of claim 15 , wherein identifying the importance level of the plurality of moments further comprises: identifying, by the at least one computing device, non-dialog spoken content in the closed captioning data; identifying, by the at least one computing device, a moment from the plurality of moments corresponding to the non-dialog spoken content; and determining, by the at least one computing device, the importance level of the moment based at least in part upon an analysis of the non-dialog spoken content.
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16. The method of claim 15 , wherein identifying the importance level of the plurality of moments further comprises: identifying, by the at least one computing device, non-dialog spoken content in the closed captioning data; identifying, by the at least one computing device, a moment from the plurality of moments corresponding to the non-dialog spoken content; and determining, by the at least one computing device, the importance level of the moment based at least in part upon an analysis of the non-dialog spoken content. 17. The method of claim 16 , wherein the non-dialog spoken content corresponds to narration.
| 0.83871 |
1. A computer-implemented method comprising: obtaining, by one or more configured computing systems of a group discussion prediction service, information about a distributed group discussion involving a plurality of users, wherein the obtained information includes first information about a plurality of content items already submitted by the plurality of users during one or more time periods and includes second information about one or more predictions by the group discussion prediction service regarding future content items that will be submitted by users for the distributed group discussion during one or more future time periods; selecting, by the one or more configured computing systems, multiple factors to use in summarizing the obtained information for each of multiple time periods that include the one or more time periods and the one or more future time periods, wherein the multiple selected factors include a total quantity of content items supplied during each of the multiple time periods and include a rate of change in total quantity of content items supplied between two or more of the multiple time periods; determining, by the one or more configured computing systems, multiple visual aspects to use to display information about the multiple selected factors to one or more users, wherein each of the multiple selected factors is associated with one of the multiple visual aspects, and wherein the multiple visual aspects include sizes of displayed items, vertical locations or movements of displayed items, halos or shadows associated with displayed items, and colors of displayed item; generating, by the one or more configured computing systems, information for display that is based on at least some of the first information and on at least some of the second information, the generated information including, for each of the multiple selected factors, a summarization that is represented using the associated one visual aspect for the selected factor and that is based on a subset of the obtained information that corresponds to the selected factor; and initiating, by the one or more configured computing systems and before the one or more future time periods, display of the generated information to the one or more users.
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1. A computer-implemented method comprising: obtaining, by one or more configured computing systems of a group discussion prediction service, information about a distributed group discussion involving a plurality of users, wherein the obtained information includes first information about a plurality of content items already submitted by the plurality of users during one or more time periods and includes second information about one or more predictions by the group discussion prediction service regarding future content items that will be submitted by users for the distributed group discussion during one or more future time periods; selecting, by the one or more configured computing systems, multiple factors to use in summarizing the obtained information for each of multiple time periods that include the one or more time periods and the one or more future time periods, wherein the multiple selected factors include a total quantity of content items supplied during each of the multiple time periods and include a rate of change in total quantity of content items supplied between two or more of the multiple time periods; determining, by the one or more configured computing systems, multiple visual aspects to use to display information about the multiple selected factors to one or more users, wherein each of the multiple selected factors is associated with one of the multiple visual aspects, and wherein the multiple visual aspects include sizes of displayed items, vertical locations or movements of displayed items, halos or shadows associated with displayed items, and colors of displayed item; generating, by the one or more configured computing systems, information for display that is based on at least some of the first information and on at least some of the second information, the generated information including, for each of the multiple selected factors, a summarization that is represented using the associated one visual aspect for the selected factor and that is based on a subset of the obtained information that corresponds to the selected factor; and initiating, by the one or more configured computing systems and before the one or more future time periods, display of the generated information to the one or more users. 4. The method of claim 1 wherein the plurality of content items includes textual user comments supplied by the plurality of users related to multiple topics within a category, and wherein the multiple selected factors include, for each of the multiple topics, a total quantity of content items during each of the multiple time periods that are associated with the topic, a rate of change in total quantity of content items supplied between two or more of the multiple time periods that are associated with the topic, and an aggregate sentiment of content items during at least one of the multiple time periods for the topic.
| 0.5 |
20. A computer-implemented method for categorizing, on behalf of a user, items of interest in an item category maintained by a network-based service, the method comprising: under control of one or more configured computer systems: comparing a mathematical description of item information related to an item of interest to the user to a mathematical description of at least one description for an item category, wherein the item category is maintained by the network-based service and is associated with a plurality of items, and wherein the item of interest is an item offered for sale using a network-based service; automatically determining at least one category recommendation for the item of interest based upon a similarity between the mathematical descriptions of the item information and at least one item category description; and enabling selection of an item category from the at least one category recommendation for assignment to the item of interest.
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20. A computer-implemented method for categorizing, on behalf of a user, items of interest in an item category maintained by a network-based service, the method comprising: under control of one or more configured computer systems: comparing a mathematical description of item information related to an item of interest to the user to a mathematical description of at least one description for an item category, wherein the item category is maintained by the network-based service and is associated with a plurality of items, and wherein the item of interest is an item offered for sale using a network-based service; automatically determining at least one category recommendation for the item of interest based upon a similarity between the mathematical descriptions of the item information and at least one item category description; and enabling selection of an item category from the at least one category recommendation for assignment to the item of interest. 31. The computer-implemented method of claim 20 , wherein the at least one category recommendation comprises a null value.
| 0.704823 |
2. The computer-implemented method of claim 1 , wherein processing the query further comprises identifying a first action performed by the user in relation to the query.
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2. The computer-implemented method of claim 1 , wherein processing the query further comprises identifying a first action performed by the user in relation to the query. 3. The computer-implemented method of claim 2 , wherein processing the query further comprises identifying one or more subsequent actions performed by the user in relation to the query, after the first action.
| 0.924785 |
1. A computerized method for personalizing a chat bot, comprising the steps: loading a query sentence and a response sentence; applying a set of reduction rules to said query sentence to get a canonicalized query sentence; matching said canonicalized query sentence against a set of patterns to get a matching pattern; combining said matching pattern with said response sentence into a pair; and adding said pair into said chat bot; wherein said query sentence for said chat bot is from a first user, and said response sentence is from a second user who is simulating a particular personality.
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1. A computerized method for personalizing a chat bot, comprising the steps: loading a query sentence and a response sentence; applying a set of reduction rules to said query sentence to get a canonicalized query sentence; matching said canonicalized query sentence against a set of patterns to get a matching pattern; combining said matching pattern with said response sentence into a pair; and adding said pair into said chat bot; wherein said query sentence for said chat bot is from a first user, and said response sentence is from a second user who is simulating a particular personality. 4. The method of claim 1 , further comprising serving context-sensitive ads in real time.
| 0.859813 |
6. A computer-implemented method comprising: determining, by an anti-spam module, an approximate display location of one or more embedded images within an electronic mail (email) message; identifying, by the anti-spam module, existence of one or more abnormal factors associated with the one or more embedded images; quantifying, by the anti-spam module, a number of text strings that are included in the embedded image by analyzing one or more blocks of the binarized representation with a text string measurement algorithm; classifying, by the anti-spam module, the email message as spam or clean based on the approximate display location, the existence of one or more abnormal factors and the number of text strings; wherein the anti-spam module is implemented in one or more processors and one or more non-transitory computer-readable storage media of one or more computer systems, the one or more non-transitory computer-readable storage media having instructions tangibly embodied therein representing the anti-spam module that are executable by the one or more processors; and wherein the one or more blocks comprise M×N virtual blocks and wherein the text string measurement algorithm employs equations having a general form as follows: T = ∑ m = 0 M ∑ n = 0 N T m , n subject to : T m , n = ∑ y t = y 0 m y max m ∑ y b = y t + 1 y max m T y t , y b m , n y 0 m = y max ∂ 0 ( m - 1 ) , y max m = y 0 m + ∂ 0 T y t , y b m , n = { 1 ∂ 1 > ∑ i = y t y b CB i n > ∂ 2 ∑ k = x 0 n x max n B k , y b + 1 < ∂ 3 , x 0 n = x max ∂ 0 ( n - 1 ) , x max n = x 0 n + ∂ 0 0 Otherwise CB i n = { 1 ∂ 4 > ∑ k = x 0 n x max n B k , i > ∂ 5 Max ( ∑ k = x w x w + ∂ 6 B k , i ) < ∂ 7 , x 0 n ≤ x w ≤ x max n 0 Otherwise where, ∂ 0 . . . ∂ 7 are adjustable parameters; T is the number of text strings; T y t ,y b m,n is a likelihood that a row between y t and y b in virtual block [m,n] represents text; CB i n is a likelihood that a line[i] is a part of text; and B k,i is a value of pixel[k,i] in the binary representation.
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6. A computer-implemented method comprising: determining, by an anti-spam module, an approximate display location of one or more embedded images within an electronic mail (email) message; identifying, by the anti-spam module, existence of one or more abnormal factors associated with the one or more embedded images; quantifying, by the anti-spam module, a number of text strings that are included in the embedded image by analyzing one or more blocks of the binarized representation with a text string measurement algorithm; classifying, by the anti-spam module, the email message as spam or clean based on the approximate display location, the existence of one or more abnormal factors and the number of text strings; wherein the anti-spam module is implemented in one or more processors and one or more non-transitory computer-readable storage media of one or more computer systems, the one or more non-transitory computer-readable storage media having instructions tangibly embodied therein representing the anti-spam module that are executable by the one or more processors; and wherein the one or more blocks comprise M×N virtual blocks and wherein the text string measurement algorithm employs equations having a general form as follows: T = ∑ m = 0 M ∑ n = 0 N T m , n subject to : T m , n = ∑ y t = y 0 m y max m ∑ y b = y t + 1 y max m T y t , y b m , n y 0 m = y max ∂ 0 ( m - 1 ) , y max m = y 0 m + ∂ 0 T y t , y b m , n = { 1 ∂ 1 > ∑ i = y t y b CB i n > ∂ 2 ∑ k = x 0 n x max n B k , y b + 1 < ∂ 3 , x 0 n = x max ∂ 0 ( n - 1 ) , x max n = x 0 n + ∂ 0 0 Otherwise CB i n = { 1 ∂ 4 > ∑ k = x 0 n x max n B k , i > ∂ 5 Max ( ∑ k = x w x w + ∂ 6 B k , i ) < ∂ 7 , x 0 n ≤ x w ≤ x max n 0 Otherwise where, ∂ 0 . . . ∂ 7 are adjustable parameters; T is the number of text strings; T y t ,y b m,n is a likelihood that a row between y t and y b in virtual block [m,n] represents text; CB i n is a likelihood that a line[i] is a part of text; and B k,i is a value of pixel[k,i] in the binary representation. 8. The method of claim 6 , wherein the email message comprises a HyperText Markup Language (HTML) formatted email message or an eXtensible Markup Language (XML) formatted email message.
| 0.579011 |
7. A text data processing method comprising: dividing, by a processor, text obtained as a result of speech recognition process into a plurality of blocks by a unit of a topic; calculating, by the processor, a frequency of symbol insertion in a block based on an appearance frequency of a symbol included in the block and number of words or characters in the block, the block being input from a result of the division; determining, by the processor, whether symbol edit for each block is necessary or not based on the frequency of symbol insertion in each block, each block being input from a result of the dividing of the text; and calculating, by the processor, likelihood of the symbol edit based on likelihood of symbol insertion for a word and a record of symbol insertion in a block including symbol already inserted and calculating a symbol edit position in the block in accordance with the likelihood of symbol edit when determining that the symbol edit is necessary.
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7. A text data processing method comprising: dividing, by a processor, text obtained as a result of speech recognition process into a plurality of blocks by a unit of a topic; calculating, by the processor, a frequency of symbol insertion in a block based on an appearance frequency of a symbol included in the block and number of words or characters in the block, the block being input from a result of the division; determining, by the processor, whether symbol edit for each block is necessary or not based on the frequency of symbol insertion in each block, each block being input from a result of the dividing of the text; and calculating, by the processor, likelihood of the symbol edit based on likelihood of symbol insertion for a word and a record of symbol insertion in a block including symbol already inserted and calculating a symbol edit position in the block in accordance with the likelihood of symbol edit when determining that the symbol edit is necessary. 11. The text data processing method according to claim 7 , wherein the likelihood of symbol edit is calculated, by the processor, based on a distance from the symbol edit position to a nearest pause position of pause positions detected by the speech recognition process.
| 0.543711 |
1. A method comprising: establishing, from a merchant site, communication between the merchant site and a generalized search entity via a communication interface, wherein the generalized search entity: presents an input field on user interface of the generalized search entity, wherein the generalized search entity processes data using a generalized search engine that indexes and searches both merchant sites and non-merchant sites; receives a text-based query in the input field; correlates the text-based query against a product database of products for sale from merchants to yield a correlation; determines, via a processor and based at least in part on the correlation, that the text-based query is associated with one of a search intent and a purchase intent to yield a determination; and when the determination indicates the search intent: presents a search result comprising a non-merchant site; receives a search interaction associated with the non-merchant site; and transitions, based on the search interaction, to the non-merchant site; and when the determination indicates the purchase intent: presents a purchase-related search result comprising a buy option associated with the text-based query, wherein the purchase-related search result is configured such that when a user interacts with the purchase-related search result and confirms a purchase via interacting with the buy option, the generalized search entity initiates processing of the purchase of an item; and receives an interaction from the user associated with the purchase-related search result.
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1. A method comprising: establishing, from a merchant site, communication between the merchant site and a generalized search entity via a communication interface, wherein the generalized search entity: presents an input field on user interface of the generalized search entity, wherein the generalized search entity processes data using a generalized search engine that indexes and searches both merchant sites and non-merchant sites; receives a text-based query in the input field; correlates the text-based query against a product database of products for sale from merchants to yield a correlation; determines, via a processor and based at least in part on the correlation, that the text-based query is associated with one of a search intent and a purchase intent to yield a determination; and when the determination indicates the search intent: presents a search result comprising a non-merchant site; receives a search interaction associated with the non-merchant site; and transitions, based on the search interaction, to the non-merchant site; and when the determination indicates the purchase intent: presents a purchase-related search result comprising a buy option associated with the text-based query, wherein the purchase-related search result is configured such that when a user interacts with the purchase-related search result and confirms a purchase via interacting with the buy option, the generalized search entity initiates processing of the purchase of an item; and receives an interaction from the user associated with the purchase-related search result. 2. The method of claim 1 , wherein the generalized search entity further: receives, from the user, an interaction with the buy option; and manages the purchase of the item based on payment information stored at the generalized search entity, wherein delivery of the item is handled via the merchant site separate from the generalized search entity.
| 0.567597 |
13. A method of selecting documents for inclusion in a title policy or a title abstract, comprising: receiving inputs from a user; from a set of documents relating to property, using the inputs to select potentially relevant documents, wherein using the inputs to select potentially relevant documents creates one or more search linkages associated with each potentially relevant document, each search linkage relating to a selection method by which the potentially relevant document was selected, wherein using the inputs to select potentially relevant documents creates a set of potentially relevant documents; organizing the set of potentially relevant documents by searching for relationships between documents in the set, thereby creating one or more organizational linkages, each of which organizational linkages identifies a relationship between at least two documents in the set; for a particular document from the set of potentially relevant documents, using one or more search linkages associated with the particular document to determine a relevance factor relating to the particular document, wherein using one or more search linkages associated with the particular document to determine a relevance factor associated with the document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons; using the one or more organizational linkages in determining the relevance factor associated with the particular document, wherein using the one or more organizational linkages to determine the relevance factor associated with the particular document comprises adjusting a baseline relevance factor if a record date of the particular document predates a specific good stop associated with the document; and using the relevance factor to determine whether to include the particular document on a title abstract or title policy.
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13. A method of selecting documents for inclusion in a title policy or a title abstract, comprising: receiving inputs from a user; from a set of documents relating to property, using the inputs to select potentially relevant documents, wherein using the inputs to select potentially relevant documents creates one or more search linkages associated with each potentially relevant document, each search linkage relating to a selection method by which the potentially relevant document was selected, wherein using the inputs to select potentially relevant documents creates a set of potentially relevant documents; organizing the set of potentially relevant documents by searching for relationships between documents in the set, thereby creating one or more organizational linkages, each of which organizational linkages identifies a relationship between at least two documents in the set; for a particular document from the set of potentially relevant documents, using one or more search linkages associated with the particular document to determine a relevance factor relating to the particular document, wherein using one or more search linkages associated with the particular document to determine a relevance factor associated with the document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons; using the one or more organizational linkages in determining the relevance factor associated with the particular document, wherein using the one or more organizational linkages to determine the relevance factor associated with the particular document comprises adjusting a baseline relevance factor if a record date of the particular document predates a specific good stop associated with the document; and using the relevance factor to determine whether to include the particular document on a title abstract or title policy. 24. The method of claim 13 , wherein adjusting the relevance factor based on one or more specific comparisons comprises adjusting the baseline relevance factor depending upon a type of document that is the particular document.
| 0.512997 |
9. The method of claim 8 further comprising: providing a hyperlink to a webpage comprising additional information related to the biosensor data.
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9. The method of claim 8 further comprising: providing a hyperlink to a webpage comprising additional information related to the biosensor data. 10. The method of claim 9 , wherein the webpage comprises a social networking webpage of a sender of the text-message component.
| 0.931401 |
1. An information retrieval method comprising the steps of generating term-by-data object matrix data to represent information files stored in a computer system, said matrix data being indicative of the frequency of occurrence of selected terms contained in the data objects stored in the information files, decomposing said matrix into a reduced singular value representation composed of distinct term and data object files, in response to a user query, generating a pseudo-object utilizing said selected terms and inserting said pseudo-object into said matrix data, and examining the similarity between said pseudo-object and said term and data object files to generate an information response and storing said response in the system in a form accessible by the user.
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1. An information retrieval method comprising the steps of generating term-by-data object matrix data to represent information files stored in a computer system, said matrix data being indicative of the frequency of occurrence of selected terms contained in the data objects stored in the information files, decomposing said matrix into a reduced singular value representation composed of distinct term and data object files, in response to a user query, generating a pseudo-object utilizing said selected terms and inserting said pseudo-object into said matrix data, and examining the similarity between said pseudo-object and said term and data object files to generate an information response and storing said response in the system in a form accessible by the user. 6. The method as recited in claim 1 further including the step of generating an organizational database associated with the authorship of the data objects and storing said organizational database in the system and said response includes information from said organizational database based on said similarity.
| 0.663455 |
13. A non-transitory computer-readable medium embodied with software for translating between schemas, the software when executed using one or more computers is configured to: receive source schema data and target schema data, the source schema data and the target schemas each comprising a taxonomy comprising a hierarchy of classes into which products may be categorized, wherein the target schema data comprises a different taxonomy then the taxonomy of the source schema data, at least the source schema data further comprising a product ontology associated with one or more of the classes, each product ontology comprising one or more product attributes, at least the source schema data further comprising one or more pointers identifying one or more seller databases and associated with at least one source class, the one or more seller databases including product data associated with one or more products categorized in the source class; generate a graphical representation of the taxonomies of the source schema data and the target schema data, the graphical representation allowing at least one of the plurality of buyer computers to graphically associate classes of the source schema data with classes of the target schema data; communicate the graphical representation to at least one of the plurality of buyer computers; associate one or more source classes of the source schema data with one or more target classes of the target schema data; and generate a product ontology for each of the target classes wherein at least one of the target classes is a parent class and the product ontology for each target class is based on the product ontologies of the associated source classes by determining an intersection of the product attributes included in the product ontologies of the target classes.
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13. A non-transitory computer-readable medium embodied with software for translating between schemas, the software when executed using one or more computers is configured to: receive source schema data and target schema data, the source schema data and the target schemas each comprising a taxonomy comprising a hierarchy of classes into which products may be categorized, wherein the target schema data comprises a different taxonomy then the taxonomy of the source schema data, at least the source schema data further comprising a product ontology associated with one or more of the classes, each product ontology comprising one or more product attributes, at least the source schema data further comprising one or more pointers identifying one or more seller databases and associated with at least one source class, the one or more seller databases including product data associated with one or more products categorized in the source class; generate a graphical representation of the taxonomies of the source schema data and the target schema data, the graphical representation allowing at least one of the plurality of buyer computers to graphically associate classes of the source schema data with classes of the target schema data; communicate the graphical representation to at least one of the plurality of buyer computers; associate one or more source classes of the source schema data with one or more target classes of the target schema data; and generate a product ontology for each of the target classes wherein at least one of the target classes is a parent class and the product ontology for each target class is based on the product ontologies of the associated source classes by determining an intersection of the product attributes included in the product ontologies of the target classes. 14. The computer-readable medium of claim 13 , wherein the software is further configured to: receive input from at least one of a plurality of buyer computers indicating one or more source classes to be associated with one or more target classes; and associate the source classes with the target classes in response to the input from at least one of the plurality of buyer computers.
| 0.754464 |
11. The one or more memory devices as recited in claim 7 , wherein the acts further comprise selecting additional common identifiers from at least one other source domain and importing the additional common identifiers to the target classifier.
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11. The one or more memory devices as recited in claim 7 , wherein the acts further comprise selecting additional common identifiers from at least one other source domain and importing the additional common identifiers to the target classifier. 12. The one or more memory devices as recited in claim 11 , wherein the selecting of the common identifiers is based at least in part on an accuracy of the common identifiers in categorizing the opinion data by sentiment.
| 0.842843 |
1. A method, comprising: receiving, in a computing apparatus from a first computing device, a plurality of text strings, each of the text strings identifying a separate search query, wherein the text strings are from search queries previously entered by users on a first plurality of computing devices; applying, by the computing apparatus, each respective rule of a first plurality of rules to each respective text string of the plurality of text strings, including determining whether the respective text string satisfies a condition of the respective rule, wherein the condition of at least one respective rule is determined to be satisfied by the respective text string in response to a determining the respective text string includes a predetermined text pattern specified for the respective rule; in response to a determining the respective text string satisfies the condition of the respective rule, associating a set of metadata of the respective rule with a search query identified by the respective text string; sorting, by the computing apparatus, the plurality of text strings based at least in part on metadata associated with the search queries via the applying of the first plurality of rules; identifying, by the computing apparatus, a potential title based on the sorting of the plurality of text strings; providing, by the computing apparatus to a second computing device, the potential title for use in creating content, the providing further comprising providing key words obtained from the plurality of text strings, wherein the second computing device is different from the first computing device; receiving, from the second computing device, the created content, wherein the created content includes the key words; transforming the potential title to generate a final title using a second plurality of rules; and publishing, by the computing apparatus, the created content under the final title, wherein the publishing provides access via a website to a second plurality of computing devices, and the second plurality of computing devices is different from the first plurality of computing devices.
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1. A method, comprising: receiving, in a computing apparatus from a first computing device, a plurality of text strings, each of the text strings identifying a separate search query, wherein the text strings are from search queries previously entered by users on a first plurality of computing devices; applying, by the computing apparatus, each respective rule of a first plurality of rules to each respective text string of the plurality of text strings, including determining whether the respective text string satisfies a condition of the respective rule, wherein the condition of at least one respective rule is determined to be satisfied by the respective text string in response to a determining the respective text string includes a predetermined text pattern specified for the respective rule; in response to a determining the respective text string satisfies the condition of the respective rule, associating a set of metadata of the respective rule with a search query identified by the respective text string; sorting, by the computing apparatus, the plurality of text strings based at least in part on metadata associated with the search queries via the applying of the first plurality of rules; identifying, by the computing apparatus, a potential title based on the sorting of the plurality of text strings; providing, by the computing apparatus to a second computing device, the potential title for use in creating content, the providing further comprising providing key words obtained from the plurality of text strings, wherein the second computing device is different from the first computing device; receiving, from the second computing device, the created content, wherein the created content includes the key words; transforming the potential title to generate a final title using a second plurality of rules; and publishing, by the computing apparatus, the created content under the final title, wherein the publishing provides access via a website to a second plurality of computing devices, and the second plurality of computing devices is different from the first plurality of computing devices. 11. The method of claim 1 , wherein the set of metadata includes indication of suitability of the respective text string as a title.
| 0.527494 |
1. A computer-implemented method for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the method comprising: providing a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations for said reservoir; receiving a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterizing the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively performing said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and storing the parameterized model in a computer-accessible memory medium, wherein the parameterized model is usable to analyze operations for the reservoir for management of the production operations for the reservoir.
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1. A computer-implemented method for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the method comprising: providing a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations for said reservoir; receiving a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterizing the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively performing said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and storing the parameterized model in a computer-accessible memory medium, wherein the parameterized model is usable to analyze operations for the reservoir for management of the production operations for the reservoir. 9. The method of claim 1 , wherein said one or more model function derivatives comprise a zeroth or higher order derivative of the model function.
| 0.611704 |
34. The method of claim 1 , further comprising indexing the programming code to generate an index.
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34. The method of claim 1 , further comprising indexing the programming code to generate an index. 38. The method of claim 34 , wherein the index contains statistical metadata comprising in combination: total number of lines of text in the programming code; total number of lines containing the programming instructions in the programming code; total number of lines containing comments in the programming code; total number of lines containing both the programming instructions and the comments; and the total number of lines that are empty or blank in the programming code.
| 0.88632 |
49. The method of claim 1 , further comprising the step of unrolling the known sequence from the SSM Matrix and the histogram of the known sequence.
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49. The method of claim 1 , further comprising the step of unrolling the known sequence from the SSM Matrix and the histogram of the known sequence. 50. The method of claim 49 , wherein the step of unrolling comprises the steps of: calculating a total number of open bigrams that are present in the known sequence by summing up all X ij elements of the SSM Matrix of the known sequence; calculating a sequence length, T, by solving the quadratic equation T(T+1)/2 and taking its positive root; extract the character histogram, h=[h 1 , h 2 , h 3 , . . . , h M ], from diagonal entries of the SSM Matrix of the known sequence by solving a quadratic equation h i (h i +1)/2=X ii for i=1, 2, 3, . . . , M; calculating a frequency for the i th character in the known sequence alphabet as h i = - 1 + 1 + 8 X ii 2 , i = 1 , … , M ; calculating row sums of the SSM Matrix of the known sequence by adding open bigram counters in each row; and reconstructing a total order of the characters in the known sequence by sorting the row sums in descending order.
| 0.698358 |
1. A method of processing network metadata generated on a network transmitting network traffic using one or more network protocols, the network including devices at least some of which receive network traffic through an ingress interface and transmit network traffic through an egress interface, the method comprising the steps of: receiving network metadata from a plurality of sources in a data processing system, in at least one data format; determining the type or character of said network metadata; processing said network metadata by applying at least one policy governing network metadata processing, wherein said at least one policy includes the steps of: comparing the source of incoming network traffic to a predefined list of monitored off-limit devices on said network; if the destination IP address is on a predefined list of off-limit devices, storing the source IP/port, as well as the destination IP/port in a potential alert list, along with the number of bytes and packets reported in the ingress NetFlow record; examining output records to determine if the source IP/port and the destination IP/port match an entry in the potential alert list; if a match is found, treating such match as an indication that an internal host replied to an outside peer request; and generating an alert message in a timely manner to inform of a potential botnet infection; and converting at least a portion of said network metadata into one or more different data formats that are used in said data processing system for other system metadata, in response, at least in part, to the results of said determining step.
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1. A method of processing network metadata generated on a network transmitting network traffic using one or more network protocols, the network including devices at least some of which receive network traffic through an ingress interface and transmit network traffic through an egress interface, the method comprising the steps of: receiving network metadata from a plurality of sources in a data processing system, in at least one data format; determining the type or character of said network metadata; processing said network metadata by applying at least one policy governing network metadata processing, wherein said at least one policy includes the steps of: comparing the source of incoming network traffic to a predefined list of monitored off-limit devices on said network; if the destination IP address is on a predefined list of off-limit devices, storing the source IP/port, as well as the destination IP/port in a potential alert list, along with the number of bytes and packets reported in the ingress NetFlow record; examining output records to determine if the source IP/port and the destination IP/port match an entry in the potential alert list; if a match is found, treating such match as an indication that an internal host replied to an outside peer request; and generating an alert message in a timely manner to inform of a potential botnet infection; and converting at least a portion of said network metadata into one or more different data formats that are used in said data processing system for other system metadata, in response, at least in part, to the results of said determining step. 9. The method as set forth in claim 1 , wherein said at least one policy is applied for the purpose of reducing the number of NetFlow messages that arrives at the device that stores said network metadata on said network.
| 0.613574 |
1. A system for generating a dynamic representation of relations among individuals, the system comprising: a memory for storing computer executable instructions; and a processing unit coupled to the memory, operable to execute the computer executable instructions, and based at least in part on the execution of the computer executable instructions operable to perform operations comprising: classifying main characters of images in an image collection based on assignments of respective groups of the images in which the main characters appear to respective events, wherein each image has a time stamp, and wherein each main character is characterized by at least one attribute; determining relation circles of the main characters based on the event assignments; and constructing a dynamic relation tree representative of relations among the main characters, wherein the dynamic relation tree provides representations of the positions of the main characters in the relation circles, and wherein views and constituents of the dynamic relation tree change when different time periods are specified during display.
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1. A system for generating a dynamic representation of relations among individuals, the system comprising: a memory for storing computer executable instructions; and a processing unit coupled to the memory, operable to execute the computer executable instructions, and based at least in part on the execution of the computer executable instructions operable to perform operations comprising: classifying main characters of images in an image collection based on assignments of respective groups of the images in which the main characters appear to respective events, wherein each image has a time stamp, and wherein each main character is characterized by at least one attribute; determining relation circles of the main characters based on the event assignments; and constructing a dynamic relation tree representative of relations among the main characters, wherein the dynamic relation tree provides representations of the positions of the main characters in the relation circles, and wherein views and constituents of the dynamic relation tree change when different time periods are specified during display. 6. The system of claim 1 , wherein based at least in part on the execution of the computer executable instructions the processing unit is operable to perform operations comprising: applying face clustering to identify face clusters, each face cluster comprising images of a main character; determining gender or age group of each main character based on a demographic assessment of each face cluster; applying a face similarity measure to identify related persons with similar facial features; and extracting co-appearances and relative positions information in the images to determine the closeness of relationship of certain of the main characters.
| 0.5 |
1. A multi-hash apparatus for use with a pattern search engine, comprising: said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said BFSM being implemented in hardware, or a combination of hardware and software, said pattern search engine having three rules comprising transition rules, default rules and initial rules, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule, wherein each said pattern search engine rule comprises a match portion, a next state portion and various flags, all of which rules may read for a given character; said pattern search engine is programmed having a rules structure in a memory that is accessed by said search engine which processes an input data stream by executing a given rules structure, wherein for each consecutive input character in said input stream, a highest-priority rule is searched in said rules structure having a test part containing conditions that match a current state and said given input character, so that the next state defined in the found rule then becomes the new state of said search engine and is used to process the next input character; said rules structure comprises a plurality of rule banks including at least one transition rule bank containing memory for storing transition rules which are read on the existing said current state and an input character; and at least one default rule bank containing memory for storing default rules which is used when no transition rule is found, each said rule bank operative to store pattern context rules; said default rules and said transition rules being indexed separately and held in separate physical data structures; said initial rule functioning when required to return said search engine to an initial state of said pattern search engine; a lookup circuit operative to perform a plurality of lookups for an input character on said plurality of rule banks, each lookup performed on either a said transition rule bank or a said default rule bank; and a multi-hash circuit operative to determine a highest priority rule from among said plurality of lookups, said highest priority rule determining the next state of said pattern search engine; multiple hashes being performed on the current character and current state, each being used respectively as a lookup to a corresponding transition rule bank , the hash results obtained therefrom being operative to output a transition rule; concurrently, only a single default hash, based on said current character is used as a lookup for a default rule bank which outputs default rules; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank.
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1. A multi-hash apparatus for use with a pattern search engine, comprising: said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said BFSM being implemented in hardware, or a combination of hardware and software, said pattern search engine having three rules comprising transition rules, default rules and initial rules, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule, wherein each said pattern search engine rule comprises a match portion, a next state portion and various flags, all of which rules may read for a given character; said pattern search engine is programmed having a rules structure in a memory that is accessed by said search engine which processes an input data stream by executing a given rules structure, wherein for each consecutive input character in said input stream, a highest-priority rule is searched in said rules structure having a test part containing conditions that match a current state and said given input character, so that the next state defined in the found rule then becomes the new state of said search engine and is used to process the next input character; said rules structure comprises a plurality of rule banks including at least one transition rule bank containing memory for storing transition rules which are read on the existing said current state and an input character; and at least one default rule bank containing memory for storing default rules which is used when no transition rule is found, each said rule bank operative to store pattern context rules; said default rules and said transition rules being indexed separately and held in separate physical data structures; said initial rule functioning when required to return said search engine to an initial state of said pattern search engine; a lookup circuit operative to perform a plurality of lookups for an input character on said plurality of rule banks, each lookup performed on either a said transition rule bank or a said default rule bank; and a multi-hash circuit operative to determine a highest priority rule from among said plurality of lookups, said highest priority rule determining the next state of said pattern search engine; multiple hashes being performed on the current character and current state, each being used respectively as a lookup to a corresponding transition rule bank , the hash results obtained therefrom being operative to output a transition rule; concurrently, only a single default hash, based on said current character is used as a lookup for a default rule bank which outputs default rules; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank. 5. The apparatus according to claim 1 , wherein hash circuit is operative to perform a multi-hash lookup for both transition rule bank and said default rule bank.
| 0.521893 |
31. A method for filtering messages received by a user, comprising: determining, in a content analysis engine, a score for each received message by analyzing a plurality of portions of a body of each received message, wherein each portion in the plurality of portions is associated with a portion score; determining whether an address associated with a sender of each received message matches an entry on a positive screening list; storing a set of received messages in a quarantine folder if the address associated with the sender of each message in the set of received messages does not match an entry on the positive screening list; and sorting the set of received messages stored in the quarantine folder according to their associated scores.
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31. A method for filtering messages received by a user, comprising: determining, in a content analysis engine, a score for each received message by analyzing a plurality of portions of a body of each received message, wherein each portion in the plurality of portions is associated with a portion score; determining whether an address associated with a sender of each received message matches an entry on a positive screening list; storing a set of received messages in a quarantine folder if the address associated with the sender of each message in the set of received messages does not match an entry on the positive screening list; and sorting the set of received messages stored in the quarantine folder according to their associated scores. 32. The method of claim 31 , further comprising: (e) obscuring one or more messages in the set of received messages having a score within a range indicating spam.
| 0.81935 |
1. A system for generating targeted advertisement recommendations, the system comprising: a data aggregation module configured to obtain word data from social-network data of one or more network resources, the word data comprising a plurality of words in the social-network data; a relationship mining module in communication with the data aggregation module, the relationship mining module configured to create word relationships between selected ones of the plurality of words in the word data to produce relationship data, each of the word relationships reflecting a degree of association between two or more of the selected words, wherein the degree of association is based at least in part on an amount of social momentum between said selected words and at least one of: a frequency of the selected words in the social network data, a recency of a subset of the social-network data that comprises the two or more selected words, and an authority factor of the subset of the social-network data; and a recommender module in communication with the relationship module, the recommender module configured to: access browse information of a target user to identify one or more first words in the target user's browse information, identify the one or more first words in the relationship data, identify one or more second words in the relationship data that have one or more of said word relationships with the one or more first words, identify one or more advertisements having at least one keyword that corresponds to the one or more second words, selecting an advertisement from the one or more advertisements based on the degree of association between said keyword and the one or more second words, and transmitting said selected advertisement.
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1. A system for generating targeted advertisement recommendations, the system comprising: a data aggregation module configured to obtain word data from social-network data of one or more network resources, the word data comprising a plurality of words in the social-network data; a relationship mining module in communication with the data aggregation module, the relationship mining module configured to create word relationships between selected ones of the plurality of words in the word data to produce relationship data, each of the word relationships reflecting a degree of association between two or more of the selected words, wherein the degree of association is based at least in part on an amount of social momentum between said selected words and at least one of: a frequency of the selected words in the social network data, a recency of a subset of the social-network data that comprises the two or more selected words, and an authority factor of the subset of the social-network data; and a recommender module in communication with the relationship module, the recommender module configured to: access browse information of a target user to identify one or more first words in the target user's browse information, identify the one or more first words in the relationship data, identify one or more second words in the relationship data that have one or more of said word relationships with the one or more first words, identify one or more advertisements having at least one keyword that corresponds to the one or more second words, selecting an advertisement from the one or more advertisements based on the degree of association between said keyword and the one or more second words, and transmitting said selected advertisement. 5. The system of claim 1 , wherein the recommender module is further configured to weight the one or more first words based at least in part on a frequency of which the one or more first words occur in the browse information of the target user.
| 0.5 |
50. The method of claim 33 , further comprising resubmitting the at least one first predictive background query in response to an update identifying the stored result of the at least one first predictive background query as being invalid.
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50. The method of claim 33 , further comprising resubmitting the at least one first predictive background query in response to an update identifying the stored result of the at least one first predictive background query as being invalid. 51. The method of claim 50 , wherein resubmitting the at least one first predictive background query further comprises deleting the stored result of the at least one first predictive background query, the deletion beginning with the result to the at least one first predictive background query least recently displayed by the user interface.
| 0.930465 |
1. A method for operating content addressable memory, the method comprising: providing a plurality of memory cells in parallel circuit, the memory cells being electrically coupled to a match line, the match line configured to receive a collective current from the memory cells during a memory search operation; receiving a data word of bit length L for storage in the memory cells; transforming the data word into a code word of bit length greater than L such that at least one code word bit in the code word depends on at least two data word bits in the data word, the code word guaranteeing a mismatch of at least two code word bits of different binary values during the memory search operation when the data word does not match a search word; and storing the code word in the memory cells.
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1. A method for operating content addressable memory, the method comprising: providing a plurality of memory cells in parallel circuit, the memory cells being electrically coupled to a match line, the match line configured to receive a collective current from the memory cells during a memory search operation; receiving a data word of bit length L for storage in the memory cells; transforming the data word into a code word of bit length greater than L such that at least one code word bit in the code word depends on at least two data word bits in the data word, the code word guaranteeing a mismatch of at least two code word bits of different binary values during the memory search operation when the data word does not match a search word; and storing the code word in the memory cells. 5. The method of claim 1 , further comprising: wherein the data word includes a plurality of digits represented as a first binary value and a second binary value; and wherein the code word includes the data word, an encoded number of occurrences of the first binary value in the data word, and a bitwise complement of the encoded number of occurrences of the first binary value in the data word.
| 0.539788 |
10. The method of claim 8 , further comprising: concurrently displaying both the first sub key button assigned with the second alphabet character and a third key button assigned with the same second alphabet character.
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10. The method of claim 8 , further comprising: concurrently displaying both the first sub key button assigned with the second alphabet character and a third key button assigned with the same second alphabet character. 11. The method of claim 10 , further comprising: replacing the first sub key button with the second sub key button at the location.
| 0.928804 |
16. The system of claim 15 , the authoring further comprising: receiving authored haptic effect characteristics for one or more authored haptic effects and multimedia event features for one or more multimedia events; associating types of authored haptic effects with types of multimedia events based on the authored haptic effect characteristics and the multimedia event features; constructing the learned haptification model based on a result of the associating.
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16. The system of claim 15 , the authoring further comprising: receiving authored haptic effect characteristics for one or more authored haptic effects and multimedia event features for one or more multimedia events; associating types of authored haptic effects with types of multimedia events based on the authored haptic effect characteristics and the multimedia event features; constructing the learned haptification model based on a result of the associating. 19. The system of claim 16 , the authoring further comprising: extracting one or more extracted characteristics describing each effect of the authored haptic effects and one or more extracted features describing each event of the multimedia event, wherein the associating includes associating the authored haptic effect characteristics with the multimedia event features based on at least the extracted characteristics and the extracted features, and wherein the extracted characteristics describing each effect includes duration, amplitude, shape, and frequency, and wherein the extracted features describing each event includes audio and visual features, scene dynamics, and a context of the event.
| 0.517834 |
1. A computing device configured to implement broadcast automation software, the computing device comprising: a processor; a non-transitory computer-readable storage medium coupled to the processor and storing a program of instructions to be executed by the processor, the program of instructions including: at least one instruction to display at least two different windows of the broadcast automation software, each different window including a plurality of user interface (UI) strings programmed into the broadcast automation software, wherein a first UI string of the plurality of UI strings is included in both a first window and a second window; at least one instruction to translate the plurality of UI strings included in the first window from a default language into a first translation language, wherein the first UI string is translated into the translation language as a first translated UI string; and at least one instruction to translate the plurality of UI strings included in the second window from the default language into the translation language, wherein the first UI string is translated into the translation language as a second translated UI string different from the first translated UI string.
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1. A computing device configured to implement broadcast automation software, the computing device comprising: a processor; a non-transitory computer-readable storage medium coupled to the processor and storing a program of instructions to be executed by the processor, the program of instructions including: at least one instruction to display at least two different windows of the broadcast automation software, each different window including a plurality of user interface (UI) strings programmed into the broadcast automation software, wherein a first UI string of the plurality of UI strings is included in both a first window and a second window; at least one instruction to translate the plurality of UI strings included in the first window from a default language into a first translation language, wherein the first UI string is translated into the translation language as a first translated UI string; and at least one instruction to translate the plurality of UI strings included in the second window from the default language into the translation language, wherein the first UI string is translated into the translation language as a second translated UI string different from the first translated UI string. 4. The computing device of claim 1 , further comprising: at least one instruction to receive user input selecting one of the first window and the second window as a focus window; and at least one instruction to translate the plurality of UI strings in the focus window.
| 0.5 |
10. A computer-implemented method of providing annotated electronic documents, the method being executed on a computer and comprising: providing, in a computer processor, access to an electronic storage configured to store at least one annotation as annotation data in a first data storage and at least one document as document data in a second data storage, the first and second data storage being searchable databases; receiving, in the computer processor from the electronic storage, a unitary single logical document for display that includes document data with at least one annotation represented by annotation data embedded seamlessly in the document data, the annotation data being retrieved from the first data storage, the document data being retrieved from the second data storage which is stored separately from the first data storage; and extracting, in the computer processor, by a split component, from the single logical document, the annotation data and the document data; updating the at least one annotation in the first data storage from the extracted annotation data; and updating the at least one document in the second data storage from the extracted document data, wherein the annotation data indexes into a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by a document-image-independent data schema, wherein the annotations data further includes, specific to the predetermined section within the document to which the annotation is embedded, a pre-defined conflict indication user-selected from at least two of pass possible and fail, and wherein the processor is further configured to search, responsive to a search request from at least one user, the search request includes annotation search criteria which includes at least one of the pre-defined conflict indications content of the annotation data in the first data storage for the annotation data that satisfies the annotation search criteria, and to output, as a search result, the at least one document indicated by the annotation data that satisfies the annotation search criteria.
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10. A computer-implemented method of providing annotated electronic documents, the method being executed on a computer and comprising: providing, in a computer processor, access to an electronic storage configured to store at least one annotation as annotation data in a first data storage and at least one document as document data in a second data storage, the first and second data storage being searchable databases; receiving, in the computer processor from the electronic storage, a unitary single logical document for display that includes document data with at least one annotation represented by annotation data embedded seamlessly in the document data, the annotation data being retrieved from the first data storage, the document data being retrieved from the second data storage which is stored separately from the first data storage; and extracting, in the computer processor, by a split component, from the single logical document, the annotation data and the document data; updating the at least one annotation in the first data storage from the extracted annotation data; and updating the at least one document in the second data storage from the extracted document data, wherein the annotation data indexes into a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by a document-image-independent data schema, wherein the annotations data further includes, specific to the predetermined section within the document to which the annotation is embedded, a pre-defined conflict indication user-selected from at least two of pass possible and fail, and wherein the processor is further configured to search, responsive to a search request from at least one user, the search request includes annotation search criteria which includes at least one of the pre-defined conflict indications content of the annotation data in the first data storage for the annotation data that satisfies the annotation search criteria, and to output, as a search result, the at least one document indicated by the annotation data that satisfies the annotation search criteria. 17. The method of claim 10 , further comprising: determining, in the computer processor, whether the at least one document is read-only; updating, in the computer processor, the at least one document in the second data storage from the extracted document data when the at least one document is determined to not be read-only; and canceling, in the computer processor, an update of the at least one document when the at least one document is determined to be read-only.
| 0.518324 |
1. A method performed by a building safety system having at least a processor, comprising: receiving a voice input by the building safety system; receiving voice data produced by a speech recognition process performed on the voice input; determining a location of an individual having transmitted the voice input; determining a response to the voice input based on the voice data; and producing the response by the building safety system, wherein the response is directional information, to a destination location, relative to the location of the individual having transmitted the voice input, and wherein the directional information is to a pull station.
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1. A method performed by a building safety system having at least a processor, comprising: receiving a voice input by the building safety system; receiving voice data produced by a speech recognition process performed on the voice input; determining a location of an individual having transmitted the voice input; determining a response to the voice input based on the voice data; and producing the response by the building safety system, wherein the response is directional information, to a destination location, relative to the location of the individual having transmitted the voice input, and wherein the directional information is to a pull station. 4. The method of claim 1 , wherein the step of determining a response to the voice input comprises determining whether the voice input is one of a request for directions to a pull station, a distress sound or a distress word, and wherein the building safety system includes a plurality of building safety devices each having a speaker, and after determining the voice input is one of a distress sound or a distress word, the building safety system produces an audible response via the speaker of a first of the building safety devices, the audible response being a phrase to prompt the individual to confirm an emergency event is occurring.
| 0.5 |
15. A system comprising: a processor configured to: display a keypad for text input to a user, the keypad including a plurality of keys, receive input from the user indicating a selection of a key from the plurality of keys, the key representing a consonant, receive a gesture input from the user, wherein the gesture input is associated with one gesture out of a set of gestures, each gesture in the set being semantically linked as defined by the user to at least one property selected from: a phonological property and a diacritic property, and display a grapheme based upon the selected key and at least one of the phonological property and the diacritic property semantically linked to the received gesture, wherein the grapheme is a modified version of a word associated with the selected key and the grapheme is predicted based on only the consonant and the at least one property associated with the received gesture.
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15. A system comprising: a processor configured to: display a keypad for text input to a user, the keypad including a plurality of keys, receive input from the user indicating a selection of a key from the plurality of keys, the key representing a consonant, receive a gesture input from the user, wherein the gesture input is associated with one gesture out of a set of gestures, each gesture in the set being semantically linked as defined by the user to at least one property selected from: a phonological property and a diacritic property, and display a grapheme based upon the selected key and at least one of the phonological property and the diacritic property semantically linked to the received gesture, wherein the grapheme is a modified version of a word associated with the selected key and the grapheme is predicted based on only the consonant and the at least one property associated with the received gesture. 18. The system of claim 15 , further comprising predicting a character that is part of the grapheme.
| 0.731616 |
1. A method of deploying a package of objects in a learning management system, the method comprising: transmitting a Shareable Content Object Reference Model (SCORM) package to a SCORM Learning Management System (LMS), wherein the SCORM package includes a manifest listing of resources needed to deploy the SCORM package from the LMS; parsing out the manifest listing from the SCORM package; iterating through the manifest listing to create an inventory of the resources in the SCORM package, wherein the inventory of the resources includes an attribute file; comparing names of all resources in the manifest listing with named resources in the attribute file in the inventory of resources available to the LMS; in response to a name in the manifest listing not completely matching any named resources in the attribute file in the inventory of resources available to the LMS, updating a character casing of the name to match a character casing of a corresponding name of a named resource in the attribute file in the inventory of resources available to the LMS, wherein the character casing of the corresponding name of the named resource includes one or more upper case letters and one or more lower case letters; and deploying the SCORM package by launching the SCORM package with a corrected list of resources matching the attribute file in the inventory of resource available to the LMS.
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1. A method of deploying a package of objects in a learning management system, the method comprising: transmitting a Shareable Content Object Reference Model (SCORM) package to a SCORM Learning Management System (LMS), wherein the SCORM package includes a manifest listing of resources needed to deploy the SCORM package from the LMS; parsing out the manifest listing from the SCORM package; iterating through the manifest listing to create an inventory of the resources in the SCORM package, wherein the inventory of the resources includes an attribute file; comparing names of all resources in the manifest listing with named resources in the attribute file in the inventory of resources available to the LMS; in response to a name in the manifest listing not completely matching any named resources in the attribute file in the inventory of resources available to the LMS, updating a character casing of the name to match a character casing of a corresponding name of a named resource in the attribute file in the inventory of resources available to the LMS, wherein the character casing of the corresponding name of the named resource includes one or more upper case letters and one or more lower case letters; and deploying the SCORM package by launching the SCORM package with a corrected list of resources matching the attribute file in the inventory of resource available to the LMS. 3. The method of claim 1 , wherein one of the resources needed to deploy the SCORM package is a driver.
| 0.86059 |
1. A method for composing text, comprising: displaying, on a display, a composition field and a second field, the second field including text; receiving an input for inclusion in the composition field; determining that a portion of the composition field is not visible on the display, including the portion being moved off-screen from the display, when the input is received; in response to the determining, displaying an overlay, the overlay including an input area, wherein the overlay is a partially transparent overlay; displaying the input in the input area of the overlay; detecting an insert event; and in response to detecting the insert event, inserting the elements entered in the input area of the overlay into the composition field and removing the overlay from the display.
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1. A method for composing text, comprising: displaying, on a display, a composition field and a second field, the second field including text; receiving an input for inclusion in the composition field; determining that a portion of the composition field is not visible on the display, including the portion being moved off-screen from the display, when the input is received; in response to the determining, displaying an overlay, the overlay including an input area, wherein the overlay is a partially transparent overlay; displaying the input in the input area of the overlay; detecting an insert event; and in response to detecting the insert event, inserting the elements entered in the input area of the overlay into the composition field and removing the overlay from the display. 4. The method of claim 1 , wherein the overlay is superimposed onto the second field.
| 0.899061 |
15. A non-transitory machine readable storage medium having instructions stored thereon which, when executed by one or more processors, cause the one or more processors to perform the operations of: receiving user input from a user; in response to the user input, accessing a plurality of electronic mail messages (emails), including a certain email, that are part of an email conversation; extracting content from each of the accessed emails, including the certain email; automatically generating a composite email which includes the content extracted from each of the accessed emails; obtaining a set of markup information indicating one or more markups that were previously made to the content of the certain email, wherein the set of markup information is separate from the content of the certain email; and applying the one or more markups to the content of the certain email to derive a marked up version of the content of the certain email in the composite email.
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15. A non-transitory machine readable storage medium having instructions stored thereon which, when executed by one or more processors, cause the one or more processors to perform the operations of: receiving user input from a user; in response to the user input, accessing a plurality of electronic mail messages (emails), including a certain email, that are part of an email conversation; extracting content from each of the accessed emails, including the certain email; automatically generating a composite email which includes the content extracted from each of the accessed emails; obtaining a set of markup information indicating one or more markups that were previously made to the content of the certain email, wherein the set of markup information is separate from the content of the certain email; and applying the one or more markups to the content of the certain email to derive a marked up version of the content of the certain email in the composite email. 18. The machine readable storage medium of claim 15 , wherein the one or more markups include one or more reminders that have been associated with at least a portion of the content of the certain email.
| 0.770178 |
1. A computer-implemented method of managing supplier intelligence, comprising: collecting procurement data regarding a procurement process from a plurality of data sources, the procurement data including information regarding a plurality of business divisions of a business entity; for each business division, generating a set of spend formulas for determining spending associated with that business division; generating a set of supplier intelligence business rules based on a variety of business parameters, each supplier intelligence business rule interrelating at least one spend formula associated with a first one of the business divisions with at least one spend formula associated with a second one of the business divisions; performing, using a computer system, an automatic analysis of at least a portion of the procurement data based on one or more of the set of supplier intelligence business rules to determine the financial effects of a decision made by the first business division on the second business division; and automatically generating a visual output indicating the results of the automatic analysis of the at least a portion of the procurement data.
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1. A computer-implemented method of managing supplier intelligence, comprising: collecting procurement data regarding a procurement process from a plurality of data sources, the procurement data including information regarding a plurality of business divisions of a business entity; for each business division, generating a set of spend formulas for determining spending associated with that business division; generating a set of supplier intelligence business rules based on a variety of business parameters, each supplier intelligence business rule interrelating at least one spend formula associated with a first one of the business divisions with at least one spend formula associated with a second one of the business divisions; performing, using a computer system, an automatic analysis of at least a portion of the procurement data based on one or more of the set of supplier intelligence business rules to determine the financial effects of a decision made by the first business division on the second business division; and automatically generating a visual output indicating the results of the automatic analysis of the at least a portion of the procurement data. 8. The method of claim 1 , wherein the automatically generated visual output comprises a three-dimensional visualization.
| 0.684175 |
18. A method comprising: generating a fingerprint data using a television; matching primary data generated from the fingerprint data with targeted data, based on a relevancy factor, using a relevancy-matching server; locating in a storage at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server, wherein the primary data is any one of a content identification data and a content identification history; constraining an executable environment in a security sandbox of a mobile device; executing a sandboxed application in the executable environment of the mobile device; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing an embedded object within the sandboxed application; and executing the embedded object through the sandboxed application to cause rendering of the targeted data therethrough, wherein the identification data of the television comprises at least one of a GUID, an alphanumeric name, a hardware address associated with the television, a public address associated with an automatic content identification service of the television, and a private address associated with the automatic content identification service of the television when the shared computer network is determined to be commonly associated with the mobile device and the television.
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18. A method comprising: generating a fingerprint data using a television; matching primary data generated from the fingerprint data with targeted data, based on a relevancy factor, using a relevancy-matching server; locating in a storage at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server, wherein the primary data is any one of a content identification data and a content identification history; constraining an executable environment in a security sandbox of a mobile device; executing a sandboxed application in the executable environment of the mobile device; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing an embedded object within the sandboxed application; and executing the embedded object through the sandboxed application to cause rendering of the targeted data therethrough, wherein the identification data of the television comprises at least one of a GUID, an alphanumeric name, a hardware address associated with the television, a public address associated with an automatic content identification service of the television, and a private address associated with the automatic content identification service of the television when the shared computer network is determined to be commonly associated with the mobile device and the television. 23. The method of claim 18 , comprising: determining the mobile device to be associated with a user based on a unique identifier that is unlikely to change.
| 0.791833 |
19. The system of claim 10 , wherein determining that the update affects the posting list for the term assigned to the second leaf node includes: determining that the update affects a document that is not in the first set of documents; determining that the term is associated with the document; and determining that the term fails to meet a popularity threshold.
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19. The system of claim 10 , wherein determining that the update affects the posting list for the term assigned to the second leaf node includes: determining that the update affects a document that is not in the first set of documents; determining that the term is associated with the document; and determining that the term fails to meet a popularity threshold. 20. The system of claim 19 , wherein determining that the update affects the posting list for the term assigned to the second leaf node further includes determining that the term is assigned to the second leaf node by applying a function to an identifier for the term.
| 0.882624 |
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