Patents by Inventor Aditya A Kalyanpur
Aditya A Kalyanpur has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 8600986Abstract: A system, method and computer program product for automatically estimating the confidence of a detected LAT to provide a more accurate overall score for an obtained candidate answer. A confidence “score” or value of each detected LAT is obtained, and the system and method performs combining the confidence score with a degree of match between a LAT and an AnswerType of the candidate answer to provide improved overall score for the candidate answer.Type: GrantFiled: August 29, 2012Date of Patent: December 3, 2013Assignee: International Business Machines CorporationInventors: James J. Fan, David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally, James W. Murdock, Wlodek W. Zadrozny
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Publication number: 20130282363Abstract: A system, method and computer program product for automatically estimating the confidence of a detected LAT to provide a more accurate overall score for an obtained candidate answer. A confidence “score” or value of each detected LAT is obtained, and the system and method performs combining the confidence score with a degree of match between a LAT and an AnswerType of the candidate answer to provide improved overall score for the candidate answer.Type: ApplicationFiled: June 18, 2013Publication date: October 24, 2013Inventors: James J. Fan, David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally, James W. Murdock, Wlodek W. Zadrozny
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Patent number: 8560483Abstract: Techniques for facilitating learning of one or more ontological rules of a resource description framework database are provided. The techniques include obtaining ontology vocabulary from a resource description framework database, generating a rule hypothesis by incrementally building upon a previously learnt rule from the database by adding one or more predicates to the previously learnt rule, performing a constraint check on the generated rule hypothesis by determining compatibility with each previously learnt rule to ensure that a complete rule set including each previously learnt rule and the generated rule hypothesis is consistent, validating the rule hypothesis as a rule using one or more association rule mining techniques to determine validity of the rule hypothesis against the database, and applying the rule to the database to infer one or more facts from the database to facilitate learning of one or more additional ontological rules.Type: GrantFiled: September 25, 2012Date of Patent: October 15, 2013Assignee: International Business Machines CorporationInventors: Achille Fokoue, Aditya Kalyanpur, Kavitha Srinivas
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Publication number: 20130246046Abstract: Systems and method automatically collect training data from manually created semantic relations, automatically extract rules from the training data to produce extracted rules, and automatically characterize existing semantic relations in the training data based on co-occurrence of the extracted rules in the existing semantic relations. Such systems and methods automatically construct semantic relation topics based on the characterization of the existing semantic relations, and group instances of the training data into the semantic relation topics to detect new semantic relations.Type: ApplicationFiled: March 16, 2012Publication date: September 19, 2013Applicant: International Business Machines CorporationInventors: JAMES J. FAN, David Gondek, Aditya A. Kalyanpur, Chang Wang
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Patent number: 8538904Abstract: A system and computer program product for facilitating learning of one or more ontological rules of a resource description framework database include obtaining ontology vocabulary from a resource description framework database, generating a rule hypothesis by incrementally building upon a previously learnt rule from the database by adding one or more predicates to the previously learnt rule, performing a constraint check on the generated rule hypothesis by determining compatibility with each previously learnt rule to ensure that a complete rule set including each previously learnt rule and the generated rule hypothesis is consistent, validating the rule hypothesis as a rule using one or more association rule mining techniques to determine validity of the rule hypothesis against the database, and applying the rule to the database to infer one or more facts from the database to facilitate learning of one or more additional ontological rules.Type: GrantFiled: November 1, 2010Date of Patent: September 17, 2013Assignee: International Business Machines CorporationInventors: Achille Fokoue, Aditya Kalyanpur, Kavitha Srinivas
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Publication number: 20130212542Abstract: A method for automatic detection of user preferences for alternate user interface model includes operating a digital device with an active user interface model and receiving one or more input signals from a user of the digital device. The method includes comparing the one or more input signals with one or more latent user interface models and determining if one of the latent user interface models has a higher likelihood given the one or more input signals than the active user interface models. The method also includes responsively substituting the latent user interface with the highest likelihood given the one or more input signals for the active user interface model.Type: ApplicationFiled: February 15, 2012Publication date: August 15, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Aaron K. Baughman, David W. Buchanan, Robert G. Farrell, Aditya A. Kalyanpur
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Patent number: 8510296Abstract: A system, method and computer program product for automatically estimating the confidence of a detected LAT to provide a more accurate overall score for an obtained candidate answer. A confidence “score” or value of each detected LAT is obtained, and the system and method performs combining the confidence score with a degree of match between a LAT and an AnswerType of the candidate answer to provide improved overall score for the candidate answer.Type: GrantFiled: September 23, 2011Date of Patent: August 13, 2013Assignee: International Business Machines CorporationInventors: James J. Fan, David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally, James W. Murdock, Wlodek W. Zadrozny
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Publication number: 20130035931Abstract: In an automated Question Answer (QA) system architecture for automatic open-domain Question Answering, a system, method and computer program product for predicting the Lexical Answer Type (LAT) of a question. The approach is completely unsupervised and is based on a large-scale lexical knowledge base automatically extracted from a Web corpus. This approach for predicting the LAT can be implemented as a specific subtask of a QA process, and/or used for general purpose knowledge acquisition tasks such as frame induction from text.Type: ApplicationFiled: August 28, 2012Publication date: February 7, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, Alfio M. Gliozzo, Aditya A. Kalyanpur
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Publication number: 20130035930Abstract: In an automated Question Answer (QA) system architecture for automatic open-domain Question Answering, a system, method and computer program product for predicting the Lexical Answer Type (LAT) of a question. The approach is completely unsupervised and is based on a large-scale lexical knowledge base automatically extracted from a Web corpus. This approach for predicting the LAT can be implemented as a specific subtask of a QA process, and/or used for general purpose knowledge acquisition tasks such as frame induction from text.Type: ApplicationFiled: July 18, 2012Publication date: February 7, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, Alfio M. Gliozzo, Aditya A. Kalyanpur
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Publication number: 20130018652Abstract: Diffusing evidence among candidate answers during question answering may identify a relationship between a first candidate answer and a second candidate answer, wherein the candidate answers are generated by a question-answering computer process, the candidate answers have associated supporting evidence, and the candidate answers have associated confidence scores. All or some of the evidence may be transferred from the first candidate answer to the second candidate answer based on the identified relationship. A new confidence score may be computed for the second candidate answer based on the transferred evidence.Type: ApplicationFiled: September 14, 2012Publication date: January 17, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally
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Patent number: 8355905Abstract: Methods, apparatus and systems, including computer program products, for reducing an error rate when mapping entities between a first ontology and a second ontology. One or more of a general language dictionary and an industry-specific dictionary are provided. Natural language processing of the first ontology is performed to identify one or more candidate relationship entities in the first ontology. Each candidate relationship entity includes a compound name having two or more semantic labels, and each candidate relationship entity has a name that neither exists in the general language dictionary or the industry-specific dictionary. Each of the one or more candidate relationship entities in the first ontology is mapped to one or more entities in the second ontology using one or more configurable computer-implemented mapping algorithms.Type: GrantFiled: May 14, 2010Date of Patent: January 15, 2013Assignee: International Business Machines CorporationInventors: Achille B. Fokoue-Nkoutche, Aditya A. Kalyanpur, Kirill M. Osipov, Kavitha Srinivas, Min Wang
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Publication number: 20120330921Abstract: A computer-implemented system, method and program product generates answers to questions in an input query text string. The method includes determining, by a programmed processor unit, a lexical answer type (LAT) string associated with an input query; automatically obtaining a candidate answer string to the input query from a data corpus; mapping the query LAT string to a first type string in a structured resource; mapping the candidate answer string to a second type string in the structured resource; and determining if the first type string and the second type string are disjointed; and scoring the candidate answer string based on the determination of the types being disjointed wherein the structured resource includes a semantic database providing ontological content.Type: ApplicationFiled: September 6, 2012Publication date: December 27, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, Aditya A. Kalyanpur, James W. Murdock, IV, Christopher A. Welty, Wlodek W. Zadrozny
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Publication number: 20120330882Abstract: A system and a computer program product for verifying a statement are provided. The system is configured to receive a statement. The system is configured to decompose the received statement into one or more sets of question and answer pairs. The system is configured to determine a confidence value of each answer in the one or more question and answer pair sets. The system is configured to combine the determined confidence values. The combined confidence values represent a probability that the received statement is evaluated as true.Type: ApplicationFiled: August 31, 2012Publication date: December 27, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally, Siddharth Patwardhan
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Publication number: 20120323906Abstract: A system, method and computer program product for automatically estimating the confidence of a detected LAT to provide a more accurate overall score for an obtained candidate answer. A confidence “score” or value of each detected LAT is obtained, and the system and method performs combining the confidence score with a degree of match between a LAT and an AnswerType of the candidate answer to provide improved overall score for the candidate answer.Type: ApplicationFiled: August 29, 2012Publication date: December 20, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: James J. Fan, David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally, James W. Murdock, Wlodek W. Zadrozny
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Publication number: 20120109859Abstract: Techniques for facilitating learning of one or more ontological rules of a resource description framework database are provided. The techniques include obtaining ontology vocabulary from a resource description framework database, generating a rule hypothesis by incrementally building upon a previously learnt rule from the database by adding one or more predicates to the previously learnt rule, performing a constraint check on the generated rule hypothesis by determining compatibility with each previously learnt rule to ensure that a complete rule set including each previously learnt rule and the generated rule hypothesis is consistent, validating the rule hypothesis as a rule using one or more association rule mining techniques to determine validity of the rule hypothesis against the database, and applying the rule to the database to infer one or more facts from the database to facilitate learning of one or more additional ontological rules.Type: ApplicationFiled: November 1, 2010Publication date: May 3, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Achille Fokoue, Aditya Kalyanpur, Kavitha Srinivas
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Publication number: 20120078890Abstract: A system, method and computer program product for automatically estimating the confidence of a detected LAT to provide a more accurate overall score for an obtained candidate answer. A confidence “score” or value of each detected LAT is obtained, and the system and method performs combining the confidence score with a degree of match between a LAT and an AnswerType of the candidate answer to provide improved overall score for the candidate answer.Type: ApplicationFiled: September 23, 2011Publication date: March 29, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: James J. Fan, David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally, James W. Murdock, Wlodek W. Zadrozny
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Publication number: 20120078636Abstract: Diffusing evidence among candidate answers during question answering may identify a relationship between a first candidate answer and a second candidate answer, wherein the candidate answers are generated by a question-answering computer process, the candidate answers have associated supporting evidence, and the candidate answers have associated confidence scores. All or some of the evidence may be transferred from the first candidate answer to the second candidate answer based on the identified relationship. A new confidence score may be computed for the second candidate answer based on the transferred evidence.Type: ApplicationFiled: September 23, 2011Publication date: March 29, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally
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Publication number: 20120078826Abstract: A system, a method and a computer program product for verifying a statement are provided. The system is configured to receive a statement. The system is configured to decompose the received statement into one or more sets of question and answer pairs. The system is configured to determine a confidence value of each answer in the one or more question and answer pair sets. The system is configured to combine the determined confidence values. The combined confidence values represent a probability that the received statement is evaluated as true.Type: ApplicationFiled: September 28, 2011Publication date: March 29, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, David C. Gondek, Aditya A. Kalyanpur, Adam P. Lally, Siddharth Patwardham
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Publication number: 20120078873Abstract: A computer-implemented system, method and program product generates answers to questions in an input query text string. The method includes determining, by a programmed processor unit, a lexical answer type (LAT) string associated with an input query; automatically obtaining a candidate answer string to the input query from a data corpus; mapping the query LAT string to a first type string in a structured resource; mapping the candidate answer string to a second type string in the structured resource; and determining if the first type string and the second type string are disjointed; and scoring the candidate answer string based on the determination of the types being disjointed wherein the structured resource includes a semantic database providing ontological content.Type: ApplicationFiled: September 24, 2011Publication date: March 29, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: David A. Ferrucci, Aditya A. Kalyanpur, James W. Murdock, IV, Christopher A. Welty, Wlodek W. Zadrozny
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Publication number: 20110282652Abstract: Methods, apparatus and systems, including computer program products, for reducing an error rate when mapping entities between a first ontology and a second ontology. One or more of a general language dictionary and an industry-specific dictionary are provided. Natural language processing of the first ontology is performed to identify one or more candidate relationship entities in the first ontology. Each candidate relationship entity includes a compound name having two or more semantic labels, and each candidate relationship entity has a name that neither exists in the general language dictionary or the industry-specific dictionary. Each of the one or more candidate relationship entities in the first ontology is mapped to one or more entities in the second ontology using one or more configurable computer-implemented mapping algorithms.Type: ApplicationFiled: May 14, 2010Publication date: November 17, 2011Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Achille B. Fokoue-Nkoutche, Aditya A. Kalyanpur, Kirill M. Osipov, Kavitha Srinivas, Min Wang