Patents by Inventor Charles E. McManis, JR.
Charles E. McManis, JR. 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: 11295219Abstract: A technique for answering questions includes receiving a question directed to a first subject. A mathematical operation is performed between each of one or more first topic vectors (associated with the first subject) and each of one or more second topic vectors (associated with a second subject) to generate respective strength values. Relevant ones of the respective strength values are summed to provide an overall strength value, which is utilized to determine a semantic distance (SD) between the first subject and the second subject. In response to the SD being within a threshold distance value (TDV), information associated with the first subject and the second subject is utilized to answer the question. In response to the SD not being within the TDV, information associated with the first subject is utilized to answer the question.Type: GrantFiled: June 19, 2017Date of Patent: April 5, 2022Assignee: International Business Machines CorporationInventors: Jennifer Ann English, Malous Melissa Kossarian, Charles E. McManis, Jr., Douglas A. Smith
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Patent number: 10740377Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of documents associated with a predetermined subject, where each of the plurality of documents contains textual data, analyzing the textual data of each of the plurality of documents to identify one or more categories within the plurality of the documents, and returning the one or more categories identified within the plurality of the documents.Type: GrantFiled: October 16, 2018Date of Patent: August 11, 2020Assignee: International Business Machines CorporationInventors: Charles E. McManis, Jr., Douglas A. Smith
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Patent number: 10621219Abstract: A technique for calculating a semantic distance between subjects includes performing a mathematical operation between each of one or more first topic vectors and each of one or more second topic vectors to generate respective strength values. The first topic vectors are associated with respective first topics of a first subject, the second topic vectors are associated with respective second topics of a second subject, and the respective strength values are indicative of a relative closeness between associated ones of the first and second topics. Relevant ones of the respective strength values are summed to provide an overall strength value between the first subject and the second subject. A semantic distance between the first subject and the second subject is determined based on the overall strength value.Type: GrantFiled: February 10, 2017Date of Patent: April 14, 2020Assignee: International Business Machines CorporationInventors: Jennifer Ann English, Malous Melissa Kossarian, Charles E. McManis, Jr., Douglas A. Smith
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Patent number: 10599694Abstract: A technique for calculating a semantic distance between subjects includes performing a mathematical operation between each of one or more first topic vectors and each of one or more second topic vectors to generate respective strength values. The first topic vectors are associated with respective first topics of a first subject, the second topic vectors are associated with respective second topics of a second subject, and the respective strength values are indicative of a relative closeness between associated ones of the first and second topics. Relevant ones of the respective strength values are summed to provide an overall strength value between the first subject and the second subject. A semantic distance between the first subject and the second subject is determined based on the overall strength value.Type: GrantFiled: June 19, 2017Date of Patent: March 24, 2020Assignee: International Business Machines CorporationInventors: Jennifer Ann English, Malous Melissa Kossarian, Charles E. McManis, Jr., Douglas A. Smith
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Publication number: 20190121905Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of documents associated with a predetermined subject, where each of the plurality of documents contains textual data, analyzing the textual data of each of the plurality of documents to identify one or more categories within the plurality of the documents, and returning the one or more categories identified within the plurality of the documents.Type: ApplicationFiled: October 16, 2018Publication date: April 25, 2019Inventors: Charles E. McManis, Jr., Douglas A. Smith
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Patent number: 10242002Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve receiving a plurality of documents having a set of subjects extracted through the use of latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.Type: GrantFiled: August 1, 2016Date of Patent: March 26, 2019Assignee: International Business Machines CorporationInventors: Jennifer A. English, Malous M. Kossarian, Charles E. McManis, Jr., Douglas A. Smith
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Patent number: 10229184Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve ingesting a plurality of documents; extracting a set of subjects from the plurality of documents using latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.Type: GrantFiled: August 1, 2016Date of Patent: March 12, 2019Assignee: International Business Machines CorporationInventors: Jennifer A. English, Malous M. Kossarian, Charles E. McManis, Jr., Douglas A. Smith
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Patent number: 10157178Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of documents associated with a predetermined subject, where each of the plurality of documents contains textual data, analyzing the textual data of each of the plurality of documents to identify one or more categories within the plurality of the documents, and returning the one or more categories identified within the plurality of the documents.Type: GrantFiled: February 5, 2016Date of Patent: December 18, 2018Assignee: International Business Machines CorporationInventors: Charles E. McManis, Jr., Douglas A. Smith
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Publication number: 20180232437Abstract: A technique for calculating a semantic distance between subjects includes performing a mathematical operation between each of one or more first topic vectors and each of one or more second topic vectors to generate respective strength values. The first topic vectors are associated with respective first topics of a first subject, the second topic vectors are associated with respective second topics of a second subject, and the respective strength values are indicative of a relative closeness between associated ones of the first and second topics. Relevant ones of the respective strength values are summed to provide an overall strength value between the first subject and the second subject. A semantic distance between the first subject and the second subject is determined based on the overall strength value.Type: ApplicationFiled: February 10, 2017Publication date: August 16, 2018Inventors: JENNIFER ANN ENGLISH, MALOUS MELISSA KOSSARIAN, CHARLES E. MCMANIS, JR., DOUGLAS A. SMITH
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Publication number: 20180232623Abstract: A technique for answering questions includes receiving a question directed to a first subject. A mathematical operation is performed between each of one or more first topic vectors (associated with the first subject) and each of one or more second topic vectors (associated with a second subject) to generate respective strength values. Relevant ones of the respective strength values are summed to provide an overall strength value, which is utilized to determine a semantic distance (SD) between the first subject and the second subject. In response to the SD being within a threshold distance value (TDV), information associated with the first subject and the second subject is utilized to answer the question. In response to the SD not being within the TDV, information associated with the first subject is utilized to answer the question.Type: ApplicationFiled: February 10, 2017Publication date: August 16, 2018Inventors: JENNIFER ANN ENGLISH, MALOUS MELISSA KOSSARIAN, CHARLES E. MCMANIS, JR., DOUGLAS A. SMITH
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Publication number: 20180232380Abstract: A technique for calculating a semantic distance between subjects includes performing a mathematical operation between each of one or more first topic vectors and each of one or more second topic vectors to generate respective strength values. The first topic vectors are associated with respective first topics of a first subject, the second topic vectors are associated with respective second topics of a second subject, and the respective strength values are indicative of a relative closeness between associated ones of the first and second topics. Relevant ones of the respective strength values are summed to provide an overall strength value between the first subject and the second subject. A semantic distance between the first subject and the second subject is determined based on the overall strength value.Type: ApplicationFiled: June 19, 2017Publication date: August 16, 2018Inventors: JENNIFER ANN ENGLISH, MALOUS MELISSA KOSSARIAN, CHARLES E. MCMANIS, JR., DOUGLAS A. SMITH
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Publication number: 20180232624Abstract: A technique for answering questions includes receiving a question directed to a first subject. A mathematical operation is performed between each of one or more first topic vectors (associated with the first subject) and each of one or more second topic vectors (associated with a second subject) to generate respective strength values. Relevant ones of the respective strength values are summed to provide an overall strength value, which is utilized to determine a semantic distance (SD) between the first subject and the second subject. In response to the SD being within a threshold distance value (TDV), information associated with the first subject and the second subject is utilized to answer the question. In response to the SD not being within the TDV, information associated with the first subject is utilized to answer the question.Type: ApplicationFiled: June 19, 2017Publication date: August 16, 2018Inventors: JENNIFER ANN ENGLISH, MALOUS MELISSA KOSSARIAN, CHARLES E. MCMANIS, JR., DOUGLAS A. SMITH
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Publication number: 20180032517Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve receiving a plurality of documents having a set of subjects extracted through the use of latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.Type: ApplicationFiled: August 1, 2016Publication date: February 1, 2018Inventors: Jennifer A. English, Malous M. Kossarian, Charles E. McManis, JR., Douglas A. Smith
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Publication number: 20180032600Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve ingesting a plurality of documents; extracting a set of subjects from the plurality of documents using latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.Type: ApplicationFiled: August 1, 2016Publication date: February 1, 2018Inventors: Jennifer A. English, Malous M. Kossarian, Charles E. McManis, JR., Douglas A. Smith
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Publication number: 20160232226Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of documents associated with a predetermined subject, where each of the plurality of documents contains textual data, analyzing the textual data of each of the plurality of documents to identify one or more categories within the plurality of the documents, and returning the one or more categories identified within the plurality of the documents.Type: ApplicationFiled: February 5, 2016Publication date: August 11, 2016Inventors: Charles E. McManis, JR., Douglas A. Smith