Patents by Inventor Kevin W. English
Kevin W. English 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: 11816131Abstract: A method and system. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by a target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of a source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability. The cross-domain clusterability is transferred to a device.Type: GrantFiled: March 25, 2019Date of Patent: November 14, 2023Assignee: KYNDRYL, INC.Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Publication number: 20190220470Abstract: A method and system. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by a target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of a source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability. The cross-domain clusterability is transferred to a device.Type: ApplicationFiled: March 25, 2019Publication date: July 18, 2019Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
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Patent number: 10311086Abstract: A method and system. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by a target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of a source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability. The cross-domain clusterability is transferred to a device.Type: GrantFiled: March 15, 2016Date of Patent: June 4, 2019Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Publication number: 20160196328Abstract: A method and system. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by a target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of a source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability. The cross-domain clusterability is transferred to a device.Type: ApplicationFiled: March 15, 2016Publication date: July 7, 2016Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
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Patent number: 9336296Abstract: A method and system for evaluating cross-domain clusterability upon a target domain and a source domain. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by the target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of the source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability.Type: GrantFiled: January 6, 2014Date of Patent: May 10, 2016Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Patent number: 8812297Abstract: Determining synonyms of words in a set of documents. Particularly, when provided with a word or phrase as input, in exemplary embodiments there is afforded the return of a predetermined number of “top” synonym words (or phrases) for an input word (or phrase) in a specific collection of text documents. Further, a user is able to provide ongoing and iterative positive or negative feedback on the returned synonym words, by manually accepting or rejecting such words as the process is underway.Type: GrantFiled: April 9, 2010Date of Patent: August 19, 2014Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu R. Godbole, Ajay K. Gupta, Ashish Verma
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Publication number: 20140122492Abstract: A method and system for evaluating cross-domain clusterability upon a target domain and a source domain. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by the target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of the source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability.Type: ApplicationFiled: January 6, 2014Publication date: May 1, 2014Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
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Patent number: 8661039Abstract: A process for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: GrantFiled: April 2, 2012Date of Patent: February 25, 2014Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Patent number: 8655884Abstract: A computer system for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: GrantFiled: March 29, 2012Date of Patent: February 18, 2014Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Patent number: 8639696Abstract: A computer program product evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: GrantFiled: March 28, 2012Date of Patent: January 28, 2014Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Patent number: 8589396Abstract: A system and associated method for cross-guided data clustering by aligning target clusters in a target domain to source clusters in a source domain. The cross-guided clustering process takes the target domain and the source domain as inputs. A common word attribute shared by both the target domain and the source domain is a pivot vocabulary, and all other words in both domains are a non-pivot vocabulary. The non-pivot vocabulary is projected onto the pivot vocabulary to improve measurement of similarity between data items. Source centroids representing clusters in the source domain are created and projected to the pivot vocabulary. Target centroids representing clusters in the target domain are initially created by conventional clustering method and then repetitively aligned to converge with the source centroids by use of a cross-domain similarity graph that measures a respective similarity of each target centroid to each source centroid.Type: GrantFiled: January 6, 2010Date of Patent: November 19, 2013Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Publication number: 20120197892Abstract: A computer system for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: ApplicationFiled: March 29, 2012Publication date: August 2, 2012Applicant: International Business Machines CorporationInventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
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Publication number: 20120191712Abstract: A computer program product evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: ApplicationFiled: March 28, 2012Publication date: July 26, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
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Publication number: 20120191713Abstract: A process for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source- target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: ApplicationFiled: April 2, 2012Publication date: July 26, 2012Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
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Patent number: 8229929Abstract: A system and associated method for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: GrantFiled: January 6, 2010Date of Patent: July 24, 2012Assignee: International Business Machines CorporationInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
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Publication number: 20110251839Abstract: Determining synonyms of words in a set of documents. Particularly, when provided with a word or phrase as input, in exemplary embodiments there is afforded the return of a predetermined number of “top” synonym words (or phrases) for an input word (or phrase) in a specific collection of text documents. Further, a user is able to provide ongoing and iterative positive or negative feedback on the returned synonym words, by manually accepting or rejecting such words as the process is underway.Type: ApplicationFiled: April 9, 2010Publication date: October 13, 2011Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu Godbole, Ajay K. Gupta, Ashish Verma
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Publication number: 20110167064Abstract: A system and associated method for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively.Type: ApplicationFiled: January 6, 2010Publication date: July 7, 2011Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, Jr., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
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Publication number: 20110166850Abstract: A system and associated method for cross-guided data clustering by aligning target clusters in a target domain to source clusters in a source domain. The cross-guided clustering process takes the target domain and the source domain as inputs. A common word attribute shared by both the target domain and the source domain is a pivot vocabulary, and all other words in both domains are a non-pivot vocabulary. The non-pivot vocabulary is projected onto the pivot vocabulary to improve measurement of similarity between data items. Source centroids representing clusters in the source domain are created and projected to the pivot vocabulary. Target centroids representing clusters in the target domain are initially created by conventional clustering method and then repetitively aligned to converge with the source centroids by use of a cross-domain similarity graph that measures a respective similarity of each target centroid to each source centroid.Type: ApplicationFiled: January 6, 2010Publication date: July 7, 2011Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA