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).

  • Patent number: 11816131
    Abstract: 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: Grant
    Filed: March 25, 2019
    Date of Patent: November 14, 2023
    Assignee: KYNDRYL, INC.
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Publication number: 20190220470
    Abstract: 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: Application
    Filed: March 25, 2019
    Publication date: July 18, 2019
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
  • Patent number: 10311086
    Abstract: 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: Grant
    Filed: March 15, 2016
    Date of Patent: June 4, 2019
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Publication number: 20160196328
    Abstract: 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: Application
    Filed: March 15, 2016
    Publication date: July 7, 2016
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
  • Patent number: 9336296
    Abstract: 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: Grant
    Filed: January 6, 2014
    Date of Patent: May 10, 2016
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Patent number: 8812297
    Abstract: 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: Grant
    Filed: April 9, 2010
    Date of Patent: August 19, 2014
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu R. Godbole, Ajay K. Gupta, Ashish Verma
  • Publication number: 20140122492
    Abstract: 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: Application
    Filed: January 6, 2014
    Publication date: May 1, 2014
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
  • Patent number: 8661039
    Abstract: 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: Grant
    Filed: April 2, 2012
    Date of Patent: February 25, 2014
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Patent number: 8655884
    Abstract: 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: Grant
    Filed: March 29, 2012
    Date of Patent: February 18, 2014
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Patent number: 8639696
    Abstract: 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: Grant
    Filed: March 28, 2012
    Date of Patent: January 28, 2014
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Patent number: 8589396
    Abstract: 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: Grant
    Filed: January 6, 2010
    Date of Patent: November 19, 2013
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Publication number: 20120197892
    Abstract: 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: Application
    Filed: March 29, 2012
    Publication date: August 2, 2012
    Applicant: International Business Machines Corporation
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
  • Publication number: 20120191712
    Abstract: 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: Application
    Filed: March 28, 2012
    Publication date: July 26, 2012
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
  • Publication number: 20120191713
    Abstract: 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: Application
    Filed: April 2, 2012
    Publication date: July 26, 2012
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
  • Patent number: 8229929
    Abstract: 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: Grant
    Filed: January 6, 2010
    Date of Patent: July 24, 2012
    Assignee: International Business Machines Corporation
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Jr., Shantanu R. Godbole, Sachindra Joshi, Ashwin Srinivasan, Ashish Verma
  • Publication number: 20110251839
    Abstract: 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: Application
    Filed: April 9, 2010
    Publication date: October 13, 2011
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Jeffrey M. Achtermann, Indrajit Bhattacharya, Kevin W. English, Shantanu Godbole, Ajay K. Gupta, Ashish Verma
  • Publication number: 20110167064
    Abstract: 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: Application
    Filed: January 6, 2010
    Publication date: July 7, 2011
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, Jr., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA
  • Publication number: 20110166850
    Abstract: 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: Application
    Filed: January 6, 2010
    Publication date: July 7, 2011
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: JEFFREY M. ACHTERMANN, INDRAJIT BHATTACHARYA, KEVIN W. ENGLISH, JR., SHANTANU R. GODBOLE, SACHINDRA JOSHI, ASHWIN SRINIVASAN, ASHISH VERMA