Patents by Inventor Bhavani K. ESHWAR

Bhavani K. ESHWAR 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: 11477031
    Abstract: A blockchain may be used to store transactions in an immutable ledger. The types of transactions may vary and the information from the transactions could be used to identify information about nodes in a particular network. One example operation may include one or more of identifying a number of nodes operating on a blockchain, determining a new blockchain transaction, and determining one or more of the nodes as having one or more characteristics based on the new blockchain transaction.
    Type: Grant
    Filed: December 1, 2019
    Date of Patent: October 18, 2022
    Assignee: International Business Machines Corporation
    Inventors: Bhavani K. Eshwar, Subramanian B. Manjunath, Soma S. Naganna, Subramanian Palaniappan
  • Publication number: 20200106621
    Abstract: A blockchain may be used to store transactions in an immutable ledger. The types of transactions may vary and the information from the transactions could be used to identify information about nodes in a particular network. One example operation may include one or more of identifying a number of nodes operating on a blockchain, determining a new blockchain transaction, and determining one or more of the nodes as having one or more characteristics based on the new blockchain transaction.
    Type: Application
    Filed: December 1, 2019
    Publication date: April 2, 2020
    Inventors: Bhavani K. Eshwar, Subramanian B. Manjunath, Soma S. Naganna, Subramanian Palaniappan
  • Patent number: 10560268
    Abstract: A blockchain may be used to store transactions in an immutable ledger. The types of transactions may vary and the information from the transactions could be used to identify information about nodes in a particular network. One example operation may include one or more of identifying a number of nodes operating on a blockchain, determining a new blockchain transaction, and determining one or more of the nodes as having one or more characteristics based on the new blockchain transaction.
    Type: Grant
    Filed: February 13, 2017
    Date of Patent: February 11, 2020
    Assignee: International Business Machines Corporation
    Inventors: Bhavani K. Eshwar, Subramanian B. Manjunath, Soma S. Naganna, Subramanian Palaniappan
  • Patent number: 10353930
    Abstract: A computer-implemented method includes detecting an update to a record in an entity table of a database. At least one of an age score, a lineage score, and a completeness score for the record is calculated, responsive to the update. A trust factor is calculated, by a computer processor, based on the at least one of the age score, the lineage score, and the completeness score for the record. The trust factor indicates a level of trustworthiness of the record. It is decided whether to use data in the record based on the trust factor.
    Type: Grant
    Filed: August 31, 2016
    Date of Patent: July 16, 2019
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Bhavani K. Eshwar, Amit Malla, Soma S. Naganna, Umasuthan Ramakrishnan
  • Patent number: 10324981
    Abstract: Determination of a degree of similarity among and between a set of text notation schema instances. One type of text notation schema instance is the JSON type. In some embodiments, the degree of similarity is expressed as a schema variance value which is determined by individually comparing the schema instances of the set of text notation schema instances to a representative majority schema. Also, determining a quality of a data source associated with the plurality of text notation schema instances based, at least in part, upon the similarity value.
    Type: Grant
    Filed: October 13, 2015
    Date of Patent: June 18, 2019
    Assignee: International Business Machines Corporation
    Inventors: Phani Kumar V. U. Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Patent number: 10262037
    Abstract: An approach for joining operations on document-oriented databases. The approach consists of receiving database identifiers, common attributes and results attributes for core and target databases being joined. Common attributes are searched for in the databases. The searches performed include string, expansive, character and nested. Common attribute join conflicts are identified and input is received to resolve attribute join conflicts. Resolved join conflicts are updated in a join substitution database for subsequent use and joined data results are output to virtual table(s).
    Type: Grant
    Filed: October 19, 2015
    Date of Patent: April 16, 2019
    Assignee: International Business Machines Corporation
    Inventors: Phani Kumar V U Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Publication number: 20180232413
    Abstract: A blockchain may be used to store transactions in an immutable ledger. The types of transactions may vary and the information from the transactions could be used to identify information about nodes in a particular network. One example operation may include one or more of identifying a number of nodes operating on a blockchain, determining a new blockchain transaction, and determining one or more of the nodes as having one or more characteristics based on the new blockchain transaction.
    Type: Application
    Filed: February 13, 2017
    Publication date: August 16, 2018
    Inventors: Bhavani K. Eshwar, Subramanian B. Manjunath, Soma S. Naganna, Subramanian Palaniappan
  • Patent number: 9922240
    Abstract: In multilevel clustering for a face recognition process, the first stage clustering is performed on each computing node, using the first x vector coefficients. From the resulting k clusters created in the first stage, a limited number of clusters are selected on which the second stage clustering is performed, using the next y vector coefficients. The search for a matching image is then limited to these selected clusters. Computational costs are reduced at the first stage clustering by using just the first x vector coefficients. Computational costs for the second stage clustering are also reduced by performing the second stage only with the limited number of clusters on a limited number of computing nodes. In this manner, the overall computational costs in the face recognition process is significantly reduced while maintaining a desired level of accuracy.
    Type: Grant
    Filed: September 6, 2017
    Date of Patent: March 20, 2018
    Assignee: International Business Machines Corporation
    Inventors: Somnath Asati, Bhavani K. Eshwar, Soma Shekar Naganna, Abhishek Seth, Vishal Tomar
  • Patent number: 9916351
    Abstract: An approach for joining operations on document-oriented databases. The approach consists of receiving database identifiers, common attributes and results attributes for core and target databases being joined. Common attributes are searched for in the databases. The searches performed include string, expansive, character and nested. Common attribute join conflicts are identified and input is received to resolve attribute join conflicts. Resolved join conflicts are updated in a join substitution database for subsequent use and joined data results are output to virtual table(s).
    Type: Grant
    Filed: December 12, 2016
    Date of Patent: March 13, 2018
    Assignee: International Business Machines Corporation
    Inventors: Phani Kumar V U Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Patent number: 9916360
    Abstract: An approach for joining operations on document-oriented databases. The approach consists of receiving database identifiers, common attributes and results attributes for core and target databases being joined. Common attributes are searched for in the databases. The searches performed include string, expansive, character and nested. Common attribute join conflicts are identified and input is received to resolve attribute join conflicts. Resolved join conflicts are updated in a join substitution database for subsequent use and joined data results are output to virtual table(s).
    Type: Grant
    Filed: December 13, 2016
    Date of Patent: March 13, 2018
    Assignee: International Business Machines Corporation
    Inventors: Phani Kumar V U Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Publication number: 20180060370
    Abstract: A computer-implemented method includes detecting an update to a record in an entity table of a database. At least one of an age score, a lineage score, and a completeness score for the record is calculated, responsive to the update. A trust factor is calculated, by a computer processor, based on the at least one of the age score, the lineage score, and the completeness score for the record. The trust factor indicates a level of trustworthiness of the record. It is decided whether to use data in the record based on the trust factor.
    Type: Application
    Filed: August 31, 2016
    Publication date: March 1, 2018
    Inventors: Bhavani K. Eshwar, Amit Malla, Soma S. Naganna, Umasuthan Ramakrishnan
  • Patent number: 9904844
    Abstract: In multilevel clustering for a face recognition process, the first stage clustering is performed on each computing node, using the first x vector coefficients. From the resulting k clusters created in the first stage, a limited number of clusters are selected on which the second stage clustering is performed, using the next y vector coefficients. The search for a matching image is then limited to these selected clusters. Computational costs are reduced at the first stage clustering by using just the first x vector coefficients. Computational costs for the second stage clustering are also reduced by performing the second stage only with the limited number of clusters on a limited number of computing nodes. In this manner, the overall computational costs in the face recognition process is significantly reduced while maintaining a desired level of accuracy.
    Type: Grant
    Filed: August 4, 2016
    Date of Patent: February 27, 2018
    Assignee: International Business Machines Corporation
    Inventors: Somnath Asati, Bhavani K. Eshwar, Soma Shekar Naganna, Abhishek Seth, Vishal Tomar
  • Publication number: 20180039823
    Abstract: In multilevel clustering for a face recognition process, the first stage clustering is performed on each computing node, using the first x vector coefficients. From the resulting k clusters created in the first stage, a limited number of clusters are selected on which the second stage clustering is performed, using the next y vector coefficients. The search for a matching image is then limited to these selected clusters. Computational costs are reduced at the first stage clustering by using just the first x vector coefficients. Computational costs for the second stage clustering are also reduced by performing the second stage only with the limited number of clusters on a limited number of computing nodes. In this manner, the overall computational costs in the face recognition process is significantly reduced while maintaining a desired level of accuracy.
    Type: Application
    Filed: August 4, 2016
    Publication date: February 8, 2018
    Inventors: Somnath ASATI, Bhavani K. ESHWAR, Soma Shekar NAGANNA, Abhishek SETH, Vishal TOMAR
  • Publication number: 20180039824
    Abstract: In multilevel clustering for a face recognition process, the first stage clustering is performed on each computing node, using the first x vector coefficients. From the resulting k clusters created in the first stage, a limited number of clusters are selected on which the second stage clustering is performed, using the next y vector coefficients. The search for a matching image is then limited to these selected clusters. Computational costs are reduced at the first stage clustering by using just the first x vector coefficients. Computational costs for the second stage clustering are also reduced by performing the second stage only with the limited number of clusters on a limited number of computing nodes. In this manner, the overall computational costs in the face recognition process is significantly reduced while maintaining a desired level of accuracy.
    Type: Application
    Filed: September 6, 2017
    Publication date: February 8, 2018
    Inventors: Somnath ASATI, Bhavani K. ESHWAR, Soma Shekar NAGANNA, Abhishek SETH, Vishal TOMAR
  • Publication number: 20170109404
    Abstract: An approach for joining operations on document-oriented databases. The approach consists of receiving database identifiers, common attributes and results attributes for core and target databases being joined. Common attributes are searched for in the databases. The searches performed include string, expansive, character and nested. Common attribute join conflicts are identified and input is received to resolve attribute join conflicts. Resolved join conflicts are updated in a join substitution database for subsequent use and joined data results are output to virtual table(s).
    Type: Application
    Filed: October 19, 2015
    Publication date: April 20, 2017
    Inventors: Phani Kumar V U Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Publication number: 20170109407
    Abstract: An approach for joining operations on document-oriented databases. The approach consists of receiving database identifiers, common attributes and results attributes for core and target databases being joined. Common attributes are searched for in the databases. The searches performed include string, expansive, character and nested. Common attribute join conflicts are identified and input is received to resolve attribute join conflicts. Resolved join conflicts are updated in a join substitution database for subsequent use and joined data results are output to virtual table(s).
    Type: Application
    Filed: December 13, 2016
    Publication date: April 20, 2017
    Inventors: Phani Kumar V U Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Publication number: 20170109405
    Abstract: An approach for joining operations on document-oriented databases. The approach consists of receiving database identifiers, common attributes and results attributes for core and target databases being joined. Common attributes are searched for in the databases. The searches performed include string, expansive, character and nested. Common attribute join conflicts are identified and input is received to resolve attribute join conflicts. Resolved join conflicts are updated in a join substitution database for subsequent use and joined data results are output to virtual table(s).
    Type: Application
    Filed: December 12, 2016
    Publication date: April 20, 2017
    Inventors: Phani Kumar V. U. Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Publication number: 20170102923
    Abstract: Determination of a degree of similarity among and between a set of text notation schema instances. One type of text notation schema instance is the JSON type. In some embodiments, the degree of similarity is expressed as a schema variance value which is determined by individually comparing the schema instances of the set of text notation schema instances to a representative majority schema. Also, determining a quality of a data source associated with the plurality of text notation schema instances based, at least in part, upon the similarity value.
    Type: Application
    Filed: October 13, 2015
    Publication date: April 13, 2017
    Inventors: Phani Kumar V. U. Ayyagari, Manish A. Bhide, Bhavani K. Eshwar, Purnachandra R. Jasti
  • Patent number: 9529830
    Abstract: A computer-implemented method includes receiving a column-oriented table comprising data for a column family, wherein the data for the column family comprises column names and corresponding column values, receiving a set of anonymous column names for the column family, receiving a set of synonymous column names for the column family, determining a weighting for each column name that is not an anonymous column name based on the count or frequency of occurrence of the column name and the synonymous column names within the column-oriented table, and processing the column-oriented table with a probabilistic matching engine using the weighting for each column name. A corresponding computer program product and computer system are also disclosed herein.
    Type: Grant
    Filed: January 28, 2016
    Date of Patent: December 27, 2016
    Assignee: International Business Machines Corporation
    Inventors: Bhavani K. Eshwar, Soma Shekar Naganna, Umasuthan Ramakrishnan, Shashidhar R. Yellareddy
  • Patent number: 9471403
    Abstract: Granular event management for service platforms. First bundle information relating to the content of a bundle is received at a first time, wherein the bundle relates to one or more resources in an application of a distributed computing environment. The bundle is monitored for a bundle event, wherein the bundle event is generated from a change in a lifecycle state of the bundle. Whether the bundle event has occurred is determined. Responsive to determining that the bundle event has occurred, second bundle information relating to the content of the bundle is received at a second time. Responsive to receiving the second bundle information, a granular event associated with the bundle event is identified, wherein the granular event relates to a difference between the first bundle information and the second bundle information.
    Type: Grant
    Filed: May 2, 2016
    Date of Patent: October 18, 2016
    Assignee: International Business Machines Corporation
    Inventors: Bhavani K. Eshwar, Soma Shekar Naganna, Umasuthan Ramakrishnan, Joseph Xaviour