Patents by Inventor Akshaya D. N

Akshaya D. N 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).

  • Dynamic detection of cross-document associations
    Patent number: 11915505
    Abstract: Systems, methods, and computer program products may be configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, for example, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.
    Type: Grant
    Filed: October 20, 2022
    Date of Patent: February 27, 2024
    Assignee: Optum Technology, Inc.
    Inventors: Swapna Sourav Rout, Sharlene L. Tan, Vamsi Bhandaru, Vineet Shukla, Akshaya D. N, Kartik Chaudhary
  • DYNAMIC DETECTION OF CROSS-DOCUMENT ASSOCIATIONS
    Publication number: 20230054624
    Abstract: Systems, methods, and computer program products may be configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, for example, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.
    Type: Application
    Filed: October 20, 2022
    Publication date: February 23, 2023
    Inventors: Swapna Sourav Rout, Sharlene L. Tan, Vamsi Bhandaru, Vineet Shukla, Akshaya D. N, Kartik Chaudhary
  • DYNAMIC DETECTION OF CROSS-DOCUMENT ASSOCIATIONS
    Publication number: 20220391451
    Abstract: Systems and methods are configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.
    Type: Application
    Filed: August 19, 2022
    Publication date: December 8, 2022
    Inventors: Swapna Sourav Rout, Sharlene L. Tan, Vamsi Bhandaru, Vineet Shukla, Akshaya D. N, Kartik Chaudhary
  • Dynamic detection of cross-document associations
    Patent number: 11508171
    Abstract: Systems and methods are configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.
    Type: Grant
    Filed: September 9, 2020
    Date of Patent: November 22, 2022
    Assignee: Optum Technology, Inc.
    Inventors: Swapna Sourav Rout, Sharlene L. Tan, Vamsi Bhandaru, Vineet Shukla, Akshaya D. N, Kartik Chaudhary
  • Dynamic detection of cross-document associations
    Patent number: 11455347
    Abstract: Systems and methods are configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.
    Type: Grant
    Filed: September 9, 2020
    Date of Patent: September 27, 2022
    Assignee: Optum Technology, Inc.
    Inventors: Swapna Sourav Rout, Sharlene L. Tan, Vamsi Bhandaru, Vineet Shukla, Akshaya D. N, Kartik Chaudhary
  • DYNAMIC DETECTION OF CROSS-DOCUMENT ASSOCIATIONS
    Publication number: 20220075831
    Abstract: Systems and methods are configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.
    Type: Application
    Filed: September 9, 2020
    Publication date: March 10, 2022
    Inventors: Swapna Sourav Rout, Sharlene L. Tan, Vamsi Bhandaru, Vineet Shukla, Akshaya D. N, Kartik Chaudhary
  • DYNAMIC DETECTION OF CROSS-DOCUMENT ASSOCIATIONS
    Publication number: 20220076007
    Abstract: Systems and methods are configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.
    Type: Application
    Filed: September 9, 2020
    Publication date: March 10, 2022
    Inventors: Swapna Sourav Rout, Sharlene L. Tan, Vamsi Bhandaru, Vineet Shukla, Akshaya D. N, Kartik Chaudhary