Patents by Inventor Madhvi Gupta

Madhvi Gupta 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).

  • Extracting joint topic-sentiment models from text inputs
    Patent number: 11238243
    Abstract: There is a need for solutions for more effective and efficient natural language processing systems for short texts. This need can be addressed, for example, by a system configured to obtain an initial term-topic correlation data object for a plurality of digital documents, obtain a user-defined term-topic correlation data object for the plurality of digital documents, generate a refined term-topic correlation data object and a refined document-sentiment correlation data object for the plurality of digital documents based at least in part on the initial term-topic correlation data object and the user-defined term-topic correlation data object, obtain a user-defined document-topic correlation data object for the plurality of digital documents, and generate a refined document-topic correlation object for the plurality of digital documents based at least in part on the refined term-topic correlation data object and the user-defined document-topic correlation data object.
    Type: Grant
    Filed: September 27, 2019
    Date of Patent: February 1, 2022
    Assignee: Optum Technology, Inc.
    Inventors: Suman Roy, Malladi Vijay Varma, Siddhartha Asthana, Madhvi Gupta, Ashish Chaturvedi
  • EXTRACTING JOINT TOPIC-SENTIMENT MODELS FROM TEXT INPUTS
    Publication number: 20210097145
    Abstract: There is a need for solutions for more effective and efficient natural language processing systems for short texts. This need can be addressed, for example, by a system configured to obtain an initial term-topic correlation data object for a plurality of digital documents, obtain a user-defined term-topic correlation data object for the plurality of digital documents, generate a refined term-topic correlation data object and a refined document-sentiment correlation data object for the plurality of digital documents based at least in part on the initial term-topic correlation data object and the user-defined term-topic correlation data object, obtain a user-defined document-topic correlation data object for the plurality of digital documents, and generate a refined document-topic correlation object for the plurality of digital documents based at least in part on the refined term-topic correlation data object and the user-defined document-topic correlation data object.
    Type: Application
    Filed: September 27, 2019
    Publication date: April 1, 2021
    Inventors: Suman Roy, Malladi Vijay Varma, Siddhartha Asthana, Madhvi Gupta, Ashish Chaturvedi