Patents by Inventor Pranathi R. TUPAKULA

Pranathi R. TUPAKULA 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).

  • Generating structured data for rich experiences from unstructured data streams
    Patent number: 11797590
    Abstract: Aspects of the present disclosure are directed to providing a rich content experience based on information received from unstructured content. A plurality of information items may be obtained from a plurality of data source, where each information item includes unstructured content. The plurality of information items may be provided to a trained machine learning model, where the model is trained with training data that includes information items and corresponding labeled entities for a plurality of historical events. In examples, a formatted request may be received, where the formatted request is associated with one or more labeled entities associated with the trained machine learning model. The trained machine learning model may identify multiple entities from the unstructured content based on the formatted request associated with the one or more labeled entities. In examples, each identified entity of the multiple identified entities is stored as structured content responsive to the formatted request.
    Type: Grant
    Filed: January 5, 2021
    Date of Patent: October 24, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Pranathi R. Tupakula, Aman Singhal, Prithvishankar Srinivasan, Marcelo M. Debarros
  • GENERATING STRUCTURED DATA FOR RICH EXPERIENCES FROM UNSTRUCTURED DATA STREAMS
    Publication number: 20220067077
    Abstract: Aspects of the present disclosure are directed to providing a rich content experience based on information received from unstructured content. A plurality of information items may be obtained from a plurality of data source, where each information item includes unstructured content. The plurality of information items may be provided to a trained machine learning model, where the model is trained with training data that includes information items and corresponding labeled entities for a plurality of historical events. In examples, a formatted request may be received, where the formatted request is associated with one or more labeled entities associated with the trained machine learning model. The trained machine learning model may identify multiple entities from the unstructured content based on the formatted request associated with the one or more labeled entities. In examples, each identified entity of the multiple identified entities is stored as structured content responsive to the formatted request.
    Type: Application
    Filed: January 5, 2021
    Publication date: March 3, 2022
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Pranathi R. TUPAKULA, Aman SINGHAL, Prithvishankar SRINIVASAN, Marcelo M. DEBARROS