Patents by Inventor John A Hancock

John A Hancock 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).

  • Machine learning techniques for normalization of unstructured data into structured data
    Patent number: 12032590
    Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for classifying unstructured data by: (i) generating probability scores of natural language classification labels for classifying unstructured data elements using an NLP-based model, (ii) generating probability scores of structured data classification labels for classifying the unstructured data elements using a classification-based model, and (iii) assigning classifications labels based on: a) the probability scores of the natural language classification labels if a distance measure difference associated with the natural language classification labels is greater than a predetermined distance, or b) a determination using an ensemble model if the distance measure difference is less than a predetermined distance.
    Type: Grant
    Filed: December 28, 2022
    Date of Patent: July 9, 2024
    Assignee: Optum, Inc.
    Inventors: Abhay Shukla, Sarosh S Shetty, Swadeep Singh, John A Hancock
  • MACHINE LEARNING TECHNIQUES FOR NORMALIZATION OF UNSTRUCTURED DATA INTO STRUCTURED DATA
    Publication number: 20240220511
    Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for classifying unstructured data by: (i) generating probability scores of natural language classification labels for classifying unstructured data elements using an NLP-based model, (ii) generating probability scores of structured data classification labels for classifying the unstructured data elements using a classification-based model, and (iii) assigning classifications labels based on: a) the probability scores of the natural language classification labels if a distance measure difference associated with the natural language classification labels is greater than a predetermined distance, or b) a determination using an ensemble model if the distance measure difference is less than a predetermined distance.
    Type: Application
    Filed: December 28, 2022
    Publication date: July 4, 2024
    Inventors: Abhay Shukla, Sarosh S Shetty, Swadeep Singh, John A Hancock