Patents by Inventor Suresh Nalliakodan

Suresh Nalliakodan 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).

  • Automated analysis of unstructured computer text for generation of an enforcement action database using machine learning
    Patent number: 11893033
    Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for generation of an enforcement action database. A computing device receives a digital document comprising a corpus of unstructured text and converts each sentence into tokens. The computing device identifies entities in the tokens and classifies each sentence as relevant or not relevant to an enforcement action. For each relevant sentence, the computing device generates a record in a first data structure and generates a record in a second data structure. The computing device maps the records in the first data structure to the records in the second data structure based upon an enforcement attribute to generate a third data structure. The computing device aggregates the records in the third data structure based upon a name of the entity and a type of the entity in the sentence to determine an aggregated first enforcement attribute for each entity.
    Type: Grant
    Filed: March 1, 2022
    Date of Patent: February 6, 2024
    Assignee: FMR LLC
    Inventors: Suresh Nalliakodan, Deepak Venkatachalapathi, Dmitry Bisikalo, Rijesh Panicker, Seth Brooks, Sharon Botwinik
  • AUTOMATED ANALYSIS OF UNSTRUCTURED COMPUTER TEXT FOR GENERATION OF AN ENFORCEMENT ACTION DATABASE USING MACHINE LEARNING
    Publication number: 20230281208
    Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for generation of an enforcement action database. A computing device receives a digital document comprising a corpus of unstructured text and converts each sentence into tokens. The computing device identifies entities in the tokens and classifies each sentence as relevant or not relevant to an enforcement action. For each relevant sentence, the computing device generates a record in a first data structure and generates a record in a second data structure. The computing device maps the records in the first data structure to the records in the second data structure based upon an enforcement attribute to generate a third data structure. The computing device aggregates the records in the third data structure based upon a name of the entity and a type of the entity in the sentence to determine an aggregated first enforcement attribute for each entity.
    Type: Application
    Filed: March 1, 2022
    Publication date: September 7, 2023
    Inventors: Suresh Nalliakodan, Deepak Venkatachalapathi, Dmitry Bisikalo, Rijesh Panicker, Seth Brooks, Sharon Botwinik