Patents by Inventor Nitin Hardeniya

Nitin Hardeniya 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).

  • Classifying unstructured computer text for complaint-specific interactions using rules-based and machine learning modeling
    Patent number: 10692016
    Abstract: Methods and apparatuses are described for analyzing unstructured computer text for identification and classification of complaint-specific interactions. A computer data stores unstructured text. A server computing device splits the unstructured text into phrases of words. The server generates a set of tokens from each phrase and removes tokens that are stopwords. The server generates a normalized sentiment score for each set of tokens. The server uses a rules-based classification engine to generate a rules-based complaint score for each set of tokens. The server uses an artificial intelligence machine learning model to generate a model-based complaint score for each set of tokens. The server determines determine whether each set of tokens corresponds to a complaint-specific interaction based upon the rules-based complaint score and the model-based complaint score.
    Type: Grant
    Filed: February 7, 2017
    Date of Patent: June 23, 2020
    Assignee: FMR LLC
    Inventors: Aravind Chandramouli, Nitin Hardeniya, Sunil Kumar
  • CLASSIFYING UNSTRUCTURED COMPUTER TEXT FOR COMPLAINT-SPECIFIC INTERACTIONS USING RULES-BASED AND MACHINE LEARNING MODELING
    Publication number: 20180225591
    Abstract: Methods and apparatuses are described for analyzing unstructured computer text for identification and classification of complaint-specific interactions. A computer data stores unstructured text. A server computing device splits the unstructured text into phrases of words. The server generates a set of tokens from each phrase and removes tokens that are stopwords. The server generates a normalized sentiment score for each set of tokens. The server uses a rules-based classification engine to generate a rules-based complaint score for each set of tokens. The server uses an artificial intelligence machine learning model to generate a model-based complaint score for each set of tokens. The server determines determine whether each set of tokens corresponds to a complaint-specific interaction based upon the rules-based complaint score and the model-based complaint score.
    Type: Application
    Filed: February 7, 2017
    Publication date: August 9, 2018
    Inventors: Aravind Chandramouli, Nitin Hardeniya, Sunil S. Kumar