Patents by Inventor Mayuresh ANAND

Mayuresh ANAND 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).

  • Utilizing machine learning models and in-domain and out-of-domain data distribution to predict a causality relationship between events expressed in natural language text
    Patent number: 11797776
    Abstract: A device may receive training data that includes datasets associated with natural language processing, and may mask the training data to generate masked training data. The device may train a masked event C-BERT model, with the masked training data, to generate pretrained weights and a trained masked event C-BERT model, and may train an event aware C-BERT model, with the training data and the pretrained weights, to generate a trained event aware C-BERT model. The device may receive natural language text data identifying natural language events, and may process the natural language text data, with the trained masked event C-BERT model, to determine weights. The device may process the natural language text data and the weights, with the trained event aware C-BERT model, to predict causality relationships between the natural language events, and may perform actions, based on the causality relationships.
    Type: Grant
    Filed: January 19, 2021
    Date of Patent: October 24, 2023
    Assignee: Accenture Global Solutions Limited
    Inventors: Vivek Kumar Khetan, Mayuresh Anand, Roshni Ramesh Ramnani, Shubhashis Sengupta, Andrew E. Fano
  • UTILIZING MACHINE LEARNING MODELS AND IN-DOMAIN AND OUT-OF-DOMAIN DATA DISTRIBUTION TO PREDICT A CAUSALITY RELATIONSHIP BETWEEN EVENTS EXPRESSED IN NATURAL LANGUAGE TEXT
    Publication number: 20220075953
    Abstract: A device may receive training data that includes datasets associated with natural language processing, and may mask the training data to generate masked training data. The device may train a masked event C-BERT model, with the masked training data, to generate pretrained weights and a trained masked event C-BERT model, and may train an event aware C-BERT model, with the training data and the pretrained weights, to generate a trained event aware C-BERT model. The device may receive natural language text data identifying natural language events, and may process the natural language text data, with the trained masked event C-BERT model, to determine weights. The device may process the natural language text data and the weights, with the trained event aware C-BERT model, to predict causality relationships between the natural language events, and may perform actions, based on the causality relationships.
    Type: Application
    Filed: January 19, 2021
    Publication date: March 10, 2022
    Inventors: Vivek Kumar KHETAN, Mayuresh ANAND, Roshni Ramesh RAMNANI, Shubhashis SENGUPTA, Andrew E. FANO