Patents by Inventor Manirupa Das

Manirupa Das 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).

  • Concept discovery from text via knowledge transfer
    Patent number: 11803583
    Abstract: Documents from a set of related documents in a domain are processed to identify keywords associated with each document. The documents are then further processed to identify the documents that are the most similar to each other. For each document, some or all of the keywords that are associated with the similar documents, but not the document itself, are selected as semantic tags for the document. These semantic tags determined for a document represent novel or hidden concepts and contexts that may relate to the document, but that do not actually appear in the document. The documents are used to train a model that generate semantic tags for a document or for keywords associated with the document. The generated model can then be used for a variety of purposes such the creation of an index for a set of documents or for query expansion.
    Type: Grant
    Filed: November 5, 2020
    Date of Patent: October 31, 2023
    Assignee: Ohio State Innovation Foundation
    Inventors: Manirupa Das, Rajiv Ramnath, John Eric Fosler-Lussier
  • CONCEPT DISCOVERY FROM TEXT VIA KNOWLEDGE TRANSFER
    Publication number: 20210141823
    Abstract: Documents from a set of related documents in a domain are processed to identify keywords associated with each document. The documents are then further processed to identify the documents that are the most similar to each other. For each document, some or all of the keywords that are associated with the similar documents, but not the document itself, are selected as semantic tags for the document. These semantic tags determined for a document represent novel or hidden concepts and contexts that may relate to the document, but that do not actually appear in the document. The documents are used to train a model that generate semantic tags for a document or for keywords associated with the document. The generated model can then be used for a variety of purposes such the creation of an index for a set of documents or for query expansion.
    Type: Application
    Filed: November 5, 2020
    Publication date: May 13, 2021
    Inventors: Manirupa Das, Rajiv Ramnath, John Eric Fosler-Lussier