Patents by Inventor Thea LEE

Thea LEE 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).

  • Computer-implemented method, non-transitory computer readable storage medium, and system for enhancing listings in an e-commerce site
    Patent number: 12639739
    Abstract: Embodiments described herein include modeling of seller profiles and behaviors on an e-commerce site to induce more listings and sales within the e-commerce site. For every seller and potential seller on the e-commerce site, their behaviors is to be understood and modeled in order to draw out more listings and completed sales per seller. An example embodiment of the present disclosure includes receiving a first information listing. At least one classification of the information listing may be generated performing at least one machine-learning (ML) process based at least in part on at least one ML model and the first information listing. A recommendation based on the classification of the first information listing may be generated. The recommendation may be recommending. A second information listing may be created.
    Type: Grant
    Filed: September 28, 2022
    Date of Patent: May 26, 2026
    Assignee: MERCARI, INC.
    Inventors: Byong Mok Oh, Hayato Ryuki, Ajay Daptardar, Thea Lee, Colin Smith
  • ITEM MATCHING AND PRICING BASED ON HISTORICAL PRICING DATA AND CLASSIFICATION OF PARTIES TO RELATED TRANSACTIONS
    Publication number: 20240104626
    Abstract: Embodiments described herein include modeling of seller profiles and behaviors on an e-commerce site to induce more listings and sales within the e-commerce site. For every seller and potential seller on the e-commerce site, their behaviors is to be understood and modeled in order to draw out more listings and completed sales per seller. An example embodiment of the present disclosure includes receiving a first information listing. At least one classification of the information listing may be generated performing at least one machine-learning (ML) process based at least in part on at least one ML model and the first information listing. A recommendation based on the classification of the first information listing may be generated. The recommendation may be recommending. A second information listing may be created.
    Type: Application
    Filed: September 28, 2022
    Publication date: March 28, 2024
    Inventors: Byong Mok OH, Hayato RYUKI, Ajay DAPTARDER, Thea LEE, Colin SMITH