Patents by Inventor Bill Vasiliadis

Bill Vasiliadis 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).

  • SYSTEM, METHOD, AND COMPUTER PROGRAM FOR TESTING THE ACCURACY OF SOFTWARE THAT IDENTIFIES USER INTERFACE ELEMENTS ON A WEBPAGE
    Publication number: 20230419021
    Abstract: The present disclosure relates to a system, method, and computer program for testing the accuracy of software that identifies user interface (UI) elements on a webpage (“the auto-identifier software”). The system enables a user to tag UI elements on a webpage with labels. The system creates a normalized specification for the webpage, where the specification includes a mapping of UI elements to normalized labels. The system uses the auto-identifier software to identify UI elements on the webpage. The system evaluates the performance of the auto-identifier software with respect to the webpage using the specification. The system displays diagnostics related to the performance of the auto-identifier software. In certain embodiments, the method is used for testing the accuracy of autofill software on a webform. In certain embodiments, the method is used for testing the accuracy of cart-scraper software on a checkout page.
    Type: Application
    Filed: September 1, 2023
    Publication date: December 28, 2023
    Inventors: Dennis Hou, Bill Vasiliadis, Travis Coulter, Jae Jung, Adam Roth
  • System, method, and computer program for testing the accuracy of software that identifies user interface elements on a webpage
    Patent number: 11775740
    Abstract: The present disclosure relates to a system, method, and computer program for testing the accuracy of software that identifies user interface (UI) elements on a webpage (“the auto-identifier software”). The system enables a user to tag UI elements on a webpage with labels. The system creates a normalized specification for the webpage, where the specification includes a mapping of UI elements to normalized labels. The system uses the auto-identifier software to identify UI elements on the webpage. The system evaluates the performance of the auto-identifier software with respect to the webpage using the specification. The system displays diagnostics related to the performance of the auto-identifier software. In certain embodiments, the method is used for testing the accuracy of autofill software on a webform. In certain embodiments, the method is used for testing the accuracy of cart-scraper software on a checkout page.
    Type: Grant
    Filed: December 30, 2021
    Date of Patent: October 3, 2023
    Assignee: Rakuten Group, Inc.
    Inventors: Dennis Hou, Bill Vasiliadis, Travis Coulter, Jae Jung, Adam Roth
  • SYSTEM, METHOD, AND COMPUTER PROGRAM FOR TESTING THE ACCURACY OF SOFTWARE THAT IDENTIFIES USER INTERFACE ELEMENTS ON A WEBPAGE
    Publication number: 20230214585
    Abstract: The present disclosure relates to a system, method, and computer program for testing the accuracy of software that identifies user interface (UI) elements on a webpage (“the auto-identifier software”). The system enables a user to tag UI elements on a webpage with labels. The system creates a normalized specification for the webpage, where the specification includes a mapping of UI elements to normalized labels. The system uses the auto-identifier software to identify UI elements on the webpage. The system evaluates the performance of the auto-identifier software with respect to the webpage using the specification. The system displays diagnostics related to the performance of the auto-identifier software. In certain embodiments, the method is used for testing the accuracy of autofill software on a webform. In certain embodiments, the method is used for testing the accuracy of cart-scraper software on a checkout page.
    Type: Application
    Filed: December 30, 2021
    Publication date: July 6, 2023
    Inventors: Dennis Hou, Bill Vasiliadis, Travis Coulter, Jae Jung, Adam Roth