System, method, and computer program for identifying order-related data on a webpage using machine learning

US12327276B2 · kind B2 · utility

Assignee

• Rakuten Group, Inc. · JP

Inventors

• Feng Xie · Shanghai, CN
• Jae Jung · Melbourne, AU
• Adam Roth · Sunshine Coast, AU
• Mujtaba Hussain · Melbourne, AU
• James Seymour-Lock · New York, US

Key dates

• Filing date: Sep 29, 2021
• Grant date: Jun 10, 2025
• Expiry date: May 6, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/0641
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

The present disclosure relates to a system, method, and computer program for identifying order-related data on a webpage using machine learning. The system identifies one or more HTML blocks on a webpage for further processing, where each HTML block includes one or more HTML tags that are each associated with metadata and a value. The system converts each of the HTML tags into a vector representation. The system applies a neural network model to each of the vector representations, resulting in another vector representation, which is converted into a machine-generated label prediction for each tag, where the neural network model is trained to predict labels, including order-related labels, corresponding to HTML tags. The system identifies order-related data on the webpage from the machine-generated label predictions for the HTML tags and the corresponding tag values. The system outputs the identified order-related data.