Year: 2024
Type: article
Abstract: This paper introduces an innovative method for price comparison on e-commerce websites using Convolutional Neural Networks (CNNs). We discuss the importance of price comparison, highlight the flaws in manual methods, and examine the limitations of existing systems. Our CNN-based solution automates price extraction and analysis from various online retailers, streamlining cross-platform comparisons. By processing both textual and visual data, such as product descriptions and images, our approach improves accuracy. Real-time data updates enhance the user experience. Through rigorous testing, we demonstrate the effectiveness of our CNN-based solution, promising a superior shopping experience for e-commerce consumers.
Authors: Shaik Aslam Basha, Shaik Mohammed Ikram
Institution: Dr. M.G.R. Educational and Research Institute
Language: English
Topic: Web Data Mining and Analysis
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409686946