ENHANCING E-COMMERCE COMPETITIVENESS: CNN-BASED PRICE COMPSRISON APPLICATION

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.

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Publication Details

Journal
International Journal of Engineering Research and Sustainable Technologies (IJERST)
Published
2024-12-25
DOI
https://doi.org/10.63458/ijerst.v2i4.95
Primary Topic
Consumer Market Behavior and Pricing
Type
article
Field-Weighted Citation Impact
0.00
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article

ENHANCING E-COMMERCE COMPETITIVENESS: CNN-BASED PRICE COMPSRISON APPLICATION

S. M. M. Ikram, Shaik Aslam Basha
1 links
International Journal of Engineering Research and Sustainable Technologies (IJERST)
Consumer Market Behavior and Pricing
article

ENHANCING E-COMMERCE COMPETITIVENESS: CNN-BASED PRICE COMPSRISON APPLICATION

S. M. M. Ikram, Shaik Aslam Basha
article en

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.

International Journal of Engineering Research and Sustainable Technologies (IJERST)Vol. 2(4)
Dr. M.G.R. Educational and Research Institute (IN)
Openalex Percentile: Top 58%
Consumer Market Behavior and Pricing
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