Work

Recommender System for Apparel Products Based on Image Recognition Using Convolutional Neural Networks

Year: 2025

Type: conference-paper

Abstract: In e-commerce and fashion, personalized recommendations are used to enhance user experience and engagement. In this study, an apparel recognition and recommender system (ARRS) using convolutional neural networks (CNNs) was employed to analyze apparel images, extract features, and provide accurate recognition and recommendations. By learning patterns and features of clothes, the system enables robust recognition and personalized suggestions. The effectiveness of ARRS in recognizing apparel and generating relevant recommendations was validated. The system enhances user satisfaction and engagement on fashion e-commerce platforms.

Source: IEEE International Conference on Knowledge Innovation and Invention (ICKII)

DOI: 10.3390/engproc2025089038

Authors: Chin-Chih Chang, Chi-Hung Wei, Yen-Hsiang Wang, Chyuan-Huei Thomas Yang, Sean Hsiao

Institutions: Chung Hua University, Shandong Vocational and Technical University of International Studies, Ming Chuan University

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4408466695

FWCI: 2.35

Cites: 17

Cited by: 2

Related to: 10