Improved recommender system using Neural Network Collaborative Filtering (NNCF) for E-commerce cosmetic product - Subhan, Subhan; Syarif, Deny Lukman; Widhihastuti, Endah; Rakainsa, Senda Kartika; Sam'an, Muhammad; Ifriza, Yahya Nur (Universitas Mercu Buana, 2025)
This study presents an enhanced recommender system tailored for e-commerce platforms specializing in cosmetic products. Traditional recommender systems often need help providing accurate and personalized recommendations due to the complexity and subjectivity inherent in cosmetic preferences. In e-commerce, personalized product recommendations are crucial to improving user engagement and driving sales. This paper presents an innovative approach to enhance recommendation systems by leveraging neural network collaborative filtering techniques for the cosmetic product domain. The proposed method integrates neural networks into collaborative filtering, namely neural network collaborative filtering with improved preprocessing step. To validate the effectiveness of our proposed system, extensive experiments were conducted using real-world e-commerce cosmetic datasets