Improved recommender system using Neural Network Collaborative Filtering (NNCF) for E-commerce cosmetic product
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-co...
Saved in:
Main Authors: | Subhan Subhan, Deny Lukman Syarif, Endah Widhihastuti, Senda Kartika Rakainsa, Muhammad Sam'an, Yahya Nur Ifriza |
---|---|
Format: | Article |
Language: | English |
Published: |
Universitas Mercu Buana
2025-01-01
|
Series: | Jurnal Ilmiah SINERGI |
Subjects: | |
Online Access: | https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/26689 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Geographic recommender systems in e-commerce based on population
by: Mohamed Shili, et al.
Published: (2025-01-01) -
Impact Of Recommender Systems in E-Commerce – A Worldwide Empirical Analysis
by: Ayşe CILACI TOMBUS, et al.
Published: (2024-12-01) -
Product collaborative filtering based recommendation systems for large-scale E-commerce
by: Trang Trinh, et al.
Published: (2025-06-01) -
Publication trends and green cosmetics buying behaviour: A comprehensive bibliometric analysis
by: Mamta, et al.
Published: (2025-01-01) -
Exploration of Cosmetic Factors Contributing to Rhinoplasty among Both Genders in Iraqi Kurdistan
by: Aram Salih Mohammed Amin Kamali, et al.
Published: (2020-12-01)