Toward Fashion-Brand Recommendation Systems Using Deep-Learning: Preliminary Analysis
Yuka Wakita, Kenta Oku, Kyoji Kawagoe · International Journal of Knowledge Engineering · 2016
Recently, the number of Electronic Commerce users has been rapidly increasing with the spread of the Internet.However, users cannot easily find their preferred clothes items among the enormous number on the Internet.As a method for solving this problem, we propose a fashion-brand recommendation system using a deep learning method.This system increases the likelihood that a user will find his/her favorite clothes items.The user must first determine his/her favorite fashion-brands.In this paper, we evaluate the effectiveness of using a deep learning method in a fashion-brand recommendation system.The preliminary analysis shows that the fashion-brand recommendation method using deep learning can dramatically improve the recommendation accuracy as compared with other machine learning methods.