HCRS: A hybrid clothes recommender system based on user ratings and product features
This addresses the challenge of product discovery for online clothing shoppers, but appears incremental as it combines existing recommendation approaches.
The authors tackled the problem of helping online shoppers find clothing products by proposing a hybrid recommender system that combines user ratings and product features. Their experiments in a simulation environment showed the system better satisfies user needs.
Nowadays, online clothes-selling business has become popular and extremely attractive because of its convenience and cheap-and-fine price. Good examples of these successful Web sites include Yintai.com, Vancl.com and Shop.vipshop.com which provide thousands of clothes for online shoppers. The challenge for online shoppers lies on how to find a good product from lots of options. In this article, we propose a collaborative clothes recommender for easy shopping. One of the unique features of this system is the ability to recommend clothes in terms of both user ratings and clothing attributes. Experiments in our simulation environment show that the proposed recommender can better satisfy the needs of users.