An intelligent garment recommendation system based on case-based reasoning technology

Garment purchasing through the Internet has become an important trend for consumers. However, various garment e-shopping systems, systematically lack personalized recommendations, like sales advisors in classical shops, to propose the most relevant products to different consumers according to their consumer profiles and successful recommendation cases. In this paper, we propose a consumer-oriented recommendation system by Case-based reasoning techniques and Similarity degree of fuzzy sets, which can be used in a garment online shopping system like a virtual sales advisor. This system has been developed by integrating successful recommendation cases and taking into account consumer profiles. It can effectively help consumers to choose garments from the Internet. Compared with other prediction methods, the proposed method is more robust and interpretable owing to its capacity to treat uncertainty. This paper presents an original method for predicting one or several relevant product profiles from the similarity degree between a specific consumer profile and a successful cases database.