A hybrid fuzzy recommender system based on user-based and item-based collaborative filtering techniques

Recommender systems are special type of information systems that help decision makers to select suitable products based on their preferences and interests. Recommender systems have been used in various domains like books, movies, music, news and articles to offer personalized recommendations. Because of different uncertainties in customers and products information, achieving high accuracy in recommendation is a challenging issue. This study proposes a hybrid recommendation approach which combines user-based and content-based collaborative filtering techniques with fuzzy set techniques to achieve better results. Experimental results confirm the effectiveness of proposed approach to help users selecting best products and services.

Keywords:

Recommender system , Collaborative filtering , Fuzzy