پديدآورندگان :
Tabatabaee Hamid hosein.salami@gmail.com Department of Computer Engineering, Quchan Branch, Islamic Azad University, Quchan, Iran , shokooh saremi Fariborz hosein.salami@gmail.com Sama technical and vocational training college, Islamic Azad University, Mashhad Branch, Mashhad, Iran , Shariat panah Davood hosein.salami@gmail.com Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran , Salami Hosein hosein.salami@gmail.com Department of Computer Engineering, Ferdows higher education institute, Mashhad, Iran
چكيده فارسي :
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.
