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

عنوان مقاله: A hybrid fuzzy recommender system based on user-based and item-based collaborative filtering techniques
شناسه ملی مقاله: RITCCCONF01_081
منتشر شده در اولین کنفرانس بین المللی فناوری اطلاعات؛ دولت الکترونیک و شهر هوشمند در سال 1396
مشخصات نویسندگان مقاله:

Hamid Tabatabaee - Department of Computer Engineering, Quchan Branch, Islamic Azad University, Quchan, Iran
Fariborz Shokooh Saremi - Sama technical and vocational training college, Islamic Azad University, Mashhad Branch, Mashhad, Iran
Davood Shariat Panah - Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Hosein Salami - Department of Computer Engineering, Ferdows higher education institute, Mashhad, Iran

خلاصه مقاله:
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.

کلمات کلیدی:
Recommender system, Collaborative filtering, Fuzzy

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1770576/