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

Publish Year: 1396
Type: Conference paper
Language: English
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RITCCCONF01_081

Index date: 30 September 2023

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

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.

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

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

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