1
Faculty of Computer Engineering and Information Technology, Sadjad University of Technology, Mashhad, Iran
2
Faculty of Industrial Engineering, Sadjad University of Technology, Mashhad, Iran
Abstract
Today, recommender systems, according to their special performance, are widely utilized in several scientific issues. Fuzzy recommender systems are the type of systems in which they are combined with fuzzy theory and give more flexibility to recommender systems. Nonetheless, in this article a new combination method from fuzzy rough set collaborative filtering is presented in which the distance is calculated based on Euclidean distance measure. In fact, by using fuzzy rough sets the applicants’ data are used regarding to have better prediction. This combination method via fuzzy rough sets increases the accuracy of prediction. Since, implemented experiments on test data depict recommended method has better validation in comparison with other reputed methods.
Hamidzadeh, J., & Sadeghzadeh, M. (2017). A User Based Fuzzy Rough Collaborative Filtering in Recommender Systems. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 47(2), 491-500.
MLA
J. Hamidzadeh; M. Sadeghzadeh. "A User Based Fuzzy Rough Collaborative Filtering in Recommender Systems". TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 47, 2, 2017, 491-500.
HARVARD
Hamidzadeh, J., Sadeghzadeh, M. (2017). 'A User Based Fuzzy Rough Collaborative Filtering in Recommender Systems', TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 47(2), pp. 491-500.
VANCOUVER
Hamidzadeh, J., Sadeghzadeh, M. A User Based Fuzzy Rough Collaborative Filtering in Recommender Systems. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 2017; 47(2): 491-500.
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