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http://dx.doi.org/10.14400/JDC.2017.15.4.461

Fuzzy-AHP Based Mobile Games Recommendation System Using Bayesian Network  

Oh, Jae-Taek (Dept. of Computer Science & Engineering, Kongju National University)
Lee, Sang-Yong (Div. of Computer Science & Engineering, Kongju National University)
Publication Information
Journal of Digital Convergence / v.15, no.4, 2017 , pp. 461-468 More about this Journal
Abstract
The current available recommendation systems for mobile games have a couple of problems. First, there is no knowing whether they make a pattern recommendation for games that actual users prefer or for games that they are simply interested in. It is also impossible to know the subjective preference of users in a direct manner. An AHP(Analytic Hierarchy Process)-based recommendation system for mobile games was thus developed to reflect the subjective preference of users directly, but it had its own problem since the degree of preference could vary among users in spite of the same scale for their preferable items. In an effort to solve those problems, this study implemented a recommendation system for mobile games by applying triangular fuzzy numbers of the Fuzzy-AHP technique and the independence of evaluation items in the Bayesian Network. The findings show that the proposed recommendation system recorded the highest accuracy of recommendation results and the highest level of user satisfaction.
Keywords
Fuzzy-Analytic Hierarchy Process; Bayesian Network; User Preference; Mobile Game; Recommendation System;
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Times Cited By KSCI : 3  (Citation Analysis)
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