Using Fuzzy Association Rules to Design E-commerce Personalized Recommendation System - Guofang Kuang; Yuanchen Li (Institute of Advanced Engineering and Science, 2014)
In order to improve the efficiency of fuzzy association rule mining, the paper defines the redundant fuzzy association rules, and strong fuzzy association rules redundant nature. As much as possible for more information in the e-commerce environment, and in the right form is a prerequisite for personalized recommendation. Personalized recommendation technology is a core issue of e-commerce automated recommendation system. Higher complexity than ordinary association rules algorithm fuzzy association rules, the low efficiency become a bottleneck in the practical application of fuzzy association rules algorithm. The paper presents using fuzzy association rules to design E-commerce personalized recommendation system. The experimental results show that the new algorithm to improve the efficiency of the implementation. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3983