Using Fuzzy Association Rules to Design E-commerce Personalized Recommendation System

Guofang Kuang, Yuanchen Li

Abstract


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


Keywords


E-commerce; personalized recommendation system;fuzzy association rule

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics