E-commerce Website Recommender System Based on Dissimilarity and Association Rule - LiFeng Zhang; ShuWen Yang; MingWang Zhang (Indonesian Journal of Electrical Engineering and Computer Science, 2014)
By analyzing the current electronic commerce recommendation algorithm analysis, put forward a kind to use dissimilarity clustering and association recommendation algorithm, the algorithm realized web website shopping user data clustering by use of the dissimilarity, and then use the association rules algorithm for clustering results of association recommendation, experiments show that the algorithm compared with traditional clustering association algorithm of iteration times decrease, improve operational efficiency, to prove the method by use of the actual users purchase the recommended, and evidence of the effectiveness of the algorithm in recommendation. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.4002