Development of a Personalized Recommendation Procedure Based on Data Mining Techniques for Internet Shopping Malls
Jaekyeong Kim, Do-Hyun Ahn, Yoon-Ho Cho · Journal of Intelligence and Information Systems · 2003
Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering is the most successful recommendation technology. Web usage mining and clustering analysis are widely used in the recommendation field. In this paper, we propose several hybrid collaborative filtering-based recommender procedures to address the effect of web usage mining and cluster analysis. Through the experiment with real e-commerce data, it is found that collaborative filtering using web log data can perform recommendation tasks effectively, but using cluster analysis can perform efficiently.