文章基本信息

标题：The Error Bound of User for Collaborative Recommender System
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作者：Uk-Pyo Han ; Gil-Mo Yang ; Jae-Soo Yoo 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2009
卷号：2
期号：1
出版社：SERSC
摘要：We predict accuracy of user's preferences by using memory-based collaborative filtering algorithm in recommender system, and then analyze the results through the EDA approach. The possibilities are presented that prediction accuracy can be evaluated before prediction process by analyzing the results. The classification functions using the generative probability of specific ratings are made, and users are classified by using the classification functions. The prediction accuracies of each classified group are analyzed through statistical tests. The method of setting the Error Bound of users who have high probabilities in low prediction accuracy will be presented.