Proceedings of the Korea Inteligent Information System Society Conference (한국지능정보시스템학회:학술대회논문집)
- 2005.05a
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- Pages.232-239
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- 2005
Simple Bayesian Model for Improvement of Collaborative Filtering
협업 필터링 개선을 위한 베이지안 모형 개발
- Lee, Young-Chan (Department of Electronic Commerce, Dongguk University)
- 이영찬 (동국대학교 상경대학 전자상거래학과)
- Published : 2005.05.27
Abstract
Collaborative-filtering-enabled Web sites that recommend books, CDs, movies, and so on, have become very popular on the Internet. Such sites recommend items to a user on the basis of the opinions of other users with similar tastes. This paper discuss an approach to collaborative filtering based on the Simple Bayesian and apply this model to two variants of the collaborative filtering. One is user-based collaborative filtering, which makes predictions based on the users' similarities. The other is item-based collaborative filtering which makes predictions based on the items' similarities. To evaluate the proposed algorithms, this paper used a database of movie recommendations. Empirical results show that the proposed Bayesian approaches outperform typical correlation-based collaborative filtering algorithms.