User preference mining through hybrid collaborative filtering and content-based filtering in recommendation system

被引:1
作者
Jung, KY
Lee, JH
机构
[1] Inha Univ, HCI Lab, Dept Comp Sci & Informat Engn, Inchon, South Korea
[2] Inha Univ, Sch Comp Sci & Engn, Inchon, South Korea
关键词
data mining; collaborative filtering; content-based filtering; machine learning; retrieval information; hybrid filtering;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.
引用
收藏
页码:2781 / 2790
页数:10
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