期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2014
卷号：8
期号：3
页码：251-254
DOI：10.14257/ijseia.2014.8.3.23
出版社：SERSC
摘要：In this paper we present an adaptive collaborative filtering algorithm using Fish School Search[1]. The proposed algorithm use not only rating information but also user demographic information and interests to improve similarity measurement. This algorithm adaptive to different user, where it could learn the best combination of features weight, leading to a better prediction. The experiment result shows that the proposed algorithm outperforms other collaborative filtering method. And on our knowledge, this is the first time Fish School Search applied in recommendation system domain
关键词：recommendation systems; collaborative filtering; fish school search
