Improved Collaborative Filtering Method Applied in Movie Recommender System

被引:0
|
作者
Liang, Tian [1 ]
Wu, Shunxiang [1 ]
Cao, Da [1 ]
机构
[1] Xiamen Univ, Dept Automat, Xiamen 361005, Fujian, Peoples R China
关键词
recommender systems; collaborative filtering; item-based; cold start problem; mixed similarity;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Due to the rapid growth of internet, a useful technology named recommender system (RS) become an effective application to make recommendations to users, nowadays, many collaborative recommender systems (CRS) have succeeded in some fields like movies and music web applications; however, there are also some ways for them to be a more effective RS. This paper introduces a new item-based collaborative filtering method which uses mixed similarity, and it also can solve the cold start problem. A series of experiments are accomplished to indicate that the new method can make a better recommendation than the pure item-based collaborative filtering method.
引用
收藏
页码:427 / 432
页数:6
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