AN IMPROVED ITEM-BASED MOVIE RECOMMENDATION ALGORITHM

被引：0
|
作者：
Zhao, Dongping [1 ]
Xiu, Jiapeng [1 ]
Bai, Yu [1 ]
Yang, Zhengqiu [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China
来源：
PROCEEDINGS OF 2016 4TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENCE SYSTEMS (IEEE CCIS 2016) | 2016年
关键词：
Improved item-based recommendation algorithm; ItemSimilarity; MAE; RMSE;
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：
To date, with the rapid development of information society, it has great significance to video web sites that using the existing relationship between users and items to analyze users' behavior and find the correlation of information, which can mine users' preferences deeply and provide the optimal recommendations to users. This paper explores an improved item-based movie recommendation algorithm based on a large number of movie recommendation algorithms, which increases cinematic genres' effect on computing ItemSimilarity. We then provide MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) to demonstrate that our proposed algorithm is more accurate than the original one.
引用
收藏
页码：278 / 281
页数：4
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