Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce

被引：1
|
作者：
Dong, Jie [1 ]
Qin, Yun [1 ,2 ]
Sun, Xue Yang [1 ]
Du, Li Ming [1 ]
机构：
[1] Shenyang Jianzhu Univ, Informat & Control Engn Coll, Shenyang 110168, Peoples R China
[2] Liaohe Oilfield Co, SAGD Project Dept, Panjin, Liaoning, Peoples R China
来源：
2016 INTERNATIONAL CONFERENCE ON MECHATRONICS, MANUFACTURING AND MATERIALS ENGINEERING (MMME 2016) | 2016年 / 63卷
关键词：
D O I：
10.1051/matecconf/20166304018
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Information overload is one of the most serious problems in big data environment, recommendation systems is a way to effectively mitigate the problem. In order to make use of rich user feedback and social networks information and to further improve the performance of the recommendation system, This thesis makes a improvement on the user-based collaborative filtering algorithm by normalization method, Meanwhile the algorithm could be run on the MapReduce in the Hadoop platform. The experimental results show that the algorithm on Hadoop platform can effectively improve the accuracy of the data to recommend and computational efficiency, so as to improve the satisfaction of users.
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页数：5
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