Competitive Recommendation Algorithm for E-commerce

被引:0
作者
Nadine, Umutoni [1 ]
Cao, Huiying [1 ]
Deng, Jiangzhou [1 ]
机构
[1] Chongqing Univ Posts & Telecommun, Coll Econ & Management, Chongqing 400065, Peoples R China
来源
2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) | 2016年
关键词
recommendation systems; collaborative filtering; data mining; E-commerce;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Collaborative filtering (CF) is commonly used and successful techniques in recommendation systems (RS) but it has showed some problems like sparsity and cold start. Different techniques are employed to overcome the collaborative problems but there is no one single algorithm which can satisfy the personalized needs of each user. This paper presents a new hybrid recommendation approach to improve the effectiveness through the competition process among a series of algorithms. Experiment has been conducted on MovieLens to verify our proposed approach. The results indicate that our approach enabled more efficient and stable recommendation than single method.
引用
收藏
页码:1539 / 1542
页数:4
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