Collaborative Filtering Recommendation Algorithm Based on Users of Maximum Similar Clique

被引：1
|
作者：
Zhou, Zhaoyang [1 ,2 ]
He, Yanju [2 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430000, Peoples R China
[2] Hubei Univ, Wuhan 430000, Peoples R China
来源：
PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CLOUD COMPUTING COMPANION (ISCC-C) | 2014年
关键词：
collaborative filtering; conformist; similar clique; recommendation system;
D O I：
10.1109/ISCC-C.2013.58
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to improve the performance of Collaborative filtering (CF), a new method of producing the nearest neighbor for active user is proposed in this paper. Inspired by the conformist of E-commerce consumers, we build the user model of maximum similar clique and we use it to improve the method of producing the nearest neighbors for target users. A collaborative filtering recommendation algorithm MCQ-CF based on user model is present. The experiment results show that the algorithm MCQ-CF has good performance for accuracy and stability.
引用
收藏
页码：852 / 857
页数：6
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