A Solution of Missing Value in Collaborative Filtering Recommendation Algorithm

被引:0
作者
Jie Qin [1 ]
Lei Cao [1 ]
Hui Peng [1 ]
机构
[1] PLA Univ Sci & Technol, Coll Command Informat Syst, Nanjing 210007, Jiangsu, Peoples R China
来源
2015 CHINESE AUTOMATION CONGRESS (CAC) | 2015年
关键词
collaborative filtering; sparsity; recommendation algorithm; MAE;
D O I
暂无
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 solve the sparsity of User-Item scoring matrix in collaborative filtering recommendation, proposed an algorithm that combining user's interests with item's quality to calculate ungraded items in matrix. By setting the weight of user and item, synthesized the value of missing value, which were used to replace the ungraded value in scoring matrix to calculate similarity. Experiment shows that the algorithm can improve the recommendation effect, and when the user's weight values 0.4, MAE reaches minimum, and recommendation quality reaches maximum.
引用
收藏
页码:2184 / 2187
页数:4
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