An asymmetric graph recommendation algorithm based on user scores and interests

被引：1
|
作者：
Zhang, Yi-Wen [1 ]
Wang, Ran [2 ]
Wang, Ting-Wei [1 ]
He, Guang-Da [1 ]
Hu, Jun [1 ]
机构：
[1] An Hui Xin Hua Univ, Hefei 230088, Anhui, Peoples R China
[2] An Hui Univ, Hefei 230601, Anhui, Peoples R China
来源：
2017 2ND INTERNATIONAL SEMINAR ON ADVANCES IN MATERIALS SCIENCE AND ENGINEERING | 2017年 / 231卷
关键词：
RANKING;
D O I：
10.1088/1757-899X/231/1/012045
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The proposed algorithm uses the symmetry similarity calculation method based on the common project, which can not reflect the user 's interest very well and the recommendation accuracy is low. In order to improve the accuracy of recommendation, this paper proposes a graph recommendation algorithm which integrates user rating and interest. In order to reflect the interests of users, using the principle of diffusion of the substance user rating information asymmetry; Experiments show that the proposed algorithm for user rating and interest fusion improves the prediction accuracy.
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页数：6
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