INTEGRATING RATING INFORMATION AND SOCIAL INFORMATION FOR COLLABORATIVE FILTERING RECOMMENDATION

被引：0
|
作者：
Mu, Ruihui [1 ]
机构：
[1] Xinxiang Univ, Coll Comp & Informat Engn, Xinxiang 453003, Henan, Peoples R China
来源：
COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES | 2019年 / 72卷 / 05期
基金：
中国国家自然科学基金;
关键词：
collaborative filtering; social information; recommendation algorithm; rating information;
D O I：
10.7546/CRABS.2019.05.03
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
In order to address the problem of cold start and data sparsity, we proposed a novel collaborative filtering recommendation algorithm based on social information by integrating the user's social information and rating information. Experimental results show that the proposed algorithm can effectively alleviate the user cold start problem in the collaborative filtering recommendation algorithm and is superior to the state-of-the-art algorithms.
引用
收藏
页码：584 / +
页数：10
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