A NOVEL NEURAL COLLABORATIVE FILTERING RECOMMENDATION BASED ON SIDE INFORMATION FUSION

被引：0
|
作者：
Mu, Ruihui [1 ]
机构：
[1] Xinxiang Univ, Coll Comp & Informat Engn, Xinxiang 453000, Henan, Peoples R China
来源：
COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES | 2023年 / 76卷 / 01期
关键词：
neural network; side information; denoising autoencoder; rating information;
D O I：
10.7546/CRABS.2023.01.09
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：
It is difficult to accurately learn user's latent features using only one single data source. In order to solve these problems, we consider to utilize relevant side information of users or items as a supplement to rating information to enhance the performance of recommender systems, and propose a novel neural collaborative filtering recommendation model based on side information fusion. Extensive experiments on different datasets validate the efficiency and accuracy of our proposed framework.
引用
收藏
页码：84 / 95
页数：12
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