文献类型：期刊文献

英文题名：A NOVEL NEURAL COLLABORATIVE FILTERING RECOMMENDATION BASED ON SIDE INFORMATION FUSION

作者：Mu, Ruihui[1]

第一作者：穆瑞辉

通讯作者：Mu, RH[1]

机构：[1]Xinxiang Univ, Coll Comp & Informat Engn, Xinxiang 453000, Henan, Peoples R China

第一机构：新乡学院计算机与信息工程学院

通讯机构：[1]corresponding author), Xinxiang Univ, Coll Comp & Informat Engn, Xinxiang 453000, Henan, Peoples R China.|[1107118]新乡学院计算机与信息工程学院;[11071]新乡学院;

年份：2023

卷号：76

期号：1

起止页码：84-95

外文期刊名：COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001010638200009)】；

语种：英文

外文关键词：neural network; side information; denoising autoencoder; rating information

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.