This paper is concerned with how to make efficient use of social information to improve recommendations. Most existing social recommender systems assume people share similar …
Y Zhang, M Zhang, Y Liu, S Ma, S Feng - Proceedings of the 22nd …, 2013 - dl.acm.org
Matrix factorization on user-item rating matrices has achieved significant success in collaborative filtering based recommendation tasks. However, it also encounters the …
X Xiao, J Wen, W Zhou, F Luo, M Gao, J Zeng - Expert Systems with …, 2022 - Elsevier
Abstract GNNs (Graph Neural Networks) use graph structure to make recommendations, receiving more and more attention. Firstly, existing work focuses on aggregating social …
C Gao, S Yuan, Z Zhang, H Yin, J Shao - … Mai, Thailand, April 22–25, 2019 …, 2019 - Springer
Matrix Approximation (MA) is a powerful technique in recommendation systems. There are two main problems in the prevalent MA framework. First, the latent factor is out of …
TN Duong, VD Than, TH Tran, QH Dang… - … on Information and …, 2018 - ieeexplore.ieee.org
Thanks to its successful application in recommendation systems, collaborative filtering (CF) technique has become one of the most popular research topic in data mining and …
K Ji, R Sun, X Li, W Shu - Neurocomputing, 2016 - Elsevier
Matrix approximation is a common model-based approach to collaborative filtering in recommender systems. Many relevant algorithms that fuse social contextual information …
H Zhang, G Liu, J Wu - PRICAI 2018: Trends in Artificial Intelligence: 15th …, 2018 - Springer
Collaborative filtering (CF) technique plays an important role in generating personalized recommendations, but its performance is challenged by the problems of data sparsity and …
J Cheng, T Yuan, J Wang, H Lu - … of the 37th international ACM SIGIR …, 2014 - dl.acm.org
Recently, some recommendation methods try to relieve the data sparsity problem of Collaborative Filtering by exploiting data from users' multiple types of behaviors. However …
C Luo, W Pang, Z Wang, C Lin - 2014 IEEE international …, 2014 - ieeexplore.ieee.org
In this paper, we investigate the social-based recommendation algorithms on heterogeneous social networks and proposed Hete-CF, a social collaborative filtering …