W Fan, Q Li, M Cheng - Proceedings of the AAAI Conference on …, 2018 - ojs.aaai.org
Social-based recommender systems have been recently proposed by incorporating social relations of users to alleviate sparsity issue of user-to-item rating data and to improve …
S Yan, KJ Lin, X Zheng, W Zhang… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Social recommender system, using social relation networks as additional input to improve the accuracy of traditional recommender systems, has become an important research topic …
Due to their potential commercial value and the associated great research challenges, recommender systems have been extensively studied by both academia and industry …
Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent …
W Reafee, N Salim, A Khan - PloS one, 2016 - journals.plos.org
The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation …
CC Hsu, MY Yeh - IEEE Transactions on Knowledge and …, 2018 - ieeexplore.ieee.org
Research of social recommendation aims at exploiting social information to improve the quality of a recommender system. It can be further divided into two classes. Explicit social …
Although Recommender Systems have been comprehensively analyzed in the past decade, the study of social-based recommender systems just started. In this paper, aiming at …
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 …
GN Hu, XY Dai, Y Song, SJ Huang, JJ Chen - arXiv preprint arXiv …, 2016 - arxiv.org
Recommender systems (RSs) provide an effective way of alleviating the information overload problem by selecting personalized choices. Online social networks and user …