H Ma - Proceedings of the 36th international ACM SIGIR …, 2013 - dl.acm.org
Social recommendation problems have drawn a lot of attention recently due to the prevalence of social networking sites. The experiments in previous literature suggest that …
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 …
TH Lin, C Gao, Y Li - Proceedings of the 27th ACM international …, 2018 - dl.acm.org
Social recommendation, which utilizes social relations to enhance recommender systems, has been gaining increasing attention recently with the rapid development of online social …
L Guo, J Ma, Z Chen, H Zhong - Soft Computing, 2015 - Springer
Recommender systems with social networks have been well studied in recent years. However, most of these methods ignore the social contextual information among users and …
Recent years have seen a surge of research on social recommendation techniques for improving recommender systems due to the growing influence of social networks to our daily …
Y Wei, H Ma, R Zhang, Z Li, L Chang - Pacific-Asia conference on …, 2021 - Springer
Online social platforms have provided a large amount of available information to recommendation systems. With this intuition, social recommendation systems emerged and …
Social recommendation has been an active research topic over the last decade, based on the assumption that social information from friendship networks is beneficial for improving …
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 …
Y LI, M SONG, E Hai-Hong, J SONG - The Journal of China Universities of …, 2014 - Elsevier
Using the social information among users in recommender system can partly solve the data sparsely problems and significantly improve the performance of the recommendation …