With the explosive growth of online social networks, it is now well understood that social information is highly helpful to recommender systems. Social recommendation methods are …
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 …
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 …
Z Huang, SE, J Zhang, B Zhang, Z Ji - IET Communications, 2016 - Wiley Online Library
Exponential growth of information generated by social networks requires efficient and scalable recommendation techniques to produce useful results. Traditional methods have …
M Zhang, B Hu, C Shi, B Wu, B Wang - … -WAIM 2018, Macau, China, July 23 …, 2018 - Springer
Social recommendation becomes a current research focus, which leverages social relations among users to alleviate data sparsity and cold-start problems in recommender systems …
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 …
M Jiang, P Cui, X Chen, F Wang… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Recommender systems can suffer from data sparsity and cold start issues. However, social networks, which enable users to build relationships and create different types of items …
With the prevalence of online social platforms, social recommendation has emerged as a promising direction that leverages the social network among users to enhance …
X Sha, Z Sun, J Zhang - IEEE Transactions on Computational …, 2021 - ieeexplore.ieee.org
Social networks have proven to be effective for high-quality item recommendation. Most social recommenders, however, are insufficient to capture the user preferences over items …