The recent boom in social networking services has prompted the research of
recommendation systems. The basic assumption behind these works was that" users' …

Collaborative Filtering (CF) is one of the most successful approaches for recommender
systems. With the emergence of online social networks, social recommendation has become …

Traditional recommendation algorithms based on collaborative filtering suffer from a data
sparsity problem. The emergence of online social network has enriched the user's …

In recent times, social recommendation has become a popular technique in recommender
systems due to its ability to enhance the accuracy of recommendations by leveraging the …

With the prevalence of online social platforms, social recommendation has emerged as a
promising direction that leverages the social network among users to enhance …

GNN-based social recommendation aims to use social network information to improve
recommendation performance of traditional user–item interaction network (U–I network) …

Social Recommender Systems (SRS) have attracted considerable attention since its
accompanying service, social networks, helps increase user satisfaction and provides …

Social information is usually jointly utilized with rating information to help the traditional
recommendation system providing more personalized services, while how to make full use …

As an effective deep representation learning technique for graph data, graph convolutional
network (GCN) has recently been widely applied to obtain better embedding of vertex. The …

Social recommender systems are expected to improve recommendation quality by
incorporating social information when there is little user-item interaction data. However …