Recommender systems have become an essential tool to help resolve the information
overload problem in recent decades. Traditional recommender systems, however, suffer …

With the exponential increase in the amount of digital information over the internet, online
shops, online music, video and image libraries, search engines and recommendation …

Graph Neural Networks (GNNs) have recently enabled substantial advances in graph
learning. Despite their rich representational capacity, GNNs remain under-explored for large …

Recommendation is one of the critical applications that helps users find information relevant
to their interests. However, a malicious attacker can infer users' private information via …

Social metaverse with VR has been viewed as a paradigm shift for social media. However,
most traditional VR social platforms ignore emerging characteristics in a metaverse, thereby …

Friend recommendations based on social relationships have attracted thousands of
research under the rapid development of social networks. However, most of the existing …

Due to the proliferation of social media, a growing number of users search for and join group
activities in their daily life. This develops a need for the study on the ranking-based group …

Many social studies and practical cases suggest that people's consumption behaviors and
social behaviors are not isolated but interrelated. However, most existing research either …

Recommender systems offer critical services in the age of mass information. Personalized
ranking has been attractive both for content providers and customers due to its ability of …

Today, the public is not willing to spend much time identifying their personal needs.
Therefore, it needs a system that automatically recommends customized items to customers …