Community detection in social networks is the process of identifying the cohesive groups of
similar nodes. Detection of these groups can be helpful in many applications, such as …

One of the greatest advancements of the modern era is the evolution of smart grid (SG),
which integrates information communication technologies with advanced power electronic …

With the explosion of social media networks, many modern applications are concerning
about people's connections, which leads to the so-called social computing. An elusive …

Detecting communities in dynamic evolving networks is of great interest. It has received
tremendous attention from researchers. One promising solution is to update communities …

Abstract In modern Online Social Networks (OSNs), the need to detect users' communities
based on their interests and social connections has became a more and more important …

Abstract Recently, Graph Neural Networks (GNNs) have gained popularity in a variety of real-
world scenarios. Despite the great success, the architecture design of GNNs heavily relies …

In recent years, a new Internet-based unsecured credit model, peer-to-peer (P2P) lending, is
flourishing and has become a successful complement to the traditional credit business …

Link prediction is an important task in complex network analysis and can be found in many
real-world applications such as recommendation systems, information retrieval, and …

Nonlinear kernel-based subspace clustering methods that can reveal the multi-cluster
nonlinear structure of samples are an emerging research topic. However, the existing kernel …

Besides the topological structure, there are additional information, ie, node attributes, on top
of the plain graphs. Usually, these systems can be well modeled by attributed graphs, where …