Community detection is one of the popular research topics in the field of complex networks
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …

Community structure is ubiquitous in real-world complex networks. The task of community
detection over these networks is of paramount importance in a variety of applications …

Network clustering is one of the fundamental unsupervised methods of knowledge
discovery. Its goal is to group similar nodes together without supervision or prior knowledge …

Community detection is a well-established problem and nontrivial task in complex network
analysis. The goal of community detection is to discover community structures in complex …

Community detection is of significant importance in understanding the structures and
functions of networks. Recently, overlap** community detection has drawn much attention …

Community detection is a fundamental task in graph data mining. Most existing studies in
contact networks, collaboration networks, and social networks do not utilize the temporal …

Community detection in signed networks is a challenging research problem, and is of great
importance to understanding the structural and functional properties of signed networks. It …

Information sharing behavior and social link building behavior have shown strong
correlation on social media. The aim of this article is to explore this correlation for …

Existing community detection algorithms may be often unsatisfactory due to low detection
accuracy in real-world graphs since the number of edges between the nodes in the same …

The task of community detection has become a fundamental research problem in complex
network analysis. Intuitively, similar nodes are more likely to be contained in the same …