Community detection, a fundamental task for network analysis, aims to partition a network
into multiple sub-structures to help reveal their latent functions. Community detection has …

The study of complex networks has significantly advanced our understanding of community
structures which serves as a crucial feature of real-world graphs. Detecting communities in …

Community detection technologies have the general research significance in complex
networks, in which the topology information of network is worthy to be the focus for its widely …

Multi-view data effectively model and characterize the underlying complex systems, and
multi-view clustering is of great significance for revealing the mechanisms of systems, which …

This paper aims to provide a comprehensive critical overview on how entities and their
interactions in Complex Networked Systems (CNS) are modelled across disciplines as they …

Social network analysis has become an important research area in recent years. Community
detection, as a fundamental task in social network analysis, aims to discover the hidden …

Temporal networks are ubiquitous in nature and society, and tracking the dynamics of
networks is fundamental for investigating the mechanisms of systems. Dynamic communities …

Clustering of vertices in complex networks to detect communities is an open challenge due
to its unknown and hidden properties and broad areas. Complex networks occur in various …

Temporal networks are ubiquitous because complex systems in nature and society are
evolving, and tracking dynamic communities is critical for revealing the mechanism of …

In complex network analysis, detecting communities is becoming increasingly important.
However, it is difficult to fuse multiple types of information to enhance the community …