Detecting a community in a network is a matter of discerning the distinct features and
connections of a group of members that are different from those in other communities. The …

The modern science of networks has made significant advancement in the modeling of
complex real-world systems. One of the most important features in these networks is the …

With the rapid development of information technologies, various big graphs are prevalent in
many real applications (eg, social media and knowledge bases). An important component of …

This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …

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 …

Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …

Multilayer network analysis has become a vital tool for understanding different relationships
and their interactions in a complex system, where each layer in a multilayer network depicts …

A multiplex network models different modes of interaction among same-type entities. In this
article, we provide a taxonomy of community detection algorithms in multiplex networks. We …

The detection of community structures is a crucial research area. The problem of community
detection has received considerable attention from a large portion of the scientific …

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 …