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 …

The expansion of the web and emergence of a large number of social networking sites
(SNS) have empowered users to easily interconnect on a shared platform. A social network …

The purpose of community detection in complex networks is to identify the structural location
of nodes. Complex network methods are usually graphical, with graph nodes representing …

Abstract This paper improved Cuckoo Search Optimization (CSO) algorithm with a Genetic
Algorithm (GA) for community detection in complex networks. CSO algorithm has problems …

Detecting and analyzing dense groups or communities from social and information networks
has attracted immense attention over the last decade due to its enormous applicability in …

In the current era of automation, machines are constantly being channelized to provide
accurate interpretations of what people express on social media. The human race nowadays …

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 …

The field of complex network clustering has been very active in the past several years. In this
paper, a discrete framework of the particle swarm optimization algorithm is proposed. Based …

A multiobjective genetic algorithm to uncover community structure in complex network is
proposed. The algorithm optimizes two objective functions able to identify densely …

In today's world, the interconnections among objects in many domains are often modeled as
networks, with nodes representing the objects and edges the existing relationships among …