Abstract Typically, Graph Coloring Problem (GCP) is one of the key features for graph
stamping in graph theory. The general approach is to paint at least edges, vertices, or the …

Complex networks (CNs) have gained much attention in recent years due to their
importance and popularity. The rapid growth in the size of CNs leads to more difficulties in …

Detecting groups within a set of interconnected nodes is a widely addressed problem that
can model a diversity of applications. Unfortunately, detecting the optimal partition of a …

Studying the structure of the evolutionary communities in complex networks is essential for
detecting the relationships between their structures and functions. Recent community …

Over the past couple of decades, the research area of network community detection has
seen substantial growth in popularity, leading to a wide range of researches in the literature …

Community detection is one of the long standing and challenging tasks in the field of
Complex Networks (CNs). Recently, deep learning is one of the promising community …

The importance of identifying mesoscale structures in complex networks can be hardly
overestimated. So far, much attention has been devoted to detect modular and bimodular …

Timely identification of terrorist networks within civilian populations could assist security and
intelligence personnel to disrupt and dismantle potential terrorist activities. Finding “small” …

Community detection is a highly active research area that aims to identify groups of vertices
with similar properties or interests within complex real-world networks. Over the years, a …

We propose a novel method for adaptive K-means clustering. The proposed method
overcomes the problems of the traditional K-means algorithm. Specifically, the proposed …