Leader-driven community detection algorithms (LdCD hereafter) constitute a new trend in
devising algorithms for community detection in large-scale complex networks. The basic …

Drug repurposing is a valuable alternative to traditional drug design based on the
assumption that medicines have multiple functions. Computer-based techniques use ever …

Evolutionary clustering (EC) refers to the applications of evolutionary optimization algorithms
such as genetic algorithm to data clustering. Although multi-objective evolutionary clustering …

This work proposes a method for data clustering based on complex networks theory. A data
set is represented as a network by considering different metrics to establish the connection …

In this paper we present an original approach for community detection in complex networks.
The approach belongs to the family of seed-centric algorithms. However, instead of …

Image segmentation is still a challenging issue in pattern recognition. Among the various
segmentation approaches are those based on graph partitioning, which present some …

Community detection is a kind of clustering task which aims to find groups of vertices
densely connected internally but sparsely connected to other groups. In comparison with …

This paper is an extensive survey of literature on complex network communities and
clustering. Complex networks describe a widespread variety of systems in nature and …

Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually
deployed in a monitoring field in order to detect some physical phenomenon. Due to the low …

With the proliferation of documents on the Internet, it has become increasingly difficult for
users to search and retrieve the information they want: information that is relevant and …