Rough Net Approach for Community Detection Analysis in Complex Networks

Abstract

Rough set theory has many interesting applications in circumstances which are characterized by vagueness. In this paper, the applications of rough set theory in community detection analysis is discussed based on the Rough Net definition. We will focus the application of Rough Net concept in community detection validity in both monoplex and multiplex complex networks. Also, the topological evolution estimation between adjacent layers in dynamic networks is discussed and a new visualization schema combining both complex network representation and Rough Net definition is adopted contributing to the understanding of the community structure. We provide some examples demonstrating how the Rough Net definition can be used to analyze the properties of the community structure in real-world networks, including dynamic networks.