Detecting Overlapping Communities in Social Networks with Voronoi and Tolerance Rough Sets

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10868)

Abstract

In this work, we propose a novel method based on Voronoi diagrams and tolerance rough set method (TRSM) to detect overlapping communities. In the proposed Voronoi TRSM approach, a social network is represented as a graph. A Voronoi diagram is a partitioning of a plane into regions based on closeness to points in a specific set of sites (seeds). These seeds are used as a core for determining tolerance classes. The upper approximation operator from TRSM is used to obtain overlapping nodes. We have experimented with three well-known real networks and compared with Fuzzy-Rough and a Matrix Factorization-based approach. The results with proposed Voronoi TRSM approach are promising in terms of the extended modularity measure and the dense communities measure.

Keywords

Community detection Density-based clustering Social networks Soft computing Tolerance rough sets Voronoi diagram 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Applied Computer ScienceUniversity of WinnipegWinnipegCanada

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