Bi-Objective Community Detection (BOCD) in Networks Using Genetic Algorithm

  • Rohan Agrawal
Conference paper

DOI: 10.1007/978-3-642-22606-9_5

Part of the Communications in Computer and Information Science book series (CCIS, volume 168)
Cite this paper as:
Agrawal R. (2011) Bi-Objective Community Detection (BOCD) in Networks Using Genetic Algorithm. In: Aluru S. et al. (eds) Contemporary Computing. IC3 2011. Communications in Computer and Information Science, vol 168. Springer, Berlin, Heidelberg

Abstract

A lot of research effort has been put into community detection from all corners of academic interest such as physics, mathematics and computer science. In this paper I have proposed a Bi-Objective Genetic Algorithm for community detection which maximizes modularity and community score. Then the results obtained for both benchmark and real life data sets are compared with other algorithms using the modularity and MNI performance metrics. The results show that the BOCD algorithm is capable of successfully detecting community structure in both real life and synthetic datasets, as well as improving upon the performance of previous techniques.

Keywords

Community Structure Community detection Genetic Algorithm Multi-objective Genetic Algorithm Multi-objective optimization modularity Normalized Mutual Information Bi-objective Genetic Algorithm 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rohan Agrawal
    • 1
  1. 1.Computer Science DepartmentJaypee Institute of Information TechnologyNoidaIndia

Personalised recommendations