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Evaluating the Performance of Clustering Algorithms in Networks

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Dynamics On and Of Complex Networks, Volume 2

Abstract

This chapter briefly reviews the most common kind of benchmark graphs in the literature, a class of networks introduced by Girvan and Newman (GN). This chapter then proposes a new class of graphs, that account for the heterogeneity in the distributions of node degrees and of community sizes and is therefore closer to real properties found in real networks. Moreover, the new benchmark is generalized to include overlapping, weighted and directed graphs. Finally, it introduces some of the most commonly used community detection algorithms and compares their performances.

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Author information

Authors and Affiliations

  1. Howard Hughes Medical Institute (HHMI), Northwestern University, Evanston, IL, 60208, USA

    Andrea Lancichinetti

  2. Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA

    Andrea Lancichinetti

Authors
  1. Andrea Lancichinetti
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Corresponding author

Correspondence to Andrea Lancichinetti .

Editor information

Editors and Affiliations

  1. Dept. Computer Science & Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Animesh Mukherjee

  2. Microsoft Research Lab India, 9 Lavelle Road, Bangalore, 560001, India

    Monojit Choudhury

  3. , Laboratoire J.A. Dieudonné, Université de Nice - Sophie Antipolis, Parc Valrose, Nice 02, 06108, France

    Fernando Peruani

  4. Dept. Computer Science & Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Niloy Ganguly

  5. Department of Mathematical Engineering, Université Catholique de Louvain, 4, Avenue George Lemaître, Louvain-la-Neuve, B-1348, Belgium

    Bivas Mitra

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Lancichinetti, A. (2013). Evaluating the Performance of Clustering Algorithms in Networks. In: Mukherjee, A., Choudhury, M., Peruani, F., Ganguly, N., Mitra, B. (eds) Dynamics On and Of Complex Networks, Volume 2. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser, New York, NY. https://doi.org/10.1007/978-1-4614-6729-8_8

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