Computational Optimization and Applications

, Volume 27, Issue 2, pp 173–186

Finding All Maximal Cliques in Dynamic Graphs

  • Volker Stix

DOI: 10.1023/B:COAP.0000008651.28952.b6

Cite this article as:
Stix, V. Computational Optimization and Applications (2004) 27: 173. doi:10.1023/B:COAP.0000008651.28952.b6


Clustering applications dealing with perception based or biased data lead to models with non-disjunct clusters. There, objects to be clustered are allowed to belong to several clusters at the same time which results in a fuzzy clustering. It can be shown that this is equivalent to searching all maximal cliques in dynamic graphs like Gt = (V,Et), where Et − 1Et, t = 1,...,T; E0 = φ. In this article algorithms are provided to track all maximal cliques in a fully dynamic graph.

maximal clique dynamic graphs fuzzy clustering 

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Volker Stix
    • 1
  1. 1.Department of Information BusinessVienna University of EconomicsVienna/Austria