Finding all maximal cliques in dynamic graphs

Publikation: Working/Discussion PaperWU Working Paper

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Abstract

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 G_t=(V,E_t), where E_(t-1) in E_t, t=1,... ,T; E_0=(). In this article algorithms are provided to track all maximal cliques in a fully dynamic graph. It is naturally to raise the question about the maximum clique, having all maximal cliques. Therefore this article discusses potentials and drawbacks for this problem as well. (author's abstract)

Publikationsreihe

ReiheWorking Papers on Information Systems, Information Business and Operations
Nummer02/2002
ISSN2518-6809

WU Working Paper Reihe

  • Working Papers on Information Systems, Information Business and Operations

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