Finding All Maximal Cliques in Dynamic Graphs
- 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 − 1 ⊂ Et, t = 1,...,T; E0 = φ. In this article algorithms are provided to track all maximal cliques in a fully dynamic graph.