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 ⊂ E t, t = 1,...,T; E 0 = φ. In this article algorithms are provided to track all maximal cliques in a fully dynamic graph.
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Stix, V. Finding All Maximal Cliques in Dynamic Graphs. Computational Optimization and Applications 27, 173–186 (2004). https://doi.org/10.1023/B:COAP.0000008651.28952.b6
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DOI: https://doi.org/10.1023/B:COAP.0000008651.28952.b6