Graph-based data clustering with overlaps

Michael Fellows, Jiong Guo, Christian Komusiewicz, Rolf Niedermeier, Johannes Uhlmann

    Research output: Contribution to journalArticlepeer-review


    We introduce overlap cluster graph modification problems where, other than in most previous works, the clusters of the target graph may overlap. More precisely, the studied graph problems ask for a minimum number of edge modifications such that the resulting graph consists of clusters (that is, maximal cliques) that may overlap up to a certain amount specified by the overlap number s. In the case of s-vertex-overlap, each vertex may be part of at most s maximal cliques; s-edge-overlap is analogously defined in terms of edges. We provide a complexity dichotomy (polynomial-time solvable versus NP-hard) for the underlying edge modification problems, develop forbidden subgraph characterizations of "cluster graphs with overlaps", and study the parameterized complexity in terms of the number of allowed edge modifications, achieving fixed-parameter tractability (in case of constant s-values) and parameterized hardness (in case of unbounded s-values).
    Original languageEnglish
    Pages (from-to)2-17
    Number of pages16
    JournalDiscrete Optimization
    Issue number1
    Publication statusPublished - 2011


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