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- W2895851246 abstract "We introduce a dynamic version of the NP-hard Cluster Editing problem. The essential point here is to take into account dynamically evolving input graphs: Having a cluster graph (that is, a disjoint union of cliques) that represents a solution for a first input graph, can we cost-efficiently transform it into a similar cluster graph that is a solution for a second (subsequent) input graph? This model is motivated by several application scenarios, including incremental clustering, the search for compromise clusterings, or also local search in graph-based data clustering. We thoroughly study six problem variants (edge editing, edge deletion, edge insertion; each combined with two distance measures between cluster graphs). We obtain both fixed-parameter tractability as well as parameterized hardness results, thus (except for two open questions) providing a fairly complete picture of the parameterized computational complexity landscape under the perhaps two most natural parameterizations: the distance of the new similar cluster graph to (i) the second input graph and to (ii) the input cluster graph." @default.
- W2895851246 created "2018-10-26" @default.
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- W2895851246 date "2018-01-01" @default.
- W2895851246 modified "2023-09-30" @default.
- W2895851246 title "Parameterized Dynamic Cluster Editing" @default.
- W2895851246 doi "https://doi.org/10.4230/lipics.fsttcs.2018.46" @default.
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