Iterative merging heuristics for correlation clustering
by Andrzej Lingas; Mia Persson; Dzmitry Sledneu
International Journal of Metaheuristics (IJMHEUR), Vol. 3, No. 2, 2014

Abstract: A straightforward natural iterative heuristic for correlation clustering in the general setting is to start from singleton clusters and whenever merging two clusters improves the current quality score merge them into a single cluster. We analyse the approximation and complexity aspects of this heuristic and its three simple deterministic or random refinements.

Online publication date: Fri, 25-Jul-2014

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