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Going Weighted: Parameterized Algorithms for Cluster Editing

  • Sebastian Böcker
  • Sebastian Briesemeister
  • Quang B. A. Bui
  • Anke Truss
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5165)

Abstract

The goal of the Cluster Editing problem is to make the fewest changes to the edge set of an input graph such that the resulting graph is a disjoint union of cliques. This problem is NP-complete but recently, several parameterized algorithms have been proposed. In this paper we present a surprisingly simple branching strategy for Cluster Editing. We generalize the problem assuming that edge insertion and deletion costs are positive integers. We show that the resulting search tree has size O(1.82 k ) for edit cost k, resulting in the currently fastest parameterized algorithm for this problem. We have implemented and evaluated our approach, and find that it outperforms other parametrized algorithms for the problem.

Keywords

Search Tree Weighted Graph Input Graph Vertex Pair Transitive Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Sebastian Böcker
    • 1
  • Sebastian Briesemeister
    • 2
  • Quang B. A. Bui
    • 1
  • Anke Truss
    • 1
  1. 1.Lehrstuhl für BioinformatikFriedrich-Schiller-Universität JenaJenaGermany
  2. 2.Div. for Simulation of Biological Systems, ZBIT/WSIEberhard Karls Universität TübingenGermany

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