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The Cluster Editing Problem: Implementations and Experiments

  • Frank Dehne
  • Michael A. Langston
  • Xuemei Luo
  • Sylvain Pitre
  • Peter Shaw
  • Yun Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4169)

Abstract

In this paper, we study the cluster editing problem which is fixed parameter tractable. We present the first practical implementation of a FPT based method for cluster editing, using the approach in [6,7], and compare our implementation with the straightforward greedy method and a solution based on linear programming [3]. Our experiments show that the best results are obtained by using the refined branching method in [7] together with interleaving (re-kernelization). We also observe an interesting lack of monotonicity in the running times for “yes” instances with increasing values of k.

Keywords

Binary Search Vertex Cover Edit Distance Common Neighbor Greedy Method 
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 2006

Authors and Affiliations

  • Frank Dehne
    • 1
  • Michael A. Langston
    • 2
  • Xuemei Luo
    • 1
  • Sylvain Pitre
    • 1
  • Peter Shaw
    • 3
  • Yun Zhang
    • 2
  1. 1.School of Computer ScienceCarleton UniversityOttawaCanada
  2. 2.Department of Computer ScienceUniversity of TennesseeKnoxvilleUSA
  3. 3.Department of Computer ScienceUniversity of NewcastleNewcastleAustralia

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