Theory of Computing Systems

, Volume 38, Issue 4, pp 373–392 | Cite as

Graph-Modeled Data Clustering: Exact Algorithms for Clique Generation

  • Jens  Gramm
  • Jiong Guo
  • Falk Hüffner
  • Rolf Niedermeier


We present efficient fixed-parameter algorithms for the NP-complete edge modification problems Cluster Editing and Cluster Deletion. Here, the goal is to make the fewest changes to the edge set of an input graph such that the new graph is a vertex-disjoint union of cliques. Allowing up to k edge additions and deletions (Cluster Editing), we solve this problem in O(2.27k + |V|3) time; allowing only up to k edge deletions (Cluster Deletion), we solve this problem in O(1.77k + |V|3) time. The key ingredients of our algorithms are two easy to implement bounded search tree algorithms and an efficient polynomial-time reduction to a problem kernel of size O(k3). This improves and complements previous work. Finally, we discuss further improvements on search tree sizes using computer-generated case distinctions.


Search Tree Input Graph Edge Addition Edge Deletion Search Tree Algorithm 
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 2005

Authors and Affiliations

  1. 1.Wilhelm-Schickard-Institut fur Informatik, Universitat Tubingen, Sand 13, D-72076 TubingenGermany
  2. 2.Institut fur Informatik, Friedrich-Schiller-Universitat Jena, Ernst-Abbe-Platz 2, D-07743 JenaGermany

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