A More Relaxed Model for Graph-Based Data Clustering: s-Plex Editing

  • Jiong Guo
  • Christian Komusiewicz
  • Rolf Niedermeier
  • Johannes Uhlmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5564)


We introduce the s -Plex Editing problem generalizing the well-studied Cluster Editing problem, both being NP-hard and both being motivated by graph-based data clustering. Instead of transforming a given graph by a minimum number of edge modifications into a disjoint union of cliques (Cluster Editing), the task in the case of s -Plex Editing is now to transform a graph into a disjoint union of so-called s-plexes. Herein, an s-plex denotes a vertex set inducing a (sub)graph where every vertex has edges to all but at most s vertices in the s-plex. Cliques are 1-plexes. The advantage of s-plexes for s ≥ 2 is that they allow to model a more relaxed cluster notion (s-plexes instead of cliques), which better reflects inaccuracies of the input data. We develop a provably efficient and effective preprocessing based on data reduction (yielding a so-called problem kernel), a forbidden subgraph characterization of s-plex cluster graphs, and a depth-bounded search tree which is used to find optimal edge modification sets. Altogether, this yields efficient algorithms in case of moderate numbers of edge modifications.


Search Tree Input Graph Reduction Rule Cluster Graph Relax Model 
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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© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jiong Guo
    • 1
  • Christian Komusiewicz
    • 1
  • Rolf Niedermeier
    • 1
  • Johannes Uhlmann
    • 1
  1. 1.Institut für InformatikFriedrich-Schiller-Universität JenaJenaGermany

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