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Towards Constrained Co-clustering in Ordered 0/1 Data Sets

  • Ruggero G. Pensa
  • Céline Robardet
  • Jean-François Boulicaut
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4203)

Abstract

Within 0/1 data, co-clustering provides a collection of bi-clusters, i.e., linked clusters for both objects and Boolean properties. Beside the classical need for grouping quality optimization, one can also use user-defined constraints to capture subjective interestingness aspects and thus to improve bi-cluster relevancy. We consider the case of 0/1 data where at least one dimension is ordered, e.g., objects denotes time points, and we introduce co-clustering constrained by interval constraints. Exploiting such constraints during the intrinsically heuristic clustering process is challenging. We propose one major step in this direction where bi-clusters are computed from collections of local patterns. We provide an experimental validation on two temporal gene expression data sets.

Keywords

Local Pattern Rand Index Gene Expression Data Analysis Interval Constraint Boolean Property 
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

  • Ruggero G. Pensa
    • 1
  • Céline Robardet
    • 1
  • Jean-François Boulicaut
    • 1
  1. 1.LIRIS CNRS UMR 5205INSA LyonVilleurbanneFrance

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