J.F.: Towards constrained co-clustering in ordered 0/1 data sets

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J.F.: Towards constrained co-clustering in ordered 0/1 data sets (2006)

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by Ruggero G. Pensa , Céline Robardet , Jean-françois Boulicaut , Bâtiment Blaise Pascal

Venue:	In: Proceedings of International Symposium on Methodologies for Intelligent Systems (LNAI
Citations:	7 - 3 self

BibTeX

@INPROCEEDINGS{Pensa06j.f.:towards,
    author = {Ruggero G. Pensa and Céline Robardet and Jean-françois Boulicaut and Bâtiment Blaise Pascal},
    title = {J.F.: Towards constrained co-clustering in ordered 0/1 data sets},
    booktitle = {In: Proceedings of International Symposium on Methodologies for Intelligent Systems (LNAI},
    year = {2006},
    pages = {4203}
}

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Abstract

Abstract. Within 0/1 data, co-clustering provides a collection of biclusters, 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. 1

Keyphrases

data set local pattern interval constraint user-defined constraint subjective interestingness aspect classical need heuristic clustering process denotes time point experimental validation temporal gene expression data set quality optimization boolean property bi-cluster relevancy major step

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