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A Unified Approach to Biclustering Based on Formal Concept Analysis and Interval Pattern Structures

Nyoman Juniarta
Miguel Couceiro
Amedeo Napoli

Abstract

In a matrix representing a numerical dataset, a bicluster is a submatrix whose cells exhibit similar behavior. Biclustering is naturally related to Formal Concept Analysis (FCA) where concepts correspond to maximal and closed biclusters in a binary dataset. In this paper, a unified characterization of biclustering algorithms is proposed using FCA and pattern structures, an extension of FCA for dealing with numbers and other complex data. Several types of biclusters -- constant-column, constant-row, additive, and multiplicative -- and their relation to interval pattern structures is presented.
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Dates and versions

hal-02266200 , version 1 (13-08-2019)

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  • HAL Id : hal-02266200 , version 1

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Nyoman Juniarta, Miguel Couceiro, Amedeo Napoli. A Unified Approach to Biclustering Based on Formal Concept Analysis and Interval Pattern Structures. DS 2019 - 22nd International Conference on Discovery Science, Oct 2019, Split, Croatia. ⟨hal-02266200⟩
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