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Conference papers

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

Nyoman Juniarta 1 Miguel Couceiro 1 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
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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Submitted on : Tuesday, August 13, 2019 - 3:11:59 PM
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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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