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

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 unied 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.
Document type :
Conference papers
Complete list of metadatas

Cited literature [21 references]  Display  Hide  Download

https://hal.inria.fr/hal-02266200
Contributor : Nyoman Juniarta <>
Submitted on : Tuesday, August 13, 2019 - 3:11:59 PM
Last modification on : Wednesday, August 14, 2019 - 1:13:34 AM

File

nj_discoveryscience.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02266200, version 1

Collections

Citation

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

Share

Metrics

Record views

61

Files downloads

91