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1 ORPAILLEUR - Knowledge representation, reasonning Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery

Abstract : In this work we present a novel technique for exhaustive bicluster enumeration using formal concept anal-ysis FCA. Particularly, we use pattern structures an ex-tension of FCA dealing with complex data to mine similar row-column biclusters, a specialization of biclustering when attribute values have coherent variations. We show how bi-clustering can benefit from the FCA framework through its ro-bust theoretical description and efficient algorithms. Finally, we evaluate our bicluster mining approach w.r.t. a standard biclustering technique showing very good results in terms of bicluster quality and performance.

Keywords : formal concept analysis data structures biclustering

Autor: Victor Codocedo - Amedeo Napoli -



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