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On boolean representation of continuous data biclustering

  • University of Warsaw

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Biclustering is considered as the method of finding two-dimensional subgroups in a matrix of scalars. The paper introduces a new approach to biclustering continuous matrices on the basis of boolean function analysis. We draw the strong relation between inclusion-maximal (maximal with respect to inclusion) biclusters of the assumed maximal difference between the data in a bicluster and prime implicants of a boolean function describing the data. These biclusters are called similarity biclusters. In the opposition to them, a new notion of dissimilarity biclusters was also introduced in the paper.

Original languageEnglish
Pages (from-to)193-217
Number of pages25
JournalFundamenta Informaticae
Volume167
Issue number3
DOIs
Publication statusPublished - 2019

Keywords

  • Bicluster
  • Boolean reasoning
  • Continuous data biclustering
  • Discernibility function
  • Dissimilarity biclusters
  • Prime implicants
  • Similarity biclusters

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Algebra and Number Theory
  • Information Systems
  • Computational Theory and Mathematics

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