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Algorithms for Computation of Concept Trilattice of Triadic Fuzzy Context

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Advances in Computational Intelligence (IPMU 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 299))

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Abstract

Triadic concept analysis (TCA) is a method of relational data analysis whose aim is to extract a hierarchically structured set of particular clusters from a three-way data describing objects, attributes, and conditions. We present two algorithms for the problem of computing all such clusters from a data describing degrees to which objects have attributes under conditions.

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Author information

Authors and Affiliations

  1. DAMOL (Data Analysis and Modeling Laboratory), Department of Computer Science, Palacký University, Olomouc, Czech Republic

    Petr Osicka

Authors
  1. Petr Osicka
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco  & Benedetto Matarazzo  & 

  2. CNRS UMR 7606, DAPA, LIP6 8, Université Pierre et Marie Curie - Paris6, rue du Capitaine Scott, F-75015, Paris, France

    Bernadette Bouchon-Meunier

  3. Dip. Matematica e Informatica, Università di Perugia, 06123, Perugia, Italy

    Giulianella Coletti

  4. Department of Computer and Management Science, University of Trento, Via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi

  5. Machine Intelligence Institute — IONA College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2012 Springer-Verlag Berlin Heidelberg

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Osicka, P. (2012). Algorithms for Computation of Concept Trilattice of Triadic Fuzzy Context. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31718-7_23

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  • DOI: https://doi.org/10.1007/978-3-642-31718-7_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31717-0

  • Online ISBN: 978-3-642-31718-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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