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Estimations of Similarity in Formal Concept Analysis of Data with Graded Attributes

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 23))

Summary

We study similarity in formal concept analysis of data tables with graded attributes. We focus on similarity related to formal concepts and concept lattices, i.e. the outputs of formal concept analysis. We present several formulas for estimation of similarity of outputs in terms of similarity of inputs. The results answer some problems which arose in previous investigation as well as some natural questions concerning similarity in conceptual data analysis. The derived formulas enable us to compute an estimation of similarity of concept lattices much faster than one can compute their exact similarity. We omit proofs due to lack of space.

Supported by grant No. 201/05/0079 of the Czech Science Foundation, by institutional support, research plan MSM 6198959214, and by Kontakt 1-2006-33.

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Author information

Authors and Affiliations

  1. Dept. Computer Science, Palacký University, Tomkova 40, CZ-779 00, Olomouc, Czech Republic

    Radim Bělohlávek & Vilém Vychodil

Authors
  1. Radim Bělohlávek
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  2. Vilém Vychodil
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Editor information

Editors and Affiliations

  1. Department of Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel

    Mark Last

  2. Institute of Computer Sciences, Technical University of Lodz, ul. Wolczanska 215, 93-1005, Lodz, Poland

    Piotr S. Szczepaniak

  3. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Piotr S. Szczepaniak

  4. Department of Software Engineering, ORT Braude College, POB. 78, 21982, Karmiel, Israel

    Zeev Volkovich

  5. Department of Computer Science and Engineering, University of South Florida, 4202 E. Fowler Ave., ENB 118, Tampa, FL, 33620, USA

    Abraham Kandel

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© 2006 Springer-Verlag Berlin Heidelberg

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Bělohlávek, R., Vychodil, V. (2006). Estimations of Similarity in Formal Concept Analysis of Data with Graded Attributes. In: Last, M., Szczepaniak, P.S., Volkovich, Z., Kandel, A. (eds) Advances in Web Intelligence and Data Mining. Studies in Computational Intelligence, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33880-2_25

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  • DOI: https://doi.org/10.1007/3-540-33880-2_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33879-6

  • Online ISBN: 978-3-540-33880-2

  • eBook Packages: EngineeringEngineering (R0)

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