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Fuzzy Association Rules on Data with Undefined Values

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications (IPMU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 855))

Abstract

Handling of missing values is a very common in data processing. However, data values may be missing not only because of lack of information, but also because of undefinedness (such as asking for the age of non-married person’s spouse). The aim of this paper is to propose an extension of fuzzy association rules framework for data with undefined values.

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Acknowledgements

Authors acknowledge support by project “LQ1602 IT4Innovations excellence in science” and by GAČR 16-19170S.

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Authors and Affiliations

  1. Institute for Research and Applications of Fuzzy Modeling, Centre of Excellence IT4Innovations, Division University of Ostrava, 30. dubna 22, 701 03, Ostrava, Czech Republic

    Petra Murinová, Viktor Pavliska & Michal Burda

Authors
  1. Petra Murinová
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  2. Viktor Pavliska
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  3. Michal Burda
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Corresponding author

Correspondence to Petra Murinová .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Institute for Research and Applications, University of Ostrava, Ostrava, Czech Republic

    Irina Perfilieva

  5. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  6. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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Murinová, P., Pavliska, V., Burda, M. (2018). Fuzzy Association Rules on Data with Undefined Values. In: Medina, J., Ojeda-Aciego, M., Verdegay, J., Perfilieva, I., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2018. Communications in Computer and Information Science, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-91479-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-91479-4_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91478-7

  • Online ISBN: 978-3-319-91479-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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