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Detecting Inconsistencies in Revision Problems

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Soft Methods for Data Science (SMPS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 456))

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Abstract

When dealing with complex knowledge, inconsistencies become a big problem. One important aspect of handling inconsistencies is their detection. In this paper we consider approaches to detect different types of inconsistencies that may occur in the formulation of revision problems. The general discussion focuses on the revision of probability distributions. In our practical analysis, we refer to probability distributions represented as Markov networks.

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Author information

Authors and Affiliations

  1. ISC Gebhardt, Celle, Germany

    Fabian Schmidt & Jörg Gebhardt

  2. Otto-von-Guericke University, Magdeburg, Germany

    Rudolf Kruse

Authors
  1. Fabian Schmidt
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  2. Jörg Gebhardt
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  3. Rudolf Kruse
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Corresponding author

Correspondence to Fabian Schmidt .

Editor information

Editors and Affiliations

  1. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maria Brigida Ferraro

  2. Department of Statistical Sciences, Sapienza University of Rome, Roma, Italy

    Paolo Giordani

  3. Dept of Basic & Applied Sciences Engg, Sapienza University of Rome, Rome, Italy

    Barbara Vantaggi

  4. Dept of Stoc Metds,Polish Academy of Sci, Systems Research Institute, Warsaw, Poland

    Marek Gagolewski

  5. Dept of Statis&OR and MD, Univ de Oviedo, Oviedo, Spain

    María Ángeles Gil

  6. Dept of Stoc Metds,Polish Aca of Science, Systems Res Inst, Warsaw, Poland

    Przemysław Grzegorzewski

  7. Sys Res Inti, Dept of Stoch Methods, Polish Acadmy Sci in Warsaw, Warsaw, Poland

    Olgierd Hryniewicz

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Schmidt, F., Gebhardt, J., Kruse, R. (2017). Detecting Inconsistencies in Revision Problems. In: Ferraro, M., et al. Soft Methods for Data Science. SMPS 2016. Advances in Intelligent Systems and Computing, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-42972-4_54

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  • DOI: https://doi.org/10.1007/978-3-319-42972-4_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42971-7

  • Online ISBN: 978-3-319-42972-4

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