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Measuring Consistency Gain and Information Loss in Stepwise Inconsistency Resolution

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6717))

Abstract

Inconsistency is a usually undesirable feature of many kinds of data and knowledge. But altering the information in order to make it less inconsistent may result in the loss of information. In this paper we analyze this trade-off. We review some existing proposals and make new proposals for measures of inconsistency and information. We prove that in both cases the various measures are all pairwise incompatible. Then we introduce the concept of stepwise inconsistency resolution and show what happens in case an inconsistency resolution step applies a deletion, a weakening, or a splitting operation.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Towson University, Towson, MD, 21252, USA

    John Grant

  2. Department of Computer Science, University of Maryland, College Park, MD, 20742, USA

    John Grant

  3. Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK

    Anthony Hunter

Authors
  1. John Grant
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  2. Anthony Hunter
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Editor information

Editors and Affiliations

  1. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, BT9 5BN, Belfast, UK

    Weiru Liu

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© 2011 Springer-Verlag Berlin Heidelberg

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Grant, J., Hunter, A. (2011). Measuring Consistency Gain and Information Loss in Stepwise Inconsistency Resolution. In: Liu, W. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2011. Lecture Notes in Computer Science(), vol 6717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22152-1_31

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  • DOI: https://doi.org/10.1007/978-3-642-22152-1_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22151-4

  • Online ISBN: 978-3-642-22152-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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