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International Conference on Scalable Uncertainty Management

SUM 2020: Scalable Uncertainty Management pp 84–97Cite as

Measuring Disagreement with Interpolants

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 12322)

Abstract

We consider the problem of quantitatively assessing the conflict between knowledge bases in knowledge merging scenarios. Using the notion of Craig interpolation we define a series of disagreement measures and analyse their compliance with properties proposed in previous work by Potyka. We study basic complexity theoretic questions in that scenario and discuss the suitability of our approaches .

Keywords

  • Disagreement measure
  • Craig interpolation

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  • DOI: 10.1007/978-3-030-58449-8_6
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Notes

  1. 1.

    http://mthimm.de/misc/rst_dismes_proofs.pdf.

  2. 2.

    http://mthimm.de/misc/rst_dismes_proofs.pdf.

  3. 3.

    More specifically, the smallest size of a \(\phi '\in [\phi ]\).

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Acknowledgements

The research reported here was partially supported by the Deutsche Forschungsgemeinschaft (grant DE1983/9-1).

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Authors and Affiliations

  1. University of Koblenz-Landau, Koblenz, Germany

    Jandson S. Ribeiro, Viorica Sofronie-Stokkermans & Matthias Thimm

Authors
  1. Jandson S. Ribeiro
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  2. Viorica Sofronie-Stokkermans
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  3. Matthias Thimm
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Corresponding author

Correspondence to Jandson S. Ribeiro .

Editor information

Editors and Affiliations

  1. KU Leuven, Heverlee, Belgium

    Jesse Davis

  2. Artois University, Lens, France

    Karim Tabia

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Ribeiro, J.S., Sofronie-Stokkermans, V., Thimm, M. (2020). Measuring Disagreement with Interpolants. In: Davis, J., Tabia, K. (eds) Scalable Uncertainty Management. SUM 2020. Lecture Notes in Computer Science(), vol 12322. Springer, Cham. https://doi.org/10.1007/978-3-030-58449-8_6

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  • DOI: https://doi.org/10.1007/978-3-030-58449-8_6

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