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Information Quality and Uncertainty

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Uncertainty Modeling

Part of the book series: Studies in Computational Intelligence ((SCI,volume 683))

Abstract

The quality of a piece of information depends, among others, on the certainty that can be attached to it, which relates to the degree of confidence that can be put in it. This paper discusses various components to be considered when assessing this certainty level. It shows that they cover a wide range of different types of uncertainty and provide a highly relevant application domain for theoretical questioning about uncertainty modelling. It also describes several frameworks that have been considered for this task.

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Notes

  1. 1.

    This paper is based on part of the panel which has been organised by Prof. Kovalerchuk at IPMU2012 on the general topic “Uncertainty Modelling”.

  2. 2.

    Conversely, a source is said to be complete if, when a piece of information is true, the source provides it [4]. This useful characterisation, related both to the source omniscience and “sharing communication type”, is however less central for the assessment of the information uncertainty.

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Author information

Authors and Affiliations

  1. Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 Place Jussieu, 75005, Paris, France

    Marie-Jeanne Lesot

  2. Université Paris 8, EA 4383, LIASD, 93526, Saint-Denis, France

    Adrien Revault d’Allonnes

Authors
  1. Marie-Jeanne Lesot
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  2. Adrien Revault d’Allonnes
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Correspondence to Marie-Jeanne Lesot .

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Editors and Affiliations

  1. University of Texas at El Paso, Department of Computer Science University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

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Lesot, MJ., Revault d’Allonnes, A. (2017). Information Quality and Uncertainty. In: Kreinovich, V. (eds) Uncertainty Modeling. Studies in Computational Intelligence, vol 683. Springer, Cham. https://doi.org/10.1007/978-3-319-51052-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-51052-1_9

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