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Probabilistic reasoning with facts and rules in deductive databases

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Symbolic and Quantitative Approaches to Uncertainty (ECSQARU 1991)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 548))

Abstract

In this paper we present a new method for probabilistic reasoning with true facts and uncertain rules within a deductive database. Besides a cautious approach to inferences on uncertain rules, we show a default approach for uncertainty reasoning including factual knowledge, based on the ideas of maximal context and detachment. Integrated into a database these approaches support many important applications with probabilistic value dependencies. One sample application will be provided: Lead qualification within a marketing database.

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Author information

Authors and Affiliations

  1. Wilhelm-Schickard-Institut, Universität Tübingen, Sand 13, D-7400, Tübingen 1

    H. Thöne & U. Güntzer

  2. Institut für Informatik, Techn. Universität München, Orleansstr. 34, D-8000, München 80

    W. Kießling

Authors
  1. H. Thöne
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  2. U. Güntzer
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  3. W. Kießling
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Editor information

Rudolf Kruse Pierre Siegel

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© 1991 Springer-Verlag Berlin Heidelberg

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Thöne, H., Güntzer, U., Kießling, W. (1991). Probabilistic reasoning with facts and rules in deductive databases. In: Kruse, R., Siegel, P. (eds) Symbolic and Quantitative Approaches to Uncertainty. ECSQARU 1991. Lecture Notes in Computer Science, vol 548. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54659-6_111

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  • DOI: https://doi.org/10.1007/3-540-54659-6_111

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54659-7

  • Online ISBN: 978-3-540-46426-6

  • eBook Packages: Springer Book Archive

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