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Measuring the Quality of Uncertain Information Using Possibilistic Logic

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3571))

Abstract

In previous papers, we have presented a framework for merging structured information in XML involving uncertainty in the form of probabilities, degrees of beliefs and necessity measures [HL04,HL05a,HL05b]. In this paper, we focus on the quality of uncertain information before merging. We first provide two definitions for measuring information quality of individually inconsistent possibilistic XML documents, and they complement the commonly used concept of inconsistency degree. These definitions enable us to identify if an XML document is of good or lower quality when it is inconsistent, as well as enable us to differentiate between documents that have the same degree of inconsistency. We then propose a more general method to measure the quality of an inconsistent possibilistic XML document in terms of a pair of coherence measures.

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Hunter, A., Liu, W. (2005). Measuring the Quality of Uncertain Information Using Possibilistic Logic. In: Godo, L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2005. Lecture Notes in Computer Science(), vol 3571. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11518655_36

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  • DOI: https://doi.org/10.1007/11518655_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27326-4

  • Online ISBN: 978-3-540-31888-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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