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Fusion and normalization of quantitative possibilistic networks

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Abstract

The problem of merging multiple-source uncertain information is a crucial issue in many applications. This paper proposes an analysis of possibilistic merging operators where uncertain information is encoded by means of product-based (or quantitative) possibilistic networks. We first show that the product-based merging of possibilistic networks having the same DAG structures can be easily achieved in a polynomial time. We then propose solutions to merge possibilistic networks having different structures and where the union of their graphs is free of cycles. Then we show how to deal with merged networks having cycles. Lastly, we handle the sub-normalization problem which reflects the presence of conflicts between different sources.

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Authors and Affiliations

  1. Université Lille-Nord de France, Artois, Rue Jean Souvraz, 62307, Lens, France

    Salem Benferhat & Faiza Titouna

  2. CRIL, 62307, Lens, France

    Salem Benferhat & Faiza Titouna

  3. CNRS UMR 8188, 62307, Lens, France

    Salem Benferhat & Faiza Titouna

  4. Université Badji Mokhtar, Annaba, Algeria

    Faiza Titouna

Authors
  1. Salem Benferhat
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  2. Faiza Titouna
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Correspondence to Salem Benferhat.

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Benferhat, S., Titouna, F. Fusion and normalization of quantitative possibilistic networks. Appl Intell 31, 135–160 (2009). https://doi.org/10.1007/s10489-008-0118-y

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  • DOI: https://doi.org/10.1007/s10489-008-0118-y

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