Solving conflicts in information merging by a flexible interpretation of atomic propositions

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Journal Article
Artificial Intelligence, 2011, 175 (11), pp. 1815 - 1855
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Although many techniques for merging conflicting propositional knowledge bases have already been proposed, most existing work is based on the idea that inconsistency results from the presence of incorrect pieces of information, which should be identified and removed. In contrast, we take the view in this paper that conflicts are often caused by statements that are inaccurate rather than completely false, suggesting to restore consistency by interpreting certain statements in a flexible way, rather than ignoring them completely. In accordance with this view, we propose a novel approach to merging which exploits extra-logical background information about the semantic relatedness of atomic propositions. Several merging operators are presented, which are based on different formalizations of this background knowledge, ranging from purely qualitative approaches, related to possibilistic logic, to quantitative approaches with a probabilistic flavor. Both syntactic and semantic characterizations are provided for each merging operator, and the computational complexity is analyzed. © 2011 Elsevier B.V.
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