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Abstract
Multi-context systems introduced by Brewka and Eiter provide a promising framework for interlinking heterogeneous and autonomous knowledge sources. The notion of diagnosis has been proposed for analyzing inconsistency in multi-context systems, which captures a pair of subsets of bridge rules of a multi-context system needed to be deactivated and activated unconditionally, respectively, in order to restore the consistency for that system. Generally, diagnoses need to be prioritized from some specific perspectives in order to select the most desirable ones to resolve inconsistency. In this paper, we propose a series of intrinsic approaches to prioritizing diagnoses based on the structure of information exchange over contexts in a multi-context system, which allow us to rank diagnoses in cases where no external knowledge is available. We use a heterogeneous graph, termed information exchange network, to formulate the information exchange over contexts via bridge rules in a multi-context system. Then we propose three kinds of approaches to prioritizing diagnoses based on the information exchange network for a multi-context system. Approaches of the first kind focus on ranking diagnoses by evaluating the impact of potential revision according to each diagnosis on direct information exchange over contexts from different perspectives, whilst approaches of the second kind rank diagnoses by evaluating the impact of potential revision according to each diagnosis on betweenness centralities of contexts with regard to the whole information exchange network. The last one uses the betweenness centralities of bridge rules in the information exchange network to prioritize diagnoses directly.