Inconsistency in heterogeneous knowledge-integration systems with non-monotonic information exchange is a major concern as it renders systems useless at its occurrence. For the knowledge-integration framework of Multi-Context Systems, the problem of finding all possible resolutions to inconsistency has been addressed previously and some basic steps have been proposed to find most preferred resolutions. Here, we refine the techniques of finding preferred resolutions of inconsistency in two directions. First, we extend available qualitative methods using domain knowledge on the intention and category of information exchange to minimize the number of categories that are affected by a resolution. Second, we present a quantitative inconsistency measure for inconsistency resolutions, being suitable for scenarios where no further domain knowledge is available. © 2012 Springer-Verlag.
CITATION STYLE
Weinzierl, A. (2012). Comparing inconsistency resolutions in multi-context systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7415 LNCS, pp. 158–174). https://doi.org/10.1007/978-3-642-31467-4_11
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