Handling Vague and Qualitative Criteria in
Case-Based Reasoning Applications

Ivo Vollrath

Artificial Intelligence/Knowledge Based Systems group, University of Kaiserslautern
vollrath@informatik.uni-kl.de
http: //wwwagr.informatik.uni-kl.de/



Abstract. In some case-based reasoning (CBR) applications for decision 
support there are a number of vague or qualitative criteria that have
to be taken into account by the similarity measure. Sometimes, these criteria 
are very hard to acquire or quantify and they often conflict with the
main quality criterion that is measured by the similarity function. Surprisingly, 
this sometimes is true even for cost criteria (mostly believed to
be quite quantitative): in certain applications, the acceptable cost limit
depends mostly on the quality that is available and thus cannot be specified 
a priori. This paper discusses the problems arising from this kind
of implicit criteria and shows approaches of how they can be integrated
into the similarity measure of a case-based reasoning system without the
need of artificially quantifying them.
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