Abstract
Abstract Non-deterministic Information Systems (NISs) are well known as systems for handling information incompleteness in data. In our previous work, we have proposed NIS-Apriori algorithm aimed at extraction of decision rules from NISs. NIS-Apriori employs the minimum and the maximum supports for each descriptor, and it effectively calculates the criterion values for defining rules. In this paper, we focus on \(Lipski\mbox{'}s\) Incomplete Information Databases (IIDs), which handle non-deterministic information by means of the sets of values and intervals. We clarify how to understand decision rules in IIDs and appropriately adapt our NIS-Apriori algorithm to generate them. Rule generation in IIDs turns out to be more flexible than in NISs.KeywordsLipski’s incomplete information databasesRule generationApriori algorithmExternal and internal interpretationsRough sets
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