Rule generation in Lipski's incomplete information databases

Authors:
Hiroshi Sakai;Michinori Nakata;Dominik Ślęzak
Affiliations:
Mathematical Sciences Section, Department of Basic Sciences, Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan;Faculty of Management and Information Science, Josai International University, Togane, Chiba, Japan;Institute of Mathematics, University of Warsaw, Warsaw, Poland and Infobright Inc., Warsaw, Poland
Venue:
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Year:
2010

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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'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.