Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Fast discovery of association rules
Advances in knowledge discovery and data mining
Representative Association Rules and Minimum Condition Maximum Consequence Association Rules
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
Mining with Cover and Extension Operators
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Representative Association Rules
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
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In the paper we consider the knowledge in the form of association rules. The consequents derivable from the given set of association rules constitute the theory for this rule set. We apply maximal covering rules as a concise representation of the theory. We prove that maximal covering rules have precisely computable values of support and confidence, though the theory can contain rules for which these values can be only estimated. Efficient methods of direct and incremental computation of maximal covering rules are offered.