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
Probabilistic Approach to Association Rules in Incomplete Databases
WAIM '00 Proceedings of the First International Conference on Web-Age Information Management
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Incomplete Database Issues for Representative Association Rules
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
Representative Association Rules
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Mining Association Rules for Estimation and Prediction
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Association Rules in Incomplete Databases
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
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A notion of legitimate definitions of support and confidence under incompleteness is defined. Properties of generic legitimate definitions of support and confidence are investigated. We show that in the case of incompleteness legitimate association rules can be derived from legitimate representative rules by the cover operator. It is proved that the minimum condition maximum consequence association rules under incompleteness constitute a subset of representative rules of the same type. Algorithms for generating association rules under incompleteness are offered.