Fast discovery of association rules
Advances in knowledge discovery and data mining
Combining Discrete Algorithmic and Probabilistic Approaches in Data Mining
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Local and Global Methods in Data Mining: Basic Techniques and Open Problems
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Probabilistic Models for Query Approximation with Large Sparse Binary Data Sets
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Data Mining and Knowledge Discovery
Mining correct properties in incomplete databases
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
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The purpose of this paper is to examine the usability of Bonferroni-type combinatorial inequalities to estimation of support of itemsets as well as general Boolean expressions. Families of inequalities for various types of Boolean expressions are presented and evaluated experimentally.