A well-known problem that limits the practical usage of association rule mining algorithms is the extremely large number of rules generated. Such a large number of rules makes the...
Girish Keshav Palshikar, Mandar S. Kale, Manoj M. ...
The use of frequent itemsets has been limited by the high computational cost as well as the large number of resulting itemsets. In many real-world scenarios, however, it is often ...
Abstract. We present an information-theoretic framework for mining dependencies between itemsets in binary data. The problem of closure-based redundancy in this context is theoreti...
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Recent studies have proposed different methods for mining frequent episodes. In this work, we study the problem of mining closed episodes based on minimal occurrences. We study the...