Mining of frequent itemsets is a fundamental data mining task. Past research has proposed many efficient algorithms for the purpose. Recent work also highlighted the importance of...
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...
This paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. Important notions in our prob...
We consider the problem of concurrent execution of multiple frequent itemset queries. If such data mining queries operate on overlapping parts of the database, then their overall I...
Pawel Boinski, Marek Wojciechowski, Maciej Zakrzew...
We explore in this paper a practicably interesting mining task to retrieve frequent itemsets with memory constraint. As opposed to most previous works that concentrate on improvin...