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 ...
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
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. ...
—We perform a statistical analysis and describe the asymptotic behavior of the frequency and size distribution of δoccurrent, minimal δ-occurrent, and maximal δ-occurrent item...