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...
In this paper, we propose an efficient algorithm, called ICMiner (Inter-transaction Closed patterns Miner), for mining closed inter-transaction itemsets. Our proposed algorithm co...
Anthony J. T. Lee, Chun-sheng Wang, Wan-Yu Weng, Y...
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
Generalized association rule mining is an extension of traditional association rule mining to discover more informative rules, given a taxonomy. In this paper, we describe a forma...
This poster paper summarizes our solution for mining max frequent generalized itemsets (g-itemsets), a compact representation for frequent patterns in the generalized environment....