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IEEE Systems and Information Engineering Design Symposium, 2003
Frequent itemsets mining plays an essential role in data mining, but it often generates a large number of redundant itemsets that reduce the efficiency of the mining task. Frequent closed itemsets are subset of frequent itemsets, but they contain all information of frequent itemsets. The most existing methods of frequent closed itemset mining are apriori-based. The efficiency of those methods is limited to the repeated database scan and the candidate set generation. This paper proposes adoi:10.1109/sieds.2003.157999 fatcat:g5mqjqundjc7njs4em3asasilm