A Constrained Maximum Frequent Itemsets Incremental Mining Algorithm

Abstract

Among all data mining algorithms of association rules, incremental algorithms fit dataset updating better. This paper proposes a novel algorithm of mining the constrained maximum frequent itemsets namely algorithm ISL-DM. This algorithm filters the item-sequences which can not get or become the maximum frequent itemsets by the constraint conditions, and it can always surround getting the maximum frequent itemsets currently.