A Constrained Maximum Frequent Itemsets Incremental Mining Algorithm
Han Wang, Lingfu Kong · 2007 IFIP International Conference on Network and Parallel Computing Workshops (NPC 2007) · 2007
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.