Fast algorithm for mining global maximum frequent itemsets based on FP-tree

Most mining maximum frequent itemsets algorithm based on local data base,so a fast algorithm for Mining Global Maximum Frequent Itemsets based on Frequent pattern tree(MGMFIF) was proposed.MGMFIF mined all global frequent items and made itemset,then local Frequent-Pattern tree(FP-tree) of each node was constructed based on this itemset.Finally,this itemset was chose as global maximum frequent itemsets,and all the global maximum frequent itemsets were obtained by top-down strategy.By adopting FP-tree structure,MGMFIF greatly reduced database scanning times and runtime comparing to Apriori-like algorithms.MGMFIF remarkably lessened candidate itemsets and communication traffic by using top-down strategy.Experimental results suggested that MGMFIF was fast and effective.