Algorithm Based on FP-tree for Mining Frequent Closed Itemsets
Most mining algorithms of frequent Itemsets are based on Apriori. However,these algorithms make huge candidate itemsets and scan large database repeatedly. In order to solve this problem,in this paper a new depth-first search algorithm called FP-MFIA based on FP-tree(frequent pattern tree) for mining maximal frequent Itemsets is proposed. This algorithm makes use of bitmap to cut down the frequency of scanning the database,which saves executing time. In addition,FP-MFIA adopts efficient strategies to distinguish maximal frequent itemsets and a new superset checking method based on projection of the maximal frequent itemsets,which can reduce the cost of accessing the tree. The experiments show that FP-MFIA is more efficient and fast.