关键词: 数据挖掘, 数据库划分, 多支持度, 频繁模式

Abstract: Mining association rules from a large database have been described as an important problem of database mining.In this paper，a novel algorithm DPCFP-growth is proposes.The algorithm based upon the MSApirori takes advantage of the advantage and offsets the disadvantage of CFP-growth that CFP-growth always needs so much EMS memory in large database that the computer can’t meet it.In DPCFP-growth algorithm，according to characters of MIS-tree，firstly partition a large database into some smaller databases which EMS memory of computer can meet them.Secondly the algorithm takes in the thinking of the CFP-growth to mining local frequent patterns.Finally，the algorithm parses the set of all the local frequent patterns to get final frequent patterns.The experiments show that the DPCFP-growth algorithm has more superiority to previous algorithm.

Key words: data mining, database partition, multiple minimum supports, frequent pattern