一种改进的增量挖掘算法  

Improved Incremental Mining Algorithm

作　　者：李春喜[1] 赵雷[1] 

机构地区：[1]苏州大学计算机科学与技术学院,江苏苏州215006

出　　处：《计算机工程》2010年第24期42-44,共3页Computer Engineering

基　　金：国家自然科学基金资助项目(61073061)

摘　　要：Pre-FUFP算法基于次频繁项的概念有效处理了频繁模式树的更新,但当有次频繁项变成频繁项时,需要判定原数据库中哪些事务包含该数据项。为此,通过引入次频繁项对应原事务标识符的索引确定需要处理原数据库的事务,减少这一过程所消耗的时间,并用基于压缩FP-tree和矩阵技术代替原始FP-growth挖掘出频繁模式。实验证明该算法在时间效率上较Pre-FUFP有大幅度提高。Pre-FUFP algorithm updates the frequent pattern tree effectively based on the concept of pre-large items. But when there are pre-large items becoming frequent items, the algorithm need check which transactions in the original database contains the pre-large items. In this paper, an index table of pre-large items to their corresponding original transactions is proposed to find out the transactions need to be processed and fasten the process of FUFP-tree modification. The frequent patterns by using compact FP-Tree and matrix based algorithm are worked out. Experimental result shows the algorithm outperforms the pre-FUFP algorithm.

关 键 词：频繁模式 次频繁项集 增量挖掘 

分 类 号：TP311.52[自动化与计算机技术—计算机软件与理论]