Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (29): 134-136.

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Mining algorithm of global frequent items in distributed database

LIU Qun,JIA Jiong   

  1. College of Mathematics,Physics and Information Engineering,Zhejiang Normal University,Jinhua,Zhejiang 321004,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-10-11 Published:2011-10-11

一种分布式全局频繁项集挖掘方法

刘 群,贾 泂   

  1. 浙江师范大学 数理与信息工程学院,浙江 金华 321004

Abstract: A kind of algorithm BFM-MGFIS(Based on Frequent-pattern tree and Most frequent items Mining Global Frequent Items Set) in distributed database is proposed.This algorithm introduces subset enumeration tree to relize mining orderly and pruning globally,not only greatly reducing candidate sets,but also promoting parallelism capacity.Experimental results show that the algorithm is effective.

Key words: frequent-pattern tree, maximum frequent items, global frequent items

摘要: 提出一种基于频繁模式树与最大频繁项集的分布式全局频繁项集挖掘算法BFM-MGFIS,该算法引入子集枚举树以实现有序挖掘与全局剪枝策略,有效地减小了候选数据集且提高了并行性,实验表明本文提出的算法是有效可行的。

关键词: 频繁模式树, 最大频繁项集, 全局频繁项集