Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (23): 135-137.DOI: 10.3778/j.issn.1002-8331.2010.23.038

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

Improved algorithm for mining weighted frequent patterns

WANG Yan,XUE Hai-yan,LI Ling-ling,SUN Xin-de   

  1. Department of Computer Science and Application,Zhengzhou Institute of Aeronautic Industry Management,Zhengzhou 450015,China
  • Received:2009-03-31 Revised:2009-05-18 Online:2010-08-11 Published:2010-08-11
  • Contact: WANG Yan


王 艳,薛海燕,李玲玲,孙新德   

  1. 郑州航空工业管理学院 计算机科学与应用系,郑州 450015
  • 通讯作者: 王 艳

Abstract: FP-growth is a classic algorithm of mining frequent patterns and it uses FP-tree to store all items in transaction database,which are related with frequent patterns.But it does not meet for mining weighted frequent patterns.So in this paper the shortages of the existing algorithms for mining weighted frequent patterns in some other papers are analyzed,the structure of a traditional FP-tree is improved and a new weighted FP-tree is constructed.Then an effective algorithm to handle the problem of mining weighted frequent patterns is proposed and analyzed through an example.Experiment results show that the new algorithm is effective for large database.

Key words: data mining, weighted FP-tree, weighted frequent pattern

摘要: FP-growth算法是挖掘频繁项集的经典算法,它利用FP-树这种紧凑的数据结构存储事务数据库与频繁项集挖掘相关的全部信息,但对于挖掘加权频繁项集并不合适。分析了现有加权频繁项集挖掘算法中存在的问题,并对FP-树进行改进,构造新的加权FP-树,提出了有效挖掘加权频繁项集的算法。最后举例说明了算法的挖掘过程,并通过实验验证了算法的有效性。

关键词: 数据挖掘, 加权FP-树, 加权频繁项集

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