计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (6): 227-230.DOI: 10.3778/j.issn.1002-8331.2010.06.066

• 工程与应用 • 上一篇    下一篇

正相关关联规则及其在中医药中的应用

肖光磊1,陆建峰1,李文林2,陈涤平2   

  1. 1.南京理工大学 计算机科学与技术学院,南京 210094
    2.南京中医药大学,南京 210046
  • 收稿日期:2008-08-25 修回日期:2008-10-28 出版日期:2010-02-21 发布日期:2010-02-21
  • 通讯作者: 肖光磊

Positively correlated association rules and its application in traditional Chinese medicine

XIAO Guang-lei1,LU Jian-feng1,LI Wen-lin2,CHEN Di-ping2   

  1. 1.School of Computer Science & Technology,Nanjing University of Science & Technology,Nanjing 210094,China
    2.Nanjing University of Traditional Chinese Medicine,Nanjing 210046,China
  • Received:2008-08-25 Revised:2008-10-28 Online:2010-02-21 Published:2010-02-21
  • Contact: XIAO Guang-lei

摘要: 关联规则是数据挖掘的重要模式之一,有着极其重要的应用价值,但是传统的基于支持度-置信度框架的关联规则挖掘算法在实际应用中存在诸多不足。引入相关性分析,设计了一种基于遗传算法的正相关关联规则挖掘算法。最后,将该算法应用于名老中医临证经验分析挖掘的实际问题,实验证明,它能有效地弥补传统关联规则挖掘算法的不足。

关键词: 数据挖掘, 关联规则, 遗传算法, 相关分析

Abstract: Association rule is one of the important modes in data mining and has a very important value.However,the traditional algorithms of association rules which are based on support and confidence framework have lots of limitation in practical applications.A new algorithm for mining positively correlated association rules based on genetic algorithms is designed.Finally,the algorithm is applied to the mining and analysis of clinical experience of famous herbalist doctors.Experimental results show that the new method can remedy the deficiency of traditional association rules algorithm.

Key words: data mining, association rules, genetic algorithms, correlated calculation

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