计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (25): 131-133.DOI: 10.3778/j.issn.1002-8331.2010.25.039

• 数据库、信号与信息处理 • 上一篇    下一篇

基于Vague集的Apriori算法的改进

沈小虎,余建坤   

  1. 云南财经大学 信息学院,昆明 650221
  • 收稿日期:2010-01-13 修回日期:2010-06-10 出版日期:2010-09-01 发布日期:2010-09-01
  • 通讯作者: 沈小虎

Improvement of Apriori algorithm based on Vague sets

SHEN Xiao-hu,YU Jian-kun   

  1. College of Information,Yunnan University of Finance and Economics,Kunming 650221,China
  • Received:2010-01-13 Revised:2010-06-10 Online:2010-09-01 Published:2010-09-01
  • Contact: SHEN Xiao-hu

摘要: 当前研究的关联规则挖掘隐含着一个假定:待挖掘数据库中每条记录的全部属性都是完整的。然而现实中得到的数据可能是不完整的,在这种情况下将无法使用传统的算法。为了解决这个问题,引入Vague集并给出基于Vague集的支持度和置信度定义,将经典的Apriori算法推广到Vague集上。最后通过一个例子来验证算法的有效性。

关键词: Vague集, 关联规则挖掘, 数据挖掘

Abstract: The research for mining association rules implies assumption:The items of databases are complete.However in the practical applications the data may be incomplete,in which case it would not be able to use the traditional method.In order to solve this problem,the definitions of the support and confidence based on Vague sets are given.And the classic Apriori algorithm is extended by Vague sets.Finally the efficiency of the algorithm is validated through an example.

Key words: Vague sets, association rule mining, data mining

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