Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (27): 127-129.DOI: 10.3778/j.issn.1002-8331.2009.27.038

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

One new association rules mining approach

PENG Zhen1,2,PEI Li-li3,YANG Bing-ru1   

  1. 1.School of Information Engineering,Beijing University of Science and Technology,Beijing 100083,China
    2.Department of Computer,North China Institute of Science and Technology,Beijing 101601,China
    3.Tangshan Industrial Vocation-Technical College,Tangshan,Heibei 063020,China
  • Received:2009-02-17 Revised:2009-03-27 Online:2009-09-21 Published:2009-09-21
  • Contact: PENG Zhen

一种新的关联规则挖掘方法

彭 珍1,2,裴丽丽3,杨炳儒1   

  1. 1.北京科技大学 信息工程学院 知识工程研究所,北京 100083
    2.华北科技学院 计算机系,北京 101601
    3.唐山工业职业技术学院,河北 唐山 063020
  • 通讯作者: 彭 珍

Abstract: Mining association rules is one of the important tasks in data mining.With the aim to further improve the cognitive feature and the performance of association rules mining algorithm,the paper proposes one new idea of association rules mining and one RBFCM-based association rules mining algorithm,which uses rule based fuzzy cognitive map to represent knowledge and to be accessible fuzzy inference to each association rule mined as so to reduce the frequency of interaction with the database.And the experiment demonstrates that the approach effectively increases the effectiveness of association rules mining and the intelligence compared with the Apriori algorithm.

Key words: data mining, frequent itemsets, association rules, Rule Based Fuzzy Cognitive Map(RBFCM), accessible inference

摘要: 关联规则挖掘是数据挖掘的主要任务之一。为了进一步提高关联规则挖掘算法的认知特性和运算效果,提出了一种新的关联规则挖掘思想并由此构造了一种基于规则模糊认知图的关联规则挖掘算法。该算法使用规则模糊认知图进行知识表示,对每个挖掘到的关联规则进行可达模糊推理,从而减少了与数据库交互的次数。实验证明该方法与Apriori的关联规则算法相比,提高了关联规则挖掘的效率,增强了智能化程度。

关键词: 数据挖掘, 频繁项集, 关联规则, 规则模糊认知图, 可达推理

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