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基于子规则的关联规则生成算法 被引量:3

An Algorithm for Generating Association Rules Based on the Information of Sub Ru les
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摘要 关联规则是数据挖掘中重要的课题之一。传统的由频繁项目集产生关联规则的 方法由于要考虑频繁项目集的每一个非空真子集,当频繁项目集的长度较长时代价较大。文 中提出用K项子频繁项目集导出关联规则以后得到的有用信息以指导K+1项父频繁项目集产生 强关联规则,由于利用了前面已有的有用信息,当频繁模式长度很长时,或者可信度较高时 ,效率尤其显著。 One of the most important data mining problems is mining association rules. Traditional method for generating association rules from frequent itemse ts is expensive because it have to consider each real sub set of the frequent it emset which is not null. The paper considers how to use the obtained useful rule information of frequent sub K-itemsets to generate strong association rules for the frequent parent (K+1)-itemsets, the performance will be better when the fre quent itemset is very long or the confidence is very high, because it uses the o btained useful information.
出处 《计算机工程》 CAS CSCD 北大核心 2004年第1期77-79,共3页 Computer Engineering
基金 上海市科委重点基础研究项目(01JC14022)
关键词 频繁项目集 强关联规则 子项目集 父项目集 Frequent itemset Strong association rule Sub itemset Parent item set
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参考文献5

  • 1[1]Han Jiawei, Kamber M. Data Mining : Concepts and Techniques. 北京: 机械工业出版社, 2001
  • 2[2]Zheng Zijian, Kohavi R, Mason L. Real World Performance of Asso - ciation Rule Algorithms . A Short Poster Version to Appear in KDD- 2001
  • 3[3]Agrawal R, Srikant R. Fast Algorithms for Mining Association Rules. In: Proccedings of 1994 International Conference on Very Large Data- base, Santiogo ,Chile ,1994: 487-499
  • 4[4]Han J, Pei J, Yin Y. Mining Frequent Patterns Without Candidate Generation . Proc . 2000 ACM-SIGMOK Int . Conf . on Management of Data(SIGMOD00), Dallas, TX , 2000-05:1-12
  • 5[5]Areaway R,Syrian R. Fast Algorithms for Mining Association Rulese. In: Proc. of the 20th Intl. Conf on VLDB, Santiago, Chile, 1994-09

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