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直接挖掘跨层关联规则的新方法 被引量：8

Directly Mining Cross Level Association Rules
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摘要 文章定义了一种跨层扩展频繁项目图Clefig,提出了基于Clefig直接产生频繁模式算法Clefig-Prod。它能高效地挖掘单层、多层特别是跨层关联规则。实验表明,在多层、跨层和支持率阀值较小的单层挖掘上,Clefig-Prod效率优于Cumulate、Apriori等经典算法。 In this paper,a new association rule production algorithm based on cross level extended frequent item graph,Clefig-Prod,is proposed.Clefig-Prod can directly mine single,multiple and cross level association rules.Compara-tive experiments with Apriori and Cumulate show that Clefig-Prod is very efficient and highly scalable.
作者 刘君强 孙晓莹 叶国荣
机构地区 杭州商学院
出处 《计算机工程与应用》 CSCD 北大核心 2002年第20期50-51,111,共3页 Computer Engineering and Applications
基金 浙江省自然科学基金资助 浙江省教育厅科技计划的资助
关键词 数据挖掘 跨层关联规则 单层挖掘 数据库 Data mining,Cross level association rules,Sigle mining
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献9

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同被引文献62

  • 1刘乃丽,李玉忱,马磊.一种有效且无冗余的快速关联规则挖掘算法[J].计算机应用,2005,25(6):1396-1397. 被引量：7
  • 2邹志文,朱金伟.数据挖掘算法研究与综述[J].计算机工程与设计,2005,26(9):2304-2307. 被引量：52
  • 3余小鹏.一种基于多层关联规则的推荐算法研究[J].计算机应用,2007,27(6):1392-1393. 被引量：7
  • 4刘君强.[D].浙江大学计算机科学与技术学院,2003.
  • 5刘君强.[D].浙江大学计算机科学与技术学院,2003.
  • 6[1]R.Agrawal,T.Imielinski,A.Swami.Mining association rules between sets of items in large database[A].In:P.Buneman,S.Jajodia,eds.Proc.of 1993 ACM SIGMOD Conf.on Management of Data[C].Washington DC:ACM Press,1993.207-216.
  • 7Junqiang Liu,Yunhe Pan,Ke Wang et al.Mining frequent item sets by opportunistic projection[C].In:Preceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, USA :ACM Press,2002:229-238.
  • 8Jiawei Han,Yong-ian Fu et al.DBMiner:A System for Mining Knowledge in Large Relational Databases[C].In:Proceedings of the 2nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, USA : ACM Press, 1996 : 250-255.
  • 9Jiawei Han,Micheline Kamber.Data Mining:Concepts and Techniques[M].USA :Morgan Kaufmann Publishers,2000.
  • 10Junqiang Liu, Yunhe Pan, Ke Wang, and Jiawei Han. Mining frequent item sets by opportunistic projection[A]. Proceedings of the 8th ACM SIGKDD International Conference onKnowledge Discovery and Data Mining[C]. USA: ACM Press, 2002: 229-238.

引证文献8

二级引证文献65

计算机工程与应用
2002年 第20期

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