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一种非频繁关联规则挖掘算法 被引量:1

An Algorithm for Mining Infrequent Association Rules
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摘要 针对关联规则挖掘问题提出一种新的算法,探讨商品与利润间的关系,称为权重式多重支持度关联规则挖掘算法。此算法可针对不同利润的商品定出不同的支持度阈值,由此产生的关联规则,可以解决高单价但交易次数稀少的商品不易被挖掘的问题。 In this article, we present an algorithm for association rules, call the Weight Algorithm with Multiple Supports for Mining Association Rules, is proposed to probe the relationship between itemsets and profit. It can set different supportive thresholds in accordance with different profit of itemsets. The related rule which was generated by WMMS algorithm can solve the problem that itemsets with high price but few trading times was difficult to find out.
作者 刘松
出处 《微计算机应用》 2006年第5期566-569,共4页 Microcomputer Applications
关键词 数据挖掘 关联规则 权重式多重支持度 data mining, association rules, weight algorithm with multiple supports
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参考文献5

  • 1Aggarwal C C,Yu P S.A New Approach to Online Generation of Association Rules.IEEE Trans.of Knowledge and Data Eng.,July/August 2001,13(4):527~540
  • 2B.Liu,W.Hsu and Y.Ma.Mining Association Rules with Multiple Minimum Supports.Proc.5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,May 1999,337~341
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  • 5刘松.隐私保护下的关联模式挖掘[J].微计算机应用,2006,27(2):185-187. 被引量:3

二级参考文献4

  • 1R.Agrawal and R.Srikant.Privacy Preserving Data Mining.Proceeding of ACM SIGMOD Conference on Management of Data,May 2000.
  • 2R.Agrawal,R.Srikant,A.Evfimievski and J.Gehrke.Privacy Preserving of Association Rules.Proceeding of 8th ACM SIGMOD Conference on Knowledge Discovery and Data Mining (KDD),July 2002.
  • 3M.Kantarcioglu and C.Clifton.Privacy-preserving Distributed Mining of Association Rules on Horizontal Partitioned Data.Proceeding of ACM Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD),June 2002.
  • 4Shariq J.Rizvi and Jayant R.Haritsa.Maintaining Data Privacy in Association Rule Mining.Proceedings of the 28th VLDB Conference,2002.

共引文献2

同被引文献5

  • 1范明 孟小峰.数据挖掘概念与技术[M].北京:机械工业出版社,2001..
  • 2R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. Proceedings of the ACM SIGMOD Conference on Management of data. 1993:207 - 216.
  • 3Tzung P H. Mining Association Rules From Quantitative Data. Intelligent Data Analysis. 1999,3 (5) : 363 - 376.
  • 4蔡伟杰,张晓辉,朱建秋,朱扬勇.关联规则挖掘综述[J].计算机工程,2001,27(5):31-33. 被引量:134
  • 5行小帅,焦李成.数据挖掘的聚类方法[J].电路与系统学报,2003,8(1):59-67. 被引量:55

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