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加权关联规则挖掘算法 被引量:1

Survey of Weighted Association Rule Mining Algorithm
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摘要 将项目权值引入传统关联规则挖掘中是在项目属性上的扩展。本文分析项目权值对加权关联规则挖掘的影响,并对加权关联规则现有的算法进行总结,同时比较各算法的优缺点。最后对加权关联规则的未来研究发展方向进行探讨。 Introduce the item weights to traditional association rules mining is the expansion in the project properties.This paper analyzes the effects of the item weights to the weighted association rules mining, and the weighted association rules of existing algorithms are summarized and compared the advantages and disadvantages of them.Finally the research of the weighted association rules of the future development trend are discussed.
作者 侯宇 张敏
出处 《大连大学学报》 2011年第3期49-52,共4页 Journal of Dalian University
基金 国家自然科学基金项目(60873042)
关键词 数据挖掘 关联规则 权值 加权支持度 加权频繁项集 data mining association rule weights weighted support weighted frequent itemset
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参考文献14

  • 1AGRAWAL R, IMIELINSKI T,SWAMI A. Min- ing Association Rules Between Sets of Items in Large Databases[C].Proc.1993 ACM SIGMOD Int'l Conf.Management of Data, Washington, 1993:207-216.
  • 2C H CAI, ADA W C FU.Mining association rules with Weighted items[C]. In IEEE Int. Database Engineering and Applications Symposium, 1998:68-77.
  • 3路松峰,胡和平.加权关联规则的开采[J].小型微型计算机系统,2001,22(3):347-350. 被引量:27
  • 4张智军,方颖,许云涛.基于Apriori算法的水平加权关联规则挖掘[J].计算机工程与应用,2003,39(14):197-199. 被引量:30
  • 5尹群,王丽珍,田启明.一种基于概率的加权关联规则挖掘算法[J].计算机应用,2005,25(4):805-807. 被引量:18
  • 6陆建江.加权关联规则挖掘算法的研究[J].计算机研究与发展,2002,39(10):1281-1286. 被引量:13
  • 7刘燕.一个改进项目的加权关联规则挖掘算法[J].昆明理工大学学报(理工版),2008,33(4):34-37. 被引量:1
  • 8WEI WANG, JIONG YANG, PHILIP YU. Efficient Mining of Weighted Association Rules (WAR)[J]. KDD '00 Proceedings of the 6th ACM SIGKDD international conference,2000:270-274.
  • 9Wei Wang, Jiong Yang, Philip Yu.WAR:weighted asso- ciation rules for item intensities[J].Knowledge and In- formation Systems, 2004,2004(6):203-229.
  • 10FENG TAO, FIONN MURTAGH, MOHSEN FARID. Weighted association rule mining using Weighted sup- port and significance framework[C]. IN PROC. of the ninth ACM SIGKDD Int' 1 Conf.on Knowledge Dis- covery and Data Mining, 2003:661-666.

二级参考文献37

  • 1尹群,王丽珍,田启明.一种基于概率的加权关联规则挖掘算法[J].计算机应用,2005,25(4):805-807. 被引量:18
  • 2段军,戴居丰.基于多支持度的挖掘加权关联规则算法[J].天津大学学报,2006,39(1):114-118. 被引量:14
  • 3Agrawal R, Srikant R. Fast Algorithms for Mining Association Rules in Large Datebases[C]//Proc. of VLDB'94. Santiago, Chile: [s. n.], 1994.
  • 4Cai Chun Hing, Fu Ada Wai-Chee, Cheng Chun-hung, et al. Mining Association Rules with Weighted Items[C]//Proc. of International Database Engineering and Applications Symposium. Cardiff, Wales, UK: [s. n.], 1998.
  • 5Cai C H,Proc the Int Database Engineering and Applications Symposium,1998年,68~77页
  • 6FAYYAD U,MANNILA H,PIATETSKY-SHAPIRO G.Data Mining and Knowledge Discovery[J].Data Mining and Knowledge Discovery,1997,1(1).5-10.
  • 7CAI CH, ADA WAI-CHEE FU.Mining association rules with weighted items[A].Proceedings of International Database Engineering and Applications Symposium(IDEAS 98)[C].1998.
  • 8TAO F,FIONN M,MOHSEN F.Weighted Association Rule Mining using Weighted Support and Significance Framework[A].Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining[C].2003.661-666.
  • 9WANG W,YANG J,YU PS.Efficient mining of weighted association rules(WAR)[A].Proceedings of the ACM SIGKDD Conference On Knowledge Discovery and Data Mining[C].2000.270-274.
  • 10Savasere A, Omiecinski E, Navathe S. An efficient algorithm for mining association rules in large databases [C]//Proceedings of the 21st VLDB Conference. Zurich, Switzerland, 1995 : 254-262.

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