期刊文献+

一种高效关联规则挖掘EARM算法的研究

A Efficient Algorithm for Mining of Association Rules's Research
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摘要 针对类Apriori关联规则挖掘算法的不足,将以往关联规则算法予改进,提出一个更有效率的关联规则挖掘算法EARM算法。通过试验评估,该文所提算法的挖掘效率比Apriori及其改良算法要快2到5倍。 This paper discusses the disadvantages of the algorithm for mining of association rules based on Apriori, presents a more efficient algorithm for mining of association rules. The experiment evaluation shows that the algorithm is faster than Apriori and its extends algorithm by a factor from two to five by experiments evaluation.
出处 《计算机应用》 CSCD 北大核心 2003年第7期46-48,共3页 journal of Computer Applications
基金 云南省信息技术基金资助 (2 0 0 2IT0 3 )
关键词 数据挖掘 关联规则 data mining association rule
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参考文献4

  • 1Aggarwal C , Yu PS . Mining Large ltemsets for Association Rules[ J]. Data Engineering Bulletin, 1998, 21 ( 1 ) : 23 - 31.
  • 2Eui-Hong Han, Karypis G, Kumar V. Scalable Parallel Data Mining for Association Rules[ J]. IEEE Transaction on Knowledge and Data Engineering, 2000, 12(3) : 351 - 377.
  • 3Park JS, Ming-Syan Chen, Yu PS. Using a Hash-Based Method with Transaction Trimming and Database Scan Reduction for Mining Association Rules[J]. IEEE Trans. on Knowledge and Data Engineering, 1997, 9(5) : 813 - 825.
  • 4Carter CH, Hamilton, Cercone N. Share Based Measures for Itemsets[ A]. Komorowski J, Zytkow J, ed. Principles of Data Mining and Knowledge Discovery[ C], 1997. 14 -24.

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