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频繁项集挖掘算法 被引量：20

Frequent Item Sets Mining Algorithms
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摘要 数据挖掘在最近几年里已被数据库界所广泛研究,而搜索频繁项集是诸如关联规则挖掘、序列模式挖掘等数据挖掘问题中的关键步骤。本文描述了频繁项集挖掘问题的特点,并根据搜索策略对已有各种频繁项集挖掘算法进行了分析和比较。 Nowadays dat mining is becoming one of most popular problems in the field of database research, Mining frequent item sets in a key step in many data mining problems, such as association rule mining, sequential pattern mining,and so on. In this paper,we introduce the characteristic of frequent item sets mining problems,and then we analyze and compare today's common approaches according to search strategy.
作者 颜跃进 李舟军 陈火旺
机构地区 国防科技大学计算机学院
出处 《计算机科学》 CSCD 北大核心 2004年第3期112-114,124,共4页 Computer Science
关键词 数据库 频繁项集 数据挖掘算法 关联规则 数据库管理系统 计算机 Frequent item sets.Apriori property .Support,Breath-first search,Depth-first search
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
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参考文献27

  • 1李雄飞,苑森淼,董立岩,全勃.多段支持度数据挖掘算法研究[J].计算机学报,2001,24(6):661-665. 被引量：23
  • 2http://www. dmgroup. org. cn/zs20. htm
  • 3Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases. In: Proc. 1993ACMSIGMOD Int. Conf. Management of Data,Washington,D.C. ,May 1993.207-216
  • 4Srikant R,Agrawal R. Mining sequential patterns: generalizations and performance improvements. In: 5th Intl. Conf. Extending Database technology,Mar. 1996
  • 5Srikant R,Agrawal R. Mining sequential patterns:generalizations and performance improvements. In: Proc. 5th EDBT, 1996.3-17
  • 6Brin S, Motwani R, Silverstein C. Beyond market basket:Generalizing association rules to correlations.In:Proc. 1997ACMSIGMOD Int. Conf. Management of Data, Tucson, Arizona, May 1997.265-276
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  • 8Agrawal R,Srikant R. Mining sequential patterns. In:Proc. 1995Int. Conf.Data Engineering,Taipei ,Taiwan, March 1995.3-14
  • 9Agrawal R,Mannila H, Srikant R,Toivonen H,Verkamo A.Fast Discovery of Assocation Rules. 1996. 307-328
  • 10Houtsma M,Swami A. Set-oriented mining for Association Rules in Relational Databases. In:Proc. of the 11th Intl. Conf. on Data Engineering. March 1995. 24-32

二级参考文献5

  • 1[1]Agrawal R, Imielinski T， Swami A. Mining association rules between sets of items in large databases. In: Proc ACM SIGMOD Conference on Management of Data, Washington D C, 1993. 207-216
  • 2[2]Agrawal R, Srikant R. Fast algorithms for mining association rules. In: Proc 20th VLDB Conference Santiago,Chile, 1994. 487-499
  • 3[3]Houtsma M, Swami A. Set-oriented mining of association rules. IBM Almaden Reserch Center，Research Report RJ 9567， 1993
  • 4[4]Bayardo R, Agrawal R. Mining the most interesting rules. In: Proc KDD-99, San Diego, 1999. 122-131
  • 5[5]Agrawal R, Mannila H, Toivonen H, Verkamo A. Fast discovery of association rules. In: Fayyad U,Piatetsky-Shapiro G Symth P, Uthurusamy R eds. Advances in Knowledge Discovery and Data Mining. New York: AAAI/MIT Press, 1996. 307-328

共引文献22

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二级引证文献126

计算机科学
2004年 第3期

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