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一种改进的Apriori算法 被引量：1

An Improved Algorithm of Apriori
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摘要 Apriori算法存在许多可以改进的地方.例如它需要反复读取数据库,并且读取的次数由项目集中的项目个数来确定,I/O负载与最大项目集的项数成正比.本文提出一种只读一次数据库的的改进算法. The algorithm of Apriori has many obvious shortcomings, which need to scan database frequently and the frequency is up to the number of items. I/O loads is directly proportional to the number of items of the largest item set. This article proposed an improved algorithm by which the database will be scanned only once.
作者 周虹 马丽丽
机构地区 佳木斯大学公共计算机教研部 佳木斯热力公司
出处 《佳木斯大学学报（自然科学版）》 CAS 2007年第4期492-494,共3页 Journal of Jiamusi University：Natural Science Edition
关键词 数据挖掘 关联规则 APRIOFI算法 database association rule Apriori algorithm
分类号 TP311 [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2

  • 1RICHARD J.ROIGER,MICHAEL W.GEATZ.著.翁敬农译.数据挖掘教程[M].北京:清华大学出版社,2003.
  • 2佟强,周园春,阎保平.关联规则挖掘算法[J].微电子学与计算机,2005,22(6):68-72. 被引量：21

二级参考文献15

  • 1Rakesh Agrawal, Tomasz Imielinski, Arun Swami. Mining Association Rules between Sets of Items in Large Databases. SIGMOD-93, May 1993: 207～216.
  • 2Rakesh Agrawal, Ramakrishnan Srikant. Fast Algorithms for Mining Association Rules in Large Databases. VLDB1994.
  • 3R S rikant, R Agrawal. Mining Quantitative Association Rules in Large Relational Tables. In Proc. of the 1996ACM SIGMOD Conf. on Management of Data, Montreal,Canada, June 1996.
  • 4Jiawei Han and Yongjian Fu. Discovery of Multiple-Level Association Rules from Large Databases. Proceedings of the 21st VLDB Conference Zurich, Swizerland, 1995.
  • 5A Savasere, E Omiecinski, and S Navathe. An Efficient Algorithm for Mining Association Rules in Large Databases. Proceedings of the 21st International Conference on Very Large Database, 1995.
  • 6R Agarwal, C Aggarwal, V V V Prasad. A Tree Projection Algorithm for Generation of Frequent Itemsets. In J. of Parallel and Distributed Computing (Special Issue on High Performance Data Ming), 2000.
  • 7J Han, J Pei and Y Yin. Mining Frequent Patterns without Candidate Generation. In SIGMOD, 2000: 1～12.
  • 8M J Zaki, S Parthasarathy, M Ogihara, and W Li. New Algorithms for Fast Discovery of Association Rules, Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, 1997.
  • 9M J Zaki. Scalable Algorithms for Association Mining.IEEE Transactions on Knowledge and Data Engineering,May/June 2000, Vol. 12.
  • 10H Toivonen. Sampling Large Databases for Association Rules, Proceedings of the 22nd VLDB Conference, 1996.

共引文献26

同被引文献5

引证文献1

二级引证文献3

佳木斯大学学报（自然科学版）
2007年 第4期

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