期刊文献+

项目集的性质研究 被引量:1

On the Research of Itemset Properties
下载PDF
导出
摘要 传统的关联规则挖掘框架产生大量的规则,使得人们很难利用它们。本文主要针对项目集进行研究,提出了项目集的上、下闭集的概念,并得到了上、下闭集及其它们之间的一些性质,为解决规则数量问题提供了理论基础。 The problem of association rule mining, which has broad applications, is one of important research aspects in the area of data mining. In the mining process, the traditional association rule mining framework will produce a large number of rules, which makes it very difficult for people to understand and use them. In this paper, we present the notations of upper and lower closed itemset of an itemset and obtain some useful properties of them, which can offer a theoretical basis for solving the problem of the number of association rule.
出处 《辽宁工程技术大学学报(自然科学版)》 CAS 北大核心 2001年第5期601-603,共3页 Journal of Liaoning Technical University (Natural Science)
基金 国家自然科学基金资助项目(60074014)
关键词 上闭集 下闭集 关联规则 数据挖掘 项目集 upper closed itemset lower closed itemset association rule data mining
  • 相关文献

参考文献20

  • 1[1]Agrawal, R., Imielinki, and Swami, A. Mining Association Rules between Sets of Items in Large Databases[C]. SIGMOD1993, Washington D. C, 1993,207-216.
  • 2[2]Agrawai, R. and Scrikant. R. Fast Algorithm for Mining Association Rules[C]. VLDB'94, Santiago, Chile, 1994,487499.
  • 3[3]Agrawal, R., Shafer, J. Parallel Mining of Association Rules[J]. IEEE Knowledge & Data Engineering,1998,8(6): 962-969.
  • 4[4]Agrawal, R., and Srikaut, R., Mining Sequential Patterns[C] ICDE'95, Taipei, Taiwan, 1995, 3-14.
  • 5[5]Park J., Chen M., Yu P. An effective hash-based algorithm for mining association rules[J]. In SIGMOD'95..1995
  • 6[6]Savasere,A., Omiecinski E., Navathe S. An efficient algorithm for mining association in large databases[C]. In VLDB'95, Zurich, 1995,423-443.
  • 7[7]Brin S., Motwani R., Ullman J. D., Tsur S., Dynamic Itemset Counting and Implication Rules for Market Basket Data[C]. In SIGMOD'97, Tucson, Arizona, 1997, 265-276.
  • 8[8]Pasquier, N., Bastide, Y., Taouil, R. and Lakhai, L., Efficient Mining of Association Rules Using Closed Itemset Lattices[J]. Information Systems, 1999,24(1):2546.
  • 9[9]Pasquier N., Bastide Y., Taouil R., Lakhal L., Discovering Frequent Closed Itemsets for Association Rules[C]. ICDT'99, Israel, 1999,398-416.
  • 10[10]Han, J. and Fu, Y., Mining Multiple-level Association Rules in Large Databases[J]. IEEE Transactions on Knowledge and Data Engineering, 1999,11(5):1-8.

同被引文献6

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部