期刊文献+

一种挖掘free项目集的快速算法

An Algorithm for Fast Free- Sets Mining
下载PDF
导出
摘要 对关联规则的挖掘是数据挖掘中一个重要的问题 .通过挖掘 free项目集来挖掘关联规则已被证明是一种十分高效的方法 .Seg Free算法将数据库分成许多分段并在这些分段中查找 free项目集 .它只耗用很小的额外内存来存储在每个分段中项目集的支持度 ,却能极大的减少项目集匹配的时间 ,而项目集匹配的时间是整个挖掘过程的瓶颈 .在真实数据集上的试验已显示了它良好的性能 . Mining of association rule is an important problem in data mining. Ming of free sets has proved to be an efficient way for association rule mining. The SegFree algorithm divide the database into segments and find free sets in each segment. The SegFree algorithm costs little memory to save additional support number of itemsets in each segment but greatly reduced the time of itemset matching which is the bottleneck of the mining process. The experiments on real datasets have showed its good performance. It can also be used in some other mining tasks.
出处 《小型微型计算机系统》 CSCD 北大核心 2004年第10期1853-1856,共4页 Journal of Chinese Computer Systems
关键词 数段挖掘 分段 关联规则 free项目集 data mining segmentation association rule free sets
  • 相关文献

参考文献2

二级参考文献6

  • 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
  • 6程继华,郭建生,施鹏飞.挖掘所关注规则的多策略方法研究[J].计算机学报,2000,23(1):47-51. 被引量:22

共引文献58

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