期刊文献+

数据采掘的基本方法及其与专家系统的差异 被引量:11

BASIC METHODS ON DATA MINING AND DIFFERENCE BETWEEN DATA MINING AND EXPERT SYSTEM
在线阅读 下载PDF
导出
摘要 目前,数据采掘技术研究正在升温,大有超过当年专家系统的趋势。本文介绍了数据采掘技术的产生背景、基本任务和方法,并举例加以说明。最后简介了目前已有的成熟的KDD系统,并从方法论的角度比较了数据采掘与专家系统的差异。 Now the research on Data Mining becomes a hot topic which far extends the former Expert System. This article introduces the background, basic tasks and methods of Data Mining with pellucid examples. At last it puts forth the difference between Data Mining and Expert System from the point view of methodology.
出处 《计算机应用》 CSCD 1999年第3期17-20,共4页 journal of Computer Applications
基金 国家自然科学基金
关键词 数据采集 数据库 专家系统 知识发现 Data mining(DM), Knowledge discovery in database, Classification, Clustering, Association
  • 相关文献

参考文献3

  • 1唐常杰 张天庆 等.基于时态数据库的Web数据周期性的发现.全国第15届数据库论文集[M].,..
  • 2Jawei,KDD’96,1996年
  • 3唐常杰,全国第15届数据库论文集

同被引文献47

  • 1曾万聃,周绪波,戴勃,常桂然,李春平.关联规则挖掘的矩阵算法[J].计算机工程,2006,32(2):45-47. 被引量:33
  • 2彭仪普,熊拥军.关联规则挖掘AprioriTid算法优化研究[J].计算机工程,2006,32(5):55-57. 被引量:24
  • 3Harjinders gill.数据仓库--客户/方服务器计算指南[M].北京:清华大学出版社,1998..
  • 4[2]Agrawal R,Imielinski T,Swami A.Mining Association Rules Between Sets of Items in Large Databases[C] //Proceedings of the ACM SIGMOD Conference on Management of Data.New York:ACM,1993:207-216.
  • 5[3]Agrawal R,SriKant R.Fast Algorithms for Mining Association Rules[C]//Proceedings of the 20th International Conference on Very Large Database.[s.l.]:Morgan Kaufman Pub Inc,1994:487-499.
  • 6[4]Park J S,Chen Ming Syan,Yu Philip S.An Effective Hash-based Algorithm for Mining Association Rules[C]//Proceedings of the ACM SIGMOD International Conference on Management of Data.New York:ACM,1995:175-186.
  • 7[5]Park J S,Chen Ming Syan,Yu Philip S.Efficient Parallel Data Mining of Association Rules[C]//Proceedings of the 4th International Conference on Information and Knowledge Management.New York:ACM,1995:31-36.
  • 8[6]Savasere A,Omiecinski E,Navathe S.An Efficient Algorithm for Mining Association Rules in Large Databases[C]//Proceedings of the 21st International Conference on Very Large Database.New York:ACM,1995:432-443.
  • 9[7]Toivonen H.Sampling Large Databases for Association Rules[C]//Proceedings of the 22nd International Conference on Very Large Database.Bombay:[s.n.],1996:134-145.
  • 10[8]Brin S,iotwani R,Ullman J D,et al.Dynamic Itemset Counting and Implication Rules for Market Basked Data[C]//Proceedings of the ACM SIGMOD International Conference on Management of Data.New York:ACM,1997:255-264.

引证文献11

二级引证文献37

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