期刊文献+

基于时间窗口的增量式关联规则更新技术 被引量:3

A TimeWindow Based Incremental Technique for Updating Association Rules
下载PDF
导出
摘要 文章提出了基于时间窗口的增量式关联规则更新技术.该方法不仅可以利用在先前发现过程中已经获得的结果,而且利用时间窗口。 A timewindow based incremental technique for updating association rules is presented in this paper, which can not only reuse the results acquired in the previous discovery process, but also focus the discovery on the recent data set using time window.
出处 《软件学报》 EI CSCD 北大核心 1999年第4期426-429,共4页 Journal of Software
基金 国家自然科学基金 国家教委博士点基金
关键词 知识发现 关联规则 时间窗口 数据库 Knowledge discovery, association rule, incremental update, timewindow.
  • 相关文献

参考文献1

二级参考文献6

  • 1Han J,Proc 1996 Int’l Conf on Data Mining and Knowledge Discovery,1996年
  • 2Han J,Proc 2th VLDB Conf Zurich,1995年
  • 3Shen W,Advances in Knowledge Discovery and Data Mining,1995年
  • 4Han J,AAAI’94 Workshop on Knowledge Discovery in Databases,1994年
  • 5Han J,IEEE Trans Knowl Data Eng,1993年,5期,29页
  • 6欧阳为民,蔡庆生.在数据库中自动发现广义序贯模式[J].软件学报,1997,8(11):864-870. 被引量:12

共引文献6

同被引文献17

  • 1辜炜东,汤庸,王路帮,谭伟民.事务数据库中的时态信息挖掘[J].计算机工程与应用,2004,40(18):174-177. 被引量:11
  • 2罗来鹏,刘二根,胡新根,王广超.基于包含度的事务数据库关联规则挖掘[J].华东交通大学学报,2004,21(5):23-25. 被引量:3
  • 3RODDICK J F, SPILIOPOULOU M. A survey of temporal knowledge discovery paradigms and methods [J]. IEEE Trans on Knowledge and Data Engineering, 2002, 14 (4) : 750-767.
  • 4HU X, XU P, WU Sh, et al. A data mining framework for time series estimation [ J ]. J Biomed Inform, 2010,43 ( 2 ) : 190-199.
  • 5LIAN X, CHEN L. Efficient similarity search over future stream time series [ J ]. IEEE Trans on Knowledge and Data Engineering, 2008, 20 (1) : 40-54.
  • 6MARTEAU P F. Time warp edit distance with stiffness adjustment for time series matching[ J ]. IEEE Trans On Pattern Analysis and Machine Intelligence, 2009,31(2): 306-318.
  • 7RICHARD J. POVINELLI XIN F. A new temporal pattern identification methord for characterization and prediction of complex time series events [ J ]. IEEE Trans on Knowledge and Data Engineering, 2003, 15(2) : 339-352.
  • 8HAN J, GONG W, YIN Y. Efficient mining of partial periodic patterns in time series database [C]//Proe 15th Intl Conf Data Eng Sydney,Australia, 1999: 106-115.
  • 9AREF W G, ELFEKY M G, ELMAGARMID A K. Incremental, online, and merge mining of partial periodic patterns in time-series databases [J]. IEEE Trans on Knowledge and Data Engineering, 2004, 16 (3) : 332-342.
  • 10Fayyad U, Piatetsky-Shapiro G, Smyth P. The KDD process for extracting useful knowledge from volumes of data [ J ]. Communications of the Association for Computer Machinery, 1996,39( 11 ):27 ~34.

引证文献3

二级引证文献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