计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (19): 42-44.

• 学术探讨 • 上一篇    下一篇

知识挖掘与它的链式特征

孟令存1,刘月兰2,郝秀梅3   

  1. 1.济宁职业技术学院,山东 济宁 232037
    2.山东省青年管理干部学院 国际贸易系,济南 250014
    3.山东财政学院 统计与数理学院,济南 250014
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-07-01 发布日期:2007-07-01
  • 通讯作者: 孟令存

Knowledge mining and its chain type properties

MENG Ling-cun1,LIU Yue-lan2,HAO Xiu-mei3   

  1. 1.Jining Vocational and Technical College,Jining,Shandong 232037,China
    2.Department of International Trade,Shandong Youth Administrative College,Ji’nan 250014,China
    3.Department of Statistics and Mathematics,Shandong Finance Institute,Ji’nan 250014,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-07-01 Published:2007-07-01
  • Contact: MENG Ling-cun

摘要: 利用S-粗集与它的属性迁移,提出f、■知识、挖掘度概念,讨论了属性迁移与知识挖掘的数量关系;给出了f、■知识链式定理和f、■知识最小、最大挖掘度定理。最后,给出了■知识挖掘的实例分析。

Abstract: This paper presents the concepts of f,■ knowledge and mining degree by using S-rough set and its attribute transfer,and discusses the relation between attribute transfer and knowledge mining data property.This paper gives some knowledge chain theorems and minimum,maximum mining degree theorem of f,■.Finally,this paper presents an analysis on ■ knowledge mining example.