计算机应用 ›› 2010, Vol. 30 ›› Issue (4): 1072-1075.

• 数据库与数据挖掘 • 上一篇    下一篇

多维概念格与关联规则发现

郭显娥1,王俊红2   

  1. 1. 山西大同大学数学与计算机科学学院
    2.
  • 收稿日期:2009-11-02 修回日期:2009-12-07 发布日期:2010-04-15 出版日期:2010-04-01
  • 通讯作者: 郭显娥

Multi-dementional concept lattice and association rules discoverey

  • Received:2009-11-02 Revised:2009-12-07 Online:2010-04-15 Published:2010-04-01
  • Contact: GUO xiane

摘要: 在引用多维数据序列对概念内涵进行不同维度的描述的基础上,提出了多维概念格的形式化定义及其构造方法;并给出了基于多维概念格的关联规则提取方法,该方法通过发现最大频繁多维数据序列研究不同维度属性之间的依赖关系。实例表明,多维概念格利于发现内容更丰富的有用信息。

关键词: 多维概念格, 维度, 多维数据序列, 最大频繁数据序列

Abstract: Based on the description of deferent dimension of concept intent using multi-dimensional data sequence, formal definition and construction method of multi-dimensional concept lattice were proposed in the paper. Also the association rules discovery method based on multi-dimensional concept latticewas given, which studied dependence relation among deferent dimension attributes thought discovering biggest frequent multi-dimensional data sequence. Examples show that multi-dimensional concept lattice helps to discover richer useful information.

Key words: multi-dimensional concept lattice, dimensionality, multi-dimensional data sequence, maximal frequent data sequence