Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (28): 157-161.

• 数据库与信息处理 • Previous Articles     Next Articles

Algorithm for mining association rules based concept lattice

WANG Su-jing1,CHEN Zhen2   

  1. 1.College of Software,Jilin University,Changchun 130012,China
    2.College of Computer Science and Technology,Jilin University,Changchun 130012,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-10-01 Published:2007-10-01
  • Contact: WANG Su-jing

一种基于概念格的关联规则挖掘算法

王甦菁1,陈 震2   

  1. 1.吉林大学 软件学院,长春 130012
    2.吉林大学 计算机科学与技术学院,长春 130012
  • 通讯作者: 王甦菁

Abstract: Association rule discovery is one of kernel tasks of data mining.Concept lattice,induced from a binary relation between objects and features,is a very useful formal analysis tool.It represents the unification of concept intension and extension.It reflects the association between objects and features,and the relationship of generalization and specialization among concepts.There is a one-to-one correspondence between concept intensions and closed frequent itemsets.This paper presents an efficient algorithm for mining association rules based concept lattice called Arca(Association Rule based Concept lAttice).Arca algorithm uses concept-matrix to build a part of concept lattice,in which the intension of every concept be put into one-to-one correspondence with a closed frequent itemset.Then all association rules are discovered by 4 operators which are defined in this paper performed on these concepts.

Key words: concept lattice, formal concept analysis, data mining, association rule

摘要: 关联规则挖掘是数据挖掘中的一项核心任务,而由二元关系导出的概念格则是一种非常有用的形式化分析工具,它体现了概念内涵和外延的统一,反映了对象和特征间的联系以及概念间的泛化与例化关系。一个概念内涵与一个关联规则中的闭合项集可以一一对应。提出了一种新有基于概念格的关联规则挖掘算法Arca(Association Rule based Concept lAttice)。Arca算法通过概念矩阵构造部分概念格,使概念格中的每个概念对应一个闭合频繁项集。然后生成一些关联规则,在这些关联规则上通过定义了四个算子来生成了所有关联规则。

关键词: 概念格, 形式概念分析, 数据挖掘, 关联规则