Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (28): 157-161.
• 数据库与信息处理 • Previous Articles Next Articles
WANG Su-jing1,CHEN Zhen2
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王甦菁1,陈 震2
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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
WANG Su-jing1,CHEN Zhen2. Algorithm for mining association rules based concept lattice[J]. Computer Engineering and Applications, 2007, 43(28): 157-161.
王甦菁1,陈 震2. 一种基于概念格的关联规则挖掘算法[J]. 计算机工程与应用, 2007, 43(28): 157-161.
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