一种基于概念格的关联规则挖掘算法

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。

Algorithm for mining association rules based concept lattice

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.