摘要
作为数据挖掘核心任务之一的关联规则发现已经得到了广泛的研究 .而由二元关系导出的概念格则是一种非常有用的形式化工具 ,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 ,因此非常适于发现数据中潜在的概念 .分析了概念格与关联规则提取之间的关系 ,根据需要对格结构进行了相应的修改 ,提出了相应的渐进式生成算法和基于概念格的关联规则提取算法 ,通过定理和性质对算法进行了说明并对关联规则进行缩减 .
Association rule discovery, as a kernel task of data mining, has been studied widely. Concept lattice, induced from a binary relation between objects and features, is a very useful formal tool and has been used in many fields. It realizes the unification of concept intension and concept extension, represents the association between objects and features, and reflects the relationship of generalization and the specialization among concepts, so it is fit for discovering the potential concept below the data. In this paper, the relationship between concept lattice and association rule discovery is analyzed. Then, the structure of node in lattice is modified according to the requirement, while two algorithms are developed for constructing the corresponding lattice incrementally and for extracting association rules, where some theorems and properties are used to reduce the number of discovered rules. Finally, the complexity problem is discussed, and the corresponding experimental results are given.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2000年第12期1415-1421,共7页
Journal of Computer Research and Development
基金
国家自然科学基金!(项目编号 6 9985 0 0 4)
国家机械发展基金!(项目编号 96 JA0 2 0 5 )
博士点专项基金!(项目编号 970 35 90 1)
关键词
概念格
关联规则
数据挖掘
数据库
知识发现
concept lattice, intension reduction, association rule, data mining€
