基于概念格的最简规则挖掘算法  

Mining Algorithm for Minimal Rule Based on Concept Lattice

作　　者：邱卫根[1,2] 

机构地区：[1]广东工业大学计算机学院,广州510090 [2]清华大学计算机科学与技术系智能技术与系统国家重点实验室,北京100084

出　　处：《模式识别与人工智能》2009年第2期318-324,共7页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金资助项目(No.60474072)

摘　　要：概念格是知识处理和数据分析的重要数学工具.概念格快速构造算法对挖掘关联规则非常重要.本文构造了决策表对应的形式背景和概念格模型,分析了扩展不可分辨矩阵、概念格和最简决策规则发现之间的关系:概念格的内涵都来自于扩展不可分辨矩阵的特征元,最简决策规则的条件元一定是概念格某个结点的内涵缩减.本文给出了形式概念格的快速渐进式构造算法和基于概念格的最简规则获取算法,该算法直观简捷.最后以一个工程实例对本算法的有效性作出了证明.The concept lattice is an important mathematic tool for knowledge treatment and data analysis, its efficient construction algorithm is significant in rules acquisition of decision table. In this paper, the formal context and concept lattice model of decision table are constructed, the relationships among the extended indistinguishable matrix, concept lattice and minimal rule are analyzed. All the concept node intension comes from property element of extended indistinguishable matrix and all the condition properties of optimal decision rule are from the intension reduction of a concept lattice node. Two algorithms are developed for constructing the corresponding concept lattice incrementally and acquisition of minimal decision rule based on the concept lattice, and their simplicity and efficiency are proved by an enterprise example.

关 键 词：规则获取 形式概念格 扩展不可分辨矩阵 内涵缩减 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TP311[自动化与计算机技术—控制科学与工程]