文献类型：期刊文献

中文题名：基于粗糙集理论的概念格属性约简及算法

英文题名：Intent Reduction of Concept Lattices and its Algorithm Based on Rough Set Theory

作者：吴强[1,2];周文[1];刘宗田[1];陈慧琼[3]

机构：[1]上海大学计算机工程与科学学院,上海200072;[2]绍兴文理学院计算机系,绍兴312000;[3]不详

年份：2006

卷号：33

期号：6

起止页码：179

中文期刊名：计算机科学

外文期刊名：Computer Science

收录：CSTPCD、、北大核心2004、CSCD2011_2012、北大核心、CSCD

基金：国家自然科学基金项目"分布式概念格数学模型及算法研究"(编号:60275022)资助。

语种：中文

中文关键词：概念格;粗糙集理论;约简

外文关键词：Formal concept analysis,Rough set theory,Reduction

中文摘要：粗糙集理论在数据分析中善于解决约简冗余属性与对象、寻求最小属性集等问题,而约简概念格是形式概念知识表示中解决复杂性的重要途径。用粗糙集的方法重新认识形式概念及概念格,并把二者有机地结合起来,为概念格的约简提供了一个新的思路和方法。本文就这些问题做了一些基本的研究。

外文摘要：Rough set theory has advantage in solving the problems of the reduction of objects and intents, seeking mini mum intent set, and etc in data analysis. In the same time, the reduction of concept lattice plays an important role to reduce the complexity in knowledge representation based on formal concept analysis. From the point of view of rough set, some new methods of concept lattice reduction are presented which take the advantage of both rough set and formal concept analysis. The aim of this paper is to produce some new methods of concept lattice reduction by the combination of rough set theory and formal concept analysis.