【作者】 杨海峰； 张继福；

【Author】 Yang Haifeng Zhang Jifu School of Computer Science and Technology, Tai-Yuan University of Science and Technology, Tai-Yuan 030024 National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080

【机构】 太原科技大学计算机科学与技术学院；

【摘要】 概念格是数据分析与知识提取的一种有效工具,由于概念格的完备性及精确性,采用概念格提取不确定知识存在较大的局限性。粗糙集理论是处理不确定性知识的一种有效数学工具。为了提高概念格的知识提取的能力,使其能够处理不确定性知识,本文针对决策形式背景,采用粗集理论中上下近似来描述内涵所拥有的外延,给出了一种新的概念格结构:粗糙概念格。并在此基础上给出了一种粗糙概念格的构造方法,从而加强了概念格处理不确定性知识的能力。更多还原

【Abstract】 Concept lattice is an effective tool for data analysis and knowledge discovery. It is very limited in mining uncertainty knowledge because of its completeness and accuracy. The theory of rough sets is an effective mathematic tool for dealing with uncertainty knowledge. In order to improve the ability of knowledge discovery of concept lattice, to deal with uncertainty knowledge, Rough Concept Lattice is proposed in this paper which is based on Decision Context. Using the approximation method of rough sets, it describes the "extent" as approximation extent. A construction method is provided based on it. It improved the ability of deal with uncertainty knowledge.更多还原