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Generalized rough set under formal context and its application in expert system

机译:正式背景下的广义粗糙集及其在专家系统中的应用

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Rough set theory and the theory of concept lattices are two efficient tools for knowledge discovery. Since an information system, the data description of rough set theory, and a formal context, the data description of concept lattice theory, can be taken as the other one. In this paper, generalized rough set model under formal context is discussed. Firstly, generalized lower and upper approximations of rough set are defined under formal context by means of information matrix. Secondly, the algorithm for getting the lower and upper approximation set is presented and new concepts of lower-matching degree and upper-matching degree are advanced. These concepts give a clearly clue and matting to the studies on rough set under formal context. Thirdly, the application of expert systems, based on the theory of generalized rough set under formal context, is introduced through medical expert systems. Finally the disadvantages and future research directions of rough set under formal context are discussed.
机译:粗糙集理论与概念格子理论是两个有效的知识发现工具。由于信息系统,粗糙集理论的数据描述以及正式的背景,概念格理论的数据描述,可以作为另一个。本文讨论了正式上下文下的广义粗糙集模型。首先,通过信息矩阵在正式上下文下定义粗糙集的广义下近似。其次,提出了用于获得下近似和上近似集的算法,提前匹配程度和上匹配程度的新概念。这些概念在正式背景下提供了关于粗糙集的研究。第三,通过医学专家系统引入了基于正式背景下的广义粗糙集理论的专家系统的应用。最后讨论了在正式背景下粗糙集的缺点和未来研究方向。

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