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

机译:形式化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:粗糙集理论和概念格理论是知识发现的两个有效工具。由于信息系统可以将粗糙集理论的数据描述和形式上下文(概念格理论的数据描述)作为另一个信息系统。本文讨论了形式化背景下的广义粗糙集模型。首先,利用信息矩阵在形式上定义了粗糙集的广义下近似和上近似。其次,提出了求上下近似集的算法,提出了下匹配度和上匹配度的新概念。这些概念为正式语境下的粗糙集研究提供了明确的线索和不足。第三,通过医学专家系统介绍了基于正式语境下的广义粗糙集理论的专家系统的应用。最后讨论了形式化背景下粗糙集的弊端和未来的研究方向。

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