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Covering-Based Reduction of Object-Oriented Concept Lattices

机译:面向对象概念格的基于覆盖的约简

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To be an efficient tool for knowledge expression and analysis, formal concept analysis has been paid more attention to in recent years. For the object-oriented concept lattice of a formal context, this paper proposes two compression methods to reduce the original lattice based on covering of the object (attribute) set. We firstly introduce the similarity degree and the neighborhood of an object (attribute) set, and then obtain the covering of the object (attribute) set. Based on which, the object-oriented concept lattice can be compressed into a smaller one through adjusting the object (attribute) neighborhood's size by the similarity degree, and the reduced lattice is a subset of the original one.
机译:作为一种有效的知识表达和分析工具,形式概念分析近年来受到了越来越多的关注。对于形式上下文的面向对象概念格,本文提出了两种基于覆盖对象(属性)集的压缩方法来减少原始格。我们首先介绍一个对象(属性)集的相似度和邻域,然后获得对象(属性)集的覆盖度。在此基础上,可以通过以相似度调整对象(属性)邻域的大小,将面向对象的概念格压缩为较小的格,而精简后的格则是原始格的子集。

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