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A Novel Approach to Attribute Reduction in Concept Lattices

机译:概念格属性约简的新方法

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摘要

Concept lattice is an effective tool for data analysis and knowledge discovery. Since one of the key problems of knowledge discovery is knowledge reduction, it is very necessary to look for a simple and effective approach to knowledge reduction. In this paper, we develop a novel approach to attribute reduction by defining a partial relation and partial classes to generate concepts and introducing the notion of meet-irreducible element in concept lattice. Some properties of meet-irreducible element are presented. Furthermore, we analyze characteristics of attributes and obtain sufficient and necessary conditions of the characteristics of attributes. In addition, we illustrate that adopting partial classes to generate concepts and the approach to attribute reduction are simpler and more convenient compared with current approaches.
机译:概念格是用于数据分析和知识发现的有效工具。由于知识发现的关键问题之一是知识减少,因此寻找一种简单有效的知识减少方法非常必要。在本文中,我们通过定义部分关系和部分类以生成概念并在概念格中引入满足不可约元素的概念,开发了一种新的属性约简方法。介绍了遇见不可约元素的一些性质。此外,我们分析属性的特征,并获得属性特征的充分和必要条件。另外,我们说明了与当前方法相比,采用局部类来生成概念和属性约简的方法更简单,更方便。

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