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Attribute Classification and Reduct Computation in Multi-Adjoint Concept Lattices

机译:多伴随概念格的属性分类和减减计算

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摘要

The problem of reducing information in databases is an important topic in formal concept analysis, which has been studied in several articles. In this article, we consider the fuzzy environment of the multi-adjoint concept lattices, since it is a general fuzzy framework that allows us to easily establish degrees of preference on the elements of the considered database. We introduce algorithms to discover the information contained in the relational system. By means of these algorithms, we classify the attributes of a multi-adjoint context, and build a minimal subset of attributes preserving the information of the original knowledge system.
机译:减少数据库信息的问题是正式概念分析中的一个重要课题,这些主题是在几篇文章中研究过的。 在本文中,我们考虑多伴随概念格的模糊环境,因为它是一种普遍模糊框架,其允许我们容易地建立对所考虑数据库的元素的偏好度。 我们介绍算法,以发现关系系统中包含的信息。 通过这些算法,我们对多相伴随上下文的属性进行分类,并构建保留原始知识系统信息的最小属性子集。

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