基于粒度形式语境的概念分析

Zhen Wang, Ling Wei, Jianjun Qi
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引用次数: 0

摘要

形式概念分析(FCA)是一种从形式语境中发现知识和制定决策的有效工具。然而,在大数据时代,FCA可能会面临一些挑战,其中之一就是从大的正式语境中发现知识可能会很困难。为了使从形式语境中发现知识变得更加容易和简单,本研究提出了基于颗粒形式语境的概念分析。首先,将FCA与颗粒计算(GrC)的分层思想相结合,提出了颗粒形式上下文。然后,在此基础上定义了相应的概念,如颗粒派生算子、颗粒形式概念和颗粒概念格。最后,给出了经典和颗粒派生算子/形式概念/概念格之间的联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Concept Analysis Based on Granular Formal Contexts
Formal concept analysis (FCA) is an efficient tool for knowledge discovery and decision making from formal contexts. However, in the era of big data, FCA may face some challenges, one of which is that discovering knowledge from a big formal context may be hard. To make knowledge discovery from formal contexts easier and simpler, this study presents concept analysis based on granular formal contexts. First, granular formal context is proposed by combining FCA with the hierarchical idea of granular computing (GrC). Then, based on which, the corresponding notions such as granular derivation operators, granular formal concept, and granular concept lattice are defined. Finally, the connections between classical and granular derivation operators/formal concepts/concept lattices are presented.
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