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Variable-precision three-way concepts in L-contexts
International Journal of Approximate Reasoning ( IF 3.9 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.ijar.2020.11.005
Xuerong Zhao , Duoqian Miao , Hamido Fujita

Abstract The notion of fuzzy concept is proposed to deal with object-attribute data with L-values (where L is a truth-value structure). One disadvantage of fuzzy concepts is that a fuzzy context contains a considerable number of fuzzy concepts. This makes it very time-consuming to generate a fuzzy concept lattice, and it is very difficult to find important concepts. In addition, the fuzzy concept shows great strictness when applying to crisp sets. To overcome these problems, we propose several new kinds of variable-precision concepts within L-contexts in this paper. First, we present two kinds of variable-precision two-way (short for VP2W) concepts: α-positive concept and β-negative concept. The family of each kind of VP2W concept forms a complete lattice. Next, considering both the positive and negative parts, we investigate two kinds of variable-precision three-way (short for VP3W) concepts: ( α , β ) -object-induced three-way concept and ( α , β ) -attribute-induced three-way concept. The family of each kind of VP3W concept forms a complete lattice. Then, we study the relationship between VP2W concepts and VP3W concepts. The results show that VP3W concept lattices can be directly generated by VP2W concept lattices. Finally, the experiments are preformed to verify the effectiveness of our model.

中文翻译:

L 上下文中的可变精度三向概念

摘要 提出模糊概念的概念来处理具有L值(其中L为真值结构)的对象属性数据。模糊概念的一个缺点是模糊上下文包含相当数量的模糊概念。这使得生成模糊概念格非常耗时,并且很难找到重要的概念。此外,模糊概念在应用于清晰集合时表现出极大的严格性。为了克服这些问题,我们在本文中提出了 L-contexts 中的几种新的可变精度概念。首先,我们提出两种可变精度双向(VP2W 的缩写)概念:α-positive 概念和 β-negative 概念。各种VP2W概念的家族构成一个完整的格子。接下来,考虑正面和负面的部分,我们研究了两种精度可变的三向(VP3W 的缩写)概念:( α , β ) - 对象诱导的三向概念和 ( α , β ) - 属性诱导的三向概念。各种VP3W概念的家族构成了一个完整的格子。然后,我们研究VP2W 概念和VP3W 概念之间的关系。结果表明VP2W概念格可以直接生成VP3W概念格。最后,进行实验以验证我们模型的有效性。结果表明VP2W概念格可以直接生成VP3W概念格。最后,进行实验以验证我们模型的有效性。结果表明VP2W概念格可以直接生成VP3W概念格。最后,进行实验以验证我们模型的有效性。
更新日期:2021-03-01
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