A representation of continuous domains via relationally approximable concepts in a generalized framework of formal concept analysis

被引:7
作者
Guo, Lankun [1 ]
Li, Qingguo [2 ]
Zhang, Guo-Qiang [3 ]
机构
[1] Hunan Normal Univ, Coll Math & Stat, Key Lab High Performance Comp & Stochast Informat, Changsha 410012, Hunan, Peoples R China
[2] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
[3] Univ Texas Hlth Sci Ctr Houston, Houston, TX 77030 USA
基金
中国国家自然科学基金;
关键词
Consistent F-augmented context; Relationally approximable concept; Continuous domain; Equivalence of categories; Formal concept analysis; CONCEPT CONSTRUCTION; ATTRIBUTE REDUCTION; INFORMATION-SYSTEMS; ACQUISITION; LATTICES;
D O I
10.1016/j.ijar.2019.08.007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, in order to realize a representation of continuous domains, the notions of relationally consistent F-augmented contexts and relationally approximable concepts are introduced, which provides a generalized framework of formal concept analysis. We also introduce the notion of F-approximable mappings which serves as the morphism between relationally consistent F-augmented contexts. The main result is that the category of relationally consistent F-augmented contexts is equivalent to that of continuous domains with Scott continuous maps being morphisms. This provides a new approach to concretely representing continuous domains and demonstrates the efficiency of formal concept analysis in representing some important partially ordered structures. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页码:29 / 43
页数:15
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