Attribute Reduction and Rule Acquisition of Formal Decision Context Based on Dual Concept Lattice

Concept lattice theory is a powerful tool for analyzing and extracting information from data sets. Rule acquisition and attribute reduction are hot research topics in formal concept analysis. This paper mainly proposes three kinds of rules based on formal concepts and dual concepts. In addition, the...

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Bibliographic Details
Published inLearning Technologies and Systems Vol. 12511; pp. 117 - 129
Main Authors Hu, Qian, Qin, Keyun
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2021
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Attribute reduction
Dual concept lattice
Formal concept analysis
Object-oriented and property-oriented concept lattice
Rule acquisition
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Summary:Concept lattice theory is a powerful tool for analyzing and extracting information from data sets. Rule acquisition and attribute reduction are hot research topics in formal concept analysis. This paper mainly proposes three kinds of rules based on formal concepts and dual concepts. In addition, the methods of rule acquisition for different kinds of rules are presented. Finally, the attribute reduction approaches to preserve different kinds of rules are given by using discernibility matrix.
Bibliography:Supported by the National Natural Science Foundation of China (Grant No. 61976130).
ISBN:303066905X
9783030669058
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-030-66906-5_11