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2021 | OriginalPaper | Chapter

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

Authors : Qian Hu, Keyun Qin

Published in: Learning Technologies and Systems

Publisher: Springer International Publishing

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Abstract

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.

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Metadata
Title
Attribute Reduction and Rule Acquisition of Formal Decision Context Based on Dual Concept Lattice
Authors
Qian Hu
Keyun Qin
Copyright Year
2021
Book
Learning Technologies and Systems

Print ISBN: 978-3-030-66905-8

Electronic ISBN: 978-3-030-66906-5

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-66906-5_11

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