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Crisp-Fuzzy Concept Lattice Based on Interval-Valued Fuzzy Sets

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Rough Sets (IJCRS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14481))

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Abstract

Fuzzy concept lattices can be viewed as the generalizations of the classical concept lattices in fuzzy formal contexts, which is a key issue and a major research direction in knowledge discovery. Crisp-fuzzy concept lattices are special fuzzy concept lattices, the existing crisp-fuzzy concept lattices can be divided into two categories, that is, one is the extension of the classical concept lattice, and the other is based on rough fuzzy approximation operations. In this paper, by combing these two types of crisp-fuzzy concept lattices and using interval-valued fuzzy sets, a novel crisp-fuzzy concept lattice is firstly presented, then the properties of the new model are discussed in detail. From two aspects of granular and algebraic structures, the new concept lattice is compared with two types of existing crisp-fuzzy concept lattices, which shows that the former has obvious advantages over the latter. Therefore, the work has not only enriched the theory of fuzzy concept lattice, but helpful for its application.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (Nos. 61773349, 61976194).

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Authors and Affiliations

  1. School of Information Engineering, Zhejiang Ocean University, Zhoushan, 316022, Zhejiang, China

    Tong-Jun Li & Yi-Qian Wang

  2. Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan, 316022, Zhejiang, China

    Tong-Jun Li

Authors
  1. Tong-Jun Li
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  2. Yi-Qian Wang
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Corresponding author

Correspondence to Tong-Jun Li .

Editor information

Editors and Affiliations

  1. IRCCS Istituto Ortopedico Galeazzi, Milano, Italy

    Andrea Campagner

  2. Ghent University, Ghent, Belgium

    Oliver Urs Lenz

  3. Chongqing University of Posts and Telecommunications, Chongqing, China

    Shuyin Xia

  4. University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

  5. AGH University of Science and Technology, Kraków, Poland

    Jarosław Wąs

  6. University of Regina, Regina, SK, Canada

    JingTao Yao

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Li, TJ., Wang, YQ. (2023). Crisp-Fuzzy Concept Lattice Based on Interval-Valued Fuzzy Sets. In: Campagner, A., Urs Lenz, O., Xia, S., Ślęzak, D., Wąs, J., Yao, J. (eds) Rough Sets. IJCRS 2023. Lecture Notes in Computer Science(), vol 14481. Springer, Cham. https://doi.org/10.1007/978-3-031-50959-9_31

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  • DOI: https://doi.org/10.1007/978-3-031-50959-9_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50958-2

  • Online ISBN: 978-3-031-50959-9

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