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Fuzzy Concepts in Formal Context

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Advances in Swarm and Computational Intelligence (ICSI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9142))

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Abstract

Formal concept analysis (FCA) provides a theoretical framework for learning hierarchies of knowledge clusters. This paper is devoted to the study of the fuzzy concept in FCA. We propose a fuzzy relation on the universe to characterize the similarity of the objects. Based on fuzzy rough set model, we present a kind of approximation operators to characterize the fuzzy concept and its accuracy degree in FCA. The basic properties of these operators are investigated.

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Author information

Authors and Affiliations

  1. College of Mathematics, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China

    Luodan Meng & Keyun Qin

Authors
  1. Luodan Meng
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  2. Keyun Qin
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Corresponding author

Correspondence to Keyun Qin .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Universidade de Pernambuco, Recife, Brazil

    Fernando Buarque

  4. Instituto Politécnico Nacional, Mexico, Mexico

    Alexander Gelbukh

  5. Indian Statistical Institute, Kolkata, India

    Swagatam Das

  6. University of Pretoria, Pretoria, South Africa

    Andries Engelbrecht

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© 2015 Springer International Publishing Switzerland

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Meng, L., Qin, K. (2015). Fuzzy Concepts in Formal Context. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9142. Springer, Cham. https://doi.org/10.1007/978-3-319-20469-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-20469-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20468-0

  • Online ISBN: 978-3-319-20469-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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