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Approximation Relation for Rough Sets

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Data Mining and Big Data (DMBD 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1454))

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Abstract

Rough set theory has the ability of deduction, reduction and common sense reasoning. First, this paper proposes the definition of the approximation relation; then, a kind of measurement method based on the approximation relation is proposed to judge whether any two sets are approximate with each other and then we can mine all of the sets that are approximate with a certain set by the measurement method in any approximation space; finally, this paper discusses algebraic properties for the measurement method, furthermore, we give its algebraic structure, which is proved a new standard boolean algebra for Rough sets.

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Acknowledgment

This work was partially supported by the Science and Technology Project of Jiangxi Provincial Education Department (Nos. GJJ201917, GJJ161109 and GJJ190941), and the National Science Foundation of China (Nos. 61763032 and 61562061).

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Authors and Affiliations

  1. School of Information Engineering, NanChang Institute Of Technology, Nanchang, 330099, China

    Shaobo Deng, Huihui Lu, Sujie Guan, Min Li & Hui Wang

Authors
  1. Shaobo Deng
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  2. Huihui Lu
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  3. Sujie Guan
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  4. Min Li
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  5. Hui Wang
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Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. The University of Sydney, Sydney, Australia

    Albert Zomaya

  4. Guangzhou University, Guangzhou, China

    Hongyang Yan

  5. Guangdong Polytechnic Normal University, Guangzhou, China

    Jun Cai

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Deng, S., Lu, H., Guan, S., Li, M., Wang, H. (2021). Approximation Relation for Rough Sets. In: Tan, Y., Shi, Y., Zomaya, A., Yan, H., Cai, J. (eds) Data Mining and Big Data. DMBD 2021. Communications in Computer and Information Science, vol 1454. Springer, Singapore. https://doi.org/10.1007/978-981-16-7502-7_38

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  • DOI: https://doi.org/10.1007/978-981-16-7502-7_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7501-0

  • Online ISBN: 978-981-16-7502-7

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