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International Joint Conference on Rough Sets

IJCRS 2016: Rough Sets pp 197–206Cite as

Matrix-Based Rough Set Approach for Dynamic Probabilistic Set-Valued Information Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9920))

Abstract

Set-valued information systems (SvIS), in which the attribute values are set-valued, are important types of data representation with uncertain and missing information. However, all previous investigations in rough set community do not consider the attribute values with probability distribution in SvIS, which may be impractical in many real applications. This paper introduces probabilistic set-valued information systems (PSvIS) and presents an extended variable precision rough sets (VPRS) approach based on \(\lambda \)-tolerance relation for PSvIS. Furthermore, due to the dynamic variation of attributes in PSvIS, viz., the addition and deletion of attributes, we present a matrix characterization of the proposed VPRS model and discuss some related properties. Then incremental approaches for maintaining rough approximations based on matrix operations are presented, which can effectively accelerate the updating of rough approximations in dynamic PSvIS.

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Acknowledgements

This work is supported by the National Science Foundation of China (Nos. 61573292, 61572406).

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Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 611756, China

    Yanyong Huang, Tianrui Li & Shi-jinn Horng

  2. College of Computer Science, Sichuan University, Chengdu, 610056, China

    Chuan Luo

Authors
  1. Yanyong Huang
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  2. Tianrui Li
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  3. Chuan Luo
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  4. Shi-jinn Horng
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Corresponding author

Correspondence to Tianrui Li .

Editor information

Editors and Affiliations

  1. Universidad Católica del Norte, Antofagasta, Chile

    Víctor Flores

  2. University of Campinas, Campinas, SP, Brazil

    Fernando Gomide

  3. University of Warsaw, Warsaw, Poland

    Andrzej Janusz

  4. Universidad del Católica del Norte, Antofagasta, Chile

    Claudio Meneses

  5. Tongji University, Shanghai, China

    Duoqian Miao

  6. University of Applied Sciences, Munich, Germany

    Georg Peters

  7. University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

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

    Guoyin Wang

  9. Universidad de Chile, Santiago, Chile

    Richard Weber

  10. University of Regina, Regina, Saskatchewan, Canada

    Yiyu Yao

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© 2016 Springer International Publishing AG

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Huang, Y., Li, T., Luo, C., Horng, Sj. (2016). Matrix-Based Rough Set Approach for Dynamic Probabilistic Set-Valued Information Systems. In: Flores, V., et al. Rough Sets. IJCRS 2016. Lecture Notes in Computer Science(), vol 9920. Springer, Cham. https://doi.org/10.1007/978-3-319-47160-0_18

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  • DOI: https://doi.org/10.1007/978-3-319-47160-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47159-4

  • Online ISBN: 978-3-319-47160-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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