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International Fuzzy Systems Association World Congress

IFSA/NAFIPS 2019 2019: Fuzzy Techniques: Theory and Applications pp 727–737Cite as

Towards Hybrid Uncertain Data Modeling in Databases

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1000))

Abstract

Uncertain data extensively exists in many real-world applications. And uncertain data modeling has been investigated in various database models. This has resulted in numerous contributions. Actually, uncertainty in data has devise semantics, mainly including objective uncertainty and subjective uncertainty. Different types of uncertainty may occur together and we face with hybrid uncertain data with objective uncertainty and subjective uncertainty. This paper devotes to identify the semantics and expressive forms of hybrid uncertain data with both objective uncertainty and subjective uncertainty, and presents an up-to-date overview of the current state of the art in hybrid uncertain data modeling in relational databases and object-oriented databases.

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Acknowledgment

The work was supported in part by the National Natural Science Foundation of China (61772269 and 61370075).

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, Jiangsu, China

    Li Yan & Zongmin Ma

Authors
  1. Li Yan
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  2. Zongmin Ma
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Corresponding author

Correspondence to Zongmin Ma .

Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA, USA

    Ralph Baker Kearfott

  2. Center for Computing Research (CIC), Instituto Politecnico Nacional, Ciudad de Mexico, Mexico

    Ildar Batyrshin

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Marek Reformat

  4. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Martine Ceberio

  5. Department of Computer Science, University of Texas at El Paso , El Paso, TX, USA

    Vladik Kreinovich

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Yan, L., Ma, Z. (2019). Towards Hybrid Uncertain Data Modeling in Databases. In: Kearfott, R., Batyrshin, I., Reformat, M., Ceberio, M., Kreinovich, V. (eds) Fuzzy Techniques: Theory and Applications. IFSA/NAFIPS 2019 2019. Advances in Intelligent Systems and Computing, vol 1000. Springer, Cham. https://doi.org/10.1007/978-3-030-21920-8_64

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