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Using Fuzzy Analogical Reasoning to Refine the Query Answers for Relational Databases with Imprecise Information

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

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Abstract

In this paper, we use the notion of equivalence degree of fuzzy data, by which we can mine the rules of fuzzy functional dependencies from the fuzzy relational databases. Following the rules of fuzzy functional dependencies, we can apply the frame of analogical reasoning to refine the imprecise query answer for the relational databases with imprecise information.

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Authors and Affiliations

  1. Northeastern University, Shenyang, Liaoning, 110004, China

    Z. M. Ma & Li Yan

  2. Liaoning Branch of China Netcom (Group) Corporation LTD., Shenyang, Liaoning, 110044, China

    Gui Li

Authors
  1. Z. M. Ma
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  2. Li Yan
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  3. Gui Li
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Ma, Z.M., Yan, L., Li, G. (2005). Using Fuzzy Analogical Reasoning to Refine the Query Answers for Relational Databases with Imprecise Information. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_34

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  • DOI: https://doi.org/10.1007/11539506_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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