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Discovering Patterns Based on Fuzzy Logic Theory

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Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3983))

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Abstract

This study investigates the formulation of fuzzy logic as integrated component of the proposed model in data mining in order to classify the dataset prior to the implementation of data mining tools such summarization, association rule discovery, and prediction. The novel contribution of this paper is the fuzzification of the dataset prior to pattern discovery. The model is compared to the classical clustering, regression model, and neural network using the Internet usage database available at the UCI Knowledge Discovery on Databases (KDD) archive. Our test is anchored on parameters like relevant measure, processing performance, discovered rules or patterns and practical use of the findings. The proposed model indicates adequate performance in clustering, higher clustering accuracy and efficient pattern discovery compared with the other models.

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Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Kunsan National University, 68 Miryong-dong, Kunsan, Chonbuk, 573-701, South Korea

    Bobby D. Gerardo & Jaewan Lee

  2. School of Electrical Electronic and Information Engineering, Wonkwang University, 344-2 Shinyong-dong, Iksan, Chonbuk, 570-749, South Korea

    Su-Chong Joo

Authors
  1. Bobby D. Gerardo
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  2. Jaewan Lee
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  3. Su-Chong Joo
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd.,, Cathedral House 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Gerardo, B.D., Lee, J., Joo, SC. (2006). Discovering Patterns Based on Fuzzy Logic Theory. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751632_97

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  • DOI: https://doi.org/10.1007/11751632_97

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34077-5

  • Online ISBN: 978-3-540-34078-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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