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The Combination of Evolutionary Algorithm Method for Numerical Association Rule Mining Optimization

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Proceedings of the Tenth International Conference on Management Science and Engineering Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 502))

Abstract

The numerical problem of association rule mining is an updated issue. Numerous authors propose some methods to solved it. A number of them are using the optimization approach by Particle Swarm Optimization (PSO). The problem is that the PSO trapped in local optima when searched the best particle in every iteration. Many researchers solved this problem by combining with Cauchy distribution because it is tremendous for searching in a large neighborhood. Hence, that combination will be implemented to accomplish the numerical association rule mining problem for some objective functions such as confidence, comprehensibility, interestingness. Based on the result the multi-objective of PSO for Numerical Association Rule Mining Problem with Cauchy Distribution (PARCD) showed the better result than the method of Multi-objective Particle Swarm Optimization for Association Rule Mining (MOPAR).

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Acknowledgments

This research supported by various parties. We would like to thank for scholarship program from Kanazawa University, Japan and Ministry of Research, Technology and Higher Education (KEMENRISTEKDIKTI) and also STMIK AMIKOM Purwokerto, Indonesia. In addition, we thank for anonymous reviewers who gave input and correction for improving this research.

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Authors and Affiliations

  1. Graduate School of Natural Science and Technology Division of Electrical Engineering and Computer Science, Kanazawa University, Kanazawa, Japan

    Imam Tahyudin & Hidetaka Nambo

Authors
  1. Imam Tahyudin
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  2. Hidetaka Nambo
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Corresponding author

Correspondence to Imam Tahyudin .

Editor information

Editors and Affiliations

  1. Business School, Sichuan University, Chengdu, Sichuan, China

    Jiuping Xu

  2. Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Asaf Hajiyev

  3. Karlsruhe Institute of Technology, Karlsruhe, Baden-Württemberg, Germany

    Stefan Nickel

  4. Tokyo University of Science, Fuzzy Logic Systems Institute, Tokyo, Japan

    Mitsuo Gen

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Tahyudin, I., Nambo, H. (2017). The Combination of Evolutionary Algorithm Method for Numerical Association Rule Mining Optimization. In: Xu, J., Hajiyev, A., Nickel, S., Gen, M. (eds) Proceedings of the Tenth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 502. Springer, Singapore. https://doi.org/10.1007/978-981-10-1837-4_2

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  • DOI: https://doi.org/10.1007/978-981-10-1837-4_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1836-7

  • Online ISBN: 978-981-10-1837-4

  • eBook Packages: EngineeringEngineering (R0)

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