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International Conference on Conceptual Modeling

ER 1998: Advances in Database Technologies pp 55–67Cite as

On the Suitability of Genetic-Based Algorithms for Data Mining

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1552))

Abstract

Data mining has as goal to extract knowledge from large databases. A database may be considered as a search space consisting of an enormous number of elements, and a mining algorithm a,s a search strategy. In general, an exhaustive search of the space is infeasible. Therefore, efficient search strategies are of vital importance. Search strategies on genetic-based algorithms have been applied successfully in a wide range of applications. We focus on the suitability of genetic-based algorithms for data mining. We discuss the design and implementation of a genetic-based algorithm for data mining and illustrate its potentials.

This research has been sponsored by the Dutch Ministry of Defense.

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Author information

Authors and Affiliations

  1. Nat. Aerospace Lab., NLR, P.O. Box 90502, 1006 BM, Amsterdam, The Netherlands

    Sunil Choenni

  2. Univ. of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands

    Sunil Choenni

Authors
  1. Sunil Choenni
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Editor information

Editors and Affiliations

  1. Graduate School of Informatics, Dept. of Social Informatics, Kyoto University, 606-8501, Yoshida Sakyo Kyoto, Japan

    Yahiko Kambayashi

  2. Dept. of Computer Science Clear Water Bay, Hong Kong University of Science and Technology, Hong Kong, China

    Dik Lun Lee

  3. School of Applied Science, Nanyang Technological University, N4-2A-12, Nanyang Avenue, 639798, Singapore

    Ee-Peng Lim

  4. School of Computer and Information Science The Levels Campus, University of South Australia, Mawson Lakes, 5095, S.A., Australia

    Mukesh Kumar Mohania

  5. Faculty of Science, Dept. of Information Sciences, Ochanomizu University, 2-1-1 Otsuka, Bunkyo-ku, 112-8610, Tokyo, Japan

    Yoshifumi Masunaga

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© 1999 Springer-Verlag Berlin Heidelberg

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Choenni, S. (1999). On the Suitability of Genetic-Based Algorithms for Data Mining. In: Kambayashi, Y., Lee, D.L., Lim, EP., Mohania, M.K., Masunaga, Y. (eds) Advances in Database Technologies. ER 1998. Lecture Notes in Computer Science, vol 1552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49121-7_5

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  • DOI: https://doi.org/10.1007/978-3-540-49121-7_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65690-6

  • Online ISBN: 978-3-540-49121-7

  • eBook Packages: Springer Book Archive

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