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Is Minimum-Support Appropriate to Identifying Large Itemsets?

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PRICAI 2004: Trends in Artificial Intelligence (PRICAI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3157))

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Abstract

Apriori-like algorithms have been based on the assumption that users can specify the minimum-support for their databases. In this paper, we propose a fuzzy strategy for identifying interesting itemsets without specifying the true minimum-support. This strategy allows users to specify their mining requirements in commonly sentences. And our algorithm generates potentially useful itemsets in fuzzy sets.

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Author information

Authors and Affiliations

  1. Faculty of IT, University of Technology, Sydney, Australia

    Shichao Zhang & Li Liu

  2. Computing School, Guangxi Normal University, Guilin, China

    Jingli Lu & Yuming Ou

Authors
  1. Shichao Zhang
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  2. Li Liu
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  3. Jingli Lu
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  4. Yuming Ou
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, and Australian ACS National Committee for Artificial Intelligence, University of Technology, Sydney, Australia

    Chengqi Zhang

  2. Department of Computer Science, Auckland University of Technology, 1020, Auckland, New Zealand

    Hans W. Guesgen

  3. Artificial Intelligence Technology Centre, Auckland University of Technology, Auckland, New Zealand

    Wai-Kiang Yeap

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© 2004 Springer-Verlag Berlin Heidelberg

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Zhang, S., Liu, L., Lu, J., Ou, Y. (2004). Is Minimum-Support Appropriate to Identifying Large Itemsets?. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_51

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  • DOI: https://doi.org/10.1007/978-3-540-28633-2_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22817-2

  • Online ISBN: 978-3-540-28633-2

  • eBook Packages: Springer Book Archive

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