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Computing the minimum-support for mining frequent patterns

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Abstract

Frequent pattern mining is based on the assumption that users can specify the minimum-support for mining their databases. It has been recognized that setting the minimum-support is a difficult task to users. This can hinder the widespread applications of these algorithms. In this paper we propose a computational strategy for identifying frequent itemsets, consisting of polynomial approximation and fuzzy estimation. More specifically, our algorithms (polynomial approximation and fuzzy estimation) automatically generate actual minimum-supports (appropriate to a database to be mined) according to users’ mining requirements. We experimentally examine the algorithms using different datasets, and demonstrate that our fuzzy estimation algorithm fittingly approximates actual minimum-supports from the commonly-used requirements.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, Guangxi Normal University, Guilin, 541004, People’s Republic of China

    Shichao Zhang

  2. Department of Computer Science, University of Vermont, Burlington, VT, 05405, USA

    Xindong Wu

  3. Faculty of Information Technology, University of Technology, Sydney, PO Box 123, Broadway, NSW, 2007, Australia

    Chengqi Zhang

  4. Institute of Information Sciences and Technology, Massey University, Palmerston North, New Zealand

    Jingli Lu

Authors
  1. Shichao Zhang
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  2. Xindong Wu
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  3. Chengqi Zhang
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  4. Jingli Lu
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Corresponding author

Correspondence to Shichao Zhang.

Additional information

This work is partially supported by Australian ARC grants for discovery projects (DP0449535, DP0559536 and DP0667060), a China NSF Major Research Program (60496327), a China NSF grant (60463003), an Overseas Outstanding Talent Research Program of the Chinese Academy of Sciences (06S3011S01), and an Overseas-Returning High-level Talent Research Program of China Human-Resource Ministry.

A preliminary and shortened version of this paper has been published in the Proceedings of the 8th Pacific Rim International Conference on Artificial Intelligence (PRICAI ’04).

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Zhang, S., Wu, X., Zhang, C. et al. Computing the minimum-support for mining frequent patterns. Knowl Inf Syst 15, 233–257 (2008). https://doi.org/10.1007/s10115-007-0081-7

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