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A fast distributed algorithm for association rule mining based on binary coding mapping relation

  • Web Information Mining and Retrieval
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Wuhan University Journal of Natural Sciences

Abstract

Association rule mining is an important issue in data mining. The paper proposed an binary system based method to generate candidate frequent itemsets and corresponding supporting counts efficiently, which needs only some operations such as “and”, “or” and “xor”. Applying this idea in the existed distributed association rule mining algorithm FDM, the improved algorithm BFDM is proposed. The theoretical analysis and experiment testify that BFDM is effective and efficient.

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Authors and Affiliations

  1. Department of Computer and Engineering, Southeast University, 210096, Nanjing Jiangsu, China

    Chen Geng, Ni Wei-wei & Sun Zhi-hui

  2. School of Computer Science and Communication Engineering, Jiangsu University, 212013, Zhenjiang Jiangsu, China

    Zhu Yu-quan

Authors
  1. Chen Geng
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  2. Ni Wei-wei
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  3. Zhu Yu-quan
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  4. Sun Zhi-hui
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Corresponding author

Correspondence to Sun Zhi-hui.

Additional information

Foundation item: Supported by the National Natural Science Foundation of China (70371015)

Biography: CHEN Geng (1965-), male, Ph. D. candidate, research direction: data mining and knowledge discovery.

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Geng, C., Wei-wei, N., Yu-quan, Z. et al. A fast distributed algorithm for association rule mining based on binary coding mapping relation. Wuhan Univ. J. Nat. Sci. 11, 27–30 (2006). https://doi.org/10.1007/BF02831698

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  • DOI: https://doi.org/10.1007/BF02831698

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