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International Conference on Intelligent Computing

ICIC 2005: Advances in Intelligent Computing pp 370–379Cite as

A Matrix Algorithm for Mining Association Rules

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3644))

Abstract

Finding association rules is an important data mining problem and can be derived based on mining large frequent candidate sets. In this paper, a new algorithm for efficient generating large frequent candidate sets is proposed, which is called Matrix Algorithm. The algorithm generates a matrix which entries 1 or 0 by passing over the cruel database only once, and then the frequent candidate sets are obtained from the resulting matrix. Finally association rules are mined from the frequent candidate sets. Numerical experiments and comparison with the Apriori Algorithm are made on 4 randomly generated test problems with small, middle and large sizes. Experiments results confirm that the proposed algorithm is more effective than Apriori Algorithm.

Supported by the Youth Key Foundations of Univ. of Electronic Science and Technology of China (Jx04042).

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Author information

Authors and Affiliations

  1. School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, P.R. China

    Yubo Yuan & Tingzhu Huang

Authors
  1. Yubo Yuan
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  2. Tingzhu Huang
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Editor information

Editors and Affiliations

  1. Intelligent Computing Lab, Institute of Intelligent Machines, Chinese Academy of Sciences,, China

    De-Shuang Huang

  2. School of Computer & Information Technology, Beijing Jiaotong University, 100044, Beijing, P.R. China

    Xiao-Ping Zhang

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, P.O. Box, Singapore

    Guang-Bin Huang

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© 2005 Springer-Verlag Berlin Heidelberg

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Yuan, Y., Huang, T. (2005). A Matrix Algorithm for Mining Association Rules. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_39

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  • DOI: https://doi.org/10.1007/11538059_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28226-6

  • Online ISBN: 978-3-540-31902-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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