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An Efficient Distributed Algorithm for Computing Association Rules

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Web-Age Information Management (WAIM 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1846))

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Abstract

Data mining aims to efficiently discover previously unknown knowledge from large databases. It is highly demanding in numerous real-life applications, such as marketing strategy, financial forecast, etc. One of the fundamental problems in the area is the efficient computation of association rules. In this paper, we shall investigate this problem in a distributed database. Particularly, we will present an efficient distributed algorithm for mining distributed association rules. Our experiment results suggest that the proposed algorithm outperforms the existing distributed algorithms. Further, we also study a distributed version of the problem of association rules; and extend our algorithm to solve this new problem.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Yijun Li & Xuemin Lin

  2. Deparment of Computer Science, University of Western Australia, Nedlands, WA, 6907, Australia

    Chi-Ping Tsang

Authors
  1. Yijun Li
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  2. Xuemin Lin
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  3. Chi-Ping Tsang
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

    Hongjun Lu

  2. Department of Computer Science, Fudan University, 220 Handan Road, Shanghai, China

    Aoying Zhou

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© 2000 Springer-Verlag Berlin Heidelberg

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Li, Y., Lin, X., Tsang, CP. (2000). An Efficient Distributed Algorithm for Computing Association Rules. In: Lu, H., Zhou, A. (eds) Web-Age Information Management. WAIM 2000. Lecture Notes in Computer Science, vol 1846. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45151-X_10

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  • DOI: https://doi.org/10.1007/3-540-45151-X_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67627-0

  • Online ISBN: 978-3-540-45151-8

  • eBook Packages: Springer Book Archive

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