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Efficient Algorithm for the Extraction of Association Rules in Data Mining

  • Conference paper
Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3981))

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Abstract

The problem of data mining is to discover the pattern or trend in huge volume of data. The problem is similar to knowledge discovery in artificial intelligence. Here our goal is to discover rules that reflect the pattern in the data. These rules are called association rules. In [AS94] an algorithm is proposed to extract these association rules from the large/frequent itemsets computed by the apriori algorithm. In this paper we present a more efficient and output sensitive algorithm to compute these association rules given the lattice L of large itemsets. Our approach is based on pruning a lot of redundant association rules that have to be tested in the algorithm of [AS94] .We use a variation of the data structure for hashing using separate chaining in our algorithm. Our algorithm, is output sensitive in the sense that its time complexity will be proportional to the number of association rules that have to be generated and it is also optimal.

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Author information

Authors and Affiliations

  1. Indian Institute of Technology Guwahati, North Guwahati, Guwahati, 781039, India

    Pinaki Mitra

  2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, 700032, India

    Chitrita Chaudhuri

Authors
  1. Pinaki Mitra
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  2. Chitrita Chaudhuri
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Mitra, P., Chaudhuri, C. (2006). Efficient Algorithm for the Extraction of Association Rules in Data Mining. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751588_1

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  • DOI: https://doi.org/10.1007/11751588_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34072-0

  • Online ISBN: 978-3-540-34074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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