Computing Frequent Itemsets in Parallel Using Partial Support Trees

  • Dora Souliou
  • Aris Pagourtzis
  • Nikolaos Drosinos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3666)


A key process in association rules mining, which has attracted a lot of interest during the last decade, is the discovery of frequent sets of items in a database of transactions. A number of sequential algorithms have been proposed that accomplish this task. In this paper we study the parallelization of the partial-support-tree approach (Goulbourne, Coenen, Leng, 2000). Results show that this method achieves a generally satisfactory speedup, while it is particularly adequate for certain types of datasets.


Parallel data mining association rules frequent itemsets partial support tree set-enumeration tree 


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  1. 1.
    Agrawal, R., Aggarwal, C., Prasad, V.: Depth First Generation of Long Patterns. In: KDD 2000, pp. 108–118. ACM, New York (2000)CrossRefGoogle Scholar
  2. 2.
    Ahmed, S., Coenen, F., Leng, P.H.: A Tree Partitioning Method for Memory Management in Association Rule Mining. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds.) DaWaK 2004. LNCS, vol. 3181, pp. 331–340. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  3. 3.
    Angiulli, F., Ianni, G., Palopoli, L.: On the complexity of inducing categorical and quantitative association rules. arXiv:cs.CC/0111009 1 (November 2001)Google Scholar
  4. 4.
    Agrawal, R., Imielinski, T., Swami, A.: Mining Association Rules between Sets of Items in Large Databases. In: Proc. of ACM SIGMOD Conference on Management of Data, Washington DC (May 1993)Google Scholar
  5. 5.
    Agrawal, R., Imielinski, T., Swami, A.: Database mining: a performance perspective. IEEE Transactions on Knowledge and Data Engineering 5(6), 914–925 (1993); Special Issue on Learning and Discovery in Knowledge-Based DatabasesCrossRefGoogle Scholar
  6. 6.
    Agrawal, R., Srikant, R.: Fast Algorithms for mining association rules. In: Proc. VLDB 1994, pp. 487–499 (1994)Google Scholar
  7. 7.
    Agrawal, R., Shafer, J.C.: Parallel Mining of Association Rules. IEEE Trans. Knowl. Data Eng. 8(6), 962–969 (1996)CrossRefGoogle Scholar
  8. 8.
    Bayardo Jr., R.J., Agrawal, R.: Mining the Most Interesting Rules. In: Proc. of the Fifth ACM SIGKDD Int’l Conf. on Knowledge Discovery and Data Mining, pp. 145–154 (1999)Google Scholar
  9. 9.
    Boros, E., Gurvich, V., Khachiyan, L., Makino, K.: On the complexity of generating maximal frequent and minimal infrequent sets. In: Alt, H., Ferreira, A. (eds.) STACS 2002. LNCS, vol. 2285, p. 133. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  10. 10.
    Coenen, F., Goulbourne, G., Leng, P.: Computing Association Rules using Partial Totals. In: Siebes, A., De Raedt, L. (eds.) PKDD 2001. LNCS (LNAI), vol. 2168, pp. 54–66. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  11. 11.
    Coenen, F., Goulbourne, G., Leng, P.: Tree Structures for Mining Association Rules. Data Mining and Knowledge Discovery 8, 25–51 (2004)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Goulbourne, G., Coenen, F., Leng, P.: Algorithms for Computing Association Rules using a Partial-Support Tree. Journal of Knowledge-Based Systems 13, 141–149 (2000)CrossRefGoogle Scholar
  13. 13.
    Han, J., Pei, J., Yin, Y., Mao, R.: Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach. Data Mining and Knowledge Discovery 8, 53–87 (2004)CrossRefMathSciNetGoogle Scholar
  14. 14.
    Raymon, R.: Search Through Systematic Search Enumeration. In: Proc. 3rd Int,l Conf. on Principles of Knowledge Representation and Reasoning, pp. 539–550Google Scholar
  15. 15.
    Savasere, A., Omiecinski, E., Navathe, S.: An Efficient Algorithm for Mining Association Rules in Large Databases. In: VLDB 1995, pp. 432–444 (1995)Google Scholar
  16. 16.
    Toivonen, H.: Sampling Large Databses for Association Rules. In: VLDB 1996, pp. 1–12 (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Dora Souliou
    • 1
  • Aris Pagourtzis
    • 1
  • Nikolaos Drosinos
    • 1
  1. 1.School of Electrical and Computer EngineeringNational Technical University of AthensZografouGreece

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