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An Efficient Graph-Based Method for Parallel Mining Problems

Author

Listed:
  • Chin-Chen Chang

    (Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi 621, Taiwan, R.O.C.)

  • Chih-Yang Lin

    (Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi 621, Taiwan, R.O.C.)

  • Pei-Yu Lin

    (Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi 621, Taiwan, R.O.C.)

Abstract

Parallel association rules mining is a noticeable problem in data mining. However, little work has been proposed to deal with three important issues: (1) less memory usage; (2) less communication, among the involved computers, over the network; and (3) load balance among computers. In this paper, we present a graph-based scheme to solve the parallel mining problem by applyingindependent groups(clusters of maximal cliques). To bring the three issues to a close, the purpose of the independent groups aims at dividing a database into several independent sub-databases, so each sub-database can be employed independently to perform mining algorithms. To emphasis the effectiveness of the graph-based scheme, we adopt the independent groups not only for maximal large itemsets mining but also for general large itemsets mining. The experimental results show that our scheme can improve the efficiency for parallel mining when the independent groups are well-organized and designed.

Suggested Citation

  • Chin-Chen Chang & Chih-Yang Lin & Pei-Yu Lin, 2004. "An Efficient Graph-Based Method for Parallel Mining Problems," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 143-154.
    • Handle: RePEc:wsi:jikmxx:v:03:y:2004:i:02:n:s0219649204000778
    DOI: 10.1142/S0219649204000778
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