Generating Large Items Efficiently For Mining Quantitative Association Rules 


Vol. 6,  No. 10, pp. 2597-2607, Oct.  1999
10.3745/KIPSTE.1999.6.10.2597


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  Abstract

In this paper, we propose an efficient large item generation algorithm that overcomes the problem of the existing algorithm for making large items from quantitative attributes. The proposed algorithm splits dataset into variable size of intervals by min_split_support and merges the intervals according to the support of each interval. It reflects characteristic of data to generated large items and can generate finer large items than the existing algorithm. It is shown through the performance evaluation that our proposed algorithm outperforms the existing algorithm.

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[IEEE Style]

c. Y. Hee, J. S. Min, Y. J. Soo, O. J. Chul, "Generating Large Items Efficiently For Mining Quantitative Association Rules," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 6, no. 10, pp. 2597-2607, 1999. DOI: 10.3745/KIPSTE.1999.6.10.2597.

[ACM Style]

choi Young Hee, Jang Su Min, Yoo Jae Soo, and Oh Jae Chul. 1999. Generating Large Items Efficiently For Mining Quantitative Association Rules. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 6, 10, (1999), 2597-2607. DOI: 10.3745/KIPSTE.1999.6.10.2597.

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