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Database Systems for Advanced Applications, International Conference on (2003)
Kyoto, Japan
Mar. 26, 2003 to Mar. 28, 2003
ISBN: 0-7695-1895-8
pp: 65
Guimei Liu , The Hong Kong Univ. of Science & Technology
Hongjun Lu , The Hong Kong Univ. of Science & Technology
Yabo Xu , The Chinese University of Hong Kong
Jeffrey Xu Yu , The Chinese University of Hong Kong
ABSTRACT
Mining frequent patterns is a fundamental and important problem in many data mining applications. Many of the algorithms adopt the pattern growth approach, which is shown to be superior to the candidate generate-and- test approach significantly. In this paper, we identify the key factor that influence the performance of the pattern growth approach, and optimize them to further improve the performance. Our algorithm uses a simple while compact data structure-ascending frequency ordered prefix-tree(AFOPT) to organize the conditional databases, in which we use arrays to store single branches to further save space. We traverse our prefix-tree structure using a top- down strategy. Our experiment results show that the combination of the top-down traversal strategy and the ascending frequency item ordering method achieves significant performance improvement over previous works.
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CITATION

G. Liu, H. Lu, J. X. Yu and Y. Xu, "Ascending Frequency Ordered Prefix-tree: Efficient Mining of Frequent Patterns," Database Systems for Advanced Applications, International Conference on(DASFAA), Kyoto, Japan, 2003, pp. 65.
doi:10.1109/DASFAA.2003.1192369
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