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Prof. karam gouda :: Publications:

Prism: A primal-encoding approach for frequent sequence mining. ICDM07
Authors: Karam Gouda, Mosab Hassaan, Mohammed J Zaki
Year: 2007
Keywords: Not Available
Journal: Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on
Volume: Not Available
Issue: Not Available
Pages: 487 - 492
Publisher: Not Available
Local/International: International
Paper Link:
Full paper karam gouda_Mosab abd el-hameed mohamed hassaan_ICDM07-prism.pdf
Supplementary materials Not Available

Sequence mining is one of the fundamental data mining tasks. In this paper we present a novel approach called Prism, for mining frequent sequences. Prism utilizes a vertical approach for enumeration and support counting, based on the novel notion o/prime block encoding, which in turn is based on prime factorization theory. Via an extensive evaluation on both synthetic and real datasets, we show that Prism outperforms popular sequence mining methods like SPADE [10], PrefixSpan [6] and SPAM [2], by an order of magnitude or more.

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