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Prism: A primal-encoding approach for frequent sequence mining. ICDM07

Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on • 2007
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Publication Information
Authors Karam Gouda, Mosab Hassaan, Mohammed J Zaki
Keywords Not Available
Journal Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on
Publisher Not Available
Volume Not Available
Issue Not Available
Pages 487 - 492
publication.type International
Paper Link Open Link
Supplementary Materials Not Available
Abstract
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.