Prism: A primal-encoding approach for frequent sequence mining. ICDM07
Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on • 2007
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.
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