Staff Members - Benha University
PRISM: A Prime-Encoding Approach for Frequent Sequence Mining
• 2007
Publication Information
Authors
Karam Gouda, Mosab Hassaan, and Mohammed J. Zaki†
Keywords
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Pages
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publication.type
International
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Supplementary Materials
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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 of 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.
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 of 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.