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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
العودة
معلومات البحث
المؤلفون Karam Gouda, Mosab Hassaan, Mohammed J Zaki
الكلمات المفتاحية Not Available
المجلة العلمية Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on
الناشر Not Available
المجلد Not Available
العدد Not Available
الصفحات 487 - 492
publication.type International
رابط البحث Open Link
المواد المرفقة Not Available
الملخص
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.