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