DocumentCode
3166273
Title
Prism: A Primal-Encoding Approach for Frequent Sequence Mining
Author
Gouda, Karam ; Hassaan, Mosab ; Zaki, Mohammed J.
Author_Institution
Fac. of Sci., Benha
fYear
2007
fDate
28-31 Oct. 2007
Firstpage
487
Lastpage
492
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.
Keywords
block codes; data mining; data mining; frequent sequence mining; prime block encoding; prime factorization theory; Bioinformatics; Computer science; Data mining; Databases; Economic indicators; Encoding; Itemsets; Mathematics; USA Councils; Unsolicited electronic mail;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on
Conference_Location
Omaha, NE
ISSN
1550-4786
Print_ISBN
978-0-7695-3018-5
Type
conf
DOI
10.1109/ICDM.2007.33
Filename
4470278
Link To Document