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 :
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