DocumentCode :
615312
Title :
On the Sequential Pattern Mining Algorithm Based on Projection position
Author :
Taoshen Li ; Weina Wang ; Qingfeng Chen
Author_Institution :
Sch. of Comput., Electron. & Inf., Guangxi Univ., Nanning, China
fYear :
2013
fDate :
26-28 April 2013
Firstpage :
460
Lastpage :
463
Abstract :
In order to avoid huge amount of projected databases produced by Prefix Span algorithm and reduce unnecessary storage space and scanning time, an improved sequential pattern mining algorithm based on projection position is proposed. The idea of improved algorithm is as follows: (1) utilizing Apriori property to delete the non-frequent items and divide search space, which can reduce unnecessary storage space and scanning time; (2) recording projected position to locate projected sequence position for mining local frequency items and mine each recursively so as to avoid physically constructing corresponding projected databases. The experimental results show that proposed algorithm has better feasibility and scalability compared with other algorithms.
Keywords :
data mining; database management systems; storage management; apriori property; local frequency item mining; projected databases; projected sequence position location; projection position; scalability; scanning time reduction; search space; sequential pattern mining algorithm; unnecessary storage space reduction; Algorithm design and analysis; Computers; Proteins; PrefixSpan algorithm; project database; projection position; sequence database; squential pattern mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Education (ICCSE), 2013 8th International Conference on
Conference_Location :
Colombo
Print_ISBN :
978-1-4673-4464-7
Type :
conf
DOI :
10.1109/ICCSE.2013.6553955
Filename :
6553955
Link To Document :
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