DocumentCode :
3160831
Title :
WSpCPs: Weighted sequential pattern mining based on cluster-pruning mechanism
Author :
Yu Fu ; Yanhua Yu ; Meina Song
Author_Institution :
PCN&CAD Center, Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2013
fDate :
26-28 Oct. 2013
Firstpage :
291
Lastpage :
294
Abstract :
One of the major important problems in sequential pattern mining is the explosion of the number of results. To solve this problem, a new algorithm, called weighted sequential pattern mining based on cluster-pruning strategy (WSpCPs), is proposed in this paper. The purpose of our algorithm is to select some high-quality sequences that describe the full result. It utilizes I-step and S-step operations to generate new sequences and their bitmaps in iterative process. WSpCPs proposes cluster-pruning strategy to select sequences from the full result. Experiments show that WSpCPs is an efficient method to reduce the number of result.
Keywords :
data mining; iterative methods; pattern clustering; I-step operations; S-step operations; WSpCPs; cluster-pruning mechanism; cluster-pruning strategy; high-quality sequences; iterative process; weighted sequential pattern mining; Algorithm design and analysis; Approximation algorithms; Clustering algorithms; Data mining; Itemsets; Vectors; cluster-pruning strategy; vertical bitmap; weighted sequential pattern mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Problem-solving (ICCP), 2013 International Conference on
Conference_Location :
Jiuzhai
Type :
conf
DOI :
10.1109/ICCPS.2013.6893508
Filename :
6893508
Link To Document :
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