A fast algorithm for mining sequential patterns from large databases

被引：3
|
作者：
Chen, N [1 ]
Chen, A
Zhou, LX
Liu, L
机构：
[1] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
[2] Chinese Acad Sci, Inst Policy & Management, Beijing 100080, Peoples R China
来源：
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY | 2001年 / 16卷 / 04期
关键词：
data mining; knowledge discovery; sequential pattern; set operation;
D O I：
10.1007/BF02948984
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Mining sequential patterns from large databases has been recognized by many researchers as an attractive task of data mining and knowledge discovery. Previous algorithms scan the databases for many times, which is often unendurable due to the very large amount of databases. In this paper, the authors introduce an effective algorithm for mining sequential patterns from large databases. In the algorithm, the original database is not used at all for counting the support of sequences after the first pass. Rather, a tidlist; structure generated in the previous pass is employed for the purpose based on set intersection operations, avoiding the multiple scans of the databases.
引用
收藏
页码：359 / 370
页数：12
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