A moving-window based partial periodic patterns update technology in time series databases

被引：3
|
作者：
Wang, Xiaoye [1 ]
Zhang, Hua [1 ]
Zhang, Degan [1 ]
Xiao, Yingyuan [1 ]
机构：
[1] Tianjin Univ Technol, Sch Comp Sci & Technol, Tianjin 300191, Peoples R China
来源：
PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 2 | 2008年
关键词：
D O I：
10.1109/ISCID.2008.140
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the actual using, the data distribution of time series maybe changed with time. This dynamic behavior will led to the find pattern can't be successful for the new data. Therefore, we present a partial periodic patterns update technology in time series databases based on the moving-window. The algorithm mines the patterns on the resent data in the moving-window, which only need to scan the data set in the moving-window two times mostly. The experiment results show that the new algorithm has more efficient than the nonmoving-window versions for the large databases.
引用
收藏
页码：98 / 101
页数：4
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