Double Wedgie: Efficient Filtering Algorithm for Streaming Time Series

被引:0
|
作者
Liu, Junling [1 ]
Liu, Jiangxiu [2 ]
Sun, Huanliang [2 ]
机构
[1] Shenyang Jianzhu Univ, Ctr Comp, Shenyang 110168, Peoples R China
[2] Shenyang Jianzhu Univ, Sch Informat & Control Engn, Shenyang 110168, Peoples R China
来源
FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 5, PROCEEDINGS | 2008年
基金
中国国家自然科学基金;
关键词
D O I
10.1109/FSKD.2008.247
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Filtering streaming time series can benefit monitoring a streaming time series for predefined patterns. Based on the Atomic Wedgie algorithm, we propose a new concept named Double Wedgie and define a tighter lower bound distance on it. The filtering algorithm based on Double Wedgie is more efficient than Atomic Wedgie. Extensive experiments demonstrate that the new algorithm can achieve tremendous improvements in the streaming time series query filtering with guaranteed no false dismissal. Also, the larger difference between the predefined patterns is, the more efficient the algorithm is.
引用
收藏
页码:335 / +
页数:2
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