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DATAMINE
2008
219views more  DATAMINE 2008»
9 years 12 months ago
Correlating burst events on streaming stock market data
Abstract We address the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. We follow a two-step methodology: first we iden...
Michail Vlachos, Kun-Lung Wu, Shyh-Kwei Chen, Phil...
LWA
2008
10 years 1 months ago
Towards Burst Detection for Non-Stationary Stream Data
Detecting bursts in data streams is an important and challenging task, especially in stock market, traffic control or sensor network streams. Burst detection means the identificat...
Daniel Klan, Marcel Karnstedt, Christian Pöli...
PKDD
2005
Springer
159views Data Mining» more  PKDD 2005»
10 years 5 months ago
Fast Burst Correlation of Financial Data
We examine the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. Our methodology is comprised of two steps: a burst dete...
Michail Vlachos, Kun-Lung Wu, Shyh-Kwei Chen, Phil...
DASFAA
2005
IEEE
157views Database» more  DASFAA 2005»
10 years 5 months ago
Adaptively Detecting Aggregation Bursts in Data Streams
Finding bursts in data streams is attracting much attention in research community due to its broad applications. Existing burst detection methods suffer the problems that 1) the p...
Aoying Zhou, Shouke Qin, Weining Qian
SAC
2009
ACM
10 years 6 months ago
Adaptive burst detection in a stream engine
Detecting bursts in data streams is an important and challenging task. Due to the complexity of this task, usually burst detection cannot be formulated using standard query operat...
Marcel Karnstedt, Daniel Klan, Christian Pöli...
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