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» Detecting Change in Data Streams
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DEXA
2009
Springer
88views Database» more  DEXA 2009»
13 years 11 months ago
Significance-Based Failure and Interference Detection in Data Streams
Detecting the failure of a data stream is relatively easy when the stream is continually full of data. The transfer of large amounts of data allows for the simple detection of inte...
Nickolas J. G. Falkner, Quan Z. Sheng
APWEB
2006
Springer
13 years 11 months ago
DSEC: A Data Stream Engine Based Clinical Information System
This demo paper describes a clinical information system: Data Stream Engine based Clinical information system (DSEC). In DSEC, data stream technology as well as traditional compute...
Yu Fan, Hongyan Li, Zijing Hu, Jianlong Gao, Haibi...
SIGMOD
2007
ACM
195views Database» more  SIGMOD 2007»
14 years 7 months ago
Effective variation management for pseudo periodical streams
Many database applications require the analysis and processing of data streams. In such systems, huge amounts of data arrive rapidly and their values change over time. The variati...
Lv-an Tang, Bin Cui, Hongyan Li, Gaoshan Miao, Don...
SIGKDD
2008
113views more  SIGKDD 2008»
13 years 7 months ago
On exploiting the power of time in data mining
We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental m...
Mirko Böttcher, Frank Höppner, Myra Spil...
DASFAA
2005
IEEE
157views Database» more  DASFAA 2005»
14 years 1 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