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» Event Discovery in Time Series.
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DAWAK
1999
Springer
13 years 12 months ago
Mining Interval Time Series
Data mining can be used to extensively automate the data analysis process. Techniques for mining interval time series, however, have not been considered. Such time series are commo...
Roy Villafane, Kien A. Hua, Duc A. Tran, Basab Mau...
ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
14 years 2 months ago
Clustering Distributed Time Series in Sensor Networks
Event detection is a critical task in sensor networks, especially for environmental monitoring applications. Traditional solutions to event detection are based on analyzing one-sh...
Jie Yin, Mohamed Medhat Gaber
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 8 months ago
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...
WSDM
2012
ACM
325views Data Mining» more  WSDM 2012»
12 years 3 months ago
Correlating financial time series with micro-blogging activity
We study the problem of correlating micro-blogging activity with stock-market events, defined as changes in the price and traded volume of stocks. Specifically, we collect messa...
Eduardo J. Ruiz, Vagelis Hristidis, Carlos Castill...
ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
14 years 25 days ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel