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» Fast algorithms for time series mining
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KDD
2009
ACM
181views Data Mining» more  KDD 2009»
15 years 4 months ago
An exploration of climate data using complex networks
To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
63
Voted
KDD
2009
ACM
172views Data Mining» more  KDD 2009»
15 years 2 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
110
Voted
WSDM
2012
ACM
245views Data Mining» more  WSDM 2012»
13 years 5 months ago
The early bird gets the buzz: detecting anomalies and emerging trends in information networks
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
Brian Thompson
SIGMOD
2004
ACM
209views Database» more  SIGMOD 2004»
15 years 10 months ago
MAIDS: Mining Alarming Incidents from Data Streams
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
MICCAI
2003
Springer
15 years 11 months ago
Exploratory Identification of Cardiac Noise in fMRI Images
A fast exploratory framework for extracting cardiac noise signals contained in rest-case fMRI images is presented. Highly autocorrelated, independent components of the input time ...
Lilla Zöllei, Lawrence P. Panych, W. Eric L. ...