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SDM
2009
SIAM
291views Data Mining» more  SDM 2009»
14 years 2 months ago
Detection and Characterization of Anomalies in Multivariate Time Series.
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
ADBIS
2006
Springer
200views Database» more  ADBIS 2006»
13 years 11 months ago
Anomaly Detection Using Unsupervised Profiling Method in Time Series Data
The anomaly detection problem has important applications in the field of fraud detection, network robustness analysis and intrusion detection. This paper is concerned with the prob...
Zakia Ferdousi, Akira Maeda
AIME
2007
Springer
13 years 11 months ago
A Human-Machine Cooperative Approach for Time Series Data Interpretation
Abstract. This paper deals with the interpretation of biomedical multivariate time series for extracting typical scenarios. This task is known to be difficult, due to the temporal ...
Thomas Guyet, Catherine Garbay, Michel Dojat
ICDM
2007
IEEE
196views Data Mining» more  ICDM 2007»
13 years 11 months ago
Diagnosing Similarity of Oscillation Trends in Time Series
Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically addresses...
Leonardo E. Mariote, Claudia Bauzer Medeiros, Rica...
ADMA
2006
Springer
112views Data Mining» more  ADMA 2006»
13 years 11 months ago
Finding Time Series Discords Based on Haar Transform
The problem of finding anomaly has received much attention recently. However, most of the anomaly detection algorithms depend on an explicit definition of anomaly, which may be i...
Ada Wai-Chee Fu, Oscar Tat-Wing Leung, Eamonn J. K...