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» Unsupervised Outlier Detection in Time Series Data
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CSDA
2010
124views more  CSDA 2010»
13 years 8 months ago
Statistical inference on attributed random graphs: Fusion of graph features and content
Abstract: Fusion of information from graph features and content can provide superior inference for an anomaly detection task, compared to the corresponding content-only or graph fe...
John Grothendieck, Carey E. Priebe, Allen L. Gorin
DATAMINE
2008
219views more  DATAMINE 2008»
13 years 8 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...
IDEAS
2008
IEEE
256views Database» more  IDEAS 2008»
14 years 2 months ago
WIDS: a sensor-based online mining wireless intrusion detection system
This paper proposes WIDS, a wireless intrusion detection system, which applies data mining clustering technique to wireless network data captured through hardware sensors for purp...
Christie I. Ezeife, Maxwell Ejelike, Akshai K. Agg...
CINQ
2004
Springer
180views Database» more  CINQ 2004»
14 years 5 days ago
Interactivity, Scalability and Resource Control for Efficient KDD Support in DBMS
The conflict between resource consumption and query performance in the data mining context often has no satisfactory solution. This not only stands in sharp contrast to the need of...
Matthias Gimbel, Michael Klein, Peter C. Lockemann
WSDM
2012
ACM
245views Data Mining» more  WSDM 2012»
12 years 4 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