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DATAMINE
2008
219views more  DATAMINE 2008»
13 years 7 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...
TON
2008
106views more  TON 2008»
13 years 7 months ago
Statistical techniques for detecting traffic anomalies through packet header data
This paper proposes a traffic anomaly detector, operated in postmortem and in real-time, by passively monitoring packet headers of traffic. The frequent attacks on network infrastr...
Seong Soo Kim, A. L. Narasimha Reddy
ICDM
2007
IEEE
199views Data Mining» more  ICDM 2007»
14 years 1 months ago
Discovering Structural Anomalies in Graph-Based Data
The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
William Eberle, Lawrence B. Holder
ANLP
2000
92views more  ANLP 2000»
13 years 9 months ago
Detecting Errors within a Corpus using Anomaly Detection
We present a method for automatically detecting errors in a manually marked corpus using anomaly detection. Anomaly detection is a method for determining which elements of a large...
Eleazar Eskin
NIPS
2004
13 years 9 months ago
Active Learning for Anomaly and Rare-Category Detection
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Dan Pelleg, Andrew W. Moore