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IDA
2007
Springer
13 years 7 months ago
Anomaly detection in data represented as graphs
An important area of data mining is anomaly detection, particularly for fraud. However, little work has been done in terms of detecting anomalies in data that is represented as a g...
William Eberle, Lawrence B. Holder
ICDCS
2012
IEEE
11 years 10 months ago
Tiresias: Online Anomaly Detection for Hierarchical Operational Network Data
Operational network data, management data such as customer care call logs and equipment system logs, is a very important source of information for network operators to detect prob...
Chi-Yao Hong, Matthew Caesar, Nick G. Duffield, Ji...
ICDCS
2012
IEEE
11 years 10 months ago
PREPARE: Predictive Performance Anomaly Prevention for Virtualized Cloud Systems
Abstract—Virtualized cloud systems are prone to performance anomalies due to various reasons such as resource contentions, software bugs, and hardware failures. In this paper, we...
Yongmin Tan, Hiep Nguyen, Zhiming Shen, Xiaohui Gu...
USENIX
2007
13 years 10 months ago
Hyperion: High Volume Stream Archival for Retrospective Querying
Network monitoring systems that support data archival and after-the-fact (retrospective) queries are useful for a multitude of purposes, such as anomaly detection and network and ...
Peter Desnoyers, Prashant J. Shenoy
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
13 years 9 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi