A comparative evaluation of novelty detection algorithms for discrete sequences

The identification of anomalies in temporal data is a core component of numerous research areas such as intrusion detection, fault prevention, genomics and fraud detection. This article provides an experimental comparison of candidate methods for the novelty detection problem applied to discrete seq...

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Veröffentlicht in:	The Artificial intelligence review Jg. 53; H. 5; S. 3787 - 3812
Hauptverfasser:	Domingues, Rémi, Michiardi, Pietro, Barlet, Jérémie, Filippone, Maurizio
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.06.2020 Springer Springer Nature B.V
Schlagworte:	Algorithms Analysis Anomalies Artificial Intelligence Candidates Computer Science Datasets Embedded systems Experiments Fraud Fraud prevention Genomics Identification methods Intrusion Probability Reaction time Response time Selection criteria Sequences Temporal data Outlier detection Discrete sequences Fraud detection Novelty detection Anomaly detection
ISSN:	0269-2821, 1573-7462
Online-Zugang:	Volltext
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