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Anomaly Detection in Dynamic Networks using Multi-view Time..:

, In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management,

Teng, Xian ; Lin, Yu-Ru ; Wen, Xidao - p. 827-836 , 2017

Link: https://dl.acm.org/doi/10.1145/3132847.3132964

RT 
T1 <cTitle>Proceedings of the 2017 ACM on Conference on Information and Knowledge Management</cTitle>: T1 <Title>Anomaly Detection in Dynamic Networks using Multi-view Time-Series Hypersphere Learning</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3132964&Exemplar=1&LAN=DE
				
A1 Teng, Xian
A1 Lin, Yu-Ru
A1 Wen, Xidao
PB ACM
YR 2017
K1 anomaly detection
K1 dynamic networks
K1 multi-view learning
K1 time- series mining
K1 urban computing
K1 Information systems
K1 Data management systems
K1 Database design and models
K1 Graph-based database models
K1 Network data models
K1 Data model extensions
K1 Temporal data
K1 Information systems applications
K1 Decision support systems
K1 Data analytics
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Unsupervised learning
K1 Anomaly detection
K1 Data mining
K1 Data stream mining
K1 Spatial-temporal systems
K1 Geographic information systems
K1 World Wide Web
K1 Web applications
K1 Social networks
SP 827
OP 836
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3132847.3132964
DO https://dl.acm.org/doi/10.1145/3132847.3132964
SF ELIB - SuUB Bremen

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