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Subset Node Anomaly Tracking over Large Dynamic Graphs:

, In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Guo, Xingzhi ; Zhou, Baojian ; Skiena, Steven - p. 475-485 , 2022

Link: https://dl.acm.org/doi/10.1145/3534678.3539389

Subset Node Anomaly Tracking over Large Dynamic Graphs:

, In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Guo, Xingzhi ; Zhou, Baojian ; Skiena, Steven - p. 475-485 , 2022

Link: https://dl.acm.org/doi/10.1145/3534678.3539389

RT 
T1 <cTitle>Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Subset Node Anomaly Tracking over Large Dynamic Graphs</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3539389&Exemplar=1&LAN=DE
				
A1 Guo, Xingzhi
A1 Zhou, Baojian
A1 Skiena, Steven
PB ACM
YR 2022
K1 anomaly detection
K1 dynamic graph
K1 personalized pagerank
K1 Information systems
K1 Information systems applications
K1 Data mining
K1 Data stream mining
K1 Computing methodologies
SP 475
OP 485
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3534678.3539389
DO https://dl.acm.org/doi/10.1145/3534678.3539389
SF ELIB - SuUB Bremen

RT 
T1 <cTitle>Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Subset Node Anomaly Tracking over Large Dynamic Graphs</Title>

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