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1 Ergebnisse
1
Runtime Anomaly Detection Method in Smart Factories using M..:
, In:
Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems
,
Choi, Joong-Hyun
;
Lee, Kang-Woo
;
Jung, Hyungkun
. - p. 304-309 , 2017
Link:
https://dl.acm.org/doi/10.1145/3093742.3095104
RT T1 <cTitle>Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems</cTitle>: T1 <Title>Runtime Anomaly Detection Method in Smart Factories using Machine Learning on RDF Event Streams : Grand Challenge</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3095104&Exemplar=1&LAN=DE A1 Choi, Joong-Hyun A1 Lee, Kang-Woo A1 Jung, Hyungkun A1 Cho, Eun-Sun PB ACM YR 2017 K1 Anomaly detection K1 Markov chain K1 RDF data stream processing K1 k-means clustering K1 Information systems K1 Information systems applications K1 Data mining K1 Data stream mining K1 Clustering K1 World Wide Web K1 Web data description languages K1 Semantic web description languages K1 Resource Description Framework (RDF) SP 304 OP 309 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3093742.3095104 DO https://dl.acm.org/doi/10.1145/3093742.3095104 SF ELIB - SuUB Bremen
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