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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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Fumin Zou, Yue Xing, Qiang Ren, Feng Guo, Zhaoyi Zhou and Zihan Ye
With the wide application of Electronic Toll Collection (ETC) systems, the effectiveness of the operation and maintenance of gantry equipment still need to be improved. This paper proposes a dynamic anomaly detection method for gantry transactions, utili...
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Hedia Zardi, Hanen Karamti, Walid Karamti and Norah Saleh Alghamdi
Anomaly detection in online social networks (OSNs) is an important data mining task that aims to detect unexpected and suspicious users. To enhance anomaly exploration, anomaly ranking is used to assess the degree of user anomaly rather than applying bin...
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Matthias Steidel, Jan Mentjes and Axel Hahn
Research in the field of maritime anomaly detection and vessel behavior prediction primarily focuses on developing methods for extracting typical vessel movement patterns from historical traffic data. However, contextual information is currently not cons...
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