Point Anomaly Detection
Point Anomaly Detection is a type of anomaly detection task in time series analysis that identifies individual data points deviating significantly from the normal pattern of the surrounding data, distinguished by the isolation of anomalous instances at the level of single observations rather than sequences or patterns.
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1.5K
Citations
144
Authors
63
Institutions
Publications per year
2017–2026
34
Variants
Point-based Anomaly Detection
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John Paparrizos, Paul Boniol, Themis Palpanas et al. · Proceedings of the VLDB Endowment · 2022 · 111 citations
Group Anomaly Detection using Flexible Genre Models
Liang Xiong, Barnabás Póczos, Jeff Schneider · Figshare · 2018 · 86 citations · Full text
Contextual Anomaly Detection in Big Sensor Data
Miriam A. M. Capretz · 2014 · 84 citations
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Carnegie Mellon University
Pittsburgh, United States
4 h-index
12 publications
558 citations
University of Washington
Seattle, United States
2 h-index
2 publications
90 citations
Lancaster University
Lancaster, United Kingdom
2 h-index
6 publications
96 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
2 h-index
3 publications
56 citations

Shandong Normal University
Jinan, China
2 h-index
6 publications
106 citations

University of Leeds
Leeds, United Kingdom
1 h-index
2 publications
56 citations
China XD Group (China)
Xi'an, China
1 h-index
1 publications
12 citations
Seattle University
Seattle, United States
1 h-index
1 publications
77 citations
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Repository · 4 publications · 79 citations
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1 publications · 37 citations
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Repository · 2 publications · 99 citations
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1 publications · 23 citations
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Conference · 1 publications · 38 citations
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