Contextual Outlier Detection
Contextual Outlier Detection is an outlier detection paradigm that identifies anomalies based on their deviation from the expected behavior within a specific context, as defined by contextual attributes, distinguishing it from global or collective outlier detection methods by incorporating situational dependency in the definition of normality.
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2.3K
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178
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86
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2017–2026
28
Variants
Context-dependent Outlier Detection
Parents
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Contextual anomaly detection framework for big sensor data
Miriam A. M. Capretz · Journal Of Big Data · 2015 · 141 citations · Full text
Advancements of Outlier Detection: A Survey
Ji Zhang · ICST Transactions on Scalable Information Systems · 2013 · 139 citations · Full text
Computing, Data Science, Data Mining +12
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Texas A&M University
College Station, United States
3 h-index
9 publications
273 citations
Auburn University
Auburn, United States
3 h-index
3 publications
76 citations
Taiyuan University of Science and Technology
Taiyuan, China
3 h-index
13 publications
341 citations

University of Alberta
Edmonton, Canada
2 h-index
3 publications
444 citations
The Ohio State University
Columbus, United States
2 h-index
4 publications
84 citations
Wright State University
Dayton, United States
2 h-index
2 publications
55 citations

Western University
London, Canada
2 h-index
4 publications
392 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
2 h-index
5 publications
100 citations
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2 publications · 315 citations
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Repository · 2 publications · 23 citations
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TIST · 2 publications · 27 citations
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JSAN · 1 publications · 84 citations
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1 publications · 14 citations
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