Text Anomaly Detection
Text Anomaly Detection is a computational methodology within anomaly detection that specifically identifies deviations from expected patterns in textual data by leveraging linguistic, statistical, or semantic features unique to natural language.
216
Publications
9.7K
Citations
761
Authors
301
Institutions
Publications per year
2017–2026
123
Parents
216
Text analysis and knowledge mining system
Tetsuya Nasukawa, Tohru Nagano · IBM Systems Journal · 2001 · 218 citations
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Carnegie Mellon University
Pittsburgh, United States
7 h-index
15 publications
776 citations

Beihang University
Beijing, China
6 h-index
22 publications
1.3K citations

Chinese Academy of Sciences
Beijing, China
4 h-index
10 publications
287 citations
University of California, Berkeley
Berkeley, United States
3 h-index
4 publications
137 citations
Institute of Software
Beijing, China
3 h-index
15 publications
807 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
11 publications
759 citations
Georgia Institute of Technology
Atlanta, United States
3 h-index
11 publications
1.6K citations

Concordia University
Montreal, Canada
3 h-index
5 publications
461 citations
1–8 of 301
Repository · 13 publications · 413 citations
11
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4 publications · 311 citations
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3 publications · 195 citations
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TKDE · 3 publications · 143 citations
3
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4 publications · 168 citations
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