Detecting unregistered users through semi-supervised anomaly detection with similarity datasets
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource, 1 online resource.
- Sprache
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Englisch
- Erschienen in
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Detecting unregistered users through semi-supervised anomaly detection with similarity datasets ; volume:10 ; number:1 ; day:12 ; month:6 ; year:2023 ; pages:1-22 ; date:12.2023
Journal of Big Data ; 10, Heft 1 (12.6.2023), 1-22, 12.2023
- Urheber
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Heo, Dong Hyuk
Park, Sung Ho
Kang, Soon Ju
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
-
10.1186/s40537-023-00791-8
- URN
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urn:nbn:de:101:1-2023091913590824836501
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:54 MESZ
Datenpartner
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Beteiligte
- Heo, Dong Hyuk
- Park, Sung Ho
- Kang, Soon Ju
- SpringerLink (Online service)
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