| metadata.tuhh.publisher.uri: | https://aisel.aisnet.org/wi2024/27 | Title: | Evaluation of outlier detection methods for anomaly detection in journal entries : a use case analysis | Language: | English | Authors: | Schreier, Tobias Gnoss, Nicolai Tropmann-Frick, Marina  Schultz, Martin |
Other : | Association for Information Systems | Keywords: | Anomaly Detection; Comparative Analysis; Journal Entry Testing; Auditing; Autoencoder | Issue Date: | 2024 | Publisher: | AIS eLibrary | Part of Series: | Wirtschaftsinformatik 2024 : proceedings | Conference: | Internationale Tagung Wirtschaftsinformatik 2024 | URI: | https://hdl.handle.net/20.500.12738/19582 | Review status: | This version was peer reviewed (peer review) | Institute: | Department Informatik (ehemalig, aufgelöst 10.2025) Fakultät Technik und Informatik (ehemalig, aufgelöst 10.2025) |
Type: | Chapter/Article (Proceedings) |
| Appears in Collections: | Publications without full text |
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