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https://doi.org/10.21256/zhaw-24615| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | Detecting errors in databases with bidirectional recurrent neural networks |
| Authors: | Holzer, Severin Stockinger, Kurt |
| et. al: | No |
| DOI: | 10.48786/edbt.2022.22 10.21256/zhaw-24615 |
| Proceedings: | Proceedings of EDBT 2022 |
| Page(s): | 364 |
| Pages to: | 367 |
| Conference details: | 25th International Conference on Extending Database Technology, Edinburgh (online), 29 March - 1 April 2022 |
| Issue Date: | Mar-2022 |
| Publisher / Ed. Institution: | OpenProceedings |
| ISBN: | 978-3-89318-086-8 |
| Language: | English |
| Subjects: | Error detection; Database; Neural network |
| Subject (DDC): | 006: Special computer methods |
| Abstract: | In this paper we introduce an architecture based on bidirectional recurrent neural networks to detect errors in databases. The experimental results with 6 different datasets demonstrate that our approach outperforms state-of-the-art error detection systems when considering the average of the F1-scores over all datasets. Moreover, our approach achieves a lower standard deviation than existing work, which shows that our system is more robust. Finally, our approach does not require additional data augmentation techniques to achieve high F1-scores. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/24615 |
| Fulltext version: | Accepted version |
| License (according to publishing contract): | CC BY-NC-ND 4.0: Attribution - Non commercial - No derivatives 4.0 International |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Applied Information Technology (InIT) |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2022_Holzer-Stockinger_Error-Dectection_EDBT.pdf | Accepted Version | 321.86 kB | Adobe PDF |  View/Open |
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Holzer, S., & Stockinger, K. (2022). Detecting errors in databases with bidirectional recurrent neural networks [Conference paper]. Proceedings of EDBT 2022, 364–367. https://doi.org/10.48786/edbt.2022.22
Holzer, S. and Stockinger, K. (2022) ‘Detecting errors in databases with bidirectional recurrent neural networks’, in Proceedings of EDBT 2022. OpenProceedings, pp. 364–367. Available at: https://doi.org/10.48786/edbt.2022.22.
S. Holzer and K. Stockinger, “Detecting errors in databases with bidirectional recurrent neural networks,” in Proceedings of EDBT 2022, Mar. 2022, pp. 364–367. doi: 10.48786/edbt.2022.22.
HOLZER, Severin und Kurt STOCKINGER, 2022. Detecting errors in databases with bidirectional recurrent neural networks. In: Proceedings of EDBT 2022. Conference paper. OpenProceedings. März 2022. S. 364–367. ISBN 978-3-89318-086-8
Holzer, Severin, and Kurt Stockinger. 2022. “Detecting Errors in Databases with Bidirectional Recurrent Neural Networks.” Conference paper. In Proceedings of EDBT 2022, 364–67. OpenProceedings. https://doi.org/10.48786/edbt.2022.22.
Holzer, Severin, and Kurt Stockinger. “Detecting Errors in Databases with Bidirectional Recurrent Neural Networks.” Proceedings of EDBT 2022, OpenProceedings, 2022, pp. 364–67, https://doi.org/10.48786/edbt.2022.22.
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