Please use this identifier to cite or link to this item:
|Publication type:||Conference paper|
|Type of review:||Peer review (publication)|
|Title:||Detecting errors in databases with bidirectional recurrent neural networks|
|Proceedings:||Proceedings of EDBT 2022|
|Conference details:||25th International Conference on Extending Database Technology, Edinburgh (online), 29 March - 1 April 2022|
|Publisher / Ed. Institution:||OpenProceedings|
|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.|
|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:
|2022_Holzer-Stockinger_Error-Dectection_EDBT.pdf||Accepted Version||321.86 kB||Adobe PDF|
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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, 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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