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https://doi.org/10.21256/zhaw-22000| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | ValueNet : a natural language-to-SQL system that learns from database information |
| Autor/-in: | Brunner, Ursin Stockinger, Kurt |
| et. al: | No |
| DOI: | 10.21256/zhaw-22000 |
| Tagungsband: | Proceedings of the 37th ICDE |
| Angaben zur Konferenz: | International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021 |
| Erscheinungsdatum: | Apr-2021 |
| Verlag / Hrsg. Institution: | IEEE |
| Andere Identifier: | arXiv:2006.00888v2 |
| Sprache: | Englisch |
| Schlagwörter: | NL-to-SQL; Natural language interface; Neural network; Transformer |
| Fachgebiet (DDC): | 005: Computerprogrammierung, Programme und Daten |
| Zusammenfassung: | In this paper we propose ValueNet light and ValueNet - two end-to-end Natural Language-to-SQL systems that incorporate values using the challenging Spider dataset.The main idea of our approach is to use not only metadata information from the underlying database but also information on the base data as input for our neural network architecture. In particular, we propose a novel architecture sketch to extract values from a user question and come up with possible value candidates which are not explicitly mentioned in the question. We then use a neural model based on an encoder-decoder architecture to synthesize the SQL query. Finally, we evaluate our model on the Spider challenge using the Execution Accuracy metric, a more difficult metric than used by most participants of the challenge. Our experimental evaluation demonstrates that ValueNet light and ValueNet reach state-of-the-art results of 67% and 62% accuracy, respectively, for translating from NL to SQL whilst incorporating values. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/22000 |
| Volltext Version: | Aktualisierte Version |
| Lizenz (gemäss Verlagsvertrag): | Keine Angabe |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Angewandte Informationstechnologie (InIT) |
| Publiziert im Rahmen des ZHAW-Projekts: | INODE - Intelligent Open Data Exploration |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2021_Brunner-Stockinger_ValueNet_ICDE-Paper.pdf | 585.22 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Brunner, U., & Stockinger, K. (2021, April). ValueNet : a natural language-to-SQL system that learns from database information. Proceedings of the 37th ICDE. https://doi.org/10.21256/zhaw-22000
Brunner, U. and Stockinger, K. (2021) ‘ValueNet : a natural language-to-SQL system that learns from database information’, in Proceedings of the 37th ICDE. IEEE. Available at: https://doi.org/10.21256/zhaw-22000.
U. Brunner and K. Stockinger, “ValueNet : a natural language-to-SQL system that learns from database information,” in Proceedings of the 37th ICDE, Apr. 2021. doi: 10.21256/zhaw-22000.
BRUNNER, Ursin und Kurt STOCKINGER, 2021. ValueNet : a natural language-to-SQL system that learns from database information. In: Proceedings of the 37th ICDE. Conference paper. IEEE. April 2021
Brunner, Ursin, and Kurt Stockinger. 2021. “ValueNet : A Natural Language-to-SQL System That Learns from Database Information.” Conference paper. In Proceedings of the 37th ICDE. IEEE. https://doi.org/10.21256/zhaw-22000.
Brunner, Ursin, and Kurt Stockinger. “ValueNet : A Natural Language-to-SQL System That Learns from Database Information.” Proceedings of the 37th ICDE, IEEE, 2021, https://doi.org/10.21256/zhaw-22000.
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