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https://doi.org/10.21256/zhaw-22738| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Bio-SODA : enabling natural language question answering over knowledge graphs without training data |
| Autor/-in: | Sima, Ana Claudia Mendes de Farias, Tarcisio Anisimova, Maria Dessimoz, Christophe Robinson-Rechavi, Marc Zbinden, Erich Stockinger, Kurt |
| et. al: | No |
| DOI: | 10.1145/3468791.3469119 10.21256/zhaw-22738 |
| Tagungsband: | Proceedings of the 33rd SSDBM |
| Seite(n): | 61 |
| Seiten bis: | 72 |
| Angaben zur Konferenz: | International Conference on Scientific and Statistical Database Management (SSDBM), Online, 6-7 July 2021 |
| Erscheinungsdatum: | Jul-2021 |
| Verlag / Hrsg. Institution: | Association for Computing Machinery |
| Andere Identifier: | arXiv:2104.13744v4 |
| Sprache: | Englisch |
| Schlagwörter: | Database; Question answering; Graph database; Unsupervised machine learning; Natural language processing |
| Fachgebiet (DDC): | 005: Computerprogrammierung, Programme und Daten 006: Spezielle Computerverfahren |
| Zusammenfassung: | The problem of natural language processing over structured data has become a growing research field, both within the relational database and the Semantic Web community, with significant efforts involved in question answering over knowledge graphs (KGQA). However, many of these approaches are either specifically targeted at open-domain question answering using DBpedia, or require large training datasets to translate a natural language question to SPARQL in order to query the knowledge graph. Hence, these approaches often cannot be applied directly to complex scientific datasets where no prior training data is available. In this paper, we focus on the challenges of natural language processing over knowledge graphs of scientific datasets. In particular, we introduce Bio-SODA, a natural language processing engine that does not require training data in the form of question-answer pairs for generating SPARQL queries. Bio-SODA uses a generic graph-based approach for translating user questions to a ranked list of SPARQL candidate queries. Furthermore, Bio-SODA uses a novel ranking algorithm that includes node centrality as a measure of relevance for selecting the best SPARQL candidate query. Our experiments with real-world datasets across several scientific domains, including the official bioinformatics Question Answering over Linked Data (QALD) challenge, show that Bio-SODA outperforms publicly available KGQA systems by an F1-score of least 20% and by an even higher factor on more complex bioinformatics datasets. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/22738 |
| Volltext Version: | Akzeptierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | Life Sciences und Facility Management School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) Institut für Computational Life Sciences (ICLS) |
| Publiziert im Rahmen des ZHAW-Projekts: | Bio-SODA – Enabling Complex, Semantic Queries to Bioinformatics Databases through Intuitive Searching over Data (SNSF NRP 75 "Big Data") |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2021_Sima-etal_BioSODA_SSDBM.pdf | Accepted Version | 544.45 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Sima, A. C., Mendes de Farias, T., Anisimova, M., Dessimoz, C., Robinson-Rechavi, M., Zbinden, E., & Stockinger, K. (2021). Bio-SODA : enabling natural language question answering over knowledge graphs without training data [Conference paper]. Proceedings of the 33rd SSDBM, 61–72. https://doi.org/10.1145/3468791.3469119
Sima, A.C. et al. (2021) ‘Bio-SODA : enabling natural language question answering over knowledge graphs without training data’, in Proceedings of the 33rd SSDBM. Association for Computing Machinery, pp. 61–72. Available at: https://doi.org/10.1145/3468791.3469119.
A. C. Sima et al., “Bio-SODA : enabling natural language question answering over knowledge graphs without training data,” in Proceedings of the 33rd SSDBM, Jul. 2021, pp. 61–72. doi: 10.1145/3468791.3469119.
SIMA, Ana Claudia, Tarcisio MENDES DE FARIAS, Maria ANISIMOVA, Christophe DESSIMOZ, Marc ROBINSON-RECHAVI, Erich ZBINDEN und Kurt STOCKINGER, 2021. Bio-SODA : enabling natural language question answering over knowledge graphs without training data. In: Proceedings of the 33rd SSDBM. Conference paper. Association for Computing Machinery. Juli 2021. S. 61–72
Sima, Ana Claudia, Tarcisio Mendes de Farias, Maria Anisimova, Christophe Dessimoz, Marc Robinson-Rechavi, Erich Zbinden, and Kurt Stockinger. 2021. “Bio-SODA : Enabling Natural Language Question Answering over Knowledge Graphs without Training Data.” Conference paper. In Proceedings of the 33rd SSDBM, 61–72. Association for Computing Machinery. https://doi.org/10.1145/3468791.3469119.
Sima, Ana Claudia, et al. “Bio-SODA : Enabling Natural Language Question Answering over Knowledge Graphs without Training Data.” Proceedings of the 33rd SSDBM, Association for Computing Machinery, 2021, pp. 61–72, https://doi.org/10.1145/3468791.3469119.
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