Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)

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Ontology-based natural language interface to public security population database

Authors
Xiangwu Ding1, Hao Liu1, *
1College of Computer Science and Technology, Donghua University, Shanghai 201620, Shanghai, China
*Corresponding author. Email: 870350571@qq.com
Corresponding Author
Hao Liu
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-102-9_38How to use a DOI?
Keywords
Ontology; Natural language interface to database; Public security population database
Abstract

Natural Language Interface to Database (NLIDB) could convert natural language queries into SQL automatically, which has been extensively studied. However, how to apply NLIDB to the public security population database (PSP-DB) remains an open problem due to the challenges to utilize domain knowledge and generate complex queries involving multiple tables. To tackle these problems, this paper proposes an ontology-based NLIDB approach combining with public security population ontology (PSP-Ontology) and syntactic analysis. Its key idea includes: (1) constructing an ontology from the schema of PSP-DB and extending it with synonym expansion; and (2) proposing an association path processing algorithm to handle multi-table connection path in SQL generation. We have evaluated the approach on the population database from Shanghai Public Security Bureau. The results show that the PSP-Ontology and association path processing algorithms could alleviate these two challenges and improve the accuracy of SQL translation effectively.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
29 December 2022
ISBN
10.2991/978-94-6463-102-9_38
ISSN
2589-4900
DOI
10.2991/978-94-6463-102-9_38How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Xiangwu Ding
AU  - Hao Liu
PY  - 2022
DA  - 2022/12/29
TI  - Ontology-based natural language interface to public security population database
BT  - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
PB  - Atlantis Press
SP  - 348
EP  - 365
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-102-9_38
DO  - 10.2991/978-94-6463-102-9_38
ID  - Ding2022
ER  -