Improving Text-to-SQL with a Hybrid Decoding Method Article Swipe
Geunyeong Jeong
,
Mirae Han
,
Seulgi Kim
,
Yejin Lee
,
Joosang Lee
,
Seongsik Park
,
Harksoo Kim
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/e25030513
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/e25030513
Text-to-SQL is a task that converts natural language questions into SQL queries. Recent text-to-SQL models employ two decoding methods: sketch-based and generation-based, but each has its own shortcomings. The sketch-based method has limitations in performance as it does not reflect the relevance between SQL elements, while the generation-based method may increase inference time and cause syntactic errors. Therefore, we propose a novel decoding method, Hybrid decoder, which combines both methods. This reflects inter-SQL element information and defines elements that can be generated, enabling the generation of syntactically accurate SQL queries. Additionally, we introduce a Value prediction module for predicting values in the WHERE clause. It simplifies the decoding process and reduces the size of vocabulary by predicting values at once, regardless of the number of conditions. The results of evaluating the significance of Hybrid decoder indicate that it improves performance by effectively incorporating mutual information among SQL elements, compared to the sketch-based method. It also efficiently generates SQL queries by simplifying the decoding process in the generation-based method. In addition, we design a new evaluation measure to evaluate if it generates syntactically correct SQL queries. The result demonstrates that the proposed model generates syntactically accurate SQL queries.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/e25030513
- https://www.mdpi.com/1099-4300/25/3/513/pdf?version=1678971011
- OA Status
- gold
- Cited By
- 6
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4327731261
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4327731261Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/e25030513Digital Object Identifier
- Title
-
Improving Text-to-SQL with a Hybrid Decoding MethodWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-16Full publication date if available
- Authors
-
Geunyeong Jeong, Mirae Han, Seulgi Kim, Yejin Lee, Joosang Lee, Seongsik Park, Harksoo KimList of authors in order
- Landing page
-
https://doi.org/10.3390/e25030513Publisher landing page
- PDF URL
-
https://www.mdpi.com/1099-4300/25/3/513/pdf?version=1678971011Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1099-4300/25/3/513/pdf?version=1678971011Direct OA link when available
- Concepts
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Computer science, SQL, Sketch, Decoding methods, Stored procedure, Data definition language, Null (SQL), Query by Example, Artificial intelligence, Programming language, Natural language processing, Data mining, Information retrieval, Algorithm, Search engine, Web search queryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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26Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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