Automated Query Generation
Automated Query Generation is a computational method that systematically produces database or information retrieval queries from structured or unstructured inputs without requiring manual formulation by users.
364
Publications
18.1K
Citations
1K
Authors
332
Institutions
Publications per year
2017–2026
157
Variants
Aqg
Parents
364
Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation
Jiaqi Guo, Zecheng Zhan, Yan Gao et al. · 2019 · 384 citations · Full text
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332
University of Washington
Seattle, United States
11 h-index
26 publications
2.3K citations

Cornell University
Ithaca, United States
7 h-index
12 publications
524 citations
Tsinghua University
Beijing, China
7 h-index
14 publications
606 citations
National University of Singapore
Singapore, Singapore
7 h-index
19 publications
1.7K citations
Fudan University
Shanghai, China
6 h-index
11 publications
417 citations
AT&T (United States)
Bedminster, United States
6 h-index
8 publications
327 citations
University of Oxford
Oxford, United Kingdom
6 h-index
15 publications
323 citations
Microsoft (United States)
Redmond, United States
6 h-index
15 publications
4.2K citations
1–8 of 332
Repository · 23 publications · 1.7K citations
17
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PVLDB · 22 publications · 1.2K citations
17
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TKDE · 8 publications · 276 citations
10
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4 publications · 162 citations
6
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4 publications · 86 citations
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