Year: 2025
Type: article
Abstract: Intelligent question answering over industrial databases is a challenging task due to the multicolumn context and complex questions. The existing methods need to be improved in terms of SQL generation accuracy. In this paper, we propose a question‐aware few‐shot Text‐to‐SQL approach based on the SDCUP pretrained model. Specifically, an attention‐based filtering approach is proposed to reduce the redundant information from multiple columns in the industrial database scenario. We further propose an operator semantics enhancement method to improve the ability of identifying complex conditions in queries. Experimental results on the industrial benchmarks in the fields of electric energy and structural inspection show that the proposed model outperforms the baseline models across all few‐shot settings.
DOI: 10.1155/int/8124797
Authors: Ren Li, Yu Chen, Hongyi Zhang, Jianxi Yang, Qiao Xiao, Shixin Jiang
Institution: Chongqing Jiaotong University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,700
OpenAlex ID: W4408961528