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辅助任务增强的中文跨域NL2SQL算法

胡亚红 刘亚冬 朱正东 刘鹏杰

国防科技大学学报2024,Vol.46Issue(2):197-204,8.
国防科技大学学报2024,Vol.46Issue(2):197-204,8.DOI:10.11887/j.cn.202402020

辅助任务增强的中文跨域NL2SQL算法

Chinese cross-domain NL2SQL algorithm enhanced by auxiliary task

胡亚红 1刘亚冬 2朱正东 3刘鹏杰3

作者信息

  • 1. 浙江工业大学计算机科学与技术学院,浙江杭州 310023
  • 2. 西安交通大学软件学院,陕西西安 710049
  • 3. 西安交通大学计算机科学与技术学院,陕西西安 710049
  • 折叠

摘要

Abstract

NL2SQL(natural language to structured query language)task aims to translate natural language queries into SQL(structured query language)executable by the database.A Chinese cross-domain NL2SQL algorithm enhanced by auxiliary tasks was proposed.Core idea was to perform multi-task training and improve the accuracy of the model by adding auxiliary tasks in the decoder and combining the prototype model.Auxiliary task was designed by modeling the database schema into a graph,predicting the dependency relations between the natural language queries and the nodes in the database schema graph,and explicitly modeling the dependency relations between the natural language query and the database schema.Through the improvement of auxiliary tasks,the model can better identify which tables/columns in the database schema are more effective for predicting the target SQL for specific natural language queries.Experimental results on the Chinese NL2SQL dataset DuSQL show that the algorithm after adding auxiliary tasks has achieved better results than the prototype model,and can better handle cross-domain NL2SQL task.

关键词

人工智能/深度学习/自然语言处理/语义解析

Key words

artificial intelligence/deep learning/natural language processing/semantic parsing

分类

信息技术与安全科学

引用本文复制引用

胡亚红,刘亚冬,朱正东,刘鹏杰..辅助任务增强的中文跨域NL2SQL算法[J].国防科技大学学报,2024,46(2):197-204,8.

基金项目

国家重点研发计划资助项目(2018YFB0204003,2018YFB0204004) (2018YFB0204003,2018YFB0204004)

国防科技大学学报

OA北大核心CSTPCD

1001-2486

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