摘要
针对嵌套查询中SQL语法结构难以构建的问题,提出结合关系分类与修正的GSC-RCC方法,以3类实体间关系表示SQL语法。首先设计关系分类深度模型,并引入列名常用词提升模型性能,用以确定语句中每个实体对所属不同关系的概率,以此生成无修正无向图;然后设计基于SQL语法的关系修正算法,对无向图进行修正,以此构建SQL语法结构。在房产数据查询任务中,GSC-RCC对多条件含嵌套复杂查询的语法结构生成准确率为92.25%,且可减轻模型对语句样本数的依赖。
Aiming at the problem that the SQL grammar structure in nested query is difficult to construct,the GSC-RCC method combining relation classification and modification is proposed,and the SQL grammar is represented by three types of entity relationships.Firstly,the relational classification depth model is designed,and the column name common words are introduced to improve the performance of the model,so as to determine the probability of different relations of each entity pair in the statement,and then generate unmodified undirected graph.Then the relationship correction algorithm based on SQL grammar is designed to modify the undirected graph and finally construct the SQL grammar structure.In the real estate data query task,for multi-conditional query statements with nested conditions,the grammar structure generation accuracy of GSC-RCC method is 92.25%,and the method can reduce the dependence of the model on the number of statement sample.
作者
万文军
窦全胜
崔盼盼
张斌
唐焕玲
WAN Wen-jun;DOU Quan-sheng;CUI Pan-pan;ZHANG Bin;TANG Huan-ling(School of Computer Science and Technology,Shandong Technology and Business University,Yantai,Shandong 264000,China;Co-innovation Center of Shandong Colleges and Universities:Future Intelligent Computing,Yantai,Shandong 264000,China)
出处
《计算机科学》
CSCD
北大核心
2020年第S02期562-569,共8页
Computer Science
基金
国家自然科学基金(61976125,61976124,61772319,61773244)
高校科技计划项目(J18KA340,J18KA385)。
关键词
NL2SQL
SQL语法结构
关系分类
关系修正
深度学习
NL2SQL
SQL grammar structure
Relationship classification
Relationship correction
Deep learning
