Synthesis of SQL Queries from Narrations

被引:0
|
作者
Obaido, George [1 ]
Ade-Ibijola, Abejide [2 ]
Vadapalli, Hima [1 ]
机构
[1] Univ Witwatersrand, Sch Comp Sci & Appl Math, Johannesburg, South Africa
[2] Univ Johannesburg, Sch Consumer Intelligence & Informat Syst, Formal Struct Algorithms & Ind Applicat Res Clust, Johannesburg, South Africa
基金
新加坡国家研究基金会;
关键词
language translation; intelligent tutoring sys-tem; relational database; synthesis of things; JFA applications;
D O I
10.1109/iscmi47871.2019.9004293
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Structured Query Language (SQL) remains a standard language used in Relational Database Management Systems (RDBMSs), and has found applications in healthcare (patient registries), businesses (inventories, trend analysis), military, and education, etc. Although, SQL statements are English-like, the process of writing SQL queries is often problematic for non-technical end-users. To address this problem, a tool called Narrations-2-SQL is developed to allow an end-user to specify a query in natural language. Narrations-2-SQL is a desktop application that uses a Jumping Finite Automaton (JFA) - a type of Finite Machine for translating natural language descriptions into SQL queries, execute the queries, and provide a feedback to a user. An experimental evaluation was performed on 204 crowdsourced queries in natural language from the XNorthwind DB. Our results show an accuracy of 88%. To get the users' perceptions of this study, we carried out a survey on 167 end-users. Majority of the participants found Narrations-2-SQL to be very helpful, and agreed that it could be useful in industry. If implemented on a large scale, the tool may be helpful to many end-users in different domains.
引用
收藏
页码:195 / 201
页数:7
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