TY - GEN
T1 - Synthesis of SQL queries from narrations
AU - Obaido, George
AU - Ade-Ibijola, Abejide
AU - Vadapalli, Hima
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
KW - Intelligent tutoring system
KW - JFA applications
KW - Language translation
KW - Relational database
KW - Synthesis of things
UR - http://www.scopus.com/inward/record.url?scp=85081545360&partnerID=8YFLogxK
U2 - 10.1109/ISCMI47871.2019.9004293
DO - 10.1109/ISCMI47871.2019.9004293
M3 - Conference contribution
AN - SCOPUS:85081545360
T3 - 2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019
SP - 195
EP - 201
BT - 2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019
Y2 - 19 November 2019 through 20 November 2019
ER -