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2023 | OriginalPaper | Chapter

INSL: Text2SQL Generation Based on Inverse Normalized Schema Linking

Authors : Tie Jun, Fan Ziqi, Sun Chong, Zheng Lu, Zhu Boer

Published in: Artificial Intelligence in China

Publisher: Springer Nature Singapore

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Abstract

Structured Query Language (SQL) is a query language widely used in databases, Text2SQL automatically parses natural language into SQL, which has great potential to facilitate non-expert users to query and mine structured data using natural language. Current research focuses on improving the matching accuracy of SQL clause tasks, but ignores the correctness of SQL syntax generation, and SQL generation involving multi-table joins still suffers from a large number of errors. Therefore, a neural network-based Text2SQL approach is proposed. To implement a practical Text2SQL workflow, the model associates natural language queries with an inverse normalized database schema, called INSL (Inverse Normalized Schema Link Generation Network). Through theoretical analysis and experimental validation on the public dataset Spider, INSL can effectively improve the quality of Text2SQL tasks.

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Metadata
Title
INSL: Text2SQL Generation Based on Inverse Normalized Schema Linking
Authors
Tie Jun
Fan Ziqi
Sun Chong
Zheng Lu
Zhu Boer
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Artificial Intelligence in China

Print ISBN: 978-981-9912-55-1

Electronic ISBN: 978-981-9912-56-8

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-99-1256-8_23

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