Data-Secure Natural Language Interfaces to Databases via Large Language Models

Natural Language Interfaces to Databases (NLIDB) aim to allow users to query databases using natural language, eliminating the need for proficiency in formal query languages like SQL. Recent advancements in Large Language Models (LLMs) have shown promise in connecting natural language and structured query generation. This paper proposes a novel approach utilizing an LLM system to translate natural language queries into optimized SQL statements while ensuring data security by not exposing database contents to external models. The system leverages the database schema. The challenges of working with morphologically rich languages like Turkish are also discussed, along with how the proposed approach addresses these issues.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/isas64331.2024.10845720
Citations
1
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.49
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article

Data-Secure Natural Language Interfaces to Databases via Large Language Models

Kadir Yunus Koc, Duygu Çakır, Volkan Illik, Enes Deniz
1 citations
Data Quality and Management
0.49
article

Data-Secure Natural Language Interfaces to Databases via Large Language Models

Kadir Yunus Koc, Duygu Çakır, Volkan Illik, Enes Deniz
article en
1 citations

Abstract

Natural Language Interfaces to Databases (NLIDB) aim to allow users to query databases using natural language, eliminating the need for proficiency in formal query languages like SQL. Recent advancements in Large Language Models (LLMs) have shown promise in connecting natural language and structured query generation. This paper proposes a novel approach utilizing an LLM system to translate natural language queries into optimized SQL statements while ensuring data security by not exposing database contents to external models. The system leverages the database schema. The challenges of working with morphologically rich languages like Turkish are also discussed, along with how the proposed approach addresses these issues.

Bahçeşehir University (TR)
Openalex Percentile: Top 27%
Data Quality and Management
0.49
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