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SQL Generation from Natural Language Using Supervised Learning and Recurrent Neural Networks

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Artificial Intelligence and Industrial Applications (A2IA 2020)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 144))

Abstract

Databases store a vast amount of today’s data and information, and to access that data users are required to have command over SQL or equivalent interface language. Hence, using a system that can convert a natural language to equivalent SQL query would make the data more accessible. In this sense, building natural language interfaces to relational databases is an important and challenging problem in natural language processing (NLP) and a widely studied field, and found recently momentum again due to the introduction of large-scale Datasets. In this paper, we present our approach based on word embedding and Recurrent Neural Networks (RNN), precisely on Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) cells. We present also the DataSet used for training and testing our models, based on WikiSQL, and finally we show where we arrived in terms of accuracy.

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Author information

Authors and Affiliations

  1. Novelis Lab, Paris, France

    Youssef Mellah, El Hassane Ettifouri, Abdelkader Rhouati & Walid Dahhane

  2. LSE2I Lab of National School of Applied Sciences, Oujda, Morocco

    Toumi Bouchentouf & Mohammed Ghaouth Belkasmi

Authors
  1. Youssef Mellah
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  2. El Hassane Ettifouri
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  3. Abdelkader Rhouati
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  4. Walid Dahhane
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  5. Toumi Bouchentouf
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  6. Mohammed Ghaouth Belkasmi
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Corresponding author

Correspondence to Youssef Mellah .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, National Graduate School for Arts and Crafts, Meknes, Morocco

    Tawfik Masrour

  2. Department of Industrial and Manufacturing Engineering, National Graduate School for Arts and Crafts, Meknes, Morocco

    Ibtissam El Hassani

  3. Department of Industrial and Manufacturing Engineering, National Graduate School for Arts and Crafts, Meknes, Morocco

    Anass Cherrafi

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Mellah, Y., Ettifouri, E.H., Rhouati, A., Dahhane, W., Bouchentouf, T., Belkasmi, M.G. (2021). SQL Generation from Natural Language Using Supervised Learning and Recurrent Neural Networks. In: Masrour, T., El Hassani, I., Cherrafi, A. (eds) Artificial Intelligence and Industrial Applications. A2IA 2020. Lecture Notes in Networks and Systems, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-030-53970-2_17

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