Asım Sinan YÜKSEL, Muhammed Abdulhamid KARABIYIK

Doğal dil işleme yöntemleriyle metinden SQL sorgusu tahmini üzerine bir çalışma

Bilgisayar bilimlerinde, kalıcı bilgiler sistematik bir şekilde veri tabanlarında tutulmaktadır. Veri tabanlarındaki bilgilere ulaşılabilmesi için belirli teknik birikimlere sahip olunması gerekmektedir. Çalışmamızda, doğal dille yapılmış sorgulardan SQL sorgusu tahmini yapılmıştır. Bu sayede teknik bir bilgi birikimi olmadan veri tabanları üzerinde sorgulamalar yapılabilmesi hedeflenmektedir. Çalışmamızda doğal dil işleme tekniklerinden faydalanmıştır. Doğal dil işlemenin ana konularından biri olan çoklu dil desteği, uygulamaya entegre edilmiştir. Doğal dilden SQL tahmini için uygulanan model, LSTM ağı kullanılarak spider veri setiyle eğitilmiştir. Yapılan SQL sorgusu tahminlerinde, %75 başarı oranına ulaşmıştır. Çoklu dil desteğiyle yapılan genel sistem değerlendirmesinde, başarı oranı %69.4’ e ulaşmıştır.

Anahtar Kelimeler:

Doğal dil işleme, Yapay zekâ, Metinden SQL dönüşümü

A study on text-to-SQL query prediction with natural language processing methods

In computer science, permanent information is kept in databases in a systematic way. In order to access the information in the databases, it is necessary to have certain technical knowledge. In our study, SQL query estimation was made from natural language queries. In this way, it is aimed to make queries on databases without any technical knowledge. In our study, natural language processing techniques were used. Multi-language support, which is one of the main subjects of natural language processing, is integrated into the application. The model applied for natural language SQL prediction is trained with the spider dataset using the LSTM network. In the SQL query estimations, it has reached 75% success rate. In the overall system evaluation with multilingual support, the success rate has reached 69.4%.

Keywords:

Natural language processing, Artificial intelligent, Text to SQL,

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