An Original Natural Language Processing Approach to Language Modeling in Turkish Legal Corpus: Improving Model Performance with Domain Classification by Using Recurrent Neural Networks Türkçe Hukuk Derleminde Dil Modellemesi Üzerine Özgün bir Dogal Dil Işleme Yaklaşimi: Yinelemeli Sinir Aglari Kullanilarak Alana Ait Siniflandirma (AAS) ile Model Başariminin Iyileştirilmesi

Erdoganyimaz C., Mengunogul B.

2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022, Antalya, Türkiye, 7 - 09 Eylül 2022, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/asyu56188.2022.9925363
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: natural language generator, natural language processing, recurrent neural networks
  • Marmara Üniversitesi Adresli: Evet

Özet

© 2022 IEEE.In this study, a new method called Domain Classification and a natural language generator system in which this method is applied have been developed in order to increase the model performance in natural language processing studies conducted in the corpus of Turkish legal texts. In short, the new method developed states that the performance of a deep learning model trained in the field of law will be higher when it is trained on a sub-field based special dataset classified according to legal disciplines. To be able to test the method during the development process of the natural language generator is designed with an architecture using Recurrent Neural Networks, which can work as a hybrid, capable of being trained and working even on low-equipped devices by using interdisciplinary study. In addition, the texts produced in different fields of Turkish law by the natural language generator system developed in this study were examined, and it was discussed in which areas the developed Domain Classification method and the natural language generator could benefit the lawyers and the judicial system in general.