Scholarly Publications - Law
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Browsing Scholarly Publications - Law by Type "Conference Paper"
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Item Open Access A transformer-based prior legal case retrieval method(IEEE - Institute of Electrical and Electronics Engineers, 2023-08-28) Öztürk, Ceyhun Emre; Özçelik, Şemsi Barış; Koç, AykutIn this work, BERTurk-Legal, a transformer-based language model, is introduced to retrieve prior legal cases. BERTurk-Legal is pre-trained on a dataset from the Turkish legal domain. This dataset does not contain any labels related to the prior court case retrieval task. Masked language modeling is used to train BERTurk-Legal in a self-supervised manner. With zero-shot classification, BERTurk-Legal provides state-of-the-art results on the dataset consisting of legal cases of the Court of Cassation of Turkey. The results of the experiments show the necessity of developing language models specific to the Turkish law domain.Item Open Access Predicting outcomes of the court of cassation of Turkey with recurrent neural networks(IEEE, 2022-08-29) Öztürk, Ceyhun E.; Özçelik, Ş. Barış; Koç, AykutNatural Language Processing (NLP) based approaches have recently become very popular for studies in legal domain. In this work, the outcomes of the cases of the Court of Cassation of Turkey were predicted with the use of Deep Learning models. These models are GRU, LSTM and BiLSTM which are variants of the recurrent neural network. Models saw only fact description parts of the case decision texts during training. Firstly, the models were trained with the word embeddings that were created from the texts from daily language. Then, the models were trained with the word embeddings that were created from downloaded legal cases from Turkish courts. The results of the experiments on the models are given in a comparative and detailed manner. It is observed based on this study and the past studies that the outcomes of the Court of Cassation can be predicted with higher accuracy than most of the courts that were investigated in previous legal NLP studies. The model which is best at predicting decisions is GRU. The GRU model achieves 96.8% accuracy in the decision prediction task.Item Open Access Taşıyıcı annelik, ortaya çıkaracağı hukuksal sorunlar ve çözüm önerileri(Doğu Akdeniz Üniversitesi, 2012-10) Koçhisarlıoğlu, Cengiz; Erişgin, Ö.