Browsing by Subject "Doğal dil işleme"
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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 Feedforward neural network based case prediction in Turkish higher courts(2022-08-29) Aras, Arda C.; Öztürk, Ceyhun E.; Koç, AykutThanks to natural language processing (NLP) methods, legal texts can be processed by computers and decision prediction applications can be developed in the legal tech field. Increase in the available data sources in the Turkish legal system provides an opportunity to develop NLP applications as well. In order to develop these applications, the necessary corpora and datasets should be created. In this work, legal case texts from the Turkish Higher Courts that are open to public access and free from personal data are used to develop decision prediction methods. Feedforward neural networks (FFNN) are deployed using word embeddings and the features extracted from texts via the Principal Component Analysis (PCA) algorithm. %85.4 Macro F1 score level is achieved.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 Transformer-based bug/feature classification(IEEE - Institute of Electrical and Electronics Engineers, 2023-08-28) Öztürk, Ceyhun Emre; Yılmaz, E. H.; Köksal, Ö.Automatic classification of a software bug report as a 'bug' or 'feature' is essential to accelerate closed-source software development. In this work, we focus on automating the bug/feature classification task with artificial intelligence using a newly constructed dataset of Turkish software bug reports collected from a commercial project. We train and test support vector machine (SVM), k-nearest neighbors (KNN), convolutional neural network (CNN), transformer-based models, and similar artificial intelligence models on the collected reports. Results of the experiments show that transformer-based BERTurk is the best-performing model for the bug/feature classification task.Item Open Access Türkçe kelime temsillerinde cinsiyetçi ön yargının incelenmesi(IEEE, 2021-07-19) Sevim, Nurullah; Koç, AykutDoğal Dil İşleme uygulamalarında cinsiyetçi ön yargının incelenmesi, olası bir cinsiyetçi yaklaşımın olumsuz sonuçlarından dolayı son zamanlarda önem kazanmıştır. Özellikle İngilizce kelime temsillerinde bu tür ön yargılar çeşitli bağlamlarda incelenerek birçok araştırma yapılmıştır. Bu çalışmada Türkçe kelime temsillerinin cinsiyetçi ön yargılar açısından durumu incelenmiştir ve Türkçe dil yapısı İngilizce dil yapısı ile cinsiyetçi ön yargılar kapsamında karşılaştırılmıştır. Kelime temsillerinde yapılan cinsiyetçi ön yargıların ölçümü sonucunda Türkçe’nin İngilizce’ye kıyasla dil yapısında cinsiyetçi ön yargıyı daha az barındırdığı sonucuna varılmıştır.