Browsing by Subject "Prior legal case retrieval"

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    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, Aykut
    In 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.
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    ItemOpen Access
    Retrieving Turkish prior legal cases with deep learning
    (2023-06) Öztürk, Ceyhun Emre
    This study utilizes deep learning models to retrieve prior legal cases in the Court of Cassation in Turkey. Given the vast legal databases that legal professionals need to navigate and the ability of computers to handle large amounts of text quickly, information retrieval algorithms prove beneficial for legal practitioners. In this thesis, we introduce our legal recurrent neural network (RNN) models and the BERTurk-Legal model. We also introduce dense word embeddings for the Turkish legal domain. Moreover, we employ RNN autoencoders, Legal RNN autoencoders, combinations of RNN autoencoders with BM25 algorithms, and BERTurk-Legal to retrieve prior legal cases. We obtain the best results with the BERTurk-Legal model.