JNLP Team: Deep Learning for Legal Processing in COLIEE 2020

Ha-Thanh Nguyen; Hai-Yen Thi Vuong; Phuong Minh Nguyen; Binh Tran Dang; Quan Minh Bui; Sinh Trong Vu; Chau Minh Nguyen; Vu Tran; Ken Satoh; Minh Le Nguyen

JNLP Team: Deep Learning for Legal Processing in COLIEE 2020

Computation and Language 2020-11-17 v1 Information Retrieval Machine Learning

Authors: Ha-Thanh Nguyen , Hai-Yen Thi Vuong , Phuong Minh Nguyen , Binh Tran Dang , Quan Minh Bui , Sinh Trong Vu , Chau Minh Nguyen , Vu Tran , Ken Satoh , Minh Le Nguyen

View on arXiv ↗ PDF ↗

Abstract

We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020. These systems are all characterized by being pre-trained on large amounts of data before being finetuned for the specified tasks. This approach helps to overcome the data scarcity and achieve good performance, thus can be useful for tackling related problems in information retrieval, and decision support in the legal domain. Besides, the approach can be explored to deal with other domain specific problems.

Keywords

legal judgment prediction machine learning

Cite

@article{arxiv.2011.08071,
  title  = {JNLP Team: Deep Learning for Legal Processing in COLIEE 2020},
  author = {Ha-Thanh Nguyen and Hai-Yen Thi Vuong and Phuong Minh Nguyen and Binh Tran Dang and Quan Minh Bui and Sinh Trong Vu and Chau Minh Nguyen and Vu Tran and Ken Satoh and Minh Le Nguyen},
  journal= {arXiv preprint arXiv:2011.08071},
  year   = {2020}
}

Comments

Also be published in JURISIN2020

JNLP Team: Deep Learning for Legal Processing in COLIEE 2020

Abstract

Keywords

Cite

Comments

Related papers