An Unsupervised Learning Method to improve Legal Document Retrieval task at ALQAC 2022-Reference-Cited by-同舟云学术

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An Unsupervised Learning Method to improve Legal Document Retrieval task at ALQAC 2022

Published:2022-10-19 Issue: Volume: Page:
ISSN:
Container-title:2022 14th International Conference on Knowledge and Systems Engineering (KSE)
language:
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Author:

Nguyen Dat T.¹,Nguyen Hieu¹,Le Tung²,Nguyen Le-Minh¹

Affiliation:

1. Japan Advanced Institute of Science and Technology,Ishikawa,Japan

2. University of Science, Vietnam National University,Faculty of Information Technology,Ho Chi Minh city,Vietnam

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9953734/9953612/09953618.pdf?arnumber=9953618

Reference19 articles.

1. Jnlp team: Deep learning approaches for legal processing tasks in coliee 2021;nguyen;arXiv preprint arXiv 2106 13112,2021

2. Dossier@ coliee 2021: Leveraging dense retrieval and summarization-based reranking for case law retrieval;althammer;arXiv preprint arXiv 2108 03490,2021

3. Legal assistance using word embeddings;kayalvizhi;FIRE (Working Notes),2019

4. Unsupervised identification of relevant cases statutes using word embeddings;mandal;FIRE (Working Notes),2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ALQAC 2022: A Summary of the Competition;2022 14th International Conference on Knowledge and Systems Engineering (KSE);2022-10-19

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