A Machine Learning Approach to Argument Mining in Legal Documents

Author:

Poudyal PrakashORCID

Publisher

Springer International Publishing

Reference16 articles.

1. Biran, O., Rambow, O.: Identifying justifications in written dialogs by classifying text as argumentative. Int. J. Semant. Comput. 5(04), 363–381 (2011). https://doi.org/10.1142/S1793351X11001328

2. Bunescu, R.C., Mooney, R.J.: A shortest path dependency kernel for relation extraction. In: Proceedings of the Human Language Technology Conference and Conference Empirical methods in Natural Language Processing (HLT/EMNLP-05), pp. 724–731. Association for Computational Linguistics, Stroudsburg (2005). https://doi.org/10.3115/1220575.1220666

3. Cabrio, E., Villata, S.: Towards a benchmark of natural language arguments. In: Proceedings of the 15th International Workshop on Non-Monotonic Reasoning (NMR 2014), Vienna (2014)

4. Doddington, G., Mitchell, A., Przybocki, M., Ramshaw, L., Strassel, S., Weischedel, R.: The automatic content extraction (ace) program-tasks, data, and evaluation. In: Proceedings of the Fourth International Conference on Language Resources and Evaluation, vol. 2, pp. 837–840 (2004)

5. Florou, E., Konstantopoulos, S., Koukourikos, A., Karampiperis, P.: Argument extraction for supporting public policy formulation. In: Proceedings of the 7th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, pp. 49–54 (2013)

Cited by 4 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. Multi-fusion Recurrent Network for Argument Pair Extraction;Artificial Neural Networks and Machine Learning – ICANN 2023;2023

2. A knowledge-centered framework for exploration and retrieval of legal documents;Information Systems;2022-05

3. Context-Aware and Data-Augmented Transformer for Interactive Argument Pair Identification;Natural Language Processing and Chinese Computing;2021

4. ARGUABLY @ AI Debater-NLPCC 2021 Task 3: Argument Pair Extraction from Peer Review and Rebuttals;Natural Language Processing and Chinese Computing;2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3