Legal Intelligence: Algorithmic, Data, and Social Challenges

Changlong Sun, Yating Zhang, Xiaozhong Liu, Fei Wu
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引用次数: 5

Abstract

In the digital era, information retrieval, text/knowledge mining, and NLP techniques are playing increasingly vital roles in legal domain. While the open datasets and innovative deep learning methodologies provide critical potentials, in the legal-domain, efforts need to be made to transfer the theoretical/algorithmic models into the real applications to assist users, lawyers, judges and the legal professions to solve the real problems. The objective of this workshop is to aggregate studies/applications of text mining/retrieval and NLP automation in the context of classical/novel legal tasks, which address algorithmic, data and social challenges of legal intelligence. Keynote and invited presentations from industry and academic will be able to fill the gap between ambition and execution in the legal domain.
法律情报:算法、数据和社会挑战
在数字时代,信息检索、文本/知识挖掘和自然语言处理技术在法律领域发挥着越来越重要的作用。虽然开放的数据集和创新的深度学习方法提供了关键的潜力,但在法律领域,需要努力将理论/算法模型转化为实际应用,以帮助用户、律师、法官和法律专业人员解决实际问题。本次研讨会的目的是在经典/新法律任务的背景下,汇集文本挖掘/检索和NLP自动化的研究/应用,这些研究/应用解决了法律智能的算法、数据和社会挑战。来自行业和学术界的主题演讲和邀请演讲将能够填补法律领域的雄心和执行之间的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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