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用自然语言处理预测荷兰判例中的引文.

Iris Schepers1,2, Masha Medvedeva3, Michelle Bruijn1

  • 1Department of Legal Methods, Faculty of Law, University of Groningen, Groningen, The Netherlands.

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概括

这项研究开发了一个系统来预测荷兰法院的判决是否会被引用,帮助法律专业人士更容易找到权威的判例法. 使用元数据的可解释模型的性能几乎与基于文本的复杂系统一样好.

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判例法 判例法 判例法引文分析 引文分析司法决定的司法决定.机器学习 机器学习自然语言处理自然语言处理.

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科学领域:

  • 法律信息学 法律信息学
  • 计算法 计算法 计算法
  • 人工智能在法律中的作用

背景情况:

  • 随着司法法的在线可访问性增加,在识别相关法律先例方面存在挑战.
  • 荷兰计划扩大在线判例法出版的计划将加剧这一问题.
  • 区分权威的判例与影响力较小的决定对于法律研究的效率至关重要.

研究的目的:

  • 开发一个预测模型来识别引用的法院判决,从而区分权威案件.
  • 帮助法律从业者和学者有效地导航大量的法律数据.
  • 减少法律案件准备和分析所需的时间和精力.

主要方法:

  • 预测建模用于预测法庭判决公布后的引用.
  • 利用手工制作的元数据功能和全文分析来开发模型.
  • 使用马修斯相关系数 (MCC) 评估模型性能.

主要成果:

  • 预测模型显示,荷兰最高法院 (MCC = 0.60) 具有很强的相关性.
  • 国务院 (MCC = 0.26) 和地区法院 (MCC = 0.17) 的表现不那么成功.
  • 仅使用元数据特征的可解释模型实现了与较不易解释的基于文本的模型可比的性能.

结论:

  • 预测引文分析为过权威法律决策提供了一种可行的方法.
  • 基于元数据的可解释的人工智能模型为法律信息学应用提供了有前途的方法.
  • 需要进一步改进,以提高不同法院级别的预测准确性.