An Explainable Approach to Deducing Outcomes in European Court of Human Rights Cases Using ADFs
An Explainable Approach to Deducing Outcomes in European Court of Human Rights Cases Using ADFs
复制标题
使用 ADF 推断欧洲人权法院案件结果的可解释方法
作者：
Joe Collenette;Katie Atkinson
.在本文中，我们提出了一种基于论证的方法来表示和推理的法律领域，以前已经通过机器学习方法解决。该领域涉及所有属于欧洲人权法院特定条款范围内的案件。我们执行的方法之间的比较，基于两个标准：模型的能力，以准确地复制的决定，在特定领域内的真实的生活中的法律的案件，和模型提供的解释的质量。我们的初步结果表明，基于论证方法的系统在准确性方面提高了机器学习结果，并且可以根据案件转向的问题以及得出结论的关键因素来解释其结果。
. In this paper we present an argumentation-based approach to representing and reasoning about a domain of law that has previously been addressed through a machine learning approach. The domain concerns cases that all fall within the re-mit of a specific Article within the European Court of Human Rights. We perform a comparison between the approaches, based on two criteria: ability of the model to accurately replicate the decision that was made in the real life legal cases within the particular domain, and the quality of the explanation provided by the models. Our initial results show that the system based on the argumentation approach improves on the machine learning results in terms of accuracy, and can explain its outcomes in terms of the issue on which the case turned, and the factors that were crucial in arriving at the conclusion.
影响因子：
3.8
作者：
Aletras, Nikolaos;Tsarapatsanis, Dimitrios;Lampos, Vasileios
通讯作者：
Lampos, Vasileios