论文标题
建立一个智能的辅导系统，用于法律文本中的论证挖掘
Toward an Intelligent Tutoring System for Argument Mining in Legal Texts
论文作者
论文摘要
我们提出了一个自适应环境（机柜），以基于新颖的认知计算框架来支持Caselaw分析（识别关键参数元素），该框架将各种机器学习（ML）功能仔细匹配，以符合用户的能力。内阁支持法学院的学生以及他们的工作中的专业人士。我们的实验的结果集中在提出的框架的可行性上。我们表明，该系统能够以非常低的假阳性率（2.0-3.5％）以及预测具有相当高的F1得分（0.74）的关键参数元素类型（例如，问题或保留）的分析中的潜在误差。
We propose an adaptive environment (CABINET) to support caselaw analysis (identifying key argument elements) based on a novel cognitive computing framework that carefully matches various machine learning (ML) capabilities to the proficiency of a user. CABINET supports law students in their learning as well as professionals in their work. The results of our experiments focused on the feasibility of the proposed framework are promising. We show that the system is capable of identifying a potential error in the analysis with very low false positives rate (2.0-3.5%), as well as of predicting the key argument element type (e.g., an issue or a holding) with a reasonably high F1-score (0.74).
