论文标题
法院判决使用主题建模和句法解析标签
Court Judgement Labeling Using Topic Modeling and Syntactic Parsing
论文作者
论文摘要
在实践普通法的地区，相关的历史案件是量刑的重要参考。为了帮助法律从业者发现以前的判断更容易，本文旨在通过某些标签标记每个法院的判断。这些标签对于总结判断并可以指导用户进行类似判断在法律上很重要。我们引入了一个启发式系统来解决该问题，该系统始于以方面驱动的主题建模，并使用依赖性解析和选区解析短语生成。我们还为香港构建了一个法律术语树，并实施了一个简化模块来支持系统。最后，我们根据生成的标签提出了类似的文档建议算法。它使用户可以根据一些选定的方面而不是整个段落找到类似的文档。实验结果表明，该系统是该特定任务的最佳方法。就汇总文档而言，它比简单的术语提取方法更好，并且建议算法比全文本比较方法更有效。我们认为，该系统在法律和其他领域都具有巨大的潜力。
In regions that practice common law, relevant historical cases are essential references for sentencing. To help legal practitioners find previous judgement easier, this paper aims to label each court judgement by some tags. These tags are legally important to summarize the judgement and can guide the user to similar judgements. We introduce a heuristic system to solve the problem, which starts from Aspect-driven Topic Modeling and uses Dependency Parsing and Constituency Parsing for phrase generation. We also construct a legal term tree for Hong Kong and implemented a sentence simplification module to support the system. Finally, we propose a similar document recommendation algorithm based on the generated tags. It enables users to find similar documents based on a few selected aspects rather than the whole passage. Experiment results show that this system is the best approach for this specific task. It is better than simple term extraction method in terms of summarizing the document, and the recommendation algorithm is more effective than full-text comparison approaches. We believe that the system has huge potential in law as well as in other areas.
