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Predicting associated statutes for legal problems

机译:预测法律法规的相关法规

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摘要

Applying text mining techniques to legal issues has been an emerging research topic in recent years. Although a few previous studies focused on assisting professionals in the retrieval of related legal documents, to our knowledge, no previous studies could provide relevant statutes to the general public using problem statements. In this work, we design a text mining based method, the three-phase prediction (TPP) algorithm, which allows the general public to use everyday vocabulary to describe their problems and find pertinent statutes for their cases. The experimental results indicate that our approach can help the general public, who are not familiar with professional legal terms, to acquire relevant statutes more accurately and effectively.
机译:近年来,将文本挖掘技术应用于法律问题已成为新兴的研究主题。尽管先前的一些研究着重于协助专业人员检索相关的法律文件,但据我们所知,以前没有研究可以使用问题陈述向公众提供相关法规。在这项工作中,我们设计了一种基于文本挖掘的方法,即三相预测(TPP)算法,该算法可使公众使用日常词汇来描述他们的问题并找到与他们的情况相关的法规。实验结果表明,我们的方法可以帮助不熟悉专业法律术语的公众更准确,更有效地获取相关法规。

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