Data mining and visualization on legal documents

Dhruv Gaur
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引用次数: 6

Abstract

LIRFSS (Legal Information Retrieval and Focused Semantic Search) is a system that performs IR(Information Retrieval) and IE(Information Extraction) on Indian Supreme Court decisions, specifically on criminal cases related to murder and provide focused semantic search results, offering a high potential of assistance for judges, lawyers and citizens in getting access to law. In this paper, development process of LIRFSS is discussed. Appropriate information to be extracted for criminal cases such as date, location of occurrence and IPC (Indian Penal code)[1] sections were determined from a sample set of documents. Better instruments than manual browsing and other search methods are required to make the most out of freely available law on internet, therefore a semantic search is carried out using extracted information and most pertinent cases were returned as a result. As analyzing the vast volumes of data becomes increasingly difficult, so information visualization is also carried out in this paper and a new hypotheses is proposed and verified. From 20 training documents, a satisfactory amount of precision was obtained.
法律文件的数据挖掘和可视化
LIRFSS (Legal Information Retrieval and Focused Semantic Search)是一个对印度最高法院的判决,特别是与谋杀有关的刑事案件,执行IR(Information Retrieval)和IE(Information Extraction)的系统,并提供集中的语义搜索结果,为法官、律师和公民获取法律信息提供了很大的帮助。本文讨论了LIRFSS的开发过程。从一组样本文件中确定了为刑事案件提取的适当信息,如日期、发生地点和IPC(印度刑法典)[1]章节。为了最大限度地利用互联网上免费提供的法律,需要比手动浏览和其他搜索方法更好的工具,因此使用提取的信息进行语义搜索,并返回最相关的案例。由于分析海量数据变得越来越困难,因此本文也进行了信息可视化,提出并验证了一个新的假设。从20个训练文件中,获得了令人满意的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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