Text Mining for the Analysis of Legal Texts

2022 12th International Conference on Advanced Computer Information Technologies (ACIT) Pub Date : 2022-09-26 DOI:10.1109/ACIT54803.2022.9913169

Olha Kovalchuk, S. Banakh, M. Masonkova, K. Berezka, Serhii Mokhun, O. Fedchyshyn

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引用次数: 2

Abstract

Words are the main tool of a lawyer. The analysis of a large amount of textual information makes up the lion's share of legal practice, in particular, when creating an evidence base in criminal proceedings, analyzing pre-trial decisions, analyzing court decisions in similar cases, observing judicial precedent, etc. There are many answers to essential questions hidden in these documents. Every year, the number of legal and law-related electronic text documents that need to be quickly and efficiently analyzed is growing exponentially. Using powerful Text Mining tools will help you discover important legal information and make the right legal decisions.Automatic text classification is one of the most effective tools for finding and analyzing information in jurisprudence. This article presents a Decision tree model using the Chi-square Automatic Interaction Detector (CHAID) growing method for classifying legal texts. A model for automatic classification of text documents related to criminal proceedings has been developed for the dataset of 1,800 text documents used in court proceedings in Ukraine from 2000 to 2020.

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用于法律文本分析的文本挖掘

语言是律师的主要工具。对大量文本信息的分析在法律实践中占了很大的比重，特别是在刑事诉讼中建立证据基础、分析审前判决、分析类似案件的法院判决、观察司法先例等方面。这些文件中隐藏着许多重要问题的答案。每年，需要快速有效地分析的法律和与法律相关的电子文本文件的数量呈指数级增长。使用强大的文本挖掘工具将帮助您发现重要的法律信息并做出正确的法律决策。自动文本分类是查找和分析法学信息最有效的工具之一。本文提出了一种使用卡方自动交互检测器(CHAID)生长方法对法律文本进行分类的决策树模型。针对2000年至2020年乌克兰法庭诉讼中使用的1800个文本文件的数据集，开发了一个与刑事诉讼相关的文本文件自动分类模型。

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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来源期刊

2022 12th International Conference on Advanced Computer Information Technologies (ACIT)

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