Possibilities of using artificial intelligence and natural language processing to analyse legal norms and interpret them

Author:

Serediuk Vitalii

Abstract

The study aaddressed the possibilities of using information technology and natural language in the study of legal norms. The study aimed to develop methods for using artificial intelligence and natural language processing to analyse jurisprudence. To achieve this goal, automatic strategies were created to recognise the main topics in legal texts, identify key legal concepts and analyse the structure of documents. The results of the study included an analysis of existing methods of using technology and natural language to analyse legal norms. The methods used included machine and deep learning, syntactic and semantic analysis, an automated classification system, relative analytics, and decision prediction. In addition, new methods of analysing legal texts based on artificial intelligence and natural language processing were introduced. These methods included the use of a thematic model that automatically identifies the main themes in legal texts, as well as automatic detection of legal concepts, which identifies key concepts. In addition, neural networks were used to analyse the structure of legal documents, which allows for more accurate recognition and analysis of various structural elements in documents. Automatic text generation based on legal information and ways to classify legal texts was also introduced. Thus, the main results were the automation of the process of analysing and understanding legal texts, an increase in the efficiency and accuracy of identifying thematic patterns and key legal concepts, and improved accessibility and speed of legal information processing. The results obtained indicate a great potential for the use of technological tools in jurisprudence, which can significantly improve the quality and accessibility of legal services, contributing to more efficient resolution of legal issues

Publisher

Scientific Journals Publishing House

Reference49 articles.

1. [1] A first-of-its-kind factory. (2024). Retrieved from https://www.legalsifter.com/combined-intelligence/ai/sifters.

2. [2] A visual guide to AI. (n.d.). Retrieved from https://www.rossintelligence.com/what-is-ai.

3. [3] AI in litigation: Tools that enhance predictive analysis. (2023). Retrieved from https://getlegalbuddies.com/blog/ai-in- litigation-tools-that-enhance-predictive-analysis/.

4. [4] Alparslan, G. (2024). The adequacy of global legal norms on legal issues related to digitalization and artificial intelligence. International Journal of Law and Politics Studies, 6(1), 68-75. doi: 10.32996/ijlps.2024.6.1.8.

5. [5] Arul Raj, D.D.A.A.R., Rukmani, K.V.R., Rukmani, K.C., Rukmani, P.M., & Rukmani, A.A. (2024). Impact of an artificial intelligence in language learning – A survey. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(2), 258-266. doi: 10.32628/cseit2410218.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3