Unveiling Themes in Judicial Proceedings: A Cross-Country Study Using Topic Modeling on Legal Documents from India and the UK
Didwania, Krish, Toshniwal, Dr. Durga, Agarwal, Amit
–arXiv.org Artificial Intelligence
Legal documents are indispensable in every country for legal practices and serve as the primary source of information regarding previous cases and employed statutes. In today's world, with an increasing number of judicial cases, it is crucial to systematically categorize past cases into subgroups, which can then be utilized for upcoming cases and practices. Our primary focus in this endeavor was to annotate cases using topic modeling algorithms such as Latent Dirichlet Allocation, Non-Negative Matrix Factorization, and BerTopic for a collection of lengthy legal documents from India and the UK. This step is crucial for distinguishing the generated labels between the two countries, highlighting the differences in the types of cases that arise in each jurisdiction. Furthermore, an analysis of the timeline of cases from India was conducted to discern the evolution of dominant topics over the years.
arXiv.org Artificial Intelligence
Jun-30-2024
- Country:
- Asia
- China > Hunan Province
- Changsha (0.04)
- India > Uttarakhand
- Roorkee (0.04)
- Middle East > Jordan (0.04)
- China > Hunan Province
- Europe > France
- Grand Est > Bas-Rhin > Strasbourg (0.04)
- North America > United States
- Illinois > Cook County > Chicago (0.04)
- Oceania > Australia (0.04)
- Asia
- Genre:
- Research Report > New Finding (0.47)
- Industry:
- Law (1.00)
- Law Enforcement & Public Safety > Crime Prevention & Enforcement (0.46)
- Technology: