Abstract:
Legal judgement recommendation systems are becoming increasingly popular in the legal sector because they can help attorneys save time and deliver more accurate recommendations to their clients. As a result of these benefits, the industry is seeing an increase in the popularity of these systems. This article presents a new strategy for the recommendation of legal judgements that makes use of machine learning algorithms to find similarities between cases and indicate the optimal legal judgement based on these similarities. The methodology is outlined in this article. To conduct an analysis of legal documents and retrieve pertinent information for comparison, the system under consideration makes use of natural language processing techniques. A user interface is also included in the system, which gives legal professionals the ability to input the specifics of their cases and receive advice in real time. In order to assess the efficacy of the system, we ran experiments on a collection of legal cases and compared the recommendations that were produced by our system to those that were offered by human specialists. The findings demonstrated that the suggested system is capable of providing recommendations that are accurate and dependable, with a high level of concordance with the opinions of human experts. We feel that this strategy has the potential to be a useful tool for solicitors, since it will enable them to rapidly locate relevant instances and make well- informed conclusions regarding the law.
