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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
Vitalii Serediuk (Sat,) studied this question.