Application of Artificial Intelligence Methods in the Analysis of Scientific Texts

The article examines the potential of machine learning and natural language processing methods in the automatic analysis of scientific publications. Based on a corpus of more than 5,000 articles, a comparative analysis of keyword extraction and topic clustering algorithms was conducted. The results demonstrated that transformer-based models improve accuracy by 18 percent compared with traditional statistical approaches. The findings may be applied to enhance the search systems of digital libraries.