THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN SCIENTOMETRIC SYSTEMS AND DATABASES

Abstract

In today's scientific environment, the use of innovative technologies in scientific publication management systems, in particular artificial intelligence and machine learning, plays a key role in improving the efficiency and accuracy of processing and analysing large amounts of scientific information. This study aims to explore the potential and benefits of using artificial intelligence and machine learning in scientific publication management systems. The main purpose of this study is to unlock the potential of artificial intelligence and machine learning to improve the efficiency of scientific publication management. An analysis of recent research and publications has shown that the use of artificial intelligence allows automating the processes of classifying and analysing scientific publications, which helps to identify new scientific trends and increases the speed of decision-making. Machine learning, on the other hand, provides the ability to create predictive models that help forecast the development of scientific disciplines and determine their impact. The article analyses modern approaches to managing scientific publications and explores the possibilities of using artificial intelligence and machine learning to optimise them. The article also considers the problems of accuracy and objectivity of scientific activity assessment, which can be solved with the help of innovative technologies. The scientific novelty of this work is to study and analyse the use of artificial intelligence and machine learning in scientific publication management systems with a focus on scientometric systems and databases. The results of the analysis indicate that the integration of innovative technologies into scientific publication management systems will significantly improve the quality and speed of processing scientific information, as well as contribute to an objective assessment of scientific activity. It is suggested that these results should be taken into account when developing and improving scientific publication management systems to ensure a more efficient and innovative approach to scientific activity.