INVESTIGATION OF THE NATURAL LANGUAGE PROCESSING MODELS FOR TEXT-BASED RECOMMENDATION SYSTEMS

This study investigates the application of natural language processing (NLP) methods in recommendation systems based on textual data. It identifies models with the highest utility coefficients for specific tasks based on criteria crucial for recommendation provision. The study underscores the importance and effectiveness of employing NLP methods in recommendation systems, utilizing the findings to develop a recommendation system.