Дослідження методів динамічної адаптації рекомендацій в іт-проектах електронної комерції

Abstract

This work focuses on analyzing recommender systems, existing methods for building recommendations and proposing new features, that can improve user experience and enhance customer loyalty. Various recommendation techniques, data mining techniques, automatic recommendation, dynamic adaptation and argumentation were analyzed in this research paper. This work provides a detailed exploration of the current state of recommender systems and the challenges and opportunities presented by these technologies. The proposed features will help improve recommender systems and make them more attractive than the existing ones