ALGORITHMIC CLUSTERING TECHNIQUES IN RECOMMENDATION SYSTEMS WITH COLLABORATIVE FILTERING

Abstract

Over the past twenty years, a lot of work has been done, both theoretical and practical, and it was devoted to the development of recommendation systems. Currently, recommendation systems keep strong scientific interest, because there are still many issues in this field, and their solution offers great opportunities for practical application, which should help users cope with a huge amount of information, as well as provide them with tools for developing personalized recommendations. Such an industry as e-commerce has been actively developing, and one of its main aims includes increasing the sales. To do this, it is needed to study the consumer's preferences for future proposal of products that meet their requirements. Hereby, recommendation systems are developed. The research subject is considered relevant, and it represents issues that need to be solved. The research is concerned with the analysis of user's preferences for providing further recommendations. The recommendation methods of collaborative filtering are the focus of this research.