Content-based approach in recommender systems: principles, methods and performance metrics

Abstract

Content-based approach in recommender systems: principles, methods and performance metrics

Klemin N.A., Abbakumov A.A., Egunova A.I., Pronchatov A.V., Groshev D.O.

Incoming article date: 08.03.2025

This paper explores the content-based filtering approach in modern recommender systems, focusing on its key principles, implementation methods, and evaluation metrics. The study highlights the advantages of content-based systems in scenarios that require deep object analysis and user preference modeling, especially when there is a lack of data for collaborative filtering.

Keywords: сontent - oriented filtering, recommendation systems, feature extraction, similarity metrics, personalization