V. I. Tsurkov

Comparison of Matrix Factorization Methods for Item-Based Recommendations

2025 · Journal of Computer and Systems Sciences International

Abstract Modern recommender systems increasingly go beyond classical personalization tasks, addressing more complex scenarios of interactions between items. One such challenge is generating complementary recommendations, where standard user-centric architectures often lack sufficient flexibility. This study …