Efficient Parallel Algorithms for LargeScale Matrix Factorization in Collaborative Filtering Systems

Novi Siti Juariah
Rizky Pratama .H
Melda Ayu Nengsi

International Journal of Applied Mathematics and Computing.
Vol. 1 No. 1 (2024): January: International Journal of Applied Mathematics and Computing

Collaborative filtering systems rely heavily on matrix factorization techniques, which often face scalability issues when handling large datasets. This paper presents an efficient parallel algorithm that leverages distributed computing to perform largescale matrix factorization. Experimental results show that our algorithm significantly reduces computation time while maintaining high accuracy. The approach has practical implications for recommendation systems, particularly in ecommerce and social media platforms.