Matrix Factorization in Recommender Systems: Algorithms, Applications, and Peculiar Challenges

Abstract

Traditional Collaborative filtering (CF) is one of the techniques of recommender systems that has been successfully exploited in various applications, but sometimes they fail to provide accurate recommendations because they depend majorly on the rating matrix, which is always scanty and of very high dimension. Matrix factorization (MF) algorithms are variants of latent factor models, which are easy, fast, and efficient. This article reviews the related research and advances in the application of matrix factorization techniques in recommender systems. Popular matrix factorization algorithms utilized in recommender systems were reviewed. The peculiar challenges of using matrix factorization in recommender systems were also enumerated and discussed with the goal of identifying the different problems solved with the use of matrix factorization techniques as applied in recommender systems.

KEYWORDS:

• Accuracy
• Collaborative filtering
• Matrix factorization
• Recommender systems
• Scalability
• Sparsity

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Folasade Olubusola Isinkaye

F O Isinkaye holds a BSc degree in computer science from the Ondo State University, Ado-Ekiti, (now EKSU) Nigeria. Her MSc and PhD degrees were obtained in computer science from the University of Ibadan, Nigeria, with a specialization in intelligent systems. She is a lecturer at the Department of Computer Science, Ekiti State University, Ado-Ekiti, Nigeria. Her research interests include recommender systems, data mining, information systems and machine She is a member of professional bodies which include the Computer Professional [Registration Council of Nigeria (CPN)] and the Association for Computing Machinery (ACM). She was a visiting PhD scholar at the Laboratory of Knowledge Management, Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Italy.