Review of collaborative filtering recommendation systems

Abstract

In the era of information overload, recommender systems develop rapidly. And because the needs of information consumers are full of diversity and the information data provided by information producers is too large, to enhance the efficiency and quality of recommendations, the research community has introduced numerous approaches to optimize recommendation systems. As collaborative filtering stands as a time-tested technique in recommendation systems, This paper facilitates a swift comprehension of recent advances in collaborative filtering. It does so by examining the techniques presented across the entire collaborative filtering recommendation systems research field in recent years, especially its development in the domain of deep learning, and have a solid understanding of the field of study.