A Survey on Data-Centric Recommender Systems

Recommender systems (RS) have become essential tools for mitigating information overload in a range of real-world scenarios. Recent trends in RS have seen a paradigm shift, moving the spotlight from model-centric innovations to the importance of data quality and quantity. This evolution has given rise to the concept of data-centric recommender systems (Data-Centric RS), marking a significant development in the field. This survey provides the first systematic overview of Data-Centric RS, covering 1) the foundational concepts of recommendation data and Data-Centric RS; 2) three primary issues in recommendation data; 3) recent research developed to address these issues; and 4) several potential future directions in Data-Centric RS.