A Decade Perspective of Recommender Systems Research: A Systematic Review

The amount of data and information created daily has made it nearly impossible for users to find what they are looking for without the help of a recommender system. A recommender system supports and simplifies selection processes by filtering for and recommending the most relevant information to its users. This systematic literature review (SLR) process critically examines past SLRs to identify recent developments and advancements in recommender systems and algorithms. Results show there has been a sharp increase in SLRs focusing on recommender systems over the past decade, accelerating in the past few years. Additionally, the field has evolved to include more specific filtering techniques. Understanding the evolution of recommender system research and large language models are crucial for improving future development; and is relevant to researchers, practitioners, and users.