  Recommendation represents a vital stage in developing and promoting the
benefits of the Internet of Things (IoT). Traditional recommender systems fail
to exploit ever-growing, dynamic, and heterogeneous IoT data. This paper
presents a comprehensive review of the state-of-the-art recommender systems, as
well as related techniques and application in the vibrant field of IoT. We
discuss several limitations of applying recommendation systems to IoT and
propose a reference framework for comparing existing studies to guide future
research and practices.
