Recommender Systems for the Internet of Things: A Survey
May S. Altulyan, Lina Yao, Xianzhi Wang, Chaoran Huang, Salil S. Kanhere, Quan Z. Sheng · arXiv (Cornell University) · 2020
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.