Recommender Systems for the Internet of Things: A Survey

Altulyan, May, Yao, Lina, Wang, Xianzhi, Huang, Chaoran, Kanhere, Salil S, Sheng, Quan Z

arXiv.org Machine Learning 

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.

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found