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arXiv · 2007.06758

Recommender Systems for the Internet of Things: A Survey

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

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.

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May Altulyan, Lina Yao, Xianzhi Wang, Chaoran Huang, Salil S Kanhere, Quan Z Sheng. 2020-07-14. Recommender Systems for the Internet of Things: A Survey. https://arxiv.org/abs/2007.06758

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