Recommender Systems for the Internet of Things: A Survey

• URL: http://arxiv.org/abs/2007.06758v1
• Date: Tue, 14 Jul 2020 01:24:44 GMT
• Title: Recommender Systems for the Internet of Things: A Survey
• Authors: May Altulyan, Lina Yao, Xianzhi Wang, Chaoran Huang, Salil S Kanhere, Quan Z Sheng
• Abstract summary: Recommendation represents a vital stage in developing and promoting the benefits of the Internet of Things. Traditional recommender systems fail to exploit ever-growing, dynamic, and heterogeneous IoT data.
• Score: 53.865011795953706
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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