A Comprehensive Study of Recommender Systems for the Internet of Things. Issue 1 (July 2021)

• Record Type: Journal Article
• Authors: Mudita, ; Gupta, Deepali
• Is Part Of: Journal of physics. Volume 1969:Issue 1(2021)
• Publication Date: 2021-07
• Subjects: Internet of Things -- Recommender System -- Collaborative filtering -- Content-based filtering -- Knowledge-based filtering -- Content-Aware filtering -- Hybrid filtering; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1969/1/012045
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Internet of Things (IoT) is an advancing technology that is a network of many smart devices connected together to provide services to various application domains such as smart offices, health monitoring, agriculture, etc. IoT-based recommendation technologies are becoming one of the key requirements that will recommend future IoT solutions. A review of existing recommendation technologies in the vibrant field of IoT is discussed in this paper. The main aim of this paper is to present a comprehensive analysis of existing literature on recommendation approaches. Several issues of applying recommendation systems to IoT are also discussed. Nearly 1000 research papers have been considered for analyses which are published by ACM, Springer, IEEE and Science Direct from 2011 to 2017. Finally, the recent research trends are spotted for future researchers intended to work in the recommendation-based IoT domain. Moreover, this paper also envisages the future of the Recommender System (RS) that opens up the newest research directions for young researchers.