Research Article
Recommendation System Comparative Analysis: Internet of Things aided Networks
@ARTICLE{10.4108/eetiot.v8i29.1108, author={Wasswa Shafik and S. Mojtaba Matinkhah and Fawad Shokoor}, title={Recommendation System Comparative Analysis: Internet of Things aided Networks}, journal={EAI Endorsed Transactions on Internet of Things}, volume={8}, number={29}, publisher={EAI}, journal_a={IOT}, year={2022}, month={5}, keywords={Companion Recommendations, Privacy, Security, Social Networks Systems}, doi={10.4108/eetiot.v8i29.1108} }
- Wasswa Shafik
S. Mojtaba Matinkhah
Fawad Shokoor
Year: 2022
Recommendation System Comparative Analysis: Internet of Things aided Networks
IOT
EAI
DOI: 10.4108/eetiot.v8i29.1108
Abstract
Today, the public is not willing to spend much time identifying their personal needs. Therefore, it needs a system that automatically recommends customized items to customers. The Recommender system has an internet of things (IoT) that entails a subclass of evidenced-based sieving structures that pursues to forecast the assessment of a customer would stretch to an item. Within social networks, numerous categories of RS operate on different recommendation expertise. In this state-of-the-art, we describe and classify current studies from three different aspects by describing different methods of recommender systems. The Friend Recommendation System in social networks is necessary and inevitable, and it is due to this kind of coordination that inevitably recommends latent friends to customers. Making recommendations for friends is an imperative assignment for community networks, as obligating supplementary networks customarily superiors to enhanced customer experience.
Copyright © 2022 Wasswa Shafik et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.