# Recommender Systems for the Internet of Things: A Survey

arXiv: https://arxiv.org/abs/2007.06758 · HTML: https://mlsanity.com/paper/2007.06758/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jul 2020.

## Built on by (most cited first, 1 of 1)

- [Edge Data Based Trailer Inception Probabilistic Matrix Factorization for Context-Aware Movie Recommendation](https://mlsanity.com/paper/2202.10236/) (2022)

## Abstract (arXiv)

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.