R.I.P.
๐ป
Ghosted
Recommender Systems for the Internet of Things: A Survey
July 14, 2020 ยท The Cartographer ยท ๐ arXiv.org
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Recommender Systems for the Internet of Things: A Survey"
Evidence collected by the PWNC Scanner
Authors
May Altulyan, Lina Yao, Xianzhi Wang, Chaoran Huang, Salil S Kanhere, Quan Z Sheng
arXiv ID
2007.06758
Category
cs.IR: Information Retrieval
Cross-listed
cs.LG,
stat.ML
Citations
10
Venue
arXiv.org
Last Checked
3 days ago
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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Information Retrieval
๐
๐
Old Age
Neural Graph Collaborative Filtering
R.I.P.
๐ป
Ghosted
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
R.I.P.
๐ป
Ghosted
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
R.I.P.
๐
404 Not Found
Graph Neural Networks for Social Recommendation
R.I.P.
๐ป
Ghosted