A Survey of Recommender Systems Based on Deep Learning
At a glance
- Citations
- 252
- References
- 148
- Comments
- 0
Abstract
In recent years, deep learning’s revolutionary advances in speech recognition, image analysis, and natural language processing have gained significant attention. Deep learning technology has become a hotspot research field in the artificial intelligence and has been applied into recommender system. In contrast to traditional recommendation models, deep learning is able to effectively capture the non-linear and non-trivial user-item relationships and enables the codification of more complex abstractions as data representations in the higher layers. In this paper, we provide a comprehensive review of the related research contents of deep learning-based recommender systems. First, we introduce the basic terminologies and the background concepts of recommender systems and deep learning technology. Second, we describe the main current research on deep learning-based recommender systems. Third, we provide the possible research directions of deep learning-based recommender systems in the future. Finally, concludes this paper.
Publication details
- DOI
- 10.1109/access.2018.2880197
- OpenAlex
- W2899849645
- Document type
- article
- Language
- EN
- Source
- IEEE Access
- Last metadata update
Comments
Log in to join the discussion.