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A Survey of Recommender Systems Based on Deep Learning - 2018

Research Area:  Machine Learning

Abstract:

In recent years, deep learnings 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.

Author(s) Name:  Ruihui Mu

Journal name:   IEEE Access

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/ACCESS.2018.2880197

Volume Information:  Volume: 6, pp 69009 - 69022