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  • 标题:Deep Learning-Based Recommendation: Current Issues and Challenges
  • 本地全文:下载
  • 作者:Rim Fakhfakh ; Anis Ben Ammar ; Chokri Ben Amar
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2017
  • 卷号:8
  • 期号:12
  • DOI:10.14569/IJACSA.2017.081209
  • 出版社:Science and Information Society (SAI)
  • 摘要:Due to the revolutionary advances of deep learning achieved in the field of image processing, speech recognition and natural language processing, the deep learning gains much attention. The recommendation task is influenced by the deep learning trend which shows its significant effectiveness and the high-quality of recommendations. The deep learning based recommender models provide a better detention of user preferences, item features and users-items interactions history. In this paper, we provide a recent literature review of researches dealing with deep learning based recommendation approaches which are preceded by a presentation of the main lines of the recommendation approaches and the deep learning techniques. We propose also classification criteria of the different deep learning integration model. Then we finish by presenting the recommendation approach adopted by the most popular video recommendation platform YouTube which is based essentially on deep learning advances.
  • 关键词:Recommender system; deep learning; neural network; YouTube recommendation
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