A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation

Hefei University of Technology · University of Science and Technology of China · +1 more institution

Indexed inarxivcrossref

Abstract

Influenced by the great success of deep learning in computer vision and language understanding, research in recommendation has shifted to inventing new recommender models based on neural networks. In recent years, we have witnessed significant progress in developing neural recommender models, which generalize and surpass traditional recommender models owing to the strong representation power of neural networks. In this survey paper, we conduct a systematic review on neural recommender models, aiming to summarize this field to facilitate researchers and practitioners working on recommender systems. Specifically, based on the data usage during recommendation modeling, we divide the work into collaborative…

Citation impact

395
total citations
FWCI
121.71
Percentile
100%
References
346
Citations per year

Authors

5

Topics & keywords

Keywords
  • Recommender system
  • Computer science
  • Collaborative filtering
  • Field (mathematics)
  • Information retrieval
  • Artificial neural network
  • Representation (politics)
  • Artificial intelligence
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