Self-attention based time-rating-aware context recommender system

HIGHLIGHTS

  • who: Yongfu Zha and collaborators from the College of Computer and Information Science Chongqing Normal University, Chongqing, China have published the Article: Self-Attention Based Time-Rating-Aware Context Recommender System, in the Journal: Computational Intelligence and Neuroscience of 17/09/2022
  • what: The study of_[30] pointed out that users` preferences are affected by different types of contexts, and the reasonable use of contextual information by the recommender system is beneficial to the recommended performance. To demonstrate the effectiveness of the SATRAC model, the authors compare SATRAC with the following baselines, which include some . . .

     

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