Attentive Contextual Denoising Autoencoder for Recommendation

  title={Attentive Contextual Denoising Autoencoder for Recommendation},
  author={Yogesh Jhamb and Travis Ebesu and Yi Fang},
Personalized recommendation has become increasingly pervasive nowadays. Users receive recommendations on products, movies, point-of-interests and other online services. Traditional collaborative filtering techniques have demonstrated effectiveness in a wide range of recommendation tasks, but they are unable to capture complex relationships between users and items. There is a surge of interest in applying deep learning to recommender systems due to its nonlinear modeling capacity and recent… CONTINUE READING