• Corpus ID: 216080737

Conditioned Variational Autoencoder for top-N item recommendation

@article{Polato2020ConditionedVA,
  title={Conditioned Variational Autoencoder for top-N item recommendation},
  author={Mirko Polato and Tommaso Carraro and Fabio Aiolli},
  journal={ArXiv},
  year={2020},
  volume={abs/2004.11141}
}
In this paper, we propose a Conditioned Variational Autoencoder (C-VAE) for constrained top-N item recommendation where the recommended items must satisfy a given condition. The proposed model architecture is similar to a standard VAE in which the condition vector is fed into the encoder. The constrained ranking is learned during training thanks to a new reconstruction loss that takes the input condition into account. We show that our model generalizes the state-of-the-art Mult-VAE… 

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