184 citations · 185 across the 2 of their papers we have counts for
2 papers
cs.IR2019★ 184 cited
RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback
Ilya Shenbin, Anton Alekseev, Elena Tutubalina +2
Recent research has shown the advantages of using autoencoders based on deep neural networks for collaborative filtering. In particular, the recently proposed Mult-VAE model, which…
cs.CL2019★ 1 cited
AspeRa: Aspect-based Rating Prediction Model
Sergey I. Nikolenko, Elena Tutubalina, Valentin Malykh +2
We propose a novel end-to-end Aspect-based Rating Prediction model (AspeRa) that estimates user rating based on review texts for the items and at the same time discovers coherent a…