311 citations · 752 across the 16 of their papers we have counts for
4 papers · 1 filter
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…
CommentsRadar: Dive into Unique Data on All Comments on the Web
Sergey Nikolenko, Elena Tutubalina, Zulfat Miftahutdinov +1
We introduce an entity-centric search engineCommentsRadarthatpairs entity queries with articles and user opinions covering a widerange of topics from top commented sites. The engin…
Deep Neural Models for Medical Concept Normalization in User-Generated Texts
Zulfat Miftahutdinov, Elena Tutubalina
In this work, we consider the medical concept normalization problem, i.e., the problem of mapping a health-related entity mention in a free-form text to a concept in a controlled v…
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…