963 citations · 2.4k across the 9 of their papers we have counts for
5 papers · 1 filter
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks
Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi +1
Session-based recommendations are highly relevant in many modern on-line services (e.g. e-commerce, video streaming) and recommendation settings. Recently, Recurrent Neural Network…
Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
Balázs Hidasi, Alexandros Karatzoglou
RNNs have been shown to be excellent models for sequential data and in particular for data that is generated by users in an session-based manner. The use of RNNs provides impressiv…
Session-based Recommendations with Recurrent Neural Networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas +1
We apply recurrent neural networks (RNN) on a new domain, namely recommender systems. Real-life recommender systems often face the problem of having to base recommendations only on…
Context-aware recommendations from implicit data via scalable tensor factorization
Balázs Hidasi, Domonkos Tikk
Albeit the implicit feedback based recommendation problem - when only the user history is available but there are no ratings - is the most typical setting in real-world application…
Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback
Balázs Hidasi, Domonkos Tikk
Albeit, the implicit feedback based recommendation problem - when only the user history is available but there are no ratings - is the most typical setting in real-world applicatio…