68 citations · 336 across the 43 of their papers we have counts for
4 papers · 1 filter
On the Impact of Communities on Semi-supervised Classification Using Graph Neural Networks
Hussain Hussain, Tomislav Duricic, Elisabeth Lex +2
Graph Neural Networks (GNNs) are effective in many applications. Still, there is a limited understanding of the effect of common graph structures on the learning process of GNNs. I…
Listener Modeling and Context-aware Music Recommendation Based on Country Archetypes
Markus Schedl, Christine Bauer, Wolfgang Reisinger +2
Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a considerable extent, in country-specific music listeni…
Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering
Tomislav Duricic, Hussain Hussain, Emanuel Lacic +3
In this work, we study the utility of graph embeddings to generate latent user representations for trust-based collaborative filtering. In a cold-start setting, on three publicly a…
Utilizing Human Memory Processes to Model Genre Preferences for Personalized Music Recommendations
Dominik Kowald, Elisabeth Lex, Markus Schedl
In this paper, we introduce a psychology-inspired approach to model and predict the music genre preferences of different groups of users by utilizing human memory processes. These…