16 citations · 23 across the 9 of their papers we have counts for
3 papers · 1 filter
Eco-Aware Graph Neural Networks for Sustainable Recommendations
Antonio Purificato, Fabrizio Silvestri
Recommender systems play a crucial role in alleviating information overload by providing personalized recommendations tailored to users' preferences and interests. Recently, Graph…
A Reproducible Analysis of Sequential Recommender Systems
Filippo Betello, Antonio Purificato, Federico Siciliano +4
Sequential Recommender Systems (SRSs) have emerged as a highly efficient approach to recommendation systems. By leveraging sequential data, SRSs can identify temporal patterns in u…
Sheaf4Rec: Sheaf Neural Networks for Graph-based Recommender Systems
Antonio Purificato, Giulia Cassarà, Federico Siciliano +2
Recent advancements in Graph Neural Networks (GNN) have facilitated their widespread adoption in various applications, including recommendation systems. GNNs have proven to be effe…