3 citations · 4 across the 2 of their papers we have counts for
3 papers
Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation
Daniele Malitesta, Claudio Pomo, Tommaso Di Noia
Graph neural networks (GNNs) have gained prominence in recommendation systems in recent years. By representing the user-item matrix as a bipartite and undirected graph, GNNs have d…
Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara +5
Recommender Systems have shown to be an effective way to alleviate the over-choice problem and provide accurate and tailored recommendations. However, the impressive number of prop…
An Empirical Study of DNNs Robustification Inefficacy in Protecting Visual Recommenders
Vito Walter Anelli, Tommaso Di Noia, Daniele Malitesta +1
Visual-based recommender systems (VRSs) enhance recommendation performance by integrating users' feedback with the visual features of product images extracted from a deep neural ne…