110 citations · 253 across the 15 of their papers we have counts for
6 papers · 1 filter
How to make latent factors interpretable by feeding Factorization machines with knowledge graphs
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio +2
Model-based approaches to recommendation can recommend items with a very high level of accuracy. Unfortunately, even when the model embeds content-based information, if we move to…
On the discriminative power of Hyper-parameters in Cross-Validation and how to choose them
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio +2
Hyper-parameters tuning is a crucial task to make a model perform at its best. However, despite the well-established methodologies, some aspects of the tuning remain unexplored. As…
Knowledge-aware Autoencoders for Explainable Recommender Sytems
Vito Bellini, Angelo Schiavone, Tommaso Di Noia +2
Recommender Systems have been widely used to help users in finding what they are looking for thus tackling the information overload problem. After several years of research and ind…
Computing recommendations via a Knowledge Graph-aware Autoencoder
Vito Bellini, Angelo Schiavone, Tommaso Di Noia +2
In the last years, deep learning has shown to be a game-changing technology in artificial intelligence thanks to the numerous successes it reached in diverse application fields. Am…
The importance of being dissimilar in Recommendation
Vito Walter Anelli, Joseph Trotta, Tommaso Di Noia +2
Similarity measures play a fundamental role in memory-based nearest neighbors approaches. They recommend items to a user based on the similarity of either items or users in a neigh…
Local Popularity and Time in top-N Recommendation
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio +2
Items popularity is a strong signal in recommendation algorithms. It strongly affects collaborative filtering approaches and it has been proven to be a very good baseline in terms…