110 citations · 253 across the 15 of their papers we have counts for
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cs.IR2019
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…
cs.IR2019★ 25 cited
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…