584 citations · 1.5k across the 28 of their papers we have counts for
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Feature Selection for Recommender Systems with Quantum Computing
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
The promise of quantum computing to open new unexplored possibilities in several scientific fields has been long discussed, but until recently the lack of a functional quantum comp…
Measuring the User Satisfaction in a Recommendation Interface with Multiple Carousels
Nicolò Felicioni, Maurizio Ferrari Dacrema, Paolo Cremonesi
It is common for video-on-demand and music streaming services to adopt a user interface composed of several recommendation lists, i.e. widgets or swipeable carousels, each generate…
A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels
Nicolò Felicioni, Maurizio Ferrari Dacrema, Paolo Cremonesi
Many video-on-demand and music streaming services provide the user with a page consisting of several recommendation lists, i.e. widgets or swipeable carousels, each built with a sp…
On the instability of embeddings for recommender systems: the case of Matrix Factorization
Giovanni Gabbolini, Edoardo D'Amico, Cesare Bernardis +1
Most state-of-the-art top-N collaborative recommender systems work by learning embeddings to jointly represent users and items. Learned embeddings are considered to be effective to…