23 citations · 56 across the 18 of their papers we have counts for
4 papers · 1 filter
Multi-Step Critiquing User Interface for Recommender Systems
Diana Petrescu, Diego Antognini, Boi Faltings
Recommendations with personalized explanations have been shown to increase user trust and perceived quality and help users make better decisions. Moreover, such explanations allow…
Rationalization through Concepts
Diego Antognini, Boi Faltings
Automated predictions require explanations to be interpretable by humans. One type of explanation is a rationale, i.e., a selection of input features such as relevant text snippets…
Fast Multi-Step Critiquing for VAE-based Recommender Systems
Diego Antognini, Boi Faltings
Recent studies have shown that providing personalized explanations alongside recommendations increases trust and perceived quality. Furthermore, it gives users an opportunity to re…
Recommending Burgers based on Pizza Preferences: Addressing Data Sparsity with a Product of Experts
Martin Milenkoski, Diego Antognini, Claudiu Musat
In this paper, we describe a method to tackle data sparsity and create recommendations in domains with limited knowledge about user preferences. We expand the variational autoencod…