31 citations · 93 across the 5 of their papers we have counts for
14 papers
Justification of Recommender Systems Results: A Service-based Approach
Noemi Mauro, Zhongli Filippo Hu, Liliana Ardissono
With the increasing demand for predictable and accountable Artificial Intelligence, the ability to explain or justify recommender systems results by specifying how items are sugges…
Using consumer feedback from location-based services in PoI recommender systems for people with autism
Noemi Mauro, Liliana Ardissono, Stefano Cocomazzi +1
When suggesting Points of Interest (PoIs) to people with autism spectrum disorders, we must take into account that they have idiosyncratic sensory aversions to noise, brightness an…
User and Item-aware Estimation of Review Helpfulness
Noemi Mauro, Liliana Ardissono, Giovanna Petrone
In online review sites, the analysis of user feedback for assessing its helpfulness for decision-making is usually carried out by locally studying the properties of individual revi…
Session-aware Recommendation: A Surprising Quest for the State-of-the-art
Sara Latifi, Noemi Mauro, Dietmar Jannach
Recommender systems are designed to help users in situations of information overload. In recent years, we observed increased interest in session-based recommendation scenarios, whe…
Faceted Search of Heterogeneous Geographic Information for Dynamic Map Projection
Noemi Mauro, Liliana Ardissono, Maurizio Lucenteforte
This paper proposes a faceted information exploration model that supports coarse-grained and fine-grained focusing of geographic maps by offering a graphical representation of data…
Personalized Recommendation of PoIs to People with Autism
Noemi Mauro, Liliana Ardissono, Federica Cena
The suggestion of Points of Interest to people with Autism Spectrum Disorder (ASD) challenges recommender systems research because these users' perception of places is influenced b…