activity
20192022
most citedUser and Item-aware Estimation of Review Helpfulness

31 citations · 93 across the 5 of their papers we have counts for

collaborators

12 papers

cs.IR20228 cited

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…

cs.IR202215 cited

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…

cs.IR202031 cited

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…

cs.HC202019 cited

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…

cs.IR202020 cited

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…

cs.IR2020

Impact of Semantic Granularity on Geographic Information Search Support

Noemi Mauro, Liliana Ardissono, Laura Di Rocco +2

The Information Retrieval research has used semantics to provide accurate search results, but the analysis of conceptual abstraction has mainly focused on information integration.…