Social Tagging for Personalized Location-Based Services
Claudio Biancalana, Fabio Gasparetti, Alessandro Micarelli, Giuseppe Sansonetti · 2011
The current generation of location-based services (LBSs) does not provide users with personalized recommendations, but only suggests nearby points of interest (POIs) based on their distance from the user current location. To overcome such a limitation, we have realized a social recommender system able to identify user preferences and information ne-eds, thus suggesting personalized recommendations related to possible POIs in the surroundings. The proposed approach allows users to leverage and assign freely chosen keywords (tags) to resources through collaborative tagging services (fol-ksonomies). Our LBS employs a user-based tag model that derives correspondences between personal tag vocabularies (personomies) and folksonomies. Experimental tests per-formed on 15 real users enabled us to assess the benefits in terms of performance that our approach is able to provide. Author Keywords