The exponentially growing availability of online information calls for personalized search and recommendation. Such systems provide recommendations typically based on user profiles built taking into account user actions. Not yet fully explored, is the domain of context-aware recommendation. In this article, we introduce a novel approach, where user profiling and context-based data filtering both concur to recommendation production. Based on the aforementioned approach, UTravel is a smart mobility application that recommends points of interest (POIs) to end users. After describing the UTravel architecture and implementation, we present the results of an experimental evaluation we carried out involving both simulated and real users.
['Michele Amoretti', 'Laura Belli', 'Francesco Zanichelli']
UTravel: Smart mobility with a novel user profiling and recommendation approach