Turist@: Agent-based personalised recommendation of tourist activities

TLDR: A novel recommendation system, [email protected], which incorporates a mixture of content-based and collaborative recommendation strategies, thus avoiding the drawbacks of each individual method, and is able to perform recommendations in heterogeneous scenarios.

Abstract: Recommender systems in e-Tourism normally focus on helping tourists to select appropriate destinations. A related problem that has been less explored in the literature is how to provide personalised recommendations of cultural and leisure activities when the tourist has already arrived at the destination. This paper presents a novel recommendation system, [email protected], which addresses this issue. Its agent-based modular design permits to model different kinds of activities in a flexible way, and allows the implementation of a location-aware front-end in the mobile device of the user. Special care has been put in the recommendation engine, implemented via a specialised Recommender Agent. It incorporates a mixture of content-based and collaborative recommendation strategies, thus avoiding the drawbacks of each individual method, and is able to perform recommendations in heterogeneous scenarios. Recommendations take into account user profiles which are implicitly updated after the analysis of user actions (e.g., queries, evaluations). The system has been successfully deployed and tested in the World Heritage-listed city of Tarragona.