In this paper, we develop a novel hybrid recommender system for the tourism domain, which combines (a) a Bayesian preferences elicitation component which operates by asking the user to rate generic images (corresponding to generic types of POIs) in order to build a user model and (b) a novel content-based (CB) recommendations component. The second component can in fact itself be considered a hybrid among two different CB algorithms, each exploiting one of two semantic similarity measures: a hierarchy-based and a non-hierarchy based one. The latter is the recently introduced Weighted Extended Jaccard Similarity (WEJS). We note that WEJS is employed for the first time within a recommender algorithm. We incorporate our algorithm within a real, already available at Google Play, tour-planning mobile application for short-term visitors of the popular touristic destination of Agios Nikolaos, Crete, Greece, and evaluate our approach via extensive simulations conducted on a real-world dataset constructed for the needs of the aforementioned mobile application. Our experiments verify that our algorithms result in effective personalized recommendations of touristic points of interest, while our final hybrid algorithm outperforms our exclusively content-based recommender algorithms in terms of recommendations accuracy. Specifically, when comparing the performance of several hybrid recommender system variants, we are able to come up with a “winner”: the most preferable variant of our hybrid recommender algorithm is one using a ⟨four elicitation slates, six shown images per slate⟩ pair as input to its Bayesian elicitation component. This variant combines increased precision performance with a lightweight preferences elicitation process.

The paper presents Visit Planner (ViP), a mobile application prototype that provides a solution to the challenging tourist trip design problem. ViP follows a holistic approach offering personalized recommendations for Points of Interest (POIs) based on preferences either explicitly collected by the application, or inferred by the users’ ongoing interaction with the system. ViP proposes to the final user, a trajectory of POIs calculated using an Expectation Maximization method that maximizes user satisfaction taking into consideration a variety of time and spatial constraints for both users and POIs. Additionally, POIs are divided into categories, so that a certain number of POIs from each category to be included in the final itinerary. The application is implemented as a user-interactive system that allows the flexibility for easy content adaptation and facilitates management of content and services by the user.The prototype has been implemented for Android-based smartphones, on an open application environment, using standard communication protocols and open database technology. Currently, it is applied to the city of Agios Nikolaos in Crete, and is available for download from Google play. MSC Classification: 68T20 , 68N99

The paper presents Visit Planner (ViP), a mobile application prototype that provides a solution to the challenging tourist trip design problem. ViP follows a holistic approach offering personalized recommendations for Points of Interest (POIs) based on preferences either explicitly collected by the application, or in34 ferred by the users’ ongoing interaction with the system. ViP proposes to the final user, a trajectory of POIs calculated using an ExpectationMaximization method that maximizes user satisfaction taking into consideration a variety of time and spatial constraints for both users and POIs. Additionally, POIs are divided into categories, so that a certain number of POIs from each category to be included in the final itinerary. The application is implemented as a user-interactive system that allows the flexibility for easy content adaptation and facilitates management of content and services by the user. The prototype has been implemented for Android-based smartphones, on an open application environment, using standard communication protocols and open database technology. Currently, it is applied to the city of Agios Nikolaos in Crete, and is available for download from Google play.