Ontology-Based Matchmaking to Provide Personalized Recommendations for Tourists.

This paper addresses the challenges to support tourists in their decision-making during the pre-trip phase and to facilitate the process of identifying those tourism objects that best fit the tourists’ preferences. The latter directly depends on the quality of the matchmaking process, i.e. finding those tourism objects that are most attractive to a particular tourist. To achieve this goal, an innovative approach is introduced that matches tourist profiles with the characteristics of tourism objects in order to obtain a ranked list of appropriate objects for a particular tourist. The matchmaking process leverages tourist factors as a shortcut to propose a first user profile and related to this, a first set of tourism objects. User feedback is then used to dynamically adapt the tourist profile and thus refine the set of recommended objects. Our approach is tested through a prototypical recommender system that suggests tourists in Vienna attractions that are tailored to their personal needs. Furthermore, a user study is conducted by asking people to interact with the system and fill in a questionnaire afterwards.