A Linked Open Data Based Approach for Trip Recommendation

International audienceA huge amount of Tourism information is provided through myriad Web services. Travelers who want to plan their trips have to sift through a large pool of Web services before figuring out the best itinerary of places to visit. Such a process gets even more tedious when travelers need to satisfy specific constraints such as visit time and price. In this paper, we propose a linked open data (LOD) service recommendation approach to help travelers plan their trips (i.e., a sequence of places to visit) given a set of preferences and constraints. The proposed approach runs a three-step process. The first step consists of annotating a set of touristic Web services with LOD resources that describe their capabilities. The second step matches user constraints and preferences with Web service provided touristic information and returns a pre-list of itineraries. The third step runs a LOD-based matching between services to improve trips recommendation. Experiments conducted on real data show promising results