A Linked Open Data Based Approach for Trip Recommendation

Abstract

A 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.