Bayesian intelligent semantic mashup for tourism

A common perception is that there are two competing visions for the future evolution of the Web: the Semantic Web and Web 2.0. In fact, Semantic Web technologies must integrate with Web 2.0 services for both to leverage each other's strengths. This paper illustrates how Semantic Web technologies can support information integration and make it easy to create semantic mashups. An intelligent recommendation system for tourism is presented to show the efficiency of our method. Through the ontology of tourism, the system allows the integration of heterogeneous online travel information. An integrated knowledge process is developed to guarantee the whole engineering procedure. Based on the Bayesian network technique, the system recommends tourist attractions to a user by taking into account the travel behavior both of the user and of other users.