Agent-based Personalized Tourist Route Advice System

This paper proposes a tourist route model that is based on the integration of GIS spatial analysis functions and a kind of heuristic search algorithm based on local optimisation. A vector-based model is used to represent tourists’ personal interests and the available tourist resources. Based on these two representations, the system can build a user model that indicates the attractions values of the tourist features in a particular area to individual tourists. The route agent then uses this user model to generate personalized tourist routes. This research adopts a Tabu search method, called extension/collapse algorithm, that is applied in the operations research for maximizing some utilities under certain constraints. It is a heuristic search method that progressively selects each tourist site based on both its attraction value and the cost value. An empirical evaluation has been carried out on the personalized route advice system. The result suggests that the tourist route model generates tourist routes that are empirically consistent with the tourists’ preferences.