Tour-sites Recommendation Mechanism for Navigation System

This work proposed a hierarchical tour-sites recommendation mechanism based on tourist group which is context, location, and time awareness. This mechanism includes two parts, Inter-site and Intra-site. We adopted the Artificial Fish Swarm Algorithm (AFSA) to build this two parts tour-sites recommendation mechanism. In the Inter-site recommendation, we combined Co-occurrence concept to predict the interest of tourists. We formulate the problem of choosing the paths among the vehicles in the same region by using non-cooperative game theory, and find out the solution of this game which is known as Nash equilibrium. This mechanism determined on reducing the average waiting time of tourist and balancing the congestion degree of sites in a city and presents a recommendation mechanism for vehicle-sharing. Moreover, it took the demand of tourists into consideration. The experimental results showed that the mechanism we proposed improve the tourism experience for tourist groups.