vastly diverse backgrounds, and therefore cannot be easily inte-grated. Furthermore, when a traveler begins to consider a trip, he or she has less than evident inclinations, especially when planning to visit a foreign location (Loh et al., 2003). Therefore, the purpose of this study is to eliminate for travelers the uncertainties involved in the information search stage of a buyer’s decision process, while also avoiding unnecessary costs. To ensure the integrity, accuracy and practicality of the ITAS, this study follows the following proce-dure: (1) extract measures from EBM model for tourist attractions;
(2) collect data from ‘‘2007 Annual Survey Report on Visitors Expenditure and Trends in Taiwan’’ published by the Tourism Bu-reau of Taiwan; (3) calculate probability of a tourist attraction appealing to a particular tourist by utilizing Bayesian network;
(4) verify accuracy of the prediction by ROC curve test; and (5) present recommended routes and tourist attractions through system with Google Maps.