Predicting the Next Scenic Spot a User Will Browse on a Tourism Website Based on Markov Prediction Model

In order to handle the information overload on the tourism websites and understand user's travel preference, we propose to build a users' preference matrix to reflect the users' preference degree on a set of scenic spots, and then propose a method of combining user clustering with Markov chain to predict the next scenic spot a user will browse on a tourism website. The experimental results indicate that the preference matrix can catch the travel preference of users and the proposed method can be used for predicting the next browsing behaviors of users.