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With demand changing for Chinese tourists who is the one of the largest markets in Japan inbound, so it is necessary to grasp their travel behaviors. Furthermore, according to the sites where tourists have traveled and evaluation for tourists' intention, it is possible to understand the reason and background of the tourism behavior and can consider the future tourism behavior trends. Therefore, we focus on the contents of the trip and travel literature which wrote by Chinese travelers, using a topic model which is one of the functions for machine learning,through calculate the similarities of travel literature contents to cluster the travel literature. Our study aims at grasping the intention and behavior of Chinese tourists. As a result of analyzing 16734 travel literature which is automatically collected from website,we got classified 152 topics. Based on the classified result, we clarified the intention and behavior of Chinese tourists who visited Japan.