Tourists from certain regions tend to visit certain places when traveling abroad. The availability of large amounts of data from social media sites allows researchers to profile their tendencies, which could be useful for many applications such as route recommendations or advertisements. We propose a method to infer the home location of a tourist, based on their travel route, using the extracted tendency for each country. Our approach uses supervised machine learning methods to learn the quantized travel route of each user. In this paper, we use foreign travelers in Japan as a case study. We evaluate the performance of our proposed method by using photographs collected from their user accounts on Flickr.