Case Study of Tourism Course Recommendation System Using Data from Social Network Services
Shizune Takahashi, Shuang Li, Keizo Yamada, Masanori Takagi, Jun Sasaki · Frontiers in artificial intelligence and applications · 2017
There are strong expectations that growth in Japan's tourism industry will stimulate regional economies. The present study aimed to create a system for recommending itineraries, including little-known local attractions, to visiting tourists. In previous research, we developed the Tourism Destination Finding System, which uses data on social network services (SNSs). In the Recommendation System, which suggests tourist itineraries using data on SNSs. Toward verifying the effectiveness of this system, this paper presents a case study; it involved collecting and analyzing photo data and check-in data to identify tourist attractions on Google Heat Maps of Iwate Prefecture. From this case study, we were able to confirm that our proposed system is able to recommend an appropriate itinerary for tourists with limited time.