@article{oai:muroran-it.repo.nii.ac.jp:00010328,
 author = {TOSPORN, Arreeras and 有村,  幹治 and ARIMURA, Mikiharu and ASADA, Takumi and 浅田, 拓海 and SAHARAT, Arreeras},
 issue = {14},
 journal = {Sustainability},
 month = {},
 note = {application/pdf, The rise of radiofrequency scanner technology has led to its potential application in the observation of people’s movements. This study used aWi-Fi scanner device to track tourists’ traveling behavior inHokkaido’s tourismarea,whichoccupies a large regionthat features auniquenatural landscape. Inbound tourists have significantly increased in recent years; thus, tourism’s sustainability is considered to be important formaintaining the tourismatmosphere in the long term. Using internet-enabled technology to conduct extensive area surveys can overcome the limitations imposed by conventional methods. This study aims to use digital footprint data to describe and understand traveler mobility in a large tourism area in Hokkaido. Association rule mining (ARM)—a machine learning methodology—was performed on a large dataset of transactions to identify the rules that link destinations visited by tourists. This process resulted in the discovery of traveling patterns that revealed the association rules between destinations, and the attractiveness of the destinations was scored on the basis of visiting frequency, with both inbound and outbound movements considered. A visualization method was used to illustrate the relationships between destinations and simplify the mathematical descriptions of traveler mobility in an attractive tourism area. Hence, mining the attractiveness of destinations in a large tourism area using an ARMmethod integrated with aWi-Fi mobility tracking approach can provide accurate information that forms a basis for developing sustainable destination management and tourism policies.},
 title = {Association Rule Mining Tourist-Attractive Destinations for the Sustainable Development of a Large Tourism Area in Hokkaido Using Wi-Fi Tracking Data},
 volume = {11},
 year = {2019},
 yomi = {アリムラ, ミキハル and アサダ, タクミ}
}