A method of modeling of basic big data analysis for Korean medical tourism: A machine learning approach using apriori algorithm

Abstract

The Republic of Korea (ROK) has emerged as a country of superior medical tourism in the last decade among the people of China, Japan, Southeast Asia, Russia and the Middle East for the plastic surgery or others requiring precision skills. Although the ROK’s medical tourism industry grew quantitatively in its revenue and the number of visitors, the report from the 2015 World Economic Forum concerning the competitiveness of ROK’s tourism including the medical tourism showed that its rank had dropped to 29th position, a drop of 4 places from 25th in 2013. Thus, it is about time to improve the situation by investigating the actual conditions of tours taken by the foreign tourists to establish new strategy, which is the main contribution of this research. As a research method, a big data analysis has been performed on the basis of machine learning and using R-studio. During the analysis process, there were some relevant regularities which were difficult to be found in the big data and based on these findings, we have attempted to find the solutions for the bad images that foreign visitors had shared in common. The result of the big data analysis showed that the their purpose of visit was different from each other depending on the age groups and the details of their experience of inconvenience varied as well.