A Method of Modeling of Basic Big Data Analysis for Korean Medical Tourism: A Machine Learning Approach Using Apriori Algorithm
A Method of Modeling of Basic Big Data Analysis for Korean Medical Tourism: A Machine Learning Approach Using Apriori Algorithm
复制标题
韩国医疗旅游基础大数据分析建模方法：使用 Apriori 算法的机器学习方法
DOI：
10.1007/978-981-10-4154-9_91
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发表时间：
2017
期刊：
影响因子：
1.9
通讯作者：
Jinmo Kim
中科院分区：
文献类型：
--
作者：
Jun;Han;Jinmo Kim
在过去的十年里，韩国已经成为中国、日本、东南亚、俄罗斯和中东地区整形手术或其他需要精密技能的人中的一个高级医疗旅游国家。尽管韩国医疗旅游业的收入和游客数量都有所增长，但2015年世界经济论坛关于包括医疗旅游在内的韩国旅游业竞争力的报告显示，韩国的排名从2013年的第25位下降到第29位，下降了4位。因此，通过调查外国游客参加旅游的实际情况来制定新的策略来改善这一状况是时候了，这是本研究的主要贡献。作为研究方法，在机器学习的基础上，利用R-STUDIO进行了大数据分析。在分析过程中，发现了一些在大数据中很难找到的相关规律，并基于这些发现，试图为外国游客共同分享的不良形象找到解决方案。大数据分析的结果显示，不同年龄段的游客的旅游目的不同，不方便体验的细节也不同。
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.