期刊文献+

A Prediction Study on the Localization Policy of Improving the Satisfaction of Chinese Visitors to Japan by Using Matrix Factorization Techniques

A Prediction Study on the Localization Policy of Improving the Satisfaction of Chinese Visitors to Japan by Using Matrix Factorization Techniques
原文传递
导出
摘要 Against the background of the rapid growth of Chinese tourists to Japan,by observing the changes in the patterns of Chinese visitors to Japan and probing into the insufficiency of researches in the past studies,it is believed that online travel reviews can be used to present the current situation of tourism industry and be of value to provide the basic data for long-term sustainable research after analysis,including how to increase Chinese tourists’satisfaction continuously and how to promote the service level of related industries.In this study,the unknown information caused by the cultural and regional differences in the reviews of Chinese visitors’to Japan is taken as the prediction object and the local tourists’travel comments as a reference group.Then,the factor decomposition technology and text mining technology are applied to predict the standards of services and projects that can meet the characteristics and demands of Chinese tourists.The comments of Chinese and Japanese tourists who stayed at hotels in the Hakone scenic area from May 2018 to April 2019(time span:one year)are taken as the samples in this study.Thus,the disparity in the purpose of travel between Chinese tourists and Japanese local tourists in this scenic spot can be effectively displayed.Besides,it also clearly points out that due to a lack of understanding of Japanese food culture,Chinese visitors were in urgent need of relevant services and assistance.Therefore,this method will provide guidance for the growth of the local tourism industry and also demonstrate the feasibility of research methods.In the end,a complete analysis and calculation method for online comment text mining is established,which also provides guidance on improving the satisfaction of Chinese visitors to Japan.Besides,this method can also be considered to apply in more tourists with the same cultural background. Against the background of the rapid growth of Chinese tourists to Japan, by observing the changes in the patterns of Chinese visitors to Japan and probing into the insufficiency of researches in the past studies, it is believed that online travel reviews can be used to present the current situation of tourism industry and be of value to provide the basic data for long-term sustainable research after analysis, including how to increase Chinese tourists’ satisfaction continuously and how to promote the service level of related industries. In this study, the unknown information caused by the cultural and regional differences in the reviews of Chinese visitors’ to Japan is taken as the prediction object and the local tourists’ travel comments as a reference group. Then, the factor decomposition technology and text mining technology are applied to predict the standards of services and projects that can meet the characteristics and demands of Chinese tourists. The comments of Chinese and Japanese tourists who stayed at hotels in the Hakone scenic area from May 2018 to April 2019(time span: one year)are taken as the samples in this study. Thus, the disparity in the purpose of travel between Chinese tourists and Japanese local tourists in this scenic spot can be effectively displayed. Besides, it also clearly points out that due to a lack of understanding of Japanese food culture, Chinese visitors were in urgent need of relevant services and assistance. Therefore, this method will provide guidance for the growth of the local tourism industry and also demonstrate the feasibility of research methods. In the end, a complete analysis and calculation method for online comment text mining is established, which also provides guidance on improving the satisfaction of Chinese visitors to Japan. Besides, this method can also be considered to apply in more tourists with the same cultural background.
机构地区 Architecture
出处 《Journal of Systems Science and Information》 CSCD 2019年第6期510-531,共22页 系统科学与信息学报(英文)
关键词 online travel reviews matrix factorization latent factors CHINESE VISITORS to JAPAN PREDICTION STUDY SCENIC area online travel reviews matrix factorization latent factors Chinese visitors to Japan prediction study scenic area
  • 相关文献

参考文献2

二级参考文献44

  • 1安辉,付蓉.影响旅游者主观风险认知的因素及对旅游危机管理的启示[J].浙江学刊,2005(1):196-200. 被引量:38
  • 2何凡,沈毅,叶众.CHAID方法在居民卫生服务需求研究中的应用[J].数理统计与管理,2006,25(4):484-491. 被引量:14
  • 3杜强,贾丽艳.SPSS统计分析:从入门到精通[M].北京:人民邮电出版社,2011:262.
  • 4Baloglu S. The relationship between destination images and sociodemographic and trip characteristics of international travellers [J]. Journal of Vacation Marketing, 1997, 3(3): 221- 233.
  • 5Srnmez S F, Graefe A R. Influences of terrorism risk on foreign tourism decision [J]. Annals of Tourism Research, 1998, 25(1): 112-144.
  • 6Lepp A, Gibson H. Tourist roles, perceived risk and international tourism [J]. Annals of Tourism Research, 2003, 30 (3): 606-624.
  • 7Wong J Y, Yeh C. Tourist hesitation in destination decision making [J]. Annals of Tourism Research, 2009, 36(1): 6-23.
  • 8Bronner F, de Hoog R. Economizing strategies during an economic crisis [J]. Annals of Tourism Research, 2012, 39(2): 1048-1069.
  • 9Ture M, Tokatli F, Kurt I. Using Kaplan - Meier analysis together with decision tree methods (C&RT, CHAID, QUEST, C4. 5 and ID3) in determining recurrence-free survival of breast cancer patients[J]. Expert Systems with Applications, 2009, 36(2): 2017- 2026.
  • 10Kass G V. An exploratory technique for investigating large quantities of categorical data[J]. Applied Statisties, 1980, 29(2): 119-127.

共引文献129

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部