Using ANN to Analyze the Correlation Between Tourism-Related Hot Words and Tourist Numbers: A Case Study in Japan

Jui-Hung Chang, Chien Yuan Tseng, Ren Hung Hwang, Mi-Chia Ma

研究成果: Conference contribution

摘要

Google's search engine has recorded the popularity of a great number of tourism-related hot words. Prior to vacationing, many people will search the four dimensions of tourism, namely food, fashion, accommodation and transportation, on the Internet before an overseas trip. Exploring the correlation between popularity trends of tourism-related hot words and the number of tourists visiting a particular destination is a potentially valuable research area for the tourist industry. Therefore, this study counted the occurrence frequency of words related to Japanese tourism in the Google search engine and in tourism articles on electronic news websites. With these data, it calculated the Pearson correlation coefficient of the number of Taiwanese tourists visiting Japan "n" months later. Additionally, a deep learning (Artificial Neural Network) model was established, and the relationship between the popularity scores of tourism-related hot words and the interval of the number of Taiwanese tourists in Japan was examined. The research results show that the popularity of tourism-related hot words on Google is highly related to the number of Taiwanese tourists visiting Japan.

原文English
主出版物標題Proceedings - 2017 IEEE 7th International Symposium on Cloud and Service Computing, SC2 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面132-137
頁數6
2018-January
ISBN(電子)9780769563282
DOIs
出版狀態Published - 2018 三月 13
事件7th IEEE International Symposium on Cloud and Service Computing, SC2 2017 - Kanazawa, Japan
持續時間: 2017 十一月 222017 十一月 25

Other

Other7th IEEE International Symposium on Cloud and Service Computing, SC2 2017
國家Japan
城市Kanazawa
期間17-11-2217-11-25

指紋

Search engines
Websites
Internet
Neural networks
Industry
Japan
Tourists
Tourism
Deep learning
Google

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Information Systems and Management

引用此文

Chang, J-H., Tseng, C. Y., Hwang, R. H., & Ma, M-C. (2018). Using ANN to Analyze the Correlation Between Tourism-Related Hot Words and Tourist Numbers: A Case Study in Japan. 於 Proceedings - 2017 IEEE 7th International Symposium on Cloud and Service Computing, SC2 2017 (卷 2018-January, 頁 132-137). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SC2.2017.27
Chang, Jui-Hung ; Tseng, Chien Yuan ; Hwang, Ren Hung ; Ma, Mi-Chia. / Using ANN to Analyze the Correlation Between Tourism-Related Hot Words and Tourist Numbers : A Case Study in Japan. Proceedings - 2017 IEEE 7th International Symposium on Cloud and Service Computing, SC2 2017. 卷 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. 頁 132-137
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Chang, J-H, Tseng, CY, Hwang, RH & Ma, M-C 2018, Using ANN to Analyze the Correlation Between Tourism-Related Hot Words and Tourist Numbers: A Case Study in Japan. 於 Proceedings - 2017 IEEE 7th International Symposium on Cloud and Service Computing, SC2 2017. 卷 2018-January, Institute of Electrical and Electronics Engineers Inc., 頁 132-137, 7th IEEE International Symposium on Cloud and Service Computing, SC2 2017, Kanazawa, Japan, 17-11-22. https://doi.org/10.1109/SC2.2017.27

Using ANN to Analyze the Correlation Between Tourism-Related Hot Words and Tourist Numbers : A Case Study in Japan. / Chang, Jui-Hung; Tseng, Chien Yuan; Hwang, Ren Hung; Ma, Mi-Chia.

Proceedings - 2017 IEEE 7th International Symposium on Cloud and Service Computing, SC2 2017. 卷 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 132-137.

研究成果: Conference contribution

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Chang J-H, Tseng CY, Hwang RH, Ma M-C. Using ANN to Analyze the Correlation Between Tourism-Related Hot Words and Tourist Numbers: A Case Study in Japan. 於 Proceedings - 2017 IEEE 7th International Symposium on Cloud and Service Computing, SC2 2017. 卷 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 132-137 https://doi.org/10.1109/SC2.2017.27