Abstract
This paper presents an ongoing public-private innovation project that integrates unsupervised machine learning tools and a marketing theory, in order to analyze segment-based attitudes and behaviors of tourists. Our case study involving the major governmental tourism stakeholders emphasizes the importance of developing a user-friendly data analytic pipeline that carefully considers users' data collection procedure, easy access to the back-office computation algorithms, an interactive output data analysis workflow and its visualization. At the end of this paper, we present our vision to further develop a cloud-based tourist data collection platform.
Original language | English |
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Title of host publication | Proceedings of the 42nd IEEE Annual Computer Software and Applications Conference : COMPSAC 2018. Volume 2 |
Editors | Sorel Reisman, Sheikh Iqbal Ahamed, Claudio Demartini, Thomas Conte, William Claycomb, Motonori Nakamura, Edmundo Tovar, Stelvio Cimato, Chung-Horng Lung, Hiroki Takakura, Ji-Jiang Yang, Toyokazu Akiyama, Zhiyong Zhang, Kamrul Hasan |
Number of pages | 6 |
Place of Publication | Los Alamitos, CA |
Publisher | IEEE |
Publication date | 2018 |
Pages | 159-164 |
Article number | 8377849 |
ISBN (Print) | 9781538626665 |
ISBN (Electronic) | 9781538626665 |
DOIs | |
Publication status | Published - 2018 |
Event | 42nd IEEE Annual Computer Software and Applications Conference: COMPSAC 2018 - Tokyo, Japan Duration: 23 Jul 2018 → 27 Jul 2018 Conference number: 42 https://ieeecompsac.computer.org/2018/ |
Conference
Conference | 42nd IEEE Annual Computer Software and Applications Conference |
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Number | 42 |
Country/Territory | Japan |
City | Tokyo |
Period | 23/07/2018 → 27/07/2018 |
Internet address |
Keywords
- Behavior prediction
- Case study
- Data visualization
- Tourism data analysis
- Unsupervised machine learning