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 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC) |
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 |
Publisher | IEEE |
Publication date | 2018 |
Pages | 159-164 |
ISBN (Print) | 978-1-5386-2667-2 |
ISBN (Electronic) | 978-1-5386-2666-5 |
DOIs | |
Publication status | Published - 2018 |
Event | 2018 IEEE 42nd Annual Computer Software and Applications Conference - Tokyo, Japan Duration: 23 Jul 2018 → 27 Jul 2018 Conference number: 42 https://ieeexplore.ieee.org/xpl/conhome/8376143/proceeding |
Conference
Conference | 2018 IEEE 42nd 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
- Tourism data analysis
- Unsupervised machine learning
- Behavior prediction
- Data visualization
- Case study