A machine learning-based approach for classifying tourists and locals using geotagged photos: the case of Tokyo
Author:
Funder
Japan Society for the Promotion of Science
Publisher
Springer Science and Business Media LLC
Subject
Social Sciences (miscellaneous),General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s40558-021-00208-3.pdf
Reference68 articles.
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2. Andrienko G, Andrienko N, Bosch H et al (2013) Thematic patterns in georeferenced tweets through space-time visual analytics. Comput Sci Eng 15(3):72–82. https://doi.org/10.1109/MCSE.2013.70
3. Chen M, Arribas-Bel D, Singleton A (2019a) Understanding the dynamics of urban areas of interest through volunteered geographic information. J Geogr Syst 21(1):89–109. https://doi.org/10.1007/s10109-018-0284-3
4. Chen W, Xu Z, Zheng X et al (2019b) Geo-tagged photo metadata processing method for beijing inbound tourism flow. ISPRS Int J Geo-Inf 8(12):556. https://doi.org/10.3390/ijgi8120556
5. Cristianini N, Shawe-Taylor J (2000) An introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, Cambridge. https://doi.org/10.1017/CBO9780511801389
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