Please use this identifier to cite or link to this item: https://doi.org/10.1145/2168752.2168770
Title: Mining travel patterns from geotagged photos
Authors: Zheng, Y.-T.
Zha, Z.-J. 
Chua, T.-S. 
Keywords: Geotagged photos
Travel pattern mining
Issue Date: 2012
Source: Zheng, Y.-T., Zha, Z.-J., Chua, T.-S. (2012). Mining travel patterns from geotagged photos. ACM Transactions on Intelligent Systems and Technology 3 (3). ScholarBank@NUS Repository. https://doi.org/10.1145/2168752.2168770
Abstract: Recently, the phenomenal advent of photo-sharing services, such as Flickr and Panoramio, have led to volumous community-contributed photos with text tags, timestamps, and geographic references on the Internet. The photos, together with their time- and geo-references, become the digital footprints of photo takers and implicitly document their spatiotemporal movements. This study aims to leverage the wealth of these enriched online photos to analyze people's travel patterns at the local level of a tour destination. Specifically, we focus our analysis on two aspects: (1) tourist movement patterns in relation to the regions of attractions (RoA), and (2) topological characteristics of travel routes by different tourists. To do so, we first build a statistically reliable database of travel paths from a noisy pool of community-contributed geotagged photos on the Internet. We then investigate the tourist traffic flow among different RoAs by exploiting the Markov chain model. Finally, the topological characteristics of travel routes are analyzed by performing a sequence clustering on tour routes. Testings on four major cities demonstrate promising results of the proposed system. © 2012 ACM 2157-6904/2012/05-ART56 $10.00.
Source Title: ACM Transactions on Intelligent Systems and Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/39885
ISSN: 21576904
DOI: 10.1145/2168752.2168770
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