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ISPRS Int. J. Geo-Inf. 2017, 6(11), 345; https://doi.org/10.3390/ijgi6110345

Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr

1,2
,
2
,
2
and
3,4,*
1
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
2
Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China
3
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
4
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
*
Author to whom correspondence should be addressed.
Received: 9 September 2017 / Revised: 4 October 2017 / Accepted: 2 November 2017 / Published: 7 November 2017
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Abstract

With millions of people traveling to unfamiliar cities to spend holidays, travel recommendation becomes necessary to assist tourists in planning their trips more efficiently. Serving as a prerequisite to travel recommender systems, understanding tourist behavior patterns is therefore of great importance. Recently, geo-tagged photos on social media platforms like Flickr have provided a rich data source that captures location histories of tourists and reflects their preferences. This article utilizes geo-tagged photos from Flickr to extract trajectories of tourists and then extends the concept of motifs from topological spaces, to temporal spaces and to semantic spaces, for detecting tourist mobility patterns. By representing trajectories in terms of three distinct types of travel motif and further using them to measure user similarity, typical tourist travel behavior patterns associated with distinct sightseeing tastes/preferences are identified and analyzed for tourism recommendation. Our empirical results confirm that the proposed analytical framework is effective to uncover meaningful tourist behavior patterns. View Full-Text
Keywords: geo-tagged photo; tourist mobility; travel motif; popular landmark; user clustering geo-tagged photo; tourist mobility; travel motif; popular landmark; user clustering
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Yang, L.; Wu, L.; Liu, Y.; Kang, C. Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr. ISPRS Int. J. Geo-Inf. 2017, 6, 345.

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