Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77590
Title: Quantifying tourist behavior patterns by travel motifs and geo-tagged photos from flickr
Authors: Yang, L
Wu, L
Liu, Y
Kang, C 
Keywords: Geo-tagged photo
Popular landmark
Tourist mobility
Travel motif
User clustering
Issue Date: 2017
Publisher: Molecular Diversity Preservation International (MDPI)
Source: ISPRS international journal of geo-information, 2017, v. 6, no. 11, 2419 How to cite?
Journal: ISPRS international journal of geo-information 
Abstract: Withmillions 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 touristmobility 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.
URI: http://hdl.handle.net/10397/77590
EISSN: 2220-9964
DOI: 10.3390/ijgi6110345
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