Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/77590
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Land Surveying and Geo-Informatics | - |
dc.creator | Yang, L | - |
dc.creator | Wu, L | - |
dc.creator | Liu, Y | - |
dc.creator | Kang, C | - |
dc.date.accessioned | 2018-08-28T01:33:25Z | - |
dc.date.available | 2018-08-28T01:33:25Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/77590 | - |
dc.language.iso | en | en_US |
dc.publisher | Molecular Diversity Preservation International (MDPI) | en_US |
dc.rights | © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Yang, L., Wu, L., Liu, Y., & Kang, C. (2017). Quantifying tourist behavior patterns by travel motifs and geo-tagged photos from flickr. Isprs International Journal of Geo-Information, 6(11), (Suppl. ), 2419, - is available athttps://dx.doi.org/10.3390/ijgi6110345 | en_US |
dc.subject | Geo-tagged photo | en_US |
dc.subject | Popular landmark | en_US |
dc.subject | Tourist mobility | en_US |
dc.subject | Travel motif | en_US |
dc.subject | User clustering | en_US |
dc.title | Quantifying tourist behavior patterns by travel motifs and geo-tagged photos from flickr | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 6 | - |
dc.identifier.issue | 11 | - |
dc.identifier.doi | 10.3390/ijgi6110345 | - |
dcterms.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. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | ISPRS international journal of geo-information, Nov. 2017, v. 6, no. 11, 2419, p. 1-18 | - |
dcterms.isPartOf | ISPRS international journal of geo-information | - |
dcterms.issued | 2017 | - |
dc.identifier.isi | WOS:000416779300026 | - |
dc.identifier.scopus | 2-s2.0-85041535245 | - |
dc.identifier.eissn | 2220-9964 | - |
dc.identifier.artn | 2419 | - |
dc.description.validate | 201808 bcrc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Yang_Quantifying_Tourist_Behavior.pdf | 6.23 MB | Adobe PDF | View/Open |
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