Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/77544
DC Field | Value | Language |
---|---|---|
dc.contributor | School of Hotel and Tourism Management | en_US |
dc.creator | Vu, HQ | en_US |
dc.creator | Li, G | en_US |
dc.creator | Law, R | en_US |
dc.creator | Zhang, Y | en_US |
dc.date.accessioned | 2018-08-28T01:33:07Z | - |
dc.date.available | 2018-08-28T01:33:07Z | - |
dc.identifier.issn | 0047-2875 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/77544 | - |
dc.language.iso | en | en_US |
dc.publisher | SAGE Publications | en_US |
dc.rights | © The Author(s) 2018 Reprints and permissions: sagepub.com/journalsPermissions.nav | en_US |
dc.rights | This is the accepted version of the publication Vu, H. Q., Li, G., Law, R., & Zhang, Y. Travel diaries analysis by sequential rule mining, Journal of Travel Research (vol. 57, no. 3), pp. 399-413. Copyright © 2018 (The Author(s) ). DOI: 10.1177/0047287517692446 which is published by Sage and is available at https://journals.sagepub.com/doi/10.1177/0047287517692446 | en_US |
dc.subject | Data mining | en_US |
dc.subject | Flickr | en_US |
dc.subject | Geotagged photo | en_US |
dc.subject | Sequential rule mining | en_US |
dc.subject | Travel diary | en_US |
dc.title | Travel diaries analysis by sequential rule mining | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 399 | en_US |
dc.identifier.epage | 413 | en_US |
dc.identifier.volume | 57 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.doi | 10.1177/0047287517692446 | en_US |
dcterms.abstract | Because of the inefficiency in analyzing the comprehensive travel data, tourism managers are facing the challenge of gaining insights into travelers’ behavior and preferences. In most cases, existing techniques are incapable of capturing the sequential patterns hidden in travel data. To address these issues, this article proposes to analyze the travelers’ behavior through geotagged photos and sequential rule mining. Travel diaries, constructed from the photo sequences, can capture comprehensive travel information, and then sequential patterns can be discovered to infer the potential destinations. The effectiveness of the proposed framework is demonstrated in a case study of Australian outbound tourism, using a data set of more than 890,000 photos from 3,623 travelers. The introduced framework has the potential to benefit tourism researchers and practitioners from capturing and understanding the behaviors and preferences of travelers. The findings can support destination-marketing organizations (DMOs) in promoting appropriate destinations to prospective travelers. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of travel research, 1 Mar. 2018, v. 57, no. 3, p. 399-413 | en_US |
dcterms.isPartOf | Journal of travel research | en_US |
dcterms.issued | 2018-03-01 | - |
dc.identifier.isi | WOS:000424059300009 | - |
dc.identifier.scopus | 2-s2.0-85041565097 | - |
dc.identifier.eissn | 1552-6763 | en_US |
dc.identifier.rosgroupid | 2017002003 | - |
dc.description.ros | 2017-2018 > Academic research: refereed > Publication in refereed journal | en_US |
dc.description.validate | 201808 bcrc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a0267-n01, a0635-n03 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingText | GRF: 15503814 | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Vu_Travel_Diraries_Analysis.pdf | Pre-Published version | 1.46 MB | Adobe PDF | View/Open |
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