Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77544
Title: Travel diaries analysis by sequential rule mining
Authors: Vu, HQ
Li, G
Law, R 
Zhang, Y
Keywords: Data mining
Flickr
Geotagged photo
Sequential rule mining
Travel diary
Issue Date: 2018
Publisher: SAGE Publications
Source: Journal of travel research, 2018, v. 57, no. 3, p. 399-413 How to cite?
Journal: Journal of travel research 
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.
URI: http://hdl.handle.net/10397/77544
ISSN: 0047-2875
EISSN: 1552-6763
DOI: 10.1177/0047287517692446
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