Warintarawej, P. and Chaikong, K. and Kadedaiwang, P. and Onsrithong, P. and Laksanajan, P. and Siwyew, S. (2014) Identifying tourist route patterns using data mining techniques. In: 2nd Tourism and Hospitality International Conference (THIC 2014), 5-6 November 2014, Langkawi, Malaysia.

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Abstract

In this study, researchers applied data mining techniques to reveal tourist route patterns to popular destinations in Surat Thani Province in southern Thailand. Data mining refers to the process of discovering patterns in large data.Two data mining techniques were employed: 1) Cluster analysis was used to identify unique clusters of tourists with common behavioral trends. 2) Association rule mining was used to determine tourist route patterns.From these two data mining techniques, the researchers were able to identify unique clusters of tourists who followed common patterns of travel.The main implications of this study are: 1) that data mining may be used to explain the movement of tourists in any region in the world, and 2) that different facets of the tourism industry can use this information to understand and respond to tourists' needs and interests.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	ISBN:978-983-2078-83-8 Organized by: School of Tourism, Hospitality and Environmental Management, Universiti Utara Malaysia
Uncontrolled Keywords:	Data mining, Cluster analysis, Association rule mining, Tourist behavior, Tourism route patterns
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) Q Science > QA Mathematics
Divisions:	College of Law, Government and International Studies
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	08 Mar 2015 03:14
Last Modified:	08 Mar 2015 03:14
URI:	https://repo.uum.edu.my/id/eprint/13313

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