Identifying tourist route patterns using data mining techniques
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 u...
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my.uum.repo.133132015-03-08T03:14:43Z http://repo.uum.edu.my/13313/ Identifying tourist route patterns using data mining techniques Warintarawej, P. Chaikong, K. Kadedaiwang, P. Onsrithong, P. Laksanajan, P. Siwyew, S. G Geography (General) QA Mathematics 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. 2014-11-05 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/13313/1/31.pdf 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. http://www.thic-uum.com/ |
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G Geography (General) QA Mathematics Warintarawej, P. Chaikong, K. Kadedaiwang, P. Onsrithong, P. Laksanajan, P. Siwyew, S. Identifying tourist route patterns using data mining techniques |
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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. |
format |
Conference or Workshop Item |
author |
Warintarawej, P. Chaikong, K. Kadedaiwang, P. Onsrithong, P. Laksanajan, P. Siwyew, S. |
author_facet |
Warintarawej, P. Chaikong, K. Kadedaiwang, P. Onsrithong, P. Laksanajan, P. Siwyew, S. |
author_sort |
Warintarawej, P. |
title |
Identifying tourist route patterns using data mining techniques |
title_short |
Identifying tourist route patterns using data mining techniques |
title_full |
Identifying tourist route patterns using data mining techniques |
title_fullStr |
Identifying tourist route patterns using data mining techniques |
title_full_unstemmed |
Identifying tourist route patterns using data mining techniques |
title_sort |
identifying tourist route patterns using data mining techniques |
publishDate |
2014 |
url |
http://repo.uum.edu.my/13313/1/31.pdf http://repo.uum.edu.my/13313/ http://www.thic-uum.com/ |
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1644281150069276672 |