Abstract
The significant economic contributions of the fast growing tourism industry have drawn worldwide attention on understanding the behavioral and demographic patterns of visitors. This research makes an attempt to develop a rough sets based model that can capture the essential information from business travelers, a segment of the market that to date has been entirely overlooked by academic researchers in data mining. Utilizing the primary data collected from an Omnibus survey carried out in Hong Kong in late 2005, experimental findings showed that the induced decision rules could classify 82% of the cases in the testing set and 41% of the classified cases were correctly estimated. Most importantly, there was no statistically significant difference between the estimated values and actual values.
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Law, R., Bauer, T., Weber, K., Tse, T. (2006). Towards a Rough Classification of Business Travelers. In: Li, X., Zaïane, O.R., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2006. Lecture Notes in Computer Science(), vol 4093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11811305_14
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DOI: https://doi.org/10.1007/11811305_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37025-3
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