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An Application of Apriori Algorithm Association Rules Mining to Profiling the Heritage Visitors of Macau

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Information and Communication Technologies in Tourism 2015

Abstract

Heritage tourism has become one of the dominant forms of tourism. It is particularly important for Macau as a means to diversify Macau’s destination image from being exclusively a gaming city to a city of culture and events. Yet little is known about the success of the official re-positioning campaign. In particular what is attractive to cultural tourists remain understudied. This study adopts Apriori Algorithm Association Rules Mining to segment Macau’s tourists and to predict tourists’ preferences for the different local heritage attractions. User-generated data of TripAdvisor were the major source of data for the analysis. The findings of this paper show that the so-called “cultural tourists” who are interested in Macau heritage attractions appear to have profiles that are similar to those who are “non-cultural tourists”. It appears that the “cultural tourists” visited only a few renowned heritage sites. It is suggested that Macau is not yet successfully attracting large amount of visitors who are interested in heritage and culture. This study showcases a use of data mining method in tourism studies.

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Authors and Affiliations

  1. Institute for Tourism Studies, Tourism College, Macao, China

    Shanshan Qi & Cora Un In Wong

Authors
  1. Shanshan Qi
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  2. Cora Un In Wong
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Corresponding author

Correspondence to Shanshan Qi .

Editor information

Editors and Affiliations

  1. School of Hospitality Business Management, Carson College of Business, Washington State University, Vancouver, Washington, USA

    Iis Tussyadiah

  2. Faculty of Management, Bournemouth University, Poole, Dorset, United Kingdom

    Alessandro Inversini

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Qi, S., Wong, C.U.I. (2015). An Application of Apriori Algorithm Association Rules Mining to Profiling the Heritage Visitors of Macau. In: Tussyadiah, I., Inversini, A. (eds) Information and Communication Technologies in Tourism 2015. Springer, Cham. https://doi.org/10.1007/978-3-319-14343-9_11

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