IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-319-14343-9_11.html
   My bibliography  Save this book chapter

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

In: Information and Communication Technologies in Tourism 2015

Author

Listed:
  • Shanshan Qi

    (Tourism College)

  • Cora Un In Wong

    (Tourism College)

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.

Suggested Citation

  • Shanshan Qi & Cora Un In Wong, 2015. "An Application of Apriori Algorithm Association Rules Mining to Profiling the Heritage Visitors of Macau," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 139-151, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-14343-9_11
    DOI: 10.1007/978-3-319-14343-9_11
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-319-14343-9_11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.