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An Application of Apriori Algorithm Association Rules Mining to Profiling

the Heritage Visitors of Macau

Shanshan Qi & Cora Un In Wong

Tourism College

Institute for Tourism Studies, Colina de Mong-Ha, Macao, China

{shanshan; cora}@ift.edu.mo

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Introduction• Heritage tourism has been recognised as one of the

most significant and fast growing forms of tourism (Hollinshead, 1996; Kerstetter, Confer & Bricker, 1998) and as such it has become an established research topic in tourism and heritage studies (Chandler & Costello, 2002; Nyaupane, White & Budruk, 2006).

• To develop a destination’s competitive edge, it is also useful to capture the profiles of the various types of tourists (Min, Min & Emam, 2002).

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Introduction• Tourists who travel to heritage sites tend to be

older, wealthier, and to be interested in partaking in activities that provide educational experiences (Christou, 2005).

• McKercher (2002, p. 32) indicates that there are different types of cultural tourists and that not all of them have the same level of interest and seriousness about heritage and culture. He used ‘centrality of purpose’ and ‘depth of experience’ as the core dimensions to construct his typology of cultural tourists.

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Macau

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Introduction• The official state endorsed message of local

authorities shows its determination to dilute Macau’s destination image as a “city for gambling” and to promote it as a cultural destination is evidenced since year 2005 in MGTO’s annual press releases (MGTO, 2005 to 2013).

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Research objectives• to present the top heritage sites of Macau and

their attractiveness as seen by visitors.• to identify the existing cultural tourists and

predict the demographic characteristics of future tourists who are likely to visit Macau’s top heritage sites.

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Methodology

• TripAdvisor data collection using (PHP 5.8： Hypertext Preprocessor)

• Association rule mining: Apriori algorithm

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Methodology

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Methodology

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Methodology

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Methodology

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Findings• A total of 1422 data were collected from 2005-2013 on

TripAdvisor.• The majority of reviewers are male tourists (54.4%) who

belong to two age groups: between 25 and 34 and between 35 and 49.

• The online reviewers are mainly from Japan, the Philippines, Malaysia, Australia, United Kingdom and U.S.A. In other words, most of the reviewers came from Asia, followed by Oceania, Europe, America, and Africa.

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Cultural Attractions of Macau ID No. of reviewers Ave. Score

Ruins of St. Paul 1 588 4.1Largo do Senado (The Senate Square) 2 363 4.1A-Ma Temple (Ma Kok Miu) 3 130 3.9St. Domingo's Church 4 78 4.0Guia Fortress 5 67 4.0Monte Forte (Fortaleza do Monte) 6 57 3.9Mandarin's House 7 32 4.1Leal Senado Building (Municipal Council) 8 24 3.8St. Anthony's Church 9 10 3.5Old Protestant Cemetery 10 9 3.3Cathedral 11 8 3.5Na Tcha Temple and Old City Walls 12 7 3.1Sao Agostinho’s Church 13 7 3.1St. Joseph Seminary and Church 14 7 3.7Teatro de Pedro V 15 7 3.7St. Augustine Square 16 6 3.5Sir Robert Ho Tung Library 17 5 3.6Quartel dos Mouros 18 4 3.3Casa de Lou Kau 19 3 3.3St. Lawrence's Church 20 3 3.7British East Indian Company 21 3 3.5Lilau Square 22 2 3.5Pagode Sam Cai Vu Cun (The Three Street Senate) 23 2 3.5

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FindingsID Strong association rules Support Confidence

1 Man 35-49 Europe ⇒ A-Ma Temple (Ma Kok Miu) 1.69% 0.86 2 Guia Fortress 25-34 Asia ⇒ Man 1.06% 1.36 3 Guia Fortress man 25-34 ⇒ Asia 1.06% 1.36 4 Guia Fortress 50-64 Asia ⇒ Woman 1.09% 0.88 5 Guia Fortress woman 50-64 ⇒ Asia 1.09% 0.88 6 Man 50-64 Asia ⇒ Largo do Senado (Senate Square) 1.97% 1.33 7 Largo do Senado (Senate Square) 50-64 Asia ⇒ Man 1.97% 4.67 8 Largo do Senado (Senate Square) Man Asia ⇒ 50-64 1.97% 1.56 9 Largo do Senado (Senate Square) Woman 35-49 ⇒ Asia 4.43% 0.88

10 Mandarin's House 35-49 Asia ⇒ Man 1.41% 1.67 11 Mandarin's House Man Asia ⇒ 35-49 1.41% 2.22 12 Mandarin's House Man 35-49 ⇒ Asia 1.41% 1.82 13 Monte Forte (Fortaleza do Monte) 35-49 Asia ⇒ Woman 3.59% 2.68 14 Monte Forte (Fortaleza do Monte) Woman Asia ⇒ 35-49 3.59% 3.40 15 Monte Forte (Fortaleza do Monte) Woman 35-49 ⇒ Asia 3.59% 4.25 16 Man 25-34 Europe ⇒ Ruins of St. Paul's Cathedral 3.66% 1.93 17 Ruins of St. Paul's Cathedral 25-34 Europe ⇒ Man 3.66% 3.47 18 Ruins of St. Paul's Cathedral man Europe ⇒ 25-34 3.66% 1.79 19 Woman 25-34 Asia ⇒ Ruins of St. Paul's Cathedral 3.73% 1.36 20 Ruins of St. Paul's Cathedral 25-34 Asia ⇒ Woman 3.73% 1.89 21 Ruins of St. Paul's Cathedral Woman Asia ⇒ 25-34 3.73% 1.61 22 Woman 50-64 Asia ⇒ Ruins of St. Paul's Cathedral 5.84% 1.20 23 Ruins of St. Paul's Cathedral 50-64 Asia ⇒ Woman 5.84% 2.13 24 Ruins of St. Paul's Cathedral Woman 50-64 ⇒ Asia 5.84% 2.18 25 Woman 50-64 Europe ⇒ Ruins of St. Paul's Cathedral 1.48% 2.10 26 Ruins of St. Paul's Cathedral 50-64 Europe ⇒ Woman 1.48% 1.91 27 Ruins of St. Paul's Cathedral Woman Europe ⇒ 50-64 1.48% 0.88 28 St. Domingo's Church 25-34 Asia ⇒ Woman 1.69% 1.71 29 St. Domingo's Church Woman Asia ⇒ 25-34 1.69% 1.20 30 St. Domingo's Church Woman 25-34 ⇒ Asia 1.69% 2.18

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FindingsID Regions Support Confidence America 1 A-Ma Temple (Ma Kok Miu) Woman 35-49 ⇒ USA 5% 0.83 2 Woman 25-34 Canada ⇒ Ruins of St. Paul's Cathedral 8% 1.60 3 Ruins of St. Paul's Cathedral Woman 35-49 ⇒ USA 8% 1

Asia

1 Woman 25-34 Indonesia 4 ⇒ Largo do Senado 1.76% 1.05 2 Woman 50-64 Japan 3 ⇒ Largo do Senado (Senate Square) 1.07% 1.38 3 Largo do Senado (Senate Square) Woman 50-64 3 ⇒ Japan 1.07% 1.83 4 Largo do Senado (Senate Square) Woman 50-64 Japan ⇒ 3 1.08% 1.22 5 Mandarin's House 35-49 Japan 4 ⇒ Man 1.04% 1 6 Man 25-34 India 4 ⇒ Ruins of St. Paul's Cathedral 1.03% 0.80 7 Man 25-34 Indonesia 4 ⇒ Ruins of St. Paul's Cathedral 1.85% 2.71 8 Ruins of St. Paul's Cathedral Woman 35-49 3 ⇒ Japan 2.01% 1.40

Oceania

1 Largo do Senado (Senate Square) 35-49 Australia 4 ⇒ Man 1.03% 1.02 2 Ruins of St. Paul's Cathedral Woman 35-49 Australia ⇒ 3 2.76% 1.30

Europe

1 Woman 35-49 UK 5 ⇒ Ruins of St. Paul's Cathedral 1.02% 0.80 2 Ruins of St. Paul's Cathedral Woman 35-49 5 ⇒ UK 1.02% 0.85 3 Ruins of St. Paul's Cathedral Woman 35-49 UK ⇒ 5 1.02% 0.90 4 Ruins of St. Paul's Cathedral Man 35-49 Germany ⇒ 4 1.02% 0.84 5 Ruins of St. Paul's Cathedral Man 25-34 Italy ⇒ 5 1.02% 0.81

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Conclusion• The main source of data is user-generated content, which is

volunteered and bereft of any interference from the researchers. They represent the natural thoughts of the informants regarding their experience of Macau.

• Association Rule Mining was the second analytical method used to obtain an estimation of the demographic profile of prospective tourists who will be interested in various cultural sites of Macau.

• Macau cultural attractions were given an over-average and tourists were generally satisfied their experience on visiting these attractions. Yet some cultural sites remain scantly visited and the core reasons are inaccessibility, lack of interpretation, or a combination of both.

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Limitations• More advanced data mining analytical methods in the

future can be used to analyze the collected data from TripAdvisor which are better for mining large number of rules.

• A large number of Chinese online reviewers have been ignored. It is due to some of the Chinese travellers choose to reveal their travel experiences in other social media exchange platforms, such as DaoDao (TripAdvisor in China) and Ctrip.com.

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Thank You

Questions & Answers