For Discovery: Significant Factors for the Promotion of Tourist Attractions based on Individual Behaviour through Data-mining Techniques

Abstract

Abstract

As the expression goes, “Thailand is the definition of Exotic Leisure”. This paper aimed to discover the significant factors necessary for tourist attractions to promote and encourage tourists to visit based on
individual behaviour by using data-mining techniques. Three main processes were employed to identify the
critical factors, composed of developing tools, collecting data, and analysing data. Sampling was collected
from 617 tourists who had travelled to two separate areas, including those who had been to Wat Nong Waeng,
a temple in Khon Kaen, and Wat Phrathat Nadun, a temple in Maha Sarakham. The methods used to discover
the factors were decision tree and association rule. Based on the results and accuracy, 14 significant factors
were identified, including 7 factors concerning tourist attractions, 4 factors concerning government policies
and 3 factors concerning individual behaviour. Moreover, the model exhibited 76.99 % accuracy that the
constructed model could reasonably reveal the relationship between tourist attractions and travellers’
individual behaviour for the promotion of travel recommendations. Keywords: Promotion of tourist attractions, Optimisation, Data-mining techniques