Identifying places of interest for tourists using knowledge discovery techniques

Abstract

Tourism is one of the most significant industries all across the globe. Information technology plays an indispensable role in promoting the industry. We utilized a web crawler to obtain online tourists' demographics and comments. This study adopts a new perspective in analyzing tourists' profiles where both quantitative (data mining) and qualitative analysis methods were performed on the data collected from one of the most frequently visited travel websites. Results from both data analysis methods that supported each other were used to build a more definite model. In this study, results show there were different groups of tourist with each group having diverse preferences. For instance, local visitors of Legoland were not satisfied with some drawbacks such as the food price whereas, international visitors praised for their enjoyable experiences spent with families. Findings from this study are useful for tourism organizations in Malaysia. Additionally, the research method using both quantitative (data mining) and qualitative methods in this study is found unique and rare in social studies.