摘要： ► The rapid growth of Taiwan’s economy has been accompanied by the country’s developing market for luxury products. ► To successfully establish the new market demand chain for the luxury industry in Taiwan, it is essential to understand customer preferences. ► This study proposes a data mining approach for exploring luxury products purchase behavior in Taiwan. ► This study uses the apriori algorithm and K-means algorithm for data mining. ► Knowledge extraction is the proposed suggestion to the luxury products industry for future development. The rapid growth of Taiwan’s economy has been accompanied by the country’s developing market for luxury products. To successfully establish the new market demand chain for the luxury industry in Taiwan, it is essential to understand customer preferences. Thus, this study uses an association rules approach and clustering analysis for data mining to mine knowledge among luxury product-buying customers in Taiwan. The results of knowledge extraction from data mining, illustrated as knowledge patterns, rules and knowledge maps, are used to make recommendations for future developments in the luxury products industry. 出版者： Elsevier Ltd 出版日期： 2012-09-15 出處： Expert systems with applications, 2012-09, Vol.39 (12), p.11257-11268 版權： 2012 Elsevier Ltd 識別號： ISSN: 0957-4174 識別號： EISSN: 1873-6793 識別號： DOI: 10.1016/j.eswa.2012.03.072
