A fuzzy ubiquitous traveler clustering and hotel recommendation system by differentiating travelers’ decision-making behaviors - Chen, Toly (Applied soft computing, 2020)
For generating hotel recommendations, clustering travelers has been demonstrated to be a viable method to elevate traveler satisfaction with the recommendation results. However, most of the existing methods that adopt this approach cluster travelers according to a variety of traveler or hotel attributes, which may not necessarily be appropriate for use in an online application such as ubiquitous hotel recommendation. To overcome this problem, a fuzzy ubiquitous traveler clustering and hotel recommendation (FUTCHR) system was developed in this study. The FUTCHR system clustered travelers according to their decision-making mechanisms that are fitted by comparing travelers’ choices with the recommendation results in the historical data. To generate recommendations, a fuzzy mixed binary-nonlinear programming model was constructed and solved. The novelty of the proposed methodology is to cluster travelers without knowing their characteristics but according to the differences in their decision-making mechanisms. The FUTCHR system was employed in a regional study, and the successful recommendation rate was superior to three existing methods in this field. •A fuzzy ubiquitous traveler clustering and hotel recommendation system is developed.•Travelers are clustered according to their decision-making mechanisms instead of their or hotels’ attributes.•A regional study is conducted to assess the effectiveness of the proposed methodology.