Enhanced hotel recommendation method addressing the deviation between overall rating and detailed criteria ratings on Tripadvisor.com

Article type: Research Article

Authors: Zhong, Leiguang | Luo, Yiyue | Zhang, Xin | Zhang, Hongyu^{; *} | Wang, Jianqiang

Affiliations: School of Business, Central South University, Changsha, China

Correspondence: [*] Corresponding author. Hongyu Zhang, School of Business, Central South University, Changsha, China. E-mail: hyzhang@csu.edu.cn.

Abstract: User rating information on multiple predefined aspects gathered by hotel recommendation systems generally shows a deviation between the overall rating and detailed criteria ratings. In this study, to address this deviation, we proposed a novel hotel recommendation method that clusters users with different preferences into different groups using the K-means algorithm. Moreover, we allocated weights to different criteria and obtained a comprehensive score. A case study on actual data from Tripadvisor.com showed that compared with three other models, our proposed model demonstrated a more impressive performance. This research can offer advantages to hotel service providers and customers in terms of decision making.

Keywords: Recommender system, hotel recommendation, multi criteria rating, K-means, Tripadvisor.com

DOI: 10.3233/JIFS-201577

Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 3, pp. 4705-4720, 2021