Clustering using ordered weighted averaging operator and 2-tuple linguistic model for hotel segmentation: The case of TripAdvisor

作者：

Highlights：

• A novel MCDM approach based on OWA and the 2-tuple linguistic model is proposed.

• Renamed linguistic quantifiers to reflect customer demand degrees are presented.

• Over 50 million TripAdvisor hotel reviews are applied to evaluate its functionality.

• The proposed model improves clustering results and linguistic interpretability.

• This approach helps to create personalized hotel rankings with customer preferences.

摘要

•A novel MCDM approach based on OWA and the 2-tuple linguistic model is proposed.•Renamed linguistic quantifiers to reflect customer demand degrees are presented.•Over 50 million TripAdvisor hotel reviews are applied to evaluate its functionality.•The proposed model improves clustering results and linguistic interpretability.•This approach helps to create personalized hotel rankings with customer preferences.

论文关键词：Ordered weighted averaging operators,Linguistic quantifiers,2-tuple linguistic model,Multi-criteria decision-making,Segmentation,TripAdvisor

论文评审过程：Received 5 April 2022, Revised 30 July 2022, Accepted 25 September 2022, Available online 30 September 2022, Version of Record 14 October 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118922