Collective Tourist Destination Recommendation: A Dynamic Trust Network-Based Fuzzy Decision-Making Model

Collective tourist destination recommendation refers to recommending tourist attractions to groups, which not only satisfies the diverse demands of consumers but also generates lucrative profits for tourism companies and further promotes macroeconomic development. However, collective recommendations are influenced by inconsistent evaluation criteria of individuals, the complexity of group decision making, and dynamically changed social relations. Hence, a dynamic trust network-based fuzzy group recommendation (DTN-FGR) model is proposed in this research. In this framework, the user-generated ratings are transformed into fuzzy preference relations (FPR) to tackle the problem of inconsistent individual evaluation criteria. Then a PageRank-based method is proposed to calculate the trust scores of each user in the trust network. Further, a mechanism for dynamic adjustment of trust networks is proposed based on dynamic decision making. Finally, a case study is carried out to verify the reliability and stability of the proposed DTN-FGR model. The results indicate that parameter variations have no effect on collective recommendations. In addition, the consensus degree of the proposed DTN-FGR model is the highest when compared with other collective recommendation models.