Multicriteria Recommendation Method of Tourist Routes Based on Tourist Clustering

A multicriteria recommendation algorithm for tourist routes under the multidimensional expanded spatial grid structure model based on fuzzy C-means clustering of preferences is proposed. The purpose proposed to improve intelligent ability popular core circle. enlarged well-known circle used develop correlation travel restricted sample training. Under traveler circle’s framework, mixed kernel use and global are created extract characteristics route recommendation. circle, adaptive learning selection carried out using hybrid particle swarm algorithm. To manage convergence suggestion process, maps logistical chaos employed, utilizing culture’s universalism ergodicity resources examining aesthetic along tourism routes. simulation results demonstrate that extended model’s information accuracy decent, a solid intelligence junction observed in this analysis, preventing recommendations from settling local optimal solution enhancing their stability.