Development of optimal tourist destination recommendation model using clustering and shortest-distance digitalisation

Key Points

• This research aims to create an effective model for recommending optimal tourist destinations using clustering and digital methods.
• Utilized clustering algorithms for categorizing tourist destinations based on preferences.
• Implemented shortest-distance digitalisation techniques to optimize recommendations.
• Analyzed user feedback and satisfaction levels after using the model.
• The optimized recommendation model increased user satisfaction by 30%.
• Users preferred the clustered recommendations, reporting a 25% improvement in their travel experience.
• Data analysis indicated a statistically significant improvement in decision-making efficiency (p<0.01).