Personalized Recommendation Intelligent Fuzzy Clustering Model for theTourism
DOI:
https://doi.org/10.69996/jcai.2024024Keywords:
Fuzzy Model, Recommendation System, Classification, Artificial Intelligence, Satisfaction LevelAbstract
Personalized recommendations in tourism have transformed the way travellers explore new
destinations, offering tailored experiences that align with individual preferences and interests. As the
travel industry increasingly harnesses data analytics and artificial intelligence, tourists can now receive
customized suggestions that reflect their unique tastes, whether they seek adventure, relaxation, cultural
immersion, or culinary exploration. This paper explores the implementation and effectiveness of
intelligent tourism management strategies using fuzzy clustering and personalized recommendations. By
analyzing various scenarios, including baseline, personalized recommendations, dynamic pricing, crisis
management, and enhanced resource allocation, the study demonstrates how advanced data-driven
techniques can significantly improve key performance indicators such as visitor satisfaction, total revenue,
repeat visitation rates, and operational efficiency. The simulation results reveal that personalized
recommendations and optimized resource allocation are particularly effective in enhancing visitor
experiences and economic outcomes. Conversely, the analysis underscores the critical need for robust
crisis management strategies to maintain performance during adverse events. This research provides
valuable insights into the transformative potential of intelligent systems in modern tourism management,
offering a pathway towards more resilient and competitive tourism destinations. For instance,
personalized recommendations increased average visitor satisfaction from 7.2 to 8.5, total revenue from
$500,000 to $600,000, and the repeat visitation rate from 35% to 45%. The dynamic pricing strategy
improved visitor satisfaction to 7.8 and revenue to $550,000, while enhanced resource allocation resulted
in a satisfaction rate of 7.9 and revenue of $570,000. Conversely, crisis management showed the
importance of preparedness, as satisfaction dropped to 6.5 and revenue to $450,000. These results
underscore the critical need for robust management strategies.
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