Enhancing User Experience in Smart Tourism via Fuzzy Logic-Based Personalization

In the era of smart tourism, providing seamless and personalized experiences has become significant for enhancing user satisfaction and engagement. This paper presents a novel fuzzy logic-based application system designed to enhance personalization in smart tourism. The proposed system integrates real-time user data and delivers customized services to each particular user. In particular, the proposed system incorporates a recommendation mechanism that combines TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) with fuzzy logic to assess multiple criteria and user preferences and provide accurate and well-rounded personalized travel destination recommendations. By employing fuzzy logic, the system effectively overcomes challenges associated with uncertainty and subjectivity in user data, enabling precise and adaptable decision-making and ensuring more accurate service recommendations. Through case studies and simulations, the paper evaluates the system's impact on enhancing user satisfaction and the overall tourism experience. Furthermore, preliminary evaluation results demonstrate the system's ability to generate meaningful and seamless personalized recommendations that enhance the provided tourism services. This work contributes to the growing field of smart tourism by offering a scalable and user-centric solution. The scalability of the system is ensured through its efficient handling of multidimensional data, adaptability to diverse user profiles, and extendability to various tourism applications, including destination ranking, activity recommendations, and hotel selection. Additionally, its integration potential with existing travel platforms highlights its applicability in real-world scenarios, making it a robust tool for enhancing smart-tourism experiences.