Optimizing User Experience in Mobile Travel Applications: A Study on Personalized Routing, Thematic Content, and Cultural Engagement

This paper presents an AI-powered personalized trip planner designed to enhance travel experiences in Sri Lanka. The platform integrates advanced machine learning techniques, including K-Nearest Neighbor (KNN) and Ant Colony Optimization (ACO), to generate customized travel itineraries that align with user preferences, budgetary considerations, and optimal seasonal factors. The system incorporates Natural Language Processing (NLP) for precise location-based promotions and synchronization with users’ schedules. Furthermore, an augmented reality (AR) tour guide, developed using Unity and Vuforia, enriches tourist interaction with local heritage sites. The research also employs sentiment analysis and topic categorization to refine recommendations based on user feedback and expenditure patterns. The findings indicate that the proposed system has significant potential to enhance tourist satisfaction and contribute to sustainable tourism development in Sri Lanka.