A Hybrid Recommendation System for Personalized Travel Experiences and Enhanced Tourism Sector Efficiency

The study looks at how crucial it is to have individualized visitor information systems in order to maximize the travel industry's economic potential. The research findings introduces a novel hybrid method that combines content- based algorithms with collaborative filtering algorithms to provide tourists accurate and personalized recommendations. To make these recommendations more accurate, item comparison using TF-IDF and cosine similarity is utilized. To ensure that it is applicable to a broad audience, the research expands its scope to include data on tourists from both India and throughout the world. In order to improve the entire user experience, an intuitive interface is developed and visual material, such as photographs, is integrated. It can be done using a user- centric approach. The research advances the tourism business by focusing on efficiency and relevancy, which benefits travelers as well as the industry as a whole.