This research article offers new recommendations aimed at improving travel planning using two different methods, including recommendations based on free questions and relevant comments on previously visited places. The system incorporates innovations in various areas, including artificial intelligence, natural language processing and interaction partner filtering to provide useful and relevant recommendations to passengers. In the first method, the system uses integrated tools to recommend places that match the customer’s interests by analyzing the user’s behavior and preferences in past trips. The second approach uses natural language processing algorithms to understand user input for free questions to provide more accurate and personalized recommendations. Additionally, the system uses technology to continually learn and adjust user recommendations so that recommendations can be continually improved to meet people’s needs over time. The conclusion of this article provides recommendations for the implementation and development of these recommendations in the travel and tourism industry, revealing their potential to improve the booking process and improve the overall tourist experience.