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Tourist Guide AI

Aditya Ramu Pardesi, Rajapandi Nadar, Atharva Gai, Manish Kumar, Prof. Vishal Patil

D.Y.Patil University, Ambi

Pune, India

Abstract—The research paper presents an innovative AI-driven platform that revolutionizes the landscape of personalized travel recommendations within specific cities. Leveraging the power of Artificial Intelligence (AI), the "Tourist Guide AI" system offers curated suggestions for attractions, activities, and dining options based on individual preferences. The platform integrates machine learning algorithms, geospatial data, and natural language processing to provide comprehensive insights into city attractions, ensuring a personalized and enriching travel experience. The deployment phase involves launching the system on cloud servers, ensuring widespread accessibility and scalability to accommodate varying user demands. The methodology employed encompasses rigorous data collection, preprocessing, and the implementation of a recommendation algorithm that combines collaborative and contentbased filtering techniques. The user interface is designed with intuitiveness and user-friendliness at its core, ensuring an intuitive experience for travelers of all backgrounds. The platform's advantages include personalized recommendations, efficient trip planning, real-time updates, and potential integration with mobile devices for on-the-go guidance. The research paper also acknowledges potential disadvantages and limitations, such as data accuracy, privacy concerns, and limited coverage for remote or lessvisited destinations, emphasizing the commitment to continuous improvement and expansion of coverage. The "Tourist Guide AI" project represents a significant step towards simplifying and enriching the tourist planning process, ensuring that each trip is a unique and tailored adventure for travelers of all backgrounds and preferences.

Keywords—Tourist Guide AI, places recommendation, OpenAI APIs, Tourism form AI,Content Based Filtering, Vectorization  .