#Tourism Destination Recommender
This project aims to develop a robust tourism destination recommender system leveraging user preferences, travel history, and ratings. Built using SQL, Python, and the Thinkter library, this recommender system provides personalized recommendations for travelers seeking new destinations to explore.
Key Features:
User Preference Analysis: Utilizes user input and preferences to tailor recommendations. Travel History Integration: Incorporates past travel data to suggest new and diverse destinations. Rating-based Recommendations: Considers ratings and reviews to ensure high-quality recommendations. Interactive Interface: Designed using the Thinkter library to provide a user-friendly and intuitive experience. Scalable SQL Database: Stores and manages user data efficiently for seamless recommendation generation. How to Use:
Input Preferences: Users provide their preferences, travel history, and ratings. Generate Recommendations: The system analyzes input data and generates personalized destination recommendations. Explore Destinations: Users receive a list of recommended destinations based on their preferences and ratings. Feedback Loop: Users can provide feedback on recommended destinations, further enhancing future recommendations. Technologies Used:
#SQL: For data storage and management. #Python: For backend logic and recommendation algorithms. #Thinkter Library: For building an interactive user interface.