Enhancing Tourism Experience in Sri Lanka through Data Driven Recommendations

Prescriptive systems used today have expanded to such an extent that it can be said to be one of the essential needs of man. These systems are designed to help users choose the best option based on their preferences. In this paper, a system called TourBuddy is proposed with the aim of solving and improving the existing problems in the Sri Lankan tourism industry. This system is also a recommendation system based on personalized recommendations. The system utilizes machine learning algorithms and large amounts of data, and the proposed mobile application aims to provide tailored suggestions for travel destinations, food and dining experiences, activities and events, and transportation options. Based on personalized recommendations, the system can recommend attractive destinations in Sri Lanka, recommend food and dining, recommend sports, festivals and activities available in Sri Lanka, and recommend transportation options. In addition to personalized recommendations, other technologies are also used to incorporate several other valuable features into the system. A component to provide cultural and ethical practices to be followed based on the specific destination, a component to identify the local food of Sri Lanka, a component to post the various events organized in Sri Lanka and a component for tourists to choose suitable vehicles for their travel. Through the seamless integration of these features, the mobile app seeks to revolutionize the way travelers plan their trips to Sri Lanka, offering a convenient and efficient online platform. This research contributes to the advancement of the travel industry by not only providing a user-friendly and reliable mobile application but also exploring the potential of data-driven personalization to improve the overall travel experience.