Published Paper Details:

Tourist Recommendation systems are used to provide personalized recommendations to tourists based on their preferences and interests. Being this popular, there is still not a large-scale environment available in the market. Our paper aims to provide a comprehensive overview of the tourist recommendation systems. The paper discusses the different techniques used in these systems, while reviewing the various datasets and evaluation metrics used in the development and evaluation of these systems. These systems use various techniques, including collaborative filtering, content-based filtering, hybrid filtering, and context-aware filtering, to recommend tourist sites, hotels, and restaurants to users. The evaluation metrics used includes precision, recall, RMSE, MAP values. The paper also explores the different applications of tourist recommendation systems, including their use in travel planning, tourist information centers, mobile applications, and chatbots. Overall, this survey paper provides a comprehensive overview of tourist recommendation systems and highlights the various techniques, applications, challenges, and future research directions in this field.