Personalized Recommendation Method of Tourist Route based on User Collaborative Filtering Model

China has become the world's third largest inbound tourism host country and outbound tourism consumer country, and is forming the largest international tourism market. Tourism plays an increasingly important role in economic growth and employment. The recommender system can automatically filter out the personalized information in line with the user's interests. At the same time, it can dynamically adjust the recommended items according to the changes of user behavior. Firstly, the nearest neighbor set is selected according to the user similarity, and then the user evaluation data in the nearest neighbor set is used to infer the target item score.