Recommendation System of Tourist Attractions Based on Artificial Intelligence Algorithm

The rapid development of tourism and people's increasing pursuit of tourism experience have prompted researchers to explore a more efficient and personalized recommendation system for tourist attractions. In this study, the application of artificial intelligence algorithm in the recommendation of tourist attractions is discussed in depth, aiming at evaluating its influence on user satisfaction and recommendation accuracy. Through comparative experiments, the traditional recommendation method is compared with the tourist attractions recommendation system based on artificial intelligence algorithm. The results show that the recommendation system based on artificial intelligence algorithm improves the score of user satisfaction by 14% compared with the traditional method, reaching 4.8 points. At the same time, the accuracy of the recommendation system based on artificial intelligence algorithm has also been significantly improved, and 82.7% of the recommendation results are consistent with the actual tour situation of users, which is significantly improved compared with the traditional method of 65.3%. The recommendation system of tourist attractions based on artificial intelligence algorithm has better user satisfaction and recommendation accuracy. It can better understand users' personal preferences, needs and interests, and provide more accurate and personalized recommendations of tourist attractions. This is of great significance to the design and improvement of recommendation system in tourism industry, and also provides users with better travel experience and opportunities to meet their personalized needs.