Yuhang Wan
ABSTRACT
In today's information explosion, the types and quantity of tourism resources show a diversified trend. Therefore, tourism data continues to soar, and people are trapped in a situation of information overload. How to make intelligent recommendation of users' personalized travel needs has become a necessary research direction. In view of this situation, this paper continues the analytical data mining technology to study the scenic spot recommendation algorithm based on the association rules and collaborative filtering transactions. According to the complexity and particularity of the application of the tourism recommendation system, a tourism recommendation system framework and page layout are proposed, and the collaborative filtering algorithm is optimized to design a very distinctive intelligent recommendation system for the tourism industry.
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