Abstract
With the ever-increasing living standards of the people in recent years, more and more people have entered the army of tourism, and our country’s tourism industry has achieved unprecedented development. A series of travel portal websites such as Ctrip.com, Qunar, and Malacca have emerged. A large amount of tourist information is presented to users, but at the same time it has led to the blind choice of users. Massive data have overwhelmed the information that users are really interested in. The emergence of tourism recommendation systems helps users solve this problem. Against the above background, this paper designs and implements a tourism recommendation system based on data mining. From the perspective of mining the similarity between users, the similarity between users is calculated through the collaborative filtering algorithm, and then the attractions visited by users with higher similarity are recommended.
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