With the continuous improvement of people’s living standards, tourism has been a rapid development. In the past, people’s biggest need for life was to have enough food and clothing, but now people have more time and money to relax through travel. The tourism industry has developed into a pillar industry chain supporting the national economy. The development of tourism can affect the gross domestic product (GDP) of a whole region, thus driving the development of regional economy, population and culture. However, with the improvement of people’s living quality, the demand is gradually expanding. In the past, if people could have the time and money to spend on travel, they would feel physically and mentally happy. Now people have been used to a high-quality lifestyle, so the pursuit of tourism has become diversified, some people pursue the process of tourism, some pursue the results of tourism, which also leads to the endless types of tourism industry, so in order to meet people’s increasingly personalized demand for tourism, it is necessary to use data mining technology to design a set of personalized tourism recommendation system. The system can provide users with personalized recommendations and services according to the data information of users’ browsing and collection of tourism pages, as well as other customer information with similar preferences. A questionnaire survey was designed based on the feelings before and after the use of the system. The survey results show that 399 people think scenic spot service is more personalized. Before the system was used, only 181 people thought scenic spots were personalized, and 392 people thought tourist spots were convenient, up from 169. Therefore, it can be shown that people have a high satisfaction index for this personalized travel recommendation system. This study provides reference value for tourism.