Tourism industry is one of the most powerful and largest industries in the current global economy, which has created huge economic benefits. With the rapid development of China's tourism industry, tourism information has become an important strategic resource, and the development of e-commerce has provided important support for tourism informatization, which makes its positive role in the value chain of the tourism industry increasingly prominent. In order to improve the service level of tourism e-commerce, a tourism system based on Boosting classification algorithm is constructed, and the random gradient descent algorithm, adaptive gradient optimization algorithm and density method are used to optimize and improve the Boosting classification algorithm. The experimental results show that compared with the traditional Kmeans classification, the improved Boosting classification algorithm can increase the browsing volume by 28.21% and the purchase volume by 15.37%. Through the application of Boosting classification algorithm, it can provide users with personalized tourism goods, improve their purchase volume, and thus improve the competitiveness of the tourism market.