Abstract: In order to solve the problem of the poor accuracy of Web map point symbol user interest during the process of Web map personalized recommendation, we proposed a method for calculating user interest degree of Web map point symbols based on eye movement data. Using mental cutting test, 39 subjects with similar cognitive ability were selected to participate in the experiment and thus we collected subjects' eye movement and mouse data in four types Web map point symbols. We filtered time, frequency and size eye movement data to calculate user interest degree, and established a new method for calculating user interest degree based on multiple eye movement data. An experiment using eye-tracking and mouse device was designed to verify the effectiveness of the method. The results indicate that the accuracy of user interest degree is 85.9%, which is better than those of mouse data. It has been proved that this method is able to effectively analyze the user interest degree, and that the user interest formula is stable and reliable, which lays the foundation for personalized recommendation and improves the effectiveness of recommendation results.