Recommendation of Higher Education Information Based on Multiple Mixed Models

In order to obtain the required educational information for users from multiple educational sources, the author proposes a higher education recommendation process based on a number of fuzzy methods. The main functional core of the system includes recycling, database module and recommended display module. After the user submits search data to the recycling process, the recycler sends search commands to the database. According to the user's choice, the database stores the most advanced training data and sends it to the recommended display module. The Display Recommendations module sends recommendation information to the client from a list of recommended devices. The test results show that the optimal return ratio is greater than 0.9 and has better visibility. As the number of users increases, it will always be higher than the other two systems and will have the least change; In the other two systems, the minimum recommended return value fell below 0.8. In practice, the system can recommend educational materials according to users’ interests, and the detection accuracy and recommendation yield are high.