Application of Improved Machine Learning and Fuzzy Algorithm in Educational Information Technology

Abstract

In order to improve the teaching effect of intelligent education, this paper combines machine learning and fuzzy algorithm to improve the application effect of educational information technology and the use of information platform. Moreover, this paper collects the user’s behavior information in the process of using the platform as the user’s interest description and selects personalized upgrade resources for the user. In addition, this paper introduces the similarity as a personalized recommendation evaluation standard and calculates the average similarity between the recommended related resources and the user’s interest. Finally, this paper constructs an educational information system based on improved machine learning and fuzzy algorithms. The experimental research results show that the intelligent system proposed in this paper can play an important role in educational information processing and teaching quality improvement.