Design and development of personalized education information management system based on artificial intelligence

Abstract

In order to combine artificial intelligence and personalized education, this paper uses semantic similarity to evaluate the similarity between personalized education models and resource information and gives a semantic similarity calculation between word lists. It is used to measure the semantic similarity between user models and texts and between texts, and a recommendation algorithm based on semantic analysis is constructed. Based on this, the needs of personalized education are analyzed, and the personalized education information management system is designed using the MVC framework with a B/S structure. After system testing, we obtained that the MSE value of the review data volume threshold set to 2 was 0.94 on the student information set, 0.86 on the teacher information set, 0.76 on the course information set, 0.74 on the score information set, and 0.81 on the administrative information set.

Keywords

• artificial intelligence
• semantic analysis
• recommendation algorithm
• personalized education
• mvc framework
• 65d17