利用内容推荐和协同过滤算法实现个性化评估  

Based on content recommendation and collaborative filtering algorithm achieving personalized evaluation

作　　者：高斐 陈德礼 严涛 GAO Fei;CHEN Deli;YAN Tao(College of Information Engineering, Putian University, Putian 351100, China)

机构地区：[1]莆田学院信息工程学院,福建莆田351100

出　　处：《安徽大学学报（自然科学版）》2022年第2期22-29,共8页Journal of Anhui University(Natural Science Edition)

基　　金：国家自然科学基金资助项目(61741111);福建省教育厅中青年教师教育科研项目(JT180479);莆田学院教育教学改革项目(JG201806)。

摘　　要：针对教学评估中存在着仅用试卷分析表无法实现个性化学习和评估的情况,将人工智能中的推荐系统技术应用到期末教学评估中.将推荐系统中的基于内容推荐算法和协同过滤算法分别应用到学生薄弱知识点的个性化学习和期末评估分析中,根据学生的知识掌握情况推荐相应资源进行个性化辅导.通过实验案例验证,该方法可以得出学生对知识点的掌握程度,并根据题目之间的相似性进行推荐.In view of the fact that it was impossible to achieve personalized learning and evaluation in the current teaching evaluation only by using the test paper analysis table,the paper applied the recommendation system technology in artificial intelligence to the final teaching evaluation.The content-based recommendation algorithm and collaborative filtering algorithm in the recommendation system were respectively applied to the personalized learning of weak knowledge points and the final assessment analysis of students.Through this experimental case,the weight of knowledge points could be obtained by this method,and the weight reflected the weakness of knowledge points,and made recommendations based on the similarity between the topics.

关 键 词：人工智能 推荐系统 教学评估 个性化推荐 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]