基于神经网络的校园课程智能推荐系统

Intelligent Recommendation System for Campus Courses Based on Neural Networks

学校在线选课和线上教育的普及,使得课程推荐成为一个重要的研究课题。文章提出了一种基于深度置信网络的校园课程智能推荐系统。该系统采用One-Hot编码的方法构建课程画像,采用多元分类编码的方法构建用户画像,并使用深度置信网络来输出用户和课程之间的匹配程度。实验结果表明,该系统的精准率、召回率和F1值均达到了良好水平。

With the popularization of online course selection and online education,course recommendation has become an important research topic.This article proposes an intelligent recommendation system for campus courses based on deep confidence networks.The system uses One-Hot coding to construct course profiles,uses multiple classification coding to construct user profiles,and uses deep confidence networks to output the degree of matching between users and courses.The experimental results show that the accuracy rate,recall rate and F1 value of the system have reached a good level.