基于深度学习的学生画像选课系统研究  

Study on the Course Selection System of Student Portrait Based on Deep Learning

作　　者：李沁颖 易豪 LI Qin-ying;YI Hao(Jiangxi University of Technology,Nanchang 330098,China)

机构地区：[1]江西科技学院,江西南昌330200

出　　处：《电脑知识与技术》2021年第10期184-186,共3页Computer Knowledge and Technology

基　　金：江西科技学院自然科学项目(ZR1904)。

摘　　要：目前,深度学习利用自身优势,已在语音识别、图像处理等方面取得了重大的突破与成就。然而,深度学习在选课推荐系统领域的研究与应用还处于早期阶段。考虑传统的选课系统难以考虑到影响学生选课的多因素,本文基于深度学习,结合协同过滤技术在选课系统中的应用,实现对学生的多方面画像,构建出一个实时感知学生喜好变化,且对其进行智能推荐选课的平台,实现从学生到课程的无误差匹配。At present, deep learning has made great breakthroughs and achievements in speech recognition and image processing bytaking advantage of its own advantages. However, the research and application of deep learning in the field of course selection recommendation system is still in the early stage. Considering the traditional course selection system is difficult to consider the manyfactors influencing students' course selection, based on the deep learning, combining the application of collaborative filtering technology in the course system, realize to the students' various portraits, construct a real-time perception student preferences change,and carries on the intelligent recommended course platform, from students to the course of matching error.

关 键 词：用户画像技术 深度学习 协同过滤技术 学生选课系统 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]