{"title":"基于深度学习的学生个性化在线学习平台课程推荐算法","authors":"Zhengmeng Xu, Hai Lin, Meiping Wu","doi":"10.4018/ijitwe.333603","DOIUrl":null,"url":null,"abstract":"This paper mainly studies the content of the recommendation algorithm of learning resource courses in online learning platforms such as MOOC and mainly introduces the automatic encoder neural network that integrates course relevance to realize the personalized course recommendation model. The authors first introduce how to embed a course relevance decoder in an autoencoder neural network. Secondly, the proposed confidence matrix method is introduced to distinguish the recommendation effect of the learned to the unlearned courses, and the training process of the model is introduced. Then, the design content of the experiment is introduced, including the model structure, comparative experiments, parameter settings, and evaluation indicators. Finally, the experimental results are analyzed in detail from the horizontal and vertical aspects. It is hoped that this research can provide a reference for personalized recommendation of learning resources based on deep learning technology and big data analysis.","PeriodicalId":51925,"journal":{"name":"International Journal of Information Technology and Web Engineering","volume":"170 2","pages":"0"},"PeriodicalIF":0.6000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Course Recommendation Algorithm for a Personalized Online Learning Platform for Students From the Perspective of Deep Learning\",\"authors\":\"Zhengmeng Xu, Hai Lin, Meiping Wu\",\"doi\":\"10.4018/ijitwe.333603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper mainly studies the content of the recommendation algorithm of learning resource courses in online learning platforms such as MOOC and mainly introduces the automatic encoder neural network that integrates course relevance to realize the personalized course recommendation model. The authors first introduce how to embed a course relevance decoder in an autoencoder neural network. Secondly, the proposed confidence matrix method is introduced to distinguish the recommendation effect of the learned to the unlearned courses, and the training process of the model is introduced. Then, the design content of the experiment is introduced, including the model structure, comparative experiments, parameter settings, and evaluation indicators. Finally, the experimental results are analyzed in detail from the horizontal and vertical aspects. It is hoped that this research can provide a reference for personalized recommendation of learning resources based on deep learning technology and big data analysis.\",\"PeriodicalId\":51925,\"journal\":{\"name\":\"International Journal of Information Technology and Web Engineering\",\"volume\":\"170 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Information Technology and Web Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijitwe.333603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information Technology and Web Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijitwe.333603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A Course Recommendation Algorithm for a Personalized Online Learning Platform for Students From the Perspective of Deep Learning
This paper mainly studies the content of the recommendation algorithm of learning resource courses in online learning platforms such as MOOC and mainly introduces the automatic encoder neural network that integrates course relevance to realize the personalized course recommendation model. The authors first introduce how to embed a course relevance decoder in an autoencoder neural network. Secondly, the proposed confidence matrix method is introduced to distinguish the recommendation effect of the learned to the unlearned courses, and the training process of the model is introduced. Then, the design content of the experiment is introduced, including the model structure, comparative experiments, parameter settings, and evaluation indicators. Finally, the experimental results are analyzed in detail from the horizontal and vertical aspects. It is hoped that this research can provide a reference for personalized recommendation of learning resources based on deep learning technology and big data analysis.
期刊介绍:
Organizations are continuously overwhelmed by a variety of new information technologies, many are Web based. These new technologies are capitalizing on the widespread use of network and communication technologies for seamless integration of various issues in information and knowledge sharing within and among organizations. This emphasis on integrated approaches is unique to this journal and dictates cross platform and multidisciplinary strategy to research and practice.