基于大数据的个性化学习资源推荐系统的设计  

Study on the Design of Personalized Learning Resource Recommendation System Based on Big Data

作　　者：刘润嘉 李佩泽 Liu Runjia;Li Peize(Liaoning Finance and Trade College,Huludao 125105;Tianjin University of Science and Technology,Tianjin 300457)

机构地区：[1]辽宁财贸学院,辽宁葫芦岛125105 [2]天津科技大学,天津300457

出　　处：《中阿科技论坛(中英文)》2025年第1期80-84,共5页China-Arab States Science and Technology Forum

摘　　要：在信息时代,在线教育在全球范围内迅速普及。借助互联网平台,教育资源可打破时空限制而得以广泛传播。随着数字教育资源的激增,如何为不同需求的学生提供差异化的网络学习资源,从而激发学生的学习兴趣并提高学习效率,成为当下在线教育平台面临的重要课题。针对关键问题,文章以提高学习资源推荐的准确性为目标,设计了一种基于大数据技术的个性化学习资源推荐系统。通过基于混合相似度模型、实时推荐优先级权重和时间权重加权的在线学习资源实时推荐算法,个性化学习资源推荐系统可构建离线推荐和实时推荐体系,精准捕捉学习者的兴趣变化与学习情况,进而动态调整资源推荐结果,为学习者提供个性化学习支持。In the information era,online education is booming globally.With the help of Internet platforms,educational resources can be widely spread in spite of the time and space constraints.With the proliferation of digital educational resources,how to provide personalized learning resources for students with different needs,thereby stimulating their learning interest and boosting learning efficiency has become a key issue faced by online education platforms nowadays.In order to enhance the accuracy of recommendations,the article designs a personalized learning resource recommendation system based on big data.The system features a real-time online learning resource recommendation algorithm that combines similarity models,real-time recommendation priority weights,and time weight weighting.Moreover,the system can provide both offline and real-time recommendations,which accurately capture learners'interest and learning status,and then dynamically adjust recommendation results to provide learners with personalized services.

关 键 词：大数据 个性化推荐 学习资源 系统设计 

分 类 号：TN948.61[电子电信—信号与信息处理]