摘要
为解决教学资源利用效率低下问题,提高个性化学习体验,本研究采用协同过滤算法作为核心技术手段,设计基于协同过滤算法资源推荐系统,基于用户历史行为与偏好数据,有效识别与推荐符合个别用户需求的教学资源。研究主要集中在系统总体框架设计、功能模块实现上,并通过对比测试来验证推荐系统功能有效性。结果表明,本推荐系统不仅可提高课程资源匹配度与使用率,还具有较高的稳定性与准确性。研究结果可为信息推荐领域发展提供实际参考。
in order to solve the problem of teaching resources using low efficiency,improve personalized learning experience,this study adopts collaborative filtering algorithm as the core technology,design based on collaborative filtering algorithm resources recommendation system,through on the basis of the user history behavior and preference data,the system effectively identify and recommend meet the needs of individual users teaching resources.The research mainly focuses on the overall framework design of the system,the implementation of functional modules,and verifies the functional validity of the recommended system through comparative testing.The results show that the recommendation system can not only improve the matching and utilization of course resources,but also have strong stability and accuracy.The research results can provide practical reference for the development of information recommendation field.
作者
王小林
WANG Xiaolin(Hunan Vocational College of Electronic Science and Technology,Changsha Hunan 410220,China)
出处
《信息与电脑》
2024年第5期254-256,共3页
Information & Computer
基金
全国高等院校计算机基础教育研究会计算机基础教育教学研究课题项目“以数字能力和素养为导向的高职信息技术课程体系研究”(项目编号:2023-AFCEC-266)。
关键词
协同过滤算法
数据库
用户界面
collaborative filtering algorithm
database
user interface
