基于协同过滤算法的移动智能学习平台的开发与设计

Development and Design of Mobile Intelligent Learning Platform on Collaborative Filtering

摘要: 针对教育类app市场中，综合类教育类app较少并仅提供网课平台学习服务，部分教育类仅提供教学辅助功能的现状，本文提出了一款既能为高校提供教学辅助，又能服务学生进行网课学习的移动智能学习平台，该平台引入了KNNBaseline协同过滤算法，先将目标用户与系统预设的用户进行相似度计算，然后再与剩余用户进行相似度计算，有效解决因为用户信息过于稀疏可能造成的问题，并且引入了用户评分随着时间改变而改变的基线模型。使用MovieLens ml-100k数据集进行实验，实验结果表明，该算法可以有效地为学生提供个性化推荐服务。

Abstract: In the education app market, there are fewer comprehensive education apps only providing online course platform learning services. Some education classes only provide the status of teaching as-sistant functions. We have proposed a teaching aid for colleges and universities. This paper put forward a mobile intelligent learning platform for students to learn online courses. The platform introduces the KNNBaseline collaborative filtering algorithm, proposes to first calculate the simi-larity between the target user and the user preset by the system, and then perform similarity cal-culation with the remaining users, effectively solving the problem. The information is too sparse to cause problems, and introduces a baseline model in which the user’s score changes over time. Experiments were carried out using the MovieLens ml-100k dataset. The experimental results show that the algorithm can effectively provide personalized recommendation services for students.