基于学习者兴趣挖掘的个性化课程推荐方法

Personalized Course Recommendation Based on Learner Interest Mining

在线教育的一个显著特征是兴趣驱动,通过对学习者的学习行为数据的分析与挖掘,建立学习者的个性化学习兴趣模型,并进一步基于学习者学习兴趣为其推荐合适的课程。首先,建立学习者多层兴趣模型,准确刻画学习者对知识主题、课程及知识领域的兴趣度;其次,构建学习者兴趣关系网,并基于兴趣关系网采用协同过滤方法为学习者进行课程推荐;最后,通过实验验证,证实了所提方法的有效性。

A significant feature of online education was interest driven.A personalized learning interest model was proposed for learners by analysing and mining the learning behavior data.The appropriate courses for learners based on their learning interest were recommended.Firstly,a multi-layer interest model was established to accurately describe learner interest in knowledge topics,courses and knowledge fields.Secondly,a learner interest network was constructed,based on which a collaborative filtering method was adopted to recommend courses for learners.Finally,the effectiveness of the proposed method was verified by experiments.