针对海量习题带来的信息过载导致学习针对性不强、效率不高等问题,提出了基于知识点层次图的个性化习题推荐算法(a personalized exercises Recommendation algorithm based on Knowledge Hierarchical Graph,Re KHG)。借鉴课程知识点体系结构的特点,构建了表征知识点层次关系的权重图,该权重图有效反映知识点间的层次关系。根据学生对知识点的掌握情况,在知识点层次图的基础上提出了一种个性化习题推荐算法。该算法通过更新学生-知识点失分率矩阵,获取学生掌握薄弱的知识点,以此实现习题推荐。实验结果表明,Re KHG算法能够针对性给学生推荐适合的习题。
【英文摘要】
Aiming at the low pertinence and efficiency problem caused by massive exercises, a personalized exercises Recommendation algorithm based on Knowledge Hierarchical Graph(Re KHG)is proposed. Firstly, in consideration of the characteristic of system architecture, a weight map is built, which characterizes the knowledge hierarchical relations.This map can reflect the hierarchical relationship among knowledges efficiently. Then, a personalized exercise recommendation algorithm is proposed according to students' ...
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