关键词: 知识点, 层次图, 习题推荐, 失分率矩阵

Abstract: Aiming at the low pertinence and efficiency problem caused by massive exercises, a personalized exercises Recommendation algorithm based on Knowledge Hierarchical Graph（ReKHG） 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’ mastery of knowledges and their hierarchical graph. The ReKHG algorithm acquires students’ weakness of knowledge mastery by updating knowledge losing-rate matrix of students. Experimental results show that ReKHG algorithm can recommend appropriate exercises for the targeted students.

Key words: knowledge, hierarchical graph, exercises recommendation, losing-rate matrix