摘要： 推荐系统是数据挖掘中强有力的技术，异构信息网络是推荐系统起步晚却发展迅猛的主流推荐方法。提出了基于异构信息网络的学生成绩预测与预警模型，该方法通过元路径计算得到学生间相似度矩阵，利用相似度矩阵构造成绩变化趋势矩阵和幅度矩阵，投票得到学生成绩预警与预测结果；最后，在公开数据集上验证所提模型的有效性，结果表明，该模型能够对学生成绩进行预警，并能在一定阈值下预测学生成绩具体分值。

推荐系统是数据挖掘中强有力的技术，异构信息网络是推荐系统起步晚却发展迅猛的主流推荐方法。提出了基于异构信息网络的学生成绩预测与预警模型，该方法通过元路径计算得到学生间相似度矩阵，利用相似度矩阵构造成绩变化趋势矩阵和幅度矩阵，投票得到学生成绩预警与预测结果；最后，在公开数据集上验证所提模型的有效性，结果表明，该模型能够对学生成绩进行预警，并能在一定阈值下预测学生成绩具体分值。

Research on the prediction and early warning model of student achievement based on heterogeneous information network

Abstract： Abstract： Recommendation system is a powerful technology in data mining. Heterogeneous information network is the mainstream recommendation method which started late but developed rapidly. In this paper, we proposed a student achievement prediction and early warning model based on heterogeneous information network. This method obtains the similarity matrix among students by Meta-Graph calculation, constructs the achievement change trend matrix and amplitude matrix by using the similarity matrix, and obtains the student achievement early warning and prediction by voting. Finally, the effectiveness of the proposed model is verified on the open data set, the experimental results show that the model can give early warning to the student achievement and can predict the specific score of students′ performance under a certain threshold.

Key words : heterogeneous information network；Meta-Graph；academic warning；academic prediction；data mining