摘要
传统的数学教学资源分类方法效率低,为此,提出两步聚类算法的数学教学资源归并分类方法。利用互信息技术的获取增量数据,提取数字化数学教学资源特征;根据两步聚类算法构建数学教学资源特征树,依据层次凝聚算法对特征树叶节点进行分组,采用欧式平方距离获得数学教学资源平方根测度连续变量,最大增长距离的聚类数即最终聚类数量。结果表明,该方法可实现数学教学资源的有效归并分类。
The traditional classification method of mathematics teaching resources is inefficient. Therefore,this paper proposes a two-step clustering algorithm to classify mathematics teaching resources,which uses mutual information technology to obtain incremental data and extract the characteristics of digital mathematics teaching resources,then constructs the feature tree of mathematics teaching resources based on the two-step clustering algorithm and divides the characteristic tree leaf nodes into groups according to the hierarchical aggregation algorithm,and finally,obtains the continuous variable of the square root measure of mathematics teaching resources by the euclidean square distance and the number of clusters with the maximum growth distance is the final number of clusters. The results show that this method can effectively merge and classify mathematics teaching resources.
作者
褚正清
CHU Zhengqing(General Education Department,Anhui Xinhua College,Hefei 230088,China)
出处
《长春大学学报》
2021年第8期82-86,共5页
Journal of Changchun University
基金
安徽省教育厅项目(2018jyxm1074)。
关键词
两步聚类算法
数字化
数学
教学资源
归并
分类方法
two-step clustering algorithm
digitization
mathematics
teaching resources
merging
classification method
