摘要
当前高校职业规划课程教学资料分类存在计算资源占用较多和分类效率及准确率较低等问题,基于此提出多重聚类算法的智能分类方法。该方法通过将高维资料转化为低维样本集合、构建教学资料特征树和运用SL层次聚类算法等步骤降低计算资源占用,提高了教学资料分类效率及准确率,进而实现了高校职业规划课程教学资料的智能分类。
In view of such problems in the classification of teaching materials of career planning course in universities as the high occupation of computing resources and the low classification efficiency and accuracy,the paper suggests the intelligent classification method based on multi-clustering algorithm.Through transforming the high-dimensional data into a low-dimensional sample collection,constructing the characteristic tree of teaching materials,and determining the clustering quantity by means of the SL hierarchical clustering algorithm,the method reduces the occupation of computing resources and improves the classification efficiency and accuracy of teaching materials,realizing the intelligent classification of teaching materials of career planning course in universities.
作者
秦丽霞
QIN Li-xia(School of Accounting,Anhui Wenda University of Information Engineering,Hefei,Anhui 230000,China)
出处
《河北北方学院学报（社会科学版）》
2024年第3期86-89,109,共5页
Journal of Hebei North University：Social Science Edition
基金
安徽文达信息工程学院校级重点教学研究项目(2022xjyxm08)。
关键词
多重聚类算法
教学资料分类
互信息
层次聚类
Multi-clustering algorithm
Classification of teaching materials
mutual information
Hierarchical clustering
