CAJ | 학술논문

在深入研究数据挖掘聚类分析算法的基础上，针对传统算法的优缺点，提出一种改进的聚类分析算法---GBKM算法，通过理论分析以及实验证明该算法的有效性和先进性，并将其运用到教学实践中。使用该算法对国家计算机二级模拟考试成绩进行分析，根据分析结果获得学员个性特征，为学员提供有针对性的、个性化的学习指导，在教学实践中具有积极的指导意义。
재심입연구수거알굴취류분석산법적기출상，침대전통산법적우결점，제출일충개진적취류분석산법---GBKM산법，통과이론분석이급실험증명해산법적유효성화선진성，병장기운용도교학실천중。사용해산법대국가계산궤이급모의고시성적진행분석，근거분석결과획득학원개성특정，위학원제공유침대성적、개성화적학습지도，재교학실천중구유적겁적지도의의。
This article studies clustering algorithm that is one of the important data mining techniques .For the advantages and disadvantages of traditional algorithms ,an improved clustering algorithm is presented .Prove the algorithm is effective and advanced through theoretical and test and use the technology in teaching practice .USE the clustering algorithm to ana-lyze the mock examinations scores of the National Computer Rank Examination and get the personal characteristics of students according to the results .Provide students with targeted ,personalized learning strategies and study guide .Im-prove the participants in NCRE .The clustering algorithm is positive significance in teaching practice .