[1]贾志先.考试数据分析及孤立点检测的谱聚类方法[J].计算机技术与发展,2013,(01):103-106.
　JIA Zhi-xian.Spectral Clustering Method for Exam Data Analysis and Outlier Detection[J].,2013,(01):103-106.
点击复制

考试数据分析及孤立点检测的谱聚类方法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年01期
页码:
103-106
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Spectral Clustering Method for Exam Data Analysis and Outlier Detection
文章编号:
1673-629X（2013）01-0103-04
作者:
贾志先
新疆财经大学 网络与实验教学中心
Author(s):
JIA Zhi-xian
关键词:
谱聚类; 特征值; 特征向量; 孤立点检测
Keywords:
spectral clustering; eigenvalue; eigenvector; outlier detection
文献标志码:
A
摘要:
孤立点(outlier)又称离群点,为位于远离与之相应的随机变量平均值的点.针对考试数据分析和孤立点检测问题,给出了答卷数据的谱聚类算法.利用答卷数据的谱聚类算法对所有考生的答卷数据进行聚类后,根据答卷数据的谱聚类算法中引入的距离矩阵,以每一位被试的答卷数据为参照,构成一个分类图,从而构建一个分类图簇.谱聚类算法在分析考试数据和检测孤立点方面具有明显的优势.实验表明,利用答卷数据的谱聚类算法对考试答卷结果进行聚类和分析,可以从中挖掘出更多有价值的信息
Abstract:
An outlier is defined as a point that lies very far from the mean of the corresponding random variable. For the problem of exam data analysis and outlier detection,give the algorithm of spectral clustering on exam data analysis. After clustering of all the answers of people who take the exam,by using spectral clustering algorithm of examination scripts,according to the introduction of the distance ma-trix in spectral clustering algorithm,each people who takes the exam can be treated as a reference,to constitute a classification chart,thus build a cluster of classification chart. The algorithm of spectral clustering has obvious advantages in the analysis of exam data and outlier detection. Experiments show that clustering and analysing the results of exam answers by using of spectral clustering,can dig out the more valuable information

相似文献/References:

[1]沈亚田 沈夏炯 张磊.基于图划分的谱聚类算法在文本挖掘中应用[J].计算机技术与发展,2009,(05):96.
　SHEN Ya-tian,SHEN Xia-jiong,ZHANG Lei.Application of Spectral Cluster Algorithm Based on Graph Partition in Text Mining[J].,2009,(01):96.
[2]王春雪 王继成 郑吉.谱聚类在图像检索中的应用[J].计算机技术与发展,2009,(01):207.
　WANG Chun-xue,WANG Ji-cheng,ZHENG Ji.Application of Spectral Clustering in Image Retrieval[J].,2009,(01):207.
[3]张江 王年 梁栋 唐俊.基于Laplace谱的图像分类[J].计算机技术与发展,2008,(05):73.
　ZHANG Jiang,WANG Nian,LIANG Dong,et al.Image Classification Based on Laplacian Spectra[J].,2008,(01):73.
[4]庞然 安博文 李丹.面向集装箱字符识别的预处理算法[J].计算机技术与发展,2010,(12):21.
　PANG Ran,AN Bo-wen,LI Dan.A Preprocess Algorithm for Container Code Recognition System[J].,2010,(01):21.
[5]李振博,徐桂琼,査九. 基于用户谱聚类的协同过滤推荐算法[J].计算机技术与发展,2014,24(09):59.
　LI Zhen-bo,XU Gui-qiong,ZHA Jiu. A Collaborative Filtering Recommendation Algorithm Based on User Spectral Clustering[J].,2014,24(01):59.
[6]胡海峰[][],刘萍萍[]. 一种基于特征间隙的检测簇数的谱聚类算法[J].计算机技术与发展,2015,25(09):37.
　HU Hai-feng[][],LIU Ping-ping[]. A Spectral Clustering Algorithm with Identifying Clustering Number Based on Eigengap[J].,2015,25(01):37.
[7]李扬,陆璐,崔红霞. 谱聚类图像分割中相似度矩阵构造研究[J].计算机技术与发展,2016,26(07):55.
　LI Yang,LU Lu,CUI Hong-xia. Research on Similarity Matrix Structure in Spectral Clustering Image Segmentation[J].,2016,26(01):55.
[8]朱庆生,付飘飘,张程. 基于自然邻的自适应谱聚类算法[J].计算机技术与发展,2017,27(11):19.
　ZHU Qing-sheng,FU Piao-piao,ZHANG Cheng. An Adaptive Spectral Clustering Algorithm Based on Natural Neighbor[J].,2017,27(01):19.
[9]贾 晖,张建刚.基于谱聚类三维模型集一致性分割算法[J].计算机技术与发展,2019,29(11):21.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 005]
　JIA Hui,ZHANG Jian-gang.Consistency Segmentation Algorithm of 3D Model Set Based on Spectral Clustering[J].,2019,29(01):21.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 005]
[10]郝敬琪,胡立华,张素兰,等.基于非负矩阵分解的均方残差多视图聚类算法[J].计算机技术与发展,2023,33(12):65.[doi:10. 3969 / j. issn. 1673-629X. 2023. 12. 009]
　HAO Jing-qi,HU Li-hua,ZHANG Su-lan,et al.Mean Square Residual Multi-view Clustering Algorithm Based on Non-negative Matrix Factorization[J].,2023,33(01):65.[doi:10. 3969 / j. issn. 1673-629X. 2023. 12. 009]

更新日期/Last Update: 1900-01-01