| 摘要: |
| 给出了K-means算法和层次聚类算法在具体网站用户细分中准确率的比较，在细分网站用户这一类问题中，K-means算法在聚类准确率和处理速度上具有较大的优势，能够满足网站用户细分准确率的基本要求，其聚类准确率达到95%左右，且K-means算法处理速度比较快；层次聚类算法的处理速度较K-means算法慢，且其聚类准确率在处理大量用户数据时低于92%，这对于处理网站用户数据这类信息并不具备优势. |
| 关键词: 聚类算法 层次 用户细分 准确率 |
| DOI：10.3969/J.ISSN.1000-5137.2018.01.008 |
| 分类号: |
| 基金项目: |
|
| Comparison of two clustering algorithms in website user segmentation |
|
Xiao Yatie1, Liu Yafei1, Li Luqun1, Li Zhemin2
|
|
1.The College of Information and Mechanical Engineering, Shanghai Normal University, Shanghai 200234, China;2.Music College, Shanghai Normal University, Shanghai 200234, China
|
| Abstract: |
| In this paper,we compare the accuracy of K-means algorithm and Hierarchical clustering algorithm in specific website user segmentation.Among the problems of subdividing website users,K-means algorithm has the advantage of accuracy and processing speed The advantages of this algorithm are that it can meet the basic requirements of website user segmentation accuracy,the clustering accuracy is about 95%,and K-means algorithm is faster;Hierarchical clustering algorithm is slower than K-means algorithm,And its clustering accuracy is less than 92% when processing a large amount of user data,which is not advantageous for processing information such as website user data. |
| Key words: clustering algorithm hierarchy user segmentation accuracy |
Editorial Board