Classification on Web Blogger Based on Clustering
College of E-Business, South China University of Technology, Guangzhou, Guangdong, China
In this paper, based on the clustering analysis method, the author tries to study some celebrities in web blogger groups and adopts unsupervised clustering evaluation methods, which is called silhouette coefficient, to evaluate the classification results of different clustering classification methods. It is concluded that K-means clustering is the best among the clustering methods compared with the traditional classifications. Furthermore, it is a dynamic, flexible method and can reduce restrictions of subjective consciousness using cluster analysis. As a result, K-means clustering is universal in web blogger groups’ classification process.
Key words: web blog / fame classification / cluster analysis / silhouette coefficient
© Owned by the authors, published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.