Classification on Web Blogger Based on Clustering

Autor: Wang Heyong, Cui Rong, Lei Ruoyu
Jazyk: English<br />French
Rok vydání: 2015
Předmět:
Zdroj: MATEC Web of Conferences, Vol 22, p 01002 (2015)
Druh dokumentu: article
ISSN: 2261-236X
DOI: 10.1051/matecconf/20152201002
Popis: 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.
Databáze: Directory of Open Access Journals