Comparison and Analysis for Social Web Clustering Algorithm
Moushuo Wu - · International Journal of Digital Content Technology and its Applications · 2011
K-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This paper compares and analyzes the word vector space model of K-means, and expands it using links information. Then it mines several links involved in social tagging network. Experimental result shows that the proposed social web clustering algorithm is effective.