How Contents Influence Clustering Features in the Web

Abstract

In World Wide Web, contents of web documents play important roles in the evolution process because of their effects on linking preference. A majority of topological properties are content-related, and among them the clustering features are sensitive to contents of Web documents. In this paper, we first observe the impacts of content similarity on web links by introducing a metric called Linkage Probability. Then we investigate how contents influence the formation mechanism of the most basic cluster, triangle, with a metric named Triangularization Probability. Experimental results indicate that content similarity has a positive function in the process of cluster formation in theWeb. Theoretical analysis predicts the contents influence on the clustering features in the Web very well.