Modeling the Evolution of Web using Vertex Content Similarity

In the evolution process of World Wide Web, contents of web pages play important roles because of their direct effect on linking preference. In this paper, we propose a model which combines vertex connectivity and content similarity in a proportional manner. Analytical solutions indicate that our model exhibits a power-law degree distribution with variable exponent determined by the weight of content similarity. Distribution of content similarity on connected vertex pairs shows content similar web pages trend to be linked together. Simulation results show our model yields remarkably agreements of both degree and content similarity distributions with real network.