BLOGRANK: Ranking Weblogs Based On Connectivity And Similarity Features

A large part of the hidden web resides in weblog servers. New content is produced in a daily basis and the work of traditional search engines turns to be insufficient due to the nature of weblogs. This work summarizes the structure of the blogosphere and highlights the special features of weblogs. In this paper we present a method for ranking weblogs based on the link graph and on several similarity characteristics between weblogs. First we create an enhanced graph of connected weblogs and add new types of edges and weights utilising many weblog features. Then, we assign a ranking to each weblog using our algorithm, BlogRank, which is a modified version of PageRank. For the validation of our method we run experiments on a weblog dataset, which we process and adapt to our search engine. (http://spiderwave.aueb.gr/Blogwave). The results suggest that the use of the enhanced graph and the BlogRank algorithm is preferred by the users.
Comment: 9 pages, in 2nd international workshop on Advanced architectures and algorithms for internet delivery and applications