Abstract:
A Web graph refers to the graph that models the
hyperlink relations between Web pages in the WWW, where a
node represents a URL and an edge indicates a link between two
URLs. A Web graph is normally a very huge graph. In the course
of users’ Web exploration, only part of the Web graph is displayed
on the screen each time according to a user’s current navigation
focus. In this paper, we make use of a fast kernel-based algorithm
that is able to cluster large graphs. The algorithm is implemented
in an online visualization system of Web graphs. In the system, a
Web crawler first generates the Web graph of web sites. The
clustering algorithm then reduces the visual complexities of the
large graph. In particular, it groups a set of highly connected
nodes and their edges into a clustered graph with abstract nodes
and edges. The experiments have demonstrated that the employed
algorithm is able to cluster graphs.
