I have a weighted graph representing traffic network. Nodes represent the locations and vertices represent available paths between locations. Weight values represent number of the passages on the path.
I would like to cluster based on the similarity of the weight values (i.e. number of passages) and establish different traffic frequentation zones. The weights in different zones are roughly similar except for a few outliers.
In the clustering techniques I've seen the methods often involve using weights as a "distance" between the nodes and finding the best way to split the graph based on the distance and connectivity. Here, I'm trying to cluster nodes according to the weights of the edges linking them. For example there are certains zones in the graph where all the nodes are connected by vertices with weights of ~4, these should form one cluster, and in another distinct part of the graph the weights are ~1, this forms another cluster. Do you know any methods for this?
Perhaps my problem is not well suited to graph theory.