Basically, I'm looking for something like this awesome research project: Gmap, which was referenced in this related SO question.
It's a rather novel data visualization that combines a network graph with an imaginary set of regions that looks like a map. Basically, the map-ification helps humans comprehend the enormous data set better.
Cool, huh? GMap doesn't appear to be open source, though I plan to contact the authors.
I already know how to create a network graph with a force-directed layout (currently using Prefuse/Flare), so an answer could be a way to layer a mapping algorithm on top of an existing graph. I'm also not concerned about the client-side at all right now - this would be a backend process, and I am flexible about technology stack and data output at this stage.
There's also this paper that describes the algorithm backing GMap. If you have heard of Voronoi diagrams (which rock, but make my head hurt), this paper is for you. I quit after Calc 1, though, so I'm hoping to avoid remembering what sigmas and epsilons are.
As a start, could you do a simple closest point sort of an algorithm? So it looks something like this: You have your force directed layout and have computed some sort of bounding box. Now you want to render it. Adjust your bounding box to line up to the origin and then as you calculate the color of each pixel, find it's closest point. This should generate some semblance of regions and should be quite simple to try out. Of course, it isn't going to be as pretty as GMap, but maybe a start? The runtime would be awful, but... I don't know about you but computing boundary lines directly sounds a lot harder to me.
来源：https://stackoverflow.com/questions/5109956/how-can-i-produce-visualizations-combining-network-graphs-and-imaginary-maps