Timeline for Graphs with fractal properties?
Current License: CC BY-SA 2.5
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Nov 18, 2009 at 3:05 | comment | added | Harrison Brown | Ahh. Well, certainly there are "random graph models" that are known to have more social-network-like properties than the Erdos-Reyni model, which I think are generically pretty good - the degree sequence is a power-law distribution, the diameter is small, etc. Here's a construction which might work fairly well: Assign to each vertex a "sociableness" which is distributed by a power law. Now draw a graph at random, such that v_i and v_j are adjacent with probability proportional to the product of their sociableness. This should be scale-free, and otherwise nice. | |
Nov 18, 2009 at 0:50 | comment | added | DoubleJay | Well, the idea behind the project is that I can find enough data about social networks to develop a way to do it much more efficiently. Also, I'd be willing to tolerate a pretty large amount of error - it just needs to look generically right. For instance, if I could figure out the general traits of social networks of a dense urban, then I could generate a big city just by some set of rules and a few data points about it. This is actually more like procedural generation than regular compression. However, the task it quite daunting, both from the data-collection and computing standpoints. | |
Nov 17, 2009 at 23:34 | history | answered | Harrison Brown | CC BY-SA 2.5 |