Difference between revisions of "Hairball Graphs (data)"

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(Created page with "A simple model generating random graphs with cohesive groups that are connected into a small world is the ''planted partition model'' (PPM). Let <math>\mathcal{C}=\{C_1, \ldots,...")
 
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We generated 50 graphs from a PPM with <math>500</math> vertices, <math>k=9</math>, <math>p_{in}=0.3</math>, and <math>p_{out}=0.01</math>. On top of that, we ran a random noise model with <math>p_{in}=p_{out}=0.1</math> to obfuscate the underlying groups. The resulting graphs are very dense, have a low diameter, and are real hairballs without any visible structure when laid out using force-directed methods.
 
We generated 50 graphs from a PPM with <math>500</math> vertices, <math>k=9</math>, <math>p_{in}=0.3</math>, and <math>p_{out}=0.01</math>. On top of that, we ran a random noise model with <math>p_{in}=p_{out}=0.1</math> to obfuscate the underlying groups. The resulting graphs are very dense, have a low diameter, and are real hairballs without any visible structure when laid out using force-directed methods.
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Data in graphml format:
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[[Media:Hairball-Graphs-PPM500.zip|'''Hairball-Graphs-PPM500.zip''']] (11 MB)

Revision as of 12:49, 28 August 2014

A simple model generating random graphs with cohesive groups that are connected into a small world is the planted partition model (PPM).

Let be a partition of $V$ for a graph . Then is called a clustering of with class for a vertex . The probability of an edge is if and if .

We generated 50 graphs from a PPM with vertices, , , and . On top of that, we ran a random noise model with to obfuscate the underlying groups. The resulting graphs are very dense, have a low diameter, and are real hairballs without any visible structure when laid out using force-directed methods.

Data in graphml format: Hairball-Graphs-PPM500.zip (11 MB)