Examining Higher Order Transformations for Scale-free Small World Graphs

author: Uwe Quasthoff, Department of Computer Science, University of Leipzig
published: Dec. 14, 2007,   recorded: October 2007,   views: 2768


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


The degree distribution of scale-free Small World networks follows a power law. For random graph generators, its exponent is constrained by the construction mechanism, whereas in real-world data, different slopes can be observed. However, the degree distribution alone does not reveal much of the local structure of these graphs. Therefore, we propose a graph transformation we call ”higher order” transformation, which encodes the number of common neighbours two vertices share in its edge weights. Studying the degree distribution of secondand third order graphs and comparing it to natural language cooccurrence data, we find that the higher order transformation reveals differences that cannot be detected by only looking at traditional measures on the original graph.

See Also:

Download slides icon Download slides: eccs07_quasthoff_eho_01.v1.ppt (621.0 KB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: