Node-Attribute Graph Layout for Small-World Networks

Helen GibsonJoe Faith

Intelligent Modelling LabIV2011 - AGT

Node-Attribute Graph Layout for Small-World Networks

Small-World Networks


• Clustered with a high clustering coefficient

• Smaller than average shortest path length

What are they?

Layout

• Force Directed

• Packed together

• Lose clusters

• Users

Examples

• Milgram (1967)

• IMDB

Node-Attributes


Information about the nodes

• Retinal Variables

• Colour

• Size

• Shape

What about nodes having multiple classifications?

Or lots of quantitative attributes?

Node Attributes


Nodes (X)Attributes (O)

Dimension Reduction + TPP


J. Faith, “Targeted Projection Pursuit for Interactive Exploration of High- Dimensional Data Sets,” 11th International Conference Information Visualization (IV ’07), Jul. 2007, pp. 286-292.

Targeted Projection Pursuit – interactive high-dimensional data exploration

Example Application


gephi.org

Gephi

• Force-directed

• Yifan Hu

Clustered

Randomly add and remove links

Assign attributesRemove attributes

http://www.gephi.org/

http://www.gephi.org/

Example Application


Targeted Projection Pursuit

http://code.google.com/p/targeted-projection-pursuit/

• Attributes as dimensions

• Number of attributes =

Number of dimensions

Which attributes are significant in clustering?


Example Application


LinLog - Andreas Noack (2007)

http://code.google.com/p/linloglayout/

• Energy Models

• Force Directed

• Graph Clusterings

http://code.google.com/p/linloglayout/

Conclusions + Further Work


• TPP - greater visual separation than force-directed layout

• TPP – doesn’t lose the context that LinLog does

But…

• Further empirical validation needed!

• Metrics

• Vary parameters

• Insights gained

• Further use of attributes

Most importantly…

• Real world applications



Node-Attribute Graph Layout for Small-World Networks

Documents

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