Concept Map: Clustering
Visualizations of
Categorical Domains
David Rouff and Mark McLean
CMSC 743 Information Visualization, Spring 07
Department of Computer Science
University of Maryland
1.INTRODUCTION
• Categorical Data Sets are hard to visualize
– No inherrent order, variable size, each element and it’s
associations is a dimension
– Popular Node-Link quickly becomes occluded
– Adjacency matrix hard to understand, elements disjoint
• Concept Map visualizes categorical data with
– Multiple, coordinated views
– Modified hierarchical clustering and SOM clustering
– Tunable clustering and display parameters
3. Design Approach
• Mockups and prototypes guided development.
ConceptMap TM
Color
Blind
Dendrogram
Relationship
DNA
Rank by
1D
Scatterplot
Node Matrix Matrix
Histogram
Feature
LinkAudio
Node
Histogram
Link
NetVis
NetVis
2D
NetVis
Node-Link
Space
Space
Information
Filling
Filling
DistriVisualization
Curve
Visualization
Curve
bution
3D
3D
2D
3D
NetVis
2D
NetVis
TreeMap
TreeMap
Dendrogram
TreeMap
Dendrogram
Pivot
ScatterPlot
Animation
ScatterPlot
Menu
Author Picklist
References list
DateRange select
Keyword Picklist
Details
On
Demand
Area for current
Highlighted
Selection
Implementation of Dendrogram
and Clustered Adjacency Matrix
Adaptations to Hierarchical
clustering
• Similarity distance calculation
N
Dis tan ce( x, y ) 
• FOIL
 AdjacencyMatrix( x, i)  AdjacencyMatrix( y, i)
i 1
N
 AdjacencyMatrix( x, i)  AdjacencyMatrix( y, i)
i 1
Interesting Features in the
Dendrogram and Adjacency
Matrix
Dendrogram and Adjacency
Matrix Demo
Then switch to SOM and
Node Link
Magic… Hierarchy from Flatness and
Clarity of Thought - Overview
Behind the Scenes
Convert articles into vectors
Compress the vectors to 24-bit space
Apply vector to random SOM
Best matching unit (BMU) learns and so does
its neighbors – Mexican hat
Group Clusters – low dimensional grouping
Create Node-Link Graph
Results
Proves a large corpus of articles can be
reconstructed
into
a
meaningful
hierarchy
This hierarchy can then be traversed to
explore articles
The node-link representation delivers a
clear distance between nodes and
relationship among nodes
Lessons learned… where to begin
Don’t bite off more than you can chew, in other words if
it sounds like you are going to save the world, it might
take more than 6 weeks to do it.
When up against a short deadline, don’t try to learn a
new language even if they swear it decreases
development time and a 6 year old can use it. (in
other words Caveat Emptor)
There is always time to design no matter how small you
think your program will be.
Conceptually problems are easy to solve…. Practically
they aren’t
Analysis, user feedback,
conclusion, questions…