![](bg8.png)
Harrison, Ryan, and Wang. From these, Wang, Dou,
Ribarsky, and Chang co-authored the paper “Parallel-
Topics: A Probabilistic Approach to Exploring Doc-
ument Collections” shown in Cluster B and related
to text and document visualization. The other paper
“Evaluating the Relationship Between User Interac-
tion and Financial Visual Analysis”—shown on the
lower right hand side (Cluster C) of Figure 9—was
written by Jeong, Dou, Chang, Ribarsky, Lipford, and
Stukes and published in 2008 at the VAST confer-
ence as well. This shows that a group of authors has
worked together in various topics of visual analytics
since their papers are found in different clusters, but
they are related to each other.
6 CONCLUSIONS AND FUTURE
WORK
A set of new techniques for the visual analysis of mul-
tivariate network clusters has been presented in this
paper. They facilitate the exploration of clustered data
by (1) showing the cluster content through the use of
tag clouds and (2) giving insight into the underlying
network through the use of two different cluster lay-
out techniques and edge routing algorithms. The anal-
ysis process is enriched with various interaction tech-
niques, such as interactive edge filtering.
There are several improvements that could further
strengthen our prototype. At the moment, only one at-
tribute can be mapped to the nodes. By simply adding
more donut slices on top of the existing node ring and
using different colors, it is possible to visualize more
attributes. This approach might be limited, because
the size of the node rings will increase. Another im-
provement would be to introduce standard zooming
and panning. At the current state, our implementa-
tion does not allow this due to the Java 2D graphics
renderer performance. Therefore, we have to port the
application to OpenGL. The edge routing algorithm
in the circular cluster layout can be improved by rout-
ing the edges directly between cluster neighbors. This
will help to reduce clutter in the center, but it might
introduce a lot of additional edge crossings around
the clusters. Another possibility for clutter reduction
is to display the most interesting edges first (subject
to user defined parameters) and to add more on de-
mand. The current interaction possibilities have to be
extended, for instance, by multiple selection of nodes
in order to provide comparisons of the concept terms
between related documents inside and outside of the
same cluster. Last but not least, we have to evaluate
our approach with respect to usability, efficiency, and
scalability.
ACKNOWLEDGEMENTS
We would like to thank Alfredo Gimenez for carefully
proof-reading the final version of this paper.
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