Visualization of information flows in a very large social network
Proceedings of the 2009 ACM symposium on Applied Computing
Structural differences between two graphs through hierarchies
Proceedings of Graphics Interface 2009
What does the user want to see?: what do the data want to be?
Information Visualization
TagNetLens: multiscale visualization of knowledge structures in social tags
Proceedings of the 3rd International Symposium on Visual Information Communication
Visual inspection of multivariate graphs
EuroVis'08 Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization
Image-based edge bundles: simplified visualization of large graphs
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
The readability of path-preserving clusterings of graphs
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Clustering, visualizing, and navigating for large dynamic graphs
GD'12 Proceedings of the 20th international conference on Graph Drawing
ChurnVis: visualizing mobile telecommunications churn on a social network with attributes
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Fast layout computation of clustered networks: Algorithmic advances and experimental analysis
Information Sciences: an International Journal
| Hi-index | 0.00 |
Several previous systems allow users to interactively explore a large input graph through cuts of a superimposed hierarchy. This hierarchy is often created using clustering algorithms or topological features present in the graph. However, many graphs have domain-specific attributes associated with the nodes and edges which could be used to create many possible hierarchies providing unique views of the input graph. GrouseFlocks is a system for the exploration of this graph hierarchy space. By allowing users to see several different possible hierarchies on the same graph, it allows users to investigate hierarchy space instead of a single, fixed hierarchy. GrouseFlocks provides a simple set of operations so that users can create and modify their graph hierarchies based on selections. These selections can be made manually or based on patterns in the attribute data provided with the graph. It provides feedback to the user within seconds, allowing interactive exploration of this space.