Graph drawing by force-directed placement
Software—Practice & Experience
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Research report: Interacting with huge hierarchies: beyond cone trees
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
Energy-based clustering of graphs with nonuniform degrees
GD'05 Proceedings of the 13th international conference on Graph Drawing
GD'04 Proceedings of the 12th international conference on Graph Drawing
Crossing reduction in circular layouts
WG'04 Proceedings of the 30th international conference on Graph-Theoretic Concepts in Computer Science
Readable Representations for Large-Scale Bipartite Graphs
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Graph visualization with latent variable models
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Survey: Cycle bases in graphs characterization, algorithms, complexity, and applications
Computer Science Review
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The need to visualize large and complex networks has strongly increased in the last decade. Although networks with more than 1000 vertices seem to be prohibitive for a comprehensive layout, real-world networks exhibit a very inhomogenous edge density that can be harnessed to derive an aesthetic and structured layout. Here, we will present a heuristic that finds a spanning tree with a very low average spanner property for the non-tree edges, the so-called backbone of a network. This backbone can then be used to apply a modified tree-layout algorithm to draw the whole graph in a way that highlights dense parts of the graph, so-called clusters, and their inter-connections.