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A fast multi-scale method for drawing large graphs." GraphDrawing. (2001)

by David Harel, Yehuda Koren
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Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data

by Danny Holten - IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS , 2006
"... A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., non-hierarchical edge ..."
Abstract - Cited by 271 (12 self) - Add to MetaCart
A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., non-hierarchical edges, together. We realize this as follows. We assume that the hierarchy is shown via a standard tree visualization method. Next, we bend each adjacency edge, modeled as a B-spline curve, toward the polyline defined by the path via the inclusion edges from one node to another. This hierarchical bundling reduces visual clutter and also visualizes implicit adjacency edges between parent nodes that are the result of explicit adjacency edges between their respective child nodes. Furthermore, hierarchical edge bundling is a generic method which can be used in conjunction with existing tree visualization techniques. We illustrate our technique by providing example visualizations and discuss the results based on an informal evaluation provided by potential users of such visualizations.
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... Issues with regard to computational complexity and layout stability have also been associated with force-directed methods [15]. However, these issues have recently been treated by various approaches =-=[14, 17]-=-. Most of these approaches also use a deterministic model to prevent the highly unpredictable layouts that were often produced by previous force-directed methods. Another method for drawing compound g...

Graph drawing by stress majorization

by Emden R. Gansner, Yehuda Koren, Stephen North - GRAPH DRAWING , 2004
"... One of the most popular graph drawing methods is based of achieving graphtheoretic target ditsances. This method was used by Kamada and Kawai [15], who formulated it as an energy optimization problem. Their energy is known in the multidimensional scaling (MDS) community as the stress function. In th ..."
Abstract - Cited by 96 (13 self) - Add to MetaCart
One of the most popular graph drawing methods is based of achieving graphtheoretic target ditsances. This method was used by Kamada and Kawai [15], who formulated it as an energy optimization problem. Their energy is known in the multidimensional scaling (MDS) community as the stress function. In this work, we show how to draw graphs by stress majorization, adapting a technique known in the MDS community for more than two decades. It appears that majorization has advantages over the technique of Kamada and Kawai in running time and stability. We also present a few extensions to the basic energy model which can improve layout quality and computation speed in practice. Majorization-based optimization is essential to these extensions.
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...ch we based our comparisons differs slightly from the implementation originally suggested [15]. We are using the more common implementation which replaces the two nested loops with a single loop; see =-=[2, 11]-=-. As noted in BranStress 2.5 1.5 0.5 x 105 3 2 1 0 Stress 4 3.5 3 2.5 2 1.5 1 0.5 x 10 5 Majorization Kamada−Kawai Qh882 0 0.5 1 1.5 2 2.5 3 3.5 Time (sec.) Fig. 1. Stress function vs. running time f...

Network Visualization by Semantic Substrates

by Ben Shneiderman, Senior Member, Aleks Aris - IEEE Transactions on Visualization and Computer Graphics
"... Abstract—Networks have remained a challenge for information visualization designers because of the complex issues of node and link layout coupled with the rich set of tasks that users present. This paper offers a strategy based on two principles: (1) layouts are based on user-defined semantic substr ..."
Abstract - Cited by 94 (8 self) - Add to MetaCart
Abstract—Networks have remained a challenge for information visualization designers because of the complex issues of node and link layout coupled with the rich set of tasks that users present. This paper offers a strategy based on two principles: (1) layouts are based on user-defined semantic substrates, which are non-overlapping regions in which node placement is based on node attributes, (2) users interactively adjust sliders to control link visibility to limit clutter and thus ensure comprehensibility of source and destination. Scalability is further facilitated by user control of which nodes are visible. We illustrate our semantic substrates approach as implemented in NVSS 1.0 with legal precedent data for up to 1122 court cases in three regions with 7645 legal citations. Index Terms — Network visualization, semantic substrate, information visualization, graphical user interfaces. 1
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... to describe the connections between connected pair of nodes ([23], [24]) or simulated annealing, which alludes to the process of heating and cooling metals ([9], [20]). Multi-scale algorithms ([18], =-=[19]-=-) are scalable versions of force-directed methods that work on a coarse representation of a large network, which refine the layout locally to achieve remarkably rapid layout for large networks (10 6 n...

Force-Directed Edge Bundling for Graph Visualization

by Danny Holten, Jarke J. Van Wijk , 2009
"... Graphs depicted as node-link diagrams are widely used to show relationships between entities. However, nodelink diagrams comprised of a large number of nodes and edges often suffer from visual clutter. The use of edge bundling remedies this and reveals high-level edge patterns. Previous methods requ ..."
Abstract - Cited by 81 (1 self) - Add to MetaCart
Graphs depicted as node-link diagrams are widely used to show relationships between entities. However, nodelink diagrams comprised of a large number of nodes and edges often suffer from visual clutter. The use of edge bundling remedies this and reveals high-level edge patterns. Previous methods require the graph to contain a hierarchy for this, or they construct a control mesh to guide the edge bundling process, which often results in bundles that show considerable variation in curvature along the overall bundle direction. We present a new edge bundling method that uses a self-organizing approach to bundling in which edges are modeled as flexible springs that can attract each other. In contrast to previous methods, no hierarchy is used and no control mesh. The resulting bundled graphs show significant clutter reduction and clearly visible high-level edge patterns. Curvature variation is furthermore minimized, resulting in smooth bundles that are easy to follow. Finally, we present a rendering technique that can be used to emphasize the bundling.

Graph Drawing by High-Dimensional Embedding

by David Harel, Yehuda Koren - In GD02, LNCS , 2002
"... We present a novel approach to the aesthetic drawing of undirected graphs. The method has two phases: first embed the graph in a very high dimension and then project it into the 2-D plane using PCA. Experiments we have carried out show the ability of the method to draw graphs of 10 nodes in few seco ..."
Abstract - Cited by 73 (10 self) - Add to MetaCart
We present a novel approach to the aesthetic drawing of undirected graphs. The method has two phases: first embed the graph in a very high dimension and then project it into the 2-D plane using PCA. Experiments we have carried out show the ability of the method to draw graphs of 10 nodes in few seconds. The new method appears to have several advantages over classical methods, including a significantly better running time, a useful inherent capability to exhibit the graph in various dimensions, and an effective means for interactive exploration of large graphs.
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...e is still the second issue of getting out of the initial random placement. Both these issues receive adequate treatment by incorporating the multi-scale strategy as suggested by several authors; see =-=[9, 10, 11, 21]-=-. These methods considerably improve running times by rapidly constructing a simplified initial globally nice layout and then refining it locally. The fastest of them all, [21], draws a 10 5 -node gra...

ACE: A Fast Multiscale Eigenvector Computation for Drawing Huge Graphs

by Yehuda Koren, Liran Carmel, David Harel , 2002
"... We present an extremely fast graph drawing algorithm for very large graphs, which we term ACE (for Algebraic multigrid Computation of Eigenvectors). ACE finds an optimal drawing by minimizing a quadratic energy function due to Hall, using a novel algebraic multigrid technique. The algorithm exhibits ..."
Abstract - Cited by 73 (13 self) - Add to MetaCart
We present an extremely fast graph drawing algorithm for very large graphs, which we term ACE (for Algebraic multigrid Computation of Eigenvectors). ACE finds an optimal drawing by minimizing a quadratic energy function due to Hall, using a novel algebraic multigrid technique. The algorithm exhibits an improvement of something like two orders of magnitude over the fastest algorithms we are aware of; it draws graphs of a million nodes in less than a minute. Moreover, the algorithm can deal with more general entities, such as graphs with masses and negative weights (to be defined in the text), and it appears to be applicable outside of graph drawing too.

TopoLayout: Multi-level graph layout by topological features

by Daniel Archambault, Tamara Munzner, David Auber - IEEE TRANS. VISUALIZATION AND COMPUTER GRAPHICS , 2007
"... We describe TopoLayout, a feature-based, multi-level algorithm that draws undirected graphs based on the topological features they contain. Topological features are detected recursively inside the graph, and their subgraphs are collapsed into single nodes, forming a graph hierarchy. Each feature is ..."
Abstract - Cited by 60 (6 self) - Add to MetaCart
We describe TopoLayout, a feature-based, multi-level algorithm that draws undirected graphs based on the topological features they contain. Topological features are detected recursively inside the graph, and their subgraphs are collapsed into single nodes, forming a graph hierarchy. Each feature is drawn with an algorithm tuned for its topology. As would be expected from a feature-based approach, the runtime and visual quality of TopoLayout depends on the number and types of topological features present in the graph. We show experimental results comparing speed and visual quality for TopoLayout against four other multi-level algorithms on a variety of datasets with a range of connectivities and sizes. TopoLayout frequently improves the results in terms of speed and visual quality on these datasets.
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...ing operator to construct the hierarchy. The maximal matching problem is to select the largest possible set of edges in the graph such that no two edges are incident to the same node. Harel and Koren =-=[19]-=- recursively apply an approximate solution to the k-centres problem, using graph theoretic distance as the ideal distance between two nodes. The k-centres problem groups a set of points into k cluster...

An Energy Model for Visual Graph Clustering

by Andreas Noack - Proceedings of the 11th International Symposium on Graph Drawing (GD 2003), LNCS 2912 , 2003
"... We introduce an energy model whose minimum energy drawings reveal the clusters of the drawn graph. Here a cluster is a set of nodes with many internal edges and few edges to nodes outside the set. The drawings of the bestknown force and energy models do not clearly show clusters for graphs whose ..."
Abstract - Cited by 59 (4 self) - Add to MetaCart
We introduce an energy model whose minimum energy drawings reveal the clusters of the drawn graph. Here a cluster is a set of nodes with many internal edges and few edges to nodes outside the set. The drawings of the bestknown force and energy models do not clearly show clusters for graphs whose diameter is small relative to the number of nodes. We formally characterize the minimum energy drawings of our energy model. This characterization shows in what sense the drawings separate clusters, and how the distance of separated clusters to the other nodes can be interpreted.
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... implement, adaptable to different drawing criteria, and give satisfactory results for many graphs ([4, Chap. 10], [7]). Since the introduction of multi-scale algorithms they are even quite efficient =-=[28,15,17,26,29]-=-. Energy-based methods generally have two parts: an energy model, and an algorithm that searches a state with minimum total energy. In force-directed methods, the model is a force system, and an algor...

GRIP: Graph dRawing with Intelligent Placement -- Short System Demonstration

by Pawel Gajer, Stephen G. Kobourov
"... This paper describes a system for Graph dRawing with Intelligent Placement, GRIP. The GRIP system is designed for drawing large graphs and uses a novel multi-dimensional force-directed method together with fast energy function minimization. The system allows for drawing graphs with tens of thousa ..."
Abstract - Cited by 50 (9 self) - Add to MetaCart
This paper describes a system for Graph dRawing with Intelligent Placement, GRIP. The GRIP system is designed for drawing large graphs and uses a novel multi-dimensional force-directed method together with fast energy function minimization. The system allows for drawing graphs with tens of thousands of vertices in under a minute on a mid-rage PC. To the best of the authors' knowledge GRIP surpasses the fastest previous algorithms. However, speed is not achieved at the expense of quality as the resulting drawings are quite aesthetically pleasing.

MGV: A System for Visualizing Massive Multi-Digraphs

by James Abello, Jeffrey Korn - IEEE Transactions on Visualization and Computer Graphics , 2002
"... We describe MGV, an integrated visualization and exploration system for massive multi-digraph navigation. ..."
Abstract - Cited by 41 (7 self) - Add to MetaCart
We describe MGV, an integrated visualization and exploration system for massive multi-digraph navigation.
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...of the corresponding multi-level drawings depends heavily on the initial embedding of the graph on the plane. Recently, force-directed methods have been considered for the drawing of large graphs. In =-=[37]-=-, a hierarchy of subgraphs is associated with a large graph. One fundamental step of the algorithm is the use of the all-pairs shortest paths making its applicability to very large graphs limited sinc...

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