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224
BigBang Simulation for Embedding Network Distances in Euclidean Space
, 2004
"... Embedding of a graph metric in Euclidean space efficiently and accurately is an important problem in general with applications in topology aggregation, closest mirror selection, and application level routing. We propose a new graph embedding scheme called BigBang Simulation (BBS), which simulates a ..."
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Cited by 152 (4 self)
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Embedding of a graph metric in Euclidean space efficiently and accurately is an important problem in general with applications in topology aggregation, closest mirror selection, and application level routing. We propose a new graph embedding scheme called BigBang Simulation (BBS), which simulates an explosion of particles under force field derived from embedding error. BBS is shown to be significantly more accurate, compared to all other embedding methods including GNP. We report an extensive simulation study of BBS compared with several known embedding schemes and show its advantage for distance estimation (as in the IDMaps project), mirror selection and topology aggregation.
A fast adaptive layout algorithm for undirected graphs
, 1995
"... Abstract. We present a randomized adaptive layout algorithm for nicely drawing undirected graphs that is based on the springembedder paradigm and contains several new heuristics to improve the convergence, including local temperatures, gravitational forces and the detection of rotations and oscilla ..."
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Cited by 134 (1 self)
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Abstract. We present a randomized adaptive layout algorithm for nicely drawing undirected graphs that is based on the springembedder paradigm and contains several new heuristics to improve the convergence, including local temperatures, gravitational forces and the detection of rotations and oscillations. The proposed algorithm achieves drawings of high quality on a wide range of graphs with standard settings. Moreover, the algorithm is fast, being thus applicable on general undirected graphs of substantially larger size and complexity than before [9, 6, 3]. Aesthetically pleasing solutions are found in most cases. We give empirical data for the running time of the algorithm and the quality of the computed layouts. 1
A Multilevel Algorithm for ForceDirected GraphDrawing
, 2003
"... We describe a heuristic method for drawing graphs which uses a multilevel framework combined with a forcedirected placement algorithm. ..."
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Cited by 112 (3 self)
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We describe a heuristic method for drawing graphs which uses a multilevel framework combined with a forcedirected placement algorithm.
Network Visualization by Semantic Substrates
 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 userdefined semantic substr ..."
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Cited by 95 (8 self)
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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 userdefined semantic substrates, which are nonoverlapping 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
A Fast MultiScale Method for Drawing Large Graphs
 JOURNAL OF GRAPH ALGORITHMS AND APPLICATIONS
, 2002
"... We present a multiscale layout algorithm for the aesthetic drawing of undirected graphs with straightline edges. The algorithm is extremely fast, and is capable of drawing graphs that are substantially larger than those we have encountered in prior work. For example, the paper contains a drawi ..."
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Cited by 92 (10 self)
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We present a multiscale layout algorithm for the aesthetic drawing of undirected graphs with straightline edges. The algorithm is extremely fast, and is capable of drawing graphs that are substantially larger than those we have encountered in prior work. For example, the paper contains a drawing of a graph with over 15,000 vertices. Also we achieve "nice" drawings of 1000 vertex graphs in about 1 second. The proposed algorithm embodies a new multiscale scheme for drawing graphs, which was motivated by the earlier multiscale algorithm of Hadany and Harel [HH99]. In principle, it could significantly improve the speed of essentially any forcedirected method (regardless of that method's ability of drawing weighted graphs or the continuity of its costfunction).
NicheWorks  interactive visualization of very large graphs
, 1999
"... The difference between displaying networks with 100–1,000 nodes and displaying ones with 10,000–100,000 nodes is not merely quantitative, it is qualitative. Layout algorithms suitable for the former are too slow for the latter, requiring new algorithms or modified (often relaxed) versions of existin ..."
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Cited by 74 (0 self)
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The difference between displaying networks with 100–1,000 nodes and displaying ones with 10,000–100,000 nodes is not merely quantitative, it is qualitative. Layout algorithms suitable for the former are too slow for the latter, requiring new algorithms or modified (often relaxed) versions of existing algorithms to be invented. The density of nodes and edges displayed per inch of screen real estate requires special visual techniques to filter the graphs and focus attention. Compounding the problem is that large reallife networks are often weighted graphs and usually have additional data associated with the nodes and edges. A system for investigating and exploring such large, complex datasets needs to be able to display both graph structure and node and edge attributes so that patterns and information hidden in the data can be seen. In this article we describe a tool that addresses these needs, the NicheWorks tool. We describe and comment on the available layout algorithms and the linked views interaction system, and detail two examples of the use of NicheWorks for analyzing Web sites and detecting international telephone fraud.
A Bayesian Paradigm for Dynamic Graph Layout
, 1997
"... Dynamic graph layout refers to the layout of graphs that change over time. These changes are due to user interaction, algorithms, or other underlying processes determining the graph. Typically, users spend a noteworthy amount of time to get familiar with a layout, i.e. ..."
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Cited by 74 (14 self)
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Dynamic graph layout refers to the layout of graphs that change over time. These changes are due to user interaction, algorithms, or other underlying processes determining the graph. Typically, users spend a noteworthy amount of time to get familiar with a layout, i.e.
Graph Drawing by HighDimensional Embedding
 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 2D plane using PCA. Experiments we have carried out show the ability of the method to draw graphs of 10 nodes in few seco ..."
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Cited by 73 (10 self)
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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 2D 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.
ACE: A Fast Multiscale Eigenvector Computation for Drawing Huge Graphs
, 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 ..."
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Cited by 73 (13 self)
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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.