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Graph Clustering Using Multiway Ratio Cut
 PROC. OF GRAPH DRAWING, VOLUME 1353 OF LECT. NOTES IN COMPUT. SCI
, 1997
"... Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes. In this paper we report on the implementation of a ..."
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Cited by 22 (2 self)
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Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes. In this paper we report on the implementation of a clustering algorithm based on the idea of ratio cut, a well known technique used for circuit partitioning in the VLSI domain. The algorithm is implemented in WINDOWS95/NT environment. The performance of the clustering algorithm on some large graphs obtained from the archives of Bell Laboratories is presented.
GrouseFlocks: Steerable exploration of graph hierarchy space
 IEEE TRANS. ON VISUALIZATION AND COMPUTER GRAPHICS
, 2008
"... 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 domainspecific attributes associated with ..."
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Cited by 22 (7 self)
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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 domainspecific 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, the system helps users investigate graph 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.
Balanced Aspect Ratio Trees and Their Use for Drawing Very Large Graphs
 Journal of Graph Algorithms and Applications
, 1998
"... We describe a new approach for clusterbased drawing of large graphs, which obtains clusters by using binary space partition (BSP) trees. We also introduce a novel BSPtype decomposition, called the balanced aspect ratio (BAR) tree, which guarantees that the cells produced are convex and have bounde ..."
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Cited by 20 (9 self)
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We describe a new approach for clusterbased drawing of large graphs, which obtains clusters by using binary space partition (BSP) trees. We also introduce a novel BSPtype decomposition, called the balanced aspect ratio (BAR) tree, which guarantees that the cells produced are convex and have bounded aspect ratios. In addition, the tree depth is O(log n), and its construction takes O(n log n) time, where n is the number of points. We show that the BAR tree can be used to recursively divide a graph embedded in the plane into subgraphs of roughly equal size, such that the drawing of each subgraph has a balanced aspect ratio. As a result, we obtain a representation of a graph as a collection of O(log n) layers, where each succeeding layer represents the graph in an increasing level of detail. The overall running time of the algorithm is O(n log n+m+D0(G)), where n and m are the number of vertices and edges of the graph G, andD0(G) is the time it takes to obtain an initial embedding of G in the plane. In particular, if the graph is planar each layer is a graph drawn with straight lines and without crossings on the n×n grid and the running time reduces to O(n log n).
Density Functions for Visual Attributes and Effective Partitioning in Graph Visualization
, 2000
"... Two tasks in Graph Visualization require partitioning: the assignment of visual attributes and divisive clustering. Often, we would like to assign a color or other visual attributes to a node or edge that indicates an associated value. In an application involving divisive clustering, we would like t ..."
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Cited by 18 (4 self)
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Two tasks in Graph Visualization require partitioning: the assignment of visual attributes and divisive clustering. Often, we would like to assign a color or other visual attributes to a node or edge that indicates an associated value. In an application involving divisive clustering, we would like to partition the graph into subsets of graph elements based on metric values in such a way that all subsets are evenly populated. Assuming a uniform distribution of metric values during either partitioning or coloring can have undesired effects such as empty clusters or only one level of emphasis for the entire graph. Probability density functions derived from statistics about a metric can help systems succeed at these tasks. CR Categories and Subject Descriptors: I.3.6 [Computer Graphics]: Methodology and Techniques  Interaction Techniques; I.3.8 [Computer Graphics]: Applications Additional Keywords: graph visualization, graph navigation, metrics, clustering 1. INTRODUCTION A key issue...
GraphXML  An XML Based Graph Interchange Format
, 2000
"... GraphXML is a graph description language in XML that can be used as an interchange format for graph drawing and visualization packages. The generality and rich features of XML make it possible to define an interchange format that not only supports the pure, mathematical description of a graph, but a ..."
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Cited by 16 (2 self)
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GraphXML is a graph description language in XML that can be used as an interchange format for graph drawing and visualization packages. The generality and rich features of XML make it possible to define an interchange format that not only supports the pure, mathematical description of a graph, but also the needs of information visualization applications that use graphbased data structures.
Graph Clustering Using Distancek Cliques
 IN PROC. OF GRAPH DRAWING
, 1999
"... Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes. In this paper we report on the implementation of a clus ..."
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Cited by 16 (1 self)
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Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes. In this paper we report on the implementation of a clustering algorithm based on the idea of distancek cliques, a generalization of the idea of the cliques in graphs. The performance of the clustering algorithm on some large graphs obtained from the archives of Bell Laboratories is presented.
Completely connected clustered graphs
 IN PROC. 29TH INTL. WORKSHOP ON GRAPHTHEORETIC CONCEPTS IN COMPUTER SCIENCE (WG 2003), VOLUME 2880 OF LNCS
, 2003
"... Planar drawings of clustered graphs are considered. We introduce the notion of completely connected clustered graphs, i.e. hierarchically clustered graphs that have the property that not only every cluster but also each complement of a cluster induces a connected subgraph. As a main result, we prove ..."
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Cited by 15 (1 self)
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Planar drawings of clustered graphs are considered. We introduce the notion of completely connected clustered graphs, i.e. hierarchically clustered graphs that have the property that not only every cluster but also each complement of a cluster induces a connected subgraph. As a main result, we prove that a completely connected clustered graph is cplanar if and only if the underlying graph is planar. Further, we investigate the influence of the root of the inclusion tree to the choice of the outer face of the underlying graph and vice versa.
Understanding Complex Network Attack Graphs through Clustered Adjacency
 Matrices”, Proceedings of the 21st Annual Computer Security Applications Conference (ACSAC
, 2005
"... We apply adjacency matrix clustering to network attack graphs for attack correlation, prediction, and hypothesizing. We selfmultiply the clustered adjacency matrices to show attacker reachability across the network for a given number of attack steps, culminating in transitive closure for attack pre ..."
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Cited by 15 (2 self)
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We apply adjacency matrix clustering to network attack graphs for attack correlation, prediction, and hypothesizing. We selfmultiply the clustered adjacency matrices to show attacker reachability across the network for a given number of attack steps, culminating in transitive closure for attack prediction over all possible number of steps. This reachability analysis provides a concise summary of the impact of network configuration changes on the attack graph. Using our framework, we also place intrusion alarms in the context of vulnerabilitybased attack graphs, so that false alarms become apparent and missed detections can be inferred. We introduce a graphical technique that shows multiplestep attacks by matching rows and columns of the clustered adjacency matrix. This allows attack impact/responses to be identified and prioritized according to the number of attack steps to victim machines, and allows attack origins to be determined. Our techniques have quadratic complexity in the size of the attack graph. 1.
Untangling Euler Diagrams
 In Proc. IEEE Conf. on Information Visualization
, 2010
"... Abstract—In many common data analysis scenarios the data elements are logically grouped into sets. Venn and Euler style diagrams are a common visual representation of such set membership where the data elements are represented by labels or glyphs and sets are indicated by boundaries surrounding thei ..."
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Cited by 14 (2 self)
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Abstract—In many common data analysis scenarios the data elements are logically grouped into sets. Venn and Euler style diagrams are a common visual representation of such set membership where the data elements are represented by labels or glyphs and sets are indicated by boundaries surrounding their members. Generating such diagrams automatically such that set regions do not intersect unless the corresponding sets have a nonempty intersection is a difficult problem. Further, it may be impossible in some cases if regions are required to be continuous and convex. Several approaches exist to draw such set regions using more complex shapes, however, the resulting diagrams can be difficult to interpret. In this paper we present two novel approaches for simplifying a complex collection of intersecting sets into a strict hierarchy that can be more easily automatically arranged and drawn (Figure 1). In the first approach, we use compact rectangular shapes for drawing each set, attempting to improve the readability of the set intersections. In the second approach, we avoid drawing intersecting set regions by duplicating elements belonging to multiple sets. We compared both of our techniques to the traditional nonconvex region technique using five readability tasks. Our results show that the compact rectangular shapes technique was often preferred by experimental subjects even though the use of duplications dramatically improves the accuracy and performance time for most of our tasks. In addition to general set representation our techniques are also applicable to visualization of networks with intersecting clusters of nodes.
Visual understanding of metabolic pathways across organisms using layout in two and a half dimensions
 JOURNAL OF INTEGRATIVE BIOINFORMATICS
, 2004
"... We propose a method for visualizing a set of related metabolic pathways across organisms using 2 1/2 dimensional graph visualization. Interdependent, twodimensional layouts of each pathway are stacked on top of each other so that biologists get a full picture of subtle and significant differences am ..."
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Cited by 14 (8 self)
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We propose a method for visualizing a set of related metabolic pathways across organisms using 2 1/2 dimensional graph visualization. Interdependent, twodimensional layouts of each pathway are stacked on top of each other so that biologists get a full picture of subtle and significant differences among the pathways. The (dis)similarities between pathways are expressed by the Hamming distances of the underlying graphs which are used to compute a stacking order for the pathways. Layouts are determined by a global layout of the union of all pathway graphs using a variant of the proven Sugiyama approach for layered graph drawing. Our variant layout approach allows edges to cross if they appear in different graphs.