5,808 research outputs found
Dynamic Multilevel Graph Visualization
We adapt multilevel, force-directed graph layout techniques to visualizing
dynamic graphs in which vertices and edges are added and removed in an online
fashion (i.e., unpredictably). We maintain multiple levels of coarseness using
a dynamic, randomized coarsening algorithm. To ensure the vertices follow
smooth trajectories, we employ dynamics simulation techniques, treating the
vertices as point particles. We simulate fine and coarse levels of the graph
simultaneously, coupling the dynamics of adjacent levels. Projection from
coarser to finer levels is adaptive, with the projection determined by an
affine transformation that evolves alongside the graph layouts. The result is a
dynamic graph visualizer that quickly and smoothly adapts to changes in a
graph.Comment: 21 page
Explorative Graph Visualization
Netzwerkstrukturen (Graphen) sind heutzutage weit verbreitet. Ihre Untersuchung dient dazu, ein besseres Verständnis ihrer Struktur und der durch sie modellierten realen Aspekte zu gewinnen. Die Exploration solcher Netzwerke wird zumeist mit Visualisierungstechniken unterstützt. Ziel dieser Arbeit ist es, einen Überblick über die Probleme dieser Visualisierungen zu geben und konkrete Lösungsansätze aufzuzeigen. Dabei werden neue Visualisierungstechniken eingeführt, um den Nutzen der geführten Diskussion für die explorative Graphvisualisierung am konkreten Beispiel zu belegen.Network structures (graphs) have become a natural part of everyday life and their analysis helps to gain an understanding of their inherent structure and the real-world aspects thereby expressed. The exploration of graphs is largely supported and driven by visual means. The aim of this thesis is to give a comprehensive view on the problems associated with these visual means and to detail concrete solution approaches for them. Concrete visualization techniques are introduced to underline the value of this comprehensive discussion for supporting explorative graph visualization
RDF Knowledge Graph Visualization From a Knowledge Extraction System
In this paper, we present a system to visualize RDF knowledge graphs. These
graphs are obtained from a knowledge extraction system designed by
GEOLSemantics. This extraction is performed using natural language processing
and trigger detection. The user can visualize subgraphs by selecting some
ontology features like concepts or individuals. The system is also
multilingual, with the use of the annotated ontology in English, French, Arabic
and Chinese
Visual Mining of Epidemic Networks
We show how an interactive graph visualization method based on maximal
modularity clustering can be used to explore a large epidemic network. The
visual representation is used to display statistical tests results that expose
the relations between the propagation of HIV in a sexual contact network and
the sexual orientation of the patients.Comment: 8 page
On labeling in graph visualization
Cataloged from PDF version of article.When visualizing graphs, it is essential to communicate the meaning of each graph object via text or graphical labels.
Automatic placement of labels in a graph is an NP-Hard problem, for which efficient heuristic solutions have been recently
developed. In this paper, we describe a general framework for modeling, drawing, editing, and automatic placement of
labels respecting user constraints. In addition, we present the interface and the basic engine of the Graph Editor Toolkit
– a family of portable graph visualization libraries designed for integration into graphical user interface application programs.
This toolkit produces a high quality automated placement of labels in a graph using our framework. A brief survey
of automatic label placement algorithms is also presented. Finally we describe extensions to certain existing automatic
label placement algorithms, allowing their integration into this visualization tool.
(C) 2007 Elsevier Inc. All rights reserved
Interactive, tree-based graph visualization
We introduce an interactive graph visualization scheme that allows users to explore graphs by viewing them as a sequence of spanning trees, rather than the entire graph all at once. The user determines which spanning trees are displayed by selecting a vertex from the graph to be the root. Our main contributions are a graph drawing algorithm that generates meaningful representations of graphs using extracted spanning trees, and a graph animation algorithm for creating smooth, continuous transitions between graph drawings. We conduct experiments to measure how well our algorithms visualize graphs and compare them to another visualization scheme
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