Skip to main content

previous disabled Page of 5
and
  1. No Access

    Chapter and Conference Paper

    Shape-Faithful Graph Drawings

    Shape-based metrics measure how faithfully a drawing D represents the structure of a graph G, using the proximity graph S of D. While some limited graph classes admit proximity drawings (i.e., optimally shape-fai...

    Amyra Meidiana, Seok-Hee Hong, Peter Eades in Graph Drawing and Network Visualization (2023)

  2. No Access

    Chapter and Conference Paper

    CelticGraph: Drawing Graphs as Celtic Knots and Links

    Celtic knots are an ancient art form often attributed to Celtic cultures, used to decorate monuments and manuscripts, and to symbolise eternity and interconnectedness. This paper describes the framework CelticGra...

    Peter Eades, Niklas Gröne, Karsten Klein in Graph Drawing and Network Visualization (2023)

  3. Article

    Open Access

    BC tree-based spectral sampling for big complex network visualization

    Graph sampling methods have been used to reduce the size and complexity of big complex networks for graph mining and visualization. However, existing graph sampling methods often fail to preserve the connectiv...

    **gming Hu, Tuan Tran Chu, Seok-Hee Hong, Jialu Chen in Applied Network Science (2021)

  4. No Access

    Chapter and Conference Paper

    Connectivity-Based Spectral Sampling for Big Complex Network Visualization

    Graph sampling methods have been used to reduce the size and complexity of big complex networks for graph mining and visualization. However, existing graph sampling methods often fail to preserve the connectiv...

    **gming Hu, Seok-Hee Hong, Jialu Chen in Complex Networks & Their Applications IX (2021)

  5. No Access

    Chapter and Conference Paper

    Spectral Vertex Sampling for Big Complex Graphs

    This paper introduces a new vertex sampling method for big complex graphs, based on the spectral sparsification, a technique to reduce the number of edges in a graph while retaining its structural properties. Mo...

    **gming Hu, Seok-Hee Hong, Peter Eades in Complex Networks and Their Applications VIII (2020)

  6. No Access

    Chapter and Conference Paper

    New Quality Metrics for Dynamic Graph Drawing

    In this paper, we present new quality metrics for dynamic graph drawings. Namely, we present a new framework for change faithfulness metrics for dynamic graph drawings, which compare the ground truth change in dy...

    Amyra Meidiana, Seok-Hee Hong, Peter Eades in Graph Drawing and Network Visualization (2020)

  7. No Access

    Article

    BJR-tree: fast skyline computation algorithm using dominance relation-based tree structure

    High-throughput label-free single-cell screening technology has been studied for the noninvasive analysis of various kinds of cells. Selecting the prominent cells with extreme features from a large number of c...

    Kenichi Koizumi, Peter Eades, Kei Hiraki in International Journal of Data Science and … (2019)

  8. Chapter and Conference Paper

    Multi-level Graph Drawing Using Infomap Clustering

    Infomap clustering finds the community structures that minimize the expected description length of a random walk trajectory; algorithms for infomap clustering run fast in practice for large graphs. In this paper ...

    Seok-Hee Hong, Peter Eades, Marnijati Torkel in Graph Drawing and Network Visualization (2019)

  9. Chapter and Conference Paper

    A Quality Metric for Visualization of Clusters in Graphs

    Traditionally, graph quality metrics focus on readability, but recent studies show the need for metrics which are more specific to the discovery of patterns in graphs. Cluster analysis is a popular task within...

    Amyra Meidiana, Seok-Hee Hong, Peter Eades in Graph Drawing and Network Visualization (2019)

  10. Chapter and Conference Paper

    Turning Cliques into Paths to Achieve Planarity

    Motivated by hybrid graph representations, we introduce and study the following beyond-planarity problem, which we call \(h\) ...

    Patrizio Angelini, Peter Eades, Seok-Hee Hong in Graph Drawing and Network Visualization (2018)

  11. Chapter and Conference Paper

    Drawing Big Graphs Using Spectral Sparsification

    Spectral sparsification is a general technique developed by Spielman et al. to reduce the number of edges in a graph while retaining its structural properties. We investigate the use of spectral sparsification to...

    Peter Eades, Quan Nguyen, Seok-Hee Hong in Graph Drawing and Network Visualization (2018)

  12. Chapter and Conference Paper

    The Weighted Barycenter Drawing Recognition Problem

    We consider the question of whether a given graph drawing \(\varGamma \) of a triconnected planar graph G i...

    Peter Eades, Patrick Healy, Nikola S. Nikolov in Graph Drawing and Network Visualization (2018)

  13. Chapter and Conference Paper

    Gap-Planar Graphs

    We introduce the family of k-gap-planar graphs for \(k \ge 0\) , i.e., graphs that have a drawing in which e...

    Sang Won Bae, Jean-Francois Baffier, **hee Chun in Graph Drawing and Network Visualization (2018)

  14. No Access

    Chapter

    Graph Visualization

    Graphs provide a versatile model for data from a large variety of application domains, for example, software engineering, telecommunication, and biology. Understanding the information that is represented by th...

    Peter Eades, Karsten Klein in Graph Data Management (2018)

  15. Chapter and Conference Paper

    Simultaneous Orthogonal Planarity

    We introduce and study the \({\textsc {OrthoSEFE}\text {-}{k}} \) problem: Given k planar graphs each with ...

    Patrizio Angelini, Steven Chaplick in Graph Drawing and Network Visualization (2016)

  16. No Access

    Article

    A Linear-Time Algorithm for Testing Outer-1-Planarity

    A graph is 1-planar if it can be embedded in the plane with at most one crossing per edge. It is known that the problem of testing 1-planarity of a graph is NP-complete. In this paper, we study outer-1-planar gra...

    Seok-Hee Hong, Peter Eades, Naoki Katoh, Giuseppe Liotta, Pascal Schweitzer in Algorithmica (2015)

  17. Chapter and Conference Paper

    Shape-Based Quality Metrics for Large Graph Visualization

    We propose a new family of quality metrics for graph drawing; in particular, we concentrate on larger graphs. We illustrate these metrics with examples and apply the metrics to data from previous experiments, ...

    Peter Eades, Seok-Hee Hong, Karsten Klein in Graph Drawing and Network Visualization (2015)

  18. No Access

    Chapter and Conference Paper

    Straight-Line Drawability of a Planar Graph Plus an Edge

    We investigate straight-line drawings of topological graphs that consist of a planar graph plus one edge, also called almost-planar graphs. We present a characterization of such graphs that admit a straight-li...

    Peter Eades, Seok-Hee Hong, Giuseppe Liotta, Naoki Katoh in Algorithms and Data Structures (2015)

  19. No Access

    Article

    2-Layer Right Angle Crossing Drawings

    A 2-layer drawing represents a bipartite graph where each vertex is a point on one of two parallel lines, no two vertices on the same line are adjacent, and the edges are straight-line segments. In this paper ...

    Emilio Di Giacomo, Walter Didimo, Peter Eades, Giuseppe Liotta in Algorithmica (2014)

  20. Chapter and Conference Paper

    GION: Interactively Untangling Large Graphs on Wall-Sized Displays

    Data sets of very large graphs are now commonplace; the scale of these graphs presents considerable difficulties for graph visualization methods. The use of interactive techniques and large screens have been p...

    Michael R. Marner, Ross T. Smith, Bruce H. Thomas, Karsten Klein in Graph Drawing (2014)

previous disabled Page of 5