Drawing Large Graphs with a Potential-Field-Based Multilevel Algorithm
By Stefan Hachul, Michael Jünger. International Symposium Graph Drawing and Network Visualization, 2004
316 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/3a389251f7e3879622eff52da5493cdc56a0ace4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jack van Wijk
- Jean-Daniel Fekete
- Arjan Kuijper
- Yifan Hu
- Stephen G. Kobourov
- J. C. Roberts
- Nathalie Henry Riche
- Jeffrey Heer
In Computer Vision and Pattern Recognition
- Jack van Wijk
- Jean-Daniel Fekete
- Arjan Kuijper
- Jörn Kohlhammer
- Tobias Schreck
- Yifan Hu
- Stephen G. Kobourov
- Shixia Liu
Citations in the corpus
- Spring Embedders and Force Directed Graph Drawing Algorithms (2012, background): “Hachul and Jünger [36] address this problem in their 2004 multilevel algorithm.”
- Visual Analysis of Large Graphs: State‐of‐the‐Art and Future Research Challenges (2011, background): “In this case, the nodes and possibly also edges of the graph have an inherent geographic location, which needs to be taken into consideration in their graphic presentation.”
- Efficient, High-Quality Force-Directed Graph Drawing (2006, methodology): “After the completion of this article, our attention was drawn to an independent work by Hachul and Jünger [28].”
- Energy Models for Graph Clustering (2007, unknown): “Ecient multi-scale algorithms for energy-based graph layout have been developed by Gajer et al. [21], Harel and Koren [27], Walshaw [51], and Hachul and J unger [ 24 ].”