Force‐Directed Edge Bundling for Graph Visualization

By Danny Holten, Jack van Wijk. 2009

662 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Yingcai Wu
2. Jun Zhu
3. Mengchen Liu
4. Z. Li
5. Jiaxin Shi
6. Chongxuan Li
7. Ronghua Liang
8. Guodao Sun

In Computer Graphics and Computer-Aided Design

1. Yingcai Wu
2. Jun Zhu
3. Mengchen Liu
4. Ronghua Liang
5. Guodao Sun
6. Shixia Liu

In Computer Vision and Pattern Recognition

1. Jun Zhu
2. Shixia Liu
3. Chongxuan Li
4. Mengchen Liu
5. Yingcai Wu
6. Ronghua Liang
7. Guodao Sun
8. Jiaxin Shi

Citations in the corpus

• Towards Better Analysis of Deep Convolutional Neural Networks (2016, methodology): “In order to reduce visual clutter, we tried the geometry-based edge bundling method [14, 25, 39] to cluster the edges between two layers.”
• An Uncertainty-Aware Approach for Exploratory Microblog Retrieval (2015, methodology): “In [19], the last item is the electrostatic force Fe = 1/‖ei − e j‖.”
• A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges (2013, methodology): “The work was extended to bundle edges in a graph using a force-directed technique without the need of hierarchy information([103]).”
• A survey on information visualization: recent advances and challenges (2014, neutral): “Graph visualization [3,8,9,13,19,20,30,36,40,42,59,62,85,91,118,120,51,133,162,167, 164,170] Text visualization [1,5,22,32,31,83,92–94,154,159,163,169]”