We propose a new graph layout method based on a modification of the t-distributed Stochastic Neighbor Embedding (t-SNE) dimensionality reduction technique. Although t-SNE is one of the best techniques for visualizing high-dimensional data as 2D scatterplots, t-SNE has not been used in the context of classical graph layout. We propose a new graph layout method, tsNET, based on representing a graph with a distance matrix, which together with a modified t-SNE cost function results in desirable layouts. We evaluate our method by a formal comparison with state-of-the-art methods, both visually and via established quality metrics on a comprehensive benchmark, containing real-world and synthetic graphs. As evidenced by the quality metrics and visual inspection, tsNET produces excellent layouts.
|Number of pages||12|
|Journal||COMPUTER GRAPHICS FORUM|
|Publication status||Published - Jun-2017|
|Event||19th Eurographics/IEEE VGTC Conference on Visualization (EuroVis) - Barcelona, Spain|
Duration: 12-Jun-2017 → 16-Jun-2017
- VISUAL ANALYSIS