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Graph Layouts by t-SNE
University of Groningen, The Netherlands.
University of Groningen, The Netherlands.
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-2901-935X
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-0519-2537
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2017 (English)In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659Article in journal (Refereed) Accepted
Abstract [en]

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.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Visualization, Graph Drawing, Information Visualization, t-SNE, Dimensionality Reduction
National Category
Computer Science
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-62137OAI: oai:DiVA.org:lnu-62137DiVA: diva2:1087497
Conference
19th EG/VGTC Conference on Visualization (EuroVis '17), 12-16 June 2017, Barcelona, Spain
Note

TO BE PUBLISHED!

Available from: 2017-04-07 Created: 2017-04-07 Last updated: 2017-04-18

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Citation style
  • apa
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  • de-DE
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Output format
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