Enhancing graph drawings through edge bundling using clustering ensembles
Edge bundling is a technique used to improve the readability of large graph drawings by grouping edges to reduce visual complexity. This paper treats this task as a clustering problem, using compatibility metrics to evaluate solutions in an optimization pipeline combined with a clustering ensemble a...
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| Veröffentlicht in: | Information visualization 2024-10, Vol.23 (4), p.366-383 |
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| container_title | Information visualization |
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| creator | Vieira, Raissa dos Santos do Nascimento, Hugo Alexandre Dantas Ferreira, Joelma de Moura Foulds, Les |
| description | Edge bundling is a technique used to improve the readability of large graph drawings by grouping edges to reduce visual complexity. This paper treats this task as a clustering problem, using compatibility metrics to evaluate solutions in an optimization pipeline combined with a clustering ensemble approach. The aim is to present the Clustering Ensemble-based Edge Bundling (CEBEB) method for solving the General-based Edge Bundling (GBEB) problem and report results for some given graphs. The CEBEB method proved very promising and generated better solutions than an existing evolutionary algorithm. Additionally, the paper introduces a new ensemble algorithm, specific for the GBEB, and reviews some previous results. |
| doi_str_mv | 10.1177/14738716241239619 |
| format | Article |
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| ispartof | Information visualization, 2024-10, Vol.23 (4), p.366-383 |
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| language | eng |
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| source | SAGE Journals |
| subjects | Bundling Clustering Evolutionary algorithms Graph theory Machine learning Optimization Readability Visual tasks |
| title | Enhancing graph drawings through edge bundling using clustering ensembles |
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