ML Anthology

Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach

Jiayu Zhou, Youfang Lin, Xi Wang
AAAI 2008 pp. 1838-1839
/aaai/2008/zhou2008aaai-visualization/

Abstract

In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimization process, we introduce subgraph rotating and scaling processes into the genetic algorithm. Compared with existing methods, the proposed approach is more feasible and promising, with more accurate graph layout and more satisfiable computationally efficient performance, as demonstrated by the experimental results.

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Cite

Text

Zhou et al. "Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach." AAAI Conference on Artificial Intelligence, 2008.

Markdown

[Zhou et al. "Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach." AAAI Conference on Artificial Intelligence, 2008.](https://mlanthology.org/aaai/2008/zhou2008aaai-visualization/)

BibTeX

@inproceedings{zhou2008aaai-visualization,
  title     = {{Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach}},
  author    = {Zhou, Jiayu and Lin, Youfang and Wang, Xi},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2008},
  pages     = {1838-1839},
  url       = {https://mlanthology.org/aaai/2008/zhou2008aaai-visualization/}
}