Bundling n-stars in polygonal maps

Victor Parque Tenorio; Tomoyuki Miyashita

doi:10.1109/ICTAI.2017.00063

Bundling n-stars in polygonal maps

Victor Parque Tenorio, Tomoyuki Miyashita

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper aims at computing minimal-length tree layouts given an n-star graph in a polygonal map. This problem is strongly related to the edge bundling problem, which consists of compounding the edges of an input graph to obtain topologically compact graph layouts being free of clutter and easy to visualize. Computational experiments using a diverse set of polygonal maps and number of edges in the input graph shows the feasibility, efficiency and robustness of our approach.

Original language	English
Title of host publication	Proceedings - 2017 International Conference on Tools with Artificial Intelligence, ICTAI 2017
Publisher	IEEE Computer Society
Pages	358-365
Number of pages	8
Volume	2017-November
ISBN (Electronic)	9781538638767
DOIs	https://doi.org/10.1109/ICTAI.2017.00063
Publication status	Published - 2018 Jun 4
Event	29th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2017 - Boston, United States Duration: 2017 Nov 6 → 2017 Nov 8

Other

Other	29th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2017
Country	United States
City	Boston
Period	17/11/6 → 17/11/8

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Keywords

Graph bundling
Minimal trees
Path planning
Polygonal maps

ASJC Scopus subject areas

Software
Artificial Intelligence
Computer Science Applications

Cite this

Parque Tenorio, V., & Miyashita, T. (2018). Bundling n-stars in polygonal maps. In Proceedings - 2017 International Conference on Tools with Artificial Intelligence, ICTAI 2017 (Vol. 2017-November, pp. 358-365). IEEE Computer Society. https://doi.org/10.1109/ICTAI.2017.00063

Parque Tenorio, V & Miyashita, T 2018, Bundling n-stars in polygonal maps. in Proceedings - 2017 International Conference on Tools with Artificial Intelligence, ICTAI 2017. vol. 2017-November, IEEE Computer Society, pp. 358-365, 29th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2017, Boston, United States, 17/11/6. https://doi.org/10.1109/ICTAI.2017.00063

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Access to Document

10.1109/ICTAI.2017.00063