Publikation: A Quality Metric for Visualization of Clusters in Graphs
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ARCHAMBAULT, Daniel, ed., Csaba D. TÓTH, ed.. Graph Drawing and Network Visualization : 27th International Symposium, GD 2019, Proceedings. Cham: Springer, 2019, pp. 125-138. Lecture Notes in Computer Science. 11904. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-35801-3. Available under: doi: 10.1007/978-3-030-35802-0_10
Zusammenfassung
Traditionally, graph quality metrics focus on readability, but recent studies show the need for metrics which are more specific to the discovery of patterns in graphs. Cluster analysis is a popular task within graph analysis, yet there is no metric yet explicitly quantifying how well a drawing of a graph represents its cluster structure. We define a clustering quality metric measuring how well a node-link drawing of a graph represents the clusters contained in the graph. Experiments with deforming graph drawings verify that our metric effectively captures variations in the visual cluster quality of graph drawings. We then use our metric to examine how well different graph drawing algorithms visualize cluster structures in various graphs; the results confirm that some algorithms which have been specifically designed to show cluster structures perform better than other algorithms.
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Graph Drawing and Network Visualization : 27th International Symposium, GD 2019, 17. Sept. 2019 - 20. Sept. 2019, Prague, Czech Republic
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MEIDIANA, Amyra, Seok-Hee HONG, Peter EADES, Daniel A. KEIM, 2019. A Quality Metric for Visualization of Clusters in Graphs. Graph Drawing and Network Visualization : 27th International Symposium, GD 2019. Prague, Czech Republic, 17. Sept. 2019 - 20. Sept. 2019. In: ARCHAMBAULT, Daniel, ed., Csaba D. TÓTH, ed.. Graph Drawing and Network Visualization : 27th International Symposium, GD 2019, Proceedings. Cham: Springer, 2019, pp. 125-138. Lecture Notes in Computer Science. 11904. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-35801-3. Available under: doi: 10.1007/978-3-030-35802-0_10BibTex
@inproceedings{Meidiana2019Quali-66540,
year={2019},
doi={10.1007/978-3-030-35802-0_10},
title={A Quality Metric for Visualization of Clusters in Graphs},
number={11904},
isbn={978-3-030-35801-3},
issn={0302-9743},
publisher={Springer},
address={Cham},
series={Lecture Notes in Computer Science},
booktitle={Graph Drawing and Network Visualization : 27th International Symposium, GD 2019, Proceedings},
pages={125--138},
editor={Archambault, Daniel and Tóth, Csaba D.},
author={Meidiana, Amyra and Hong, Seok-Hee and Eades, Peter and Keim, Daniel A.}
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