Large graph visualization by hierarchical clustering

Huang, ML; Nguyen, QV

Large graph visualization by hierarchical clustering

Huang, ML

Nguyen, QV

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Publication Type:: Journal Article
Citation:: Ruan Jian Xue Bao/Journal of Software, 2008, 19 (8), pp. 1933 - 1946
Issue Date:: 2008-08-01

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Field	Value	Language
dc.contributor.author	Huang, ML https://orcid.org/0000-0002-6896-6480	en_US
dc.contributor.author	Nguyen, QV	en_US
dc.date.issued	2008-08-01	en_US
dc.identifier.citation	Ruan Jian Xue Bao/Journal of Software, 2008, 19 (8), pp. 1933 - 1946	en_US
dc.identifier.issn	1000-9825	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9041
dc.description.abstract	This paper proposes a new technique for visualizing large graphs of several ten thousands of vertices and edges. To achieve a graph abstraction, a hierarchical clustered graph is extracted from a general large graph based on the community structures discovered in the graph. An enclosure geometrical partitioning algorithm is then applied to achieving the space optimization. For graph drawing, it uses a combination of spring-embbeder and circular drawing algorithms that archives the goal of optimization of display space and aesthetical niceness. The paper also discusses an interaction mechanism accompanied with the layout solution. The interaction not only allows users to navigate hierarchically through the entire clustered graph, but also provides a way to navigate multiple clusters concurrently. Animation is also implemented to preserve user mental maps during the interaction.	en_US
dc.relation.ispartof	Ruan Jian Xue Bao/Journal of Software	en_US
dc.relation.isbasedon	10.3724/SP.J.1001.2008.01933	en_US
dc.subject.classification	Software Engineering	en_US
dc.title	Large graph visualization by hierarchical clustering	en_US
dc.type	Journal Article
utslib.citation.volume	8	en_US
utslib.citation.volume	19	en_US
utslib.for	0803 Computer Software	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	open_access
pubs.issue	8	en_US
pubs.publication-status	Published	en_US
pubs.volume	19	en_US

Abstract:

This paper proposes a new technique for visualizing large graphs of several ten thousands of vertices and edges. To achieve a graph abstraction, a hierarchical clustered graph is extracted from a general large graph based on the community structures discovered in the graph. An enclosure geometrical partitioning algorithm is then applied to achieving the space optimization. For graph drawing, it uses a combination of spring-embbeder and circular drawing algorithms that archives the goal of optimization of display space and aesthetical niceness. The paper also discusses an interaction mechanism accompanied with the layout solution. The interaction not only allows users to navigate hierarchically through the entire clustered graph, but also provides a way to navigate multiple clusters concurrently. Animation is also implemented to preserve user mental maps during the interaction.

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http://hdl.handle.net/10453/9041