On the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphs

dc.contributor.authorFahnenschreiber, Sebastianen_US
dc.contributor.authorLaux, Melvinen_US
dc.contributor.authorLandesberger, Tatiana vonen_US
dc.contributor.editorJan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urbanen_US
dc.date.accessioned2014-12-16T07:26:40Z
dc.date.available2014-12-16T07:26:40Z
dc.date.issued2014en_US
dc.description.abstractMultivariate networks are present in various domains such as biology, or social science. In such networks, the nodes often have several quantitative attributes, which determine similarity of nodes (e.g., person's characteristics in social networks). When interpreting these networks, often both node connectivity and node similarity need to be analyzed simultaneously. Such analysis can be supported by suitable layouts. We present and evaluate a layout for graphs with multivariate numeric attributes, which combines graph structure and node similarity. It extends local dimension reduction techniques (esp. LLE, MEU, or ISOMAP) with graph connectivity information encoded in techniques' local neighborhood function. We evaluate these extensions and available layouts using two conflicting criteria: distance preservation and graph aesthetics. Although the results vary across data sets, the new approach is able to find a balance of these criteria.en_US
dc.description.seriesinformationVision, Modeling & Visualizationen_US
dc.identifier.isbn978-3-905674-74-3en_US
dc.identifier.urihttps://doi.org/10.2312/vmv.20141285en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputer Graphics [I.3.3]en_US
dc.subjectViewing Algorithmsen_US
dc.subjectComputer Graphics [I.3.6]en_US
dc.subjectMethodology and Techniquesen_US
dc.subjectGraphics data structures and data typesen_US
dc.titleOn the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphsen_US
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