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

Fahnenschreiber, Sebastian ; Laux, Melvin ; Landesberger von Antburg, Tatiana (2014)
On the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphs.
VMV 2014.
doi: 10.2312/vmv.20141285
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Multivariate 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.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2014
Autor(en): Fahnenschreiber, Sebastian ; Laux, Melvin ; Landesberger von Antburg, Tatiana
Art des Eintrags: Bibliographie
Titel: On the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphs
Sprache: Englisch
Publikationsjahr: 2014
Verlag: Eurographics Association, Goslar
Veranstaltungstitel: VMV 2014
DOI: 10.2312/vmv.20141285
Kurzbeschreibung (Abstract):

Multivariate 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.

Freie Schlagworte: Forschungsgruppe Visual Search and Analysis (VISA), Computer graphics, Viewing algorithms, Graphics data structures, Graphics data types, Visualization, Networks, Graph drawing, Multivariate data
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 12 Nov 2018 11:16
Letzte Änderung: 22 Jul 2021 18:31
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