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

Fahnenschreiber, Sebastian and Laux, Melvin and Landesberger, Tatiana von (2014):
On the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphs.
Eurographics Association, Goslar, In: VMV 2014, DOI: 10.2312/vmv.20141285, [Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2014
Creators: Fahnenschreiber, Sebastian and Laux, Melvin and Landesberger, Tatiana von
Title: On the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphs
Language: English
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.

Publisher: Eurographics Association, Goslar
Uncontrolled Keywords: Forschungsgruppe Visual Search and Analysis (VISA), Computer graphics, Viewing algorithms, Graphics data structures, Graphics data types, Visualization, Networks, Graph drawing, Multivariate data
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: VMV 2014
Date Deposited: 12 Nov 2018 11:16
DOI: 10.2312/vmv.20141285
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