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

Fahnenschreiber, Sebastian; Laux, Melvin; Landesberger, Tatiana von

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

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Date

2014

Authors

Fahnenschreiber, Sebastian
Laux, Melvin
Landesberger, Tatiana von

Publisher

The Eurographics Association

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.

        @inproceedings{:10.2312/vmv.20141285
,
booktitle = {Vision, Modeling & Visualization
},
editor = {Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
},
title = {{On the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphs
}},
author = {Fahnenschreiber, Sebastian and 
Laux, Melvin and 
Landesberger, Tatiana von
},
year = {2014
},
publisher = {The Eurographics Association
},
ISBN = {978-3-905674-74-3
},
DOI = {/10.2312/vmv.20141285
}
}