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Visualizing Dynamic Network via Sampled Massive Sequence View

Authors :
Chen Wenjiang
Yanni Peng
Ying Zhao
Wu Qing
Xiaoping Fan
Yanmin She
Source :
VINCI
Publication Year :
2019
Publisher :
ACM, 2019.

Abstract

Massive Sequence View(MSV) is an important timeline-based technique for dynamic network visualization. However, it often suffers from severe visual clutter when limited screen space holds excessive network edges. Inspired by the use of graph sampling in static graph analysis, we propose to utilize graph sampling to reduce visual clutter in MSV. An edge sampling method based on accept-reject random sampling is designed for visualizing dynamic network via MSV. The method is able to improve the overall readability of MSV while preserving time varying network behaviors. It is also a preliminary attempt to apply graph-sampling technique into dynamic network analysis.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 12th International Symposium on Visual Information Communication and Interaction
Accession number :
edsair.doi...........32e7594ef6e848b47c16eb2c94118432
Full Text :
https://doi.org/10.1145/3356422.3356454