A Visual Evaluation Study of Graph Sampling Techniques

Article Status: Peer-reviewed conference papers
Publication Year: 2017
Zhang, Fangyan; Zhang, Song; Chung Wong, Pak; Medal, Hugh; Bian, Linkan; Swan II, J. Edward; Jankun-Kelly, T.J.. Proceedings of the 7th annual IS&T International Symposium on Electronic Imaging 2017, no. 1 (2017): 110-117. Atlanta, GA.
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We evaluate a dozen prevailing graph-sampling techniques with an ultimate goal to better visualize and understand big and complex graphs that exhibit different properties and structures. The evaluation uses eight benchmark datasets with four different graph types collected from Stanford Network Analysis Platform and NetworkX to give a comprehensive comparison of various types of graphs. The study provides a practical guideline for visualizing big graphs of different sizes and structures. The paper discusses results and important observations from the study.