A Visual Evaluation Study of Graph Sampling Techniques

Conference · Sun Jan 29 00:00:00 EST 2017

DOI:https://doi.org/10.2352/ISSN.2470-1173.2017.1.VDA-394· OSTI ID:1440692

Zhang, Fangyan; Zhang, Song; Wong, Pak C.; Medal, Hugh; Bian, Linkan; Swan, II, J. Edward; Jankun-Kelly, TJ

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.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1440692
• Report Number(s): PNNL-SA-122748; 453040300
• Resource Relation: Conference: IS&T International Symposium on Electronic Imaging Science and Technology: Visualization and Data Analysis 2017, January 29-February 2, 2017, Burlingame, CA, 110-117
• Country of Publication: United States
• Language: English

Related Subjects

Big graphs
Graph sampling
Graph properties
Graph drawing
Visualization