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Visualizing large graphs
Author(s) -
Hu Yifan,
Shi Lei
Publication year - 2015
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.1343
Subject(s) - computer science , exploratory data analysis , visualization , graph drawing , graphics , statistical graphics , data visualization , exploratory analysis , graph layout , data mining , data science , theoretical computer science , graph , big data , machine learning , computer graphics (images)
With the prevalence of big data, there is a growing need for algorithms and techniques for visualizing very large and complex graphs. In this article, we review layout algorithms and interactive exploration techniques for large graphs. In addition, we briefly look at softwares and datasets for visualization graphs, as well as challenges that need to be addressed. WIREs Comput Stat 2015, 7:115–136. doi: 10.1002/wics.1343 This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data Analysis Data: Types and Structure > Graph and Network Data Statistical and Graphical Methods of Data Analysis > Statistical Graphics and Visualization