# DB Seminar: Jay-Yoon Lee

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How can we visualize billion-scale graphs? How to spot outliers in such graphs quickly? Visualizing graphs is the most direct way of understand- ing them; however, billion-scale graphs are very difficult to visualize since the amount of information overflows the resolution of a typical screen.

In this paper we propose NET-RAY, an open-source package for visualization- based mining on billion-scale graphs. NET-RAY visualizes graphs using the spy plot (adjacency matrix patterns), distribution plot, and correlation plot which in- volve careful node ordering and scaling. In addition, NET-RAY efficiently sum- marizes scatter clusters of graphs in a way that finds outliers automatically, and makes it easy to interpret them visually. To the best of our knowledge, NET-RAY is the first work for visual mining on billion-scale graphs.

Extensive experiments show that NET-RAY handles very large graphs with bil- lions of nodes and edges efficiently and effectively. Specifically, among the var- ious datasets that we study, we visualize in multiple ways the YahooWeb graph which spans 1.4 billion webpages and 6.6 billion links, and the Twitter who- follows-whom graph, which consists of 62.5 million users and 1.8 billion edges. We report interesting clusters and outliers spotted and summarized by NET-RAY.