GARUDA: A System for Large-Scale Mining of Statistically Significant Connected Subgraphs

Unraveling “interesting” subgraphs corresponding to disease/crime hotspots or characterizing habitation shift patterns is an important graph mining task. With the availability and growth of large-scale real-world graphs, mining for such subgraphs has become the need of the hour for graph miners as well as non-technical end-users. In this demo, we present GARUDA, a system capable of mining large-scale graphs for statistically significant subgraphs in a scalable manner, and provide: (1) a detailed description of the various features and user-friendly GUI of GARUDA; (2) a brief description of the system architecture; and (3) a demonstration scenario for the audience. The demonstration showcases one real graph mining task as well as its ability to scale to large real graphs, portraying speedups of upto 8–10 times over the state-of-the-art MSCS algorithm.