Catching bad guys with graph mining
XRDS: Crossroads, The ACM Magazine for Students - The Fate of Money
TourViz: interactive visualization of connection pathways in large graphs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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We present Graphite, a system that allows the user to visually construct a query pattern, finds both its exact and approximate matching subgraphs in large attributed graphs, and visualizes the matches. For example, in a social network where a person's occupation is an attribute, the user can draw a 'star' query for "finding a CEO who has interacted with a Secretary, a Manager, and an Accountant, or a structure very similar to this". Graphite uses the G-Ray algorithm to run the query against a user-chosen data graph, gaining all of its benefits, namely its high speed, scalability, and its ability to find both exact and near matches. Therefore, for the example above, Graphite tolerates indirect paths between, say, the CEO and the Accountant, when no direct path exists. Graphite uses fast algorithms to estimate node proximities when finding matches, enabling it to scale well with the graph database size.We demonstrate Graphite’s usage and benefits using the DBLP author-publication graph, which consists of 356K nodes and 1.9M edges. A demo video of Graphite can be downloaded at http://www.cs.cmu.edu/~dchau/graphite/graphite.mov.