Graph Mining: Patterns and Tools

by Christos Faloutsos

CMU, Tepper

  April 4, 2017

Abstract

Given a large graph, like who-calls-whom, or who-likes-whom, what behavior is normal and what should be surprising, possibly due to fraudulent activity? How do graphs evolve over time? What tools are available, to find the most important nodes? the most strange nodes?

For the first, we present a list of static and temporal laws, and how they help us to find anomalies. For the second, we show describe the powerful tool of Singular Value Decomposition (SVD), and we show how it can find important nodes (HITS, PageRank), as well as help with visualization and anomalies.

Foils



Last updated by: Christos Faloutsos, April 2, 2017.