Invited Talk: Predictive Analysis of Massive Streaming Graphs

Abstract

Prof. David Bader, one of the nation’s leading experts in massive-scale graph analytics, presents a case study on predictive analytics on a homeland security knowledge graph that connects disparate data from multiple sources such as spreadsheets and relational databases. Graphs are a natural representation for connecting information in real-world challenges such as understanding financial transactions in digital currencies, finding new communities in social networks, increasing power grid resiliency, and protecting us from cyberattack. Bader will discuss his Spatio-Temporal Interaction Networks and Graphs (STING) initiative that supports new methods for finding interesting patterns and features in these critical knowledge graphs.