AIC Seminar Series

Dynamic semantic graphs are directed graphs that evolve over time. The term “semantic” refers to the fact that such graphs have multi-modal nodes and multi-relational links. In this talk, I will illustrate why standard graph metrics are not adequate for semantic graphs. I will describe a suite of new metrics that capture both local and global properties of dynamic semantic graphs. Finally, I will demonstrate the usefulness of these new metrics in various problems ranging from knowledge representation to visual analysis.

Tina Eliassi-Rad is a computer scientist at the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. She earned a Ph.D. in Computer Sciences (with a minor in Mathematical Statistics) at the University of Wisconsin-Madison in 2001. Her research interests include artificial intelligence, machine learning, knowledge discovery and data mining. Her work has been applied to the World-Wide Web, large-scale scientific simulation data, and complex networks.

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