TITLE: Graph Mining: Laws, Generators and Tools
SPEAKER: Christos Faloutsos (CMU)

ABSTRACT:
How do graphs look like? How do they evolve over time?
How can we generate realistic-looking graphs?
We review some static and temporal 'laws',
and we describe the ``Kronecker'' graph generator,
which naturally matches all of the known properties of real graphs.
Moreover, we present tools for discovering anomalies and patterns
in two types of graphs, static and time-evolving.
For the former, we present the 'CenterPiece' subgraphs (CePS),
which expects $q$ query nodes (eg., suspicious people)
and finds the node that is best connected to all $q$ of them
(eg., the master mind of a criminal group).
We also show how to compute CenterPiece subgraphs efficiently.
For the time evolving graphs, we present tensor-based methods,
and apply them on real data, like the DBLP author-paper dataset,
where they are able to find natural research communities,
and track their evolution.

Finally, we also briefly mention some results on
influence and virus propagation on real graphs,
as well as on the emerging map/reduce approach
and its impact on large graph mining.

BIOGRAPHICAL NOTE

Christos Faloutsos is a Professor at Carnegie Mellon University.
He has received the Presidential Young Investigator Award by
the National Science Foundation (1989),
the Research Contributions Award in ICDM 2006,
twelve ``best paper'' awards, and several teaching awards.
He has served as a member of the executive committee of SIGKDD;
he has published over 160 refereed articles, 11 book chapters
and one monograph.  He holds five patents and
he has given over 20 tutorials and over 10 invited distinguished lectures.
His research interests include data mining
for streams and networks, fractals, indexing for
multimedia and bio-informatics data, and database performance.