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Jiawei Han
Professor
Department of Computer Science
University of Illinois at Urbana-Champaign
February 12 at 3:00pm
106 Woodward
Abstract:
Knowledge is power but for interrelated data, knowledge is often
hidden in massive links. We explore the power of links at mining
heterogeneous information networks and introduce a new line of
research, called RankClus, that integrates clustering and ranking
and explores its power at mining heterogeneous information networks.
We show that the method has its unique power at clustering
interrelated data and demonstrate the power of RankClus and its
extensions at mining some real information networks. We also
discuss several of our on-going studies in this direction.
Bio:
Jiawei Han, Professor, Department of Computer Science, University of
Illinois at Urbana-Champaign. He has been working on research into
data mining, data warehousing, database systems, data mining from
spatiotemporal data, multimedia data, stream and RFID data, Web
data, social network data, and biological data, with over 400
journal and conference publications. He has chaired or served on
over 100 program committees of international conferences and
workshops, including PC co-chair for KDD, SDM, and ICDM conferences,
and Americas Coordinator for a VLDB conference. He is also serving
as the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery
from Data. He is a Fellow of ACM and IEEE, and has received 2004 ACM
SIGKDD Innovations Award and 2005 IEEE Computer Society Technical
Achievement Award. His book "Data Mining: Concepts and Techniques"
(2nd ed., Morgan Kaufmann, 2006) has been popularly used as a
textbook worldwide.
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