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TUTORIAL III
Data Stream Mining in Mobile and Distributed Environments
Hillol Kargupta
University of Maryland Baltimore County
Audience: This tutorial will introduce attendees
to issues involved in mobile and distributed
data stream mining. It will assume that
the audience has introductory knowledge of
data mining, but no knowledge of data stream
mining in a ubiquitous environment.
Course Description: This tutorial will present
an overview of the state-of-the-art technology
for ubiquitous data-stream mining (UDM) in
mobile and distributed environments. Accessing
and analyzing time critical data streams from
a ubiquitous computing device offer many
challenges. It requires a new breed of data
mining algorithms that can handle continuous
stream of data. In addition, UDM techniques
should pay attention to the cost due to communication,
computation, security, power consumption,
and other factors. The tutorial will
cover the following material: 1) Ubiquitous
data mining: Introduction and motivation,
2) Accessing data streams in ubiquitous
environments, 3) Data mining in a ubiquitous
environment: An overview, 4) Cost of UDM:
Systems, communication, power, security
issues, 5) Data stream mining algorithms from
single and multiple sources, 6) Communication
languages for UDM applications, 7) Human-computer
interaction issues, 8) Applications:
Case studies, and 9) Future possibilities.
Lecturer: Dr. Kargupta is an Assistant
Professor in the Department of Computer
Science and Electrical Engineering, University
of Maryland Baltimore County. He is also a
cofounder of Agnik (http://www.agnik.com),
a company specializing on ubiquitous data
intelligence. He received his Ph.D. in Computer
Science from University of Illinois at Urbana-Champaign
in 1996. His research interests
include mobile and distributed data mining
and computation in gene expression.
Dr. Kargupta won the National Science
Foundation (NSF) CAREER award in 2001
for his research on ubiquitous and distributed
data mining. His research is also funded by
several other grants from NSF, NASA, TRW
Research Foundation, and Others. He won
the 1997 Los Alamos Award for Outstanding
Technical Achievement. His dissertation
earned him the 1996 SIAM (Society for
Industrial and Applied Mathematics) annual
conferences, and books. He is the primary
editor of a book entitled "Advances in
Distributed and Parallel Knowledge Discovery",
AAAI/MIT Press. He is an Associate Editor
of the IEEE Transactions on System, Man,
and Cybernetics, Part B. He has been in the
Organizing Committee of the 2001, 2002,
and 2003 SIAM International Data Mining
Conference. He is a member of the program
committee for the 2001 ACM SIGKDD
conference and the 2002 IEEE International
Conference on Data Mining, 2002 HiPC
Conference, and 2002 CIKM among others.
He organized numerous workshops, offered
several tutorials, and edited journal special
issues. More information about him can be
found at http://www.cs.umbc.edu/~hillol.
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