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Organized by:
Co-organized by:
In
Cooperation with:
The
Japanese Society for Artificial Intelligence
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Accepted
Tutorials
We
have selected three out of nine tutorial proposals.
We wish to thank the Tutorial Selection Committee
for their effort and time in the reviews of
the tutorials.
Sourav
Saha Bhowmick, Nanyang Technological
University, Singapore
Osmar
R. Zaiane, University of Alberta,
Canada
Tutorial Chairs
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Tutorial Selection Committee
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| Xiaofang Zhou |
University of
Queensland, Australia |
| Francesco Bonchi |
KDD lab, Pisa,
Italy |
| Ke Wang |
Simon Fraser
University, Canada |
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Tutorials
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Text Clustering:
Algorithms, Semantics and Systems
Joshua Huang (University of Hong Kong,
China)
Michael Ng (Hong Kong Baptist University,
China)
Dr Joshua Huang
is an Assistant Director at the E-Business
Technology Institute (ETI), a Principal
Consultant at ETI Consulting Limited (ETIC),
Honorary Professor at the Department of
Mathematics of the University of Hong Kong
(HKU) and Visiting Professor at the School
of Computer Science of Harbin Institute
of Technology. Dr Huang has been involved
in a number of research projects at ETI,
serving as the Principal Investigator for
the project, "A Knowledge-Based Business
Intelligence Platform", and as the
Deputy Coordinator for the project, "Intelligent
Classification Technologies for Email Data
in Chinese and Mixed Languages". Dr
Huang is also a Co-Principal Investigator
in two national 863 projects on business
intelligence and Grid Computing in Mainland
China.
Dr Huang has contributed to the development
of a series of k-means type algorithms in
data mining, including k-modes, fuzzy k-modes
and k-prototypes which are being widely
used in research and real world applications.
In the past few years, his research has
been focused on development of text clustering
technology and systems. In particular, collaborating
with his colleagues, he has contributed
to the development of the new variable weighting
k-means type algorithms, which turn out
to have the capability of subspace clustering
of very high dimensional text data. These
algorithms are published in Pattern Recognition
and IEEE Transactions on Pattern Analysis
and Machine Intelligence in 2004 and 2005.
His team has applied the new algorithms
to text data and obtained very good results.
On system development, Dr Huang's team has
recently developed a general data mining
system AlphaMiner that has been opened for
public use in education, research and applications.
Prof. Michael Ng is a Professor of the Mathematics
Department, Hong Kong Baptist University,
and is an Honorary Professor in the Department
of Mathematics, and Adjunct Research Fellow
in the E-Business Technology Institute,
at the University of Hong Kong. As an applied
mathematician, Michael's main research areas
include Bioinformatics, Data Mining, Operations
Research and Scientific Computing. He develops
computer and mathematical models for large-scale
problems and computational tools to extract
useful information from the rapidly expanding
volumes of data. He has provided consultancy
services to CLP Power, PCCW, HK Government
Environmental Protection Department, Hong
Kong financial companies: M-finance and
ExchangeRepublic.com, and LOGISTICS, HK
Productivity Council Publications. He (as
a Principal Investigator) obtained and finished
an Innovation and Technology Fund Project,
Intelligent Classification Technologies
for Email Data in Chinese and Mixed Languages
(2003--2004).
Michael has published and edited several
books, and published extensively in international
journals and conferences, and has organized
and served in many international conferences.
Now he serves on the editorial boards of
SIAM Journal on Scientific Computing, Numerical
Linear Algebra with Applications, Multidimensional
Systems and Signal Processing, International
Journal of Computational Science and Engineering,
Numerical Mathematics, A journal of Chinese
Universities (English Series), and several
special issues of the international journals.
http://www.math.hkbu.edu.hk/~mng/
Download this tutorial
(Requires password).
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Database Mining:
Bringing Algorithms to Data
Sharma Chakravarthy (University of Texas
at Arlington, USA)
Sharma Chakravarthy
is Professor of Computer and Engineering
Department at The
University of Texas at Arlington, Texas.
He established the Information Technology
Laboratory at UT Arlington in Jan 2000 and
currently heads it. Sharma Chakravarthy
has also established the NSF funded, Distributed
and Parallel Computing Cluster (DPCC@UTA)
at UT Arlington in 2003. He is the recipient
of the university-level
“Creative Outstanding Researcher”
award for 2003 and the department level
senior
outstanding researcher award in 2002.
He is well known for his work on semantic
query optimization, multiple query
optimization, active databases (HiPAC project
at CCA and Sentinel project at the
University of Florida, Gainesville), and
more recently scalability issues in graph
mining
and its applications. His group at UTA is
currently developing DB-Subdue – a
scalable
system for graph mining, and InfoSift –
a classification system for text, email,
and web that uses graph mining techniques.
His current research includes web technologies,
stream data processing, database mining
and knowledge discovery – association,
graph and text, active and real-time databases,
distributed and heterogeneous databases,
query optimization, and multi-media databases.
He has published over 115 papers in refereed
international journals and conference proceedings.
He has given tutorial on a number of database
topics, such as active, real-time, distributed,
object-oriented, and heterogeneous databases
in North America, Europe, and Asia. He is
listed in Who's Who Among South Asian Americans
and Who's Who Among America's Teachers.
Prior to joining UTA, he was with the University
of Florida, Gainesville. Prior to that,
he worked as a Computer Scientist at the
Computer Corporation of America (CCA) and
as a Member, Technical Staff at Xerox Advanced
Information Technology, Cambridge, MA.
Sharma Chakrvarthy received the B.E. degree
in Electrical Engineering from the Indian
Institute of Science, Bangalore and M.Tech
from IIT Bombay, India. He worked at TIFR
(Tata Institute of Fundamental Research),
Bombay, India for a few years. He received
M.S. and Ph.D degrees from the University
of Maryland in College park in 1981 and
1985, respectively.
http://itlab.uta.edu/sharma/
Download this tutorial
(Requires password).
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Outlier Detection: Principles,
Techniques and Applications
Sanjay Chawla (University of Sydney,
Australia)
Sanjay
Chawla is an Associate Professor (and Associate
Head) in the School of Information Technologies,
University of Sydney. He is also the Chief
Scientific
Officer of Dtecht, a Capital Markets CRC
spin-off which builds systems for fraud
prevention in health insurance transactions.
His research interests include data mining
and spatial database management systems.
He is a co-author on the textbook "Spatial
databases: A Tour" which has now been
translated into Russian and Chinese.
Download this tutorial
(Requires password).
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