ICDM: The Third IEEE International Conference on Data Mining, Sponsored by the IEEE Computer Society, Melbourne, Florida, USA, November 19 - 22, 2003 2003.

YEAR: 2003
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LABEL: Data Mining | IDCM | semi-structured data
PLACES: Florida
THINGS: learning algorithms | Text analysis
TIME: 2003
30.05.2003 11:08
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IEEE Data Mining 2003: Call for Papers

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ICDM '03: The Third IEEE International Conference on Data Mining
Sponsored by the IEEE Computer Society

Melbourne, Florida, USA
November 19 - 22, 2003


Call for Papers
(Papers Due: June 10, 2003)

Invited Speakers

- Thomas G. Dietterich, Oregon State University, USA
- Usama M. Fayyad, digiMine, Inc., USA
- Heikki Mannila, University of Helsinki, Finland
- Gene W. Myers, University of California, Berkeley, USA
- Philip S. Yu, IBM T.J. Watson Research Center, USA

The 2003 IEEE International Conference on Data Mining (IEEE ICDM '03)
provides a leading international forum for the sharing of original
research results and practical development experiences among
researchers and application developers from different data mining
related areas such as machine learning, automated scientific
discovery, statistics, pattern recognition, knowledge acquisition,
soft computing, databases and data warehousing, data visualization,
and knowledge-based systems. The conference seeks solutions to
challenging problems facing the development of data mining systems,
and shapes future directions of research by promoting high quality,
novel and daring research findings. As an important part of the
conference, the workshops program will focus on new research
challenges and initiatives, and the tutorial program will cover
emerging data mining technologies and the state-of-the-art of data
mining developments.

Topics of Interest

Topics related to the design, analysis and implementation of data
mining theory, systems and applications are of interest. These
include, but are not limited to the following areas:

- Foundations of data mining
- Data mining and machine learning algorithms and methods in
traditional areas (such as classification, regression, clustering,
probabilistic modeling, and association analysis), and in new
- Mining text and semi-structured data, and mining temporal, spatial
and multimedia data
- Data and knowledge representation for data mining
- Complexity, efficiency, and scalability issues in data mining
- Data pre-processing, data reduction, feature selection and feature
- Post-processing of data mining results
- Statistics and probability in large-scale data mining
- Soft computing (including neural networks, fuzzy logic,
evolutionary computation, and rough sets) and uncertainty
management for data mining
- Integration of data warehousing, OLAP and data mining
- Human-machine interaction and visualization in data mining, and
visual data mining
- High performance and distributed data mining
- Pattern recognition and scientific discovery
- Quality assessment and interestingness metrics of data mining
- Process-centric data mining and models of data mining process
- Security, privacy and social impact of data mining
- Data mining applications in electronic commerce, bioinformatics,
computer security, Web intelligence, intelligent learning database
systems, finance, marketing, healthcare, telecommunications, and
other fields

Conference Publications and ICDM Best Paper Awards

High quality papers in all data mining areas are solicited. Papers
exploring new directions will receive especially careful and
supportive reviews.

There are two types of paper submissions for IEEE ICDM '03: (1)
research-track submissions and (2) industry-track submissions. All paper
submissions will be handled electronically. Please use the Submission
Form at the ICDM '03 webpage to submit your paper.

For research-track submissions, papers should be limited to a maximum
of 6,000 words (approximately 20 A4 pages), and will be reviewed by
the Program Committee on the basis of technical quality, relevance to
data mining, originality, significance, and clarity. Accepted papers
will be published in the conference proceedings by the IEEE Computer
Society Press.

For industry-track submissions, please make sure that the following
conditions are met: (a) Papers cannot exceed 3,000 words, (b) At least
one author of each industry-track paper should be from an industrial
company, and the paper should be about industrial or other real-world
applications of data mining, AND (c) a description of how the
application has been conceived, developed and deployed must be
provided. (Papers that present interesting data mining applications
but do not qualify as industry-track submissions according to the
these criteria can be submitted to the research track.) The
conference will provide an opportunity for the authors of accepted
industry-track papers to showcase their efforts in front of the
world's finest data miners via a software demonstration.

All papers submitted to the industry track will also be reviewed by
the Program Committee, and each accepted industry-track paper will be
allocated 4 pages in the conference proceedings by the IEEE Computer
Society Press.

A selected number of IEEE ICDM '03 accepted papers will be invited for
possible inclusion, in an expanded and revised form, in the Knowledge
and Information Systems journal (http://www.cs.uvm.edu/~xwu/kais.html)
by Springer-Verlag.

IEEE ICDM Best Paper Awards will be conferred at the conference on the
authors of (1) the best research paper and (2) the best application
paper. Papers from the industry track and application-oriented papers
from the research track will both be considered for the best
application award.

Important Dates

June 10, 2003 Research-track paper submissions
Industry-track paper submissions
Tutorial proposals
June 30, 2003 Panel proposals due
August 15, 2003 Paper acceptance notices
September 10, 2003 Final camera-readies
November 19, 2003 Workshops
November 20-22, 2003 Conference

All paper submissions will be handled electronically. Detailed
instructions are provided on the conference home page at

Conference Chair:

Jude Shavlik, University of Wisconsin - Madison

Program Committee Chairs:

Xindong Wu, University of Vermont

Alex Tuzhilin, New York University

Vice Chairs:

Christopher W. Clifton, Purdue University, USA
Douglas H. Fisher, Vanderbilt University, USA
Paolo Frasconi, Universit di Firenze, Italy
Dunja Mladenic, J. Stefan Institute, Slovenia
Raghu Ramakrishnan, University of Wisconsin - Madison, USA
Rajeev Rastogi, Lucent, USA
Michele Sebag, Universite Paris-Sud, France
Dale Schuurmans, University of Waterloo, Canada
Jaideep Srivastava, University of Minnesota, USA
Mohammed Zaki, Rensselaer Polytechnic Institute, USA

Industry Track Chair:

Roberto Bayardo, IBM Almaden Research Center, USA

Panels Chair:

Nick Cercone, Dalhousie University

Workshops Chair:

David Page, University of Wisconsin - Madison

Tutorials Chair:

Martin Ester, Simon Fraser University

Publicity Chair:

Balaji Padmanabhan, University of Pennsylvania

Local Arrangements Chair:

Philip Chan, Florida Institute of Technology

Web Master:

Ning Zhong, Maebashi Institute of Technology

ICDM Steering Committee

Xindong Wu (Chair), University of Vermont, USA
Max Bramer, University of Portsmouth, UK
Nick Cercone, Dalhousie University, Canada
Ramamohanarao Kotagiri, University of Melbourne, Australia
Vipin Kumar, University of Minnesota, USA
Katharina Morik, University of Dortmund, Germany
Gregory Piatetsky-Shapiro, KDnuggets, USA
Philip S. Yu, IBM T.J. Watson Research Center, USA
Benjamin W. Wah, University of Illinois, Urbana-Champaign, USA
Ning Zhong, Maebashi Institute of Technology, Japan

Further Information

Professor Xindong Wu (ICDM 2003)
Department of Computer Science,
University of Vermont,
351 Votey Building,
Burlington, VT 05405,

Phone: +1-802-656-7839
Fax: +1-802-656-0696
E-mail: xwu@cs.uvm.edu