[DL] IEEE Data Mining 2003: Call for Papers

icdm at wi-lab.com icdm at wi-lab.com
Fri Apr 11 11:14:56 CEST 2003

[Apologies if you receive this more than once]
 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.com, 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
   May 15, 2003           Workshop proposals due
   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
   (shavlik at cs.wisc.edu)
 Program Committee Chairs:
   Xindong Wu, University of Vermont
   (xwu at cs.uvm.edu)
   Alex Tuzhilin, New York University
   (atuzhili at stern.nyu.edu)
 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
   (bayardo at almaden.ibm.com)
 Panels Chair:
   Nick Cercone, Dalhousie University
   (nick at cs.dal.ca)
 Workshops Chair:
   David Page, University of Wisconsin - Madison
   (page at biostat.wisc.edu)
 Tutorials Chair:
   Martin Ester, Simon Fraser University
   (ester at cs.sfu.ca)
 Publicity Chair:
   Balaji Padmanabhan, University of Pennsylvania
   (balaji at wharton.upenn.edu)
 Local Arrangements Chair:
   Philip Chan, Florida Institute of Technology
   (pkc at cs.fit.edu)
 Web Master:
   Ning Zhong, Maebashi Institute of Technology
   (zhong at maebashi-it.ac.jp)
 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 at cs.uvm.edu

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