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ICDM'09: The 9th IEEE International Conference on Data Mining
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Sponsored by the IEEE Computer Society

December 6-9, 2009
Miami, U.S.A.
http://www.cs.umbc.edu/ICDM09/

Important Dates
April 13, 2009        Deadline for Workshop Proposals
April 30, 2009        Deadline for ICDM Contest Proposals
June 26, 2009         Deadline for Paper Submission,
                                   Tutorial Submission, and
                                   Panel Proposals
July 7, 2009          Deadline for Exhibits and Demos Proposals
September 4, 2009     Notification to authors
September 28, 2009    Deadline for camera-ready copies
December 6-9, 2009    Conference

Call for Papers
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The IEEE International Conference on Data Mining (ICDM) has established
itself as the world's premier research conference in data mining. The 2009
edition of ICDM provides a leading forum for presentation of original
research results, as well as exchange and dissemination of innovative,
practical development experiences. The conference covers all aspects of data
mining, including algorithms, software and systems, and applications.  In
addition, ICDM draws researchers and application developers from a wide
range of data mining related areas such as statistics, machine learning,
pattern recognition, databases and data warehousing, data visualization,
knowledge-based systems, and high performance computing. By promoting novel,
high quality research findings, and innovative solutions to challenging data
mining problems, the conference seeks to continuously advance the
state-of-the-art in data mining. Besides the technical program, the
conference will feature workshops, tutorials, panels, and the ICDM data
mining contest.

Paper Submissions
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High quality papers in all data mining areas are solicited. Original papers
exploring new directions will receive especially careful consideration.
Papers that have already been accepted or are currently under review for
other conferences or journals will not be considered for ICDM'09.

Paper submissions should be limited to a maximum of 10 pages in the IEEE
2-column format, the same as the camera-ready format (see the IEEE Computer
Society Press Proceedings Author Guidelines
http://www.ieeeconfpublishing.org/cpir/AuthorKit.asp?
Community=CPS&Facility=CPS_Dec&ERoom=ICDM+2008). All papers will be reviewed
by the Program Committee on the basis of technical quality, relevance to
data mining, originality, significance, and clarity. A double blind review
process will be adopted. Authors should avoid using identifying information
in the text of the paper. A Submission Form to submit your work will be
announced on the ICDM'09 website.

Accepted papers will be published in the conference proceedings by the IEEE
Computer Society Press and accorded oral presentation times in the main
conference. Submissions accepted as regular papers will be allocated 10
pages in the proceedings. Submissions accepted as short papers will be
allocated 6 pages in the proceedings and will have a shorter presentation
time at the conference than regular papers.

A selected number of IEEE ICDM'09 accepted papers will be invited for
possible inclusion, in expanded and revised form, in the Knowledge and
Information Systems journal published by Springer-Verlag.

ICDM Best Paper Awards
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IEEE ICDM Best Paper Awards will be conferred at the conference on the
authors of (1) the best research paper, (2) the best application paper, and
(3) the best student paper.  Strong, foundational results will be considered
for the best research paper award and application-oriented submissions will
be considered for the best application paper award. The best student paper
award will be given to the authors of the best paper written solely by one
or more students.

Workshops and Tutorials
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ICDM'09 will host short and long tutorials as well as workshops that focus
on new research directions and initiatives. All accepted workshop papers
will be included in a separate workshop proceedings published by the IEEE
Computer Society Press.

ICDM Data Mining Contest
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ICDM'09 will host a data mining contest to challenge researchers and
practitioners with a real practical data mining problem. For further details
on proposals and expression of interest, please see the Call for Data Mining
Contest Proposals.

ICDM Exhibits and Demos
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The ICDM'09 Exhibit and Demo section will consist of an Exhibit Session and
a Demo Session. The Exhibit Session will offer opportunities to distribute
product, service, and company literature, give demonstrations and carry out
recruitment activities. The Demo Session will provide data mining
researchers and practitioners an exciting and highly interactive way to
explore new ideas and results.

Topics of Interest
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* Data mining foundations
  - Novel data mining algorithms in traditional areas (such as
    classification, regression, clustering, probabilistic modeling,
    pattern discovery, and association analysis)
  - Models and algorithms for new, structured, data types, such as
    arising in chemistry, biology, environment, and other scientific
    domains
  - Developing a unifying theory of data mining
  - Mining sequences and sequential data
  - Mining spatial and temporal datasets
  - Mining textual and unstructured datasets
  - Distributed data mining
  - High performance implementations of data mining algorithms
  - Privacy and anonymity-preserving data analysis
* Mining in emerging domains
  - Stream data mining
  - Mining moving object data, RFID data, and data from sensor networks
  - Ubiquitous knowledge discovery
  - Mining multi-agent data
  - Mining and link analysis in networked settings: web, social and
    computer networks, and online communities
  - Mining the semantic web
  - Data mining in electronic commerce, such as recommendation,
    sponsored web search, advertising, and marketing tasks
* Methodological aspects and the KDD process
  - Data pre-processing, data reduction, feature selection, and feature
    transformation
  - Quality assessment, interestingness analysis, and post-processing
  - Statistical foundations for robust and scalable data mining
  - Handling imbalanced data
  - Automating the mining process and other process related issues
  - Dealing with cost sensitive data and loss models
  - Human-machine interaction and visual data mining
  - Integration of data warehousing, OLAP and data mining
  - Data mining query languages
  - Security and data integrity
* Integrated KDD applications, systems, and experiences
  - Bioinformatics, computational chemistry, eco-informatics
  - Computational finance, online trading, and analysis of markets
  - Intrusion detection, fraud prevention, and surveillance
  - Healthcare, epidemic modeling, and clinical research
  - Customer relationship management
  - Telecommunications, network and systems management
  - Sustainable mobility and intelligent transportation systems

Organizing Committee
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Conference Co-Chairs:
  Sanjay Ranka, University of Florida
  Philip S. Yu, University of Illinois at Chicago

Program Co-Chairs:
  Hillol Kargupta, University of Maryland, Baltimore County
  Wei Wang, University of North Carolina Chapel Hill

Steering Committee:
  David J. Hand, Imperial College, London, UK
  Ramamohanarao Kotagiri, University of Melbourne, Australia
  Vipin Kumar, University of Minnesota, USA
  Heikki Mannila, University of Helsinki, Finland
  Gregory Piatetsky-Shapiro, KDnuggets, USA
  Shusaku Tsumoto, Shimane University
  Benjamin W. Wah, University of Illinois, Urbana-Champaign, USA
  Xindong Wu (Chair), University of Vermont, USA
  Philip S. Yu, IBM T.J. Watson Research Center, USA
  Osmar R. Zaiane, University of Alberta

Local Arrangements Chair:
  Tao Li, Florida International University

Finance Chair:
  Vagelis Hristidis, Florida International University

Awards Committee:
  James Bailey, University of Melbourne, Australia
  Wei Fan, IBM T.J. Watson Research Center, USA
  Minos N. Garofalakis, Technical University of Crete, Greece
  Bart Goethals, University of Antwerp, Belgium
  Jiawei Han (Chair), University of Illinois at Urbana-Champaign, USA
  Hillol Kargupta, University of Maryland at Baltimore County, USA
  Wei Wang, University of North Carolina at Chapel Hill, USA

Panels Chair:
  Haym Hirsh, NSF and Rutgers

Workshop Co-Chairs:
  Yucel Saygin, Sabanci University
  Jeffrey Xu Yu, CUHK

Tutorials Chair:
  Sanghamitra Bandyopadhyay, Indian Statistical Institute

ICDM Data Mining Contest Chair:
  Qiang Yang, HKUST

Sponsorship Chair:
  Gabor Melli, PredictionWorks

Publicity Chairs:
  Ina Lauth, Fraunhofer IAIS (Europe)
  Kun Liu, IBM Almaden Research Center (North America)

Exhibit and Demo Chairs
  Kanishka Bhaduri, NASA Ames Research Center
  LongBing Cao, University of Technology Sydney

Vice Chairs
  Deepak Agarwal, Yahoo!
  Charu Aggarwal,IBM T J Watson Research Center
  Alok Choudhary,NWU
  Diane Cook,Washington State University
  Gautam Das,University of Texas at Arlington
  Ian Davidson, University of California, Davis,
  Robert Grossman, University of Illinois at Chicago
  George Karypis, University of Minnesota
  Ravi Kumar, Yahoo!
  Ling Liu, Georgia Institute of Technology
  Katharina Morik, University of Dortmund, Germany,
  Olfa Nasraoui, University of Louisville
  Srinivasan Parthasarathy, The Ohio State University
  Jian Pei, Simon Fraser University
  Naren Ramakrishnan, Virginia Tech
  Rajeev Rastogi, Yahoo!, India
  Ambuj Singh, UCSB
  Shashi Shekhar, University of Minnesota
  Kyuseok Shim, Seoul National University, Korea
  Assaf Schuster, Technion
  Myra Spiliopoulou, University of Magdeburg, Germany
  Ashok Srivastava, NASA Ames Research Center
  Jaideep Srivastava, University of Minnesota
  Hannu Toivonen, University of Helsinki
  Haixun Wang, IBM T.J. Watson Research Center
  Carlo Zaniolo, UCLA
  Osmar Zaiane, Univ of Alberta

Further Information
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