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 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 areas
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 transformation
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 results
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
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/~kais/) 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.
|Workshop proposals due.|
(501 paper submissions received)
|Research-track paper submissions
Industry-track paper submissions
|Panel proposals due.|
|Paper acceptance notices.|
All paper submissions will be handled electronically. Detailed instructions are provided on the paper submission page at http://www.wi-lab.com/cyberchair/icdm03/html/submit.html.
Conference Chair: ================= Jude Shavlik, University of Wisconsin - Madison Program Committee Chairs: ========================= Xindong Wu, University of Vermont Alex Tuzhilin, New York University 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, Japan
Professor Xindong Wu (ICDM 2003) Department of Computer Science, University of Vermont, 351 Votey Building, Burlington, VT 05405, USA Phone: +1-802-656-7839 Fax: +1-802-656-0696 E-mail: firstname.lastname@example.org