To be Held in Conjunction with the
Third IEEE International Conference on Data Mining
(ICDM 2003)
Applications in various domains often lead to very large and frequently high-dimensional data; the dimension of the data being in the hundreds or thousands, for example in text/web mining and bioinformatics. In addition to the high dimensionality, these data sets are also often sparse. Clustering such large and high-dimensional data sets is a contemporary challenge. Successful algorithms must avoid the curse of dimensionality but at the same time should be computationally efficient.
A one-day workshop on Clustering Large Data Sets is being held in conjunction with ICDM 2003 in Melbourne, Florida (November '03) to bring together researchers to present their current approaches and results in clustering large data sets that arise in various applications. Particular areas of interest are text mining, clustering of bio-informatics data, online clustering, market-basket and web log data.
Clustering Algorithms and Models
- Probabilistic Models
- Vector-space Models
- Graph-based Models
- Density based clustering (k-means, EM)
- Software and Toolkits
Applications
- Text Mining
- Feature selection
- Bioinformatics
- Web log analysis
- Factor Analysis
- Clustering of Streaming Data
Original papers on clustering large and high-dimensional data are solicited. For consideration, send an electronic submission (postscript or PDF versions printable on 8.5 x 11 paper only) to Jacob Kogan: kogan@math.umbc.edu; phone: (410)-455-3297; fax: (410)-455-1066.
An email including the title, authors and abstract of the paper should be sent separately in plain ASCII format (no HTML-tags please).
To guarantee consideration, manuscripts must be received by September 10, 2003 (the final manuscript must be no more than 10 pages). Submission of work in progress is also encouraged.
All accepted papers whose camera-ready copies are received by the October 15, 2003 deadline (see below) will be distributed as photocopied proceedings available at the conference for purchase by attendees (Latex style file available here).
Cliff Behrens, Telcordia Technologies
Pavel Berkhin, Yahoo
Alex Bolshoy, Genome Diversity Center
Paul Bradley, Bradley Data Consulting, LLC
Moses Charikar,
Princeton University
Chris Ding,
Lawrence Berkeley National Lab
Chris Fraley,
University of Washington
Thomas Hoffman,
Brown University
George Karypis,
University of Minnesota
Shailesh Kumar, HNC
Arie Leizarowitz, Technion, Israel
Dharmendra Modha, IBM Almaden
Research Center
Amit Sahai,
Princeton University
Nick Street, University of Iowa
Mark Teboulle, Tel-Aviv University
Zeev (Vladimir) Volkovich, Ort
Braude College, Israel
Shi Zhong,
Florida Atlantic University
Luba Zlatin, C-Ark, Israel
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Organizers Daniel Boley Department of Computer Science & Engineering University of Minnesota Minneapolis, MN 55455 Phone: (612) 625-3887 Fax: (612) 625-0572 |
Inderjit Dhillon Department of Computer Science University of Texas Austin, TX 78712-1188 Phone: (512) 471-9725 Fax: (512) 471-8885 |
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Joydeep Ghosh Department of Electrical & Computer Engineering and Department of Computer Sciences University of Texas Austin, TX 78712-1188 Phone: (512) 471-8980 Fax: (512) 471-2893 |
Jacob Kogan Department of Mathematics & Statistics and Department of Computer Science & Electrical Engineering Univ. of Maryland, Baltimore County Baltimore, MD 21250 Phone: (410) 455-3297 Fax: (410) 455-1066 |
Last modified on October 20, 2003.