Ohio State University
University of Calibria, Italy
University of Alabama, Huntsville
H. Andrade, University of Maryland
P. Brezany, University of Vienna
E. Bertino, DSI, University of Milan
I. Cruz, University of Illinois, Chicago
M. Dikaiakos, University of Cyprus
R. Grossman, University of Illinois, Chicago
V. Kumar, University of Minnesota
R. Musick, iKuni Inc.
G. Ostrouchov, Oak Ridge National Labs
S. Orlando, University of Venice
Y. Pan, Georgia State University
R. Ramachandran, University of Alabama, Huntsville
S. Ranka, University of Florida
J. Rushing, University of Alabama, Huntsville
K. Sivakumar, Washington State University
A. Srivastava, NASA Ames
V. Sunderam, Emory University
G. Williams, National University of Australia
M. Zaki, RPI
N. Zhong, Maebashi Inst. of Technology
Hillol Kargupta, University of Maryland, Baltimore County
Vipin Kumar, University of Minnesota
Srinivasan Parthasarathy, Ohio State University
David Skillicorn, Queens University
Mohammed Zaki, RPI
HPDM: High Performance and Distributed Mining
7th International Workshop on High Performance and Distributed Mining:
in conjunction with
This is the 7th workshop on this theme held annually.
The first four held
in conjunction with IPDPS were
held at Orlando (
HPDM'98), San Juan (
and San Francisco (PDDM01).
Last two years' workshop were held along-side the SIAM
Data Mining conference.
This year's workshop, while continuing its focus on traditional
areas of high performance data mining, has a special focus on
grid-based and distributed data mining.
This workshop will focus on the emerging field of high performance,
distributed, and grid-based mining. With the emergence of grid
architectures and standards, many efforts are being initiated on
grid-based and distributed mining. This brings in new challenges
in applying and developing distributed and high-performance
algorithms. Privacy, security, and resource discovery are all important
issues. Interoperability with grid standards is another issues.
This area also has synergy with the growing area of mining in mobile and sensor
Topics of interest include (but are not limited to):
- Distributed and Grid-based data mining algorithms.
- Systems and tools for data mining and exploration in grid-based and
- Standards and architectures for grid-based data mining.
- Privacy and security considerations in distributed data mining.
- P2P data mining.
- Resource-aware data mining.
- Data mining in mobile / sensor network environments.
- Data stream mining and management.
- Efficient, scalable, disk-based, parallel and distributed algorithms
for large-scale data mining.
- Parallel and distributed techniques for incremental, exploratory and
- Frameworks for parallel data mining.
- Applications of parallel, distributed, grid-based, and mobile
- Theoretical foundation of parallel, distributed, and grid-based data mining.
Paper Submissions due :
January 15, 2004
- Notification to authors:
Feb 20, 2004.
- Final papers due:
March 10, 2004.
We invite papers treating the above topics in one of many ways.
The papers could describe new results, give overview or experiences with
existing systems, describe new and emerging applications, present work in progress where interesting insights have been gained, or critically survey existing work.
The papers should not exceed 3000 words. This is roughly
equal to 6 pages of single spaced text with 10 pt format.
You can submit by emailing the PS or
PDF file to email@example.com .