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                    PAPER SUBMISSION DEADLINE EXTENDED

            ECML PKDD 2006 Workshop on Parallel Data Mining
                          (at ECML/PKDD '06)

                           Berlin, Germany
                         September 18, 2006
                http://www.inf.uni-konstanz.de/pdm06/

Recently major processor manufacturers have announced a dramatic shift in
their paradigm to increase computing power over the coming years. Instead
of focusing on faster clock speeds and more powerful single core CPUs,
the trend clearly goes towards multi core systems. This will also result
in a paradigm shift for the development of algorithms for computationally
expensive tasks, such as data mining applications. Obviously, work on
parallel algorithms is not new per se but concentrated efforts in the
many application domains are still missing. Multi-core systems, but also
clusters of workstations and even large-scale distributed computing
infrastructures provide new opportunities and pose new challenges for the
design of parallel and distributed algorithms.

Since data mining and machine learning systems rely on high performance
computing systems, research on the corresponding algorithms must be on
the forefront of parallel algorithm research in order to keep pushing
data mining and machine learning applications to be more powerful and,
especially for the former, interactive. The workshop focus will encompass
data mining and machine learning approaches from low to high degree of
parallelism, embracing algorithms for tightly coupled sharedmemory
systems (as will become widely available using multi core systems) and
also distributed approaches making use of the increasingly mature grid
infrastructure.

TOPICS OF INTEREST

Contributions are sought in all areas of high performance computing in
Data Mining and Machine Learning, in particular:

• Systems
• Distributed, grid and peer-to-peer computing
• parallel computing, multi-core systems
• distributed and shared-memory systems
• Methods
• Mining distributed datasets
• Meta learning
• Distributed, partial model learning
• Platforms and Tools
• Parallel data mining workflow management environments
• Distributed systems and tools for data mining and data exploration

We also welcome submissions on data mining for the analysis of
distributed systems as well as reports on applications of particular
interest.

For more information, please email PDM06@inf.uni-konstanz.de

IMPORTANT DATES

• Paper submission deadline: July 7, 2006 (12pm GMT)
• Notification: July 31th, 2006
• Camera ready deadline: August 16, 2006
• Workshop: September 18, 2006

See website for detailed instructions on submitting a paper.

WORKSHOP CHAIRS

• Giuseppe Di Fatta, University of Konstanz (Germany) and ICAR-CNR (Italy)
• Michael R. Berthold, University of Konstanz
• Srinivasan Parthasarathy, The Ohio State University

PUBLICITY CHAIR

• Matthew Eric Otey, The Ohio State University

PROGRAM COMMITTEE

• Gagan Agrawal, The Ohio State University, USA
• Pradeep Dubey, Intel Corp., USA
• Mario Cannataro, University "Magna Graecia" of Catanzaro, Italy
• Alok Choudhary, Northwestern University, USA
• Salvatore Gaglio, University of Palermo, Italy
• Robert Grossman, University of Illinois-Chicago, USA
• Yike Guo, Imperial College, UK
• Ruoming Jin, Kent State University, USA
• Hillol Kargupta, University of Maryland, USA
• George Karypis, University of Minnesota, USA
• Shonali Krishnaswamy, Monash University, Australia
• Shinichi Morishita, University of Tokyo, Japan
• Salvatore Orlando, University of Venice, Italy
• Matthew Otey, The Ohio State University
• Raffaele Perego, ISTI-CNR, Italy
• Omer F. Rana, Cardiff University, UK
• Sanjay Ranka, University of Florida, USA
• Assaf Schuster, TECHNION, Israel Institute of Technology, Israel
• Domenico Sacca', ICAR-CNR and University of Calabria, Italy
• Krishnamoorthy Sivakumar, Washington State University, USA
• Domenico Talia, University of Calabria, Italy
• Alfonso Urso, ICAR-CNR, Italy
• Jason T. L. Wang, New Jersey Institute of Technology, USA
• Ran Wolff, University of Maryland at Baltimore County, USA
• Mohammed J. Zaki, Rensselaer Polytechnic Institute, USA
• Albert Y Zomaya, University of Sydney, Australia