Call for Papers 

ECML PKDD 2006 Workshop on Parallel Data Mining

The Workshop on Parallel Data Mining will be held on September 18, 2006 in conjunction with the 17th European Conference on Machine Learning and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases in Berlin, Germany.


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

Paper Submission

Authors are invited to submit original and unpublished manuscripts to Submitted papers will undergo a peer-review process. Final versions of accepted papers will appear in the workshop proceedings. Submission implies the willingness of at least one of the authors to register and present the paper.
The instructions for authors and the LaTeX packages can be found at Manuscripts should not exceed 12 pages in this format.


Workshop Program

The workshop schedule is available here.


The workshop proceedings will be available at the conference.


Workshop Chairs:

  • Giuseppe Di Fatta

    University of Reading
    School of Systems Engineering

  • Michael R. Berthold

    University of Konstanz
    Department of Computer and Information Science

  • Srinivasan Parthasarathy

    The Ohio State University
    Department of Computer Science and Engineering, and Department of Biomedical Informatics

Publicity Chair:

  • Matthew Eric Otey

    The Ohio State University
    Department of Computer Science and Engineering

Program Committee

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