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Title:Euro-Par 2006 in Dresden, Germany; Picture of Dresden: DWT/Dittrich
Parallel and Distributed Databases, Data Mining and Knowledge Discovery

Topic5 as .pdf
Topic5 as .txt

Description

Managing and efficiently analysing the vast amounts of data produced by a huge variety of data sources is one of the big challenges in computer science. The development and implementation of algorithms and applications that can extract information diamonds from these ultra-large, and often distributed, databases is a key challenge for the design of future data management infrastructures. Today's data-intensive applications often suffer from performance problems and an inability to scale to high numbers of distributed data sources. Therefore, distributed and parallel databases have a key part to play in overcoming resource bottlenecks, achieving guaranteed quality of service and providing system scalability. The increased availability of distributed architectures, clusters, Grids and P2P systems, supported by high performance networks and intelligent middleware provides parallel and distributed databases and digital repositories with a great opportunity to cost-effectively support key everyday applications. Further, there is the prospect of data mining and knowledge discovery tools adding value to these vast new data resources by automatically extracting useful information from them.
We especially solicit submissions for either the Experience and Application Section, or the traditional System and Research Section.

Focus

    Experience and Application Section
    1. data mining, knowledge discovery
    2. multimedia applications
    3. data warehousing and decision support
    4. discovering structures in web data, web data mining
    5. mobile computing and databases
    6. web applications
    7. information retrieval and web search engines
    8. data-intensive grid
    9. case studies
    System and Research Section
    1. query optimization and query processing
    2. parallel algorithms for data mining
    3. communication requirements for parallel data mining
    4. data representation and storage for fast access
    5. middleware and architectural issues
    6. transaction processing
    7. distributed knowledge discovery


Global Chair

Local Chair

Dr. Patrick Valduriez
INRIA and LINA
Nantes, France
Prof. Dr. Wolfgang Lehner
TU Dresden
Dept. Of Computer Science
Dresden, Germany

Vice Chair

Vice Chair

Prof. Dr. Domenico Talia
DEIS, University of Calabria
Rende CS, Italy
Prof. Dr. Paul Watson
University of Newcastle Upon Tyne
School of Computing Science
Newcastle Upon Tyne, UK