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E-FORENSICS 2008
WKDD 2008
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    WKDD

    1st International ICST Workshop on Knowledge Discovery and Data Mining

    Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. Knowledge discovery a…

    Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. Knowledge discovery and data mining can be extremely beneficial for the field of Artificial Intelligence in many areas, such as industry, commerce, government, education and so on.

    In view of this, a workshop on knowledge Discovery and Data Mining aims to provide an opportunity for the sharing of original research results, innovative ideas, state-of-the-art developments, and implementation experiences in knowledge discovery and data mining among researchers in academic and industrial organizations.

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    Editor(s): Qi LuoWuhan (Institute of Technology, China), Mingmin Gong, Feng Xiong and Fei Yu
    Publisher
    ACM
    ISBN
    0-7695-3090-7
    Conference dates
    23rd–24th Jan 2008
    Location
    Adelaide, Australia
    Appeared in EUDL
    2011-11-29

    Copyright © 2011–2025 ICST

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    Showing 31–33 of 33 results
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    • The Development and Application of Chinese Intelligent Question Answering System Based on J2EE Technology

      Research Article in 1st International ICST Workshop on Knowledge Discovery and Data Mining

      Shouning Qu, Bing Zhang, Xinsheng Yu, Qin Wang
    • The method engineering process for multi-agent system development

      Research Article in 1st International ICST Workshop on Knowledge Discovery and Data Mining

      Xue Xiao, Zhang Xue Yan
    • Towards Self-tuning of Dynamic Resources for Workloads

      Research Article in 1st International ICST Workshop on Knowledge Discovery and Data Mining

      FU Duan, Yongjie Han, Qiuyong Zhao, Keming Xie
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