PAKDD-01, Hong Kong, April 16-18: Call for Participation

From: Graham Williams (
Date: Fri Mar 02 2001 - 12:10:30 MET

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    Pacific-Asia Conference on Knowledge Discovery and Data Mining

    Visit the PAKDD-01 Home Page:


    Early Bird Registration Due March 16:


    There are several international fairs, exhibitions, and conferences
    (some related to PAKDD, including DASFAA and IFIP DS-9) in Hong Kong
    during the month of April 2001. Reserve your accommodation soon:




      PAKDD 2001, Hong Kong, 16--18 April, is the Fifth Pacific-Asia
      Conference on Knowledge Discovery and Data Mining. It is the successor
      of earlier PAKDD conferences held in Singapore (1997), Melbourne,
      Australia (1998), Beijing, China (1999), and Kyoto, Japan (2000).

      PAKDD 2001 will be an international forum for the sharing of original
      research results and practical development experiences. Practitioners
      and researchers alike will benefit from the technical program and
      scholarly exchange.


      Incompleteness in Data Mining

      Professor H. V. Jagadish, a world leading researcher in data mining
      from the University of Michigan thinks that the current data mining
      techniques, with carefully engineered algorithms, are extremely
      expensive. Since the central goal of data mining is to find SOME
      interesting patterns, he will argue that it is not necessary to find
      ALL of them -- is incompleteness the right answer ?

      Mining E-commerce Data: The Good, the Bad, and the Ugly

      Dr. Ronny Kohavi, Director of Data Mining at Blue Martini Software,
      is an industrial leader in Data Mining software. He will talk about
      the lessons, stories, and challenges of data mining based on mining
      real data. According to Ronny e-commerce provides all the right
      ingredients for data mining (the Good). So, what are the Bad and the
      Ugly ?

      Seamless Integration of Data Mining with DBMS and Applications

      Professor Hongjun Lu of The Hong Kong University of Science and
      Technology, an internationally renowned researcher in data mining,
      will argue that most data mining algorithms can only be loosely
      coupled with data infrastructures in organizations and are difficult
      to infuse into existing mission-critical applications. He will
      propose to tackle the problem of integration of data mining
      with DBMS and applications from three directions.


      The technical program features 38 regular presentations and 22 short
      presentations. Topics include: Web and Text Mining; Sequence, Spatial
      and Temporal Mining; Applications and Tools; and more.

      For a complete list of papers visit:


      PAKDD01 has created a new track for practitioners, vendors and users
      to present experiences in data mining in their respective areas.

      - Data Mining at Standard Chartered Bank, Steven Parker, Standard and

      - Improving web design - mining web data at, H.P.Lo, City U
        of Hong Kong

      - Data Mining Application and Implementation in Banking, a Case
        Study, Dick Cheng, SAS Institute, Australia

      - Data Mining Application in Internet Polling, Dennis Pang,
        Superpoll, Taiwan

      - and many more ....


      An Introduction to MARS
        - Dr. Dan Steinberg, CEO of Salford Systems, USA

      Static and Dynamic Data Mining Using Advanced Machine Learning
         - Professor Ryszard S. Michalski, George Mason University, USA

      Sequential Pattern Mining: From Shopping History Analysis to
      Weblog Mining and DNA Mining
         - Professor Jiawei Han and Mr. Jian Pei, Simon Fraser University,

      Recent Advances in Data Mining Algorithms for Large Databases
         - Dr. Rajeev Rastogi and Dr. Kyuseok Shim, AT&T Bell Lab
           & KAIST, Korea.

      Web Mining for E-Commerce
         - Professor Jaideep Srivastava, University of Minnesota, USA

      From Evolving Single Neural Networks to Evolving Ensembles
         - Professor Xin Yao, The University of Birmingham, United Kingdom.


      Spatial and Temporal Data;

      Statistical Techniques in Data Mining;

      Data Mining an Electronic Business.


    Conference Chairs:
     Chung-Jen Tan (University of Hong Kong and IBM Watson)
     Jiawei Han (Simon Fraser University, Canada)

    Program Committee Chairs:
     David Cheung (University of Hong Kong)
     Qing Li (City University of Hong Kong)
     Graham Williams (CSIRO, Australia)

    Tutorial Chair:
     Joshua Z Huang (University of Hong Kong)

    Workshop Chair:
     Michael K Ng (University of Hong Kong)

    Industrial Chair:
     Joseph Fong (City University of Hong Kong)

    Demonstration Chair:
     Jiming Liu (Baptist University of Hong Kong)

    Local arrangements Chairs:
     Ronnie Cheung (Hong Kong Poly University)
     Ben Kao (University of Hong Kong)

    Publicity Chairs:
     Vincent Ng (Hong Kong Poly University)
     Rohan Baxter (CSIRO, Australia)
     Hiroyuki Kawano (Kyoto University, Japan)

     Ada Fu (Chinese University of Hong Kong)


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