BISC: BISC NEWSLetter for the Week of June 11;

From: masoud nikravesh (nikraves@eecs.berkeley.edu)
Date: Mon Jun 11 2001 - 05:25:22 MET DST

  • Next message: Vladik Kreinovich: "CIT-2001: deadline extended to July 2, 2001"

    *********************************************************************
    Berkeley Initiative in Soft Computing (BISC)
    *********************************************************************

    ========================
    Instance Selection and Construction for Data Mining
          edited by Huan Liu & Hiroshi Motoda

    THE KLUWER INTERNATIONAL SERIES IN ENGINEERING AND
    COMPUTER SCIENCE Volume 608

    Table of Contents and Authors:
    http://www.wkap.nl/bookcc.htm/0-7923-7209-3

    The ability to analyze and understand massive
    data sets lags far behind the ability to gather
    and store the data. To meet this challenge,
    knowledge discovery and data mining (KDD) is
    growing rapidly as an emerging field. However,
    no matter how powerful computers are now or will
    be in the future, KDD researchers and
    practitioners must consider how to manage
    ever-growing data which is, ironically, due to
    the extensive use of computers and ease of data
    collection with computers. Many different
    approaches have been used to address the data
    explosion issue, such as algorithm scale-up and
    data reduction. Instance, example, or tuple
    selection pertains to methods or algorithms that
    select or search for a representative portion of
    data that can fulfill a KDD task as if the whole
    data is used. Instance selection is directly
    related to data reduction and becomes
    increasingly important in many KDD applications
    due to the need for processing efficiency and/or
    storage efficiency.

    One of the major means of instance selection is
    sampling whereby a sample is selected for
    testing and analysis, and randomness is a key
    element in the process. Instance selection also
    covers methods that require search. Examples can
    be found in density estimation (finding the
    representative instances - data points - for a
    cluster); boundary hunting (finding the critical
    instances to form boundaries to differentiate
    data points of different classes); and data
    squashing (producing weighted new data with
    equivalent sufficient statistics). Other
    important issues related to instance selection
    extend to unwanted precision, focusing, concept
    drifts, noise/outlier removal, data smoothing,
    etc.

     Instance Selection and Construction for Data
    Mining brings researchers and practitioners
    together to report new developments and
    applications, to share hard-learned experiences
    in order to avoid similar pitfalls, and to shed
    light on the future development of instance
    selection. This volume serves as a comprehensive
    reference for graduate students, practitioners
    and researchers in KDD.

    Kluwer Academic Publishers, Boston
    * Hardbound, ISBN 0-7923-7209-3
    February 2001, 448 pp.

    ===============================

    7th Fuzzy Days in Dortmund - International Conference on Computational
    Intelligence, Dortmund, Germany, October 1-3, 2001
    http://ls1-www.cs.uni-dortmund.de/fd7

    =======================================

       ICDM '01: The 2001 IEEE International Conference on Data Mining
                    Sponsored by the IEEE Computer Society

    ----------------------------------------------------------------------
                 Doubletree Hotel, San Jose, California, USA
                        November 29 - December 2, 2001
           Home Page: http://kais.mines.edu/~xwu/icdm/icdm-01.html
    ===============================================
    The Call for papers hereafter is aimed at the scientific community
    interested in Networked Learning:

    World Conference
    NL 2002 - Networked Learning in a Global Environment:
    Challenges and Solutions for Virtual Education

    http://www.icsc-naiso.org/conferences/nl2002

    Sponsors of NL 2002

    Virtual Global University for Worldwide Education
    http://www.vg-u.de

    Counsil of European Professional Informatics Societies
    http://www.cepis.org

    Gesellschaft für Informatik E.V.
    http://www.gi-ev.de

    Technical University of Berlin, Germany
    http://www.tu-berlin.de

    European University Viadrina Frankfurt (Oder)
    http://www.euv-frankfurt-o.de

    ICSC-NAISO
    http://www.icsc-naiso.org

    Venue and Date
    May 1 - 4, 2002, Technical University of Berlin, Germany

    =============================================

    APPLIED SOFT COMPUTING

    Publisher: Elsevier Science

    The Official Journal of the World Federation on Soft Computing (WFSC)

    Journal homepage: http://www.elsevier.com/locate/asoc/

    ===============================================

     EXTENDED DEADLINE: CALL FOR PAPERS

    The deadline for receipt of submissions to this workshop has been
    extended to June 27.

                ***************************************************
                * FUZZ-IEEE 2001 WORKSHOP ON MODELLING WITH WORDS *
                ***************************************************

                           FUZZ-IEEE 2001 Conference

                            University of Melbourne,
                                  Australia.

                             December 2nd / 3rd 2001

                 http://www.enm.bris.ac.uk/ai/enjl/workshop.html

           CONFERENCE WEBPAGE http://www.studentadmin.unimelb.edu.au/fuzzy/

    =================================================================

    Knowledge and Information Systems: An International Journal
         -----------------------------------------------------------

                      ISSN: 0219-1377 (printed version)
                    ISSN: 0219-3116 (electronic version)
                             by Springer-Verlag

              Home Page: http://kais.mines.edu/~kais/home.html
              ================================================

    Volume 3, Number 3, August 2001

    =============================================================

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