Special Session in KES'2002: "Data clustering based on nonmetric similarity measures"

From: Francesco Marcelloni (f.marcelloni@iet.unipi.it)
Date: Tue Jan 08 2002 - 00:03:34 MET

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     Dear Reader concerned in Soft Computing,
    We are trying to organize a Special Session in KES'2002, Sixth International
    Conference on Knowledge-Based Intelligent Information & Engineering Systems,
    16-18 September 2002, Crema, Italy. (For more details on this conference,
    please consult the KES'2002 home page:

    http://www.bton.ac.uk/kes/kes2002).

    Title of the session: "Data clustering based on nonmetric similarity
    measures".

    One of the crucial aspects of clustering algorithms is the identification of
    the similarity (most commonly, dissimilarity) measure used to drive the data
    partitioning. Actually, the similarity between any two patterns may depend
    on aspects (e.g., related to contextual or conceptual information) that
    cannot be expressed in terms of distance measures. Approaches based on
    context modeling or conceptual similarity have been proposed in the
    literature. Of course, these techniques require adequate and complete
    knowledge of either the surrounding context or pre-defined concepts,
    respectively. Unfortunately, real-world data tend to be incomplete;
    furthermore, pre-defined concepts are not easily identifiable in real-world
    applications.

    The aim of this session is to encourage researchers to propose new,
    alternative approaches to data clustering that are able to identify the
    similarity measure most suited to the specific application.

    Participation:

    Prospective authors are requested to send papers to the address indicated
    below (electronic submissions are possible). The guidelines for submission
    of papers can be found at the afore-mentioned KES'2002 home page.

    Deadlines:

    Receipt of papers: 15 April 2002

    Notification of acceptance: 1 May 2002

    Final papers due: 25 May 2002

    Best regards

    Beatrice Lazzerini and Francesco Marcelloni

    Dipartimento di Ingegneria della Informazione
    University of Pisa
    Via Diotisalvi, 2 -56122 Pisa, ITALY
    e-mail: {b.lazzerini, f.marcelloni}@iet.unipi.it

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