[UAI] Relational Data Mining School

From: Saso Dzeroski (Saso.Dzeroski@ijs.si)
Date: Wed Jun 12 2002 - 09:27:29 PDT

  • Next message: Rich Neapolitan: "[UAI] Applications of Bayesian Networks"

    -------------------------------------------------------------------------------

    Relational Data Mining Summer School

    17 and 18 August 2002, Helsinki, Finland
    (Just before ECML/PKDD-2002)

    http://www-ai.ijs.si/SasoDzeroski/RDMSchool/

    [Apologies if you receive multiple copies of this message.]

    ------------------------------------------------------------------------------

    Relational Data Mining (RDM) is the multi-disciplinary field dealing
    with knowledge discovery from relational databases consisting of
    multiple tables. To emphasize the contrast to typical data mining
    approaches that look for patterns in a single database relation, the
    name Multi-Relational Data Mining (MRDM) is often used as well. Mining
    data which consists of complex/structured objects also falls within
    the scope of this field: the normalized representation of such objects
    in a relational database requires multiple tables. The field aims at
    integrating results from existing fields such as inductive logic
    programming (ILP), KDD, data mining, machine learning and relational
    databases; producing new techniques for mining multi-relational data;
    and practical applications of such tecniques.

    Present RDM approaches consider all of the main data mining tasks,
    including association analysis, classification, clustering, learning
    probabilistic models and regression. The pattern languages used by
    single-table data mining approaches for these data mining tasks have
    been extended to the multiple-table case. Relational pattern languages
    now include relational association rules, relational classification
    rules, relational decision trees, and probabilistic relational models,
    among others. RDM algorithms have been developed to mine for patterns
    expressed in relational pattern languages. Typically, data mining
    algorithms have been upgraded from the single-table case: for example,
    distance-based algorithms for prediction and clustering have been
    upgraded by defining distance measures between examples/instances
    represented in relational logic. RDM methods have been successfully
    applied accross many application areas, ranging from the analysis of
    business data, through bioinformatics (including the analysis of
    complete genomes) and pharmacology (drug design) to Web mining (e.g.,
    information extraction from Web sources).

    The Summer School on Relational Data Mining will provide
    a comprehensive introduction to the techniques and applications
    of relational data mining by leading experts in the field.
    The Summer School is organized with the help and support of
    the University of Helsinki and is financially supported by ILPnet2
    (The Network of Excellence in Inductive Logic Programming).
    Attendance will be free of charge, but registration is required.

    More information at http://www-ai.ijs.si/SasoDzeroski/RDMSchool/



    This archive was generated by hypermail 2b29 : Wed Jun 12 2002 - 09:31:41 PDT