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Mining Complex Data - ECML/PKDD 2007 Third International Workshop, MDC 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers (Paperback, 2008 ed.)
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Mining Complex Data - ECML/PKDD 2007 Third International Workshop, MDC 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers (Paperback, 2008 ed.)
Series: Lecture Notes in Artificial Intelligence, 4944
Expected to ship within 10 - 15 working days
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This volume contains 20 papers selected for presentation at the
Third Inter- tional Workshopon Mining Complex Data-MCD2007-held in
Warsaw, Poland, September 17-21, 2007. MCD is a workshop series
that started in conjunction with the 5th IEEE International
Conference on Data Mining (ICDM) in Ho- ton, Texas,
November27-30,2005.ThesecondMCDworkshopwasheldagainin conjunction
with the ICDM Conference in Hong Kong, December 18-22, 2006. Data
mining and knowledge discovery, as stated in their early de?nition,
can today be considered as stable ?elds with numerous e?cient
methods and studies that have been proposed to extract knowledge
from data. Nevertheless, the famous golden nugget is still
challenging. Actually, the context evolved since the ?rst de?nition
of the KDD process, and knowledge now has to be extracted from data
becoming more and more complex. In the frameworkof data mining,
many softwaresolutions were developedfor
theextractionofknowledgefromtabulardata(whicharetypicallyobtainedfrom
relationaldatabases).Methodologicalextensionswereproposedtodealwithdata
initiallyobtainedfromothersources, e.g.,
inthecontextofnaturallanguage(text mining) and image (image
mining). KDD has thus evolved following a unimodal scheme
instantiated according to the type of the underlying data (tabular
data, text, images, etc.), which, at the end, always leads to
working on the classical double entry tabular format. However, in a
large number of application domains, this unimodal approach appears
to be too restrictive. Consider for instance a corpus of medical
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