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In den WarenkorbZustand: New. pp. 284 Illus.
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2008
ISBN 10: 3540684158 ISBN 13: 9783540684152
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 1st edition. 265 pages. 9.00x6.00x0.75 inches. In Stock.
Sprache: Englisch
Verlag: Springer Berlin Heidelberg, 2008
ISBN 10: 3540684158 ISBN 13: 9783540684152
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.
Taschenbuch. Zustand: Neu. Mining Complex Data | ECML/PKDD 2007 Third International Workshop, MDC 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers | Zbigniew W. Ras (u. a.) | Taschenbuch | x | Englisch | 2008 | Springer | EAN 9783540684152 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 284 | Sprache: Englisch | Produktart: Bücher | This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.