Document (#15325)

Author

Hausdorf, C.
Müller, M.
Stoyan, H.

Title

¬Eine Theorie der Interessantheit für die Entdeckung von Wissen in Datenbanken

Source

Herausforderungen an die Informationswirtschaft: Informationsverdichtung, Informationsbewertung und Datenvisualisierung. Proceedings des 5. Internationalen Symposiums für Informationswissenschaft (ISI'96), Humboldt-Universität zu Berlin, 17.-19. Oktober 1996. Hrsg.: J. Krause u.a

Imprint

Konstanz : Universitätsverlag

Year

1996

Pages

S.167-178

Series

Schriften zur Informationswissenschaft; Bd.27

Abstract

Wir stellen einen Ansatz vor, mit dem die Flut von Ergebnissen, die Data-Mining-Methoden produzieren, eingedämmt wird, indem diese bezüglich ihrer Interessantheit für den benutzer bewertet und sortiert werden. Der Ansatz basiert auf einer Theorie der Interessantheit für die Entdeckung von Wissen in Datenbanken (KDD), die mit einem sprachorietierten KDD-Model motiviert wird. Wir definieren ein subjektives, dynamisches und kontinuierliches Maß für die Interessantheit von Data-Mining-Ergebnissen und beschreiben die wissensbasierte Bewertung einer Vielzahl von Interessantheitsfacetten. Der Prototyp 'Knowledge Discovery Assistant' wird in einem medizinischen Anwendungsbereich evaluiert

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