Zusammenfassung
Dieser Artikel gibt einen überblick über das Gebiet der Wissensentdeckung in Datenbanken und Data Mining. Ferner gibt der Artikel eine übersicht zu existierenden Techniken, Werkzeugen und Anwendungen in wissenschaftlicher Forschung und industrieller Praxis. Die verschiedenen Phasen des Prozesses der Wissensentdeckung werden vorgestellt und analysiert. Es gibt eine Reihe von Data Mining Zielen, die sich durch Anwendung des extrahierten Wissens bearbeiteten lassen. Wir beschreiben diese Ziele und stellen die entsprechenden Verfahren vor, die zur Erreichung dieser Ziele geeignet sind. Solche Verfahren basieren auf statistischen Methoden, neuronalen Netzen, Case-Based Reasoning und symbolischen Lernverfahren. Einige wichtige Phasen des Prozesses, wie die Vorbereitung der Daten, die eigentliche Entdeckung neuen Wissens und Bewertung der Ergebnisse werden wir ausfuhrlicher diskutieren. Inzwischen hat die Wissensentdeckung in Datenbanken in verschiedenen Gebieten zahlreiche Anwendungen gefunden. Außerdem sind die Anzahl der existierenden Systeme für die Wissensentdeckung explosionsartig in die Höhe gestiegen. Aus diesem Grund ist eine Beschreibung diverser Anwendungen und die Vorstellung aller existierender Systeme nicht möglich. Wir stellen jedoch einige Anwendungen vor und beschreiben einige ausgewählte Systeme. Ein überblick über die aktuellen Forschungsthemen schließt den Artikel ab.
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Nakhaeizadeh, G., Reinartz, T., Wirth, R. (1998). Wissensentdeckung in Datenbanken und Data Mining: Ein überblick. In: Nakhaeizadeh, G. (eds) Data Mining. Beiträge zur Wirtschaftsinformatik, vol 27. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-86094-2_1
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