Anzeige
Erschienen in:
2004 | OriginalPaper | Buchkapitel
Fuzzy Taxonomic, Quantitative Database and Mining Generalized Association Rules
verfasst von : Hong-bin Shen, Shi-tong Wang, Jie Yang
Erschienen in: Rough Sets and Current Trends in Computing
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Mining association rules and the relative knowledge from databases has been a focused topic in recent data mining fields. This paper focuses on the issue of how to mine generalized association rules from quantitative databases with fuzzy taxonomic structure, and a new fuzzy taxonomic quantitative database model has been proposed to solve the problem. The new model is demonstrated effective on a real-world databases.