Abstract
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.
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CITATION STYLE
Shen, H. B., Wang, S. T., & Yang, J. (2004). Fuzzy taxonomic, quantitative database and mining generalized association rules. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3066, pp. 610–617). Springer Verlag. https://doi.org/10.1007/978-3-540-25929-9_75
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