Clustering Association Rules with Fuzzy Concepts

Author:

Steinbrecher Matthias,Kruse Rudolf

Publisher

Springer Berlin Heidelberg

Reference7 articles.

1. Agrawal, R., Imielinski, T., & Swami, A. N. (1993). Mining association rules between sets of items in large databases. In P. Buneman & S. Jajodia (Eds.), Proc. ACM Sigmod Int. Conf. on Management of Data, Washington, D.C., May 26–28, 1993 (pp. 207–216). ACM Press.

2. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., & Verkamo, A. I. (1996). Fast discovery of association rules. In Advances in knowledge discovery and data mining (pp. 307–328). Cambridge, MA: AAAI/MIT Press.

3. Borgelt, C. (2003). Efficient implementations of apriori and eclat. In Workshop frequent item set mining implementations (FIMI 2003, Melbourne, FL, USA). Aachen, Germany: CEUR Workshop Proceedings 90.

4. Borgelt, C. (2005). An implementation of the FP-growth algorithm. In Proc. workshop open software for data mining (OSDM 2005, Chicago, IL) (pp. 1–5). New York: ACM Press.

5. Steinbrecher, M., & Kruse, R. (2007). Visualization of possibilistic potentials. In Foundations of fuzzy logic and soft computing (Vol. 4529, pp. 295–303). Heidelberg: Springer.

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