Abstract
An important data mining problem is to restrict the number of association rules to those that are novel, interesting, useful. However, there are situations when a user is not allowed to access the database and can deal only with the rules provided by somebody else. The number of rules can be limited e.g. for security reasons or the rules are of low quality. Still, the user hopes to find new interesting relationships. In this paper we propose how to induce as much knowledge as possible from the provided set of rules. The algorithms for inducing theory as well as for computing maximal covering rules for the theory are provided. In addition, we show how to test the consistency of rules and how to extract aconsistent subset of rules.
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References
Agrawal, R., Imielinski, T., Swami, A.: Mining Associations Rules between Sets of Items in Large Databases. In: Proc. of the ACM SIGMOD Conference on Management of Data. Washington, D.C. (1993) 207–216
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast Discovery of Association Rules. In: Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R. (eds.): Advances in Knowledge Discovery and Data Mining. AAAI, Menlo Park, California (1996) 307–328
Kryszkiewicz, M.: Representative Association Rules. In: Proc. of PAKDD '98. Melbourne, Australia. LNAI1394. Springer-Verlag (1998) 198–209
Kryszkiewicz, M.: Fast Discovery of Representative Association Rules. In: Proc. of RSCTC '98. Warsaw, Poland. LNAI 1424. Springer-Verlag (1998) 214–221
Kryszkiewicz, M.: Mining with Cover and Extension Operators. In: Proc. of PKDD'00. Lyon, France. To appear as a Springer-Verlag LNAI volume
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Kryszkiewicz, M. (2001). Inducing Theory for the Rule Set. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_48
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DOI: https://doi.org/10.1007/3-540-45554-X_48
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