Abstract
An attribute-oriented induction has been developed in the previous study of knowledge discovery in databases. A concept tree ascension technique is applied in concept generalization. In this paper, we extend the background knowledge representation from an unconditional non-rule-based concept hierarchy to a rule-based concept hierarchy, which enhances greatly its representation power. An efficient rule-based attribute-oriented induction algorithm is developed to facilitate learning with a rule-based concept graph. An information loss problem which is special to rule-based induction is described together with a solution suggested.
The research of the third author was supported in part by grants from the Natural Sciences and Engineering Research Council of Canada and the Centre for Systems Science of Simon Fraser University.
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© 1994 Springer-Verlag Berlin Heidelberg
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Cheung, D.Wl., Wai-Chee Fu, A., Han, J. (1994). Knowledge discovery in databases: A rule-based attribute-oriented approach. In: Raś, Z.W., Zemankova, M. (eds) Methodologies for Intelligent Systems. ISMIS 1994. Lecture Notes in Computer Science, vol 869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58495-1_17
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DOI: https://doi.org/10.1007/3-540-58495-1_17
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