Abstract
In this paper we analyze relationships between different forms of knowledge that can be discovered in the same data matrix (database): contingency tables, equations, concept definitions, and concept hierarchies. We argue for the basic role of contingency tables and equations (law-like knowledge), and for the limitations of concept hierarchies. We show how a subset of contingency tables which approximate logical equivalence can be used to construct concept hierarchies: (1) each of those regularities leads to an element of the conceptual hierarchy, (2) the elements are merged to increase their empirical contents, and (3) hierarchy elements are combined into concept hierarchy. The possibility of different hierarchies leads to the question of choice between hierarchies, for which we provide our optimality criterion. We illustrate our algorithm by an application on the soybean database, and we show how our results go beyond the results obtained by the COBWEB approach to clustering.
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© 1994 Springer-Verlag Berlin Heidelberg
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Troxel, M., Swarm, K., Zembowicz, R., żytkow, J.M. (1994). Concept hierarchies: a restricted form of knowledge derived from regularities. 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_44
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DOI: https://doi.org/10.1007/3-540-58495-1_44
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