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A generalization model based on OI-implication for ideal theory
refinement
F. Esposito,
N. Fanizzi,
S. Ferilli,
and G. Semeraro.
Fundamenta Informaticae, 47(1-2):15--33, August 2001.
Abstract
A framework for theory refinement is presented pursuing the efficiency and
effectiveness of learning regarded as a search process. A refinement operator
satisfying these requirements is formally defined as ideal. Past results have
demonstrated the impossibility of specifying ideal operators in search spaces
where standard generalization models, like logical implication or
q-subsumption, are adopted. By assuming the object identity bias over a space
defined by a clausal language ordered by logical implication, a novel
generalization model, named OI-implication, is derived and we prove that
ideal operators can be defined for the resulting search space.
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