DLFoil: Class Expression Learning Revisited.

EKAW(2018)

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摘要
The paper presents the ultimate version of a concept learning system which can support typical ontology construction/evolution tasks through the induction of class expressions from groups of individual resources labeled by a domain expert. Stating the target task as a search problem, a Foil-like algorithm was devised based on the employment of refinement operators to traverse the version-space of candidate definitions for the target class. The algorithm has been further enhanced including a more general definition for the scoring function and better refinement operators. An experimental evaluation of the resulting new release of DL-Foil, which implements these improvements was carried out to assess its performance also in comparison with other concept learning systems.
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