The paper presents the ultimate version of a concept learning system which can support typical ontology construction/evo-lution 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.
CITATION STYLE
Fanizzi, N., Rizzo, G., D’amato, C., & Esposito, F. (2018). Dlfoil: Class expression learning revisited. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11313, pp. 98–113). Springer Verlag. https://doi.org/10.1007/978-3-030-03667-6_7
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