Abstract
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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Notes
- 1.
A space endowed with a quasi-ordering, i.e. a reflexive and transitive relationship.
- 2.
This may be considered a basic upper refinement operator allowed by expressive DL languages (encompassing \(\mathcal {ALC}\)).
- 3.
An acyclic TBox does not contains multiple definitions for a concept name and such a concept is not used to the right-side of an equivalence axiom.
- 4.
The source code and the datasets/ontologies are publicly available at: https://bitbucket.org/grizzo001/dl-foil/src/master/.
- 5.
Assessed by JFact reasoner: http://jfact.sourceforge.net/.
- 6.
The experiments were carried out on a 8-core Ubuntu server with 16 GB RAM.
- 7.
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Fanizzi, N., Rizzo, G., d’Amato, C., Esposito, F. (2018). DLFoil: Class Expression Learning Revisited. In: Faron Zucker, C., Ghidini, C., Napoli, A., Toussaint, Y. (eds) Knowledge Engineering and Knowledge Management. EKAW 2018. Lecture Notes in Computer Science(), vol 11313. Springer, Cham. https://doi.org/10.1007/978-3-030-03667-6_7
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