Abstract
When developing ontologies, knowledge engineers and domain experts often use predicates that are vague, i.e., predicates that lack clear applicability conditions and boundaries such as High, Expert or Bad. In previous works, we have shown how such predicates within ontologies can hamper the latter's shareability and meaning explicitness and we have proposed Vagueness Ontology (VO), an OWL metaontology for representing vagueness-aware ontologies, i.e., ontologies whose (vague) elements are annotated by explicit descriptions of the nature and characteristics of their vagueness. A limitation of VO is that it does not model the way vagueness and its characteristics propagate when defining more complex OWL axioms (such as conjunctive classes), neither does it enforce any kind of vagueness-related consistency. For that, in this paper, we expand VO by means of formal inference rules and constraints that model the way vagueness descriptions of complex ontology elements can be automatically derived. More importantly, we enable the efficient execution of these rules by means of a novel meta-reasoning framework.
Original language | English |
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Title of host publication | Proceedings - 2016 IEEE 10th International Conference on Semantic Computing, ICSC 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 222-229 |
Number of pages | 8 |
ISBN (Electronic) | 9781509006618 |
DOIs | |
Publication status | Published - 22 Mar 2016 |
Event | 10th IEEE International Conference on Semantic Computing, ICSC 2016 - Laguna Hills, United States Duration: 3 Feb 2016 → 5 Feb 2016 |
Conference
Conference | 10th IEEE International Conference on Semantic Computing, ICSC 2016 |
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Country/Territory | United States |
City | Laguna Hills |
Period | 3/02/16 → 5/02/16 |
Keywords
- metamodeling Reasoning
- ontological Metamodeling
- vague Concept
- vagueness Ontology
- ontologies
- OWL
- Iris
- context
- companies
- cognition
- electronic mail