Name
Abstract | ||
|---|---|---|
When using ontology in dynamic environments, we should adapt it accordingly to follow the new requirements. Ontology should remain in a consistent state after changes. Otherwise, ontology inconsistency would be propagated to the dependent artifacts and may engender serious errors. This issue is addressed in this paper, by proposing an a priori repair action to prevent inconsistencies when updating OWL 2 DL ontologies. Predictive algorithms are defined to foresee the potential inconsistencies and to keep the ontology logically consistent, free of syntactical invalidities and style issues after each change. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3102254.3102285 | WIMS |
Field | DocType | ISBN |
Ontology (information science),Ontology,Ontology-based data integration,Data mining,Process ontology,Information retrieval,Computer science,Predictive analytics,A priori and a posteriori,Repair - action,Web Ontology Language | Conference | 978-1-4503-5225-3 |
Citations | PageRank | References |
0 | 0.34 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leila Bayoudhi | 1 | 1 | 0.71 |
| Najla Sassi | 2 | 26 | 5.26 |
| Wassim Jaziri | 3 | 33 | 10.87 |