COntExt: Towards Context-Aware Ontology Extension from Operational Metrics

COntExt is a framework that uses structured operational metric definitions as contextual evidence for extending an existing ontology. It formulates the problem as three subtasks: parent class prediction, relation type prediction, and data property assignment. The authors evaluate multiple algorithms across four cybersecurity ontologies. According to the abstract, metric-derived context improves relation type prediction and data property assignment over baselines using ontology context alone. However, the supplied abstract reports no dataset sizes, evaluation metrics, numerical gains, or evidence quantifying the claimed reduction in ontology-maintenance cost.