AgreementMakerLight 2.0: Towards Efficient Large-Scale Ontology Matching

In recent years, ontology matching systems have had a growing interest in terms of reasoning capabilities, and we propose that a combination of these strategies with pattern-

In this paper, we present YAM++ - an ontology matching tool, which supports: (i) discovering alignment of ontologies by machine learning approaches; (ii) discovering alignment

In this paper, we present YAM++ - an ontology matching tool, which supports: (i) discovering alignment of ontologies by machine learning approaches; (ii) discovering alignment

Besides real-world specific match- ing tasks, involving e.g., large biomedical ontologies, OAEI 2016 introduced the process model matching track as well as a desease-phenotype

The traditional approach refers to the BK selection methods that match the source and target ontologies to all the preselected ontologies, and then they use the gen- erated

We have developed a method of specifically ontological quality control in ontology mapping which combines a suite of partially overlapping mapping heuristics

In our evaluation, we have shown that our system is actually capable of matching large ontologies, that the choice of a particular partitioning algorithm is only of minor

In this paper, we have presented different strategies to improve the precision of background knowledge based Ontology Matching systems, by considering the semantics of the terms to