With the semantic web, data becomes machine-readable and ontologies define the data. Ontologies in any domain are heterogeneous due to rapid increase in ontology development and differences in views of developers. Agents can fully understand the data only if the correspondences between ontologies are known. Various ontology alignment systems have been developed to automatically discover such correspondences. However, human involvement is still indispensible because the results provided by fully

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... automatic systems are not always complete or precise. This paper introduces Falcon-AO++, an extension of the Falcon-AO alignment system that supports the interactive contribution of a domain expert in the matching process. The evaluation results have shown that contribution of an expert and matching ability of matchers can improve alignment results.