- Amr Ahmed, Andrew O. Arnold, Luis Pedro Coelho, Joshua D. Kangas, Abdul-Saboor Sheikh, E. Xing, William W. Cohen, R. Murphy. 2010. Web Semantics: Science, Services and Agents on the World Wide Web. Abstract: abstract Ontologymappingseekstoﬁndsemanticcorrespondencesbetweensimilarelementsofdifferentontolo-gies. It is a key challenge to achieve semantic interoperability in building the Semantic Web. This paperproposes a new generic and adaptive ontology mapping approach, called the PRIOR+, based on propa-gation theory, information retrieval techniques and artiﬁcial intelligence. The approach consists of threemajormodules,i.e.,theIR-basedsimilaritygenerator,theadaptivesimilarityﬁlterandweightedsimilar-ity aggregator, and the neural network based constraint satisfaction solver. The approach ﬁrst measuresboth linguistic and structural similarity of ontologies in a vector space model, and then aggregates themusing an adaptive method based on their harmonies, which is deﬁned as an estimator of performanceof similarity. Finally to improve mapping accuracy the interactive activation and competition neuralnetwork is activated, if necessary, to search for a solution that can satisfy ontology constraints. Theexperimental results show that harmony is a good estimator of f-measure; the harmony based adaptiveaggregation outperforms other aggregation methods; neural network approach signiﬁcantly boosts theperformance in most cases. Our approach is competitive with top-ranked systems on benchmark testsat OAEI campaign 2007, and performs the best on real cases in OAEI benchmark tests.© 2009 Elsevier B.V. All rights reserved.
