WordNet: a lexical database for English
Communications of the ACM
Ontology Matching
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Exploring the Semantic Web as Background Knowledge for Ontology Matching
Journal on Data Semantics XI
Media Meets Semantic Web --- How the BBC Uses DBpedia and Linked Data to Make Connections
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Ontology alignment for linked open data
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
Contextual ontology alignment of LOD with an upper ontology: a case study with proton
ESWC'11 Proceedings of the 8th extended semantic web conference on The semantic web: research and applications - Volume Part I
A machine learning approach to multilingual and cross-lingual ontology matching
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Leveraging community-built knowledge for type coercion in question answering
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part II
DBpedia spotlight: shedding light on the web of documents
Proceedings of the 7th International Conference on Semantic Systems
A string metric for ontology alignment
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
A survey of schema-based matching approaches
Journal on Data Semantics IV
Cross-lingual knowledge linking across wiki knowledge bases
Proceedings of the 21st international conference on World Wide Web
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Ontology Matching: State of the Art and Future Challenges
IEEE Transactions on Knowledge and Data Engineering
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The inherent heterogeneity of datasets on the Semantic Web has created a need to interlink them, and several tools have emerged that automate this task. In this paper we are interested in what happens if we enrich these matching tools with knowledge of the domain of the ontologies. We explore how to express the notion of a domain in terms usable for an ontology matching tool, and we examine various methods to decide what constitutes the domain of a given dataset. We show how we can use this in a matching tool, and study the effect of domain knowledge on the quality of the alignment. We perform evaluations for two scenarios: Last.fm artists and UMLS medical terms. To quantify the added value of domain knowledge, we compare our domain-aware matching approach to a standard approach based on a manually created reference alignment. The results indicate that the proposed domain-aware approach indeed outperforms the standard approach, with a large effect on ambiguous concepts but a much smaller effect on unambiguous concepts.