Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Matching directories and OWL ontologies with AROMA
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Ontology Matching
Machine Learning Approach for Ontology Mapping Using Multiple Concept Similarity Measures
ICIS '08 Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008)
Indirect Alignment between Multilingual Ontologies: A Case Study of Korean and Swedish Ontologies
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Cross-Lingual Ontology Mapping --- An Investigation of the Impact of Machine Translation
ASWC '09 Proceedings of the 4th Asian Conference on The Semantic Web
Challenges for the multilingual Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
MultiFarm: A benchmark for multilingual ontology matching
Web Semantics: Science, Services and Agents on the World Wide Web
Domain-Aware ontology matching
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Boosting cross-lingual knowledge linking via concept annotation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Ontology matching is a task that has attracted considerable attention in recent years. With very few exceptions, however, research in ontology matching has focused primarily on the development of monolingual matching algorithms. As more and more resources become available in more than one language, novel algorithms are required which are capable of matching ontologies which share more than one language, or ontologies which are multilingual but do not share any languages. In this paper, we discuss several approaches to learning a matching function between two ontologies using a small set of manually aligned concepts, and evaluate them on different pairs of financial accounting standards, showing that multilingual information can indeed improve the matching quality, even in cross-lingual scenarios. In addition to this, as current research on ontology matching does not make a satisfactory distinction between multilingual and cross-lingual ontology matching, we provide precise definitions of these terms in relation to monolingual ontology matching, and quantify their effects on different matching algorithms.