A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Ontology mapping: the state of the art
The Knowledge Engineering Review
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
ACM SIGMOD Record
Ontology Alignment: Bridging the Semantic Gap (Semantic Web and Beyond)
Ontology Alignment: Bridging the Semantic Gap (Semantic Web and Beyond)
Ontology Matching
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
The recovery of a schema mapping: bringing exchanged data back
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Matching large ontologies: A divide-and-conquer approach
Data & Knowledge Engineering
Reverse data exchange: coping with nulls
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Improving Ontology Matching Using Meta-level Learning
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
RiMOM: A Dynamic Multistrategy Ontology Alignment Framework
IEEE Transactions on Knowledge and Data Engineering
Inverting schema mappings: bridging the gap between theory and practice
Proceedings of the VLDB Endowment
UFOme: An ontology mapping system with strategy prediction capabilities
Data & Knowledge Engineering
Evaluation of two heuristic approaches to solve the ontology meta-matching problem
Knowledge and Information Systems
A semantically enhanced service repository for user-centric service discovery and management
Data & Knowledge Engineering
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Ontology Matching aims to find the semantic correspondences between ontologies that belong to a single domain but that have been developed separately. However, there are still some problem areas to be solved, because experts are still needed to supervise the matching processes and an efficient way to reuse the alignments has not yet been found. We propose a novel technique named Reverse Ontology Matching, which aims to find the matching functions that were used in the original process. The use of these functions is very useful for aspects such as modeling behavior from experts, performing matching-by-example, reverse engineering existing ontology matching tools or compressing ontology alignment repositories. Moreover, the results obtained from a widely used benchmark dataset provide evidence of the effectiveness of this approach.