PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
Semantic-integration research in the database community
AI Magazine - Special issue on semantic integration
MoA: OWL ontology merging and alignment tool for the semantic web
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Ontology Alignment: Bridging the Semantic Gap (Semantic Web and Beyond)
Ontology Alignment: Bridging the Semantic Gap (Semantic Web and Beyond)
Ontology Matching
Comparing two approaches for aligning representations of anatomy
Artificial Intelligence in Medicine
Formalizing Ontology Alignment and its Operations with Category Theory
Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
Semantic precision and recall for ontology alignment evaluation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Towards automatic merging of domain ontologies: The HCONE-merge approach
Web Semantics: Science, Services and Agents on the World Wide Web
Challenging research issues in data mining, databases and information retrieval
ACM SIGKDD Explorations Newsletter
Applying Semantic Web Technologies to Ontology Alignment
International Journal of Intelligent Information Technologies
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With the emergence of the Semantic Web, ontologies are being exposed on the Web to support a variety of applications, including enhanced search and discovery, rapid enterprise integration and cross-domain knowledge sharing. This explosion of knowledge sharing on the web is also leading to the formation of knowledge silos and a growing need for integration of these sources. Automated solutions to mapping ontologies are emerging that address this growing need with very promising results. However, most approaches have focused on mapping ontologies using relationships of similarity and equivalence and very few have applied knowledge in upper ontologies. We built algorithms to acquire relationships between ontological components beyond similarity and equivalence that include hyponymy and more importantly, algorithms to map ontologies based on relationships that are specified within the ontologies. These algorithms employ the semantics of OWL in conjunction with online linguistic resources and upper ontologies. Initial test results are promising.