A methodology for ontology integration
Proceedings of the 1st international conference on Knowledge capture
The PROMPT suite: interactive tools for ontology merging and mapping
International Journal of Human-Computer Studies
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Using Bayesian decision for ontology mapping
Web Semantics: Science, Services and Agents on the World Wide Web
A METHOD FOR ONTOLOGY CONFLICT RESOLUTION AND INTEGRATION ON RELATION LEVEL
Cybernetics and Systems
A Method for Integration of WordNet-Based Ontologies Using Distance Measures
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I
Identifying Potentially Important Concepts and Relations in an Ontology
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
A Hybrid Method for Integrating Multiple Ontologies
Cybernetics and Systems
WordNet::Similarity: measuring the relatedness of concepts
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
An efficient and scalable algorithm for segmented alignment of ontologies of arbitrary size
Web Semantics: Science, Services and Agents on the World Wide Web
An adaptive ontology mapping approach with neural network based constraint satisfaction
Web Semantics: Science, Services and Agents on the World Wide Web
Ontological analysis of taxonomic relationships
ER'00 Proceedings of the 19th international conference on Conceptual modeling
An Effective Method for Ontology Integration by Propagating Inconsistency
KSE '10 Proceedings of the 2010 Second International Conference on Knowledge and Systems Engineering
Conflicts of ontologies – classification and consensus-based methods for resolving
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Partition-Based block matching of large class hierarchies
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
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Previous work on ontology integration involves only blind or exhaustive matching among all the concepts in different ontologies. Therefore, the computational complexity rapidly increases in integrating large ontologies. In addition, semantic mismatches, logical inconsistencies, and conceptual conflicts in ontology integration have not yet become avoidable. The aim of this paper is to investigate a method to reduce the computational complexity and enhance accurate matching ontology. In this paper, a novel approach has been proposed using propagating Priorly Matchable Concepts (PMCs). The key idea of our approach is analyzing multiple contexts, including the role of ''natural categories'', relations, and constraints among concepts to provide additional suggestions for possible matching concepts. PMC is a collection of pairs of concepts across two different ontologies in the same Concept Types that are arranged in descending order of Concept Importance distances for the pairs. PMC guides on how to priorly check the similarity between concepts. It is useful to avoid checking similarities among unmatchable concepts. In addition, dependency rules are applied to filter mismatches in PMC during the integration process. Our experiments compare the computational complexity and accurate matching to previous approaches. The use of PMC as a pre-process in the integration process enhances both complexity and accuracy compared to unused PMC.