A comparative analysis of methodologies for database schema integration
ACM Computing Surveys (CSUR)
An order-sorted logic for knowledge representation systems
Artificial Intelligence
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Supporting ontological analysis of taxonomic relationships
Data & Knowledge Engineering - ER2000
Managing Semantic Heterogeneity with Production Rules and Persistent Queues
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
The PROMPT suite: interactive tools for ontology merging and mapping
International Journal of Human-Computer Studies
Order-sorted logic programming with predicate hierarchy
Artificial Intelligence
IC-based ontology expansion in devouring accessibility
AOW '05 Proceedings of the 2005 Australasian Ontology Workshop - Volume 58
Towards OntoClean 2.0: A framework for rigidity
Applied Ontology
Building a global normalized ontology for integrating geographic data sources
Computers & Geosciences
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Matching (or mapping) between heterogeneous ontologies becomes crucial for interoperability in distributed and intelligent environments. Although many efforts in ontology mapping have already been conducted, most of them rely heavily on the meaning of entity names rather than the semantics defined in ontologies. In order to deal with semantic heterogeneity, we enrich the semantics of ontologies for content-based matching. In this paper, we propose a semantically-enriched model of ontologies (called MetaOntoModel) where the semantics of concepts are enriched by adding concept-level knowledge (called meta-knowledge) based on three philosophical notions: identity, rigidity, and dependency. Then, we develop a MetaOntoModel-based ontology matching method. Our novel idea is that if two concepts are semantically equivalent, then they have the same meta-knowledge. On the contrary, if two concepts possess different kinds of meta-knowledge, then they cannot be matched. We prove that meta-knowledge can determine not only the scope of matches, but also the closest corresponding properties between two similar concepts.