An automatic technique for detecting type conflicts in database schemes
Proceedings of the seventh international conference on Information and knowledge management
Semantic integration of semistructured and structured data sources
ACM SIGMOD Record
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Handling semantic heterogeneities using declarative agreements
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Global Viewing of Heterogeneous Data Sources
IEEE Transactions on Knowledge and Data Engineering
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Using Bayesian decision for ontology mapping
Web Semantics: Science, Services and Agents on the World Wide Web
A visual tool for ontology alignment to enable geospatial interoperability
Journal of Visual Languages and Computing
The problem of ontology alignment on the web: a first report
WAC '06 Proceedings of the 2nd International Workshop on Web as Corpus
A survey of schema-based matching approaches
Journal on Data Semantics IV
Content-based ontology matching for GIS datasets
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Similarity as a Quality Indicator in Ontology Engineering
Proceedings of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008)
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
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In geospatial applications with heterogeneous classification schemes that describe related domains, an ontology-driven approach to data sharing and interoperability relies on the alignment of concepts across different ontologies. To enable scalability both in the size and the number of the ontologies involved, the alignment method should be automatic. In this paper, we propose two fully automatic alignment methods that use the structure of the ontology graphs for contextual information, thus providing the matching process with more semantics. We have tested our methods on a set of geospatial ontologies pertaining to the domain of wetlands and on four sets that belong to an ontology repository that is becoming the standard for testing ontology alignment techniques. We have compared the effectiveness and efficiency of the proposed methods against two previous approaches. The effectiveness results that we have obtained with at least one of the new methods are as good or better than the results obtained with the previously proposed methods.