Foundations of statistical natural language processing
Foundations of statistical natural language processing
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Am overview of the EDR electronic dictionary and the current status of its utilization
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Mapping WordNets using structural information
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Automatic construction of an English-Chinese bilingual FrameNet
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
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This paper analyzes the results of automatic concept alignment between two ontologies. We use an iterative algorithm to perform concept alignment. The algorithm uses the similarity of shared terms in order to find the most appropriate target concept for a particular source concept. The results show that the proposed algorithm not only finds the relation between the target concepts and the source concepts, but the algorithm also shows some flaws in the ontologies. These results can be used to improve the correctness of the ontologies.