Resolving semantic heterogeneity in schema integration
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Measuring Similarity between Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Learning to match ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Ontology mapping: the state of the art
The Knowledge Engineering Review
The Knowledge Engineering Review
Ontology-Based Information Retrieval Model for the Semantic Web
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
A mapping system for the integration of OWL-DL ontologies
Proceedings of the first international workshop on Interoperability of heterogeneous information systems
ACM SIGMOD Record
Ontology Matching
A string metric for ontology alignment
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Reaching agreement over ontology alignments
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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Ontology mapping has a key importance for applications such as information retrieval, database integration, and agent-communication. This paper presents an Argumentation Framework, with confidence degrees associated to the arguments, to combine ontology mapping approaches. Our agents apply individual mapping algorithms and cooperate in order to exchange their local results (arguments). Based on their preferences and confidence of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. The model is evaluated using a benchmark for ontology mapping. The results are promising especially what concerns precision.