Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
The three semantics of fuzzy sets
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Strong similarity measures for ordered sets of documents in information retrieval
Information Processing and Management: an International Journal
Domain Independent Learning of Ontology Mappings
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Schema and ontology matching with COMA++
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Towards large-size ontology alignment by mapping groups of concepts
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems
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This paper presents a new ontology mapping method This method addresses the case in which a non-structured ontology is to be mapped with a structured one Both ontologies are composed of triplets of the form (object, characteristic, value) Structured means that the values describing the objects according to a given characteristic are hierarchically organized using the a kind of relation The proposed method uses fuzzy conceptual graphs [8] to represent and map objects from a source ontology to a target one First, we establish a correspondence between characteristics of the source ontology and characteristics of the target ontology based on the comparison of their associated values Then, we propose an original way of translating the description of an object of the source ontology using characteristics and values of the target ontology The description thus translated is represented as a fuzzy conceptual graph Finally, a new projection operation is used to find mappings between translated objects and actual objects of the target ontology This method has been implemented and the results of an experimentation concerning the mapping of ontologies in the field of risk in food are presented.