DocumentCode :
1614538
Title :
Ontology mapping based on concept classification
Author :
Yang, Kai ; Steele, Robert
Author_Institution :
Univ. of Sydney, Sydney, NSW, Australia
fYear :
2009
Firstpage :
656
Lastpage :
661
Abstract :
Ontology mapping is a crucial task for achieving large scale semantic inter-operation of heterogeneous information sources. Conventional mapping solutions mainly focus on the mapping of a pair of ontologies. While such approaches are effective in creating one-to-one ontology mappings, they are less efficient when dealing with the many-to-many ontology mapping scenarios. To cope with the complexity issue faced by pair-wise mapping solutions, we propose a many-to-many ontology mapping approach. By treating ontology mapping as a concept classification problem, we aim to reduce the number of concept comparisons involved in many-to-many ontology mapping. A preliminary evaluation of performance was also carried out, and results show that the proposed mapping solution requires less concept comparison cycles for many-to-many ontology mapping.
Keywords :
ontologies (artificial intelligence); pattern classification; semantic Web; concept classification; heterogeneous information source; large scale semantic inter-operation; many-to-many ontology mapping; semantic Web; Bioinformatics; Classification tree analysis; Computational complexity; Databases; Ecosystems; Electronic mail; Information retrieval; Large-scale systems; Ontologies; Semantic Web; Concept Classification; Many-to-Many Ontology Mapping; Ontology Mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Ecosystems and Technologies, 2009. DEST '09. 3rd IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-2345-3
Electronic_ISBN :
978-1-4244-2346-0
Type :
conf
DOI :
10.1109/DEST.2009.5276722
Filename :
5276722
Link To Document :
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