Authors:
C. Tatsiopoulos
and
B. Boutsinas
Affiliation:
University of Patras, Greece
Keyword(s):
Ontology Mapping, Interoperability, Association Rule Mining.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cloud Computing
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Information Engineering Methodologies
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Semantic Web Technologies
;
Sensor Networks
;
Services Science
;
Signal Processing
;
Soft Computing
;
Software Agents and Internet Computing
;
Symbolic Systems
Abstract:
Ontology mapping is one of the most important processes in ontology engineering. It is imposed by the decentralized nature of both the WWW and the Semantic Web, where heterogeneous and incompatible ontologies can be developed by different communities. Ontology mapping can be used to establish efficient information sharing by determining correspondences among such ontologies. The ontology mapping techniques presented in the literature are based on syntactic and/or semantic heuristics. In almost all of them, user intervention is required. In this paper, we present a new ontology mapping technique which, given two input ontologies, is able to map concepts in one ontology onto those in the other, without any user intervention. It is based on association rule mining applied to the concept hierarchies of the input ontologies. We also present experimental results that demonstrate the accuracy of the proposed technique.