A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Ontology Matching
Advanced Methods for Inconsistent Knowledge Management (Advanced Information and Knowledge Processing)
A METHOD FOR ONTOLOGY CONFLICT RESOLUTION AND INTEGRATION ON RELATION LEVEL
Cybernetics and Systems
Web Semantics: Science, Services and Agents on the World Wide Web
An ontology-based measure to compute semantic similarity in biomedicine
Journal of Biomedical Informatics
Attribute mapping as a foundation of ontology alignment
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Ontology alignment evaluation initiative: six years of experience
Journal on data semantics XV
Semantic distance measure between ontology concept's attributes
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
On how to perform a gold standard based evaluation of ontology learning
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
A METHOD FOR ONTOLOGY ALIGNMENT BASED ON SEMANTICS OF ATTRIBUTES
Cybernetics and Systems - LEARNING, SCHEDULING, RESOURCE OPTIMIZATION, AND EVOLUTION IN SMART ARTIFICIAL SYSTEMS: CHALLENGES AND SUPPORT
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The problem of ontology alignment is based on finding mappings between instances, concepts and relations of two ontologies which (following Gruber's work [8]) can be defined as explicit specification of decomposition of some part of reality. This specification spreads over three levels of detail: the concept attribute level, the concept level and the relation level. This paper concentrates on identifying matches between relations of concepts which describe how these entities interact with each other. After careful analysis we have noticed that this level can be a source of many inconsistencies when two ontologies are blindly integrated. We take our work on attribute-based concept alignment and the consensus theory as a starting point. We extend it to handle the issues that appear when aligning relations. We give formal definitions along with careful formalization of set of requirements that eventual mapping algorithm should satisfy in order to reliably designate matches between ontologies on relation level.