An Ontology Alignment Hybrid Method Based on
Decision Rules
Mohamed Biniz1
and Mohamed Fakir2
1Department of Mathematics and Computer Science, Sultan
Moulay Slimane University, Morocco
2Department of
Informatics, Sultan Moulay Slimane University, Morocco
Abstract: In this paper, we propose a hybrid approach based on the extraction of
decision rules to refine the alignment results due to the use of three
alignment strategies. This approach contains two phases: training phase which
uses structural similarity, element similarity, instance-based similarity and
C4.5 algorithms to extract decision rules, and evaluation phase which refines
discovered alignment by three alignment strategies using extracted decision
rules. This approach is compared with the best systems according to benchmark
OAEI 2016: Framework for Ontology Alignment and Mapping (FOAM), A Dynamic Multistrategy Ontology Alignment
Framework (RIMOM), AgreementMakerLight and Yet Another
Matcher-Biomedical Ontologies (YAM-BIO), the
proposed method gives good results (good recall, precision and F-measure).
Experimental results show that the proposed approach is effective.
Keywords: Decision
rules, alignment, ontology, similarity, similarity flooding.