Authors:
A. Laadhar
1
;
F. Ghozzi
2
;
I. Megdiche
1
;
F. Ravat
1
;
O. Teste
1
and
F. Gargouri
2
Affiliations:
1
University of Toulouse, France
;
2
University of Sfax, Tunisia
Keyword(s):
Semantic Web, Ontology Matching System, Syntactic Matching, Structural Matching.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
e-Business
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontology Matching and Alignment
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
The identification of alignments between heterogeneous ontologies is one of the main research issues in the
semantic web. The manual matching of the ontologies is a complex, time consuming and an error prone task.
Therefore, ontology matching systems aims to automate this process. Usually, these systems perform the
matching process by combining element and structural level matchers. Selecting the optimal string similarity
measure associated with its threshold is an important issue in order to enhance the effectiveness of the element
level matcher, which in turn will improve the whole ontology system results. In this paper, we present POMap,
an ontology matching system based on a syntactic study covering element and structural levels. For the element
level matcher we have adopted the best configuration based on the analysis of the performances of many string
similarity measures associated with their thresholds. For the structural level, we have performed a syntactic
study on
both subclasses and siblings in order to infer the structural similarity. Our proposed matching system
is validated and evaluated on the Anatomy, the Conference and the Large Biomedical tracks provided by the
benchmark of OAEI 2016 ontology matching campaign.
(More)