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Communication Dans Un Congrès Année : 2014

A semi-automatic mapping selection in the ontology alignment process

Résumé

Ontologies are considered as one of the most powerful tools for knowledge representation and reasoning. Thus, they are considered as a fundamental support for image annotation, indexing and retrieval. In order to build a remote sensing satellite image ontology that models the geographic objects that we find in a scene, their characteristics as well as their relationships, we propose to reuse existing geographic ontologies to enrich an ontological core. Reusing high quality resources (called source ontologies) helps ensuring a good quality for the extracted knowledge, and alleviating the conceptualization stage, i.e. avoiding building a new ontology from scratch. Ontology alignment is an important phase within the enrichment process. It is a process that allows discovering mappings between core and source ontologies, where each mapping is a couple of entities brought from each ontology and linked together either by an equivalence or a subsumption relationship. Such relationships are based on various similarity measures. In this paper, we first present a brief literature review of existing theoretical frameworks for similarity measures, then we describe a new alignment approach based on a semi-automatic mapping selection process that needs little human intervention. First experiments show the benefit from using the proposed approach.
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Dates et versions

hal-01186365 , version 1 (24-08-2015)

Identifiants

  • HAL Id : hal-01186365 , version 1

Citer

Hafedh Nefzi, Mohamed Farah, Imed Riadh Farah, Basel Solaiman. A semi-automatic mapping selection in the ontology alignment process. KEOD 2014 : 6th International conference on knowledge engineering and ontology development, Oct 2014, Rome, Italy. ⟨hal-01186365⟩
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