Considering the high heterogeneity of the ontologies pub-lished on the web,
ontology matching is a crucial issue whose aim is to establish links between an
entity of a source ontology and one or several entities from a target ontology.
Perfectible similarity measures, consid-ered as sources of information, are
combined to establish these links. The theory of belief functions is a powerful
mathematical tool for combining such uncertain information. In this paper, we
introduce a decision pro-cess based on a distance measure to identify the best
possible matching entities for a given source entity.