EXONA results for OAEI 2015

This paper presents the results of EXONA in the Ontology Alignment Evaluation Initiative (OAEI) 2015. EXONA is an automatic instance-based ontology alignment systems in which we parse ontology as rst step. In the second step, we index instances of the rst ontology. These indexed instances will be applied for the querying phase. In the last step, our system aligns instances based by aggregating score of di erent terminological matchers. We rst describe the overall framework of our matching System (EXONA) then we detail the techniques used in the framework for instance matching. Last, we give a thorough analysis on our results and discuss some future work on our system. It's our rst participation in the OAEI instance matching, the results are good in terms of recall, precision and F-measure. 1 Presentation of the system Ontology matching is a key interoperability enabler for the semantic web, as well as a useful tactic in data integration tasks. Knowledge about one object may be contained in multiple and di erent knowledge bases. Therefore, a lot of work has already been built to obtain more complete knowledge about things existing in di erent domains. This is in order to exceed the area of divergence obstacle, by creating cross-domain knowledge. Accordingly, it's strongly recommended to focus on the more active element of ontology which it called instance. Many instances matching approaches have been proposed, and among which is ours. In fact, our system is proposed for large scale instance matching. It operates on three successive modules, namely : transformation, indexation and correspondence. Transformation consists in transforming separately both of knowledge bases on an exploitable form and then creating our own instance object as a profession object. Indexation is the process of indexing instances of knowledge base; only instances of the source base knowledge