On the composition of large biomedical ontologies alignment

Ontology alignment process is seen as a key mechanism in order to reduce heterogeneity and linking diverse data masses and ontologies arising in the semantic Web. In such a large infrastructures and environments, it is inconceivable to assume that all ontologies dealing with a particular knowledge domain are aligned in pairs. Moreover, the high performance of the alignment techniques is closely related to two major factors, i.e., time consumption and resource machine limitations. Indeed, good quality alignments are valuable and it would be appropriate to harness. From this statement, this paper introduces a new indirect ontology alignment method. Indeed, the proposed method treats biomedical ontologies alignments and implements a strategy of indirect ontology alignment based on a smart and efficient direct alignments composition and reuse. The core of the proposed method process relies on the alignment algebra that governs the composition of semantic relations and confidence values. Results obtained after extensive and detailed carried experiments are very encouraging and highlight many useful insights about the new proposed method.