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Revisiting Indirect Ontology Alignment : New Challenging Issues in Cross-Lingual Context
Ontology alignment process is overwhelmingly cited in Knowledge Engineering
as a key mechanism aimed at bypassing heterogeneity and reconciling various
data sources, represented by ontologies, i.e., the the Semantic Web
cornerstone. In such infrastructures and environments, it is inconceivable to
assume that all ontologies covering a particular domain of knowledge are
aligned in pairs. Moreover, the high performance of alignment approaches is
closely related to two factors, i.e., time consumption and machine resource
limitations. Thus, good quality alignments are valuable and it would be
appropriate to exploit them. Based on this observation, this article introduces
a new method of indirect alignment of ontologies in a cross-lingual context.
Indeed, the proposed method deals with alignments of multilingual ontologies
and implements an indirect ontology alignment strategy based on a composition
and reuse of effective direct alignments. The trigger of the proposed method
process is based on alignment algebra which governs the semantics composition
of relationships and confidence values. The obtained results, after a thorough
and detailed experiment are very encouraging and highlight many positive
aspects about the new proposed method.Comment: 14 page